altas europeu

THE EUROPEAN SOLAR RADIATION ATLAS

Vol. 1: Fundamentals and maps

K. Scharmer and J. Greif

Les Presses de l’École des Mines

Paris, 2000

Nelson

Sticky Note

Pág 25 - movimento do sol

© École des Mines de Paris, 200060, Boulevard Saint-Michel, 75272 Paris cedex 06FRANCEe-mail : [email protected]://www.ensmp.fr/Presses

ISBN : 2-911762-21-5Dépôt légal : mars 2000Achevé d’imprimé en France en mars 2000 (Grou-Radenez, Paris)

Tous droits de reproduction, de traduction, d’adaptation et d’exécutionrésevés pour tous les pays

THE SOLAR RADIATION ATLAS – Contents

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Contents

ACKNOWLEDGEMENTS....................................................................................... V

ESRA IN A NUTSHELL.......................................................................................... 3

1 The ESRA-concept................................................................................................................................... 3

2 Data Base .................................................................................................................................................. 4

3 Solar Algorithms ...................................................................................................................................... 5

4 Use of the Tool Box to assess solar system performance ...................................................................... 6

5 The CD-ROM........................................................................................................................................... 7

6 The Atlas Book ......................................................................................................................................... 7

1 INTRODUCTION ................................................................................................. 9

2 THE CONCEPT OF THE EUROPEAN SOLAR RADIATION............................ 11

2.1 Geographical area.................................................................................................................................. 11

2.2 The content ............................................................................................................................................. 11

2.3 Users of ESRA........................................................................................................................................ 14

3 BASICS OF SOLAR RADIATION ................................................................... 17

3.1 Introduction .............................................................................................................................................. 17

3.2 The choice of fundamental observational data in relation to mapping possibilities ........................... 17

3.3 Time systems ............................................................................................................................................. 19

3.4 The Julian day and the hour angle......................................................................................................... 20

3.5 Extraterrestrial radiation from the sun................................................................................................. 21


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3.6 Geometry of solar movements as seen from the earth.......................................................................... 23 3.6.1 The sun-earth geometry...................................................................................................................... 23 3.6.2 Declination angle ................................................................................................................................ 24 3.6.3 The solar altitude angle ....................................................................................................................... 25 3.6.4 Solar azimuth angle............................................................................................................................. 26 3.6.5 Sunset hour angle and daylength......................................................................................................... 27 3.6.6 Relative daily sunshine duration ......................................................................................................... 27 3.6.7 Angle of incidence .............................................................................................................................. 27

3.7 Choice of calculation times ..................................................................................................................... 28

3.8 The solar radiation at the surface of the earth....................................................................................... 28

3.9 User needs................................................................................................................................................. 30

3.10 Transmission of solar radiation through the cloudless atmosphere................................................... 31 3.10.1 Direct and diffuse irradiation ............................................................................................................ 31 3.10.2 Relative optical air mass.................................................................................................................... 31 3.10.3 The Linke turbidity factor ................................................................................................................. 32 3.10.4 Estimating the Rayleigh optical thickness........................................................................................ 33 3.10.5 Estimating clear sky diffuse irradiance ............................................................................................. 33 3.10.6 The clear sky global irradiation........................................................................................................ 34

3.11 Monthly mean daily global radiation and the monthly mean daily Clearness Index ....................... 34

3.12 Splitting the monthly mean daily global radiation into its beam and diffuse components .............. 35

4 FROM SOLAR MEASUREMENTS TO THE SOLAR DATA BASE .................. 37

4.1 Ground measuring techniques for solar radiation components ........................................................... 37 4.1.1 Sunshine duration................................................................................................................................ 37 4.1.2 Hemispherical solar radiation.............................................................................................................. 38 4.1.3 Terrestrial radiation............................................................................................................................. 40

4.2 Solar radiation data from satellite images.............................................................................................. 40

4.3 Detection of errors within raw data ........................................................................................................ 40

5 THE ESRA DATABASE.................................................................................... 43

5.1 The reference period and the reference area ......................................................................................... 43

5.2 Ground measured and derived data ....................................................................................................... 43

5.3 Satellite derived data................................................................................................................................ 44


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5.4 Sources of data.......................................................................................................................................... 44

5.5 Data guarantee.......................................................................................................................................... 45

5.6 Maps of solar radiation components....................................................................................................... 46

5.7 Zones of similar irradiation climates ...................................................................................................... 47

5.8 Zones of similar biomass parameters........................................................................................................ 47

5.9 Test, Design and Biomass Reference Years............................................................................................ 48

6 THE ESRA SOFTWARE PACKAGE................................................................. 49 (The European Solar Radiation Atlas, vol. 2 : database, models and exploitation software)

6.1 Content of the CD-ROM.......................................................................................................................... 49

6.2 The map mode........................................................................................................................................... 50

6.3 Station mode.............................................................................................................................................. 54

6.4 Sub-menus and examples......................................................................................................................... 55

6.5 Further applications ................................................................................................................................. 62

7 MAPS................................................................................................................. 63

7.1 The geographical are of the Atlas ......................................................................................................... 63

7.2 Ground based measuring stations........................................................................................................... 63

7.3 Global solar irradiation (Ten year average)........................................................................................... 63

7.4 Diffuse solar irradiation (Ten year average) .......................................................................................... 63

7.5 Direct (beam) solar irradiation (Ten year average)............................................................................... 63

7.6 Clearness index (Ten year average) ........................................................................................................ 64

7.7 Zones of similar irradiation climates ...................................................................................................... 64

7.8 Zones of similar biomass productivity parameters................................................................................ 64


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REFERENCES...................................................................................................... 65

MAPS.................................................................................................................... 67

ANNEX 1..................................................................SYMBOLS AND DEFINITIONS

A1.1 Introduction ........................................................................................................................................... 93

A1.2 Basic concepts and General Rules ........................................................................................................ 93

A1.3 Definitions............................................................................................................................................... 95

REFERENCES.................................................................................................... 100

ANNEX 2...................................................................................LIST OF STATIONS

THE SOLAR RADIATION ATLAS - Acknowledgements

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Acknowledgements

The material provided for this publication came from many sources. The contributions of all organisa-tions and persons mentioned below were greatly appreciated by the authors and the editors. They are all gratefully acknowledged.

Data on observed daily global and monthly sums of sunshine duration were put at disposal of the project from the World Radiation Data Centre (WRDC), St. Petersburg (Russia). Additional important and necessary data of daily sums of sunshine duration were supplied by National Weather Services and scientific institutes of the following countries. Some of these institutions delivered data on daily global solar radiation and/or diffuse solar radiation as well. This supporting data was greatly appreci-ated by the project participants and helped to bring the project into strong forces.

National Weather Services and Institutes which supported the project are set down in alphabetic or-der.

Austria Zentralanstalt für Meteorologie und Geodynamik, Vienna Belgium Insitut Royal Météorologique de Belgique, Brussels Croatia Drzavni Hidrometeoroloski Zavod, Zagreb Cyprus Meteorological Service, Nicosia Czech Republic Czech Hydrometeorological Institute, Praha and Solar and Ozone Observatory,

Hradec Kralove Denmark Technical University of Denmark Finland Finnish Meteorological Institute, Helsinki Germany Deutscher Wetterdienst, Offenbach GKSS – Forschungszentrum, Geesthacht Zentrum für Sonnenenergie- und Wasserstoff-Forschung, Stuttgart Greece Hellenic National Meteorological Service, Athens Iceland Icelandic Meteorological Office, Reykjavik Ireland Meteorological Service, Dublin Italy Servizio Meteorologico dell´Aeronautica Militare, Roma Jordan Meteorological Departement, Amman Civil Airport, Amman Malta Meteorological Ofiice, Civil Aviation Departement, Luqa Netherlands Koninklijk Nederlands Meteorologisch Instituut, De Bilt Norway University of Bergen, Geophysical Institute, Bergen Poland Institute of Meteorology and Water Management, Warszawa Russia World Radiation Data Centre, St. Petersburg Switzerland Schweizerische Meteorologische Anstalt, Zürich Sweden Sveriges Meteorologiska och Hydrologiska Insititut, Norrköping Turkey Turkish State Meteorological Service, Ankara United Kingdom The Meteorological Office, Bracknell

Satellite images from METEOSAT were supplied to the project by GKSS Research Centre in

Geesthacht, Germany, by Deutscher Wetterdienst, Offenbach, Germany and by NASA Langley Re-search Centre, USA.

THE SOLAR RADIATION ATLAS - Acknowledgements

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We also have to thank the Centre of Solar Energy and Hydrogen Research, Stuttgart, Germany and Alain de la Casinière, University Jacques Fourier, Grenoble, France for cooperation on spectral solar irradiation data.

The origin of other meteorological parameters as daily maximum and minimum air temperatures and precipitation is a CD-ROM named “Global Daily Summary” published by the National Climate Data Centre, Asheville, N.C., USA. Long-term monthly means of air temperature, vapour pressure, precipitation and atmosphere pressure were contributed from Deutscher Wetterdienst, Offenbach, Germany.

The Test Reference Years (TRY) are kindly supplied by:

• Royal Meteorological Service, Uccle, Belgium • Meteorological Service, Dublin, Ireland • Hungarian Meteorological Service, Budapest, Hungary • Main Geophysical Observatory, St. Petersburg, Russia • National Observatory of Athens, Inst. of Meteorology and Physic of the Atmospheric Environment,

Athens, Greece • German Weather Service, Offenbach, Germany.

For valuable help in establishing the Biomass Reference Years, we thank

• P. Vossen, J.R.C. – Institute for Remote Sensing Applications, Agriculture Information Systems, Ispra, Italy

• Ghislain Gosse, INRA – Institut National de la Recherche Agronomique, Thiveral, France Digital information on elevation, water covered areas, coastlines and political borderlines are taken

from topographical maps published by the National Centre of Atmospheric Research (NCAR), Boul-der, Co., USA.

THE SOLAR RADIATION ATLAS - ESRA in a nutshell

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The European Solar Radiation Atlas (ESRA) in a nutshell

1 The ESRA-concept

ESRA is a logical continuation of the European Solar Radiation Atlas of 1984. It covers a wider geo-graphical area and is backed with a data base that is considerably extended both in space and in time detail. It takes full advantage of recent advances in information technology to present PC based maps and to provide an associated user friendly software package to enable users to develop their own spe-cific data systematically from the data base (see The European Solar Radiation Atlas, vol. 2 : database and exploitation software which consists of a CD-ROM with its guidebook. It is a working tool for

• engineers and architects,

• meteorologists and climatologists, • agronomers and biologists, • settlement-planners • landscape designers • teachers and students, • journalists and • politicians.

The main features of ESRA can be summarised as follows:

• The geographical coverage ranges from

30° W to 70° E 29° N to 75 °N.

• Solar radiation measurements and meteorological values which have served to build-up the radia-

tion maps and the station time series range from

1981 – 1990.

• ESRA is structured in the following way:

The data base contains all solar radiation information for the whole area and additional meteoro-logical information. The data exist at two main levels, monthly mean daily level, and daily time series for selected stations. There is also a limited amount of observed data at the hourly time scale.

Retrieval Softwareand SolarAlgorithms EditorData Base


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A set of algorithms which enable the user to compute – starting from the values in the data base de-rived information to match user defined needs.

A software package which allows the systematic inspection of maps, easy retrieval of numeric data, processing of data under user specification, the editing and saving of results.

2 Data Base (see The European Solar Radiation Atlas, vol. 2: database and exploitation software)

The data base hosts the following information:

A. Digital maps with pixel size of 5´ x 5´ (or approximately 10 km x 10 km at 50° N and 40° E)

showing: • geomorphology and country borders, • daily solar irradiation on horizontal planes (monthly and yearly means from the period 1981 – 1990)

• global irradiation, • diffuse irradiation, • direct irradiation,

• monthly mean clearness index KT,

• solar climate regions,

• biomass climate regions.

The maps for global irradiation have been constructed from 10 year averages of observed global ir-

radiation from ground based sites in combination with satellite image data for a shorter period struc-tured together using the co-kriging interpolation method. Diffuse irradiation maps were calculated from global irradiation maps using the clearness index information with an empirical polynomial re-gression formula, using regression coefficients adjusted to monthly mean daily global and diffuse ra-diation measurements in Europe. The direct irradiation is mapped as the difference between global and diffuse irradiation.

Solar climate regions and biomass climate regions have been calculated by cluster analysis for simi-lar clearness index respectively for similar biomass growth parameters (global irradiation, daily mean temperatures and daily temperature ranges and precipitation).

B. Station data (time series from selected ground measuring stations) • Daily values

out of 90 reference stations: 89 stations with global irradiation, 32 stations with sums of sunshine duration, 86 stations with mean, maximum (85) and minimum tem-peratures and precipitation,


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• hourly values: six stations with sums of sunshine duration and global and diffuse

irradiation on horizontal planes, • 30 minutes-values: one station with sums of sunshine duration and global and diffuse irradiation on horizontal planes, • monthly values

(not all values are available for all stations): 695 stations with monthly means of sunshine duration,

586 stations with monthly means of daily sums from 10-year averages of global irradiation, sunshine duration (556 stations) and monthly means of minimum and maximum air temperatures (435 stations), precipitation (435 stations), air pressure (266 stations) and vapour pressure (274 stations), 595 stations with monthly means of the Ångström coefficients a + b.

C. Composed data sets: • six stations (St. Petersburg, Dublin , Brussels (UCCLE), Freiburg, Budapest and Athens) with Test

Reference Years (TRY), • one station (Kobenhaven) with Design Reference Year (DRY), • two stations (Kobenhaven , Ispra) with „long“ Biomass Reference Years (BRY), • five stations (Kobenhaven, Ispra, Passau, Marignane, Brindisi) with „short“ Biomass Reference

Years (BRY).

3 Solar Algorithms (see The European Solar Radiation Atlas, vol. 2: database and exploitation software)

Mathematical models are used to derive input data for scientific and technological problems, like the irradiation on inclined planes, using the measured data compiled in the data base, which are restricted to horizontal surfaces. Most of these input data are monthly mean data or daily data. The derived data can be presented at the finer time scale of one hour using the concept of mean daily profiles of hori-zontal irradiation (There are only few observed hourly data in the data base). A widespread survey of literature was performed at the start of the project, and the selected algorithms were validated against European data. The complete documentation of this area is provided in the ESRA volume 2: database and exploitation software.

The following algorithmic chains reside as computational facilities within the software package, and are automatically called, as appropriate, to generate the requested outputs.

Chain 1 - From Gd (i.e. daily averages of global irradiation) series to series of daily mean profiles of hourly direct, sky diffuse, ground reflected diffuse and global irradiation, and respective daily sums

Chain 2 - From Gd and Sd (i.e. daily sunshine hours) series to daily mean profiles of hourly average direct, sky diffuse, ground reflected diffuse and global illuminance

Chain 3 - From (Gd)m (i.e. monthly averages of daily means of global irradiation) values to monthly average daily mean profiles of hourly direct, sky diffuse, ground reflected diffuse and global irradiation, and respective daily sums

Chain 4 - From (Gd)m and Sm values to monthly average daily mean profiles of hourly average di-rect, sky diffuse, ground reflected diffuse and global illuminance


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Chain 5 - From (Gd)m and (TL)m (monthly average Linke turbidity) values monthly average daily mean profiles of hourly direct, sky diffuse, ground reflected diffuse and global irradiation under cloudless skies, and respective daily sums

Chain 6 - From (Gd)m and Sm values to monthly average global spectral irradiance values

Chain 7 - From (Tmin)m and (Tmax)m values (i.e. monthly average minimum and maximum ambient temperatures) to daily mean profiles of hourly temperature and respective averages

Chain 8 - From Gd series to cumulative probability and utilizability functions of global and beam irradiance and respective available energy functions

Chain 9 - From Gd and Sd series to cumulative probability and utilizability functions of global and diffuse illuminance and available illuminance functions

Chain 10 - From (Tmin)m, (Tmax)m, Sm, and (pW)m (i.e. monthly average vapour pressure) values to monthly average downward sky hourly and daily long wave irradiation values.

Chains nos. 1 to 5 and 8 to 10 include the cases of horizontal plane and of tracking or non-tracking inclined surfaces.

4 Use of the Tool Box to assess solar system performance (see The European Solar Radiation Atlas, vol. 2: database and exploitation software)

Simplified computer models for system performance assessment of four systems are integrated within the ESRA software package.

• Solar water heaters and active solar systems • Photovoltaic systems • Passive solar buildings • Biomass production

Examples are provided using these models in conjunction with the solar radiation data base. The selection of these simplified models has been based on a detailed analysis of user data needs in

the context of the different computer programmes currently used by professional groups like archi-tects, engineers and agronomists.

The principles of the use of data for simulation are also reviewed and reference is made to a wide range of simulation models in current use.

The impact of the quality of the solar horizontal data inputs on the assessment of system perform-ance using inclined collection systems has been analysed.

Statistical data have also been prepared demonstrating the significance of inter annual variations in solar radiation availability in the assessment of long term performance.


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5 The CD-ROM (see The European Solar Radiation Atlas, vol. 2: database and exploitation software)

As primary tool, the whole ESRA-system is presented on CD-ROM.

Necessary hardware:

• PC-compatible (at least 486-DX2-66, preferred Pentium 120) • SVGA display (at least 800 x 600, 256 colours, preferred 1024 x 768 and 64 k colours), • CD-ROM drive (at least speed = x 4, preferably x 8) Necessary software: • Windows 95 (not installable on Windows 3.1x, nor Windows NT) The CD-ROM contains • the entire data base, • the retrieval system to select data from the base or from external data input for further purposes, • the 10 algorithmic chains, • some simple models for dimensioning of practical solar energy appliances, solar architecture, bio-

mass production, • software to manage data flow and computation, • visualisation and interactive structures, • editing facilities (printing of tables, maps and graphs), • export of data sets to other external or internal files of the user.

6 The Atlas Book (The European Solar Radiation Atlas, vol. 1: fondamentals and maps)

The atlas book gives a general survey on solar energy, solar mapping, mapping of solar and biomass climate regions, the structure of the data base and its main applications. Solar radiation values from the data base are presented in annual and monthly multi-coloured digital maps.

THE SOLAR RADIATION ATLAS – 1 Introduction

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1 Introduction

This new European Solar Radiation Atlas – ESRA – has to be seen as a logical continuation of the support the European Commission has given to research and demonstration of solar energy through its Directorate General XII research programme.

The previous atlas (Commission of the European Communities, 1984) has been out of print for some time, so an updated and improved edition was published in 1996 (Commission of the European Communities, 1996). These Atlases are based on solar data from the period of 1966 to 1975, and only the member states of the European Community (with some neighbouring countries) are included.

ESRA was prepared within the framework of the JOULE II programme (1994) by an integrated group of scientists.

• Main contractor and project coordination: GET – Gesellschaft für

Entwicklungstechnologie mbH, Jülich/Germany

• Project coordinator: K. Scharmer (GET mbH) J. Greif (European Commission, DG XII)

• Scientific coordination: J.K. Page (Em. Prof. University of Sheffield) R. Dogniaux (formerly IRM, Brussels)

• Primary data and data base - Deutscher Wetterdienst (DWD), Hamburg/Germany G. Czeplak, U. Terzenbach,

I. Bernhardt - Ecole des Mines, Centre Energétique, Groupe

Télédetection et Modélisation (ARMINES), Sophia-Antipolis/France

L. Wald, S. Antoine, O. Bauer, L. Beaudoin, H.-G. Beyer, E. François, M. Lefevre, N. Poloubinski, Ch. Rigollier

- Technical University Denmark, Thermal Insulation Laboratory (TUD), Lyngby/Denmark

H. Lund, J. Möller-Jensen

- Institut Royal Météorologique de Belgique (IRM), Brussels/Belgium

A. Joukoff, J. Tempels

- A.I. Voeikov Main Geophysical Observatory – MGO, St. Petersburg/Russia

E.P. Borisenko, A. Tsvetkov

Task coordinator: L. Wald (ARMINES)

• Solar Algorithms - Instituto Nacional de Engenharia e Tecnologia

Industrial, Instituto de Tecnologias Energéticas – Departamento de Energias Renováveis (INETI), Lisbon/Portugal

R. Aguiar, M.J. Carvalho, M. Collares Pereira

THE SOLAR RADIATION ATLAS – 1 Introduction

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- Deutscher Wetterdienst (DWD), Hamburg/Germany G. Czeplak - University of Sheffield, Sheffield/United Kingdom J.K. Page - Building Research Establishment, Watford/

United Kingdom P. Littlefair

Task coordinator: J.K. Page • Software Infrastructure (The CD-ROM) - Ecole des Mines, Centre Energétique, Groupe

Télédetection et Modélisation (ARMINES), Sophia-Antipolis/France

M. Albuisson

• User Needs and Validation - Ecole des Mines de Nantes (ARMINES),

Nantes/France B. Bourges. L. Kadi

Task coordinator: B. Bourges

Scientists from this task force have been engaged in similar work for many years, e.g. the European

Solar Radiation Atlas (Commission of the European Communities, 1984), The Solar Microclimate Project (K. Scharmer et al., 1989), the Daylighting Atlas (D.N. Asimakopoulos et al.,1996), the Solar Radiation Atlas of Africa (E. Raschke, R. Stuhlmann, W. Palz and T.C. Steemers (Ed.) ,1991), the Climatic Data Handbook for Europe (B. Bourges (Ed.), 1992), the Atlas of Hydrometeorological Data (Army Publishing House, Moscow, 1991), the Bavarian Solar and Wind Atlas (Bayerisches Staatsmin-isterium für Wirtschaft, Verkehr und Technologie (Pub.), 1995) and other solar projects. This experi-ence has enabled the authors to use the most reliable and up to date know-how on data processing, solar algorithms and mapping techniques as far as the time framework and the financial limits of the project allowed.

Following the recent rapid development of information technology, it was decided to present the main part of the Atlas information on CD-ROM (ESRA vol. 2), to be used with personal computers, so, that the Atlas integrates itself onto the “tool-shelf” of today’s generation of scientists, architects and engineers.

Nevertheless, some of the key information, including the most important maps, are published in this book. These give a preliminary information on the Atlas contents and allow for retrieval of information on “strategic” scale and should make the reader inquisitive to examine the content of the CD-ROM (ESRA vol. 2).

The CD-ROM (ESRA vol. 2) is accompanied by a User’s Guidebook (ESRA vol. 2) which gives full details on structure, content, nature and origin of data and the level of confidence as well provid-ing the primary data base for the various derived data sets. Importantly it provides detailed instructions for the CD-ROM-user.

Any reader, who looks for more basic information is referred to the numerous publications which have already originated from this project. There are more scientific publications to come, describing scientific advances achieved during the project including the “Book of Algorithms” (R. Aguiar and J. Page, to be published). This publication is the result of a thorough review of mathematical models actually used in solar radiation calculations. These have been subjected to a detailed validation and adaptation programme for the meteorological conditions prevailing in the various climatic regions of the area covered by the Atlas.

THE SOLAR RADIATION ATLAS – 2 The concept of ESRA

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2 The concept of the European Solar Radiation Atlas

2.1 Geographical area

Map 2.1 shows the geographic exterit of the area for which solar radiation parameters have been estab-lished. The mapped zone runs from 30° West to 70° East and from 25° North to 75° North, in other words from the Azores in the West to Tashkent in the East and from Oasis Kufra in the Sahara to No-vaj Semlja in the Barents Sea. The printed maps in this Atlas are in Albers projection. The computer version gives the same information, but on the canonical Projection shown in Fig. 2.1.

Fig. 2.1: The area covered by ESRA in canonical x-y co-ordinates, x - longitude; y - latitude

2.2 The content

The Atlas is built from two major components:

• the data base, • the software package (The European Solar Radiation Atlas, vol. 2).


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The data base was compiled from measurements of solar irradiation and of other meteorological and climatological parameters within the reference period 1st January 1981 to 31st December 1990. Images from satellites have been used in addition to ground based measurements to prepare clearness index maps from which the global, diffuse and direct beam irradiation maps were prepared.

From the carefully screened and quality controlled “primary data”, the following information was integrated into the data base:

Digital maps with a standard pixel size of 5´ x 5´ or approximately 10 x 10 km in the centre of the

area covered by the atlas. The following information for each pixel is needed in order to build the map • geographic position, • altitude, • global, diffuse and direct solar irradiation on horizontal surfaces, • clearness index, • biomass growth parameters and • various types of auxiliary information such as borderlines, country names, map colours, water bod-

ies, etc. The second data block consists of: Station data. These are time series of solar and meteorological data from 586 selected ground

measuring stations compiled over various time intervals from 10 year monthly averages to daily, hourly and half-hourly values. The following physical quantities are available (but not for all stations):

• sunshine duration, • global irradiation, • Ångström coefficients am & bm, • dry bulb air temperatures, • atmosphere pressure, • vapour pressure, • precipitation.

Additionally some composed data sets for individual locations, selected statistically on a month by month basis from different years observed data, are integrated:

• six Test Reference Years (TRY), • one Design Reference Year (DRY), daily level • seven Biomass Reference Years (BRY).

Figure 2.2 shows the position of the ground measuring stations. It is evident from the inhomogene-

ous distribution, that the digital maps over large parts of the mapped area are strongly based on infor-mation from satellite images.


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Fig. 2.2: Positions of ground based measuring stations

The software package (ESRA vol. 2), together with the data base, allows the user to generate in-formation for research on and application of solar energy.

Fig. 2.3: Schematic of the ESRA database and software package

The main part of the software package consists of a selection of algorithms which translate ob-served data, e.g. global solar irradiation on horizontal plane, sun hours, air temperature, etc. into useful physical information for users of solar energy, e.g. short wave radiation on an oriented surface at a

Data Base- digital maps- station data

Algorithms andsimple application

models

Editor

MapsGraphsData listingsSimple solarapplications

Hardcopy Input for furthercalculations


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given hour of a specific day, from direct, diffuse and ground reflected radiation or monthly daily aver-ages, or utilizability functions of global and/or beam irradiance etc..

These calculations in principle can be made for any geographical site inside of the area covered by the atlas – then the calculation starts from the monthly average irradiation values of the solar maps, or – with higher precision – from the data base for those sites, where daily measured series are available. For fast survey calculations simple models are integrated for assessing the performance of solar water heaters, photovoltaic devices, passive solar buildings and biomass productivity.

2.3 Users of ESRA

The atlas is designed for professional use as well as for research and teaching. It also provides an overview for those seeking rapid information on the potential of solar energy in Europe. It is applica-ble to many professional groups.

The first group are:

• engineers, • architects.

Their work is supported through the direct access to solar energy information at any specific site in

Europe from the data base of ESRA. The software package permits this primary data to be trans-formed into technical/energetic information, which in turn can be transformed to provide input pa-rameters for different types of more sophisticated computer programmes which are in use today for dimensioning of equipment, power generators, assesing solar gains for buildings, designing daylight-ing or similar problems.

The second group of users are people whose work is connected with vegetation growth:

• agronomists and foresters, • landscape designers, • settlement planners.

Special attention has been given to their needs. To assist these fields of work, additonal information

to the solar impact data is supplied for a large number of ground measuring stations on those meteoro-logical parameters which influence biomass production: air temperature, atmosphere pressure, humid-ity and precipitation.

The maps with areas of similar biomass productivity conditions may help with large-scale biomass production analysis.

The third group of users, more interested in fundamental problems are:

• solar energy research workers, • climatologists, • teachers and students.

A chapter with some fundamental information on solar radiation measurements is included with a

short description of the basic approach used in preparing the solar and meteorological information entered in the ESRA data base.

The algorithms used are described, including the tests and validation methods which have been used to select the most appropriate computational chains for inclusion in the software package. The com-paratively large number of measuring stations with long-term data provided at high resolution in time (daily and hourly values) will help in developing and testing of new mathematical models. The solar


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maps which cover the whole area of the atlas, include areas where up to now only very little or no information at all on solar energy has been available. This data, together with the meteorological data sets, can be a valuable source of information for climatologists and for research programmes on global change of our climate in Europe, especially if read in conjunction with the earlier Atlases.

Last not least, ESRA provides information to people who are concerned with long-term planning and political issues related to solar energy, biomass production and climatological impact as well as with public information:

• politicians and • journalists.

Here, the Atlas provides with its maps and surveys valuable information which is accessible without

the need to be familiar with all details of data processing and algorithmic calculations.

THE SOLAR RADIATION ATLAS – 3 Basics of solar radiation

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3 Basics of solar radiation

3.1 Introduction

Any user of solar energy is interested in the quantity of radiation which can be received and trans-formed into useful energy at a given time or given time interval at a given geographical place or area. This is true independently of whether the useful output energy will be in the form of electricity, ther-mal energy or chemically bound energy, for instance in form of biomass.

It follows that the solar irradiation must be predicted in its spectral form, defining its direction, its mix of diffuse and beam, its geographical distribution and its distribution with time.

The solar radiation at the outer edge of the atmosphere can be predicted with high precision, as it depends essentially on astronomical geometric parameters. At the surface prediction is more difficult because of the interaction of the solar beam with the atmosphere containing aerosols, with varying cloud cover and with differing soil surfaces. Mean solar radiation is subject to a large number of in-fluences with a broad statistical spectrum which cannot be predicted with mathematical precision. Thus these influences have to be determined with help of the analysis of historical measurements from which algorithms are derived which allow – together with the known astronomical geometry - the prediction of the geographical distribution of solar irradiation and its distribution in time within the bandwidth of known statistical deviations.

The three most important parameters solar geometry, time systems and interactions of solar energy with atmosphere and earth’s surface are discussed in this Chapter.

3.2 The choice of fundamental observational data in relation to mapping possibilities

Data on solar energy may be presented at any chosen level of time. The instantaneous flux of short wave radiant energy is called the irradiance. It is stated in this Atlas in W/m2.The irradiation is the integral of the irradiance over any convenient stated period of time.

As compaction is essential for practicability, Meteorological Services present their observed irradia-tion data at two principle levels of integration time, hour by hour data and day by day data. It is usual for Meteorological Services to present observed hour to hour irradiation data in solar time, also called local apparent time (LAT). In this system of time, the movements of the sun are symmetrical about the North-South line. Month by month monthly means are derived from these primary data. All calcu-lated irradiance and illuminance data in this Atlas are generated in LAT.

The design of the Atlas required making choices of appropriate integration time intervals for the ir-radiation data to be used to construct the data base and so implicitly for consequent map construction. The actual data availability was one issue. Data base compactness was a second issue. The day was selected as the appropriate generally achievable integration period. When using the Atlas, data for time levels below the day are reached in most cases through calculation using the CD-ROM tool box


24

(ESRA vol. 2), though there are a few example years on the CD-ROM with hourly or half-hourly ob-served data.

The daily global irradiation on horizontal surfaces, and their corresponding 10 year monthly mean daily values were selected as the primary observed data to be used in the construction of this Atlas after appropriate quality control. The irradiation units used are Wh/m2 per day.

As the ground observational sites are very sparse in some parts of the geographic area covered, it was considered essential for the success of the project to make effective use of available satellite ob-servations to improve spatial coverage. The final mapped 10-year monthly mean daily global irradia-tion values for horizontal surfaces presented had to be reached through a combination of ground based observations and satellite observations. These data were complemented by an extensive network of ground based stations providing year by year observations of monthly mean bright sunshine. These sunshine data enabled ground based estimates to be made of monthly mean daily global irradiation in any month in the 10 year data series (1981 - 1990), using the Angstrom formula with its two site spe-cific month by month regression coefficients, am and bm.

It was decided spatial irradiation mapping should only attempted at the monthly mean level and that the mapping should be confined to horizontal surface data. However, it was decided that the mapping process and the associated software should be designed so the inputs for slope calculations at the monthly mean level for any place could be extracted very simply from these maps. Considerations of practicability led to the decision that 10 yea day by day global irradiation time series data for only a 100 representative sites should be incorporated in the final CD-ROM data sets.

Another policy decision concerned the generation of 10 year mean values of beam and diffuse daily irradiation on horizontal surfaces. The global irradiation on horizontal surfaces consists of tow parts, the direct beam irradiation and the diffuse irradiation from the sky. Diffuse irradiation observations were only available for a limited number of sites in the mapped area. Data were needed for all mapped pixels. It was essential to fill this important gap. This limited sit of diffuse irradiation observations from Europe was used to develop computational methods to estimate 10-year daily means of diffuse irradiance, pixel by pixel. These methods are discussed later. The direct beam was then found by dif-ference. The development of these processes opened up the opportunity of providing mapped values of 10-year monthly mean beam and diffuse irradiation on horizontal surfaces. Such data were not avail-able in previous versions of the European Solar Radiation Atlas.

The final basic mapping concept used in the development of the Atlas was the decision to make sys-tematic use of a key dimensionless ratio called the clearness index, or KT value, as the fundamental basis for mapping data coordination between ground data and satellite data. This ratio is defined as the daily global horizontal irradiation at the surface divided by the corresponding daily global irradiation on a horizontal surface outside the atmosphere. The use of the dimensionless ratio reduces the impacts of variation of latitude, so bringing out more clearly the effects of mean cloudiness. Clearness index values may be extracted at the daily level or the monthly mean level. It was decided to include the 10 year monthly mean maps of clearness index in the Atlas. These maps give the user a good idea of the relative cloudiness of any region. 10 year monthly mean values below 0.30 imply very cloudy cli-mates, while 10 year monthly means above 0.60 imply very sunny climates.

The were no systematic data sets of illuminance. It was decided to adopt the recommendations of the earlier CEC Daylighting project to enable users to generate illuminance data, presented in kilolux.

In view of the demand for spectral data, it was decided a special study should be commissioned to develop a spectral irradiation model, and test it against the few European observed spectral data sets available.

Finally it was recognised that interest often centred on inclined planes. A systematic algorithmic system for calculating slope irradiances and illuminance had to be created. Any slope models had to be checked against European slope irradiation observations at the hour by hour level.


25

3.3 Time systems

The movements of the sun as seen from the earth are obviously a function of time of day. Civil time is defined for convenience to cover wide geographical areas, for example the Central European Time (CET.) Zone. Sunrise and sunset times in Civil Time depend on both latitude, which determines the daylength and also on longitude. Longitude influences the precise times of sunrise and sunset in Civil Time. Longitude does not influence the daylength. Daylength is determined solely by the date in the year and the latitude. As one moves eastwards in a given time zone, the sun at any given latitude both rises earlier and also sets earlier. The shift is 4 minutes earlier per degree of longitude moved to the East. Civil time is often called Local Mean Time (LMT).

An alternative time system widely used in solar energy studies is Solar Time often called Local Ap-parent Time (LAT). Noon in solar time is set as the instant when the sun crosses the North South me-ridian line. This is the moment when the sun has its greatest elevation. Sunrise and sunset are symmet-rical about noon in solar time. The sunrise and sunset times in solar time are independent of longitude.

Most Meteorological Services summarize solar irradiation observations on an hour by hour basis us-ing Solar Time. The algorithms used in this Atlas have also been prepared in Solar Time, so it is im-portant sometimes to be able to relate the two systems of time.

The reference longitude for Universal Time (U.T.) is Greenwich, where the longitude is zero. Due to small motions of the earth about its North South polar axis, there are small differences between Civil Time and Solar Time at Greenwich. These differences are described by the Equation of Time. Figure 3.3.1 shows the values of the Equation of Time as a function of day number in minutes. If one stays in the time zone covered by Greenwich Mean Time, each degree of longitude to the west will represent a displacement of -1/15 hours (-4 minutes). Civil time is based on defined time zones. A reference longitude can be ascribed to any defined time displacement. Central European Time is one hour ahead of GMT.

Fig. 3.3.1 The equation of time

-20-15-10-505

101520

1 31 61 91 121 151 181 211 241 271 301 331 361

Julian days

min

utes


26

The consequent relationship between Civil Time (L.M.T.) and Solar Time (L.A.T.) is given by:

L.A.T. = L.M.T. + ET + (λ - λR)/15 - c (decimal hours)

where ET is the Equation of Time in decimal hours.

λ is the longitude in degrees (East positive) λR is the longitude of the time zone selected in degrees (East positive)

c is the correction for summer time set normally 1 hour in those countries where summer time is applied.

Each one hour advance on GMT represents a change of 15 degrees in the reference longitude. Each

hour difference behind GMT represents a change of -15 degrees in reference longitude. The significance of longitude in determining the difference between L.A.T. and L.M.T. is best illus-

trated by an example drawn within a single time zone. Oviedo in Spain is at 43 21' N and 5 52' West, Berlin in Germany is 52 28' N and 13 18' E. War-

saw is at 52 16'N and 20 59' E. The Equation of Time on January 29th is -12.95 minutes (see Figure 3.3.1). If it is noon in clock time at Oviedo, the Solar Time will be 10:24. If it is noon in clock time at Berlin, Solar Time will be 11:40. If it is noon at Warsaw, Solar Time will be 12:11. If the site is close to the time reference meridian, the differences will be small. Where there are big longitudinal differ-ences as in Oviedo, the differences are very significant. When summer time is in operation, there is an additional displacement of 1 hour, which may make the displacement between the two systems of time even larger. In interpreting all hourly graphs and tables from the Tool Box, users must take special care to remember the data are all presented to the user in Solar Time.

3.4 The Julian day and the hour angle

The time system used for computing the geometric position of the sun is based on the use of the Julian day, j, to describe the position of the day in the annual sequence of days and the use of the hour angle, ω, to describe the time of day as an angle measured from solar noon. The hour angle at solar noon is set as zero. The Earth rotates about its axis once in 24 hours, so the passage of one hour represents a 15 degree rotation. The hour angle is set as positive after solar noon and negative before solar noon. Thus 09:00 L.A.T. yields an hour angle of -45o, 15:00 L.A.T. an hour angle of +45o. Table 3.4.1 gives the Julian day number both for non-leap years and for leap years, month by month, as a function of day number in the month. The Julian day is converted into a Day angle, j', for some calculation purposes. This is done by multiplying j by 360o and dividing by the mean length of the year (365.25 days taking account of the leap year cycle).


27

Table 3.4.1 The Julian day j corresponding to the i-th day of the month

Month

J for ith day of month

leap year

January i February 31 + i March 59 + i (+1) April 90 + i (+1) May 120 +i (+1) June 151 + i (+1) July 181 + i (+1) August 212 + i (+1) September 243 + i (+1) October 273 + i (+1) November 304 + i (+1) December 334 + i (+1)

3.5 Extraterrestrial radiation from the sun

The mean irradiance normal to the solar beam outside the atmosphere of the Earth at mean solar dis-tance is 1367 W/m2. This value is known as the Solar Constant Io. However the earth revolves around the sun in an elliptical orbit. So the earth is slightly closer to the sun in the Northern Hemisphere win-ter and slightly further away during the Northern Hemisphere summer. The time of closest approach is known as the Perihelion and occurs around January 2nd. The point of greatest distance is known as the Aphelion (see Figure 3.5.1).

Fig. 3.5.1 Elliptical revolution of the earth around the sun


28

The distance between the earth and sun varies by + 1.7%. Following the inverse square law, the range of the irradiance is + 3.3%. In addition the value of Io varies within a period of 11.2 years by about 1 W/m2. This is caused by cyclical variations of solar activity. The irradiance falling on a hori-zontal plane outside the atmosphere, Go is given by:

Go = ε 1367 sin γs W/m2 (3.5.1)

where ε is the correction to mean solar distance γs is the solar altitude in degrees.

ε is calculated as

ε = 1 + 0.0334 cos(j'-2.80o), where j' is the day angle (3.5.2) The extraterrestrial irradiance falling on a horizontal surface may be integrated over the day to find

the daily irradiation between sunrise and sunset falling on a horizontal surface, God. It is expressed here in Wh/m2. Figure 3.5.2 shows graphically the variation of God with Latitude and Julian day in the Northern Hemisphere. Such daily extraterrestrial data are used as denominators in the systematic analysis of daily irradiation reaching the surface to generate the Clearness Index, Gd/God, from the observed daily global irradiation, Gd.

Fig. 3.5.2 The extraterrestrial irradiation at the top of the atmosphere in the Northern Hemisphere as a function of day in the year and latitude

The average extraterrestrial irradiance onto the earth´s atmosphere can easily be estimated using simple geometric principles. The mean extraterrestrial flux per unit surface area is given by the prod-uct of the solar constant and the ratio of the area of the cross section πR2 divided by the total area of the surface 4πR2 , i.e. 1367/4 = 342 W/m

2 . Refer Figure 3.5.3.

0

2000

4000

6000

8000

10000

12000

14000

1 51 101 151 201 251 301 351

Julian day number

Extr

ater

rest

rial i

rrad

iatio

n, W

h/m

^2

per d

ay

Lat. 60 NLat. 50 NLat. 40 NLat. 30 NLat. 20 NLat. 10 NLat. 0 N


29

Fig 3.5.3 Available extraterrestrial mean solar irradiance per m2 striking the atmosphere

The considerable modifications introduced by the atmosphere now have to be considered. These modifications are strongly influenced by the solar geometry, which will be considered first.

3.6 Geometry of solar movements as seen from the earth

3.6.1 The sun-earth geometry

The knowledge of the geometrical parameters describing the position of the sun as seen from the earth is essential when information on solar radiation for a specific location and time is required. Three fun-damental parameters are needed to determine the position of the sun as seen from any point of the earth.

• the Latitude of the site of observation. • the Julian day number. • the time of day expressed as an hour angle from solar noon.

Su

R

Mean solar irradi-onto earth´s atmosphere

I

/4 = 342 W/m

Earth, radius R

R

Solar constant = 1367 W/m

equator


30

3.6.2 Declination angle

The key calculation input for generating the solar geometry is the declination. The declination angle δ is the angle between the Equatorial Plane and the line joining the centre of the Earth's sphere to the centre of the Solar disk. The axis of rotation of the Earth about the poles is set at an angle to the so-called Plane of the Ecliptic. The angle of inclination is 23o 27'. The maximum declination angle of 23o 27' in the Northern Hemisphere occurs at the Summer Solstice, on June 21st. The minimum declina-tion angle of -23o 27' in the Northern Hemisphere occurs at the Winter Solstice on December 22nd. The declination of the sun is a continuously varying function of time, but the rate of change within a specific day is small enough to allow the use of a constant value for any Julian day. One parameter, the Julian day number, enables the solar declination to be established for any point in time with ac-ceptable practical accuracy. For very high accuracy the Year Number, the Longitude of the site and the precise time of day have to be introduced into the calculation, but this refinement is not usually neces-sary in most practical studies. Latitude enters in the subsequent geometric calculations.

The following simplified declination formula has been successfully used for many years in the vari-ous CEC Solar Radiation Atlas Programmes.

δ = sin -1{0.3978 sin(j'-80.2o+1.92(sin(j'-2.80o)))} degrees (3.6.1)

where j' is the Julian day number expressed as a day angle in degrees. The formula provides mean daily values averaged over the four year leap year time cycle. Figure

3.6.1 plots the declination calculated with this formula against the Julian Day number.

Fig. 3.6.1 Declination angle δ as a function of Julian Day number

-30.00

-20.00

-10.00

0.00

10.00

20.00

30.00

1 51 101 151 201 251 301 351

Julian day number

Dec

linat

ion

degr

ees


31

3.6.3 The solar altitude angle

Figure 3.6.2 sets down the geometric definitions of the solar altitude and azimuth angles.

Fig. 3.6.2 Solar azimuth αs and solar altitude γs seen from an observer at position P

The solar altitude angle (often referred to as solar elevation angle) is calculated as a function of time of day, expressed as an hour angle ω using the following formula:

γs = sin -1(sin φ sin δ + cos φ cos δ cos ω) degrees (3.6.1)

where φ is the latitude, Northern Hemisphere positive, degrees, δ is the solar declination angle, degrees, ω is the solar hour angle, degrees.

Time, t, in decimal hours on the 24 hour clock (using Local Apparent Time) is first converted to an

hour angle using:

ω = 15(t-12) degrees (3.6.2)

Ф

( s

αs


32

3.6.4 Solar azimuth angle

The direction of the sun is given by its azimuth angle. The solar azimuth angle, αs, is the angle be-tween the vertical plane containing the direction of the sun, and the vertical plane running true North South. It is measured from due South in the Northern Hemisphere and from due North in the Southern Hemisphere. The azimuth angle has a positive value when the sun is to the West of the South-North meridian, i.e. during afternoon in solar time. These angles may be converted into bearings from true north, but it is important to adopt the correct definition of azimuth angle in using the algorithms that follow. Refer Figure 3.6.2. The azimuth angle may be calculated as:

cos αs = (sin φ sin γs − sin δ) /cos φ cos γ s (3.6.3.a) sin αs = cos δ sin ω/cos γs (3.6.3.b) If sin αs < 0 then αs = − cos-1(cos αs ) (3.6.3.c) If sin αs > 0 then αs = cos-1(cos αs ) (3.6.3.d)

(Both formulae are needed in order to attribute the azimuth angle automatically into the correct

quadrant in computing programmes). Note in the Southern Hemisphere, cos αs = - (sin φ sin γs − sin δ) /cos φ cos γs

Fig. 3.6.3 Geometry of the earth-sun system from the viewpoint of an observer at the position P on earth’s surface.

Φ

plane of ecliptic, plane ofEarth’s orbit around sun

solstice21.June

declination δ

solar hour angle

vernal equinoxδ=0°

S

solstice22.December

Φ

Φ


33

3.6.5 Sunset hour angle and daylength

The sunset hour angle, ωss, is the hour angle at sunset. It defines the length of the astronomical day. The sunset hour angle is easily calculated as cos-1(-tan φ tan δ) degrees; the sunrise hour angle, ωsr, as -cos-1(-tan φ tan δ) degrees. Sunrise occurs at a time of (12 - cos-1(-tan φ tan δ)/15) hours L.A.T., while sunset occurs at time (12 + cos-1(-tan φ tan δ)/15 hours L.A.T). The astronomical daylength, Sod, is given by cos-1(-tan φ tan δ)/7.5 hours.

If (-tan φ tan δ)>1 then the sun never rises on that day (Polar winter). If (-tan φ tan δ)<-1 then the sun never sets on that day (Polar summer).

3.6.6 Relative daily sunshine duration

It is often useful to express the daily observed sunshine in dimensionless terms. This is simply achieved by dividing the observed daily sunshine Sd by the astronomical day-length, Sod. Thus σd = Sd/Sod. This ratio is called the daily relative sunshine duration, alternatively % possible sunshine. The monthly mean is (σd)m. This dimensionless ratio is widely used in the calculation of mean daily global radiation from observed mean daily sunshine duration. See below.

3.6.7 Angle of incidence

The beam irradiance on any surface of azimuth orientation α and tilt β is given by Bn cos ν(β,α) where ν(β,α) is the angle of incidence on the specific surface. Its calculation requires a specification of the orientation of the plane, β, as a surface azimuth angle, measured from due South in the Northern Hemisphere and from due North in the Southern Hemisphere. The inclination angle of the surface, α, is measured from the horizontal plane.

In the calculation of cos ν(β,α), the wall solar azimuth angle is first determined. The wall solar azi-

muth angle is the angle between the vertical plane containing the normal to the surface and the vertical plane passing through the centre of the solar disc, i.e. it is the resolved angle on the horizontal plane between the direction of the sun and the normal to the surface. Its value must lie between -180o and +180o degrees.

αF = αs − α degrees (3.6.4)

If αF > 180ο then αF = αF - 360o degrees.

If αF < 180ο then αF = αF + 360o degrees.

The sign convention normally used in the Northern Hemisphere is as follows, sun anti-clockwise

from normal on plan, sign negative, sun clockwise from normal on plan, sign positive. In the Southern


34

Hemisphere the sun travels in an anti-clockwise direction and the sign convention is changed. In be-tween the Tropic of Cancer and the Tropic of Capricorn, the direction of movement of the sun re-solved on plan varies with season. Greater care is then needed with sign conventions.

Defining the surface inclination as β, (vertical = 90o), the cosine of the angle of incidence is given

by: cos ν(β, α) = cos γs sin β cos αF + sinγs cos β (3.6.5)

If cos ν(β, α) is negative, the sun lies behind the surface. A simpler form may be used on vertical surfaces: cos ν(90ο, α) = cos γs cos αF (3.6.6)

3.7 Choice of calculation times

The ESRA Atlas tool box calculations are normally based on the use of the mid hour times in L.A.T., i.e. 09:30, 10:30, except in the sunrise and sunset hours. In these hours, the hour angle used was set midway between the sunrise hour angle, ωsr and the hour angle at the end of the sunrise hour at the start of the day, INT(ωsr)+1 and midway between the hour angle at beginning of the sunset hour INT(ωss) and the hour angle at sunset, ωss, where INT refers to the integer of the expression. Unless this measure is adopted in the place of the standard mid hour calculation used for other hours, no solar geometry will be generated if sunrise occurs after the middle of the sunrise hour in the morning or sets before the middle of sunset hour in afternoon. Furthermore unrepresentatively low mean solar eleva-tions will be calculated for the period if the sun is in fact up.

3.8 The solar radiation at the surface of the earth

The global irradiation is the short wave energy that actually reaches a horizontal surface after all the absorption and scattering processes. This amount is influenced by the path length through the atmos-phere, the clarity of atmosphere, the amount and type of cloud cover.

The interaction of the solar radiation with the atmosphere involves a series of quite complex proc-esses. In order to simplify understanding of the role of the atmosphere, the energetic equilibrium be-tween the atmosphere, the surface of the earth and incoming solar radiation can be separated into three processes:

1. Solar radiation entering the atmosphere being absorbed and scattered before reaching the ground. 2. Thermal (long wave) radiation originating from the surface of the earth and the atmosphere above. 3. Non-radiative heat and energy transport processes in the atmosphere and between soil and the at-

mosphere. This Atlas deals primarily with processes which belong to the first category concerning the short

wave solar radiation in the waveband 0.2 to 4.0 µm, though there is a module in the CD-ROM tool box and in the User's Handbook dealing with the estimation of the long wave radiation balance.


35

The incoming extraterrestrial irradiation enters the atmosphere and interacts with the atmospheric components, i.e. the various gases, (including water vapour) and the condensed water droplets and other aerosols. Some of these absorb short wave radiant energy, and others scatter it. In broad terms

• Absorption by gas molecules, aerosols and condensed water accounts for 20% of the energy loss.

This results in a heating of the atmosphere. • Back scattering and back reflection mainly from clouds sends 23% of the incoming solar energy

directly back to space. • Averaging over the globe, only 57% of the primary incoming solar energy reaches the ground. • 30% of the incident extraterrestrial energy reaches the ground as beam radiation. • 27% of the incoming extraterrestrial energy reaches the ground as beam radiation.

Depending on the reflectance of ground for solar radiation (the albedo), 8% of the short wave radia-

tion is reflected back to space from the ground. This occurs with only minor spectral degradation. 49% of the extraterrestrial flux is absorbed at the surface and is transformed into sensible heat or converted chemically bound energy forms like biomass, or transformed into other renewable energy (wind, wa-ter).

The second path of heat loss to space is through thermal radiation in the band 4.0 to 100 µm. The thermal radiation resulting from the absorption of short wave radiation complements the thermal radia-tion to space resulting from the Earth's internal geological processes and radioactive decay. The pro-portion attributable to the solar budget is 49%. There is an added contribution to the outgoing long wave radiation to space from the short wave energy absorbed in clouds and in the atmosphere. This brings the absorbed short wave contribution to outgoing thermal radiation to 69% of the incoming short wave radiation.

The global energy balance of the outer surface of the atmosphere of the earth is thus: Incoming short wave radiation 100% Scattered and reflected short wave radiation -31% Thermal radiation to space -69% Figure 3.8.1 shows these processes in a graphical form.


36

Fig. 3.8.1 The mean distribution of the solar energy and radiation in the system earth/atmosphere. Modified after Treubert at al., IPCC 1996

3.9 User needs

Users of solar energy need to be able to establish the following parameters quantitatively:

• G(φ, λ, t1, t2) the total amount of solar irradation at latitude φ, longitude λ, between time t1 and time t2 on surfaces of any orientation

• The relative proportion of beam irradiation and diffuse irradiation. • The spectral breakdown of the radiation at the surface.

Solar radiation


37

The Atlas allows the provision of radiation data at a number of time scales. The maps present daily averages of global, beam and diffuse radiation over each month and also annual averages. The CD-ROM tool-box (The European Solar Radiation Atlas, vol. 2) allows breakdown of this primary data to shorter time intervals.

3.10 Transmission of solar radiation through the cloudless atmosphere

3.10.1 Direct and diffuse irradiation

The global solar irradiation on a horizontal surface has two components, the direct beam component B and the diffuse component D. Clouds impact strongly on the global radiation received. So it is difficult to predict the components of global radiation in the presence of clouds. Under clear sky conditions, reasonably accurate predictions can be made from a knowledge of the solar geometry and the level of water vapour and particulates in the atmosphere.

3.10.2 Relative optical air mass

The path length through the atmosphere exerts an important influence. This path length is described by the relative optical air mass m. Its value depends on the solar altitude angle γs and on the site at-mospheric pressure p, which is influenced by site height above sea level. The value m of the relative optical air mass can be calculated with an error of less than 0.5% for all solar elevations (F. Kasten & A.T. Young, 1989) as:

m = (p/po)/{sin γs + 0.50572 (γs + 6.07995o) -1.6364} (3.10.1)

where γs is the solar altitude in degrees and (p/po) is the pressure correction for station height.

The following simple expression is adequate to estimate (p/po) :

(p/po) = exp(-z/HR) (3.10.2)

where z is the site elevation above sea level in metres and HR = 8400 m. Figure 3.10.1 gives a

schematic representation of the relative optical air mass at sea level.


38

Fig. 3.10.2 The relative optical air mass m at sea level. It is important for sites significantly above sea level to apply the correction (p/po).

3.10.3 The Linke turbidity factor

The other factor in the attenuation of the atmosphere is a function of the concentrations of the various constituents in the atmosphere. Their impacts can be assessed by comparison of the actual observed optical depth with the theoretical optical depth of a perfectly clean dry scattering Rayleigh atmos-phere, δr(m). This reference optical depth is a function of air mass. It is calculated as described below. The ratio of the two optical depths is known as the Linke turbidity factor, TLK. The clear sky beam irradiance normal to the beam at the surface is calculated as:

Ic = 1367. ε exp ( - 0.8662 TLK m δr(m) ) W/m2 (3.10.3)

where TLK is the air mass 2 Linke Turbidity Factor,

m is the optical air mass corrected for station height, δr (m) is the Rayleigh optical depth at air mass m,

ε is the correction factor to mean solar distance. The beam irradiance on a horizontal surface from the clear sky is calculated by resolving the beam

normal irradiance onto the horizontal plane, as: B c = 1367. ε exp ( -0.8662 TLK m δr (m) ) sin γs W/m2 (3.10.4)

where γs is the solar altitude in degrees.

With the formulation now adopted, no solar altitude correction has to be applied to TLK, unlike the

formulation used in earlier versions of the European Solar Radiation Atlases. The two formulations

earth surface at sea level, z = 0 ⇒⇒⇒⇒ p ≈≈≈≈ p0

atmospheric layer

space, p = 0

1 sin γ + a ( γ + b ) cm =m = 1

γ


39

match perfectly at air mass 2, which is used as the reference base for Linke turbidity factor data de-rived from observations.

The following are rough guide-line values for selecting the Linke turbidity factor. More detailed methods appropriate for specific sites are given in the User's Handbook.

• very clear cold air in winter TLK = 2 • clear warm air TLK = 3 • moist warm air TLK = 4-6 • polluted air TLK > 6

In Europe there is normally an annual cycle of Linke turbidity factor with the lowest values in De-

cember and January and the highest values in July and August. The first step in using these equations 3.10.3 and 3.10.4 is to estimate the Rayleigh optical depth for the perfectly clean dry atmosphere.

3.10.4 Estimating the Rayleigh optical thickness

The Rayleigh optical depth is calculated from the optical air mass by the algorithm as first set down by Louche, Peri and Iqbal and modified by Kasten (1996). If m<20 then

1/δr(m) = 6.6296 + 1.7513 m - 0.1202 m2 + 0.0065 m3 - 0.00013 m4 (3.10.5.a)

where m is the optical air mass.

The polynomial equation fit limit is an air mass less than or equal 20. If m greater 20, the following expression must be used: 1/δr(m) = (10.4 + 0.718 m) (3.10.5.b)

The Equation 3.10.5a gives unreliable erratic results in this region, and its use should be strictly

avoided in this range.

3.10. 5 Estimating clear sky diffuse irradiance

The detailed estimation of the clear sky diffuse irradiance on horizontal surfaces is discussed in the User's Handbook. The diffuse irradiance increases as the Linke turbidity factor increases. Figure 3.10.1 illustrates the relationship between diffuse irradiance and Linke turbidity factor as a function of solar altitude for a sea level site. As the beam irradiance decreases, the diffuse irradiance from the clear sky increases.


40

Fig. 3.10.1 The clear sky diffuse irradiance falling on a horizontal surface as a function of solar altitude and air mass 2 Linke turbidity factor, TLK

3.10.6 The clear sky global irradiation

The clear sky global irradiation on a horizontal surface is estimated as the sum of the horizontal beam irradiance and the horizontal diffuse irradiance. The hour by hour values can be integrated to provide daily values of clear sky global irradiation on horizontal planes for any Linke turbidity factor. Input-ting a Linke turbidity factor of 3.5 enabled Figure 3.10.2 to be calculated. This shows the clear day global irradiation in the Northern Hemisphere as a function of Latitude and Julian day number for a Linke turbidity factor of 3.5. The steep fall off in winter at high Latitudes is very evident. The latitu-dinal gradient of solar global radiation on clear days is very much less in summer.

3.11 Monthly mean daily global radiation and the monthly mean daily Clearness Index

While God and hence the monthly mean (God)m, can be calculated, Gd has to be either directly ob-served or indirectly estimated. Cloud cover has a big impact on the monthly mean global irradiation. Satellite observations allow the cloud cover to be spatially assessed. The impact of cloud on ground level sunshine availability and on the consequent irradiation is very great.

The monthly mean global radiation data in this Atlas have been compounded from three sources:

• Ground stations observing solar radiation and usually sunshine as well. • Ground stations observing only sunshine. • Satellite observations.

Clear sky diffuse irradiance on horizontal surfaces as a function of Linke turbidity factor at m.s.d.

050

100150200250300350400

0 20 40 60 80 100

Solar altitude, degrees

Diff

use

irrad

ianc

e, W

/m^2

Linke turb 8Linke turb 7Linke turb 6Linke turb 5Linke turb 4Linke turb 3Linke turb 2


41

Ground based sunshine observations can be used to assess monthly mean global radiation. A key physical concept, fundamental to the development of this Atlas, is the Clearness Index. Its daily value is calculated as the ratio Gd/God. Graphical values of the denominator God are given in Figure 3.10.1 as a function of Latitude and Julian day number. This daily ratio is often called the daily KT value, KTd. The monthly mean daily Clearness Index is designated as (KTd)m = (Gd)m/(God)m. This dimen-sionless quantity is used in many standard calculation procedures.

This monthly mean daily Clearness Index is the primary monthly mapped variable in this Atlas. A powerful technique, widely used in the development of this Atlas, has been the use of daily ob-

served sunshine data which are more widely available than global radiation data to estimate the Clear-ness Index from ground observations of sunshine for a number of sites with no radiation observations. This process has reinforced the more limited ground observed solar radiation data base. The following relationship called the Angstrom formula was used:

(KTd)m = am + bm(σd)m (3.11.1)

where am and bm are site dependent monthly regression coefficients and (σd)m is the monthly mean relative sunshine duration.

It follows that (Gd)m = (am + bm(σd)m ) (God)m (3.11.2) Site dependent values of am and bm are available in the ESRA Database (The European Solar Ra-

diation Atlas, vol. 2) as quality controlled values calculated from 10 year daily series of observed sun-shine and observed global radiation for a large number of sites.

The satellite data base was then related to this expanded ground data base expressed in the dimen-

sionless form of monthly mean daily Clearness Indices. Readers should note the mapped values of monthly mean global radiation, beam and diffuse radiation provided in this Atlas were derived from the satellite interpolated (KTd)m mapped values, pixel by pixel.

3.12 Splitting the monthly mean daily global radiation into its beam and diffuse components

The diffuse radiation data presented in the maps of this Atlas are all estimated data. Observed monthly mean diffuse radiation data were available for a number of sites. These data were used to construct a polynomial model to estimate the ratio of the monthly mean daily diffuse irradiation to the monthly mean daily global irradiation, (Dd)m/(Gd)m from the monthly mean daily Clearness Index, (KTd)m. The basic model took the form:

(Dd)m/(Gd)m = co + c1 (KTd)m + c2( (KTd)m)2 + c3 ( (KTd)m)3 (3.12.1)

If (Dd)m/(Gd)m >1 then (Dd)m/(Gd)m = 1


42

The coefficients co, c1 c2, c3 were derived dividing the observed data into 4 latitude bands grouped in 4 seasons. The monthly mean diffuse maps were developed from the monthly mean daily clearness index maps, pixel by pixel, using the above equation using the appropriate coefficients for the latitude band and the season for each pixel. For details refer to the User's Handbook (The European Solar Ra-diation Atlas, vol. 2).

If (KTd)m falls to 0.2 virtually all the radiation is diffuse and there is practically no beam radiation.

In very sunny climates between 20% and 30% of the radiation on horizontal surfaces is diffuse. More typically the beam diffuse mix lies in the range 40%-60% according to mean sunniness. Diffuse radia-tion thus forms a significant part of the resource.

THE SOLAR RADIATION ATLAS – 4 From solar measurements to the solar database

43

4 From solar measurements to the solar data base

Two types of solar radiation measurements used for the Atlas have to be distinguished: ground based measurements made at specific sites at the earth´s surface and measurements derived from satellite images covering a certain section on earth with restricted solution. Geostationary satellites which have a fixed position respective to the Earth routinely measure the energy reflected by the system earth/atmosphere in different wave length bands. Thus they are capable of observing the same wide geographical area with a high repetition in time. The images provided by satellites are very useful in meteorology for daily forecasting or for the monitoring of devastating tropical cyclones. They are fre-quently displayed on TV channels and are well known to people. A series of METEOSAT satellites have been observing Europe and Africa. These data have been of primary interest in the construction of this Atlas.

4.1 Ground measuring techniques for solar radiation components

There are four basic types of measuring instruments for radiation components: sunshine recording, pyrheliometers, pyranometers and pyrgeometers. The first one delivers information on sunshine dura-tion. The second delivers information on short wave beam radiation normal to the beam. The third measures the hemispherical short wave solar diffuse and global radiation. The last measures long wave terrestrial radiation. Most solar energy measuring instruments have digitised data outputs stored by computers. Errors within these data are mainly caused by insufficient maintenance and calibration but also by using unsuitable instruments.

4.1.1 Sunshine duration

The most simple and widely used instrument for registration of sun hours is the Campbell-Stokes He-liograph (Fig. 4.1.1). The key component is a glass bowl working as a burning glass. It burns a track in a registration paper if sun is shining with sufficient intensity. The threshold intensity normal to the solar beam for registration of sunshine by this measuring technique is about 120 W/m2 . There are four main types of errors in sunshine duration regristration with this type of instrument:

• the overburning of the registration paper during intermittened sunshine which results in overesti-

mates of sunshine duration, • the threshold sensitivity of the Campbell-Stokes recorder of 120 W/m2 which results in underesti-

mates of sunshine duration, • the analysis of the registration paper made by hand may cause additional errors in either direction, • and finally deteriorations of the performance of the glass sphere caused by weather phenomena like

rain or hoarfrost and by insufficient maintenance which results in underestimates of sunshine dura-tion.


44

Fig 4.1.1 Campbell-Stokes-Heliograph

New types of sunshine recorders based on photoelectric measuring techniques combined with a digi-tised data output, generally stored by computer, could minimise the possible errors except those due to the soiling of the instrument. The threshold value of 120 W/m2 is implemented artificially to meet a WMO convention which aims to keep data measured with different types of instruments homogene-ous. This requirement has to be respected especially at higher latitudes, where elevation of sun may be small all day causing errors in the registration of sunshine.

4.1.2 Hemispherical solar radiation

The horizontal solar irradiance is generally measured with pyranometers (Fig. 4.1.2). One measuring principle used is based on the differences of temperature between two thermo-elements with different heat capacities. Protected against long wave radiation and other weather influences by a special glass dome, only letting solar radiation from 0.3 to 3 µm pass, the solar radiation heats one element. Simul-taneously the other element is heated by electricity to keep the same temperature. The squared power of the electric heating is then proportional to the solar energy. The calibration factor has to be deter-mined for each individual pyranometer. The accuracy of well calibrated and modern pyranometers is about 2% but may be deteriorate considerably in case of insufficient maintenance or in case of operat-ing instruments of moderate quality. Pyranometers are used for measuring the global solar radiation as the total energy of solar irradiance from all directions of the sky including the beam solar radiation. For measuring diffuse radiation a shading disk or ring is fitted to the pyranometer shading the sun´s direct radiation. When shading rings are used, measured data have to be corrected for the shaded part of the sky. The correction depends on the radius and the width of the shadow ring. Further advice on the use of pyranometers is given in standard ISO 9060. This ISO standard can act as a guideline in choosing the right detector specification.


45

Fig 4.1.2 Pyranometer

To complete the list of instruments measuring solar radiation quantities the pyrheliometer for re-cording direct solar radiation has to be mentioned. The registration method is again based on tempera-ture differences caused by heating of absorbing planes, but the instrument itself is constructed in a different way. It has to be oriented exactly in direction of the sun´s disk. New types of pyrheliometer mounted on automatic tracking supports therefor are very expensive. Fig 4.1.3 shows an example for a roof installed solar tracker. Unfortunately pyrheliometers are generally not used within routine ob-servations because direct solar radiation can be easily derived from the difference between global and diffuse radiation. Indeed routine measuring of all three radiation quantities would make the detection of errors within one quantity easier.

Fig. 4.1.3 Solar tracker, equipped with a pyrheliometer, the tubular instrument on the left, and three horizontal pyranometers, using two shading disks


46

4.1.3 Terrestrial radiation

Pyrgeometers are used for measuring the terrestrial long wave radiation. They differ essentially from pyranometers in the composition of the dome, which is mirrored in a way that as much as possible short wave radiation from the sun is reflected. The material used only allows infrared radiation from 3 to 50 µm to pass. Nevertheless, about 3 % of the short wave radiation still penetrates the dome and increases the thermopile output. To reduce this pyrgeometers should be used in combination with a shading disk to exclude effects of direct solar radiation.

4.2 Solar radiation data from satellite images

Meteorological satellites are generally equipped with sensors having broad spectral bands and thus observe most of the sunlight reflected by the system earth/atmosphere. Several methods have been developed to derive the global solar radiation impinging at ground from these remote measurements. Most of them are based upon the same principles. The radiation received by a location under clear-sky can be modelled either by empirical laws or by sophisticated numerical models of the radiative trans-fer within the atmosphere. The energy measured by the satellites sensor at a specific instant is com-pared to this clear-sky radiation. The discrepancy is a function of the optical thickness of the atmos-phere which is interlinked to the clearness index. The clearness index is the ratio of the global solar radiation to the extraterrestrial radiation. The accuracy of these data is not as good as ground measured data. For the Möser-Raschke model (W. Möser, E. Raschke, 1984) tests have shown that the modelled daily totals of global solar radiation deviates from ground measurements by about 10% during summer and by about 20% during winter. When considering monthly means the deviation reduces to about 5% (F.J. Dieckmann et al., 1988). These deviations are caused mainly by insufficient estimation of the atmospheric transmission in the presence of clouds but also by an insufficient temporal sampling rate of the satellite images which is mostly hourly. Ground based data are measured generally with a sam-pling rate of a minute and record therefore micro-scale processes in variation of solar radiation. In contrast, satellite derived data with an hourly sampling rate record only meso-scale processes. Never-theless, satellite derived data offer a unique possibility for assessing the solar radiation in areas where ground based measurements are scarce or even non-existent.

4.3 Detection of errors within raw data

When taking observations and processing their results, errors may be made which should be detected and corrected. The major responsibility for the correctness of ground measured solar radiation data remains with the national services or the bodies delivering these data, except for data that were deliv-ered explicitly with reference to a missing validation. The results of radiation measurements should be checked in two stages: a technical control and a quality control. The technical control deals with the correctness of arithmetic calculations, the quality control with physical agreement of the observed parameter to other radiation parameters. For measured data which are used in this Atlas, it was as-sumed that all data had passed already through a technical control. Because of different quality control methods all daily totals of solar radiation data were controlled using the following steps:


47

• solar radiation values had to be less than extraterrestrial values, sunshine duration values had to be less or equal the corresponding astronomical value,

• solar radiation values had to lie within the range of the expected clear-sky extreme values consider-ing the influence of the atmospheric layer,

• values of solar radiation parameters had to be in a specific range compared with nearby station val-ues with allowance for their spatial variability

• basic relationships between different radiation components should be fulfilled • variation of the relative terms G/G0 of the Angstrom regression should lie within a defined range.

Obviously erroneous values are rejected from the entire data set in contrast to questionable data.

These are marked with an indicator in order not to reject values that may be still of scientific interest. With the quality control algorithms used (U. Terzenbach, 1995) a rate of about 4% of the entire solar radiation data had to be rejected or marked as questionable.

THE SOLAR RADIATION ATLAS – 5 The ESRA database

49

5 The ESRA database

5.1 The reference period and the reference area

The data base of ESRA, available on the CD-Rom of the European Solar Radiation Atlas, vol. 2, has been constructed in order to allow proper descriptions of the irradiation both in space and time, permitting an appropriate exploitation of the data to derive information of ahigher level. The user of solar data generally needs exact information on the distribution of solar energy in space and in time. He expects that the future trend can be extrapolated from historical measurements. As long term meas-urements are available only from a limited number of unevenly distributed stations, and as older measurements often are not fully reliable, it was decided to adopt the following framework:

The reference period for the bulk of data selected was between 1981 to 1990. This statement is valid for the ground measured data of solar radiation and other meteorological parameters. Satellite derived data, which were used to obtain information in areas, where no ground measurement stations were available and to aid interpolation, do not cover the whole period.

The area covered by the Atlas extends from 25° North to 75° North and from 30° West to 70° East, and thus includes the whole of geographical Europe, North Africa and the western part of Asia.

5.2 Ground measured and derived data

The many year measurement series of solar irradiation and sunshine duration from the European ra-diometric and synoptic network stations were collected and quality controlled in a common data base. The list of sites is given in Annex 2.

Measurements of daily sums of global solar irradiation on the horizontal plane within the period 1981-1990 were delivered by the World Radiation Data Centre (WRDC), Saint Petersburg (Russia), and by several national weather services in Europe (see Table 5.1). Data for 586 sites were provided.

Daily sums of observed diffuse solar radiation on the horizontal plane within the period 1981-1990 were available for 63 sites with nearly complete measurements for 36 sites.

Hourly sums of global and diffuse solar irradiation on the horizontal plane were available for the fol-lowing sites:

Belgium (1981-1990) Uccle, Ostende, Melle Cyprus Athalassa (1984-1990) Germany (1981-1990) Hamburg, Braunschweig, Wahnsdorf, Trier, Würzburg, Weihenstephan Norway (1981-1990) Bergen Sweden Lulea (1983-1990), Stockholm (1986-1990), Norrköpping (1984-1989), Lund (1983-1990)

Daily sums of sunshine duration were available at 586 sites. Sunshine duration data delivered by WRDC provided only monthly sums. Sunshine duration for 691 sites were supplied as monthly sums, with nearly complete observations, that is at least 96 monthly sums, for 558 sites.


50

Hourly means of spectral solar irradiance measurements were recorded at Uccle, in Belgium, Grenoble, in France, and at two stations in Germany. The spectral range is 320 - 1050 nm within the period 1989-1991 for Stuttgart-Vaihingen and Widderstall. Hourly datasets for 2700 hours were supplied for Stuttgart-Vaihingen and 1000 hours for Widderstall.

Radiation data and other meteorological data were calculated for the period 1981-1990 as long time monthly means (12 values per site and per parameter) for the following parameters: • daily sum of horizontal global irradiation (588 sites) • daily sum of sunshine duration (558 sites) • daily minimum air temperature (254 sites) • daily maximum air temperature (254 sites) • daily sum of precipitation (254 sites) • atmospheric pressure (247 sites) • water vapour pressure (254 sites)

The coefficients am and bm of the Ångström regression were derived at 199 sites with available daily values of sunshine duration and global solar irradiation by regression methods. Finally 141 pairs of Ångström coefficients of excellent quality were obtained using the remaining sites, called reference sites.

The number of sites with available monthly means of global solar irradiation (observed and estimated) increased to 610 by using the Ångström regression at sites where only sunshine duration measurements are available, or at sites where the number of observations of daily global solar irradiation was small and their monthly mean values were not representative for the whole period 1981-1990.

5.3 Satellite derived data

Images originating from the geostationary Meteosat satellite have been processed by several weather services and research institutes for the assessment of the global irradiation on horizontal plane (see e.g., Grüter et al. 1986). Some of these satellite-derived assessments have been made available to the Atlas project for the construction of the final maps in the CD-ROM (the European Solar Radiation Atlas, vol. 2). The existing maps offered various geographical coverages, spatial resolutions and tem-poral coverages, making their merging into a single map difficult. Major datasets were the following:

World, without poles regions (SRB project, Anonymous 1994) resol. about 180 km 1985-1988 Western and Central Europe (Solar radiation atlas of Africa 1991) resol. about 50 km 1985-1986 Western and Central Europe resol. about 10 km 1983-1985

5.4 Sources of data

Measurements of daily sums of global solar irradiation and monthly sums of sunshine duration were supplied by the World Radiation Data Centre (WRDC), Saint Petersburg (Russia). Additional data of daily sums of sunshine duration were provided by several national weather services and scientific in-stitutes. Some of these delivered measurements of global and diffuse radiation as well, on a daily or hourly basis. Several maps of satellite-derived global radiation were also kindly supplied to build the Atlas. The support provided from these data was greatly appreciated by all project participants. All these institutions are especially thanked for their good will and co-operation. Table 5.1 lists the sup-porting institutions.


51

Table 5.1 List of institutions that have supplied data for the construction of the Atlas (alphabetic order)

Country Organisation

Austria Zentralanstalt für Meteorologie und Geodynamik, Wien Belgium Institut Royal Météorologique de Belgique, Bruxelles Croatia Drzavni Hidrometeoroloski Zavod, Zagreb Cyprus Meteorological Service, Nicosia Czech Republic Czech Hydrometeorological Institute, Praha

Solar and Ozone Observatory, Hradec Kralove Denmark Technical University of Denmark, Lyngby

Royal Veterinary and Agricultural University, Section for Agrohydrology and Bioclimato- logy, Taastrup

Finland Finnish Meteorological Institute, Helsinki Germany Deutscher Wetterdienst, Offenbach

GKSS - Forschungszentrum, Geesthacht Zentrum für Sonnenenergie- und Wasserstoff-Forschung, Stuttgart

Greece Hellenic National Meteorological Service, Athens Hungary Hungarian Meteorological Service, Budapest Iceland Icelandic Meteorological Office, Reykjavik Ireland Meteorological Service, Dublin Italy Servizio Meteorologico dell'Aeronautica Militare, Roma

Joint Research Center of the European Commission, Ispra Jordan Meteorological Department, Amman Civil Airport, Amman Malta Meteorological Office, Civil Aviation Department, Luqa Netherlands Koninklijk Nederlands Meteorologisch Institut, De Bilt Norway University of Bergen, Geophysical Institute, Bergen Poland Institute of Meteorology and Water Management, Warsaw Russia World Radiation Data Centre, St. Petersburg Switzerland Schweizerische Meteorologische Anstalt, Zürich Sweden Sveriges Meteorologiska och Hydrologiska Institut, Norrköping Turkey Turkish State Meteorological Service, Ankara United Kingdom Meteorological Office, Bracknell United States of America NASA Langley Research Centre, Virginia

NCDC, Asheville, North Carolina

Data for the former Union of Soviet Socialist Republics (USSR) have been provided by the World Radiation Data Centre, St Petersburg, Russia; all the countries of the former USSR are not listed, only Russia.

The Test Reference Years (TRY) were kindly supplied by Institut Royal Météorologique de Bel-gique (Uccle), Irish Meteorological Service (Dublin), Hungarian Meteorological Service (Budapest), Greek National Observatory (Athens), Deutscher Wetterdienst (Freiburg). The Design Reference Year (DRY) for St. Petersburg and Copenhagen as well as the Biomass Reference Years (BRY) were com-piled during the realisation of this Atlas.

Digital information on terrain elevation were taken from the ETOPO5 digital terrain model, freely available from the National Centre of Atmospheric Research (NCAR), Boulder, Co., USA. Coastlines, water bodies, and borders originated from the Defence Mapping Agency (USA). All this information was corrected for Europe during the realisation of the Atlas, using the maps published by Institut Géographi-que National (France) and other geographical atlases.

Names of countries originated from the CD-ROM GEOname digital gazetteer, from GDE Systems, Inc., USA.

5.5 Data guarantee

The database was subjected to quality control procedures. These checking procedures enabled a num-ber of data errors to be corrected. While checks have been applied in the development of the database,


52

neither the European Commission, nor the institutions responsible for the realisation of the Atlas, nor the publisher can accept any guarantee or any liability arising from potential defects in the data given in this publication or on the CD-ROM (the European Solar Radiation Atlas, vol. 2). Users must therefore make their own judgements on the reliability of any data provided in this publication and on the CD-ROM (the European Solar Radiation Atlas, vol. 2).

A complete list of station data available in the database is compiled in Annex 2.

5.6 Maps of solar radiation components

The database comprises digital maps of solar radiation components. That means for each pixel (ap-proximate size: 10 km) within the whole geographical area covered by this Atlas, values of solar radia-tion components are available. These maps are ten-years averages of monthly means of daily sums of global irradiation on horizontal plane, of its diffuse and direct components and of the clearness index.

The maps have been constructed taking advantage of both kinds of data. Ground measurements and satellite observations have been combined to provide an unique set of consistent information on solar radiation, thus enhancing the quality of the predicted spatial distribution of the solar radiation, com-pared with pure interpolation between ground measurements.

Co-kriging technique was used for merging both types of data. The two datasets were subjected to separate processing to prepare them for application within the co-kriging technique.

In brief, this technique is a linear interpolation technique, making use of weights which are defined according to the effective distance between the location under concern and the neighbouring WMO stations. The definition of these weights takes into account the structure of the spatial correlation of the latitude-free clearness indices computed on the one hand from the observations made by the WMO network, and on the other hand from the satellite dataset, as well as of the cross-correlation between both datasets. This procedure is fully described in detail and justified in Beyer et al. (1997). This procedure provided maps of the ten-years average of the monthly means of clearness index for the whole area. From these twelve maps, a yearly mean was computed.

Starting from these 12 maps of clearness index, the twelve maps for the monthly means of daily sums of global irradiation on the horizontal plane, as well as the yearly mean, were computed. Maps are made up of pixels. Each pixel is coded on one byte, that is it can only take values in the range of 0 to 255. The irradiations were converted into bytes. It follows from this digitisation that there is an uncertainty of 25 Wh m-2 in the reading of the value of any pixel on the map.

The maps for the diffuse component were calculated by using the appropriate algorithm

with KT from the clearness index maps and C0, C1, C2 calculated with a regression process for three latitude bands and for four seasons using measured diffuse irradiation values.

This algorithm was applied on the maps of global irradiation and clearness index. The uncertainty factor for the global radiation and beam radiation maps is 25 Wh m-2. Twelve monthly maps plus the yearly average were thus constructed.

Finally, the direct component was mapped by calculating the difference between the global and the diffuse component for each pixel. Again, thirteen maps were made, including the yearly mean. The uncertainty factor is 50 Wh m-2

These results are stored for each pixel in the database.

3md3

2md2md10 )(KTC )(KTC )(KTC C

)()( +++=

md

md

GD


53

5.7 Zones of similar irradiation climates

The irradiation maps give a pattern with high resolution in space from which the user can extract eas-ily the monthly mean of daily sums of global, diffuse and direct irradiation in time as an average over the ten Reference Years 1981 – 1990. Due to this averaging the fine structure of irradiation is not available for each pixel but the user is referred to the geographically nearest ground measuring station where long-term measuring series are available.

Nevertheless each station exhibits to its own specific microclimate. The nearest station may not be representative of the site selected by the user.

To overcome this situation, 20 zones have been defined, within which the average variation of the yearly mean of the clearness index KT is small. Then one or more stations were selected which ex-hibit the best agreement with the zones average KT as representative station of each zone.

The long-term measured series of these representative stations are considered to be the best choice for a user, who wishes to link his selected site to the available long-term measurements.

Nevertheless, the reference station values are not identical with the selected site, but a simple pro-portionality relationship can be used for fine structure studies. The proportionality factor can be calcu-lated using the relation of the monthly mean KT of the reference station KTm, ref.st. and the site KTm

site. Thus the irradiation at any time at the site can be approximated by

(5.7.1) Now, G(t)site could be Gd, site, Gh, site and similar for D(t) and B(t). For further details please consult

the ESRA User Guidebook (the European Solar Radiation Atlas, vol. 2).

5.8 Zones of similar biomass parameters

Both, solar radiation and other meteorological parameters are important in biomass productivity. Monthly means of daily sums of global irradiation, mean temperature and daily temperature variation and precipitation have been calculated from 503 measuring stations.

Nineteen zones of similar biomass climate (‘biomass zones’) have been defined. A clustering procedure similar as for the zoning of the clearness index was used. The parameters used in the clustering procedure (Tmean, Tmax - Tmin,), global irradiation and precipitation are uncorrelated as far as possible.

Biomass production in most cases is influenced in the same direction by high temperatures, high global irradiation and (sufficient) high precipitation. However there are crop-specific threshold values or non-linearities for all three parameters. The same applies to many other problems, for which these daily data could be useful.

The clustering procedure was run for the full year, for the growing season (April through September) and for the heating season (October through March). However, the length of the growing season depends on crop types. Furthermore both seasons are latitude dependent. However the clustering procedure was forced to use constant length for both seasons for all stations.

The result is a map of zones of similar biomass parameters which can be displayed and scrutinised from the CD-ROM (the European Solar Radiation Atlas, vol. 2). The limits should be considered with care.

One or more measuring stations were selected as representative of each of these zones. For these stations, daily values for mean, maximum and minimum temperatures, daily sums of precipitation,

site, m

st ref. m,ref.st.

.ref.stm

site m,site

KT G(t)

G

)(KTG

tG ⋅⋅≅


54

atmospheric pressure, water vapour pressure and global irradiation are available from the database on CD-ROM.

5.9 Test, Design and Biomass Reference Years

Test reference years (TRY), design reference years (DRY) and biomass reference years (BRY) are special time-series of meteorological and radiation parameters, extracted from continuous observations spanning over ten or more years.

TRYs and DRYs are made up of hourly values of several parameters using twelve months selected from different years. These reference years are "typical" years, which means that every month is se-lected, according to criteria based on the statistical distribution of the important parameters. For exam-ple, the ‘Danish’ method used in some countries for the generation of the test reference years is based on minimal departures of monthly means and monthly standard deviations of daily mean temperature, daily maximum temperature, and daily sums of global irradiation from the long term series values in each month, using at least 10 years data. This mathematical selection is combined with a more general climatological evaluation incorporating 10 - 20 parameters.

The main reason for constructing a reference year for a particular site is to give industrial engineers, consultants, architects, and research institutions a standardised set of climate data to be used as input data for computer simulations of complicated systems needing more than one climate parameter, and nor-mally also containing non-linearities. Reference years with hourly data are often used for calculations of indoor climate, building energy consumption or energy conservation measures; however many other uses have been observed.

Such reference years describe a typical year. They are not suitable for tasks for which weather ex-tremes occurring with frequencies less than once per year are required.

BRYs are made up of time-series of daily values for a year assembled of twelve months out of ten or more years or for ten or more consecutive years. They can be used for computer simulations, where daily data are sufficient. BRYs have been developed for five stations only for this Atlas. For the multi-year BRYs each month has been ranked using four parameters: daily sum of global irradiation and of precipi-tation, daily mean temperature and relative humidity.

THE SOLAR RADIATION ATLAS – 6 The ESRA software package

55

6 The ESRA software package (The European Solar Radiation Atlas, vol. 2: database and exploitation software, CD-Rom and guidebook)

6.1 The CD-ROM: necessary requirements and content

6.1.1 Computational resource requirements

The complete ESRA software package is available on CD-ROM. It works on personal computers un-der Windows® 95. The following hardware is necessary:

• PC-compatible (at least 486-DX2-66, preferred Pentium 120) • SVGA display (at least 800 x 600, 256 colours, preferred 1024 x 768 and 64 k colours), • CD-ROM drive (at least speed = x 4, preferably x 8) Necessary software: • Windows 95 (not installable on Windows 3.1x, nor Windows NT)

The complete user instruction is integrated in Chapter 4 of the User’s Guidebook.

6.1.2 Content of the CD-ROM

The main contents of the CD-ROM are:

• The map data base, consisting of the geographical and solar irradiation mapping data, • The solar and meteorological data from ground measuring stations, • the algorithmic chains, • the application models, • the output programme which generates maps, charts and tables from the database and initiates cal-

culations run with inputs from the data base.

The computional chains are explained in the Chapter “ESRA in a nutshell”.

These elements are accessible under the following operational modes using the relevant sub-menus:

• the map mode allows the user to visualise the maps from the data base, • the station mode allows the user to consult data from measuring stations integrated in the data base,

THE SOLAR RADIATION ATLAS – 6 The ESRA software package 56

• the sub-menu data base allows the user to visualise measured climatolotical data for any selected site with data,

• the sub-menu calculation produces derived data with the help of the integrated algorithmic chains, • the sub-menu applications permits the calculation of the impacts of sun radiation on water heater,

PV-system and passive solar building performance, • the sub-menu draw allows the production of diagrams and spread-sheets with data from the data-

base or calculated by the calculation sub-menu.

6.2 The map mode

The map mode is used to view maps from the data base on the computer screen. As an example, Fig. 6.2.1 shows the direct solar irradiation on horizontal plane over the mapped area. This map in reality , in computational terms, is composed of the solar direct irradiation map of June with an overlay, show-ing frontiers, oceans and other water bodies. The irradiation values are suppressed over the water bod-ies. However, the irradiation information over the water is available as is shown in Fig. 6.2.2. This presents the complete irradiation pattern, covering the whole geographical area. Nevertheless, it is difficult to work with such a map unless further information and orientation aids are integrated. It should be noted, that in Fig. 6.2.1 the computer screen does not show the entire geographical zone.

Fig. 6.2.1 Example of a map : average daily direct irradiation over Europe in June. Access to the whole mapped area is ob-tained by scrolling the map using the scroll bars.


57

The integrated colour-bar with gradation indicates visually the intensity of irradiation. The mouse pointer can be used for precise information – in our example, it is located at 53° 0´ N and 13° 20´ E where the June average for direct irradiation is 2,025 Wh m-2 . For a selected site at 43° 40´ N and 6° 55´ E the closest ground measuring station which is available from the database is Nice at 43° 39 N and 7° 12´E.

Similar maps can be produced for the following quantities:

• 10 year monthly daily means of global, diffuse and direct irradiation on horizontal plane and for the monthly mean clearness index KT, one map per month plus the yearly average,

• countries, relief, measuring stations, solar radiation zones, biomass zones and two maps of global irradiation from the Upper Rhine valley with high precision information.

The daily irradiation information is given in steps of 50 Wh m-2 for global and direct irradiation and 25 Wh m-2 for diffuse irradiation.

Fig. 6.2.2 Average daily direct irradiation in June over the area covered by the Atlas

The following options exist within the map mode: • Draw: this option allows the user to draw diagrams of available parameters over the day, the

month and the whole year for a selected site. Figure 6.2.3 gives an example.


Fig. 6.2.3 10 year mean hourly global irradiation on a South oriented plane with 50° tilt for a site at 50° 15´and 7° 4´ calcu-lated with chain 3 from monthly averages

• Calculation: Starting from the parameters displayed on the map for a selected site, derived values can be calculated. As the irradiation maps in the data base can provide only daily means of monthly averages as input parameters, only Chain 3 can be used. This generates monthly average daily mean profiles of hourly direct, sky diffuse, ground reflected diffuse and global irradiation as well as the respective daily sums (see Fig. 6.2.4). If the Linke turbidity factor is available for the site, monthly average daily mean profiles of hourly direct, sky diffuse and ground reflected diffuse and global irradiation under cloudless sky as well as the respective daily sums may be calculated using Chain 5. Fig. 6.2.5 shows an example, where the default values of the CD-ROM have been used where the Linke turbidity factor TLK has been set at a constant value of 3.0 for all months.

Monthly Averages (1981-1990) Hourly and Daily Irradiations (Azim: 0°/Tilt: 50°)

Global Irradiation

03

69

12 06

1218

240

0.10.20.30.40.50.6

Months (50°15' / 7°4' / from map)

Hours

KWh/m²


59

Fig. 6.2.4 10 year mean hourly irradiation in January on a south-oriented flat plate collector with a 50° tilt at a location of 50° 15´ N and 7° 4´ E. Ground albedo 0.2.

Fig. 6.2.5 Mid month hourly clear sky irradiation on a south-facing, 50° tilted flat plate collector in January with TLK = 3.0. Ground albedo = 0.2

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0 3 6 9 12 15 18 21 24

kWh/

m²

(Az

im: 0

° / T

ilt: 5

0°)

Hours (50°15' / 7°4' / from map)

Monthly average Hourly and Daily clear sky Irradiation (M=January)

GlobalDirect

DiffuseReflected

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

0 3 6 9 12 15 18 21 24

kWh/

m²

(Az

im: 0

° / T

ilt: 5

0°)

Hours (50°15' / 7°4' / from map)

Monthly Averages (1981-1990) Hourly and Daily Irradiations (M=January)

GlobalDirect

DiffuseReflected


• Application: makes use of simple model calculation for solar hot water heaters, PV-generators and

passive solar buildings. • Animation: shows a movie of the twelve monthly maps in sequence • Copy: allows the displayed maps, graphs and tables to be into the Windows-Clipboard. The graphs

and maps these can be printed with the “draw”-option.

6.3 Station mode

In order to obtain data from a specific station, it is possible to start in the map mode and select – as indicated in Fig. 6.2.1 the indicated “nearest” station. It should be noted that in all these cases this is the geographically nearest station. In contrast, when working with zones or biomass zone maps, the indicated station is not the geographically nearest site but the most representative site for that specific zone. Alternatively, a station can be selected from the station list of Annex 2 using the station name or the station’s WMO number.

The station mode supplies data as represented in Figure 6.3.1 The tabulated data of the station can be visualised on the screen in addition to the identification pa-

rameters of the station.

Fig. 6.3.1 Typical display for a ground measuring station when working under station mode, with sub-menu Database and option daily


61

6.4 Sub-menus and examples

Certain of sub-menus allow the user to work with daily irradiation data for some 89 stations:

• Data base sub-menu is used to visualise the data available in the data base for the identified station on the screen. With help of the following options specific parts of the data set in the data base can be selected:

• climatological data set: 10 year monthly mean observed data (1981 – 1990) in all stations (see Fig. 6.4.1)

• monthly data set: monthly sums of sunshine duration in the period 1981 - 1990 (all stations) • daily data set: long-term series of daily observed values of meteorological parameters in the

period 1981 - 1990 (89 representative stations) • hourly data set: long-term series of hourly observed values of meteorological values (only few

stations) • half-hourly data set: long-term chains of half-hourly averages of irradiation and sunshine dura-

tion (only one station: UCCLE).

Fig. 6.4.1 Climatological means of monthly means in the period 1981 - 90 in Uccle.

• Calculation: This sub-menu is the interface to the ten algorithmic chains as described earlier and can be applied to map data as well as to station data, but is dependent on the availability of the nec-essary inputs for individual algorithmic chains. The following options are available under this sub-menu:


• options: permits the choice of site input data defined by the user for blackbox calculations (tilt, azimuth, etc....) also allows for adjustment of Linke turbidity factor and ground albedo

• solar irradiation: calls in Chain 1 for generation of hourly and daily mean irradiation values or Chain 3 for monthly averaged daily mean profiles,

• clear sky irradiation: calls in Chain 5 for hourly and daily clear sky irradiation, • illuminance: calls in Chain 4 for hourly values, • sky downward longwave irradiation: calls in Chain 10 for monthly average, hourly and daily

longwave irradiation from the sky alone, • spectral irradiation: calls in Chain 6 for average spectral irradiance • temperature: calls in Chain 7 for calculation of hourly mean temperature values, • statistics: calls in Chain 8 and 9 for irradiance and illuminance probability and utilizability based

calculations • use your own data: permits the use of the blackbox chains with external input data supplied by

the user • radiation summary: permits the user to display the summary of horizontal surface irradiation pa-

rameters.

Fig. 6.4.2 – 6.4.8 show some examples.

Fig. 6.4.2 Day by day irradiation in January 1990 on a south-oriented flat plate solar collector with 50° tilt at Uccle (calcu-lated with chain 1). Note (H = 00 - 24) in the header indicates a daily sum has been extracted. Ground albedo 0.2

0

0.5

1

1.5

2

2.5

3

3.5

4

0 5 10 15 20 25 30

kWh/

m²

(Az

im: 0

° / T

ilt: 5

0°)

Days (50°48' / 4°21' / Uccle)

Hourly and Daily Irradiations (period 1/1990) (H=00-24 )

GlobalDirect

DiffuseReflected


63

Fig. 6.4.3 Monthly average hourly illuminance on a South-West oriented vertical window at Uccle in January presented as an average daily profile (calculated with chain 6) . The ground reflected component was calculated from a ground albedo of 0.2

0.23

0.232

0.234

0.236

0.238

0.24

0.242

0.244

0 3 6 9 12 15 18 21 24

kWh/

m²

(Az

im: 0

° / T

ilt: 5

0°)

Hours (50°48' / 4°21' / Uccle)

Monthly Average (1981-1990) Hourly and Daily sky downward long wave irradiation (M=January)

Global

Fig. 6.4.4 Monthly mean hourly long-wave irradiation from the sky alone in January on a 50° tilted collector at Uccle calcu-lated with chain 10

0

2

4

6

8

10

12

14

16

18

0 3 6 9 12 15 18 21 24

Klux

(A

zim

: 45°

/ Ti

lt: 9

0°)

Hours (50°48' / 4°21' / Uccle)

Monthly Average (1981-1990) Hourly and Daily Illuminances (M=January)

GlobalDirect

DiffuseReflected


Fig. 6.4.5 10 year monthly mean hourly temperature in January at Uccle calculated with chain 7

Fig. 6.4.6 10 year monthly mean daily global spectral irradiation in January at Ucle calculated with chain 6.(Horizontal surface is the only option).

0

0.2

0.4

0.6

0.8

1

1.2

1.4

400 500 600 700 800 900 1000

Wh/

m²/n

m

Nanometers (50°48' / 4°21' / Uccle)

Monthly Average Global Spectral Irradiation on Horizontal plane (M=January)

Global

1

1.5

2

2.5

3

3.5

4

4.5

5

0 3 6 9 12 15 18 21 24

°C

Hours (50°48' / 4°21' / Uccle)

Monthly Average (1981-1990) Hourly and Daily Ambient Temperatures (M=January)

Temperature


65

Fig.6.4.7 Summary of monthly irradiation data on horizontal plane for Uccle obtained by using “radiation summary” for the period 1981 - 90. Gmax is the absolute maximum daily irradiation in any month. Gmin is the absolute minimum daily irra-diation in any month.

Fig. 6.4.8 Summary of monthly solar data (normalised) from “radiation summary” in Uccle in the period 1981 - 90

0

2

4

6

8

10

12

0 1 2 3 4 5 6 7 8 9 10 11 12

kWh/

m²

Months (50°48' / 4°21' / Uccle)

Summary of solar data (From daily values) - Irradiation

GmeanGmaxGmin

G0Dmean

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0 1 2 3 4 5 6 7 8 9 10 11 12Months (50°48' / 4°21' / Uccle)

Summary of solar data (From daily values) on normalised values

G/G0KtmaxKtmin

D/GmeanS/S0


• Reference Years: is a sub-menu which allows the user to examine data from Reference Years. While data from Design Reference Years and Biomass Reference Years only can be visualised on the screen and transferred to the text editor for further use, the Test Reference Year data for Dublin airport, Uccle, Budapest, Athenai Observatory and St. Petersburg Observatory can be processed by the algorithmic chains, the application’s sub-menu and the draw sub-menu.

• Applications: is a sub-menu which allows the user to calculate the performance of some simple

types of solar applications. There are five system options:

• 1 - yearly energy output from a solar water heater • 2 - photovoltaic grid connected system • 3 - photovoltaic stand-alone system with batteries • 4 - daily energy output from a solar water heater • 5 - passive solar heating (direct gain) in buildings

Figure 6.4.9 gives the example of a PV stand-alone system with batteries and Fig. 6.4.10 for solar

gain in a passive solar house with one south-oriented window.

Fig. 6.4.9 Sizing of a stand-alone PV-system with battery. Design power output is 1 kWh per day with 24 volt and battery autonomy for 10 days without sunshine


67

The first line on the screen display shows the site coordinates and the orientation of the collector. The programme selects the monthly averages of daily sums of global irradiation for the site from the database. The next block in the table shows the monthly averages of the electric load, the desired autonomy and the voltage of the system. These are user inputs. The blackbox module sizes the system, i.e. the normalised PV-peak power and the battery capacity needed. In addition, the critical months for the panel sizing and the battery sizing are identified.

Fig. 6.4.10 Calculation of gross solar gains, gross space heating and consequent net space heating load for a building with vertical South double glazied windows at Uccle, Belgium. Heating period October through May.

The passive solar heating direct gain module calls in the necessary climate data of the site and the window orientation selected. The monthly mean daily solar irradiation on the window, and the mean maximum and minimum temperatures are extracted on a month by month basis. These values appear at the top of Figure 6.4.10. The user then enters the building parameters, and the heating period. The heating base temperature also has to be defined. In the evaluation, the number of degree days are es-timated and the gross heat load. The gross solar heat gain through the window is calculated using the window area and the transmission of the window type selected. The gross space heating load is calcu-lated and the net space heating load is found from the difference.


• Draw: This is a sub-menu which is used to plot data displayed as diagrams on the screen. Two op-

tions are available:

• draw 2D: under this option, two-dimensional diagrams are produced (Figures 6.4.2 – 6.4.8 are produced with this sub-menu).

• draw 3D: permits the production of three-dimensional graphs (see Fig. 6.2.3).

6.5 Further applications

The direct and well organised access to a large number of solar and meteorological data as well as to composed data sets (TRY, DRY, BRY) opens a wide potential of preparing input files for more com-plex applications. For instance, synthetic programmes as TRNSYS can be operated with site specific data sets which can be generated using the data files of the ESRA CD-ROM. Climatologists may profit from the systematically organised and quality controlled meteorological data sets as well as biologists, agronomists, town planners and landscape designers. Users of ESRA have at their disposal high quality long-term data sets as well as good coverage over large geographical areas from the solar maps.

This information will improve the quality of the prediction of direct or indirect solar impact as well for individual solar application as for large scale planning.

THE SOLAR RADIATION ATLAS – 7 Maps

69

7 Maps

7.1 The geographical area of the Atlas

Map 1 shows the geographical area of the Atlas in Albers-projection, with relief overlay and country borders.

7.2 Ground based measuring stations

Map 2 shows the measuring stations used in preparing this Atlas. Annex 2 gives a list with all neces-sary information.

7.3 Global solar irradiation (Ten year average)

Maps 3 to 6 show the monthly means of daily sums of global solar irradiation on horizontal plane for March, June, September and December. Map 7 gives the annual mean.

Maps 8 and 9 show an example of a high resolution digital map for monthly means of daily sums of global irradiation of the Upper Rhine Valley.

7.4 Diffuse solar irradiation (Ten year average)

Maps 10 – 13 show the monthly means of daily sums of diffuse irradiation on horizontal planes for March, June, September and December. Map 14 shows the ten annual means.

7.5 Direct (beam) solar irradiation (Ten year average)

Maps 15 – 18 show the monthly means of daily sums of direct solar irradiation on horizontal plane for March, June, September and December. Map 19 gives the annual mean.

THE SOLAR RADIATION ATLAS – 7 Maps

70

7.6 Clearness index (Ten year average)

Maps 20 – 23 show the monthly mean of daily sums of the clearness index for March, June, Septem-ber and December.

Map 24 gives the annual mean.

7.7 Zones of similar irradiation climates

Map 25 shows 20 zones with similar irradiation climates defined by cluster analysis.

7.8 Zones of similar biomass productivity parameters

Map 26 shows 19 zones of similar biomass productivity parameters.

THE SOLAR RADIATION ATLAS – References 71

References

Anonymous (1994). SRB (Surface Radiation Budget) dataset document. NASA Langley Research Center, Maryland, USA. R. Aguiar et al. (to be published), Book of Algorithms N. Asimakopoulos et al. (1996), European Daylighting Atlas. Published for the Commission of the European Communities

by National Observatory of Athens, Greece Atlas of hydrometeorological data (1991). Europe vol. 1. In Russian. Published by Army Publishing House, Moscow. 371p. Bayerisches Staatsministerium für Wirtschaft, Verkehr und Technologie (Pub.), Bayerischer Solar- und Windatlas (1995),

Bayerisches Staatsministerium für Wirtscahft, Verkehr und Technologie, Pringenregentenstraße 28, 80538 München Beyer H. G., Czeplak G., Terzenbach U. and Wald L. (1997). Assessment of the method used to construct clearness index

maps for the new European Solar Radiation Atlas (ESRA). Solar Energy, 61, 6, 389-397. B. Bourges (Ed.) (1992), Climatic Data Handbook for Europe. Climatic Data for the Design of Solar Energy Systems. Pub-

lished for the Commission of the European Communities. Kluwer Academic Publishers. Dordrecht/Boston/London Commission of the European Communities, European Solar Radiation Atlas (1984), Volume I, (2nd edition) F. Kasten, H.J.

Golchert, R. Dogniaux, M. Lemoine, Ed., W. Palz, Verlag TÜV Rheinland, Cologne Commission of the European Communities, European Solar Radiation Atlas (1997). W. Palz, J. Greif (Ed.), Springer Verlag

Berlin, Heidelberg, and New York ISBN 3-540-61179-7 Commission of the European Communities, Solar Radiation Atlas of Africa. E. Raschke, R. Stuhlmann, W. Palz and T.C.

Steemers (Ed.) (1991), A.A. Balkema/Rotterdam/Brookfield Diekmann, F.J. et al.: An operational estimate of global solar irradiance at ground level from METEOSAT data: results from

1985 to 1987, Meteorol. Rundschau 41, 65-79 (1988). ESRA - European Solar Radiation Atlas (1994), JOULE II project no. JOU2-CT-94-00305 Grüter W., Guillard H., Möser W., Monget J.-M., Palz W., Raschke E., Reinhardt R. E., Schwarzmann P. and Wald L.

(1986). Determination of solar radiation at ground level from images of the earth transmitted by meteorological satellites, Solar Energy R&D in the European Community, Series F, vol. 4: Solar radiation data from satellite images, D. Reidel Publishing Co. for the Commission of the European Communities, 100 p.

ISO, Solar Energy - Specification and classification of instruments for measuring hemispherical solar and direct solar radia-tion. Instrumental Standard ISO 9060. International Organisation for Standardization, Geneva, Switzerland (1990).

F. Kasten,and A.T.Young (1989), Revised optical air masstables and approximation formula. Appl. Optics 28, 4735-4738 9). Möser, W. and E.Raschke: Incident solar radiation over Europeestimated from METEOSAT data. (1984) Jour. of Climate

and Appl. Meteorology 23, 166-170. K. Scharmer et al. (1989), Solar European Microclimates. Final Report. EC-Contract no. EN3S-00490-D(B) Terzenbach, U.: Quality control algorithms on solar radiation data. Internal paper of ESRA Project No. JOU2-CT94-0305,

Task II Algorithms (1995). Treuberth, K.E., J.T.Houghton, L.G.Meira-Filho: The Climate System: an overwiew. Climate Change 1995: Contribution of

Working Group I to the Second Assesment of the Intergovernmental Panel on Climate Change, 58 (1996) WMO: Meteorological aspects of the utilization of solar radiation as an energy source. (1981) Geneva: Secretariat of the

World Meteorological Organization, Techn. Note No. 172; WMO-No. 557, 122

Annex 1 – Symbols and Definitions 73

Annex 1 Symbols and Definitions

A1.1 Introduction

During the second meeting of Task II Group (Lyon, 30th November) it was decided to elaborate a document containing the symbols and definitions necessary to the European Solar Radiation Atlas project. This proposal is based on previous work of European Community Experts, namely the work of Dogniaux et al. (1984). The structure of this reference is used here as the basis for the introduction of new proposals of symbols. The elaboration of this document is also based on proposals contained in other references, namely the previous version of the Solar Radiation Atlas, (1984), the list of symbols used within Eufrat Project (B.Bourges, 1992). Other sources are those from the list of symbols of the CIE, TC-4.2.Daylighting (Draft for discussion, Nov., 1986) and Daylighting in architecture. A European Reference Book (1993).

A1.2 Basic concepts and General Rules

Based on R.Dogniaux et al. (1984), some basic concepts and general rules are first established.

Basic concepts: • Solar radiation at the earth surface - radiation between 0.29µm and 4µm (corresponding to 99% of

the sun's radiation reaching the earth) • Terrestrial radiation - radiation above 4µm. • Radiance - radiant power per unit area per unit solid angle (steroradian) (Wsr-1m-2) • Irradiance - radiant power per unit area (Wm-2) • Irradiation - radiant energy per unit area (Wh m-2 or Jm-2)

For the terms Luminance and Illuminance see the definitions given in Daylighting in architecture. An European Reference Book (1993) General rules:

For radiance and luminance the symbol used is L with subscripts e and v, respectively. For

irradiance and illuminance the proposed symbols are listed below. Luminance values will always have the subscript v. • G - global irradiance or illuminance values • D - diffuse irradiance or illuminance values (diffuse component of solar radiation) • I - normal direct irradiance or illuminance values (normal beam component of solar radiation)


• B - direct irradiance or illuminance values (beam component of solar radiation) • R - reflected irradiance or illuminance values

Symbols used for irradiance, irradiation and illuminance are all referred to horizontal planes except in the case of symbol I for normal direct irradiance. For tilted planes azimuth and slope are indicated in brackets, e.g. • G - Global irradiance on the horizontal plane • G(β,α) - Global irradiance on a plane of azimuth α and slope β

Letter I is also used for irradiance on a solar collector, which is calculated based on the beam, diffuse and reflected components of solar radiation, with expressions depending on collector type (see e.g. Rabl (1985)). Symbols specifically referred to collector performance are listed in a separate table (see Table A1.3.4). The basic time intervals to which the irradiation values refer are identified by the following subscripts: h hourly values d daily values m mean monthly values When these subscripts are used in combination, a bracket is used, e.g. (Gd)m will stand for monthly mean daily horizontal global irradiation. Other subscripts used are: 0 extraterrestrial or astronomical values g ground related values c clear sky (i.e. cloudless sky) values b overcast sky values max maximum value of some quantity min minimum value of some quantity This way of indicating time scales and averages was adopted also in view of the ability to provide a clear translation to constant, parameter and variable names used in computer programming. Superscript * is used to indicate radiation threshold levels and angles related to points on the the sky dome. This description of the system used for symbols and nomenclature, as well as the listing provided in the following tables, are however not exhaustive. In particular contexts other symbols have been formed which are defined locally in the texts produced.


A1.3 Definitions

Table A1.3.1. Angles (rad.)

Symbol Definition j' Day angle, i.e. day in the year expressed as an angle from the start of the year α Azimuth angle of a plane, i.e. the angle between the projection of the normal on the

horizontal and true south (in northern hemisphere) or true north (in southern hemisphere). East negative. West positive

α* Sky point azimuth. Measured from due south in northern hemisphere north (in southern hemisphere. East negative. West positive)

αs Solar azimuth. Measured from due south in northern hemisphere: west from south positive, east from south negative

αF Wall solar azimuth angle, i.e. the angle between the vertical plane containing the normal to the surface and the vertical plane passing through the centre of the solar disk

β Inclination angle of a plane with respect to the horizontal plane γ* Sky point elevation i.e. altitude angle above horizon of a point in the hemisphere γ*

vert Vertical shadow angle, also called vertical profile angle γs Solar elevation i.e. altitude angle above horizon δ Solar declination i.e. the angle between the sun's rays and the equatorial plane. Positive

in northen hemisphere summer ζs Solar zenith angle i.e. angle between the vertical and the centre of the sun's disc: π/2 -

γs ζ* Sky point zenith angle i.e. angle between vertical and the point in the hemisphere: π/2 -

γ∗ θ(β,α) Angle of incidence between the sun's rays and an inclined plane

with azimuth α and inclination β λ Longitude (sign convention East of Greenwich positive) φ Latitude (sign convention North of Equator positive) ω Solar hour angle. Measured from solar noon: p.m. is positive ωs Sunset hour angle (-ωs: sunrise hour angle)


Table A1.3.2. Radiation related quantities with dimensions

Symbol Definition Unit

AT Thermal amplitude of ambient temperature for a certain day °C (AT)m Monthly average thermal amplitude °C B Direct irradiance, i.e. direct solar irradiance on the horizontal B = I cos ζs Wm-2 Bc Clear sky direct irradiance Wm-2 Bch Hourly clear sky direct irradiation Wh m-2 Bcd Daily clear sky direct irradiation Wh m-2 Bd Daily direct irradiation, i.e. daily integral of direct irradiance Wh m-2 (Bd)m Monthly mean daily direct irradiation Wh m-2 Bh Hourly direct irradiation, i.e. hourly integral of direct irradiance Wh m-2 (Bh)m Monthly mean hourly beam irradiation Wh m-2 (B(t))m Monthly mean beam irradiance at time t Wm-2 Bv Illuminance from direct sunlight on a given surface lux D Diffuse irradiance, i.e. irradiance from the sky on the horizontal Wm-2 Db Overcast sky diffuse irradiance Wm-2 Dbh Hourly overcast sky diffuse irradiation Wh m-2 Dbd Daily overcast sky diffuse irradiation Wh m-2 Dc Clear sky diffuse irradiance Wm-2 Dch Hourly clear sky diffuse irradiation Wh m-2 Dcd Daily clear sky diffuse irradiation Wh m-2 Dd Daily sky diffuse irradiation, i.e. daily integral of irradiance from the sky Wh m-2 (Dd)m Monthly mean daily sky diffuse irradiation Wh m-2 Dh Hourly diffuse irradiation, i.e. hourly integral of irradiance from the sky Wh m-2 (Dh)m Monthly mean hourly diffuse irradiation from the sky Wh m-2 (D(t))m Monthly mean diffuse irradiance received from sky at time t Wm-2 Dv Diffuse illuminance on a given surface lux E(λ) Spectral irradiance, i.e. irradiance (direct, diffuse or global) per unit band width centered

at a wavelength λ Wm-2nm-1

G Global irradiance: sum of diffuse and direct irradiance Wm-2 Gb Overcast sky global (=diffuse) irradiance Wm-2 Gc Clear sky global irradiance Wm-2 Gch Hourly clear sky global irradiation Wh m-2 Gcd Daily clear sky global irradiation Wh m-2 Gd Daily global irradiation, i.e. daily integral of global irradiance Wh m-2 (Gd)m Mean monthly daily global irradiation Wh m-2 Gh Hourly global irradiation, i.e. hourly integral of global irradiance Wh m-2 (Gh)m Monthly mean hourly global irradiation from the sky Wh m-2 (G(t))m Monthly mean global irradiance received from sky at time t Wm-2 Gv Global illuminance on a given surface lux Gvb Illuminance from an unobstructed overcast sky on a given surface lux Gvc Illuminance from an unobstructed cloudless sky on a given surface lux

G0 Solar constant, i.e. annual mean value of the extraterrestrial irradiance normal to beam (1367 W.m-2)

Wm-2

G0d Daily extraterrestrial global irradiation on a horizontal plane Wh m-2 (G0d)m Monthly mean daily extraterrestrial global irradiation on a horizontal plane Wh m-2 I Normal direct irradiance, i.e. direct solar irradiance normal to beam Wm-2 Ic Clear sky direct irradiance normal to beam Wm-2 Ich Clear sky hourly direct irradiation normal to beam Wm-2 Icd Clear sky daily irradiance normal to beam Wm-2


Table A1.3.2 Cont´d Radiation related quantities with dimensions

Symbol Definition Unit Id Daily normal direct irradiation Wh m-2 (Id)m Monthly mean daily normal direct irradiation Wh m-2 Ih Hourly normal direct irradiation Wh m-2 (Ih)m Monthly mean daily extraterrestrial global irradiation on a horizontal plane Wh m-2 (I(t))m Monthly mean direct irradiance normal to the beam at time t Wm-2 K0 Luminous efficacy of extraterrestrial radiation lm W-1 K Luminous efficacy of global radiation lm W-1 Kb Luminous efficacy of beam radiation lm W-1 Kg Luminous efficacy of ground reflected diffuse radiation lm W-1 Ksky Luminous efficacy of sky diffuse radiation lm W-1 L Terrestrial irradiance, i.e. long-wave radiation of terrestrial origin Wm-2 L↓ Incoming terrestrial irradiance from the sky, i.e. long wave radiation from the atmosphere

falling on a horizontal surface Wm-2

L↑ Outgoing terrestrial irradiance, from the ground towards the sky, i.e. long wave radiation from a horizontal surface emitted upwards towards the atmosphere

Wm-2

Lsky (β,α) Incoming terrestrial irradiance emitted from the sky falling on an inclined surface of tilt β and azimuth α

Wm-2

Lg↑(β,α) Terrestrial irradiance emitted from the ground and sky obstructing surfaces falling on an

inclined surface of tilt β and azimuth α Wm-2

L* Net longwave balance on horizontal surfaces (L↓ - L↑) Wm-2 Le Radiance Wsr-1m-2 Le(ζ*,ϕ*) Radiance of a sky element at zenith angle ζ* and azimuth ϕ* Wsr-1m-2 Lv Luminance cd m-2 Lv(ζ*,ϕ*) Luminance of a sky element at zenith angle ζ* and azimuth ϕ* cd m-2 N Cloud amount okta Rg(β,α) Reflected diffuse irradiance from the ground (reaching an inclined surface) Wm-2 Rgd(β,α) Daily ground reflected diffuse irradiation Wh m-2 Rgh(β,α) Hourly ground reflected diffuse irradiation Wh m-2 (Rg(β,α,t))m Monthly mean irradiance on a surface of tilt β and azimuth α at time t due to ground

reflected radiation Wm-2

(Rgh(β,α))m Monthly mean hourly irradiation on a surface tilt β and azimuth α due to ground reflected radiation

Wh m-2

Rv Reflected illuminance lux λ Radiation wavelength nm σSB Stephan-Boltzmann constant (5.67x 10-8 Wm-2 K-4) Wm-2 K-4


Table A1.3.3. Other quantities and functions with dimensions

Symbol Definition Unit

E Energy transfer over defined period Wh or J ET Equation of time used in conversion from LAT to LMT h j day number in year, i.e. Jan. 1st = 1, …, Feb. 1st =32, … Mar. 1st = 60 in non leap year, or

61 in leap year day

LAT Local apparent (solar) time h LMT Local mean (clock) time h M (no suffix) Mass kg M (w/suffix) Mass flow rate kg s-1 p Atmospheric pressure Pa p0 Mean atmospheric pressure at sea level Pa pw Partial vapour pressure Pa Sh Hourly sunshine duration, i.e. for a certain hour of the day, measured sunshine duration

for which direct irradiance exceeds a certain threshold Decimal h

Sd Daily sunshine duration, i.e. measured sunshine duration for which direct irradiance exceeds a certain threshold (this occurs in DRY´s and TRY´s)

h

S0h Astronomical hourly sunshine duration, i.e. normally 1 hour, except in the sunrise and sunset hour

h

S0d Astronomical daily sunshine duration or daylength, i.e. the time during which the solar elevation is positive (no correction for refraction is made)

h

S(0d)m Monthly mean astronomical daily sunshine duration, i.e. the monthly mean time between sunrise and sunset (no correction for refraction is made)

h

t Time in decimal hours, usually in LAT, except in some TRYs and DRYs h tmax Time of a maximum event in the day h tmin Time of a minimum event in the day h T Temperature (also referred as ambient or dry bulb temperature) °C Td Daily mean temperature °C Th Hourly mean temperature °C Thm(t) Monthly mean daily profile of temperature, i.e. value of the hourly mean monthly

temperature for time t. °C

Tm Monthly mean temperature °C Tmax Maximum temperature for a certain day °C (Tmax)m Monthly average of maximum daily temperatures °C Tmin Minimum temperature for a certain day °C (Tmin)m Monthly average of minimum daily temperatures °C v wind speed at measurement height (usually 10 m) ms-1 w Precipitable water content of the atmosphere kg m-2 W(x*) Available energy for threshold x* of parameter x Wh m-2 z Station height above sea level m


Table A1.3.4 Dimensionless quantities and functions

Symbol Definition

am, bm Angstrom regression coefficients (monthly basis) in Gd/G0d = am + bm (Sd/S0d) F(x < y) Distribution function for value y of parameter x (also referred as cumulative frequency curve) KTd Daily clearness index for global irradiation on a horizontal plane, i.e. Gd/G0d (KTd)m Monthly average daily clearness index for global irradiation on a horizontal plane, i.e. Gh/G0h KTh Hourly clearness index for global irradiation on a horizontal plane m or AM Relative optical air mass, i.e. the length of path through the atmosphere traversed by the direct solar

beam, expressed as a multiple of the path to a point at sea level with the sun at zenith (the latter is called AM 1, extraterrestrial is called AM 0).

n Fractional cloud amount ri(β) View fraction of the sky dome, i.e. the fraction of the sky dome that is viewed

by an inclined plane with tilt angle β rg(β) View fraction of the ground, i.e. the fraction of the ground that is viewed

by an inclined plane with tilt angle β TL(m) Linke turbidity factor. Ratio of the observed optical thickness of the atmosphere (due to scattering and

absorption) to the theoretical optical thickness of a dry and dust free Rayleigh clear sky at air mass m. Its value is dependent on the formula used to calculate the Rayleigh optical thickness.

TL Linke turbidity factor for AM 2 TLK Linke turbidity factor for AM 2, calculated using the Kasten formulation for the Rayleigh optical

thickness (TLK)m Monthly mean Linke turbidity factor for AM 2, calculated using the Kasten formulation for the Rayleigh

optical thickness βA Angstrom turbidity coefficient i.e. the spectral extinction coefficient of the atmosphere

due to gases and aerosol particles δR Rayleigh optical thickness

(of a dry and clean atmosphere when only Rayleigh scattering occurs) ε Sun-Earth distance correction factor εl Long wave emittance of a surface involved in long wave heat exchanges η Efficiency of a step or an overallprocess, used in conjunction with suffixes Φ(x*) Utilizability function for threshold x* of parameter x ρg Ground albedo, i.e. reflectivity of the ground for solar radiation σ Daily fraction of bright sunshine, Sd/S0d, also referred to as the sunshine fraction or the relative duration

of bright sunshine σm Monthly mean percentage of daily possible sunshine, often called monthly relative sunshine duration,

i.e. (Sm/(S0m) Φ(x*) Utilizability function, i.e. fraction of the total energy available above a defined reference threshold

radiation x*

Acknowledgements

In the 2nd draft important suggestions made by R. Dogniaux, B. Bourges and P. Littlefair were included. The 3rd, 4th and 5th drafts also included suggestions from J. Page and R. Aguiar.


References

C.E.C. European Solar Radiation Atlas (1984): Vols. I and II. EUR 9344 and 9345; Publisher: Verlag TUV Rheinland C.E.C. Climatic Data Handbook for Europe (1992): Climatic data for the design of solar energy systems. Edited by Bernard

Bourges, Kluwer Academic Publishers C.E.C. Daylighting in architecture (1993): A European reference book. Edited by N.Baker, A.Fanchiotti, K.Steemers, James

&James (Science Publishers) Ltd Guide on daylighting of building interiors, Part I. CIE, Technical Committee TC-4.2. Daylighting (1986): Draft for

discussion at the Second International Daylighting Conference, Long Beach, California, USA, November Dogniaux, R. et al. (1984): Solar Meteorology (Units and Symbols), recommendations by the solar energy R&D programme

of the European community. Int.Journal of Solar Energy, vol.2, page 249-255, 1984. Rabl, A. (1985): Active solar collectors and their applications. A. Rabl, Oxford University Press

Annex 2 – List of Stations

81

Annex 2 List of stations

This annex provides the list of ground-measuring stations whose data are published in the CD-ROM. The countries are ranking by alphabetic order, according to their names in English. Within a country, stations are ordered by their number in the list of the World Meteorological Organisation (WMO). The spelling of the names is similar to what appears onto the screen using the companion software. The selected font in this software is Arial, which is available in each PC. Accordingly, a limited number of characters are available, i.e. the English characters only.

For each station are given its WMO number, its name, its geographical co-ordinates (in hundredths of degrees) and elevation above mean sea level (in meters).

Some indicators provide information on the availability of data for each station. Under the heading ‘Daily values’:

• Gd stands for daily sums of global horizontal irradiation (units are Whm-2) • S stands for daily values of sunshine duration (unit is 0.1 h) • T stands for daily temperature and precipitation values

Under the heading ‘Month’:

• Sm stands for monthly means of sunshine duration (unit is 0.1 h) Under the heading ‘Ten-year average’:

• Gdm stands for ten-year averages of monthly means of daily sums of global irradiation (units are Whm-2)

• Sm stands for ten-year averages of monthly means of daily values of sunshine duration (unit is 0.1 h)

• Tm stands for ten-year averages of monthly means of daily values of minimum and maximum temperatures

• rrm stands for ten-year averages of monthly sum of precipitation • pm stands for ten-year averages of monthly means of daily values of air pressure • pwm stands for ten-year averages of monthly means of daily values of water vapour pressure

Table A2.1. List of the measuring stations included in the ESRA database

Daily values Month Ten-year average WMO

number Name of the station lat. lon. elev. Gd S T Sm Gdm Sm Tm rrm pm pwm

Austria 11013 Steyr 4807 1460 309 - - - x - - - - - - 11028 St. Poelten 4820 1562 272 - - - x x x x x x x 11035 Wien / Hohe Warte 4825 1637 203 x x x x x x x x x x 11036 Wien Schwechat Airport 4812 1657 183 - - - x - - x x - - 11037 Gross Enzersdorf 4820 1657 153 - - - x - - - - - -


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Table A2.1 Cont´d. List of the measuring stations included in the ESRA database



11150 Salzburg Airport 4780 1300 434 x x x x x x x x x x 11155 Feuerkogel 4782 1373 1618 - - - x x x x x - x 11212 Villacheralpe 4660 1367 2140 - - - x - - x x - x 11231 Klagenfurt 4665 1433 448 - - - x x x x x x x 11240 Graz-Thalerhof Airport 4698 1545 342 - - - x x x x x x x 11290 Graz Universitaet 4708 1545 366 - - - x - - - - - - 11320 Innsbruck Universitaet 4727 1138 577 - - - x x x - - - - Belarus 26850 Minsk 5387 2753 234 - - - x x x x x x x 33008 Brest 5212 2368 144 - - - x x x x x - - Belgium 06407 Oostende / Middelkerke 5120 287 5 - - - x x x x x - - 06428 Munte 5093 373 55 - - - x x x x x - - 06430 Melle 5098 383 17 - - - - x x - - - - 06432 Chievres 5057 383 63 - - - x x x x x - - 06447 Uccle 5080 435 100 x x x x x x x x x x 06448 Stabroek 5133 437 5 - - - x x x - - - - 06449 Gosselies 5047 445 187 - - - x x x x x - - 06454 Dourbes 10 436 240 - - - x x x - - - - 06457 Gembloux 5058 469 159 - - - x x x - - - - 06468 Gorsem 5083 518 39 - - - - x x - - - - 06476 St. Hubert 5003 540 556 - - - x x x x x - - 06478 Bierset 5063 545 191 - - - x x x x x - - 06479 Kleine Brogel 5117 547 65 - - - x x x x x - - 06485 Nadrin 5015 568 405 - - - - - - - - - - Bosnia-Herzegovina 13242 Banja Luka 4478 1722 153 - - - x x x x x - - 13354 Sarajevo 4382 1833 510 - - - x - - - - x x Bulgaria 15511 Lom 4382 2325 32 - - - x x x x x x x 15526 Pleven 4342 2457 64 - - - x x - x x - - 15552 Varna 4320 2792 41 - - - x x x x x x x 15613 Cherni Vrah 4258 2327 2286 - - - x x x - - - - 15614 Sofia Observatory 4282 2338 586 x - x x x x x x x x 15635 Chirpan 4220 2533 173 - - - x x - - - - - 15655 Burgas 4248 2748 16 - - - x - - x x x x 15712 Sandanski 4152 2327 206 - - - x - - x x - - Croatia 14216 Rijeka / Kozala 4533 1445 120 - - - x x x - - - - 14219 Parg 4560 1463 863 - - - x x x - - - - 14235 Puntijarka 4592 1597 988 - - - x x x - - - - 14236 Zagreb / Gric 4582 1598 157 - - - x x x - - - - 14240 Zagreb / Maksimir 4582 1603 123 x x x x x x - - - - 14246 Varazdin 4630 1638 167 - - - x x x - - - -


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14258 Daruvar 4560 1723 161 - - - x x x - - - - 14283 Osijek / Zeleno Polje 4553 1873 89 - - - x x x - - - - 14284 Pula 4487 1385 30 - - - x x x - - - - 14314 Mali Losinj 4453 1447 53 - - - x x x - - - - 14321 Rab 4475 1477 24 - - - x x x - - - - 14323 Senj 4498 1490 26 - - - x x x - - - - 14324 Zavizan 4482 1498 1594 - - - x x x - - - - 14328 Ogulin 4527 1523 328 - - - x x x - - - - 14330 Gospic 4455 1537 564 - - - x x x - - - - 14370 Slavonski Brod 4517 1800 88 - - - x x x - - - - 14428 Zadar / Puntamika 4413 1522 5 - - - x x x - - - - 14438 Sibenik 4373 1592 77 - - - x x x - - - - 14442 Knin 4403 1620 255 - - - x x x - - - - 14445 Split / Marjan 4352 1643 122 - - - x x x - - - - 14447 Hvar 4317 1645 20 - - - x x x - - - - 14452 Lastovo 4277 1690 186 - - - x x x - - - - 14472 Dubrovnik / Gorica 4265 1808 52 - - - x x x - - - - 14480 Sinj 4372 1667 308 - - - x x x - - - - 14481 Krizevci 4603 1655 155 - - - x x x - - - - Cyprus 17600 Acheila / Paphos 3473 3248 45 - - - x x x x x - - 17601 Akrotiri 3458 3298 23 - - - x x x x x - - 17607 Athalassa 3515 3340 162 - - - x x - - - - - 17609 Larnaca 3488 3363 2 - - - x x x x x x x Czech Republic 11406 Cheb 5008 1240 471 - - - x x x x x x x 11438 Tusimice 5038 1333 321 - - - x x x - - - - 11448 Plzen 4967 1328 364 - - - x - - x x - - 11457 Churanov 4907 1362 1122 x - x x x x x x - - 11487 Kocelovice 4947 1383 522 - - - x x x - - - - 11502 Usti n. Labem 5068 1403 376 - - - x x x - - - - 11518 Praha / Ruzyn 5010 1428 380 - - - x x x x x x x 11519 Praha / Karlov 5007 1442 262 x - x x x x - - - - 11520 Praha / Libus 5000 1445 303 - - - x x x x x x x 11603 Liberec 5077 1502 400 - - - x x x x x - - 11628 Kosetice 4953 1508 470 - - - x x - - - - - 11649 Hradec Kralove 5018 1583 285 - - - x x x - - - - 11683 Svratouch 4973 1603 737 - - - x x x - - - - 11698 Kucharovice 4888 1608 339 - - - x x x - - - - 11710 Luka 4965 1695 518 - - - x x x - - - - 11723 Brno / Turany 4915 1670 238 - - - x x x x x x x 11755 Straznice 4888 1732 187 - - - x x x - - - - 11782 Ostrava / Mosnov 4968 1812 256 - - - x x x x x x x 11790 Ostrava / Poruba 4980 1825 242 x - x x x x - - - - Denmark 06101 Toldboden / Kobenhavn 5568 1260 20 - - - x x x - - - - 06163 Risoe / Roskilde 5570 1208 2 - - - - x - - - - -


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06182 Taastrup / Kobenhavn 5567 1230 28 x x x x x x x x - - Eire 03952 Roches Point 5180 -825 40 - - - x x x x x x x 03953 Valentia Observatory 5193 -1025 9 x x x x x x x x x x 03955 Cork Airfield 5185 -848 153 - - - x x x x x x x 03957 Rosslare 5225 -633 23 - - - x x x x x x x 03960 Kilkenny 5267 -727 63 - - - x x x x x x x 03962 Shannon Airfield 5270 -892 14 - - - x x x x x x x 03964 Galway 5328 -902 18 - - - x x x - - x x 03965 Birr 5308 -788 70 - - - x x x x x x x 03967 Cascement Aerodrome 5330 -643 97 - - - x x x - - - - 03969 Dublin Airport 5343 -625 68 x x x x x x x x x x 03970 Claremorris 5372 -898 69 - - - x x x x x x x 03971 Mullingar 5353 -737 101 - - - x x x x x x x 03974 Clones 5418 -723 87 - - - x x x x x x x 03976 Belmullet 5423 -1000 9 - - - x x x x x x x 03980 Malin Head 5537 -733 20 - - - x x x x x x x Estonia 26038 Tallin 5942 2480 44 - - - x x x x x x x Finland 02805 Utsjoki Kevo 6975 2703 107 x - x x x x x x x x 02807 Ivalo 6862 2742 143 - - - x x x x x - - 02836 Sodankylae 6737 2665 179 - - - x x x x x x x 02864 Kemi 6578 2458 10 - - - x - - x x - - 02875 Oulu 6493 2537 12 - - - x x x x x x x 02897 Kajaani 6428 2768 132 - - - x x x x x x x 02903 Kruunupyy 6372 2315 24 - - - x x x x x - - 02910 Valassaaret 6343 2107 4 x - x x x x x x - - 02911 Vaasa 6305 2177 4 - - - x x x x x x x 02917 Kuopio 6302 2780 94 - - - x x x x x - - 02920 Ylistaro 6293 2250 26 - - - x x x - - - - 02929 Joensuu 6267 2963 116 - - - x x x x x x x 02935 Jyvaeskylae 6240 2568 141 - - - x x x x x x x 02944 Tampere-Pirkkala 6142 2358 112 - - - x x x x x - - 02952 Pori 6147 2180 13 - - - x x x x x - - 02958 Lappeenranta 6108 2815 105 - - - x x x x x x x 02963 Jokioinen 6082 2350 104 - - - x x x x x x x 02966 Utti Lentokenttae 6090 2693 99 - - - x x x x x - - 02970 Maarianhamina 6012 1990 4 - - - x x x x x - - 02972 Turku / Abo 6052 2227 49 - - - x x x x x x x 02974 Helsinki / Vantaan 6032 2497 51 x - x x x x x x x x 02976 Kotka Rankki 6037 2697 11 - - - x x x x x - - 02981 Korppoo Utue 5978 2138 9 - - - x x x x x - - France 07024 Cherbourg 4965 -147 139 - - - x x x x x x x 07027 Caen 4918 -45 78 - - - x x x x x - -


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07061 St. Quentin 4982 320 98 - - - x x x x x - - 07070 Reims 4930 403 95 - - - x x x x x - - 07110 Brest 4845 -442 99 - - - x x x x x x x 07130 Rennes 4807 -173 37 - - - x x x x x - - 07145 Trappes 4877 202 168 x - x x x - - - - - 07150 Paris le Bourget 4897 245 66 - - - x x x x x x x 07156 Paris Montsouris 4882 233 75 - - - x x x - - - - 07180 Nancy / Essy 4868 622 225 - - - x x x x x x x 07186 Phalsbourg 4877 730 377 - - - x - - - - - - 07190 Strasbourg 4855 763 153 - - - x x x x x x x 07197 Colmar 4792 740 211 - - - x x x x x - - 07221 Ile de Noirmoutier 4700 -233 2 - - - x - - - - - - 07222 Nantes 4717 -160 27 - - - x x x x x x x 07240 Tours 4745 72 108 - - - x x x x x - - 07255 Bourges 4707 237 161 x - - x x x x x x x 07265 Auxerre 4780 355 207 - - - x x x x x - - 07280 Dijon 4727 508 222 - - - x x x x x x x 07300 Saint Sauveur 4670 -233 32 - - - - - - x x - - 07306 La Roche sur Yon 4670 -138 90 - - - x x - - - - - 07315 La Rochelle 4615 -115 4 x - x x x - x x - - 07385 Macon 4630 480 221 - - - x x x x x - - 07434 Limoges 4587 118 396 - - - x x x x x x x 07460 Clermont Ferrand 4578 317 332 x - x x x x x x - - 07480 Lyon 4572 495 200 - - - x x x x x x x 07503 Biscarosse 4443 -125 33 - - - x x x - - - - 07510 Bordeaux / Merignac 4483 -70 49 x - x x x x x x x x 07517 Captieux 4418 -28 132 - - - x - - - - - - 07524 Agen 4418 60 61 - - - x x - x x - - 07558 Millau 4412 302 715 - - - x x - x x - - 07586 Carpentras 4408 505 99 - - - x x x - - - - 07591 Embrun 4457 650 871 - - - x x x x x - - 07610 Pau 4338 -42 188 - - - x x - x x - - 07630 Toulouse 4363 137 152 - - - x x x x x x x

07635 Carcassonne 4322 232 130 - - - x x x x x - - 07643 Montpellier 4358 397 5 - - - x x x x x - - 07645 Nimes 4387 440 60 - - - x x x x x x x 07650 Marignane 4345 523 6 - - - x x x x x x x 07678 Toulon / Ile du Levant 4303 647 110 - - - x x x - - - - 07690 Nice 4365 720 4 x - x x x x x x x x 07739 Odeillo 4248 212 1580 - - - x x - - - - - 07747 Perpignan 4273 287 43 x - x x x x x x x x 07761 Ajaccio 4192 880 6 - - - x x x x x x x Georgia 37549 Tbilisi 4168 4495 490 x x x x x x x x x x Germany 10015 Helgoland 5418 790 4 - - - x x x x x x x 10020 List / Sylt 5502 842 33 - - - x x x x x x x


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10033 Flensburg 5478 945 58 - - - x x x - - - - 10035 Schleswig 5453 955 59 x - x x x x x x x x 10040 Ploen 5417 1040 26 - - - x - - - - - - 10091 Arkona 5468 1343 42 - - - x x x x x - - 10113 Norderney 5372 715 29 - - - x x x x x - - 10141 Hamburg – Sasel 5365 1012 49 - - - x x x - - - - 10147 Hamburg Airport 5363 1000 14 - - - x x x x x x x 10161 Boltenhagen 5400 1120 15 - - - x x x x x - - 10162 Schwerin 5365 1138 59 - - - x x x x x - - 10166 Heiligendamm 5415 1185 21 - - - x x x - - - - 10170 Rostock – Warnemuende 5418 1208 4 - - - x x x x x x x 10177 Teterow 5377 1262 46 - - - x x x x x - - 10184 Greifswald 5410 1340 2 - - - x x x x x x x 10203 Emden Hafen 5335 720 5 - - - x x x x x x x 10224 Bremen 5305 880 24 - - - x x x x x - - 10261 Seehausen 5290 1173 21 - - - x x x x x - - 10270 Neuruppin 5290 1282 38 - - - x x x x x - - 10280 Neubrandenburg 5355 1320 73 - - - x x x x x - - 10289 Gruenow 5332 1393 55 - - - x x x - - - - 10291 Angermuende 5303 1400 56 - - - x x x x x - - 10313 Muenster 5195 758 60 - - - x x x - - x x 10317 Osnabrueck 5225 805 104 - - - x x x x x - - 10338 Hannover 5247 970 56 - - - x x x x x x x 10348 Braunschweig 5230 1045 83 x x x x x x x x - - 10361 Magdeburg 5212 1158 79 - - - x x x x x - - 10378 Potsdam 5237 1308 107 x - x x x x - - - - 10381 Berlin–Dahlem 5247 1330 51 - - - x x x x x x x 10384 Berlin–Tempelhof Airport 5247 1340 50 - - - x x x x x x x 10393 Lindenberg 5222 1412 98 - - - x x x x x x x 10406 Bocholt 5183 653 24 - - - x x x x x - - 10410 Essen 5140 697 152 - - - x x x x x x x 10411 Gelsenkirchen 5150 708 63 - - - x x x - - - - 10419 Luedenscheid 5122 763 465 - - - x - - - - - - 10430 Bad Lippspringe 5178 883 162 - - - x x x x x - - 10438 Kassel 5130 945 237 - - - x x x x x x x 10444 Goettingen 5155 995 175 - - - x - - x x - - 10449 Leinefelde 5140 1032 356 - - - x x x x x - - 10452 Braunlage 5173 1060 615 - - - x x x x x - - 10453 Brocken / Harz 5180 1062 1142 x - x x x x x x - - 10458 Harzgerode 5165 1113 404 - - - x x x - - - - 10460 Artern 5138 1130 164 - - - x x x x x - - 10466 Halle / Saale 5152 1195 96 - - - x x x - - - - 10469 Leipzig Airport 5142 1223 131 - - - x x x x x x x 10474 Wittenberg 5188 1265 105 - - - x x x x x - - 10480 Oschatz 5130 1310 150 - - - x x x - - - - 10486 Dresden – Wahnsdorf 5112 1368 246 x - x x x x - - - - 10488 Dresden Airport 5113 1378 222 - - - x x x x x x x 10496 Cottbus 5178 1432 69 - - - x x x - - - - 10499 Goerlitz 5117 1495 237 - - - x x x x x x x 10501 Aachen 5078 607 213 - - - x - - x x - -


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10517 Bonn – Friesdorf 5070 715 65 - - - x x x - - - - 10519 Bonn – Roleber 5073 720 160 - - - - - - - - - - 10532 Giessen 5058 870 201 - - - x x x x x - - 10548 Meiningen 5057 1038 450 - - - x x x x x x x 10552 Schmuecke 5065 1077 937 - - - x x x x x - - 10554 Erfurt Airport 5098 1097 312 - - - x x x x x x x 10555 Weimar 5098 1132 275 - - - x x x - - - - 10567 Gera / Leumnitz 5088 1213 311 - - - x x x x x - - 10577 Chemnitz 5080 1287 418 - - - x x x x x - - 10578 Fichtelberg 5043 1295 1219 - - - x x x x x - x 10582 Zinnwald 5073 1375 877 - - - x x x x x - - 10609 Trier 4975 667 278 - - - x x x x x x x 10628 Geisenheim 4998 795 111 - - - x x x - - x x 10637 Frankfurt am Main

Airport 5005 860 111 - - - x x x x x x x

10655 Wuerzburg 4977 997 275 - - - x x x x x - - 10671 Coburg 5028 1098 331 - - - x x x x x - - 10708 Saarbruecken 4922 712 325 - - - x x x x x - - 10729 Mannheim 4952 855 106 - - - x x x x x - - 10739 Stuttgart 4883 920 318 - - - x x x - - x x 10761 Weissenburg 4902 1097 428 - - - x x x x x - - 10763 Nuernberg 4950 1108 312 - - - x x x x x x x 10803 Freiburg 4800 785 308 x - x x x x x x x x 10863 Weihenstephan 4840 1170 472 x x x x x x - - - - 10866 Muenchen – Riem 4813 1170 530 - - - x x x x x x x 10893 Passau 4858 1347 412 - - - x x x x x x x 10929 Konstanz 4768 918 450 - - - x x x x x x x 10961 Zugspitze 4742 1098 2960 - - - x x x x x - x 10962 Hohenpeissenberg 4780 1102 990 x - x x x x x x - - Greece 16619 Trikkala 3955 2177 112 - - - x x x - - - - 16622 Thessaloniki 4052 2297 8 x - x x x x x x x x 16627 Alexandroupolis 4085 2592 7 - - - x x x x x - - 16641 Kerkyra 3962 1992 2 - - - x x x x x x x 16648 Larissa 3963 2242 73 - - - x x x x x x x 16654 Arta 3917 2100 10 x - x x x x - - - - 16674 Aliartos 3838 2310 110 - - - x x x - - - - 16682 Andravidha 3792 2128 17 - - - x x x x x - - 16690 Korinthos 3798 2273 12 - - - x x x - - - - 16701 Athinai / Filadelfia 3805 2307 136 - - - x - x - - - - 16714 Athinai / Observatory 3797 2372 107 - - - x x x - - x x 16716 Athinai / Helliniki 3790 2373 28 - - - x x x x x x x 16719 Zakynthos 3762 2090 8 - - - x - - - - x x 16723 Samos Airport 3770 2692 2 - - - x x x x x - - 16724 Argos / Pyrgela 3760 2278 100 - - - x x x - - - - 16726 Kalamata 3707 2202 6 - - - x x x - - x x 16732 Naxos 3710 2538 9 - - - x x x x x - - 16744 Santorini 3642 2543 40 - - - x x x - - - - 16746 Souda 3548 2412 146 - - - x x x x x x x


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16749 Rodos 3640 2808 4 - - - x x x x x - - 16754 Heraklion 3533 2518 37 x - x x x x x x x x 16759 Timbakion 3500 2475 7 - - - x x x - - - - Hungary 12772 Miskolc 4810 2078 233 - - - x - - x x x x 12805 Sopron 4768 1660 233 - - - x x x x x - - 12812 Szombathly 4727 1663 220 - - - x x x x x - - 12840 Budapest 4752 1903 118 - - - x x x - - x x 12843 Budapest / Lorinc 4743 1918 138 x - x x x x x x x x 12882 Debrecen 4748 2163 110 - - - x x x x x x x 12892 Nyiregyhaza 4802 2173 105 - - - x - - x x - - 12942 Pecs 4600 1823 202 - - - x x x x x x x 12975 Szarvas 4687 2053 85 - - - x x x - - - - 12982 Szeged 4625 2010 82 - - - x x x x x x x Iceland 04030 Reykjavik 6413 -2190 52 x x x x x x x x x x 04056 Hveravellir 6487 -1957 641 - - - x x x - - - - 04063 Akureyri 6568 -1808 23 - - - x x x x x x x 04099 Haganes 6558 -1707 280 - - - x x x - - - - Israel 40179 Bet Dagan 3200 3482 30 x x x x x x - - - - 40180 Tel Aviv Airport 3200 3490 40 - - - x x x x x x x 40184 Jerusalem 3178 3522 809 - - - x x x x x - x 40199 Eilat 2955 3495 12 - - - x - x x x - - Italy 16020 Bolzano 4647 1133 241 x x x x x x x x - - 16033 Dobbiaco 4673 1222 1222 - - - - - - x x - - 16045 Udine / Rivolto 4598 1303 51 - - - x x x x x x x 16052 Monte Pian Rosa 4593 770 3480 - - - x x x x x - - 16059 Torino / Caselle 4522 765 301 - - - x x - x x - - 16061 Torino / Bric della Croce 4503 773 709 - - - x - - x x - - 16064 Novara / Cameri 4552 867 178 - - - x - - - - x x 16067 Ispra 4582 860 200 - - - - x - - - - - 16072 Mt. Bisbino 4587 907 1319 - - - x - - x x - - 16080 Milano / Linate 4543 928 107 - - - x x - x x x x 16090 Verona / Villafranca 4538 1087 67 - - - - - - x x x x 16099 Treviso / San Angelo 4565 1218 18 - - - x - - - - x x 16105 Venezia / Tessera 4550 1233 2 - - - x x x x x x x 16110 Trieste 4565 1375 20 - - - x x x x x x x 16120 Genova / Sestri 4442 885 2 - - - x x x x x - - 16134 Monte Cimone 4420 1070 2173 - - - x x x x x - - 16140 Bologna / Borgopanigale 4453 1130 36 x x x x x x x x - - 16148 Cervia 4422 1230 6 - - - - - - - - - - 16149 Rimini 4403 1262 12 - - - x - - x x x x 16153 Capo Mele 4395 817 221 - - - x x x x x - - 16158 Pisa / Santo Giusto 4368 1038 6 - - - x x x x x x x


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16181 Perugia 4308 1250 208 - - - - - - x x - - 16191 Falconara Marittima 4362 1337 12 - - - x - - x x x x 16197 Elba / Monte Calamita 4273 1040 396 - - - x - - - - - - 16219 Monte Terminillo 4247 1298 1874 - - - x x x x x - - 16224 Vigna di Valle 4208 1222 266 - - - x x x - - - - 16230 Pescara 4243 1420 10 - - - x x x x x x x 16239 Roma / Ciampino 4180 1255 105 x x x x x x - - - - 16252 Campobasso 4157 1465 793 - - - x - - x x - - 16261 Foggia / Amendola 4153 1572 57 - - - x x x x x - - 16289 Napoli 4085 1430 88 - - - x x - x x x x 16310 Capo Palinuro 4002 1528 184 - - - x x x x x - - 16320 Brindisi 4065 1795 10 x x x x x x x x x x 16350 Crotone 3900 1707 155 - - - x x x x x - - 16362 Lamezia Terme 3890 1625 15 - - - x - - x x - - 16400 Isla Ustica 3870 1318 242 - - - x x x x x - - 16420 Messina 3820 1555 54 - - - x x x x x x x 16429 Trapani 3792 1250 7 - - - x x x x x x x 16453 Gela 3708 1422 11 - - - x x x x x - - 16470 Isla Pantelleria 3682 1197 191 - - - x x x x x - - 16480 Cozzo Spadaro 3668 1513 46 - - - - - - x x - - 16520 Alghero / Fertilia 4063 828 23 - - - x x x x x x x 16531 Olbia 4090 952 11 - - - x x - - - - - 16550 Capo Bellavista 3993 972 138 - - - - - - x x - - 16560 Cagliari / Elmas 3925 905 18 - - - x x x x x x x Jordania 40250 H-4 3250 3820 686 - - - x - - x x x x 40270 Amman Airport 3198 3598 767 - - - x - - x x x x 40310 Ma'an 3017 3578 1069 - - - x - - x x - x Kazakhstan 28952 Kustanaj 5322 6362 171 - - - x - - - - x x 35394 Karaganda 4980 7313 555 - - - x - - - - x x 35700 Gur'yev 4702 5185 0 - - - x x x x x x x 35796 Balhas 4690 7500 423 - - - x - - - - x x 35925 Sam 4542 5620 82 - - - x - - x x x x 38001 Fort Shevchenko 4455 5025 -20 - - - x - - x x x x Kuwait 40582 Kuwait Airport 2922 4798 55 - - - x - - - - x x Latvia 26422 Riga 5697 2407 3 - - - x x x x x - - Lebanon 40100 Beyrouth – Khaldé 3382 3548 29 - - - x - - - - x x Liechtenstein 06990 Vaduz 4713 952 460 - - - x x x x x - -


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Lithuania 26629 Kaunas 5488 2388 73 x - x x x x x x x x Luxembourg 06590 Luxembourg 4962 622 376 x x x x x x x x x x Macedonia 13583 Bitola 4105 2137 586 - - - x x x x x - - 13586 Skopje / Petrovac 4197 2165 238 - - - x - - x x x x Malta 16597 Luqa / Malta 3585 1448 91 - - - x x x x x x x Morroco 60101 Tanger 3573 -592 16 - - - x x x x x - - 60105 Larache 3518 -613 47 - - - x x x x x - - 60107 Al Hoceima 3518 -385 12 - - - x x x x x - - 60115 Oujda 3478 -193 465 - - - x x x x x - - 60120 Kenitra 3430 -660 5 - - - x x x - - - - 60127 Taza 3422 -400 509 - - - x x x x x - - 60135 Rabat-Sale 3405 -677 76 - - - x x x x x - - 60136 Sidi Slimane 3423 -605 52 - - - x x x - - - - 60141 Fes Sais 3397 -498 572 - - - x x x x x - - 60150 Meknes 3388 -553 549 - - - x x x - - - - 60155 Casablanca 3357 -767 57 x x x x x x x x - - 60156 Nouasseur 3337 -758 200 - - - x x x x x - - 60160 Ifrane 3350 -517 1664 - - - x x x - - - - 60165 El Jadida 3323 -852 270 - - - x x x - - - - 60178 Khouribga 3288 -690 771 - - - x - - - - - - 60185 Safi 3228 -923 45 - - - x x x x x - - 60190 Kasba Tadla 3253 -628 518 - - - x x x - - - - 60191 Beni Mellal 3237 -640 468 x x x x x x x x - - 60195 Midelt 3268 -473 1515 - - - x x x x x - - 60200 Bouarfa 3257 -195 1142 - - - x - - - - - - 60210 Rachidia 3193 -440 1037 - - - x - - x x - - 60220 Essaouira 3152 -978 7 - - - x x x x x - - 60230 Marrakech 3162 -803 464 - - - x x x x x - - 60250 Agadir 3038 -957 32 - - - x x x x x - - 60265 Ouarzazate 3093 -690 1136 - - - x x x x x - - 60285 Tan-Tan 2847 -1115 229 - - - x x x - - - - 60318 Tetouan 3558 -533 5 - - - x x x x x - - 60340 Nador 3515 -292 7 - - - x x x x x - - Netherlands 06211 Gemert 5155 568 0 - - - x x x - - - - 06212 Numansdorp 5173 443 0 - - - x x x - - - - 06213 Dedemsvaart 5260 647 10 - - - x x x - - - - 06214 Schiermonnikoog 5347 617 15 - - - x x x - - - - 06235 De Kooy 5292 478 0 x x x x x x x x - - 06240 Amsterdam / Schiphol 5230 477 -4 - - - x x x x x - -


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06260 De Bilt 5210 518 2 x x x x x x x x x x 06270 Leeuwarden 5322 575 0 - - - x x x x x - - 06275 Deelen 5207 588 50 - - - x x x x x - - 06280 Eelde 5313 658 4 - - - x x x x x - - 06290 Twente 5227 690 36 - - - x x x x x - - 06310 Vlissingen 5145 360 8 - - - x x x x x - - 06350 Gilze-Rijen 5157 493 11 - - - x x x x x - - 06380 Zuid / Limburg 5092 578 114 - - - x x x x x - - 06395 Harderwijk 5235 562 0 - - - x x x - - - - 06396 Ijmuiden 5247 463 0 - - - x x x - - - - 06397 Heel 5118 590 0 - - - x x x - - - - 06398 Scheveningen 5208 427 0 - - - x x x - - - - 06399 Tollebeck 5267 567 0 - - - x - - - - - - Norway 01316 Bergen 6040 532 41 x x x x x x - - x x Poland 12100 Kolobrzeg 5418 1558 3 - - - x x x x x - - 12145 Gdynia 5452 1855 22 x - x x x x - - - - 12195 Suwalki 5410 2295 193 - - - x x x x x - - 12230 Pila 5313 1675 72 - - - x x x x x - - 12280 Mikolaski 5378 2158 140 - - - x x x x x - - 12345 Kolo 5220 1867 116 - - - x x x x x - - 12372 Warszawa 5228 2097 98 x - x x x x - - - - 12415 Legnica 5120 1620 122 - - - x x x x x - - 12469 Sulejow 5135 1987 188 - - - x x x x x - - 12471 Belsk 5183 2080 180 - - - x x x - - - - 12491 Pulawy 5142 2195 147 - - - x x x - - - - 12595 Zamosc 5070 2325 211 - - - x x x x x - - 12600 Bielsko – Biala 4980 1900 398 - - - x x x x x - - 12625 Zakopane 4930 1995 857 x - x x x x x x - - 12690 Lesko 4947 2233 420 - - - x x x x x - - Portugal 08503 Corvo (Azores) 3967 -3112 28 - - - x - - - - - - 08506 Horta (Azores) 3852 -2863 60 - - - x - - - - x x 08511 Angra do Heroismo

(Azores) 3867 -2722 74 x - - x x x - - - -

08513 Ponta Delgada (Azores) 3775 -2567 35 - - - x x x - - x x 08522 Funchal (Madeira) 3263 -1690 58 - - - x - - - - x x 08535 Lisboa 3872 -915 77 - - - x x x - - x x 08546 Porto 4113 -860 93 x - x x x x - - x x 08549 Coimbra 4020 -842 141 - - - x x x x x x x 08554 Faro 3702 -797 7 - - - x x x x x x x 08557 Evora 3857 -790 309 x - x x x x x x x x 08568 Penhas Douradas 4042 -755 1380 - - - x x x - - - - 08570 Castelo Branco 3983 -748 386 - - - x - - - - - - 08575 Braganza 4180 -673 691 - - - x x x x x x x 08594 Sal 1673 -2295 54 - - - x - - - - x x


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Romania 15085 Bistrita 4713 2450 366 - - - x - - x x x x 15090 Iasi 4717 2763 102 - - - x x x x x x x 15120 Cluj / Napoka 4678 2357 410 x - x x x x x x x x 15247 Timisoara 4577 2125 86 - - - x x x x x x x 15260 Sibiu 4580 2415 443 - - - x - - x x x x 15310 Galati 4550 2802 71 - - - x x x x x - - 15360 Sulina 4515 2967 3 - - - x - - x x x - 15420 Bucuresti 4450 2613 90 - - - x x x x x - - 15450 Craiova 4423 2387 192 - - - x - - x x - - 15480 Constanta 4422 2863 13 x - x x x x x x - - Russia 20046 Polar GMO IM.E.T.

Krenkelja 8062 5805 20 - - - x x x - - x x

20069 Ostrov Vize 7950 7698 11 - - - x x x - - x x 20292 GMO IM.E.T. Fedorova 7772 10428 13 - - - x - - - - x x 20674 Ostrov Dikson 7350 8023 47 - - - x x x - - x x 20891 Khatanga 7198 10247 33 - - - x - x - - x x 22113 Murmansk 6897 3305 46 - - - x x x x x x x 22165 Kanin Nos 6865 4330 49 - - - x x x x x x x 22217 Kandalaksha 6713 3243 26 - - - x x x x x - - 22550 Arkhangel'sk 6458 4050 13 x x x x x x x x x x 22602 Reboly 6382 3082 181 - - - x x x x x x x 22837 Vytegra 6102 3645 59 - - - x x x x x x x 23205 Nar'jan / Mar 6765 5302 7 - - - x x x x x x x 23219 Khoseda Khard 6708 5938 84 - - - x x x x x x x 23330 Sale – Khard 6653 6653 35 - - - x x x - - x x 23418 Pechora 6512 5710 56 - - - x x x x x - - 23472 Turukhansk 6578 8795 32 - - - x - x - - x x 23552 Tarko – Sale 6492 7782 27 - - - x x - - - x x 23711 Troicko-Pecerskoe 6270 5620 107 - - - x x x x x - - 23724 Nyaksimvol 6243 6087 50 - - - x - - - - x x 23804 Syktyvkar 6167 5085 96 - - - x x x x x x x 23884 Bor 6160 9000 63 - - - x - x - - x x 23933 Khanty – Mansiysk 6097 6907 40 - - - x x x - - x x 26063 St. Petersburg

Observatory 5997 3030 4 x x x x x x x x x x

26477 Velikie Luki 5638 3060 98 - - - x x x x x x x 27037 Vologda 5928 3987 118 - - - x x x x x x x 27196 Kirov 5865 4962 164 - - - x x x x x x x 27595 Kazan 5578 4918 64 - - - x x x x x x x 27612 Moscwa 5575 3757 156 x - x x x x x x x x 27613 Moscwa University 5570 3750 192 - - - x x x - - - - 28225 Perm 5802 5630 161 - - - x x x x x x x 28275 Tobol'sk 5815 6818 44 - - - x x x - - x x 28440 Ekaterinsburg 5680 6063 237 - - - x x x - - x x 28698 Omsk 5493 7340 94 - - - x x x - - x x 28722 Ufa 5475 5600 197 - - - x x x x x - -


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28900 Samara 5325 5045 44 x x x x x x x x - - 34122 Voronez 5170 3917 164 - - - x x x x x x x 34172 Saratov 5157 4603 156 - - - x x x x x x x 34646 Volgodonsk 4773 4225 104 - - - x x x - - - - 34731 Rostov na Donu 4725 3982 77 - - - x - - x x x x 34824 Primorsko-Ahtarsk 4603 3815 5 - - - x x x x x - - 34880 Astrakhan 4627 4803 18 - - - x x x x x x x 35121 Orenburg 5175 5510 109 - - - x x x x x x x 35358 Turgay 4963 6350 123 - - - x - - - - x x 37050 Pyatigorsk 4405 4303 0 - - - x x x - - x x 37099 Sochi 4358 3972 0 - - - x x x - - - - Former Spanish Sahara 60033 El Aaiun 2717 -1322 64 - - - x x x - - - - 60060 Sidi Ifni 2937 -1018 50 - - - x x x x x - - 60096 Dakhla 2372 -1593 11 - - - x x x - - - - Saudi Arabia 40360 Guriat 3142 3727 509 - - - x - - - - x x 40362 Rafha 2963 4348 449 - - - x - - x x x x 40375 Tabuk 2837 3658 778 - - - x - - x x x x 40394 Hail 2743 4168 1015 - - - x - - x x x x 40400 Wejh 2623 3643 20 - - - x - - x x x x 40416 Dhahran 2627 5015 26 - - - x - - x x x x Slovakia 11816 Bratislava 4817 1712 292 x - x x x x x x - - 11858 Hurbanovo 4787 1820 119 - - - - x - x x - - 11903 Sliac 4863 1915 316 - - - x x x x x x x 11933 Strbske Pleso 4912 2008 1353 - - - x x x - - - - 11934 Poprad / Tatry 4907 2025 718 - - - x x x x x - x 11978 Trebisov 4867 2173 107 - - - x x - - - - - Slovenia 13015 Ljubljana / Bezigra 4607 1452 299 x - x x x x - - x x 13105 Portoroz 4552 1357 92 - - - x x x x x - - Spain 08001 La Coruna 4337 -842 58 - - - x x x x x x x 08015 Oviedo 4335 -587 335 x - x x x - x x - - 08023 Santander 4347 -382 64 - - - x x - x x - - 08025 Bilbao 4330 -293 40 - - - x - - x x - - 08042 Santiago / Labacolla 4290 -843 370 - - - x - - x x - - 08045 Vigo / Peinador 4222 -863 245 - - - x - - x x - - 08075 Burgos / Villafria 4237 -363 894 - - - x - - - - - - 08083 Logrono 4247 -238 364 - - - x x - - - - - 08130 Zamora 4150 -573 670 - - - x - - x x - - 08141 Valladolid 4165 -477 734 - - - x x x x x x x 08160 Zaragoza Airport 4167 -102 257 - - - x - - x x x x 08161 Zaragoza 4163 -90 221 - - - x - - - - x x


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08181 Barcelona Airport 4128 207 4 - - - x - - x x x x 08184 Gerona 4190 277 143 - - - x - - x x - - 08210 Avila 4067 -452 1130 - - - x - - - - - - 08213 Segovia 4095 -412 1005 - - - x - - x x - - 08215 Navacerrada 4078 -402 1894 - - - x - - x x - - 08220 Madrid Universidad 4045 -372 664 x - - x x - x x - - 08222 Madrid Barajas 4042 -368 655 - - - x x x - - x x 08232 Molina de Aragon 4085 -188 1056 - - - x - - - - - - 08261 Caceres 3947 -633 405 - - - x x - x x - - 08272 Toledo 3988 -405 515 - - - x x - x x - - 08301 Palma de Mallorca 3955 262 6 - - - x x x - - x x 08306 Palma de Mallorca / San

Juan 3955 273 4 - - - x - - x x x x

08314 Mahon 3987 423 87 - - - x - x x x x x 08329 Badajoz 3888 -697 198 - - - x x x - - x x 08359 Alicante 3837 -50 81 - - - x x x - - x x 08390 Sevilla / Tablada 3737 -600 8 - - - x x x - - x x 08391 Sevilla / San Pablo 3742 -590 34 - - - x x - x x - - 08419 Granada Aiport 3718 -378 567 - - - x - - x x - - 08430 Murcia 3800 -117 61 x - x x x - x x - - 08433 Murcia / San Javier 3778 -80 5 - - - x - - x x - - 08482 Malaga Airport 3667 -448 16 - - - x - - x x - - 08487 Almeria Airport 3685 -238 15 - - - x - - x x x x 08495 Gibraltar 3615 -535 5 - - - x x x x x x x Sweden 02045 Kiruna Geofysika 6783 2043 408 - - - x x x - - - - 02185 Lulea 6555 2213 17 x - x x x x - - - - 02226 Oestersund 6318 1450 376 - - - x x x x x x x 02283 Umea / Robacksdalen 6382 2025 10 - - - x x x - - - - 02415 Karlstad 5937 1347 46 - - - x x x - - - - 02435 Borlaenge Airport 6043 1550 153 - - - x - - - - - - 02483 Stockholm 5935 1807 30 x - x x x x - - - - 02513 Goeteborg 5770 1200 5 - - - x x x - - - - 02571 Norrkoeping 5858 1625 5 - - - x x x - - - - 02590 Visby Airport 5767 1835 51 - - - x x x x x x x 02627 Lund 5572 1322 73 - - - x x x - - - - 02641 Vaxjoe / Kronoberg 5693 1473 182 - - - x x x - - - - Switzerland 06601 Basel – Binningen 4755 758 316 - - - x x x - - - - 06604 Neuchatel 4700 695 485 - - - x x x - - - - 06605 Chasseral 4713 707 1599 - - - x x x - - - - 06609 Moleson 4655 702 1972 - - - x x x - - - - 06610 Payerne 4682 695 490 x - x x x x x x - - 06612 La Chaux de Fonds 4708 680 1018 x - x x x x x x - - 06616 Fahy 4743 695 596 - - - x x x - - - - 06619 La Fretaz 4683 658 1202 - - - x x x - - - - 06620 Schaffhausen 4768 862 437 - - - x x x - - - - 06621 Guettingen 4760 928 440 - - - x x x - - - -


95




06628 Plaffeien 4675 727 1042 - - - x - - - - - - 06631 Bern / Liebefeld 4693 742 565 - - - x x x - - - - 06633 Buchs / Suhr 4738 808 387 - - - x - - - - - - 06639 Napf 4700 793 1406 - - - x x x - - - - 06643 Wynau 4725 778 422 - - - x x x x x - - 06645 Ruenenberg 4743 788 610 - - - x x x - - - - 06650 Luzern 4703 830 456 - - - x x x - - - - 06655 Engelberg 4682 842 1035 - - - x x x - - - - 06659 Pilatus 4698 825 2106 - - - x x x - - - - 06660 Zuerich SMA 4738 857 556 - - - x x x x x x x 06664 Reckenholz 4743 852 443 - - - x x x - - - - 06669 Laegern 4748 840 868 - - - x - - x x - - 06670 Zuerich Airport 4748 853 436 x - x x x x x x - - 06672 Altdorf 4687 863 449 - - - x x x x x - - 06673 Waedenswil 4722 868 463 - - - x x x - - - - 06679 Taenikon 4748 890 536 - - - x x x - - - - 06680 Saentis 4725 935 2490 x - x x x x x x - x 06681 St. Gallen 4743 940 779 - - - x x x - - - - 06685 Glarus 4703 907 515 - - - x x x - - - - 06700 Geneve-Cointrin 4625 613 420 x - x x x x x x x x 06702 La Dole 4643 610 1670 - - - x x x x x - - 06705 Changins 4640 623 430 - - - x x x - - - - 06711 Pully 4652 667 461 - - - x x x - - - - 06712 Aigle 4633 692 381 - - - x x x - - - - 06716 Fey 4618 727 737 - - - x - - - - - - 06717 Grand St. Bernard 4587 717 2472 - - - x x x - - - - 06720 Sion 4622 733 482 - - - x x x x x - - 06722 Evolene / Villaz 4612 752 1825 - - - x - - - - - - 06724 Montana 4632 748 1508 - - - x x x x x - - 06727 Visp 4630 785 640 - - - x - x - - - - 06730 Jungfraujoch 4655 798 3580 - - - x x x x x - - 06734 Interlaken 4667 787 580 - - - x x x - - - - 06735 Adelboden 4650 757 1320 - - - x x x - - - - 06744 Grimsel Hospiz 4657 833 1980 - - - x - - - - - - 06745 Ulrichen 4650 832 1345 - - - x x x - - - - 06748 Zermatt 4603 775 1638 - - - x x x - - - - 06750 Guetsch 4665 862 2287 - - - x x x x x - - 06753 Piotta 4652 868 1007 - - - x x x x x - - 06756 Comprovasco 4647 893 575 - - - x - - - - - - 06759 Cimetta 4620 880 1672 - - - x x x x x - - 06760 Locarno / Monti 4617 878 366 x - x x x x x x - - 06762 Locarno / Magadino 4617 888 197 - - - x x x x x - - 06770 Lugano 4600 897 273 - - - x x x x x x x 06771 Stabio 4585 893 353 - - - x x x - - - - 06780 Weissfluhjoch 4683 982 2690 - - - x x x - - - - 06782 Disentis 4670 885 1190 - - - x x x x x - - 06783 San Bernardino 4647 918 1639 - - - x x x - - - - 06786 Chur-Ems 4687 953 555 - - - x x x x x - - 06788 Hinterrhein 4652 918 1611 - - - x x x - - - - 06791 Corvatsch 4642 982 3315 x - x x x x x x - -


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06792 Samedan 4653 988 1705 - - - x x x x x - - 06793 Davos 4680 982 1592 - - - x x x - - - - 06794 Robbia 4635 1007 1078 - - - x x x x x - - 06798 Scuol 4680 1028 1298 - - - x x x - - - - Syria 40001 Kamishli 3702 4122 452 - - - x - - - - x x 40007 Aleppo 3618 3722 390 - - - x - - x x x x 40061 Palmyra 3455 3830 395 - - - x - - - - x x 40080 Damascus 3342 3652 610 - - - x - - x x x x Turkey 17029 Samsun 4127 3630 162 - - - x - - - - - - 17030 Samsun 4128 3633 4 x x x x x - x x x x 17061 Istanbul Gebze 4080 2943 130 - - - x - - - - - - 17062 Istanbul Goztepe 4097 2908 33 x - x x x x - - x x 17130 Ankara 3995 3288 891 x x x x x x - - x x 17220 Izmir 3843 2717 25 - - - x x x - - x x 17280 Diyarbakir 3788 4018 686 x x x x x x x x x x 17300 Antalya 3687 3073 50 x x x x x x x x x x Turkmenistan 38507 Krasnovodsk 4003 5298 89 - - - x x x x x x x 38687 Chardzhou 3908 6360 36 - - - x x x - - x x 38880 Ashkhabad 3797 5833 228 - - - x x x x x x x United Kingdom 03005 Lerwick 6013 -118 82 x - x x x x x x x x 03017 Kirkwall Airport 5895 -290 26 - - - x x x x x - - 03026 Stornoway 5822 -632 9 - - - x x x x x x x 03049 Cape Wrath 5862 -500 112 - - - x x x x x - - 03063 Aviemore 5720 -383 220 - - - x x - - - - - 03066 Kinloss 5765 -357 7 - - - x - - x x x x 03072 Kinbrace 5823 -392 103 - - - x x x - - - - 03091 Aberdeen 5720 -222 65 - - - x x x x x x x 03100 Tiree 5650 -688 12 - - - x x x x x x x 03112 Dunstaffnage 5647 -543 3 - - - x x - - - - - 03115 Onich 5672 -522 15 - - - x x x - - - - 03136 Auchincruive 5547 -457 48 - - - x x x - - - - 03137 Whithorn 5470 -442 40 - - - x x x - - - - 03159 Edinburgh East Craigs 5595 -333 61 - - - x - x - - - - 03160 Edinburgh Airport 5595 -335 41 - - - x - x x x x x 03162 Eskdalemuir 5532 -320 242 x - x x x x x x x x 03169 Mylnefield / Dundee 5645 -307 30 - - - x x - - - - - 03170 Shanwell 5643 -287 4 x - x x x x - - - - 03204 Ronaldsway Airport 5408 -463 16 - - - x x x x x - - 03224 Hazlerigg 5402 -275 95 - - - x x x - - - - 03240 Boulmer 5542 -160 23 - - - x x x x x - - 03257 Leeming 5430 -153 40 - - - x x x x x x x 03282 Whitby 5448 -62 41 - - - x x x - - - -


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03302 Valley 5325 -453 11 - - - x x x x x x x 03318 Blackpool Airport 5377 -303 10 - - - x - - x x x x 03322 Aughton 5355 -292 54 x - x x x x x x - - 03334 Manchester Airport 5335 -227 78 - - - x x x x x x x 03356 Cawood 5383 -115 6 - - - x x x - - - - 03360 Finningley 5348 -100 17 - - - x x - x x - - 03377 Waddington 5317 -52 70 - - - x x x x x x x 03415 Shawbury 5280 -267 72 - - - x x x - - - - 03468 Kirton 5293 -5 4 - - - x x x - - - - 03470 Denver Complex 5258 35 3 - - - x x x - - - - 03496 Hemsby 5268 168 13 - - - x x x x x - - 03500 Gogerddan 5243 -402 40 - - - - x - - - - - 03502 Aberporth 5213 -457 133 - - - x x x x x x x 03534 Elmdon / Birmingham

Airport 5245 -173 96 - - - x x x x x x x

03561 Silsoe 5202 -42 59 - - - x x x - - - - 03570 Broom's Barn 5227 57 75 x - - x x x - - - - 03586 Honington 5233 77 54 - - - x - - x x x x 03655 Wallingford 5160 -117 49 - - - x x - - - - - 03660 Grendon Underwood 5190 -102 70 - - - x - - - - - - 03679 Rothampstead 5180 -35 128 - - - x x - - - - - 03680 Hoddesdon 5178 0 47 - - - x x - - - - - 03715 Cardiff / Wales Airport 5140 -335 67 - - - x x x x x x x 03720 Long Ashton 5143 -267 51 - - - x x - - - - - 03721 Yeovilton 5100 -263 18 - - - x - - - - - - 03740 Lyneham 5150 -198 156 - - - x - - x x x x 03763 Easthampstead/ Bracknell 5138 -78 73 - - - x x x x x - - 03774 Crawlay 5108 -22 144 - - - x x x - - - - 03776 London Gatwick Airport 5115 -18 62 - - - x x x x x x x 03779 London Weather Centre 5152 -12 77 x - x x x x x x - - 03790 East Malling 5128 45 37 - - - x x x - - - - 03797 Manston 5135 135 55 - - - x - - x x x x 03808 Camborne 5022 -532 87 - - - x x x x x - - 03827 Plymouth Mount Batten 5035 -412 50 - - - x x x x x x x 03829 Bude 5083 -455 15 - - - x x x - - - - 03862 Bournemouth Airport 5078 -183 11 - - - x x x x x x x 03863 Efford 5073 -157 16 - - - x x x - - - - 03870 Rustington 5082 -52 8 - - - x x - - - - - 03894 Guernsey 4943 -260 101 - - - x x x x x - - 03895 Jersey Airport 4922 -220 84 - - - x x x x x - - 03917 Belfast / Aldergrove 5465 -622 81 x x x x x x x x x x Ukraine 33345 Kiev 5040 3045 179 x - x x x x x x x x 33393 L'vov 4982 2395 325 - - - x - - x x x x 33837 Odessa 4648 3063 64 x x x x x x x x x x 33946 Simferopol 4502 3398 205 - - - x x x x x x x 34300 Khar'kov 4993 3628 152 - - - x x x x x x x Uzbekistan


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38262 Cimbaj 4295 5982 66 - - - x - - x x x x 38413 Tamdy 4173 6462 220 - - - x - - - - x x 38457 Tashkent 4127 6927 428 - - - x x x - - x x Yugoslavia 13274 Beograd 4480 2047 132 x - x x x x - - x x 13295 Negotin 4423 2255 42 - - - x x x x x - - 13378 Kopaonik 4328 2080 1711 - - - x x x - - - - 13461 Bar 4210 1910 4 - - - x x x - - - - 13462 Podgorica / Golubovci 4237 1925 33 - - - x - - x x x x 13481 Pristina 4265 2115 573 - - - x x x - - - -

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