support for the 2014 olympic games in sotchi pierre eckert meteoswiss, geneva
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Support for the 2014 Olympic Games in Sotchi Pierre Eckert MeteoSwiss, Geneva COSMO WG4 coordinator « Interpretation and applications » COSMO General meeting, September 2010. Plan of the session. General introduction (P. Eckert) Postprocessing / statistical downscaling - PowerPoint PPT PresentationTRANSCRIPT
Federal Department of Home Affairs FDHAFederal Office of Meteorology and Climatology MeteoSwiss
Support for the 2014 Olympic Games in Sotchi
Pierre EckertMeteoSwiss, Geneva
COSMO WG4 coordinator« Interpretation and applications »
COSMO General meeting, September 2010
2 Sotchi Olympic Games, General Introduction ¦ COSMO General Meeting September 2010Pierre.Eckert[at]meteoswiss.ch
Plan of the session
• General introduction (P. Eckert)• Postprocessing / statistical downscaling• Some methods used in Vancouver 2010
• Experiences from Torino 2006 (M. Milelli)• Input from Roshydromet (I. Rosinkina, G. Rivin,…)
• Know-how in postprocessing• Planed organisation / setup of measurements
• Elements of discussion (for further treatment)• Setup of 0.5-2 km model, incl. assimilation• Implementation of a probabilistic model (EPS)• Connection with demonstration project• Role of the COSMO w.r. to other collaborations
• Definition of WG4 working packages
3
Enhanced observational network; Nowcasting tools; Regional data assimilation; High-resolution NWP models and EPS; Meso-scale verification system; Means of NWP output interpretation and
delivery (new parameters and products, visualization etc); postprocessing;
Training
Primary meteorological needs for Sochi-2014:
4 Sotchi Olympic Games, General Introduction ¦ COSMO General Meeting September 2010Pierre.Eckert[at]meteoswiss.ch
Postprocessing
• Derived fields: pressure levels, PV, radar reflectivity,…• Generation of products: TV, Internet,…• Diagnostics: turbulence, icing, snowfall limit,…
• Local adaptation, downscaling• Statistical downscaling (correction of model with
observations)• Blending (mixture of model output and observations
(gridded), INCA,…)• Downstream models (1d, 2d, 3d,…)
5 Sotchi Olympic Games, General Introduction ¦ COSMO General Meeting September 2010Pierre.Eckert[at]meteoswiss.ch
Perfect Prog, MOS
Use two sets of historical data:1. The predictand = the local element you want to predict:
temperature at Sotchi, occurrence of fog on the downhill slope,…
2. The predictors = a bunch of model parameters: pressure, instability indices, 850 hPa temperature, winds,…It is allowed to take recent observations of the predicand as predictor.
Correlations (regression, discriminance,…) between the predictand and the predictors are computed. Often the predictors are selected by significance.
Kalman filtering is probably a subclass
6 Sotchi Olympic Games, General Introduction ¦ COSMO General Meeting September 2010Pierre.Eckert[at]meteoswiss.ch
Non linear methods
• The same data sets can be treated with non linear methods• Neural networks• Boosting• …
• Instead of defining hyperplanes in the predictor space, arbitrary shapes can be found.
• The selection of predictors, the choice of an optimal separation surface and the computation of coefficients is called “learning”
7 Sotchi Olympic Games, General Introduction ¦ COSMO General Meeting September 2010Pierre.Eckert[at]meteoswiss.ch
Classification
• A set of fixed meteorological situations is defined.• Every country has several such classifications• They are usually correlated to sensible weather (in
the situation 7b, the sun is shining in 90% of the corresponding days,…), in situation SWa there is an 80% chance to get hill fog over the downhill slope,…
8 Sotchi Olympic Games, General Introduction ¦ COSMO General Meeting September 2010Pierre.Eckert[at]meteoswiss.ch
Classification and interpretation
Luganorain > 1 mm/24h
Luganorain > 10 mm/24h %
9 Sotchi Olympic Games, General Introduction ¦ COSMO General Meeting September 2010Pierre.Eckert[at]meteoswiss.ch
Analogs
• This method looks for the n situations in the past which are closest to a given forecast according to some distance.
• A statistics on the weather elements corresponding to these n situations is then made.
• As with the classifier, it is possible that the closest situation is far away from the presented situation.
Federal Department of Home Affairs FDHAFederal Office of Meteorology and Climatology MeteoSwiss
Statistical Adaptation for COSMO
COSMO General Meeting 2010
Vanessa Stauch
11 Sotchi Olympic Games, General Introduction ¦ COSMO General Meeting September 2010Pierre.Eckert[at]meteoswiss.ch
calibration with Kalman Filter
>> recursive estimation of forecast error (prediction – correction)
>> requires online observations
>> can be used quasi-instantaneously (no large historical database)
>> cannot predict fast changes (assumption of persistent error for each fcst)
>> suitable for a subset of parameters (normally distributed errors)
12 Sotchi Olympic Games, General Introduction ¦ COSMO General Meeting September 2010Pierre.Eckert[at]meteoswiss.ch
Kalman Filter @ MeteoSwiss
operational:
T2m, TD2m
for
COSMO-LEPS mean
COSMO-7
COSMO-2
IFS
in preparation:
FF10m, TW2m, RH2m
for
COSMO-LEPS mean
COSMO-7
COSMO-2
IFS
13 Sotchi Olympic Games, General Introduction ¦ COSMO General Meeting September 2010Pierre.Eckert[at]meteoswiss.ch
T2m predictions
COSMO-7
COSMO-2COSMO-2
KFC7
COSMO-7
KFC2
COSMO-7COSMO-7
performance?
14 Sotchi Olympic Games, General Introduction ¦ COSMO General Meeting September 2010Pierre.Eckert[at]meteoswiss.ch
benefit COSMO-2 vs COSMO-7?
04.04.08 – 31.10.08 RMSE RMSE
All ANETZ stations 11.0 % 4.0 %Low ANETZ stations 8.8 % 5.2 %High ANETZ stations 13.0 % 3.2 %
04.04.08 – 31.10.08 STD STD
All ANETZ stations 12.3 % 4.0 %Low ANETZ stations 12.7 % 5.2 %
High ANETZ stations 12.6 % 3.2 %
C2 vs C7 C2-KF vs C7-KF
=
Differences between COSMO-2 and COSMO-7 with KF smaller but still significant. Bias in KF predictions totally removed
15 Sotchi Olympic Games, General Introduction ¦ COSMO General Meeting September 2010Pierre.Eckert[at]meteoswiss.ch
Short term Kalman filter for radiation
Short-term correction: based on previous hour and every new obs
» exploits temporal autocorrelation of the error with the Kalman filter» corrects a few hours only» also beneficial for temperature forecasts
Zurich, 01.07.-10.07.2007solar heat gain for south orientation (derived from global radiation)
16 Sotchi Olympic Games, General Introduction ¦ COSMO General Meeting September 2010Pierre.Eckert[at]meteoswiss.ch
Calibration with multiple regression MOS
>> estimation of multiple linear regression models
>> requires large historical database (observations and forecasts)
>> models can be „arbitrarily“ complicated (provided the data)
>> possibly less adaptive than the KF (constant regression parameters)
>> suitable for a larger subset of parameters (compared to KF)
17 Sotchi Olympic Games, General Introduction ¦ COSMO General Meeting September 2010Pierre.Eckert[at]meteoswiss.ch
COSMO-7 vs COSMO-2
COSMO-7 COSMO-2 (03)Chasseral (CHA) 56 > 44Evionnaz (EVI) 90 < 99Gütsch (GUE) 55 > 45Oron (ORO) 53 < 59Piz Martegnas (PMA) 51 > 45Schaffhausen (SHA) 54 > 52Uetliberg (UEB) 76 > 69
rRMSE (%) für 1-24h, period 01.09.08 – 31.03.09
CHA
EVI
GUEPMA
SHA
OROUEB
18 Sotchi Olympic Games, General Introduction ¦ COSMO General Meeting September 2010Pierre.Eckert[at]meteoswiss.ch
effect on MOS-postprocessing
COSMO-7 MOS
COSMO-2 (03) MOS
Chasseral (CHA) 34 > 32Evionnaz (EVI) 78 > 77Gütsch (GUE) 45 > 39Oron (ORO) 59 > 47Piz Martegnas (PMA) 69 > 42Schaffhausen (SHA) 85 > 77Uetliberg (UEB) 59 > 54
rRMSE (%) für 1-24h, period 01.09.08 – 31.03.09
CHA
EVI
GUEPMA
SHA
OROUEB
19 Sotchi Olympic Games, General Introduction ¦ COSMO General Meeting September 2010Pierre.Eckert[at]meteoswiss.ch
plans for COSMO-MOS
>> development of a regression-based model output statistics system
>> target parameter:
wind speed and direction, sunshine duration, global radiation
>> using information of COSMO-7, COSMO-2 and COSMO-LEPS
>> project duration 08.2010 – 08.2012
20 Sotchi Olympic Games, General Introduction ¦ COSMO General Meeting September 2010Pierre.Eckert[at]meteoswiss.ch
Summary
Statistical postprocessing profits from a better NWP input model
„dynamical downscaling“ does not replace statistical adaptation to
local observations (in particular if results being verified against
those)
Long time series of model forecasts and observations (≥ 2 years)
are prerequisite for the development of a robust statistical model
21 Sotchi Olympic Games, General Introduction ¦ COSMO General Meeting September 2010Pierre.Eckert[at]meteoswiss.ch
1d, 2d, 3d models
• It is also possible to feed 1d, 2d, 3d models forced by the 3d (4d) model.
• Ex. Fog model: soil model, a lot of levels in the few 10’s of meters of the atmosphere, aerosols,…
• Should ideally be incorporated into the full model, but can be expensive.
Federal Department of Home Affairs FDHAFederal Office of Meteorology and Climatology MeteoSwiss
Local 2d and 3d models for the 2010 Vancouver Olympic Games
COSMO General Meeting 2010
Thanks to André Méthod, CMC
23
Real-Time Experimental Land Surface System Real-Time Experimental Land Surface System for the 2010 Vancouver Games for the 2010 Vancouver Games
with contributions from:
Maria Abrahamowicz, Bernard Bilodeau, Marco Carrera, Nathalie Gauthier, Lily Ioannidou, Alain Patoine, et
Sylvie Leroyer
Natacha Bernier Linying Tong
andStéphane Bélair
SLIDE 1
24
Concept of external land surface modeling (again!)
ATMOSMODEL
3D INTEGRATION
ExternalLand SurfaceModel
With horizontal resolution as high as that of surface databases (e.g., 100 m)
ATMOSPHERIC FORCING at FIRST ATMOS. MODEL LEVEL (T, q, U, V)
2D INTEGRATION
Computational cost of off-line surface modeling system is much less than an integration of the atmospheric model
ATMOSPHERIC FORCING at SURFACE (RADIATION andPRECIPITATION)
LOW-RES
HIGH-RES
SLIDE 2
25
Applications to the 2010 Vancouver Games:Two surface systems: “2D” and “Point”1400 x 1800 computational grid (100-m grid size)
USA
VAN
Whistler
Blackcomb
Callaghan
VANCOUVERCypress
Bowl
SLIDE 3
26
Experimental real-time “2D” land surface system
ANALYSIS / ASSIMILATION
FORECAST
24-h open-loop run
Geophysicalfields
00 UTCInitial timeSurface analysis
REG-15 12Z (12-18h)
REG-15 00Z (6-18h)
REG-15 12Z (6-12h)
ATMOSPHERIC FORCING
24-h open-loop runfor next day
96-h forecast run
REG-15 00Z (0-48h)Av. at 03Z
48h
GLB-33 00Z (48-96h)Av. at 06Z
SLIDE 4
27
Experimental real-time “point” land surface system
ANALYSIS / ASSIMILATION
24-h background run
Geophysicalfields
00 UTCInitial timeSurface analysis
Snow obs
ATMOSPHERIC FORCING
24-h background runfor next day
96-h forecast run
SCREEN-LEVEL OBS +MODEL FORCING
FORECAST
SLIDE 5
REG-15 00Z (0-48h)Av. at 03Z
48h
GLB-33 00Z (48-96h)Av. at 06Z
28
Two-dimensional snow analysis against surface observations
(Bernier et al. 2010, part I)
Close relationship with height of observations and of model outputs, ... but not always...
SLIDE 6
29
Verification of “point” snow analysis at VOC
VOC Blackcomb Mt. Base
2008
REG-OP (15 km)
“POINT”
OBS
2D-100m
LAM-OP (2.5 km)
Atmospheric forcing (e.g., precipitation phase) is of crucial importance for the 2D system (without assimilation of surface snow obs)
As could be expected, “point” system is right on target (because of the asssimilation of surface snow data)
SLIDE 7
33
List of products
• Last 10 days meteograms (forcing + screen-level diagnostics from surface system)
• Last 10 days surfacegrams (surface prognostic variables – focus on snow conditions)
• Next 4 days meteograms (forcing + screen-level diagnostics from surface system)
• Next 4 days surfacegrams (surface prognostic variables – focus on snow conditions)
SLIDE 11
34
Examples of Meteograms and “Surfacegrams”
SLIDE 12
1.0 km
WhistlerWhistler
VancouverVancouver
15 km
2.5 km
High resolution Numerical Weather Prediction Systems High resolution Numerical Weather Prediction Systems for the Vancouver 2010 Winter Olympics and for the Vancouver 2010 Winter Olympics and Paralympics GamesParalympics Games
A. Erfani, B. Denis, A. GigA. Erfani, B. Denis, A. Giguèreuère, , N. McLennan, N. McLennan, A. Plante, L. Tong, A. Plante, L. Tong,
Environment Canada / MSC/ DevelopmentEnvironment Canada / MSC/ Development
S. BS. Bélair, élair, M. Charron,M. Charron, J. Mailhot, J. Mailhot, R. McTaggart-Cowan, J. MilbrandtR. McTaggart-Cowan, J. Milbrandt
Environment Canada / Meteorological Research Environment Canada / Meteorological Research DivisionDivision
High Resolution Prediction System - cascading
Growing Orography• 3 h → LAM_2.5• 1 h →LAM_1.0
00 06 18 00 06 12 18 0000 06 12 18 12UTC
16 22 10 16 22 04 10 1616 22 04 10 04PST
00 06 18 00 06 12 18 0000 06 12 18 12UTC
16 22 10 16 22 04 10 1616 22 04 10 04PSTREGIONAL R100 (48hrs)
LAM_15 (39hrs)
LAM_2.5 (33hrs)
LAM_1.0 (19hrs)
06Z.
11Z. 06Z
15Z
REGIONAL R100 (48hrs)
LAM_15 (39hrs)
LAM_2.5 (33hrs)
LAM_1.0 (19hrs)
06Z.
11Z. 06Z
15Z
00Z.
00 06 18 00 06 12 18 0000 06 12 18 12UTC
16 22 10 16 22 04 10 1616 22 04 10 04PST
00 06 18 00 06 12 18 0000 06 12 18 12UTC
16 22 10 16 22 04 10 1616 22 04 10 04PSTREGIONAL R112 (48hrs)
LAM_15 (36hrs)
LAM_2.5 (33hrs)
LAM_1.0 (19hrs)
15Z.
20Z. 15Z
00Z
12Z.
LAM 2.5km Product period
LAM 1.0km Product period
Available to forecasters:
• by 7:00 a.m. local (for the morning briefing)
• by 12:00 noon local (for afternoon briefing)
• Based on Olympic forecasters’ feedback:- products, display format,…
• Easy display (Weather Viewer)• Comprehensive list of model outputs:
- 2D maps, time series at stations, vertical soundings and cross-sections
• Products available for evaluation by support desk and briefings
Customized output packageCustomized output package
2D maps:• Screen-level potential temperature• Screen-level relative humidity• 10-m winds• Wind gusts (gust estimates, minimum, maximum)• Standard deviations of 10-m wind speed and direction • Accumulated precipitation types (liquid / freezing / snow /
frozen)• Precipitation accumulation (liquid / solid / total)• Precipitation rate (liquid / solid / total)• Snow/liquid ratio• Cloud cover (high/ mid/ low)• Cloud base height• Visibility (through fog, rain, snow)• Freezing level (0C isotherm)• Snow level• Wind chill factor
Customized output packageCustomized output package
TemperatureTemperatureDewpoint, RHDewpoint, RH
Surface windsSurface winds
Cloud cover:Cloud cover:Low, mid, highLow, mid, highLow level windsLow level winds Wind gustsWind gusts
WindchillWindchillCloud baseCloud base
QPF: QPF: /1h, /3h,/1h, /3h, /6h, /6h, cumulativecumulative
QPF QPF by type:by type:cumul. , instant.cumul. , instant.
2-D maps2-D maps(1 km)(1 km)
Visibility: Visibility: fog, rain, snow, fog, rain, snow, resultantresultant
Customized output packageCustomized output package
MeteogramsMeteograms(1 km)(1 km)
General WxGeneral WxT, TT, Tdd etc. etc.
Wind and GustsWind and Gusts
PrecipitationPrecipitationPCP RatesPCP Rates
Clouds and visibilityClouds and visibility
SnowSnow
Customized output packageCustomized output package
General weather:low-level temperature,
cloud cover,
total precipitation,
wind speed and direction
1-km LAM model
Callaghan Valley (VOD)
Customized output packageCustomized output package
Precipitation Precipitation AmountsAmountsRatesRates
High Resolution Prediction System - Multi-model Meteograms
Thank You!Thank You!
48 Sotchi Olympic Games, General Introduction ¦ COSMO General Meeting September 2010Pierre.Eckert[at]meteoswiss.ch
Plan of the session
• General introduction (P. Eckert)• Postprocessing / statistical downscaling• Some methods used in Vancouver 2010
• Experiences from Torino 2006 (M. Milelli)• Input from Roshydromet (I. Rosinkina, G. Rivin,…)
• Know-how in postprocessing• Planed organisation / setup of measurements
• Elements of discussion (for further treatment)• Setup of 0.5-2 km model, incl. assimilation• Implementation of a probabilistic model (EPS)• Connection with demonstration project• Role of the COSMO w.r. to other collaborations
• Definition of WG4 working packages