STORMS IN NORTHERN EUROPE –CHANGES, PERSPECTIVES, AND IMPACTS

HANS VON STORCHInstitute of Coastal Research,

(Helmholtz Zentrum Geesthacht), andKlimaCampus Hamburg, Germany

TOKIO MARINE'S 2011 SUMMIT ON GLOBAL WARMING AND CLIMATE CHANGE, APRIL 29, 2011, ATLANTA USA

Counting storms in

weather maps – steady

increase of NE Atlantic storms since the 1930s

….

Popular argument

When it is getting warmer, then we have more water vapor in the atmosphere, and mid-latitude storms become more intense („more fuel“).

However at mid latitudes, intense storms are baroclinic, and thus driven by temperature differences – explaining, why we have more storms in the cold season that in the warm season.

Unchanging extratropical storm conditions are not inconsistent with a

rise in temperature

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Causes of inhomogenities:Changes in

– Instruments– Sampling frequencies – Measuring units– Environments (e.g. trees,

buildings)– Station relocations

(Dotted lines)

Homogeneity of local observations

(Wind speed measurement; SYNOP Measuring net of German Weather service; Coastal stations at the German Bight; Observation period: 1953-2005)

Lindenberg et al., 2011

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Representativity of near surface wind speed measurements

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The major problem for applying statistical analysis in climate change studies is related

- to the assumptions of a stationary sampling process, and

- to the assumption of representativity.• The local data change their statistics because of

changing observational practices and conditions (inhomogeneity); also their representativity for a larger area is often compromised.

• Usage of weather analyses, incl. re-analyses and proxies such as damages are generally not suitable.

a) Use of proxies derived from air pressure readings.b) Simulation by empirical or dynamical downscaling of

large scale information.

For assessing recent and ongoing changes of mid-latitude storm conditions, principally two approaches are possible:

A proxy of storminess: Intraseasonal statistics of daily geostrophic winds (pressure gradients)

• Air pressure readings are mostly homogenous• The scaled pressure gradient is called “geostrophic wind”.• The tropospheric wind is to first order approximation

proportional to atmospheric pressure gradient • We use annual/seasonal percentiles (e.g., 95 or 99%iles ) of

geostrophic wind derived from triangles of pressure readings as proxies for annual /seasonal storminess.

Schmidt and von Storch, 1993

Krueger and von Storch, 2011

Testing the robustness of the link seasonal percentiles of geostrophic wind speed and of surface wind speeds in the virtual reality of a 50 years regional simulation

Triangles used

Correlations between time series of geostrophic wind speed percentiles and wind speed percentiles

Geostropic wind stats N Europe99%iles of annual geostrophic wind speeds

for a series of station triangles in the North Sea regions and in the Baltic Sea region.

Alexandersson et al., 2002

• Dynamical downscaling to obtain high-resolution (10-50 km grid; 1 hourly) description of weather stream- with spectral nudging constraint- use of NCEP or ERA re-analysis allows reconstruction of regional weather in past decades (1948-2010)- when global scenarios are used, regional scenarios with better description of space/time detail can be derived.

• Meteorological data are fed into dynamical models of weather-sensitive systems, such as ocean waves, catchment hydrology, long-range pollution etc.

Dynamical (process based model) downscaling cascade for constructing variable regional marine weather statistics

Weisse, pers. comm.

Extreme value analysis of wind speed at platform K13 (southern North Sea)

January 1980-January 1997

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Stormcount 1958-2001

Wei

sse

et a

l., J.

Clim

ate,

200

5

Change of # Bft 8/year

t ≤ T t ≥ T

Skill in representing wave conditions

Red: buoy, yellow: radar, blue: wave model run with REMO winds

wave direction

significant wave height

[days]

[days]

Gerd Gayer, pers. comm., 2001

The CoastDat data set:• Long (50 years) and high-resolution reconstructions of recent offshore and coastal conditions mainly in terms of wind, storms, waves, surges and currents and other variables in N Europe• Scenarios (100 years) of possible consistent futures of coastal and offshoreconditions• extension – ecological variables, SE Asia

Clients:• Governmental: various coastal agencies dealing with coastal defense and coastal traffic• Companies: assessments of risks (ship and offshore building and operations) and opportunities (wind energy)• General public / media: explanations of causes of change; perspectives and options of change

www.coastdat.de

Wave Energy Flux [kW/m]

Currents Power [W/m2]

Some applications of- Ship design- Navigational safety- Offshore wind- Interpretation of measurements- Oils spill risk and chronic oil pollution- Ocean energy- Scenarios of storm surge conditions- Scenarios of future wave conditions

Range of changes in seasonal maximum wind (10 m) in Northern Germany in a series of dynamically downscaled scenarios (HadCM, MPI; A2, B2)

© Dundee Satellite Receiving Station

~300 km

Scan

dina

via

Spitz-bergen

Polar lows

Mesoscale (< 1000 km) sized maritime storms

●intense/ strong winds , severe weather

●occur polewards of the Polar Fronts in both hemispheres during winter

●typically induced by disturbances in the air flow

●typically driven by convective processes

●Here: only Northern North Atlantic

Past annual frequencies of polar lows

PLS: Polar Low Season (July-June) Zahn and von Storch, 2008

Downscaling scenarios

Downscaling scenarios and simulations

C20 (1960-1989)

A2, B1, A1B1 (2070-2099)

… run with ECHAM5/MPIOM1

… downscaled with CLM, employing spectral nudging.

Projected changes in polar low frequency and vertical atmospheric stability

A2

C20

A1BB1

Zahn and von Storch, 2010

Differences of the area and time-averaged ice-free SST and T500hPa over the maritime northern North Atlantic as proxy for frequency of favorable polar low conditions (CMIP3/IPCC AR4)

Past changes according to dynamical downscaling of NCEP/NCAR re-analysis 1949-2005 Strong inter annual variability Frequency remains on a similar level – no systematic trend

Polar lows become less frequent in the Northern North Atlantic in the coming 100 years according to regional modeling (dynamical downscaling) - control and scenario simulations with one GCM, and by analysis of vertical stability in a large set of (CMIP3) global climate simulations; all simulations show an increase in projected stability.The genesis regions shift northward.

Past and future occurrence of North Atlantic Polar Lows

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Conclusion: Usage of proxies

1. Monitoring extra-tropical storminess may be based on air pressure proxies.

2. This allows assessments for 100 and more years.3. Decades long upward and downwards trends have been

detected in recent years in the Northern European and other regions.

4. These trends are not sustained and have show recent reversals in all considered regions.

5. Recent trends are not beyond the range of natural variations, as given by the historical past, but are more of intermittent character. Regional temperatures rose significantly at the same time.

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Conclusion: Usage of dynamical downscaling

1. Dynamical downscaling for describing synoptic and mesoscale variability is doable.

2. Analysis of 60 year simulations point to strong year-to-year variability, to less decade-to-decade variability and no noteworthy trend in the region of the North Atlantic/European Sector – both in terms of baroclinic storms and polar lows.

3. Similar study done for North Atlantic Polar Lows , E Asian typhoons and medicanes. (work in progress)

Mediterranean hurricanes are strong mesoscale cyclones with some resemblance with tropical cyclones and polar lows (warm core, cloud-free eye, winds up to hurricane speed) that develop occasionally over the Mediterranean Sea.

Medicanes

15 Jan 1995

Leone Cavicchia, pers. comm

Dynamically downscaled

Take-Home Message1.Baroclinic storms and polar lows represent key climatic risks in Northern Europe.2.In the past, no noteworthy systematic changes have been detected, when homogeneous, sufficiently long times series of evidence has been considered.3.For the futures, scenarios describe the possibility for a weak intensification of strong wind cases (baroclinic storms) in winter, and a reduction and northward shift of polar low activity.4.Scenarios are consistent with ongoing change.5.The methodology, based on dynamical downscaling and the usage of proxies for storminess are well developed. They may be employed for analyzing conditions in other parts of the world.

Reserve

How do size and surface conditions influence the description of storm activity?

Single-station based proxies

correlations between annual 99th percentiles of ground level wind speed and annual number of pressure observations below 980 hPa

(median 0.198, 0.05-quantile -0.09)

Local pressure stats since 1800

Time series of pressure-based storminess indices derived from pressure readings in Lund and Stockholm. From top to bottom: Annual number of pressure observations below 980 hPa (Np980), annual number of absolute pressure differences exceeding 16 hPa/12 h (NDp/Dt), Intra-annual 95-percentile and 99-percentile of the pressure differences (P95 and P99) in units of hPa.

From Bärring and von Storch, 2005: see also BACC 2008.

Stockholm

Lund

Special application – assessing the lull wind conditions, leading to

insufficient energy harvest by wind mills in Germany,

winters 2008-2009

Weisse, pers. Comm.

Downscaling vs. “obs”

C=0,72

NCEP-based downscaling (black) and observations (red) of MetNo (Noer, pers comm)Monthly comparison of NCEP-

downscaling (in black) with analysed observed data (in red; Blechschmidt, 2008)

Bracegirdle, T. J. and S. L. Gray, 2008

Density of polar low genesis

Genesis in NCEP downscaling RCM simulation