A dynamical reconstruction of detailed atmospheric and related regional variability 1958 2000
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A dynamical reconstruction of detailed atmospheric and related regional variability, 1958-2000. Hans von Storch, Frauke Feser, Ralf Weisse, Arnt Pfizenmayer, Katja Woth, Insa Meinke, Mariza Cabral, Charlotte Hagner, Hilmar Messal

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A dynamical reconstruction of detailed atmospheric and related regional variability 1958 2000

A dynamical reconstruction of detailed atmospheric and related regional variability, 1958-2000.

Hans von Storch, Frauke Feser, Ralf Weisse, Arnt Pfizenmayer, Katja Woth, Insa Meinke, Mariza Cabral, Charlotte Hagner, Hilmar Messal

Institute for Coastal Research, GKSS Research Center, Geesthacht, Germany

Wroclaw, 27. June 2003



Institut für Küstenforschung spectral nudging, validation

I f K

Concept of Dynamical Downscaling

RCM

Physiographic detail

3-d vector of state

Known large scale state

projection of full state on large-scale scale

Large-scale (spectral) nudging


Spectral nudging vs. standard formulation spectral nudging, validation

Large scale

Medium scale

Large scale

Medium scale


Institut für Küstenforschung spectral nudging, validation

I f K

Spectral nudging vs. standard formulation

Similarity of zonal wind at 850 hPa between simulations and NCEP re-analyses

large scales

medium scales

standard formulation large-scale nudging


Institut für Küstenforschung spectral nudging, validation

I f K

Spectral nudging vs. standard formulation


Mean monthly spectral nudging, validation

precipitation [mm/month]

for 1999.

NCEP

REMO

HIPOCAS meeting Madrid Atmospheric fields REMO 5.0 run GKSS Frauke Feser


Institut für Küstenforschung spectral nudging, validation

I f K

Spectral nudging vs. standard formulation


Extreme wind speeds spectral nudging, validation

Southern North Sea

Feser, pers. comm.

DWD

REMO

20-year return values of wind speed,

based on daily 1992-97 data (color codes)

plus from station data in NL (numbers in black)


Institut für Küstenforschung spectral nudging, validation

I f K

Skill in representing marine winds

significant wave height

[days]

wave direction

[days]

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

Gerd Gayer, pers. comm., 2001


Lars Bärring, pers. comm., 2003 spectral nudging, validation


1955 spectral nudging, validation

1995

1955

Estimatedlead emissions

(from Pacyna and Pacyna, 2000)

1975


1995 spectral nudging, validation

Calculated depositions

deposition


Institut für Küstenforschung spectral nudging, validation

I f K

model estimate


Hillmar Messal, 2003 spectral nudging, validation

Analysis REMO simulation difference


REMO simulation (forced with NCEP gobal re-analysis) spectral nudging, validation

Arnt Pfizenmayer, pers. comm., 2003


Precipitation in the odra catchment
Precipitation in the Odra catchment spectral nudging, validation

Hillmar Messal, pers. comm.


A1 spectral nudging, validation

A world of rapid economic growth and rapid

introduction of new and more efficienttechnology.

A very heterogeneous world with an emphasis on

family values and local traditions.

A world of “dematerialization” and introduction of

clean technologies.

A world with an emphasis on local solutions to

economic and environmental sustainability.

“ business as usual ” scenario (1992).

A2

B1

B2

Institut für Küstenforschung

IS92a

I f K

“SRES” ScenariosSRES = IPCC Special Report on Emissions Scenarios

IPCC, 2001


Scenario for changing precipitation in summer spectral nudging, validationat the end of the 21st century

Christensen and Christensen, 2003, nature

Change (%) in

mean summer precipitation total in 99% quantile 5-daily precipitation amounts (rare events)


Wind statistics, A2-scenario for 2070-2100 spectral nudging, validationSMHI RCAO

Ralf Weisse, 2003


Conclusions
Conclusions spectral nudging, validation

  • Multi-decade reconstruction of hourly weather on 50 km grid in all of Europe available, 1958-2002.

  • Several aspects checked but far from complete validation. Wind over the sea ok. Broad features of precip, cloudiness ok as well, but other quantities unknown.

  • Data (wind, precip, temp ….) may be used to reconstruct various other environmental conditions, such as ocean waves, storm surges, flooding, extreme events, long range transport of matter.

  • Data freely available for other research groups.

  • Polish groups welcome to validate, and use, data in particular with respect to Polish territory.


Reconstruction of past decades and longer regional and local environmental conditions relevant
Reconstruction of past decades (and longer) regional and local environmental conditions relevant …

  • For determination of extreme events (frequency (Poison?), intensity) in terms of weather and impact variables. Preparation of adequate adaptation measures. Minimizing weather related risks.

  • Basis of reconstruction of historical climate (transfer functions; proxy data; historical data).

  • A posteriori analysis of past political regulations (example: lead, but also: flood protection).

  • Determination of range of „normal“ variations, in order to discriminate between natural climate variability and man-made climate change („detection and attribution“).


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