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.

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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


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

  • The basic atmospheric reconstruction; dynamical downscaling, spectral nudging, validation

  • Applications – storms, (waves), lead transport, run-off

  • Scenarios of plausible future change


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

Institut für Küstenforschung

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


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

Spectral nudging vs. standard formulation

Large scale

Medium scale

Large scale

Medium scale


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

Institut für Küstenforschung

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


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

Institut für Küstenforschung

I f K

Spectral nudging vs. standard formulation


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

Mean monthly

precipitation [mm/month]

for 1999.

NCEP

REMO

HIPOCAS meeting Madrid Atmospheric fields REMO 5.0 run GKSS Frauke Feser


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

Institut für Küstenforschung

I f K

Spectral nudging vs. standard formulation


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

Extreme wind speeds

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)


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

Institut für Küstenforschung

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


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

Lars Bärring, pers. comm., 2003


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

1955

1995

1955

Estimatedlead emissions

(from Pacyna and Pacyna, 2000)

1975


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

1995

Calculated depositions

deposition


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

Institut für Küstenforschung

I f K

model estimate


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

Hillmar Messal, 2003

Analysis REMO simulation difference


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

REMO simulation (forced with NCEP gobal re-analysis)

Arnt Pfizenmayer, pers. comm., 2003


Precipitation in the odra catchment

Precipitation in the Odra catchment

Hillmar Messal, pers. comm.


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

A1

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


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

Scenario for changing precipitation in summer at the end of the 21st century

Christensen and Christensen, 2003, nature

Change (%) in

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


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

Wind statistics, A2-scenario for 2070-2100SMHI RCAO

Ralf Weisse, 2003


Conclusions

Conclusions

  • 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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