era40 dynamical downscaling · institut für meteorologie dr. bodo ahrens und geophysik der...
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Dr. Bodo AhrensInstitut für Meteorologie und Geophysik derUniversität Wien
ERA40 Dynamical Downscaling
Bodo Ahrens, Alexander BeckInstitut für Meteorologie und Geophysik, Universität Wien
e-mail: [email protected]
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Dr. Bodo AhrensInstitut für Meteorologie und Geophysik derUniversität Wien
Motivation
● High-resolution Alpine climate description (daily, Dx ~ 10km)● Training input for climate impact models● Test-bed for ECHAM DDS
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Dr. Bodo AhrensInstitut für Meteorologie und Geophysik derUniversität Wien
Mesoscale Alpine Programme SOP: Sept. 7 to Nov. 15, 1999 \Bougeault et al 2001
FH analysis: ~6500 rain stations, no bias correction, daily/25km mesh size -> all data is interpolated to this mesh size
ERA40 (mesh size ~120km)
ALADIN (50km) ALADIN (12km)
MAP SOP precipitationFrei & Haeller (2001) analysis
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Dr. Bodo AhrensInstitut für Meteorologie und Geophysik derUniversität Wien
Sequence of hindcasts
• 30h hindcasts, 6h coupling time step• discarding the first 6h (model spin up)• one-way nesting e.g. 12km nest directly in 120km ERA40 => a scale jump of a factor of 10
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Dr. Bodo AhrensInstitut für Meteorologie und Geophysik derUniversität Wien
The problem: Optimal nesting strategy?
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Dr. Bodo AhrensInstitut für Meteorologie und Geophysik derUniversität Wien
Nesting StrategiesERA40 (~120km)
LACE (12km)8pt buffer(op. in ARP)
direct
LACE (12km)32pt buffer
dire
ct32
LACE (12km)8pt buffer,blending(climate mode for small scales)
blen
ding
LACE (12km)8pt buffer
50km nest8pt buffer
double
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Dr. Bodo AhrensInstitut für Meteorologie und Geophysik derUniversität Wien
Impact of Nesting ConfigurationFrei & Haeller (2001) analysis
direct double
bias:(mm/d)
doubleblendingdirect32directERA40
0.19 0.26 0.06 0.22
-1.03
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Dr. Bodo AhrensInstitut für Meteorologie und Geophysik derUniversität Wien
Resolution Effects
50km
direct (12km), but 50km orography
direct (12km)
26 Sep. 1999 precipitation
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Dr. Bodo AhrensInstitut für Meteorologie und Geophysik derUniversität Wien
12 km Nests
blendingdouble
direct direct32
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Dr. Bodo AhrensInstitut für Meteorologie und Geophysik derUniversität Wien
Statistics
SPREX: temporal mean of ratios of spatial field variancesSPRET: spatial mean of ratios of pixel time series variancesR^2_X: temporal mean of squared spatial field correlationsR^2_T: spatial mean of squared time series correlations
1day
⇒ other errors are more important than differences due to nesting strategy
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Dr. Bodo AhrensInstitut für Meteorologie und Geophysik derUniversität Wien
Pattern of R^2_X
Pattern of R^2_T
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Dr. Bodo AhrensInstitut für Meteorologie und Geophysik derUniversität Wien
Statistics
Performance or evaluation problem below 100km?
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Dr. Bodo AhrensInstitut für Meteorologie und Geophysik derUniversität Wien
Conclusions ● Precipitation patterns at 1d/100km scale are bet-
ter represented in ALADIN-12km than in ERA40-120km simulations.
● Nesting configuration not crucial despite the large resolution jump (factor 10), especially double nest-ing not necessary – “There are other problems!”
● Continuous blending (= spectral nudging) seems to be promising, but expensive!?
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Dr. Bodo AhrensInstitut für Meteorologie und Geophysik derUniversität Wien
OutlookDirect nesting => DDS, but no regional climate due to lack of memory!
0.5 step into “climate simulation”: Surface blending, i.e.relaxation of ISBA sfc. to TESSEL sfc.
Implementation and test by Jure C. (for MAP SOP):- 90% blending better than 97% or no blending (-> memory is good & ERA40 sfc assimilation too!)- 100% blending (no reinitialization) worst (died in a 1999 sim. -> climate ISBA, improved radiation scheme)
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Dr. Bodo AhrensInstitut für Meteorologie und Geophysik derUniversität Wien
NO vs 97% blending
Hydrol. Sim with WaSiM (500m,1h) in an Alpine watershed(2600km^2)
1999
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Dr. Bodo AhrensInstitut für Meteorologie und Geophysik derUniversität Wien
Why with ALADIN?
● Operational in Austria and most neighbors● Packaged and phased with ARPEGE/IFS and closely related with ARPEGE-CLIMATE – Will this prevail??