objective / approach
Post on 05-Feb-2016
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D13 Summary:
Recommendations on the most reliable predictor variables and evaluation of inter-relationships
Objective / Approach
Qualify the accuracy of predictors
–> Criterion for the „robust-ness“ in methods. (D16)
Accuracy of inter-relationships
–> Benchmark to assess stationarity
Compare GCM against NCEP– Seasonal mean– Daily standard deviation– Inter-relationships
Common key predictors
ETH MSLP, Z, T, Q, @850, 700, 500 (Europe, NA)daily standard deviation
Method- and region-specific predictors
UEA PCs seasonal MSLP (variance and patterns)
CNRS CPs (Z@700). Precip inter-relationships
ARPA-SMR PCs seasonal MSLP and Z500. Blocking.
ADGB Z, Vg @500, rel. hum. @700 hPa, single GPs
DMI Vorticity (based on MSLP).
ETH Daily precipitation statistics.
USTUTT-IWS Moisture flux, diverg., vorticity.; CPs of MSLP.
AUTH CPs (Z@500, 1000-500 Thickness).
http://www.iac.ethz.ch/staff/freich/download/STARDEX/D13_web/
Results: MSLPD
JF
HadAM3P NCEP HadAM3P-NCEP
JJA
Comparison to earlier Model Versions
Icelandic Low:HadCM2: too shallow
(10 hPa)HadAM3P:too deep
(4 hPa)
NW Europe Westerlies:HadCM2: too weak HadAM3P:too strong
Results: Summer T850T
850
HadAM3P NCEP HadAM3P-NCEP
St.
dev
(T85
0)
Results: Summer Q850 (g/kg)Q
85
0
HadAM3P NCEP HadAM3P-NCEP
St.
dev
(Q8
50)
Results for Specific Predictors
• AUTH: – Good representation of frequency in cyclonic and anticyclonic CPs.
in Greece. – Cyclones travel too far south. – Thickness errors in summer gives too large within-CP variability.
• ADGB:– Geopotential and geostrophic wind pdfs are realistic– Potential problems with relative humidity in summer avoided by
choice of northern grid point.
• DMI:– Vorticity based on MSLP is noisy in NCEP.– Use grid-point MSLP as predictor instead.
Results for Specific Predictors
• ETH: – GCM captures coarse pattern of P intensity / frequency in Alps
better than NCEP.– No obvious effects from GCM circulation errors.
• U-STUTT:– Lower-tropospheric (westerly) moisture flux overestimated in winter
and underestimated in summer.
DJF JJA
Results for Specific Predictors
• UEA and ARPA-SMR: – Principal Components of MSLP, Z500, T850– Good correspondence in # of significant components and explained
variance (seasonal variation).– Differences in patterns larger in summer. (Sampling uncertainty?)
Results for Specific Predictors
• CNRS-INLN:– Daily CPs (Z@700), clusters, transition probabilities– Inter-relationships: Good correspondence for CPs conditional to
heavy precipitation. Frequency errors (Sampling?).
Ha
dA
M3
PN
CE
P/O
BS
35% 30% 35%
37% 34% 29%
Conclusions
• In winter HadAM3P:– represents continental-scale predictors better than earlier model
versions.– has too strong westerlies and underestimates variance (cyclone
activity). Error compensation in downscaling ?
• In summer HadAM3P:– has large biases for lower tropospheric temperature, temperature
variability and humidity – Concern with reliability over Southern Europe? Careful with single
grid points?
• For other seasons see Archive of Figures:– http://www.iac.ethz.ch/staff/freich/download/
STARDEX/D13_web/
– To bee transferred to UEA
Finalisation of D13
• Amendments of synthesis report so far (Version 2):– New figure added illustrating problems in summer– Indicate potential problems with NCEP humidity– References on testing GCM inter-relationships– New partner report from CNRS-INLN included
• Additional comments?– Summary table, qualifying reliability: high, medium, low
• Inclusion of other ensemble members?
• All potential predictors covered ?
• Further partner reports / extensions (inter-relationships)?
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