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

Results: MSLP DJF HadAM3PNCEPHadAM3P-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 T850 T850 HadAM3PNCEPHadAM3P-NCEP St.dev(T850)

Results: Summer Q850 (g/kg) Q850 HadAM3PNCEPHadAM3P-NCEP St.dev(Q850)

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 clusters, transition probabilities –Inter-relationships: Good correspondence for CPs conditional to heavy precipitation. Frequency errors (Sampling?). HadAM3P NCEP/OBS 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: – 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)?