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)?