Proceedings - C-SRNWP Project

Currently the size of the super ensemble is limited to 40 members, because only two sets of
integrations at 00 and 12 UTC are undertaken.
Fig. 1 shows the integration areas used for each of the models. Horizontal resolutions of the
used configurations are about 25 km or 0.25º latxlon. Forty levels in vertical are used for each
of them. Figure 2 shows the common Europe-North Atlantic area where the forecast fields are
interpolated with a resolution of 0.25º and 40 levels. The number of grid points is so
480x184x40. The computer time requirements for this exercise are high, and the integration
uses a substantial part of the CRAY X1E vector machine with 16nodes with 8MSP’s each,
equivalent to a 2.4 Tf peak (sustained performance about 800 Gf).
Part of the postprocessing is undertaken in a couple of enhanced PCs with Linux. The postprocessing
makes wide use of the ECMWF Metview package and is additional local
developments.
To monitor the system in real time a website has been developed (accessible by the time being
only from the INM intranet) where both deterministic and probabilistic products are shown in
real time. An example of it is the stamps chart of model by boundaries for geopotential height
and temperature of 500 hPa, figure 3. It is internally used for monitoring when the completion
of each member run has been achieved. Figure 4 presents an example of probability maps of
2m temperature 24 h. trend, and figure 5 shows a deterministic output where the ensemble
mean and the spread of 500 hPa height for a concrete projection are presented. An example of
probability maps for 6h accumulated precipitation higher than >= 1, 5, 10 and 20mm
thresholds, and the verifying map is given in figure 6. Also, 10m wind speed probabilistic
maps and EPSgrams are regularly prepared.
3. Objetive Verification
Verification of the twice a day ensemble runs for the period January to June 2006 both against
observations and ECMWF analyses are undertaken. Results are computed to check, on one
hand, the ensemble calibration for the synoptic variables Z500, T500, Pmsl; and, on the other
hand, the ensemble response to binary events like 10m surface wind and 6h and 24h
accumulated precipitation higher than specific thresholds.
The performed verifications presented in figure 7 show the Spread-skill diagram for the 6 to
72 hour 500 hPa forecasts and the rank histogram for the 24 hours Geopotential Height of 500
hPa forecast. They are computed against ECMWF analyses and use the EWGLAM reference
synoptic network of surface and upper air observations.
For the synoptic variables (here Z500) the spread-skill and rank histograms against
observations show that the ensemble is under-dispersive and a bit under-forecasting. The
same against ECMWF analysis is very good.
The evolution of Bias and RMSE with forecast length for all members and for the ensemble
mean are computed for the model synoptic variables Z500, T500 and Msl Presure, although
not shown. The bias and RMSE of the ensemble mean are lower than the each member ones.
An example of the response of the system to binary events is given in figure 8, where for 24
hours accumulated precipitation a stamp map of reliability and sharpness, ROC and ROC area
scores, temporal evolution of the Brier Skill score, and Relative value diagrams, versus
observations and ECMWF analyses is presented. Results that expands also to the other
verified surface variables indicate that 24h accumulated precipitation against observations
(top) show medium/quite good reliability and good resolution, degrading with threshold
(clearly) and forecast length, being much better the verification against ECMWF analyses.
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