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Mirta Patarčić and Čedo Branković

Abstract

Various measures of forecast quality are analyzed for 2-m temperature seasonal forecasts over Europe from global and regional model ensembles for winter and summer seasons during the period 1991 to 2001. The 50-km Regional Climate Model (RegCM3) is used to dynamically downscale nine-member ensembles of ECMWF global experimental seasonal forecasts. Three sets of RegCM3 experiments with different soil moisture initializations are performed: the RegCM3 default initial soil moisture, initial soil moisture taken from ECMWF seasonal forecasts, and initial soil moisture obtained from RegCM3 ECMWF interim Re-Analysis (ERA-Interim)-driven integrations (RegCM3 climatology). Both deterministic and probabilistic skill metrics are estimated.

The better-resolved spatial scales in near-surface temperature by RegCM3 do not necessarily lead to the improved regional model skill in the regions where systematic errors are large. The impact of initial soil moisture on RegCM3 forecast skill is seen in summer in the southern part of the integration domain. When regional model soil moisture was initialized from ECMWF seasonal forecasts, systematic errors were reduced and deterministic skill was enhanced relative to the other RegCM3 experiments. The Brier skill score for rare cold anomalies in this experiment is comparable to that of the global model, whereas in other experiments it is significantly smaller than in global model.

There is no major impact of soil moisture initialization on forecast skill in winter. However, some significant improvements in RegCM3 probabilistic skill scores for positive anomalies in winter are found in the central part of the domain where RegCM3 systematic errors are smaller than in global model.

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Čedo Branković and T. N. Palmer

Abstract

Results from a set of nine-member ensemble seasonal integrations with a T63L19 version of the European Centre for Medium-Range Weather Forecasts (ECMWF) model are presented. The integrations are made using observed specified sea surface temperature (SST) from the 5-year period 1986–90, which included both warm and cold El Niño–Southern Oscillation (ENSO) events. The distributions of ensemble skill scores and internal ensemble consistency are studied. For years in which ENSO was strong, the model generally exhibits a relative high skill and high consistency in the Tropics. In the northern extratropics, the highest skill and consistency are found for the northern Pacific–North American region in winter, whereas for the northern Atlantic–European region the spring season appears to be both skillful and consistent. For years in which ENSO was weak, the distributions of ensemble skill and consistency are relatively broad and no clear distinction between Tropics and extratropics can be made.

Applying a t test to interannual fluctuations over various tropical and extratropical regions, estimates of a minimum useful ensemble size are made. Explicit calculations are done with ensemble size varying between three and nine members; estimates for larger sizes are made by extrapolating the t values. Based on an analysis of 2-m temperature and precipitation, the use of relatively large (approximately 20 members) ensembles for extratropical predictions is likely to be required; in the Tropics, smaller-sized ensembles may be adequate during years in which ENSO is strong, particularly for regions such as the Sahel.

The role of the SST forcing in a seasonal timescale ensemble is to bias the probability distribution function (PDF) of atmospheric states. Such PDFs can, in addition, be a convenient way of condensing a vast amount of data usually obtained from ensemble predictions. Interannual variability in PDFs of monsoon rainfall and regional geopotential height probabilities is discussed.

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Čedo Branković, Blaženka Matjačić, Stjepan Ivatek-Šahdan, and Roberto Buizza

Abstract

Dynamical downscaling has been applied to global ensemble forecasts to assess its impact for four cases of severe weather (precipitation and wind) over various parts of Croatia. It was performed with the Croatian 12.2-km version of the Aire Limitée Adaptation Dynamique Développement International (ALADIN) limited-area model, nested in the ECMWF TL255 (approximately 80 km) global ensemble prediction system (EPS). The 3-hourly EPS output was used to force the ALADIN model over the central European/northern Mediterranean domain.

Results indicate that the identical clustering algorithm may yield differing results when applied to either global or to downscaled ensembles. It is argued that this is linked to the fact that a downscaled, higher-resolution ensemble resolves more explicitly small-scale features, in particular those strongly influenced by orographic forcing. This result has important implications in limited-area ensemble prediction, since it implies that downscaling may affect the interpretation or relevance of the global ensemble forecasts; that is, it may not always be feasible to make a selection (or a subset) of global lower-resolution ensemble members that might be representative of all possible higher-resolution evolution scenarios.

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Ivan Güttler, Igor Stepanov, Čedo Branković, Grigory Nikulin, and Colin Jones

Abstract

The hydrostatic regional climate model RCA, version 3 (RCA3), of the Swedish Meteorological and Hydrological Institute was used to dynamically downscale ERA-40 and the ECMWF operational analysis over a 22-yr period. Downscaling was performed at four horizontal resolutions—50, 25, 12.5, and 6.25 km—over an identical European domain. The model-simulated precipitation is evaluated against high-resolution gridded observational precipitation datasets over Switzerland and southern Norway, regions that are characterized by complex orography and distinct climate regimes.

RCA3 generally overestimates precipitation over high mountains: during winter and summer over Switzerland and during summer over central-southern Norway. In the summer, this is linked with a substantial contribution of convective precipitation to the total precipitation errors, especially at the coarser resolutions (50 and 25 km). A general improvement in spatial correlation coefficients between simulated and observed precipitation is observed when the horizontal resolution is increased from 50 to 6 km. The 95th percentile spatial correlation coefficients during winter are much higher for southern Norway than for Switzerland, indicating that RCA3 is more successful at reproducing a relatively simple west-to-east precipitation gradient over southern Norway than a much more complex and variable precipitation distribution over Switzerland. The 6-km simulation is not always superior to the other simulations, possibly indicating that the model dynamical and physical configuration at this resolution may not have been optimal. However, a general improvement in simulated precipitation with increasing resolution supports further use and application of high spatial resolutions in RCA3.

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