How Skillful Are the European Subseasonal Predictions of Wind Speed and Surface Temperature?

Author:

Goutham Naveen12ORCID,Plougonven Riwal2,Omrani Hiba1,Parey Sylvie1,Tankov Peter3,Tantet Alexis2,Hitchcock Peter4,Drobinski Philippe2

Affiliation:

1. a EDF Laboratory Paris-Saclay, Palaiseau, France

2. b Laboratoire de Météorologie Dynamique-IPSL, Ecole Polytechnique, Institut Polytechnique de Paris, ENS, PSL Research University, Sorbonne Université, CNRS, France

3. c CREST/ENSAE, Institut Polytechnique de Paris, Palaiseau, France

4. d Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, New York

Abstract

Abstract Subseasonal forecasts of 100-m wind speed and surface temperature, if skillful, can be beneficial to the energy sector as they can be used to plan asset availability and maintenance, assess risks of extreme events, and optimally trade power on the markets. In this study, we evaluate the skill of the European Centre for Medium-Range Weather Forecasts’ subseasonal predictions of 100-m wind speed and 2-m temperature. To the authors’ knowledge, this assessment is the first for the 100-m wind speed, which is an essential variable of practical importance to the energy sector. The assessment is carried out on both forecasts and reforecasts over European domain gridpoint wise and also by considering several spatially averaged domains, using several metrics to assess different attributes of forecast quality. We propose a novel way of synthesizing the continuous ranked probability skill score. The results show that the skill of the forecasts and reforecasts depends on the choice of the climate variable, the period of the year, and the geographical domain. Indeed, the predictions of temperature are better than those of wind speed, with enhanced skill found for both variables in the winter relative to other seasons. The results also indicate significant differences between the skill of forecasts and reforecasts, arising mainly due to the differing ensemble sizes. Overall, depending on the choice of the geographical domain and the forecast attribute, the results show skillful predictions beyond 2 weeks, and in certain cases, up to 6 weeks for both variables, thereby encouraging their implementation in operational decision-making.

Funder

Programme d'Investissement d'Avenir

Publisher

American Meteorological Society

Subject

Atmospheric Science

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