Incremental correction for the dynamical downscaling of ensemble mean atmospheric fields

TitleIncremental correction for the dynamical downscaling of ensemble mean atmospheric fields
Publication TypeJournal Article
Year of Publication2013
AuthorsYoshimura K, Kanamitsu M
JournalMonthly Weather Review
Date Published2013/09
Type of ArticleArticle
ISBN Number0027-0644
Accession NumberWOS:000323655400009
KeywordsData assimilation; Ensembles; General circulation; internal variability; model; models; parameterization; reanalysis; Regional models; scale; Seasonal forecasting; simulations

This research was motivated by the need for an improved method compared to the conventional brute-force approach to ensemble downscaling. That method simply applies dynamical downscaling to each ensemble member. It obtains a reliable forecast by taking the ensemble average of all the downscaled ensemble members. This approach, although straightforward, has a problem in that the computational cost is too large for an operational environment. Herein a method for downscaling ensemble mean forecasts is proposed. Although this method does not provide probabilistic forecasts, it will provide the regional-scale detail at minimum cost. In this product, all of the predicted parameters are dynamically and physically consistent (i.e., most likely to occur on a seasonal time scale). It is believed that such a product has great utility for regional climate forecast and application products. The method applies a correction to one of the global forecast members in such a way that the seasonal mean is equal to that of the ensemble mean, and it then downscales the corrected global forecast. This method was tested for a 140-yr period by using the Twentieth-Century Reanalysis dataset, which is a product of ensemble Kalman filtering data assimilation. Use of the method clearly improves the downscaling skill compared to the case of using only a single member; the skill becomes equivalent to that achieved when between two and six members are used directly.

Short TitleMon. Weather Rev.
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