Akperov, Mirseid, Rinke, Annette, Mokhov, Igor I., Matthes, Heidrun, Semenov, Vladimir A., Adakudlu, Muralidhar, Cassano, John, Christensen, Jens H., Dembitskaya, Mariya A., Dethloff, Klaus, Fettweis, Xavier, Glisan, Justin, Gutjahr, Oliver, Heinemann, Günther, Koenigk, Torben, Koldunov, Nikolay V., Laprise, René, Mottram, Ruth, Nikiéma, Oumarou, Scinocca, John F., Sein, Dmitry, Sobolowski, Stefan, Winger, Katja and Zhang, Wenxin (2018) Cyclone Activity in the Arctic From an Ensemble of Regional Climate Models (Arctic CORDEX). Journal of Geophysical Research: Atmospheres, 123 (5). pp. 2537-2554. DOI 10.1002/2017JD027703.

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Abstract

The ability of state‐of‐the‐art regional climate models to simulate cyclone activity in the Arctic is assessed based on an ensemble of 13 simulations from 11 models from the Arctic‐CORDEX initiative. Some models employ large‐scale spectral nudging techniques. Cyclone characteristics simulated by the ensemble are compared with the results forced by four reanalyses (ERA‐Interim, National Centers for Environmental Prediction‐Climate Forecast System Reanalysis, National Aeronautics and Space Administration‐Modern‐Era Retrospective analysis for Research and Applications Version 2, and Japan Meteorological Agency‐Japanese 55‐year reanalysis) in winter and summer for 1981–2010 period. In addition, we compare cyclone statistics between ERA‐Interim and the Arctic System Reanalysis reanalyses for 2000–2010. Biases in cyclone frequency, intensity, and size over the Arctic are also quantified. Variations in cyclone frequency across the models are partly attributed to the differences in cyclone frequency over land. The variations across the models are largest for small and shallow cyclones for both seasons. A connection between biases in the zonal wind at 200 hPa and cyclone characteristics is found for both seasons. Most models underestimate zonal wind speed in both seasons, which likely leads to underestimation of cyclone mean depth and deep cyclone frequency in the Arctic. In general, the regional climate models are able to represent the spatial distribution of cyclone characteristics in the Arctic but models that employ large‐scale spectral nudging show a better agreement with ERA‐Interim reanalysis than the rest of the models. Trends also exhibit the benefits of nudging. Models with spectral nudging are able to reproduce the cyclone trends, whereas most of the nonnudged models fail to do so. However, the cyclone characteristics and trends are sensitive to the choice of nudged variables.

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