Can climate models represent the precipitation associated with extratropical cyclones?

Article


Hawcroft, Matthew K., Shaffrey, Len C., Hodges, Kevin I. and Dacre, Helen F.. 2016. "Can climate models represent the precipitation associated with extratropical cyclones?" Climate Dynamics. 47 (3), pp. 679-695. https://doi.org/10.1007/s00382-015-2863-z
Article Title

Can climate models represent the precipitation associated with extratropical cyclones?

ERA Journal ID1962
Article CategoryArticle
AuthorsHawcroft, Matthew K. (Author), Shaffrey, Len C. (Author), Hodges, Kevin I. (Author) and Dacre, Helen F. (Author)
Journal TitleClimate Dynamics
Journal Citation47 (3), pp. 679-695
Number of Pages17
Year2016
PublisherSpringer
Place of PublicationGermany
ISSN0930-7575
1432-0894
Digital Object Identifier (DOI)https://doi.org/10.1007/s00382-015-2863-z
Web Address (URL)https://link.springer.com/article/10.1007%2Fs00382-015-2863-z
Abstract

Extratropical cyclones produce the majority of precipitation in many regions of the extratropics. This study evaluates the ability of a climate model, HiGEM, to reproduce the precipitation associated with extratropical cyclones. The model is evaluated using the ERA-Interim reanalysis and GPCP dataset. The analysis employs a cyclone centred compositing technique, evaluates composites across a range of geographical areas and cyclone intensities and also investigates the ability of the model to reproduce the climatological distribution of cyclone associated precipitation across the Northern Hemisphere. Using this phenomena centred approach provides an ability to identify the processes which are responsible for climatological biases in the model. Composite precipitation intensities are found to be comparable when all cyclones across the Northern Hemisphere are included. When the cyclones are filtered by region or intensity, differences are found, in particular, HiGEM produces too much precipitation in its most intense cyclones relative to ERA-Interim and GPCP. Biases in the climatological distribution of cyclone associated precipitation are also found, with biases around the storm track regions associated with both the number of cyclones in HiGEM and also their average precipitation intensity. These results have implications for the reliability of future projections of extratropical precipitation from the model

Keywordsprecipitation, extratropical cyclones, climate models, HiGEM, reanalysis, remote sensing data
ANZSRC Field of Research 2020419999. Other environmental sciences not elsewhere classified
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Byline AffiliationsUniversity of Reading, United Kingdom
Institution of OriginUniversity of Southern Queensland
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