Simulation of Northeast U.S. Extreme Precipitation and Its Associated Circulation by CMIP5 Models
Historical simulations from 14 models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) are evaluated for their ability to reproduce observed precipitation in the northeastern United States and its associated circulation, with particular emphasis on extreme (top 1%) preci...
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Veröffentlicht in: | Journal of climate 2020-11, Vol.33 (22), p.9817-9834 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Historical simulations from 14 models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) are evaluated for their ability to reproduce observed precipitation in the northeastern United States and its associated circulation, with particular emphasis on extreme (top 1%) precipitation. The models are compared to observations in terms of the spatial variations of extreme precipitation, seasonal cycles of precipitation and extreme precipitation frequency and intensity, and extreme precipitation circulation regimes. The circulation regimes are identified using k-means clustering of 500-hPa geopotential heights on extreme precipitation days, in both observations and in the models. While all models capture an observed northwest-to-southeast gradient of precipitation intensity (reflected in the top 1% threshold), there are substantial differences from observations in the magnitude of the gradient. These differences tend to be more substantial for lower-resolution models. However, regardless of resolution, and despite a bias toward too-frequent precipitation, many of the models capture the seasonality of observed daily precipitation intensity, and the approximate magnitude and seasonality of observed extreme precipitation intensity. Many of the simulated extreme precipitation circulation patterns are visually similar to the set of observed patterns. However, the location and magnitude of specific troughs and ridges within the patterns, as well as the seasonality of the patterns, may differ substantially from the observed corresponding patterns. A series of metrics is developed based on the observed regional characteristics to facilitate comparison between models. |
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ISSN: | 0894-8755 1520-0442 |
DOI: | 10.1175/JCLI-D-19-0757.1 |