4.6 Article

Effects of spatial resolution in the simulation of daily and subdaily precipitation in the southwestern US

期刊

JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
卷 118, 期 14, 页码 7591-7605

出版社

AMER GEOPHYSICAL UNION
DOI: 10.1002/jgrd.50590

关键词

Extreme precipitation; Regional Climate Modeling; Southwestern US precipitation

资金

  1. Department of Energy (DOE) [DE-SC0001172]
  2. National Science Foundation (NSF) [1038938]
  3. Direct For Biological Sciences
  4. Division Of Environmental Biology [1038651] Funding Source: National Science Foundation
  5. Directorate For Geosciences
  6. Division Of Earth Sciences [1038938] Funding Source: National Science Foundation

向作者/读者索取更多资源

We evaluate the effects of spatial resolution on the ability of a regional climate model to reproduce observed extreme precipitation for a region in the Southwestern United States. A total of 73 National Climate Data Center observational sites spread throughout Arizona and New Mexico are compared with regional climate simulations at the spatial resolutions of 50km and 10km for a 31 year period from 1980 to 2010. We analyze mean, 3-hourly and 24-hourly extreme precipitation events using WRF regional model simulations driven by NCEP-2 reanalysis. The mean climatological spatial structure of precipitation in the Southwest is well represented by the 10km resolution but missing in the coarse (50km resolution) simulation. However, the fine grid has a larger positive bias in mean summer precipitation than the coarse-resolution grid. The large overestimation in the simulation is in part due to scale-dependent deficiencies in the Kain-Fritsch convective parameterization scheme that generate excessive precipitation and induce a slow eastward propagation of the moist convective summer systems in the high-resolution simulation. Despite this overestimation in the mean, the 10km simulation captures individual extreme summer precipitation events better than the 50km simulation. In winter, however, the two simulations appear to perform equally in simulating extremes.

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