Climate Dynamics

, Volume 23, Issue 3, pp 243–258

Effects of model resolution and subgrid-scale physics on the simulation of precipitation in the continental United States

  • J. P. Iorio
  • P. B. Duffy
  • B. Govindasamy
  • S. L. Thompson
  • M. Khairoutdinov
  • D. Randall
Article

DOI: 10.1007/s00382-004-0440-y

Cite this article as:
Iorio, J.P., Duffy, P.B., Govindasamy, B. et al. Climate Dynamics (2004) 23: 243. doi:10.1007/s00382-004-0440-y

Abstract

We analyze simulations of the global climate performed at a range of spatial resolutions to assess the effects of horizontal spatial resolution on the ability to simulate precipitation in the continental United States. The model investigated is the CCM3 general circulation model. We also preliminarily assess the effect of replacing cloud and convective parameterizations in a coarse-resolution (T42) model with an embedded cloud-system resolving model (CSRM). We examine both spatial patterns of seasonal-mean precipitation and daily time scale temporal variability of precipitation in the continental United States. For DJF and SON, high-resolution simulations produce spatial patterns of seasonal-mean precipitation that agree more closely with observed precipitation patterns than do results from the same model (CCM3) at coarse resolution. However, in JJA and MAM, there is little improvement in spatial patterns of seasonal-mean precipitation with increasing resolution, particularly in the southeast USA. This is because of the dominance of convective (i.e., parameterized) precipitation in these two seasons. We further find that higher-resolution simulations have more realistic daily precipitation statistics. In particular, the well-known tendency at coarse resolution to have too many days with weak precipitation and not enough intense precipitation is partially eliminated in higher-resolution simulations. However, even at the highest resolution examined here (T239), the simulated intensity of the mean and of high-percentile daily precipitation amounts is too low. This is especially true in the southeast USA, where the most extreme events occur. A new GCM, in which a cloud-resolving model (CSRM) is embedded in each grid cell and replaces convective and stratiform cloud parameterizations, solves this problem, and actually produces too much precipitation in the form of extreme events. However, in contrast to high-resolution versions of CCM3, this model produces little improvement in spatial patterns of seasonal-mean precipitation compared to models at the same resolution using traditional parameterizations.

Copyright information

© Springer-Verlag  2004

Authors and Affiliations

  • J. P. Iorio
    • 1
  • P. B. Duffy
    • 1
  • B. Govindasamy
    • 1
  • S. L. Thompson
    • 1
  • M. Khairoutdinov
    • 2
  • D. Randall
    • 2
  1. 1.Lawrence Livermore National LaboratoryUSA
  2. 2.Colorado State UniversityUSA