Climate Dynamics

, Volume 37, Issue 11, pp 2271–2287

Evaluating IPCC AR4 cool-season precipitation simulations and projections for impacts assessment over North America

  • Stephanie A. McAfee
  • Joellen L. Russell
  • Paul J. Goodman
Article

DOI: 10.1007/s00382-011-1136-8

Cite this article as:
McAfee, S.A., Russell, J.L. & Goodman, P.J. Clim Dyn (2011) 37: 2271. doi:10.1007/s00382-011-1136-8

Abstract

General circulation models (GCMs) have demonstrated success in simulating global climate, and they are critical tools for producing regional climate projections consistent with global changes in radiative forcing. GCM output is currently being used in a variety of ways for regional impacts projection. However, more work is required to assess model bias and evaluate whether assumptions about the independence of model projections and error are valid. This is particularly important where models do not display offsetting errors. Comparing simulated 300-hPa zonal winds and precipitation for the late 20th century with reanalysis and gridded precipitation data shows statistically significant and physically plausible associations between positive precipitation biases across all models and a marked increase in zonal wind speed around 30°N, as well as distortions in rain shadow patterns. Over the western United States, GCMs project drier conditions to the south and increasing precipitation to the north. There is a high degree of agreement between models, and many studies have made strong statements about implications for water resources and about ecosystem change on that basis. However, since one of the mechanisms driving changes in winter precipitation patterns appears to be associated with a source of error in simulating mean precipitation in the present, it suggests that greater caution should be used in interpreting impacts related to precipitation projections in this region and that standard assumptions underlying bias correction methods should be scrutinized.

Keywords

PrecipitationGeneral circulation model (GCM)BiasStorm track

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Stephanie A. McAfee
    • 1
    • 2
  • Joellen L. Russell
    • 1
  • Paul J. Goodman
    • 1
  1. 1.Department of GeosciencesThe University of ArizonaTucsonUSA
  2. 2.The Wilderness SocietyAnchorageUSA