Evaluation of continental precipitation in 20th century climate simulations: The utility of multimodel statistics

In support of the Intergovernmental Panel on Climate Change (IPCC), simulations of 20th century climate have been performed recently with some 20 global coupled ocean‐atmosphere models. In view of its central importance for biological and socioeconomic systems, model‐simulated continental precipitation is evaluated relative to three observational estimates at both global and regional scales. Many models are found to display systematic biases, deviating markedly from the observed spatial variability and amplitude/phase of the seasonal cycle. However, the pointwise ensemble mean of all the models usually shows better statistical agreement with the observations than does any single model. Deficiencies of current models that may be responsible for the simulated precipitation biases as well as possible reasons for the improved estimate afforded by the multimodel ensemble mean are discussed. Implications of these results for water resource managers also are briefly addressed.

[1]  Mark M. Morrissey,et al.  The Global Precipitation Climatology Project , 2007 .

[2]  S. Swenson,et al.  Climate model biases in seasonality of continental water storage revealed by satellite gravimetry , 2006 .

[3]  A. V. Vecchia,et al.  Global pattern of trends in streamflow and water availability in a changing climate , 2005, Nature.

[4]  K. Mo,et al.  Impact of Model Resolution on the Prediction of Summer Precipitation over the United States and Mexico , 2005 .

[5]  P. Wilcock,et al.  Characteristic dimensions of the step‐pool bed configuration: An experimental study , 2005 .

[6]  D. Lawrence,et al.  Regions of Strong Coupling Between Soil Moisture and Precipitation , 2004, Science.

[7]  K. Taylor,et al.  An Appraisal of Coupled Climate Model Simulations , 2004 .

[8]  K. Trenberth,et al.  The changing character of precipitation , 2003 .

[9]  K. Taylor,et al.  An overview of results from the Coupled Model Intercomparison Project , 2003 .

[10]  M. Noguer,et al.  Climate change 2001: The scientific basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change , 2002 .

[11]  K. Taylor.  Summarizing multiple aspects of model performance in a single diagram , 2001 .

[12]  G. Boer,et al.  CMIP1 evaluation and intercomparison of coupled climate models , 2001 .

[13]  M. Kanamitsu,et al.  The Comparison of Two Merged Rain Gauge–Satellite Precipitation Datasets , 2000 .

[14]  P. Jones,et al.  Representing Twentieth-Century Space-Time Climate Variability. Part II: Development of 1901-96 Monthly Grids of Terrestrial Surface Climate , 2000 .

[15]  P. Xie,et al.  Global Precipitation: A 17-Year Monthly Analysis Based on Gauge Observations, Satellite Estimates, and Numerical Model Outputs , 1997 .

[16]  Gilbert A. Valverde,et al.  An Overview Of Results , 1997 .

[17]  C. Schönwiese,et al.  Overview of Results , 1997 .

[18]  J. Janowiak,et al.  The Global Precipitation Climatology Project (GPCP) combined precipitation dataset , 1997 .

[19]  Fuzhong Weng,et al.  An eight-year (1987-1994) time series of rainfall, clouds, water vapor, snow cover, and sea ice derived from SSM/I measurements , 1996 .

[20]  S. Grotch,et al.  The impact of horizontal resolution on moist processes in the ECMWF model , 1995 .

[21]  S. Hameed,et al.  Harmonic analysis of the seasonal cycle in precipitation over the United States: a comparison between observations and a general circulation model , 1989 .

[22]  Phillip A. Arkin.  The Global Precipitation Climatology Project , 1989 .

[23]  R. Sausen,et al.  Coupled ocean-atmosphere models with flux correction , 1988 .