A COMPARISON OF THE NCEP-NCAR REANALYSIS PRECIPITATION AND THE GPCP RAIN GAUGE-SATELLITE COMBINED DATASET WITH OBSERVATIONAL ERROR CONSIDERATIONS

The Global Precipitation Climatology Project (GPCP) has released month ly mean estimates of precipitation that comprise gauge observations an d satellite-derived precipitation estimates. Estimates of standard ran dom error for each month at each grid location are also provided in th is data release. One of the primary intended uses of this dataset is t he validation of climatic-scale precipitation fields that are produced by numerical models. Nearly coincident with this dataset development, the National Centers for Environmental Prediction and the National Ce nter for Atmospheric: Research have joined in a cooperative effort to reanalyze meteorological fields from the present back to the 1940s usi ng a fixed state-of-the-art data assimilation system and large input d atabase. In this paper, monthly accumulations of reanalysis precipitat ion are compared with the GPCP combined rain gauge-satellite dataset o ver the period 1988-95. A unique feature of this comparison is the use of standard error estimates that are contained in the GPCP combined d ataset. These errors are incorporated into the comparison to provide m ore realistic assessments of the reanalysis model performance than cou ld be attained by using only the mean fields. Variability on timescale s from intraseasonal to interannual are examined between the GPCP and reanalysis precipitation. While the representation of large-scale feat ures compares well between the two datasets, substantial differences a re observed on regional scales. This result is not unexpected since pr esent-day data assimilation systems are not designed to incorporate ob servations of precipitation. Furthermore, inferences of deficiencies i n the reanalysis precipitation should nor be projected to other fields in which observations have been assimilated directly into the reanaly sis model.