Validation of mesoscale precipitation in the NCEP reanalysis using a new gridcell dataset for the northwestern United States

Precipitation fields from the National Centers for Environmental Prediction (NCEP) reanalysis are validated with high-resolution, gridded precipitatio n observations over Oregon and Washington. The NCEP reanalysis is thought o f as a proxy for an ideal GCM that nearly perfectly represents the synoptic -scale pressure, temperature, and humidity but does not resolve the complex topography of this region. The authors' main goal is to understand how use ful precipitation fields from such a model are for estimating temporal vari ability in local precipitation. The gridded observations represent area-ave raged precipitation on a 50-km grid and have daily temporal resolution. The y are calculated with a newly developed scheme, which explicitly takes into account the effect of the topography on precipitation. This gridding metho d profits from the already existing, high-resolution climatologies for the monthly mean precipitation in the United States, obtained from the precipit ation-Elevation Regressions on Independent Slopes Model (PRISM), by using t hese climatologies for calibration. The estimation of daily precipitation o n scales as small as 4 km is also discussed. The reanalysis captures well p recipitation amounts and month-to-month variability on spatial scales of ab out 500 km or three grid cells, which indicates a good performance of the p recipitation parameterization scheme. On smaller spatial scales the NCEP re analysis has systematic biases, which can be mainly attributed to the poor representation of the topography but nevertheless can be used to reconstruc t the temporal variability of local precipitation on daily to yearly timesc ales. This suggests that GCM precipitation might be a good predictor for st atistical downscaling techniques.