HR: 1340h
AN: A53A-0868    [Abstracts]
TI: Impact of Precipitation Observations on Regional Climate Simulations
AU: * Nunes, A M
EM: anunes@ucsd.edu
AF: Scripps Institution of Oceanography, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0224 United States
AU: Roads, J O
EM: jroads@ucsd.edu
AF: Scripps Institution of Oceanography, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0224 United States
AU: Kanamitsu, M
EM: mkanamitsu@ucsd.edu
AF: Scripps Institution of Oceanography, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0224 United States
AB: We seek the improvement of regional downscaling of large-scale analyses, aiming particularly at hydrological and energy budget consistency for improving regional climate analyses and forecasts. Currently available reanalyses (NCEP/NCAR Reanalysis, NCEP/DOE Reanalysis, ERA-15, ERA-40 and others) provide reasonably accurate analysis of atmospheric states, but the hydrological component of such analyses is weak, and the energy budget still suffers from a systematic tendency error that makes it difficult to close the budget equation. The weakest component of those reanalyses is the model-produced precipitation, which has very large errors compared to observations. For this reason, we intend to make the downscaled analysis suitable for regional forecast initial conditions and for consistent energy budget research by assimilating observed precipitation. In this study, we use a regional climate model to assimilate different precipitation data sets: (a) the .25 deg. National Oceanic and Atmospheric Administration's Climate Prediction Center (NOAA/CPC) daily precipitation analyses, disaggregated to hourly time scales from a coarser 2-deg. data set; (b) the new 1/2 hourly .25 deg NOAA/CPC MORPHed precipitation (CMORPH). To develop our study, we chose a large domain, which includes North and Central America. The sensitivity of the precipitation assimilation method to these precipitation data sets is being investigated and the results will be reported during the meeting.
DE: 3337 Numerical modeling and data assimilation
DE: 3354 Precipitation (1854)
SC: Atmospheric Sciences [A]
MN: 2004 AGU Fall Meeting