HR: 17:50h
AN: A14A-10    [Abstracts]
TI: Precipitation estimation from CloudSat
AU: * Haynes, J M
EM: haynes@atmos.colostate.edu
AF: Dept. of Atmospheric Science, Colorado State University, 1371 Campus Delivery, Fort Collins, CO 80523, United States
AU: L'Ecuyer, T S
EM: tristan@atmos.colostate.edu
AF: Dept. of Atmospheric Science, Colorado State University, 1371 Campus Delivery, Fort Collins, CO 80523, United States
AU: Stephens, G L
EM: stephens@atmos.colostate.edu
AF: Dept. of Atmospheric Science, Colorado State University, 1371 Campus Delivery, Fort Collins, CO 80523, United States
AU: Mitrescu, C
EM: cristian.mitrescu@nrlmry.navy.mil
AF: Naval Research Laboratory, 7 Grace Hopper Ave, MS#2, Monterey, CA 93943, United States
AU: Miller, S D
EM: miller@cira.colostate.edu
AF: Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO 80523, United States
AB: CloudSat, a satellite in the A-Train constellation containing a nadir-pointing 94 GHz cloud radar, is well suited for the detection of precipitation and the quantification of precipitation intensity, being especially sensitive to lighter rainfall. A new algorithm for retrieving precipitation intensity from CloudSat observations is described. Considering path integrated attenuation (PIA) by hydrometeors as a measurement rather than noise, it is possible to estimate rainfall intensity using observations of the decrease in the surface backscatter under precipitating columns. Multiple scattering within the precipitating column can be significant for rainfall exceeding a few millimeter per hour, so Monte Carlo modeling is used to simulate the relationship between rainfall and observed PIA for various vertical profiles of precipitation. A model of the melting layer is also incorporated into the Monte Carlo calculations to better represent the transition from snow to rain. Results of a year of analysis of precipitation incidence and accumulation using the retrieval are presented, including comparisons with estimates from other sensors. The regional variation of precipitation efficiency, in terms of the fraction of clouds that produce precipitation, is also discussed.
DE: 0321 Cloud/radiation interaction
DE: 3354 Precipitation (1854)
DE: 3360 Remote sensing
SC: Atmospheric Sciences [A]
MN: 2007 Fall Meeting