HR: 1340h
AN: A53D-1439    [Abstracts]
TI: Evaluating Simulated Clouds With NASA A-Train Observations
AU: * Molthan, A L
EM: andrew.molthan@nsstc.nasa.gov
AF: Department of Atmospheric Science, University of Alabama Huntsville, 320 Sparkman Drive, Huntsville, AL 35805, United States
AU: Jedlovec, G J
EM: gary.jedlovec@nasa.gov
AF: Short-term Prediction Research and Transition Center, NASA/MSFC, 320 Sparkman Drive, Huntsville, AL 35805, United States
AU: Lapenta, W M
EM: bill.lapenta@nasa.gov
AF: Short-term Prediction Research and Transition Center, NASA/MSFC, 320 Sparkman Drive, Huntsville, AL 35805, United States
AB: As computer resources mature, operational forecasts are being initiated at higher spatial resolution, allowing for the simulation of cloud systems through parameterization schemes that predict the evolution of their microphysical properties. Clouds are a dominant component of sensible weather by affecting the diurnal temperature cycle, the heating or cooling of a vertical column, and the distribution of precipitation. The NASA A- Train, a satellite constellation consisting of high resolution instruments that are nearly coincident in time and space, provides an opportunity to compare observed cloud properties to those produced by high resolution model forecasts. Verification data provided by the NASA A-Train include products derived from the MODIS aboard Aqua and the CloudSat Cloud Profiling Radar. Distributions of cloud top and cloud profile properties from MODIS are compared to model derived properties during the evolution of a midlatitude cyclone from March 2007. A radiative transfer model is used to compare CloudSat radar reflectivity to reflectivity simulated from WRF cloud profiles. Sensitivities in the simulation of clouds are examined through experiments with modified parameters focusing on changes in the ice phase components.
DE: 3355 Regional modeling
DE: 3360 Remote sensing
SC: Atmospheric Sciences [A]
MN: 2007 Fall Meeting