HR: 1340h
AN: IN43B-1180    [Abstracts]
TI: A Rapid Prototyping Capability Experiment to Evaluate CrIS / ATMS Observations for Urban Modeling Applications
AU: Hill, C M
EM: hillcm@ngi.msstate.edu
AF: Northern Gulf Institute - Mississippi State University, Campus Box 9627, Mississippi State, MS 39762, United States
AU: Fitzpatrick, P J
EM: fitz@ngi.msstate.edu
AF: Northern Gulf Institute - Mississippi State University, Campus Box 9627, Mississippi State, MS 39762, United States
AU: * Anantharaj, V G
EM: val@gri.msstate.edu
AF: GeoResources Institute - Mississippi State University, Campus Box 9652, Mississippi State, MS 39762, United States
AU: Riishojgaard, L
EM: riishojgaard@gmao.gsfc.nasa.gov
AF: Global Modeling and Assimilation Office - NASA Goddard Space Flight Center, Code 610.1, Greenbelt, MD 20771, United States
AB: The goal of this project is to evaluate the potential for data from the Advanced Technology Microwave Sounder (ATMS) and the Crosstrack Infrared Sounder (CrIS) to impact forecasting of a significant mesoscale weather event over a major urban center along the coast of the Gulf of Mexico. The ATMS and the CrIS will be deployed as part of a suite of atmospheric sensors aboard the National Polar-orbiting Operational Environmental Satellite System (NPOESS) and the preceding NPOESS Preparatory Project (NPP) satellite, scheduled to be launched in 2009. An Observing System Simulation Experiment (OSSE) methodology is adopted to characterize the uncertainties associated with instrument measurement and retrieval processes. The methodology will be based on the procedures adopted by NASA Global Modeling and Assimilation Office (GMAO) and NOAA Environmental Modeling Center (EMC). Within the OSSE framework, a nature run (NR) is a proxy for real atmospheric and land surface conditions; it is based on a "free run" of a global-scale forecast model. For an OSSE, it is very important that different data-assimilating models be used to generate the NR and subsequent sensitivity tests. Otherwise, a "fraternal twin" problem may result, in which a low error bias between models does not realistically portray the error bias expected with assimilation of the candidate sensor data. A regional-scale NR (RSNR) will be produced using the MM5, and will serve as "truth" for our modeling experiments. The RSNR will be a nest simulation within one of the larger scale NRs produced from the ECMWF model. To simulate observations from the candidate sensors, error and bias characteristics may be adopted from the NPOESS Aircraft Sounder Testbed (NAST), in which prototypes of the ATMS and the CrIS were tested aboard aircraft. The WRF model is in conjunction with the MM5 to perform the sensitivity experiments involving the assimilation of existing sensor data and synthesized data representing candidate sensors. We expect that data transmitted from the ATMS and the CrIS will greatly supplement the existing networks of surface observations and upper-air observations in the analysis of atmospheric temperature, humidity, and pressure; enhance the quality of data assimilated into operational forecast models; and subsequently help to improve the simulation of weather on regional and local scales.
DE: 3315 Data assimilation
DE: 3329 Mesoscale meteorology
DE: 3333 Model calibration (1846)
DE: 3355 Regional modeling
DE: 3360 Remote sensing
SC: Earth and Space Science Informatics [IN]
MN: 2007 Fall Meeting