Improving Cloud and Moisture Representation in Weather Prediction Model Analyses with Geostationary Satellite Information

Autor/innen

  • Jordan Gerth Department of Atmospheric and Oceanic Sciences Cooperative Institute for Meteorological Satellite Studies University of Wisconsin, Madison, Wisconsin

DOI:

https://doi.org/10.17307/wsc.v0i0.56

Abstract

This paper develops a methodology for an experiment with several parallel regional Weather Research and Forecasting (WRF) model simulations initialized with satellite-based retrievals. The intent is to clarify the impact of observations, in the form of retrievals, from the Geostationary Operational Environmental Satellite (GOES) Sounder on 12, 24, and 36-hour WRF model forecasts of precipitable water. Two experimental analyses are built from a CIMSS Regional Assimilation System (CRAS) pre-forecast spin-up. The CRAS assimilates precipitable water and cloud products derived from the GOES Sounder. An experimentation period between late September and early October 2011 found that the majority of impact in the experimental simulations compared to the control is recognized in the total precipitable water field over the first 12 hours. 

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Zitationsvorschlag

Gerth, J. (2012). Improving Cloud and Moisture Representation in Weather Prediction Model Analyses with Geostationary Satellite Information. Proceedings of the Wisconsin Space Conference. https://doi.org/10.17307/wsc.v0i0.56

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Rubrik

Geosciences