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An example of the use of synthetic 3.9 m GOES-12 imagery for two-moment microphysical evaluation

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In preparation for the launch of the next generation of geostationary satellites, considerable effort has been placed on developing new products and algorithms for operational purposes. In addition to satellite-based products and algorithms, satellite imagery can be used to evaluate numerical weather prediction models. Important first steps have already been undertaken to produce synthetic satellite imagery from numerical model output. By comparing synthetic imagery with observed imagery, model performance can be evaluated with a relatively new metric. In this paper, synthetic Geostationary Operational Environmental Satellite (GOES)-12 imagery was used to improve the two-moment prediction of pristine ice in the RAMS (Regional Atmospheric Modeling System) mesoscale model. A thunderstorm event that occurred on 27 June 2005 over the central plains of the USA was chosen for study. Synthetic GOES-12 3.9 m imagery of RAMS output was compared with observed GOES-12 3.9 m imagery. A discrepancy between brightness temperatures of two anvils of thunderstorms led to an improvement in the prediction of pristine ice number concentrations. After the model was re-run, subsequent synthetic GOES-12 3.9 m imagery of one anvil exhibited an improvement compared with observed imagery. Brightness temperatures of the second anvil became too warm, an issue that may be related to model-specified cloud condensation nuclei (CCN) concentrations. This example highlights the potential importance of using synthetic imagery to evaluate numerical weather prediction models.

Document Type: Research Article


Affiliations: 1: Cooperative Institute for Research in the Atmosphere, Fort Collins, CO, USA 2: NOAA/NESDIS/STAR/RAMMB, Fort Collins, CO, USA

Publication date: April 1, 2011

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