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A System for the Hourly Assimilation of Surface Observations in Mountainous and Flat Terrain

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  • 1 NOAA Environmental Research Laboratories, Forecast Systems Laboratory, Boulder, Colorado
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Abstract

An assimilation system is presented that was designed to provide timely, detailed, and coherent analyses of surface data, even when the data are collected in rough terrain where station elevations differ widely and observations are often subject to local effects. Analyses with improved spatial continuity are obtained from these data through careful choice of analysis method and variables. The analysis method has the ability to handle varying data density, and the analysis variables, when possible, were chosen in such a way as to cancel out the effects of elevation differences. In addition, the method accounts for physical blocking and channeling by mountainous terrain by incorporating elevation and potential temperature differences in its horizontal correlation functions. The correlation functions also enable the method to move accurately represent surface gradients.

An hourly analysis cycle is used in which each analysis uses as a background the previous hourly analysis (a 1-h persistence forecast). The cycling is important in providing temporal continuity between analyses.

Detailed explanations of the analysis variables and method are given, along with a discussion of the objective quality-control procedures necessary to ensure reliable analyses in an operational environment. The assimilation system has been used experimentally by National Weather Service forecasters since 1996. Quality-control statistics summarizing the observational errors of surface stations across the 48 contiguous states are also presented.

The effects of variable terrain on the analyses are demonstrated in examples. Sample analyses are presented, including diagnosed fields, for a severe-storm case. Overall, the surface analyses described here allow better temporal and spatial resolution than the current operational National Meteorolegical Center surfaces analyses.

Abstract

An assimilation system is presented that was designed to provide timely, detailed, and coherent analyses of surface data, even when the data are collected in rough terrain where station elevations differ widely and observations are often subject to local effects. Analyses with improved spatial continuity are obtained from these data through careful choice of analysis method and variables. The analysis method has the ability to handle varying data density, and the analysis variables, when possible, were chosen in such a way as to cancel out the effects of elevation differences. In addition, the method accounts for physical blocking and channeling by mountainous terrain by incorporating elevation and potential temperature differences in its horizontal correlation functions. The correlation functions also enable the method to move accurately represent surface gradients.

An hourly analysis cycle is used in which each analysis uses as a background the previous hourly analysis (a 1-h persistence forecast). The cycling is important in providing temporal continuity between analyses.

Detailed explanations of the analysis variables and method are given, along with a discussion of the objective quality-control procedures necessary to ensure reliable analyses in an operational environment. The assimilation system has been used experimentally by National Weather Service forecasters since 1996. Quality-control statistics summarizing the observational errors of surface stations across the 48 contiguous states are also presented.

The effects of variable terrain on the analyses are demonstrated in examples. Sample analyses are presented, including diagnosed fields, for a severe-storm case. Overall, the surface analyses described here allow better temporal and spatial resolution than the current operational National Meteorolegical Center surfaces analyses.

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