Objective Sea-Level Pressure Analysis for Data-Sparse Areas

Leonard M. Druyan Institute for Space Studies, Goddard Space Flight Center, NASA, New York, N. Y. 10025

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Abstract

A computer procedure, described in an earlier study, uses the wind speed field near the ocean surface in combination with a small number of observations of pressure and wind velocity to specify the maritime sea-level pressure field. An improved version was used to analyze the pressure distribution over the North Pacific Ocean for eleven synoptic times in February 1967. Independent knowledge of the central pressures of lows is shown to reduce the analysis errors for very sparse data coverage. The application of planned remote sensing of sea-level wind speeds is shown to make a significant contribution to the quality of the analysis especially in the high gradient mid-latitudes and for sparse coverage of conventional observations (such as over Southern Hemisphere oceans). Uniform distribution of the available observations of sea-level pressure and wind velocity yields results far superior to those derived from a random distribution. A generalization of the results indicates that the average lower limit for analysis errors is between 2 and 2.5 mb based on the perfect specification of the magnitude of the sea-level pressure gradient from a known verification analysis, and 15 uniformly distributed, high-quality buoy, weather ship or island observations of the pressure and wind velocity. (A less than perfect specification will derive from wind-pressure relationships applied to satellite-observed wind speeds.) Analysis errors computed using poorly defined wind fields indicate the procedure's potential for sparse data analysis even without supplementary satellite data.

Abstract

A computer procedure, described in an earlier study, uses the wind speed field near the ocean surface in combination with a small number of observations of pressure and wind velocity to specify the maritime sea-level pressure field. An improved version was used to analyze the pressure distribution over the North Pacific Ocean for eleven synoptic times in February 1967. Independent knowledge of the central pressures of lows is shown to reduce the analysis errors for very sparse data coverage. The application of planned remote sensing of sea-level wind speeds is shown to make a significant contribution to the quality of the analysis especially in the high gradient mid-latitudes and for sparse coverage of conventional observations (such as over Southern Hemisphere oceans). Uniform distribution of the available observations of sea-level pressure and wind velocity yields results far superior to those derived from a random distribution. A generalization of the results indicates that the average lower limit for analysis errors is between 2 and 2.5 mb based on the perfect specification of the magnitude of the sea-level pressure gradient from a known verification analysis, and 15 uniformly distributed, high-quality buoy, weather ship or island observations of the pressure and wind velocity. (A less than perfect specification will derive from wind-pressure relationships applied to satellite-observed wind speeds.) Analysis errors computed using poorly defined wind fields indicate the procedure's potential for sparse data analysis even without supplementary satellite data.

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