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The Merger of Mesoscale Datasets into a Common Cartesian Format for Efficient and Systematic Analyses

Carl G. MohrNational Center for Atmospheric Research, Boulder, CO 80307

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L. Jay MillerNational Center for Atmospheric Research, Boulder, CO 80307

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Robin L. VaughanNational Center for Atmospheric Research, Boulder, CO 80307

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Harold W. FrankNational Center for Atmospheric Research, Boulder, CO 80307

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Abstract

During the 1981 summer season within a 70 000 km2 area surrounding Miles City, Montana, researchers from approximately twenty institutions participated in the Cooperative Convective Precipitation Experiment (CCOPE). The measurements collected during this project comprise one of the most comprehensive datasets ever acquired in and around individual convective storms on the high plains of North America. Principal data systems utilized during CCOPE included 8 ground-based radar (7 of which had Doppler capability), 12 instrumented research aircraft, and a network of 123 surface stations.

A major data processing goal has been to combine these independently acquired mesoscale measurements into a numerical description of observed atmospheric conditions at any point in time. Using the CCOPE data archive as an example, this paper describes the procedures used to reduce these high resolution observations to a common spatial and temporal framework. The final product is a digital description of the environment similar to that employed by most modelers—a three-dimensional Cartesian coordinate system containing fields that represent the instantaneous state of the atmosphere at discrete times across the period of interest. A software package designed to facilitate the construction and analysis of these composite data structures will also be discussed.

Abstract

During the 1981 summer season within a 70 000 km2 area surrounding Miles City, Montana, researchers from approximately twenty institutions participated in the Cooperative Convective Precipitation Experiment (CCOPE). The measurements collected during this project comprise one of the most comprehensive datasets ever acquired in and around individual convective storms on the high plains of North America. Principal data systems utilized during CCOPE included 8 ground-based radar (7 of which had Doppler capability), 12 instrumented research aircraft, and a network of 123 surface stations.

A major data processing goal has been to combine these independently acquired mesoscale measurements into a numerical description of observed atmospheric conditions at any point in time. Using the CCOPE data archive as an example, this paper describes the procedures used to reduce these high resolution observations to a common spatial and temporal framework. The final product is a digital description of the environment similar to that employed by most modelers—a three-dimensional Cartesian coordinate system containing fields that represent the instantaneous state of the atmosphere at discrete times across the period of interest. A software package designed to facilitate the construction and analysis of these composite data structures will also be discussed.

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