Editorial Type:
Article
Article Type:
Research Article

Simulation of a Midlatitude Convective Storm Initialized with Bistatic Doppler Radar Data

Thibaut Montmerle Department of Atmospheric and Oceanic Sciences, McGill University, Montreal, Quebec, Canada, and J. S. Marshall Weather Observatory, Sainte Anne de Bellevue, Quebec, Canada

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Alain Caya Department of Atmospheric and Oceanic Sciences, McGill University, Montreal, Quebec, Canada, and J. S. Marshall Weather Observatory, Sainte Anne de Bellevue, Quebec, Canada

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Isztar Zawadzki Department of Atmospheric and Oceanic Sciences, McGill University, Montreal, Quebec, Canada, and J. S. Marshall Weather Observatory, Sainte Anne de Bellevue, Quebec, Canada

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Print Publication:
01 Aug 2001
DOI:
https://doi.org/10.1175/1520-0493(2001)129<1949:SOAMCS>2.0.CO;2
Page(s):
1949–1967
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Abstract

An analysis is developed to initialize a cloud-resolving model from an explicit structure of a precipitating convective system derived from multiple-Doppler radar observations. The different fields of the model prognostic variables that compose the initial state of the simulation are estimated or retrieved using a 4DVAR assimilation method in which the model is used as a weak constraint using two time level observations. This allows for the retrieval of physical fields consistent with the observations and the equations of the model.

This method is applied on a midlatitude summer storm sampled by the McGill bistatic Doppler radar network that occurred on 2 August 1997. During the 30-min-forward simulation, the model succeeds in representing the observed features of the three main cells that compose the storm in terms of precipitation distribution and evolution of the convective activity. After this period, the model produces less stratiform precipitations. Comparisons with a Lagrangian persistency prediction are performed and show a notable improvement in the short-term forecast.

Corresponding author address: Thibaut Montmerle, Dept. of Atmospheric and Oceanic Sciences, McGill University, 805 Sherbrooke Street West, Montreal, PQ H3A 2K6, Canada. Email: montmerl@cumulus.meteo.mcgill.ca

Abstract

An analysis is developed to initialize a cloud-resolving model from an explicit structure of a precipitating convective system derived from multiple-Doppler radar observations. The different fields of the model prognostic variables that compose the initial state of the simulation are estimated or retrieved using a 4DVAR assimilation method in which the model is used as a weak constraint using two time level observations. This allows for the retrieval of physical fields consistent with the observations and the equations of the model.

This method is applied on a midlatitude summer storm sampled by the McGill bistatic Doppler radar network that occurred on 2 August 1997. During the 30-min-forward simulation, the model succeeds in representing the observed features of the three main cells that compose the storm in terms of precipitation distribution and evolution of the convective activity. After this period, the model produces less stratiform precipitations. Comparisons with a Lagrangian persistency prediction are performed and show a notable improvement in the short-term forecast.

Corresponding author address: Thibaut Montmerle, Dept. of Atmospheric and Oceanic Sciences, McGill University, 805 Sherbrooke Street West, Montreal, PQ H3A 2K6, Canada. Email: montmerl@cumulus.meteo.mcgill.ca

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