Editorial Type:
Article
Article Type:
Research Article

Three-Dimensional Simple Adjoint Velocity Retrievals from Single-Doppler Radar

Jidong Gao Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma

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Ming Xue Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma

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Alan Shapiro Center for Analysis and Prediction of Storms, School of Meteorology, Coastal Meteorology Research Program, University of Oklahoma, Norman, Oklahoma

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Qin Xu National Severe Storms Laboratory, Norman, Oklahoma

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Kelvin K. Droegemeier Center for Analysis and Prediction of Storms, School of Meteorology, University of Oklahoma, Norman, Oklahoma

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Print Publication:
01 Jan 2001
DOI:
https://doi.org/10.1175/1520-0426(2001)018<0026:TDSAVR>2.0.CO;2
Page(s):
26–38
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Abstract

In this paper, the original simple adjoint method of Qiu and Xu is improved and tested for retrieving the 3D storm-scale wind field from single-Doppler radar data. The method incorporates single-radar data and background fields, along with a dynamical constraint, smoothness, and anelastic mass continuity constraint, in a cost function. The minimization of the cost function, with the desired fit to these constraints, is obtained in an iterative procedure.

The current method is tested on simulated datasets of supercell storms. It is shown that the circulation inside and around the storms, including the strong updraft and associated downdraft, are well retrieved. Furthermore, the method is robust in the presence of data error.

Corresponding author address: Dr. Jidong Gao, Center for Analysis and Prediction of Storms, Sarkey’s Energy Center, Suite 1110, 100 East Boyd, Norman, OK 73019.

Abstract

In this paper, the original simple adjoint method of Qiu and Xu is improved and tested for retrieving the 3D storm-scale wind field from single-Doppler radar data. The method incorporates single-radar data and background fields, along with a dynamical constraint, smoothness, and anelastic mass continuity constraint, in a cost function. The minimization of the cost function, with the desired fit to these constraints, is obtained in an iterative procedure.

The current method is tested on simulated datasets of supercell storms. It is shown that the circulation inside and around the storms, including the strong updraft and associated downdraft, are well retrieved. Furthermore, the method is robust in the presence of data error.

Corresponding author address: Dr. Jidong Gao, Center for Analysis and Prediction of Storms, Sarkey’s Energy Center, Suite 1110, 100 East Boyd, Norman, OK 73019.

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