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Raindrop Spectra and Updraft Determination by Combining Doppler Radar and Disdrometer

Alan D. ThomsonDepartment of Physics, University of Toronto, Toronto, Ontario, Canada

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Roland ListDepartment of Physics, University of Toronto, Toronto, Ontario, Canada

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Abstract

A new method is presented by which raindrop size spectra are determined from power spectra measured by an X-band Doppler radar. Prior to drop size spectrum calculation, bias caused by vertical wind, vw, is removed by an iterative process that uses a disdrometer-determined relation that is characteristic of the rainfall type. The specific relation (Z ≈ 507 R1.44) is determined from the best correlated data pair formed between Z or w with one of R, M, and vm. The vertical wind is estimated by shifting (rotating) the power spectrum along the velocity axis until this Z-R relation is satisfied. This method works for any shape of drop size spectrum.

The power spectrum noise is studied by a computer simulation that indicates that smoothing of the spectra by a running average is not reliable for suppressing stochastic measurement noise. Consequently, a vertically pointing radar scanning strategy was designed to allow averaging of the power spectra prior to drop spectrum calculation. This scan was tested during Phase II of the Canadian Atlantic Storms Program. A Joss-Waldvogel disdrometer was used to characterize the rainfall type. Once the vertical wind is calculated and removed, drop size spectra derived from calibrated radar measurements made near the surface agree well with the spectra determined by disdrometer. Thus, extrapolation of the method to higher levels is possible.

Abstract

A new method is presented by which raindrop size spectra are determined from power spectra measured by an X-band Doppler radar. Prior to drop size spectrum calculation, bias caused by vertical wind, vw, is removed by an iterative process that uses a disdrometer-determined relation that is characteristic of the rainfall type. The specific relation (Z ≈ 507 R1.44) is determined from the best correlated data pair formed between Z or w with one of R, M, and vm. The vertical wind is estimated by shifting (rotating) the power spectrum along the velocity axis until this Z-R relation is satisfied. This method works for any shape of drop size spectrum.

The power spectrum noise is studied by a computer simulation that indicates that smoothing of the spectra by a running average is not reliable for suppressing stochastic measurement noise. Consequently, a vertically pointing radar scanning strategy was designed to allow averaging of the power spectra prior to drop spectrum calculation. This scan was tested during Phase II of the Canadian Atlantic Storms Program. A Joss-Waldvogel disdrometer was used to characterize the rainfall type. Once the vertical wind is calculated and removed, drop size spectra derived from calibrated radar measurements made near the surface agree well with the spectra determined by disdrometer. Thus, extrapolation of the method to higher levels is possible.

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