Empirical relations between size parameters of ice hydrometeor populations and radar reflectivity

Empirical relations between size parameters of ice hydrometeor populations and radar reflectivity AbstractEmpirical power-law relations between the equivalent radar reflectivity factor, Ze, and the slope parameter of the gamma-function Λ, (i.e., Λ=cZed), which is used to describe ice hydrometeor size distributions, are derived. The Λ parameter can also be considered as a size parameter since it is proportional to the inverse of the hydrometeor characteristic size which is important geophysical parameter describing the entire distribution. Two data sets from two-dimensional microphysical probes collected during aircraft flights in subtropical and mid-latitude regions were used to obtain Λ, by fitting measured size distributions. Reflectivity for different radar frequencies were calculated from microphysical probe data using nonspherical particle models. The derived relations have exponent d values around -0.35 ─ -0.40 and the prefactors are approximately between 30 and 55 (when Λ is cm-1 and Ze is in mm6m-3). There is a tendency of the exponent d and the prefactor c to decrease when radar frequency increases from Ku-band (~14 GHz) to W-band (~94 GHz). Correlation coefficients between Ze and Λ can be quite high (~ 0.8), especially for lower frequencies. Such correlations are similar to those for empirical relations between reflectivity and ice water content (IWC), which are used in many modeling and remote sensing applications. Close correspondences of reflectivity to both Λ and IWC is due to a relatively high correlation between these two microphysical parameters. Expected uncertainties of estimating Λ from reflectivity could be as high as a factor of 2 although estimates at lower radar frequencies are more robust. Stratifying retrievals by temperature could result in relatively modest improvement of Λ estimates. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Applied Meteorology and Climatology American Meteorological Society

Empirical relations between size parameters of ice hydrometeor populations and radar reflectivity

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1558-8432
D.O.I.
10.1175/JAMC-D-17-0076.1
Publisher site
See Article on Publisher Site

Abstract

AbstractEmpirical power-law relations between the equivalent radar reflectivity factor, Ze, and the slope parameter of the gamma-function Λ, (i.e., Λ=cZed), which is used to describe ice hydrometeor size distributions, are derived. The Λ parameter can also be considered as a size parameter since it is proportional to the inverse of the hydrometeor characteristic size which is important geophysical parameter describing the entire distribution. Two data sets from two-dimensional microphysical probes collected during aircraft flights in subtropical and mid-latitude regions were used to obtain Λ, by fitting measured size distributions. Reflectivity for different radar frequencies were calculated from microphysical probe data using nonspherical particle models. The derived relations have exponent d values around -0.35 ─ -0.40 and the prefactors are approximately between 30 and 55 (when Λ is cm-1 and Ze is in mm6m-3). There is a tendency of the exponent d and the prefactor c to decrease when radar frequency increases from Ku-band (~14 GHz) to W-band (~94 GHz). Correlation coefficients between Ze and Λ can be quite high (~ 0.8), especially for lower frequencies. Such correlations are similar to those for empirical relations between reflectivity and ice water content (IWC), which are used in many modeling and remote sensing applications. Close correspondences of reflectivity to both Λ and IWC is due to a relatively high correlation between these two microphysical parameters. Expected uncertainties of estimating Λ from reflectivity could be as high as a factor of 2 although estimates at lower radar frequencies are more robust. Stratifying retrievals by temperature could result in relatively modest improvement of Λ estimates.

Journal

Journal of Applied Meteorology and ClimatologyAmerican Meteorological Society

Published: Jul 17, 2017

References

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