Backscatter Differential Phase—Estimation and Variability. Trömel, S., Kumjian, M. R., Ryzhkov, A. V., Simmer, C., & Diederich, M. Journal of Applied Meteorology and Climatology, 52(11):2529–2548, November, 2013. ![Backscatter Differential Phase—Estimation and Variability [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Abstract On the basis of simulations and observations made with polarimetric radars operating at X, C, and S bands, the backscatter differential phase δ has been explored; δ has been identified as an important polarimetric variable that should not be ignored in precipitation estimations that are based on specific differential phase K DP , especially at shorter radar wavelengths. Moreover, δ bears important information about the dominant size of raindrops and wet snowflakes in the melting layer. New methods for estimating δ in rain and in the melting layer are suggested. The method for estimating δ in rain is based on a modified version of the “ZPHI” algorithm and provides reasonably robust estimates of δ and K DP in pure rain except in regions where the total measured differential phase Φ DP behaves erratically, such as areas affected by nonuniform beam filling or low signal-to-noise ratio. The method for estimating δ in the melting layer results in reliable estimates of δ in stratiform precipitation and requires azimuthal averaging of radial profiles of Φ DP at high antenna elevations. Comparisons with large disdrometer datasets collected in Oklahoma and Germany confirm a strong interdependence between δ and differential reflectivity Z DR . Because δ is immune to attenuation, partial beam blockage, and radar miscalibration, the strong correlation between Z DR and δ is of interest for quantitative precipitation estimation: δ and Z DR are differently affected by the particle size distribution (PSD) and thus may complement each other for PSD moment estimation. Furthermore, the magnitude of δ can be utilized as an important calibration parameter for improving microphysical models of the melting layer.
@article{tromel_backscatter_2013,
title = {Backscatter {Differential} {Phase}—{Estimation} and {Variability}},
volume = {52},
issn = {1558-8424, 1558-8432},
url = {https://journals.ametsoc.org/view/journals/apme/52/11/jamc-d-13-0124.1.xml},
doi = {10.1175/JAMC-D-13-0124.1},
abstract = {Abstract
On the basis of simulations and observations made with polarimetric radars operating at X, C, and S bands, the backscatter differential phase
δ
has been explored;
δ
has been identified as an important polarimetric variable that should not be ignored in precipitation estimations that are based on specific differential phase
K
DP
, especially at shorter radar wavelengths. Moreover,
δ
bears important information about the dominant size of raindrops and wet snowflakes in the melting layer. New methods for estimating
δ
in rain and in the melting layer are suggested. The method for estimating
δ
in rain is based on a modified version of the “ZPHI” algorithm and provides reasonably robust estimates of
δ
and
K
DP
in pure rain except in regions where the total measured differential phase Φ
DP
behaves erratically, such as areas affected by nonuniform beam filling or low signal-to-noise ratio. The method for estimating
δ
in the melting layer results in reliable estimates of
δ
in stratiform precipitation and requires azimuthal averaging of radial profiles of Φ
DP
at high antenna elevations. Comparisons with large disdrometer datasets collected in Oklahoma and Germany confirm a strong interdependence between
δ
and differential reflectivity
Z
DR
. Because
δ
is immune to attenuation, partial beam blockage, and radar miscalibration, the strong correlation between
Z
DR
and
δ
is of interest for quantitative precipitation estimation:
δ
and
Z
DR
are differently affected by the particle size distribution (PSD) and thus may complement each other for PSD moment estimation. Furthermore, the magnitude of
δ
can be utilized as an important calibration parameter for improving microphysical models of the melting layer.},
number = {11},
urldate = {2023-07-17},
journal = {Journal of Applied Meteorology and Climatology},
author = {Trömel, Silke and Kumjian, Matthew R. and Ryzhkov, Alexander V. and Simmer, Clemens and Diederich, Malte},
month = nov,
year = {2013},
pages = {2529--2548},
}
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Moreover, δ bears important information about the dominant size of raindrops and wet snowflakes in the melting layer. New methods for estimating δ in rain and in the melting layer are suggested. The method for estimating δ in rain is based on a modified version of the “ZPHI” algorithm and provides reasonably robust estimates of δ and K DP in pure rain except in regions where the total measured differential phase Φ DP behaves erratically, such as areas affected by nonuniform beam filling or low signal-to-noise ratio. The method for estimating δ in the melting layer results in reliable estimates of δ in stratiform precipitation and requires azimuthal averaging of radial profiles of Φ DP at high antenna elevations. Comparisons with large disdrometer datasets collected in Oklahoma and Germany confirm a strong interdependence between δ and differential reflectivity Z DR . Because δ is immune to attenuation, partial beam blockage, and radar miscalibration, the strong correlation between Z DR and δ is of interest for quantitative precipitation estimation: δ and Z DR are differently affected by the particle size distribution (PSD) and thus may complement each other for PSD moment estimation. Furthermore, the magnitude of δ can be utilized as an important calibration parameter for improving microphysical models of the melting layer.","number":"11","urldate":"2023-07-17","journal":"Journal of Applied Meteorology and Climatology","author":[{"propositions":[],"lastnames":["Trömel"],"firstnames":["Silke"],"suffixes":[]},{"propositions":[],"lastnames":["Kumjian"],"firstnames":["Matthew","R."],"suffixes":[]},{"propositions":[],"lastnames":["Ryzhkov"],"firstnames":["Alexander","V."],"suffixes":[]},{"propositions":[],"lastnames":["Simmer"],"firstnames":["Clemens"],"suffixes":[]},{"propositions":[],"lastnames":["Diederich"],"firstnames":["Malte"],"suffixes":[]}],"month":"November","year":"2013","pages":"2529–2548","bibtex":"@article{tromel_backscatter_2013,\n\ttitle = {Backscatter {Differential} {Phase}—{Estimation} and {Variability}},\n\tvolume = {52},\n\tissn = {1558-8424, 1558-8432},\n\turl = {https://journals.ametsoc.org/view/journals/apme/52/11/jamc-d-13-0124.1.xml},\n\tdoi = {10.1175/JAMC-D-13-0124.1},\n\tabstract = {Abstract \n \n On the basis of simulations and observations made with polarimetric radars operating at X, C, and S bands, the backscatter differential phase \n δ \n has been explored; \n δ \n has been identified as an important polarimetric variable that should not be ignored in precipitation estimations that are based on specific differential phase \n K \n DP \n , especially at shorter radar wavelengths. Moreover, \n δ \n bears important information about the dominant size of raindrops and wet snowflakes in the melting layer. New methods for estimating \n δ \n in rain and in the melting layer are suggested. The method for estimating \n δ \n in rain is based on a modified version of the “ZPHI” algorithm and provides reasonably robust estimates of \n δ \n and \n K \n DP \n in pure rain except in regions where the total measured differential phase Φ \n DP \n behaves erratically, such as areas affected by nonuniform beam filling or low signal-to-noise ratio. The method for estimating \n δ \n in the melting layer results in reliable estimates of \n δ \n in stratiform precipitation and requires azimuthal averaging of radial profiles of Φ \n DP \n at high antenna elevations. Comparisons with large disdrometer datasets collected in Oklahoma and Germany confirm a strong interdependence between \n δ \n and differential reflectivity \n Z \n DR \n . Because \n δ \n is immune to attenuation, partial beam blockage, and radar miscalibration, the strong correlation between \n Z \n DR \n and \n δ \n is of interest for quantitative precipitation estimation: \n δ \n and \n Z \n DR \n are differently affected by the particle size distribution (PSD) and thus may complement each other for PSD moment estimation. Furthermore, the magnitude of \n δ \n can be utilized as an important calibration parameter for improving microphysical models of the melting layer.},\n\tnumber = {11},\n\turldate = {2023-07-17},\n\tjournal = {Journal of Applied Meteorology and Climatology},\n\tauthor = {Trömel, Silke and Kumjian, Matthew R. and Ryzhkov, Alexander V. and Simmer, Clemens and Diederich, Malte},\n\tmonth = nov,\n\tyear = {2013},\n\tpages = {2529--2548},\n}\n\n\n\n","author_short":["Trömel, S.","Kumjian, M. R.","Ryzhkov, A. 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