Characterization of rain microphysics based on disdrometer and polarimetric radar observations

被引：3

作者：

Cao, Qing ^{[1
]}

Zhang, Guifu ^{[1
]}

Schuur, Terry ^{[2
]}

Ryzhkov, Alexander ^{[2
]}

Brandes, Edward ^{[3
]}

Ikeda, Kyoko ^{[3
]}

机构：

[1] Univ Oklahoma, Sch Meteorol, Norman, OK 73019 USA

[2] Natl Severe Storms Lab, Norman, OK 73019 USA

[3] Natl Ctr Atmospher Res, Boulder, CO 80301 USA

来源：

2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8 | 2006年

关键词：

disdrometer; drop size distribution; sampling error; fitting; radar retrieval;

D O I：

10.1109/IGARSS.2006.139

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

Characterization of rain microphysics requires information on raindrop size distributions (DSDs). DSD measurements and retrievals, however, contain errors. In this paper, data from side-by-side disdrometer comparisons are presented to provide information that is not possible from single disdrometer measurements alone, allowing error effects to be quantified and a rain DSD model for radar retrieval to be improved. We also propose methods to mitigate sampling errors by filtering with sorting and averaging and by fitting to a Gamma DSD model with truncation and extrapolation. The Constrained-Gamma DSD model has thus been refined for the Southern Great Plains region of the United States.

引用

页码：523 / +

页数：3