Abstract

Vertical raindrop size distributions of two stratiform rain events were measured with a Micro Rain Radar during summer 2009 at a semiarid continental site located in Xilinhot, China (43°38′N, 116°42′E). The sequential intensity filtering technique (SIFT) was used to minimize the effect of the spurious variability on disdrometric data to obtain the reflectivity–rain rate (ZR) relationship (Z = aRb). Compared with the least squares regression (LSR) method, SIFT led to a −5% to 4% change in the coefficient (a) and an 8%–15% increase in the exponent (b) of the ZR relationship at 300 m. Rainfall estimation using the ZR relationship with SIFT had lower standard deviation than that with LSR. The vertical variability of the mean rain rate, total raindrop numbers, and parameters (a and b) of the ZR relationship was small below a melting layer, suggesting that using the radar reflectivity of weather radar to estimate stratiform rainfall is relatively accurate, at least in the Xilinhot area.

Details

Title
An observational study on vertical raindrop size distributions during stratiform rain in a semiarid plateau climate zone
Author
CHEN, Yong 1 ; Jun-Ling, AN 2 ; Hui-Zhi, LIU 1 ; DUAN, Jing 3 

 State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China 
 State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China; Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, China 
 Key Laboratory for Cloud Physics, Chinese Academy of Meteorological Sciences, Beijing, China 
End page
184
Publication year
2016
Publication date
May 2016
Publisher
KeAi Publishing Communications Ltd
ISSN
16742834
e-ISSN
23766123
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2215242890
Copyright
© 2016 The Author(s). Published by Taylor & Francis. This work is licensed under the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.