期刊
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
卷 121, 期 7, 页码 3584-3607出版社
AMER GEOPHYSICAL UNION
DOI: 10.1002/2015JD024446
关键词
radar; microphysics; precipitation
资金
- U.S. Department of Energy [ER65459]
- NOAA/Office and Atmospheric Research under NOAA-University of Oklahoma, U.S. Department of Commerce [NA11OAR4320072]
- DOE ASR [DE-SC0008648]
- National Science Foundation
Polarimetric radar observations increasingly are used to understand cloud microphysical processes, which is critical for improving their representation in cloud and climate models. In particular, there has been recent focus on improving representations of ice collection processes (e.g., aggregation and riming), as these influence precipitation rate, heating profiles, and ultimately cloud life cycles. However, distinguishing these processes using conventional polarimetric radar observations is difficult, as they produce similar fingerprints. This necessitates improved analysis techniques and integration of complementary data sources. The Midlatitude Continental Convective Clouds Experiment (MC3E) provided such an opportunity. Quasi-vertical profiles of polarimetric radar variables in two MC3E stratiform precipitation events reveal episodic melting layer sagging. Integrated analyses using scanning and vertically pointing radar and aircraft measurements reveal that saggy bright band signatures are produced when denser, faster-falling, more isometric hydrometeors (relative to adjacent times) descend into the melting layer. In one case, strong circumstantial evidence for riming is found during bright band sagging times. A bin microphysical melting layer model successfully reproduces many aspects of the signature, supporting the observational analysis. If found to be a reliable indicator of riming, saggy bright bands could be a proxy for the presence of supercooled liquid water in stratiform precipitation, which may provide important information for mitigating aircraft icing risks and for constraining microphysical models.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据