Satellite-based estimation of cloud-base heights using constrained spectral radiance matching

被引：25

作者：

Sun, X. J. ^{[1
]}

Li, H. R. ^{[1
]}

Barker, H. W. ^{[2
,3
]}

Zhang, R. W. ^{[1
]}

Zhou, Y. B. ^{[1
]}

Liu, L. ^{[1
]}

机构：

[1] PLA Univ Sci & Technol, Coll Meteorol & Oceanog, Shuanglong St 60, Nanjing 211101, Jiangsu, Peoples R China

[2] Environm Canada, Toronto, ON, Canada

[3] McMaster Univ, Sch Geog & Earth Sci, Hamilton, ON, Canada

来源：

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY | 2016年 / 142卷 / 694期

基金：

中国国家自然科学基金;

关键词：

cloud-base height; layer-cloud fractions; active and passive satellite remote sensing; A-TRAIN; MODIS; CIRCULATION; SYSTEM;

D O I：

10.1002/qj.2647

中图分类号：

P4 [大气科学（气象学）];

学科分类号：

0706 ; 070601 ;

摘要：

A method for estimating cloud-base heights (CBHs) across wide swaths of passive satellite imagery is introduced. The constrained spectral radiance matching (CSRM) algorithm assigns donor columns observed by CloudSat/CALIPSO to recipient pixels across MODIS imagery. The column meeting the constraint is selected as a donor via spectral radiance matching (SRM). Results are compared using eight cloud characteristics, retrieved from passive imagery, as constraints and distinct values for a matching controlling factor . Cloud-top pressure and = 0.3 are used in the final algorithm. Estimates are made of CBH and layer-cloud fraction profile made by SRM, CSRM, cloud-type matching (CTM), and retrieved data matching (RDM) using a data-exclusion procedure. Results show that the CSRM is superior at estimating lowest CBH and layer-cloud fraction. It is also shown that, when cloud types are provided by merged CloudSat and CALIPSO data, the CTM provides the best estimates of uppermost CBH, with the CSRM taking second. Both the CSRM method and the straight SRM method construct layer-cloud fraction profiles very well for clouds between 2 and approximate to 15 km. A preliminary 3D rendering of tropical storm Soulik is presented.

引用

页码：224 / 232

页数：9

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