Synthetic Satellite Imagery for Real-Time High-Resolution Model Evaluation

被引：39

作者：

Bikos, Dan ^{[1
]}

Lindsey, Daniel T. ^{[2
]}

Otkin, Jason ^{[3
]}

Sieglaff, Justin ^{[3
]}

Grasso, Louie ^{[1
]}

Siewert, Chris ^{[4
]}

Correia, James, Jr. ^{[4
]}

Coniglio, Michael ^{[5
]}

Rabin, Robert ^{[3
,5
]}

Kain, John S. ^{[5
]}

Dembek, Scott ^{[4
]}

机构：

[1] Colorado State Univ, Cooperat Inst Res Atmosphere, Ft Collins, CO 80523 USA

[2] NOAA, NESDIS, STAR, RAMMB, Ft Collins, CO USA

[3] Univ Wisconsin, Cooperat Inst Meteorol Satellite Studies, Madison, WI USA

[4] Univ Oklahoma, Cooperat Inst Mesoscale Meteorol Studies, Norman, OK 73019 USA

[5] Natl Severe Storms Lab, Norman, OK 73069 USA

来源：

WEATHER AND FORECASTING | 2012年 / 27卷 / 03期

基金：

美国海洋和大气管理局;

关键词：

RADIATIVE-TRANSFER MODEL; CLOUDS; FIELDS; SPACE; RETRIEVALS; VALIDATION;

D O I：

10.1175/WAF-D-11-00130.1

中图分类号：

P4 [大气科学（气象学）];

学科分类号：

0706 ; 070601 ;

摘要：

Output from a real-time high-resolution numerical model is used to generate synthetic infrared satellite imagery. It is shown that this imagery helps to characterize model-simulated large-scale precursors to the formation of deep-convective storms as well as the subsequent development of storm systems. A strategy for using this imagery in the forecasting of severe convective weather is presented. This strategy involves comparing model-simulated precursors to their observed counterparts to help anticipate model errors in the timing and location of storm formation, while using the simulated storm evolution as guidance.

引用

页码：784 / 795

页数：12

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