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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hui Han Ni Quo Dihua Cai Jing Wang |
| Copyright Year | 2011 |
| Description | Author affiliation: Institute of Arid Meteorology, CMA, Lanzhou; 730020, China (Hui Han; Ni Quo; Dihua Cai; Jing Wang) |
| Abstract | This paper employed an index called surface temperature change (STC) for assisting the sandstorm forecasting over Northwest China. The index was retrieved from Chinese FY-2D/S-VISSR (Stretched - Visible and Infrared Spin-Scan Radiometer) data. For examining the accuracy of sandstorm forecasts that regard STC as a predictor or not, we applied this index to all sandstorm cases that occurred in research region during 2007–2008. The results showed: 1) Employing the STC as a single predictor, 2/7 of those cases were successful predicted; 2) Comparing the sandstorm forecasts which just considered conventional meteorological data with those considered both conventional data and FY-2D retrieved STC, the latter forecasted 1/6 of cases those the former failed to forecast. It indicated that satellite retrieved STC has a little value as a predictor for sandstorm forecasting over northwest China, but only serves as a complement to the ground observations of temperature variations. Because of the ultra high temporal resolution of this index, it would have a better performance in dynamic analysis/rolling forecast cases. |
| Starting Page | 3261 |
| Ending Page | 3264 |
| File Size | 363828 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781457710032 |
| ISSN | 21537003 |
| e-ISBN | 9781457710056 |
| DOI | 10.1109/IGARSS.2011.6049915 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-07-24 |
| Publisher Place | Canada |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Satellites Forecasting Satellite broadcasting Land surface temperature Weather forecasting Surface treatment sandstorm forecasting FY-2D satellite surface temperature change Maximum Value Composites |
| Content Type | Text |
| Resource Type | Article |
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