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Probability Index of Low Stratus and Fog at Dawn using Dual Geostationary Satellite Observations from COMS and FY-2D near the Korean Peninsula

Title
Probability Index of Low Stratus and Fog at Dawn using Dual Geostationary Satellite Observations from COMS and FY-2D near the Korean Peninsula
Authors
Yang, Jung-HyunYoo, Jung-MoonChoi, Yong-SangWu, DongJeong, Jin-Hee
Ewha Authors
유정문최용상
SCOPUS Author ID
유정문scopus; 최용상scopus
Issue Date
2019
Journal Title
REMOTE SENSING
ISSN
2072-4292JCR Link
Citation
REMOTE SENSING vol. 11, no. 11
Keywords
fogLSFdawnprobability indexCOMSFY-2Dremote sensingthresholdradiative transfer model
Publisher
MDPI
Indexed
SCIE; SCOPUS WOS
Document Type
Article
Abstract
We developed a new remote sensing method for detecting low stratus and fog (LSF) at dawn in terms of probability index (PI) of LSF from simultaneous stereo observations of two geostationary-orbit satellites; the Korean Communication, Ocean, and Meteorological Satellite (COMS; 128.2 degrees E); and the Chinese FengYun satellite (FY-2D; 86.5 degrees E). The algorithm was validated near the Korean Peninsula between the months of April and August from April 2012 to June 2015, by using surface observations at 45 meteorological stations in South Korea. The optical features of LSF were estimated by using satellite retrievals and simulated data from the radiative transfer model. The PI was calculated using the combination of three satellite-observed variables: 1) the reflectance at 0.67 m (R-0.67) from COMS, and 2) the FY-2D R-0.67 minus the COMS R-0.67 (oR(0.67)) and 3) the FY-2D-COMS difference in the brightness temperature difference between 3.7 and 11.0 m (BTD3.7-11). The three variables, adopted from the top three probability of detection (POD) scores for their fog detection thresholds: oR(0.67) (0.82) > BTD3.7-11 (0.73) > R-0.67 (0.70) > BTD3.7-11 (0.51). The LSF PI for this algorithm was significantly better in the two case studies compared to that using COMS only (i.e., R-0.67 or BTD3.7-11), so that this improvement was due to oR(0.67) and BTD3.7-11. Overall, PI in the LSF spatial distribution has the merits of a high detection rate, a specific probability display, and a low rate of seasonality and variability in detection accuracy. Therefore, PI would be useful for monitoring LSF in near-real-time, and to further its forecast ability, using next-generation satellites.
DOI
10.3390/rs11111283
Appears in Collections:
사범대학 > 과학교육과 > Journal papers
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