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Nighttime sea fog detection from satellite is very hard due to limitation in using visible channels. Currently, most widely used method for the detection is the Dual Channel Difference (DCD) method based on Brightness Temperature Difference between 3.7 and 11 μm channel (BTD). However, this method have difficulty in distinguishing between fog and low cloud, and sometimes misjudges middle/high cloud as well as clear scene as fog. Using CALIPSO Lidar Profile measurements, we have analyzed the intrinsic problems in detecting nighttime sea fog from various satellite remote sensing algorithms and suggested the direction for the improvement of the algorithm. From the comparison with CALIPSO measurements for May-July in 2011, the DCD method excessively overestimates foggy pixels (2542 pixels). Among them, only 524 pixel are real foggy pixels, but 331 pixels and 1687 pixels are clear and other type of clouds, respectively. The 514 of real foggy pixels accounts for 70% of 749 foggy pixels identified by CALIPSO. Our proposed new algorithm detects foggy pixels by comparing the difference between cloud top temperature and underneath sea surface temperature from assimilated data along with the DCD method. We have used two types of cloud top temperature, which obtained from 11 μm brightness temperature (B_S1) and operational COMS algorithm (B_S2). The detected foggy 1794 pixels from B_S1 and 1490 pixel from B_S2 are significantly reduced the overestimation detected by the DCD method. However, 477 and 446 pixels have been found to be real foggy pixels, 329 and 264 pixels be clear, and 989 and 780 pixels be other type of clouds, detected by B_S1 and B_S2 respectively. The analysis of the operational COMS fog detection algorithm reveals that the cloud screening process was strictly enforced, which resulted in underestimation of foggy pixel. The 538 of total detected foggy pixels obtain only 187 of real foggy pixels, but 61 of clear pixels and 290 of other type clouds. Our analysis suggests that there is no winner for nighttime sea fog detection algorithms, but loser because real foggy pixels are less than 30% among the foggy pixels declared by all algorithms. This overwhelming evidence reveals that current nighttime sea fog algorithms have provided a lot of misjudged information, which are mostly originated from difficulty in distinguishing between clear and cloudy scene as well as fog and other type clouds. Therefore, in-depth researches are urgently required to reduce the enormous error in nighttime sea fog detection from satellite.
목차
Abstract
1. 서론
2. 자료
3. 본론
4. 결론
REFERENCES
참고문헌 (35)
참고문헌 신청
1. [학술지(정기간행물)] - Ahn, M.-H. / 2003 / A new algorithm for sea fog/stratus detection using GMS-5 IR data / Adv. Atmos. Sci 20 : 899 ~ 913
2. [단행본] - Ahrens, C. D / 2001 / Essentials of Meteorology: An invitation to the Atmosphere / Brooks/Cole : 94 ~
3. [학술대회논문] - Bendix, J / 1991 / Operational detection of fog in the alpine region by means of advanced very high resolution radiometer (AVHRR) imagery of NOAA-satellites / Proc. 5th AVHRR Data User’s Meeting : 307 ~ 312
4. [학술대회논문] - Bendix, J / 2003 / Fog Detection With Terra-MODIS and MSG-SEVIRI / Proc. 2003 Meteorological Satellite Data Users’ Conference
5. [학술대회논문] - Bendix, J. / 2004 / New perspectives in remote sensing of fog and low stratus-TERRA/ AQUA-MODIS and MSG / Proc. 3rd International Conference on Fog
2. [단행본] - Ahrens, C. D / 2001 / Essentials of Meteorology: An invitation to the Atmosphere / Brooks/Cole : 94 ~
3. [학술대회논문] - Bendix, J / 1991 / Operational detection of fog in the alpine region by means of advanced very high resolution radiometer (AVHRR) imagery of NOAA-satellites / Proc. 5th AVHRR Data User’s Meeting : 307 ~ 312
4. [학술대회논문] - Bendix, J / 2003 / Fog Detection With Terra-MODIS and MSG-SEVIRI / Proc. 2003 Meteorological Satellite Data Users’ Conference
5. [학술대회논문] - Bendix, J. / 2004 / New perspectives in remote sensing of fog and low stratus-TERRA/ AQUA-MODIS and MSG / Proc. 3rd International Conference on Fog
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