globalchange  > 影响、适应和脆弱性
DOI: 10.1002/2016JD025408
论文题名:
Deep convective cloud characterizations from both broadband imager and hyperspectral infrared sounder measurements
作者: Ai Y.; Li J.; Shi W.; Schmit T.J.; Cao C.; Li W.
刊名: Journal of Geophysical Research: Atmospheres
出版年: 2017
卷: 122, 期:3
起始页码: 1700
结束页码: 1712
语种: 英语
英文关键词: broadband imager ; deep convective cloud ; hyperspectral IR sounder
Scopus关键词: accuracy assessment ; aircraft ; AIRS ; brightness temperature ; convective cloud ; detection method ; imagery ; MTSAT ; radiance ; radiative transfer ; signal-to-noise ratio ; spectral resolution ; storm ; water vapor
英文摘要: Deep convective storms have contributed to airplane accidents, making them a threat to aviation safety. The most common method to identify deep convective clouds (DCCs) is using the brightness temperature difference (BTD) between the atmospheric infrared (IR) window band and the water vapor (WV) absorption band. The effectiveness of the BTD method for DCC detection is highly related to the spectral resolution and signal-to-noise ratio (SNR) of the WV band. In order to understand the sensitivity of BTD to spectral resolution and SNR for DCC detection, a BTD to noise ratio method using the difference between the WV and IR window radiances is developed to assess the uncertainty of DCC identification for different instruments. We examined the case of AirAsia Flight QZ8501. The brightness temperatures (Tbs) over DCCs from this case are simulated for BTD sensitivity studies by a fast forward radiative transfer model with an opaque cloud assumption for both broadband imager (e.g., Multifunction Transport Satellite imager, MTSAT-2 imager) and hyperspectral IR sounder (e.g., Atmospheric Infrared Sounder) instruments; we also examined the relationship between the simulated Tb and the cloud top height. Results show that despite the coarser spatial resolution, BTDs measured by a hyperspectral IR sounder are much more sensitive to high cloud tops than broadband BTDs. As demonstrated in this study, a hyperspectral IR sounder can identify DCCs with better accuracy. ©2017. American Geophysical Union. All Rights Reserved.
资助项目: "The RTTOV model in this study was run on computers provided by the University of Wisconsin-Madison Space Science Engineering Center (SSEC). ECMWF is thanked for the operational model analysis data set. The data from AIRS, MTSAT-2, COMS-1, and Himawari-8 imagery were obtained from SSEC's Data Center at the University of Wisconsin-Madison (http://www.ssec.wisc.edu/datacenter/). The CloudSat/CAPLISO data were obtained freely from the CloudSat Data Processing Center (http://www.cloudsat.cira.colostate.edu). This work was completed during Y. Ai and W. Shi's visit to the University of Wisconsin-Madison funded by the China Scholarship Council (CSC). This research is partly supported by the NOAA GOES-R high-impact weather and proving ground programs and the JPSS algorithm project. Tim Schmit, NOAA NESDIS STAR, is thanked for constructive comments on this manuscript. The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy of any agency of the U.S. government.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/62707
Appears in Collections:影响、适应和脆弱性
气候减缓与适应

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作者单位: Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, China; Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin-Madison, Madison, WI, United States; State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China; Center for Satellite Applications and Research, NESDIS/NOAA, Silver Spring, MD, United States

Recommended Citation:
Ai Y.,Li J.,Shi W.,et al. Deep convective cloud characterizations from both broadband imager and hyperspectral infrared sounder measurements[J]. Journal of Geophysical Research: Atmospheres,2017-01-01,122(3)
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