气候变化领域集成服务门户(CCPortal): Improved Himawari-8/AHI Radiance Data Assimilation With a Double Cloud Detection Scheme

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DOI	10.1029/2020JD032631
	Improved Himawari-8/AHI Radiance Data Assimilation With a Double Cloud Detection Scheme
	Li X.; Zou X.; Zhuge X.; Zeng M.; Wang N.; Tang F.
发表日期	2020
ISSN	2169897X
卷号	125 期号:13
英文摘要	This study explores the possibility of improving the impact of the Advanced Himawari Imager (AHI) clear-sky radiance data assimilation (DA), focusing on cloud detection. First, the performance of the “clear-channel” detection scheme of the minimum residual (MR) method embedded in the Gridpoint Statistical Interpolation (GSI) DA system is compared with the performances of the CLouds from Advanced Very High Resolution Radiometer Extended (CLAVR-x) cloud processing system and the Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-product-generating algorithm. The MR scheme does not reliably identify optically thin clouds along cloud edges. The MR-estimated cloud-top pressures are often too high for upper-level clouds, rendering some cloud-contaminated channels falsely clear. An infrared-only AHI cloud mask (ACM) algorithm is added to the MR scheme to perform a so-called double cloud detection (DCD). The DCD scheme adds nine ACM tests for selecting clear pixels and two thin cloud tests for rejecting pixels affected by upper-level clouds. For a 1-month period, we show the positive impacts of assimilating AHI infrared channels on short-term forecasts of temperature and humidity using the DCD scheme rather than the MR scheme. Improvements in the DCD experiment extend more vertically, horizontally, and temporally than those in the MR experiment during the 48-hr forecasting time. In terms of daily variations in forecasting performance, the DCD experiment consistently improves while the MR experiment fluctuates between improvement and degradation. Such improvements come from an elimination of those data having negative observation-minus-background values of large magnitudes due to cloud contamination, which causes positive biases in humidity analyses. ©2020. American Geophysical Union. All Rights Reserved.
英文关键词	cloud detection; data assimilation; satellite infrared imager
语种	英语
来源期刊	Journal of Geophysical Research: Atmospheres
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/185951
作者单位	Key Laboratory of Transportation Meteorology, CMA, Nanjing, China; Jiangsu Research Institute of Meteorological Sciences, Nanjing, China; Nanjing Joint Institute for Atmospheric Sciences, Nanjing, China; The Joint Center for Data Assimilation Research and Applications, Nanjing University of Information Science and Technology, Nanjing, China; School of Atmospheric Sciences and Key Laboratory of Mesoscale Severe Weather of the Ministry of Education, Nanjing University, Nanjing, China; Jiangsu Climate Center, Nanjing, China
推荐引用方式 GB/T 7714	Li X.,Zou X.,Zhuge X.,et al. Improved Himawari-8/AHI Radiance Data Assimilation With a Double Cloud Detection Scheme[J],2020,125(13).
APA	Li X.,Zou X.,Zhuge X.,Zeng M.,Wang N.,&Tang F..(2020).Improved Himawari-8/AHI Radiance Data Assimilation With a Double Cloud Detection Scheme.Journal of Geophysical Research: Atmospheres,125(13).
MLA	Li X.,et al."Improved Himawari-8/AHI Radiance Data Assimilation With a Double Cloud Detection Scheme".Journal of Geophysical Research: Atmospheres 125.13(2020).