globalchange  > 气候减缓与适应
DOI: 10.1029/2017JD028063
Scopus记录号: 2-s2.0-85048982711
论文题名:
Evaluation of Radiative Transfer Models With Clouds
作者: Aumann H.H.; Chen X.; Fishbein E.; Geer A.; Havemann S.; Huang X.; Liu X.; Liuzzi G.; DeSouza-Machado S.; Manning E.M.; Masiello G.; Matricardi M.; Moradi I.; Natraj V.; Serio C.; Strow L.; Vidot J.; Chris Wilson R.; Wu W.; Yang Q.; Yung Y.L.
刊名: Journal of Geophysical Research: Atmospheres
ISSN: 2169897X
出版年: 2018
卷: 123, 期:11
起始页码: 6142
结束页码: 6157
语种: 英语
英文关键词: climate ; cloud ; hyperspectral ; infrared ; radiative transfer ; weather forecasting
Scopus关键词: AIRS ; climate ; cloud ; cloud cover ; cloud radiative forcing ; correlation ; histogram ; model test ; radiative transfer ; temperature ; vertical profile ; water vapor ; weather forecasting
英文摘要: Data from hyperspectral infrared sounders are routinely ingested worldwide by the National Weather Centers. The cloud-free fraction of this data is used for initializing forecasts which include temperature, water vapor, water cloud, and ice cloud profiles on a global grid. Although the data from these sounders are sensitive to the vertical distribution of ice and liquid water in clouds, this information is not fully utilized. In the future, this information could be used for validating clouds in National Weather Center models and for initializing forecasts. We evaluate how well the calculated radiances from hyperspectral Radiative Transfer Models (RTMs) compare to cloudy radiances observed by AIRS and to one another. Vertical profiles of the clouds, temperature, and water vapor from the European Center for Medium-Range Weather Forecasting were used as input for the RTMs. For nonfrozen ocean day and night data, the histograms derived from the calculations by several RTMs at 900 cm−1 have a better than 0.95 correlation with the histogram derived from the AIRS observations, with a bias relative to AIRS of typically less than 2 K. Differences in the cloud physics and cloud overlap assumptions result in little bias between the RTMs, but the standard deviation of the differences ranges from 6 to 12 K. Results at 2,616 cm−1 at night are reasonably consistent with results at 900 cm−1. Except for RTMs which use full scattering calculations, the bias and histogram correlations at 2,616 cm−1 are inferior to those at 900 cm−1 for daytime calculations. ©2018. American Geophysical Union. All Rights Reserved.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/113698
Appears in Collections:气候减缓与适应

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作者单位: Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States; Department of Climate and Space Science, University of Michigan, Ann Arbor, MI, United States; European Center for Medium-Range Weather Forecasting, Reading, United Kingdom; UK Met Office, Exeter, United Kingdom; NASA Langley Research Center, Hampton, VA, United States; School of Engineering, University of Basilicata, Potenza, Italy; Department of Physics, University of Maryland, Baltimore County, Catonsville, MD, United States; ESSIC, University of Maryland, College Park, MD, United States; Meteo France, Toulouse, France; Department of Planetary Science, California Institute of Technology, Pasadena, CA, United States

Recommended Citation:
Aumann H.H.,Chen X.,Fishbein E.,et al. Evaluation of Radiative Transfer Models With Clouds[J]. Journal of Geophysical Research: Atmospheres,2018-01-01,123(11)
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