气候变化领域集成服务门户(CCPortal): Novel assessment of numerical forecasting model relative humidity with satellite probabilistic estimates

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DOI	10.5194/acp-22-3811-2022
	Novel assessment of numerical forecasting model relative humidity with satellite probabilistic estimates
	Radice, Chloe; Brogniez, Helene; Kirstetter, Pierre-Emmanuel; Chambon, Philippe
发表日期	2022
ISSN	1680-7316
EISSN	1680-7324
起始页码	3811
结束页码	3825
卷号	22 期号:6 页码:15
英文摘要	A novel method of comparison between an atmospheric model and satellite probabilistic estimates of relative humidity (RH) in the tropical atmosphere is presented. The method is developed to assess the Meteo-France numerical weather forecasting model ARPEGE (Action de Recherche Petite Echelle Grande Echelle) using probability density functions (PDFs) of RH estimated from the SAPHIR (Sondeur Atmospherique du Profil d'Humidite Intertropicale par Radiometrie) microwave sounder. The satellite RH reference is derived by aggregating footprint-scale probabilistic RH to match the spatial and temporal resolution of ARPEGE over the April-May-June 2018 period. The probabilistic comparison is discussed with respect to a classical deterministic comparison confronting each model RH value to the reference average and using a set confidence interval. This study first documents the significant spatial and temporal variability in the reference distribution spread and shape. We demonstrate the need for a finer assessment at the individual case level to characterize specific situations beyond the classical bulk comparison using determinist best reference estimates. The probabilistic comparison allows for a more contrasted assessment than the deterministic one. Specifically, it reveals cases where the ARPEGE-simulated values falling within the deterministic confidence range actually correspond to extreme departures in the reference distribution, highlighting the shortcomings of the too-common Gaussian assumption of the reference, on which most current deterministic comparison methods are based.
学科领域	Environmental Sciences; Meteorology & Atmospheric Sciences
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
WOS记录号	WOS:000773398900001
来源期刊	ATMOSPHERIC CHEMISTRY AND PHYSICS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/273123
作者单位	Centre National de la Recherche Scientifique (CNRS); UDICE-French Research Universities; Sorbonne Universite; Universite Paris Cite; Universite Paris Saclay; University of Oklahoma System; University of Oklahoma - Norman; National Oceanic Atmospheric Admin (NOAA) - USA; Centre National de la Recherche Scientifique (CNRS); Meteo France; Universite de Toulouse
推荐引用方式 GB/T 7714	Radice, Chloe,Brogniez, Helene,Kirstetter, Pierre-Emmanuel,et al. Novel assessment of numerical forecasting model relative humidity with satellite probabilistic estimates[J],2022,22(6):15.
APA	Radice, Chloe,Brogniez, Helene,Kirstetter, Pierre-Emmanuel,&Chambon, Philippe.(2022).Novel assessment of numerical forecasting model relative humidity with satellite probabilistic estimates.ATMOSPHERIC CHEMISTRY AND PHYSICS,22(6),15.
MLA	Radice, Chloe,et al."Novel assessment of numerical forecasting model relative humidity with satellite probabilistic estimates".ATMOSPHERIC CHEMISTRY AND PHYSICS 22.6(2022):15.