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contributor authorHou, Yu-Tai
contributor authorCampana, Kenneth A.
contributor authorMitchell, Kenneth E.
contributor authorYang, Shi-Keng
contributor authorStowe, Larry L.
date accessioned2017-06-09T17:27:26Z
date available2017-06-09T17:27:26Z
date copyright1993/12/01
date issued1993
identifier issn0739-0572
identifier otherams-856.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4229066
description abstractCLAVR [cloud from AVHRR (Advanced Very High Resolution Radiometer)] is a global cloud dataset under development at NOAA/NESDIS (National Environmental Satellite, Data, and Information Service). Total cloud amount from two experimental cases, 9 July 1986 and 9 February 1990, are intercompared with two independent products, the Air Force Real-Time Nephanalysis (RTNEPH), and the International Satellite Cloud Climatology Project (ISCCP). The ISCCP cloud database is a climate product processed retrospectively some years after the data are collected. Thus, only CLAVR and RTNEPH can satisfy the real-time requirements for numerical weather prediction (NWP) models. Compared with RTNEPH and ISCCP, which only use two channels in daytime retrievals and one at night, CLAVR utilizes all five channels in daytime and three at night from AVHRR data. That gives CLAVR a greater ability to detect certain cloud types, such as thin cirrus and low stratus. Designed to be an operational product, CLAVR is also compared with total cloud forecasts from the National Meteorological Center (NMC) Medium Range Forecast (MRF) Model. The datasets are mapped to the orbits of NOAA polar satellites, such that errors from temporal sampling are minimized. A set of statistical scores, histograms, and maps are used to display the characteristics of the datasets. The results show that the CLAVR data can realistically resolve global cloud distributions. The spatial variation is, however, less than that of RTNEPH and ISCCP, due to current constraints in the CLAVR treatment of partial cloudiness. Results suggest that if the satellite cloud data is available in real time, it can be used to improve the cloud parameterization in numerical forecast models and data assimilation systems.
publisherAmerican Meteorological Society
titleComparison of an Experimental NOAA AVHRR Cloud Dataset with Other Observed and Forecast Cloud Datasets
typeJournal Paper
journal volume10
journal issue6
journal titleJournal of Atmospheric and Oceanic Technology
identifier doi10.1175/1520-0426(1993)010<0833:COAENA>2.0.CO;2
journal fristpage833
journal lastpage849
treeJournal of Atmospheric and Oceanic Technology:;1993:;volume( 010 ):;issue: 006
contenttypeFulltext


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