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    GOES Multispectral Rainfall Algorithm (GMSRA)

    Source: Journal of Applied Meteorology:;2001:;volume( 040 ):;issue: 008::page 1500
    Author:
    Ba, Mamoudou B.
    ,
    Gruber, Arnold
    DOI: 10.1175/1520-0450(2001)040<1500:GMRAG>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: A multispectral approach is used to optimize the identification of raining clouds located at a given altitude estimated from the cloud-top temperature. The approach combines information from five channels on the National Oceanic and Atmospheric Administration Geostationary Operational Environmental Satellite (GOES): visible (0.65 ?m), near infrared (3.9 ?m), water vapor (6.7 ?m), and window channels (11 and 12 ?m). The screening of nonraining clouds includes the use of spatial gradient of cloud-top temperature for cirrus clouds (this screening is applied at all times) and the effective radius of cloud-top particles derived from the measurements at 3.9 ?m during daytime. During nighttime, only clouds colder than 230 K are considered for the screening; during daytime, all clouds having a visible reflectance greater than 0.40 are considered for the screening, and a threshold of 15 ?m in droplet effective radius is used as a low boundary of raining clouds. A GOES rain rate for each indicated raining cloud group referenced by its cloud-top temperature is obtained by the product of probability of rain (Pb) and mean rain rate (RRmean) and is adjusted by a moisture factor that is designed to modulate the evaporation effects on rain below cloud base for different moisture environments. The calibration of the algorithm for constants Pb and RRmean is obtained using collocated instantaneous satellite and radar data and hourly gauge-adjusted radar products collected during 17 days in June and July 1998. A comparison of the combined visible and a temperature threshold of 230 K (e.g., previous infrared/visible algorithms) with the combined visible and a threshold of 15 ?m demonstrates that the latter improves the detection of rain from warm clouds without lowering the skill of the algorithm. The quantitative validation shows that the algorithm performs well at daily and monthly scales. At monthly scales, a comparison with GOES Precipitation Index (GPI) shows that GOES Multispectral Rainfall Algorithm's performance against gauges is much better for September and October 1999.
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      GOES Multispectral Rainfall Algorithm (GMSRA)

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4148442
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    • Journal of Applied Meteorology

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    contributor authorBa, Mamoudou B.
    contributor authorGruber, Arnold
    date accessioned2017-06-09T14:08:00Z
    date available2017-06-09T14:08:00Z
    date copyright2001/08/01
    date issued2001
    identifier issn0894-8763
    identifier otherams-13036.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4148442
    description abstractA multispectral approach is used to optimize the identification of raining clouds located at a given altitude estimated from the cloud-top temperature. The approach combines information from five channels on the National Oceanic and Atmospheric Administration Geostationary Operational Environmental Satellite (GOES): visible (0.65 ?m), near infrared (3.9 ?m), water vapor (6.7 ?m), and window channels (11 and 12 ?m). The screening of nonraining clouds includes the use of spatial gradient of cloud-top temperature for cirrus clouds (this screening is applied at all times) and the effective radius of cloud-top particles derived from the measurements at 3.9 ?m during daytime. During nighttime, only clouds colder than 230 K are considered for the screening; during daytime, all clouds having a visible reflectance greater than 0.40 are considered for the screening, and a threshold of 15 ?m in droplet effective radius is used as a low boundary of raining clouds. A GOES rain rate for each indicated raining cloud group referenced by its cloud-top temperature is obtained by the product of probability of rain (Pb) and mean rain rate (RRmean) and is adjusted by a moisture factor that is designed to modulate the evaporation effects on rain below cloud base for different moisture environments. The calibration of the algorithm for constants Pb and RRmean is obtained using collocated instantaneous satellite and radar data and hourly gauge-adjusted radar products collected during 17 days in June and July 1998. A comparison of the combined visible and a temperature threshold of 230 K (e.g., previous infrared/visible algorithms) with the combined visible and a threshold of 15 ?m demonstrates that the latter improves the detection of rain from warm clouds without lowering the skill of the algorithm. The quantitative validation shows that the algorithm performs well at daily and monthly scales. At monthly scales, a comparison with GOES Precipitation Index (GPI) shows that GOES Multispectral Rainfall Algorithm's performance against gauges is much better for September and October 1999.
    publisherAmerican Meteorological Society
    titleGOES Multispectral Rainfall Algorithm (GMSRA)
    typeJournal Paper
    journal volume40
    journal issue8
    journal titleJournal of Applied Meteorology
    identifier doi10.1175/1520-0450(2001)040<1500:GMRAG>2.0.CO;2
    journal fristpage1500
    journal lastpage1514
    treeJournal of Applied Meteorology:;2001:;volume( 040 ):;issue: 008
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian