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    Statistical Characteristics of a Real-Time Precipitation Forecasting Model

    Source: Weather and Forecasting:;1998:;volume( 013 ):;issue: 004::page 966
    Author:
    Gaudet, Brian
    ,
    Cotton, William R.
    DOI: 10.1175/1520-0434(1998)013<0966:SCOART>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: At Colorado State University the Regional Atmospheric Modeling System (RAMS) has been used to produce real-time forecasts of precipitation for the Colorado mountain region since 1991. Originally a so-called dump-bucket scheme was used to generate precipitation, but starting in the fall of 1995 real-time forecasts used the bulk microphysics scheme available with RAMS. For the month of April 1995, a series of 24-h accumulated precipitation forecasts for the month were generated with both the dump-bucket and microphysics versions of the forecast model. Both sets of output were compared to a set of 167 community-based station reports and another set of 32 snow telemetry (SNOTEL) automatic pillow-sensor stations. The addition of microphysics improved the forecasting of the areal extent and maximum amount of precipitation, especially when compared to the SNOTEL observational set, which is found at locations more representative of the model topography. Climatological station precipitation forecasts were improved on the average by correcting for the difference between a station?s actual elevation and the cell-averaged topography used by the model. The model had more problems with the precise timing and geographical location of the precipitation features, probably due in part to the influence of other model physics, the failure of the model to resolve adequately wintertime convection events, and inadequate initializations.
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      Statistical Characteristics of a Real-Time Precipitation Forecasting Model

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4167346
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    contributor authorGaudet, Brian
    contributor authorCotton, William R.
    date accessioned2017-06-09T14:56:20Z
    date available2017-06-09T14:56:20Z
    date copyright1998/12/01
    date issued1998
    identifier issn0882-8156
    identifier otherams-3005.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4167346
    description abstractAt Colorado State University the Regional Atmospheric Modeling System (RAMS) has been used to produce real-time forecasts of precipitation for the Colorado mountain region since 1991. Originally a so-called dump-bucket scheme was used to generate precipitation, but starting in the fall of 1995 real-time forecasts used the bulk microphysics scheme available with RAMS. For the month of April 1995, a series of 24-h accumulated precipitation forecasts for the month were generated with both the dump-bucket and microphysics versions of the forecast model. Both sets of output were compared to a set of 167 community-based station reports and another set of 32 snow telemetry (SNOTEL) automatic pillow-sensor stations. The addition of microphysics improved the forecasting of the areal extent and maximum amount of precipitation, especially when compared to the SNOTEL observational set, which is found at locations more representative of the model topography. Climatological station precipitation forecasts were improved on the average by correcting for the difference between a station?s actual elevation and the cell-averaged topography used by the model. The model had more problems with the precise timing and geographical location of the precipitation features, probably due in part to the influence of other model physics, the failure of the model to resolve adequately wintertime convection events, and inadequate initializations.
    publisherAmerican Meteorological Society
    titleStatistical Characteristics of a Real-Time Precipitation Forecasting Model
    typeJournal Paper
    journal volume13
    journal issue4
    journal titleWeather and Forecasting
    identifier doi10.1175/1520-0434(1998)013<0966:SCOART>2.0.CO;2
    journal fristpage966
    journal lastpage982
    treeWeather and Forecasting:;1998:;volume( 013 ):;issue: 004
    contenttypeFulltext
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