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    Sensitivity of Surface Analyses over the Western United States to RAWS Observations

    Source: Weather and Forecasting:;2008:;volume( 023 ):;issue: 001::page 145
    Author:
    Myrick, David T.
    ,
    Horel, John D.
    DOI: 10.1175/2007WAF2006074.1
    Publisher: American Meteorological Society
    Abstract: Federal, state, and other wildland resource management agencies contribute to the collection of weather observations from over 1000 Remote Automated Weather Stations (RAWS) in the western United States. The impact of RAWS observations on surface objective analyses during the 2003/04 winter season was assessed using the Advanced Regional Prediction System (ARPS) Data Assimilation System (ADAS). A set of control analyses was created each day at 0000 and 1200 UTC using the Rapid Update Cycle (RUC) analyses as the background fields and assimilating approximately 3000 surface observations from MesoWest. Another set of analyses was generated by withholding all of the RAWS observations available at each time while 10 additional sets of analyses were created by randomly withholding comparable numbers of observations obtained from all sources. Random withholding of observations from the analyses provides a baseline estimate of the analysis quality. Relative to this baseline, removing the RAWS observations degrades temperature (wind speed) analyses by an additional 0.5°C (0.9 m s?1) when evaluated in terms of rmse over the entire season. RAWS temperature observations adjust the RUC background the most during the early morning hours and during winter season cold pool events in the western United States while wind speed observations have a greater impact during active weather periods. The average analysis area influenced by at least 1.0°C (2.5°C) by withholding each RAWS observation is on the order of 600 km2 (100 km2). The spatial influence of randomly withheld observations is much less.
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      Sensitivity of Surface Analyses over the Western United States to RAWS Observations

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    contributor authorMyrick, David T.
    contributor authorHorel, John D.
    date accessioned2017-06-09T16:21:32Z
    date available2017-06-09T16:21:32Z
    date copyright2008/02/01
    date issued2008
    identifier issn0882-8156
    identifier otherams-66410.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4207743
    description abstractFederal, state, and other wildland resource management agencies contribute to the collection of weather observations from over 1000 Remote Automated Weather Stations (RAWS) in the western United States. The impact of RAWS observations on surface objective analyses during the 2003/04 winter season was assessed using the Advanced Regional Prediction System (ARPS) Data Assimilation System (ADAS). A set of control analyses was created each day at 0000 and 1200 UTC using the Rapid Update Cycle (RUC) analyses as the background fields and assimilating approximately 3000 surface observations from MesoWest. Another set of analyses was generated by withholding all of the RAWS observations available at each time while 10 additional sets of analyses were created by randomly withholding comparable numbers of observations obtained from all sources. Random withholding of observations from the analyses provides a baseline estimate of the analysis quality. Relative to this baseline, removing the RAWS observations degrades temperature (wind speed) analyses by an additional 0.5°C (0.9 m s?1) when evaluated in terms of rmse over the entire season. RAWS temperature observations adjust the RUC background the most during the early morning hours and during winter season cold pool events in the western United States while wind speed observations have a greater impact during active weather periods. The average analysis area influenced by at least 1.0°C (2.5°C) by withholding each RAWS observation is on the order of 600 km2 (100 km2). The spatial influence of randomly withheld observations is much less.
    publisherAmerican Meteorological Society
    titleSensitivity of Surface Analyses over the Western United States to RAWS Observations
    typeJournal Paper
    journal volume23
    journal issue1
    journal titleWeather and Forecasting
    identifier doi10.1175/2007WAF2006074.1
    journal fristpage145
    journal lastpage158
    treeWeather and Forecasting:;2008:;volume( 023 ):;issue: 001
    contenttypeFulltext
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