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Local-scale validation of the Surface Observation Gridding System with in situ weather observations in a semi-arid environment

机译:半干旱环境中具有地面天气观测的地面观测网格系统的局部验证

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摘要

Although the Surface Observation Gridding System (SOGS) provides spatially continuous models of meteorological conditions, little work has been done to validate SOGS data independently for site-specific research and, as a result, a single nearby weather station is commonly selected instead. This study sought to determine local-scale accuracy of SOGS data (1) by correlation with independent, in situ weather station measurements and (2) relative to a nearby weather station. Correlations between SOGS data and in situ weather observations and between in situ weather observations and a nearby weather station were examined in a semi-arid environment of southeastern Idaho over the 2006 growing season. The results indicate that both SOGS and nearby weather station data were significantly correlated with in situ weather station measurements. Although temperature correlations between in situ and the nearby weather station were slightly greater compared to SOGS, SOGS data were a better predictor of precipitation. This suggests that the use of a nearby weather station is appropriate for local temperature parameters but precipitation parameters are better estimated using SOGS data. Overall, the validation of the SOGS weather models agreed closely with independent, in situ weather measurements and, as a result, greater confidence can be placed in the accuracy of the productivity, biomass and global climate change models derived from these data.
机译:尽管地面观测网格系统(SOGS)提供了空间连续的气象条件模型,但是很少进行任何工作来独立验证SOGS数据以进行特定地点的研究,因此,通常会选择一个附近的气象站。这项研究试图确定SOGS数据的局部尺度精度(1)通过与独立的原地气象站测量值相关以及(2)相对于附近气象站的相关性。在2006年生长季节期间,在爱达荷州东南部的半干旱环境中,研究了SOGS数据与原位气象观测值之间以及原位气象观测值与附近气象站之间的相关性。结果表明,SOGS和附近的气象站数据均与原地气象站测量值显着相关。尽管与SOGS相比,原位与附近气象站之间的温度相关性稍高,但SOGS数据是降水的更好预测指标。这表明使用附近的气象站适合当地的温度参数,但使用SOGS数据可以更好地估算降水参数。总体而言,SOGS天气模型的验证与独立的原位天气测量结果非常吻合,因此,人们可以更加放心地根据这些数据得出的生产力,生物量和全球气候变化模型的准确性。

著录项

  • 来源
    《International journal of remote sensing》 |2010年第16期|p.4411-4422|共12页
  • 作者单位

    GIS Training and Research Centre, Idaho State University, Pocatello, ID 83209-8104,USA;

    GIS Training and Research Centre, Idaho State University, Pocatello, ID 83209-8104,USA;

    Departement de Geomatique Appliquee, Universite de Sherbrooke, Sherbrooke,Quebec, Canada J1K 2R1;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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