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首页> 外文期刊>International Journal of Climatology: A Journal of the Royal Meteorological Society >The GeoProfile metadata, exposure of instruments, and measurement bias in climatic record revisited
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The GeoProfile metadata, exposure of instruments, and measurement bias in climatic record revisited

机译:重新审查了GeoProfile元数据,仪器的暴露情况和气候记录中的测量偏差

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Station metadata plays a critical role in the accurate assessment of climate data and eventually of climatic change, climate variability, and climate prediction. However, current procedures of metadata collection are insufficient for these purposes. This paper introduces the GeoProfile as a model for documenting and visualizing enhanced spatial metadata. In addition to traditional metadata archiving, GeoProfiles integrate meso-scale topography, slope, aspect, and land-use data from the vicinity of climate observing stations (http://kyclim.wku.edu/tmp/geoprofiles/geoprofiles-main.html). We describe how GeoProfiles are created using Geographical Information Systems (GIS) and demonstrate how they may be used to help identify measurement bias in climate observations due to undesired instrument exposures and the subsequent forcings of micro- and meso-environments. A study involving 12 COOP and US Historical Climate Network (USHCN) stations finds that undesirable instrument exposures associated with both anthropogenic and natural influences resulted in biased measurement of temperature. Differences in average monthly maximum and minimum temperatures between proximate stations are as large as 1.6 and 3.8 degrees C, respectively. In addition, it is found that the difference in average extreme monthly minimum temperatures can be as high as 3.6 degrees C between nearby stations, largely owing to the differences in instrument exposures. Likewise, the difference in monthly extreme maximum temperatures between neighboring stations are as large as 2.4 degrees C. This investigation finds similar differences in the diurnal temperature range (DTR). GeoProfiles helped us to identify meso-scale forcing, e.g. instruments on a south-facing slope and topography, in addition to forcing of micro-scale setting. Copyright (c) 2006 Royal Meteorological Society.
机译:台站元数据在准确评估气候数据以及最终评估气候变化,气候变异性和气候预测中起着至关重要的作用。但是,当前的元数据收集过程不足以实现这些目的。本文介绍了GeoProfile作为用于记录和可视化增强的空间元数据的模型。除传统的元数据存档外,GeoProfiles还集成了来自气候观测站附近的中尺度地形,坡度,坡度和土地利用数据(http://kyclim.wku.edu/tmp/geoprofiles/geoprofiles-main.html )。我们描述了如何使用地理信息系统(GIS)创建GeoProfile,并展示了如何将其用于帮助识别由于不希望的仪器暴露以及随后的微环境和中观环境的强迫而导致的气候观测中的测量偏差。一项涉及12个COOP和美国历史气候网络(USHCN)站的研究发现,与人为和自然影响相关的不良仪器暴露会导致温度测量偏差。临近站点之间的平均每月最高和最低温度之差分别高达1.6和3.8摄氏度。此外,发现附近站点之间的每月平均极端最低温度差异可能高达3.6摄氏度,这主要是由于仪器暴露的差异所致。同样,相邻站点之间的每月极端最高温度之差也高达2.4摄氏度。这项研究发现,昼夜温度范围(DTR)也存在类似的差异。 GeoProfiles帮助我们确定了中尺度强迫,例如除了强迫进行微尺度设置外,还应在朝南的坡度和地形上使用各种仪器。版权所有(c)2006皇家气象学会。

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