Challenges Associated with Classifying Urban Meteorological Stations: The Oklahoma City Micronet Example
Challenges Associated with Classifying Urban Meteorological Stations: The Oklahoma City Micronet Example
复制标题
与城市气象站分类相关的挑战：俄克拉荷马城微网示例
DOI：
10.2174/1874282301004010088
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
Bradley G. Illston
中科院分区：
文献类型：
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作者：
Amanda J. Schroeder;J. Basara;Bradley G. Illston
2007-2008年期间，在俄克拉荷马州城市大都市区部署了密集的气象站网络，以收集整个城市环境中大气变量的实时、研究质量观测：俄克拉荷马州城市气象网（OKCNET）。由于农村和城市地区以及整个城市的地表特征可能有很大的不同，因此部署在城市地区的气象站观测到的当地小气候存在很大的差异。因此，记录任何地点附近的特征（即，元数据）对于充分了解该地点的总体代表性和大气条件的相关演变至关重要。到目前为止，还没有一个通用的城市气象站分类系统。因此，本研究利用四种不同的方法对OKCNET网站进行分类，并增加单个网站和整个网络的元数据。结果表明，虽然每个分类系统都有其具体的优点，但由于（a）与方法有关的局限性和（B）地表条件的异质性，在为这些地点建立一致的元数据方面存在重大挑战。特别是，部署在城市到郊区和郊区到农村的过渡区内的台站在为这些地点建立一致的元数据方面面临最大的挑战。
During 2007-2008, a dense network of meteorological stations was deployed across the Oklahoma City metropolitan area to collect real-time, research-quality observations of atmospheric variables throughout the urban environment: the Oklahoma City Micronet (OKCNET). Because surface characteristics can be vastly different between rural and urban areas as well as throughout a city, significant variability exists in the local microclimates observed by meteorological stations deployed in an urban area. As such, documenting the characteristics near any site (i.e., metadata) is critical to fully understand the overall representativeness of the site and the associated evolution of atmospheric conditions. To date, a universal classification system for urban meteorological stations does not exist. Thus, this study utilized four different methodologies to classify OKCNET sites and increase the metadata for the individual sites and the overall network. The results demonstrated that while each classification system had specific merits, significant challenges existed in establishing consistent metadata for the sites due to (a) limitations associated with the methodologies and (b) the heterogeneity of surface conditions. In particular, stations deployed within the transition zones form urban to suburban and suburban to rural posed the greatest challenges in establishing consistent metadata for the sites.