Theoretical and Applied Climatology

, Volume 132, Issue 3–4, pp 857–865 | Cite as

An analysis of spatial representativeness of air temperature monitoring stations

  • Suhua Liu
  • Hongbo SuEmail author
  • Jing TianEmail author
  • Weizhen Wang
Original Paper


Surface air temperature is an essential variable for monitoring the atmosphere, and it is generally acquired at meteorological stations that can provide information about only a small area within an r m radius (r-neighborhood) of the station, which is called the representable radius. In studies on a local scale, ground-based observations of surface air temperatures obtained from scattered stations are usually interpolated using a variety of methods without ascertaining their effectiveness. Thus, it is necessary to evaluate the spatial representativeness of ground-based observations of surface air temperature before conducting studies on a local scale. The present study used remote sensing data to estimate the spatial distribution of surface air temperature using the advection-energy balance for air temperature (ADEBAT) model. Two target stations in the study area were selected to conduct an analysis of spatial representativeness. The results showed that one station (AWS 7) had a representable radius of about 400 m with a possible error of less than 1 K, while the other station (AWS 16) had the radius of about 250 m. The representable radius was large when the heterogeneity of land cover around the station was small.



This work is supported by the National Natural Science Foundation of China (grant number 41571356), the National Key Research and Development Program of China (grant number 2016YFA0602501), and the National Natural Science Foundation of China (grant numbers 41671354, 41671373, 41671368, 41371348).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© Springer-Verlag Wien 2017

Authors and Affiliations

  1. 1.Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.Department of Civil, Environmental and Geomatics EngineeringFlorida Atlantic UniversityFloridaUSA
  4. 4.Cold and Arid Regions Environmental and Engineering Research InstituteChinese Academy of SciencesLanzhouChina

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