Development of High Resolution and Homogenized Gridded Land Surface Air Temperature Data: A Case Study Over Pan-East Asia

Jiayi Cheng, Qingxiang Li, Liya Chao, Suman Maity, Boyin Huang, Phil Jones

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Abstract

The Land Surface Air Temperature (LSAT) climatology during the period of 1961–1990 and the anomalies (relative to the 1961–1990 climatology) have been developed over Pan-East Asian region at a (monthly) 0.5° × 0.5° resolution. The development of these LSAT data sets are based on the recently released C-LSAT station datasets and the high resolution Digital Elevation Model (DEM), and interpolated by the Thin Plate Spline (TPS) method (through ANUSPLIN software) and the Adjusted Inverse Distance Weighting (AIDW) method. Then they are combined into the high resolution gridded LSAT datasets (including the monthly mean, maximum, and minimum temperature). Considering the mean LSAT for example, the Cross Validation (CV) of the datasets indicates that the regional average of the Root Mean Square Error (RMSE) for the climatology is about 0.62°C, and the average RMSE and Mean Absolute Error (MAE) for the anomalies are between 0.47–0.90°C and 0.32–0.63°C during the study period. The analysis also demonstrate that the gridded anomalies describe the spatial pattern fairly well for the coldest (1912, 1969) and the warmest (1948, 2007) years during the first and second half of the 20th century. Further analysis reveals that the high resolution dataset also performs well in the estimation of long-term LSAT change trend. Thus it can be concluded that this newly constructed datasets is a useful tool for regional climate monitoring, climate change research as well as climate model verification.

Original languageEnglish
Article number588570
JournalFrontiers in Environmental Science
Volume8
DOIs
Publication statusPublished - 29 Oct 2020

Keywords

  • adjusted inverse distance weight (AIDW)
  • gridded dataset
  • high resolution
  • land surface air temperature (LSAT)
  • thin plate spline (TPS)

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