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Evaluation of CLDAS and GLDAS Datasets for Near-Surface Air Temperature over Major Land Areas of China

Author

Listed:
  • Shuai Han

    (Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China
    National Engineering Laboratory of Efficient Crop Water Use and Disaster Reduction, Beijing 100081, China
    Key Laboratory of Agricultural Environment, Ministry of Agriculture, Beijing 100081, China
    National Meteorological Information Center, Beijing 100081, China)

  • Buchun Liu

    (Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China
    National Engineering Laboratory of Efficient Crop Water Use and Disaster Reduction, Beijing 100081, China
    Key Laboratory of Agricultural Environment, Ministry of Agriculture, Beijing 100081, China)

  • Chunxiang Shi

    (National Meteorological Information Center, Beijing 100081, China)

  • Yuan Liu

    (Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China
    National Engineering Laboratory of Efficient Crop Water Use and Disaster Reduction, Beijing 100081, China
    Key Laboratory of Agricultural Environment, Ministry of Agriculture, Beijing 100081, China)

  • Meijuan Qiu

    (Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China
    National Engineering Laboratory of Efficient Crop Water Use and Disaster Reduction, Beijing 100081, China
    Key Laboratory of Agricultural Environment, Ministry of Agriculture, Beijing 100081, China)

  • Shuai Sun

    (National Meteorological Information Center, Beijing 100081, China)

Abstract

As one of the most principal meteorological factors to affect global climate change and human sustainable development, temperature plays an important role in biogeochemical and hydrosphere cycle. To date, there are a wide range of temperature data sources and only a detailed understanding of the reliability of these datasets can help us carry out related research. In this study, the hourly and daily near-surface air temperature observations collected at national automatic weather stations (NAWS) in China were used to compare with the China Meteorological Administration (CMA) Land Data Assimilation System (CLDAS) and the Global Land Data Assimilation System (GLDAS), both of which were developed by using the advanced multi-source data fusion technology. Results are as follows. (1) The spatial and temporal variations of the near-surface air temperature agree well between CLDAS and GLDAS over major land of China, except that spatial details in high mountainous areas were not sufficiently displayed in GLDAS; (2) The near-surface air temperature of CLDAS were more significantly correlated with observations than that of GLDAS, but more caution is necessary when using the data in mountain areas as the accuracy of the datasets gradually decreases with increasing altitude; (3) CLDAS can better illustrate the distribution of areas of daily maximum above 35 °C and help to monitor high temperature weather. The main conclusion of this study is that CLDAS near-surface air temperature has a higher reliability in China, which is very important for the study of climate change and sustainable development in East Asia.

Suggested Citation

  • Shuai Han & Buchun Liu & Chunxiang Shi & Yuan Liu & Meijuan Qiu & Shuai Sun, 2020. "Evaluation of CLDAS and GLDAS Datasets for Near-Surface Air Temperature over Major Land Areas of China," Sustainability, MDPI, vol. 12(10), pages 1-19, May.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:10:p:4311-:d:362565
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    References listed on IDEAS

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    1. Xinlei Hu & Zuliang Zhao & Lin Zhang & Zhe Liu & Shaoming Li & Xiaodong Zhang, 2019. "A High-Temperature Risk Assessment Model for Maize Based on MODIS LST," Sustainability, MDPI, vol. 11(23), pages 1-15, November.
    2. Yao-Tsung Ko, 2020. "Modeling an Innovative Green Design Method for Sustainable Products," Sustainability, MDPI, vol. 12(8), pages 1-23, April.
    3. Cristina Raluca Gh. Popescu & Gheorghe N. Popescu, 2019. "An Exploratory Study Based on a Questionnaire Concerning Green and Sustainable Finance, Corporate Social Responsibility, and Performance: Evidence from the Romanian Business Environment," JRFM, MDPI, vol. 12(4), pages 1-79, October.
    4. Huan Wang & Jiejun Huang & Han Zhou & Lixue Zhao & Yanbin Yuan, 2019. "An Integrated Variational Mode Decomposition and ARIMA Model to Forecast Air Temperature," Sustainability, MDPI, vol. 11(15), pages 1-11, July.
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    1. Yanqin Xu & Shuai Han & Chunxiang Shi & Rui Tao & Jiaojiao Zhang & Yu Zhang & Zheng Wang, 2023. "Comparative Analysis of Three Near-Surface Air Temperature Reanalysis Datasets in Inner Mongolia Region," Sustainability, MDPI, vol. 15(17), pages 1-21, August.

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