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Journal of Meteorological Research

, Volume 32, Issue 5, pp 758–767 | Cite as

Effects of Updated RegCM4 Land Use Data on Near-Surface Temperature Simulation in China

  • Yulong Ren
  • Yaohui LiEmail author
  • Zhaoxia Pu
  • Tiejun Zhang
  • Haixia Duan
  • Wei Wang
Special Collection on Weather and Climate under Complex Terrain and Variable Land Surfaces: Observations and Numerical Simulations
  • 231 Downloads

Abstract

Biogeophysical effects of land use and land cover (LULC) changes play a significant role in modulating climate on various spatial scales. In this study, a set of recent LULC products with a spatial resolution of 500 m was developed in China for update in RegCM4 (regional climate model version 4). Two sets of comparative numerical experiments were conducted to study the effects of LULC changes on near-surface temperature simulation. The results show that after LULC changes, areas of crops and mixed woodlands as well as urban areas increase over entire China, accompanied with greatly expanded mixed farming and forests/field mosaics in southern China, and reduced areas of 1) irrigated crops and short grasses in northern China and the Tibetan Plateau, and 2) semi-desert and desert in northwestern China. Improvements in the LULC data clearly result in more accurate simulations of the near-surface temperature. Specifically, increasing latent heat and longwave albedo due to enhanced LULC in certain areas lead to reduction in land surface temperature (LST), while changes in shortwave albedo and sensible heat also exert a great influence on the LST. Overall, these parameter adjustments reduce the biases in near-surface temperature simulation.

Key words

land use and land cover RegCM4 (regional climate model version 4) temperature simulation 

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Copyright information

© The Chinese Meteorological Society and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Yulong Ren
    • 1
  • Yaohui Li
    • 1
    Email author
  • Zhaoxia Pu
    • 2
  • Tiejun Zhang
    • 1
  • Haixia Duan
    • 1
  • Wei Wang
    • 1
  1. 1.Institute of Arid Meteorology of China Meteorological Administration (CMA)Key Laboratory of Arid Climatic Change and Disaster Reduction of Gansu Province and CMALanzhouChina
  2. 2.Department of Atmospheric SciencesUniversity of UtahUtahUSA

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