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Impacts of land cover changes on climate trends in Jiangxi province China

Overview of attention for article published in International Journal of Biometeorology, February 2013
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Title
Impacts of land cover changes on climate trends in Jiangxi province China
Published in
International Journal of Biometeorology, February 2013
DOI 10.1007/s00484-013-0645-z
Pubmed ID
Authors

Qi Wang, Dirk Riemann, Steffen Vogt, Rüdiger Glaser

Abstract

Land-use/land-cover (LULC) change is an important climatic force, and is also affected by climate change. In the present study, we aimed to assess the regional scale impact of LULC on climate change using Jiangxi Province, China, as a case study. To obtain reliable climate trends, we applied the standard normal homogeneity test (SNHT) to surface air temperature and precipitation data for the period 1951-1999. We also compared the temperature trends computed from Global Historical Climatology Network (GHCN) datasets and from our analysis. To examine the regional impacts of land surface types on surface air temperature and precipitation change integrating regional topography, we used the observation minus reanalysis (OMR) method. Precipitation series were found to be homogeneous. Comparison of GHCN and our analysis on adjusted temperatures indicated that the resulting climate trends varied slightly from dataset to dataset. OMR trends associated with surface vegetation types revealed a strong surface warming response to land barrenness and weak warming response to land greenness. A total of 81.1 % of the surface warming over vegetation index areas (0-0.2) was attributed to surface vegetation type change and regional topography. The contribution of surface vegetation type change decreases as land cover greenness increases. The OMR precipitation trend has a weak dependence on surface vegetation type change. We suggest that LULC integrating regional topography should be considered as a force in regional climate modeling.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 4%
Unknown 25 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 23%
Researcher 6 23%
Student > Ph. D. Student 4 15%
Professor > Associate Professor 2 8%
Professor 1 4%
Other 1 4%
Unknown 6 23%
Readers by discipline Count As %
Earth and Planetary Sciences 8 31%
Environmental Science 5 19%
Agricultural and Biological Sciences 4 15%
Social Sciences 1 4%
Medicine and Dentistry 1 4%
Other 1 4%
Unknown 6 23%