期刊
INTERNATIONAL JOURNAL OF CLIMATOLOGY
卷 38, 期 5, 页码 2250-2264出版社
WILEY
DOI: 10.1002/joc.5331
关键词
climate change; delta downscaling; Mann-Kendall trend test; Sen's slope estimator; Loess Plateau
资金
- National Natural Science Foundation of China [41601058, 31602004]
- CAS 'Light of West China' Program [XAB2015B07]
- China Special Fund for Meteorological Research in the Public Interest [GYHY201506001-3]
- key cultivation project of Chinese Academy of Sciences 'The promotion and management of ecosystem functions of restored vegetation in Loess Plateau, China'
The Loess Plateau (LP) in China is sensitive to climate change because of its fragile ecological environment and geographic features. This study presents a detailed assessment of the climate change trends over the LP from 1901 to 2100 based on the 1-km spatial resolution climate data generated through delta downscaling. The following results are drawn: (1) Delta downscaling performs well in detecting the monthly precipitation and temperature over the LP based on the mean absolute error between downscaled data and independent surface observations. Among the 28 general circulation models, the GFDL-ESM2M and NorESM1-M models show the best performance in reproducing the monthly precipitation and temperature in the future period, respectively. (2) The annual precipitation over the entire LP shows no significant trends in the historical and future periods. By contrast, the annual temperature shows a significantly increasing trend with 0.097 degrees C/10 year in the historical period (1901-2014) and with 0.113, 0.24, 0.355, and 0.558 degrees C/10 year in the future period (2015-2100) under the RCP2.6, RCP4.5, RCP6.0, and RCP8.5 scenarios, respectively. (3) The significantly increasing trends in precipitation and temperature at each grid of the LP present various spatial distributions in terms of their magnitude. The significant trend magnitude calculated by the downscaled data has a larger range and a higher percentage of area - and is even observed at a small area-compared with that calculated by the raw data. (4) The spatial results calculated by the downscaled data provide more detailed information about the locations and percentages of area, both of which are valuable in assessing the change trends in precipitation and temperature. These spatio-temporal results present the climate change trends over the LP in detail and provide valuable insights for developing flexible adaptation and mitigation strategies to address the climate change challenges in this region.
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