Abstract
A new bias-corrected, statistically downscaled product, the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset, has been developed and released to help in understanding climate change at local to regional scales. Here, we evaluate the performance of the NEX-GDDP data in simulating daily maximum temperature (TX) and daily minimum temperature (TN) in the historical period 1961–2005 over China at national and regional scales. Projected future changes in TX and TN are assessed under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 emissions scenarios. Results show that the NEX-GDDP data can capture the basic spatial patterns of TX and TN, but these results underestimate the warming trends of TX and TN from 1961 to 2005 over China. The largest biases are found in western China due to its complex terrain conditions; these biases are 2.33 and 2.21 times larger than those found in eastern China for TX and TN, respectively. The climate projections show that the difference in uncertainties is small between the east and the west, and higher warming changes correspond to greater uncertainties. The increasing trends under the RCP8.5 are 2.22 and 2.31 times the size found under the RCP4.5 by the end of the twenty-first century for TX and TN, respectively. The Tibetan plateau has the fastest warming trend under the two scenarios.
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Acknowledgments
This research was supported by the Second Tibetan Plateau Scientific Expedition and Research (2019QZKK0405), the National Natural Science Foundation of China (No. 41877155), and the National Key Research and Development Program of China (No. 2018YFC0507004). We are grateful to the China Meteorological Administration (CMA) for providing the observed climatic data (http://data.cma.cn/) and the NASA Ames Research Center for providing the NEX-GDDP dataset (https://cds.nccs.nasa.gov/nex-gddp/). We would like to thank the high-performance computing support from the Center for Geodata and Analysis, Faculty of Geographical Science, Beijing Normal University (https://gda.bnu.edu.cn/).
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Wu, Y., Miao, C., Duan, Q. et al. Evaluation and projection of daily maximum and minimum temperatures over China using the high-resolution NEX-GDDP dataset. Clim Dyn 55, 2615–2629 (2020). https://doi.org/10.1007/s00382-020-05404-1
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DOI: https://doi.org/10.1007/s00382-020-05404-1