Climate Change Research ›› 2021, Vol. 17 ›› Issue (6): 730-743.doi: 10.12006/j.issn.1673-1719.2021.005
• Changes in Climate System • Previous Articles Next Articles
Evaluation on the performance of CMIP6 global climate models with different horizontal resolution in simulating the precipitation over China
HU Yi-Yang1,2(
), XU Ying2(), LI Jin-Jian1, HAN Zhen-Yu2
- 1 Chengdu University of Information Technology, Chengdu 610225, China
2 Laboratory for Climate Studies, China Meteorological Administration, Beijing 100081, China
-
Received:2021-01-06Revised:2021-03-10Online:2021-11-30Published:2021-11-26 -
Contact:XU Ying E-mail:491706897@qq.com;xuying@cma.gov.cn
Cite this article
HU Yi-Yang, XU Ying, LI Jin-Jian, HAN Zhen-Yu. Evaluation on the performance of CMIP6 global climate models with different horizontal resolution in simulating the precipitation over China[J]. Climate Change Research, 2021, 17(6): 730-743.
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Table 1 Basic information on 9 sets of global climate models provided by HighResMIP in CMIP6
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Table 1 Basic information on 9 sets of global climate models provided by HighResMIP in CMIP6
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Fig. 1 Observation (a) and low-resolution MME (b) and high-resolution MME (c) of mean annual precipitation, and the relative deviation (d, e) between simulated results and observation in 1961-2014 (The dots indicate that 78% or more of models agree on the sign of biases)
Fig. 1 Observation (a) and low-resolution MME (b) and high-resolution MME (c) of mean annual precipitation, and the relative deviation (d, e) between simulated results and observation in 1961-2014 (The dots indicate that 78% or more of models agree on the sign of biases)
Fig. 2 The spatial distribution of model biases in mean annual precipitation in 1961-2014. (a) Low-resolution models, (b) high-resolution models (The number corresponds to Table 1)
Fig. 2 The spatial distribution of model biases in mean annual precipitation in 1961-2014. (a) Low-resolution models, (b) high-resolution models (The number corresponds to Table 1)
Fig. 3 Box-and-whisker plots for multi-year average monthly precipitation distribution in China simulated by low-resolution models (purple) and high-resolution models (black) during 1961-2014 (The upper and lower boundaries of the box represent the 75% and 25% quantiles respectively)
Fig. 3 Box-and-whisker plots for multi-year average monthly precipitation distribution in China simulated by low-resolution models (purple) and high-resolution models (black) during 1961-2014 (The upper and lower boundaries of the box represent the 75% and 25% quantiles respectively)
Fig. 4 Taylor diagram for low-resolution models (a), high-resolution models (b) simulated seasonal and annual precipitation in China during 1961-2014 compared with the observation (The different colors represent the season, and the different numbers represent the model)
Fig. 4 Taylor diagram for low-resolution models (a), high-resolution models (b) simulated seasonal and annual precipitation in China during 1961-2014 compared with the observation (The different colors represent the season, and the different numbers represent the model)
Fig. 5 Low-resolution models (b) and high-resolution models (c) simulated EOF1 of interannual variation of summer precipitation spatial distribution in eastern China during 1961-2014 and observation (a). (b0 and c0 are MME. Dot area in panels indicates that they are all statistically significant at the 95% confidence level. The green box indicates that the spatial positive correlation with observation is statistically significant at the 95% confidence level)
Fig. 5 Low-resolution models (b) and high-resolution models (c) simulated EOF1 of interannual variation of summer precipitation spatial distribution in eastern China during 1961-2014 and observation (a). (b0 and c0 are MME. Dot area in panels indicates that they are all statistically significant at the 95% confidence level. The green box indicates that the spatial positive correlation with observation is statistically significant at the 95% confidence level)
Fig. 6 As in Fig. 5 except for EOF2
Fig. 6 As in Fig. 5 except for EOF2
Table 2 The spatial correlation coefficients of the first and second dominant mode of interannual variation by each model groups and observation
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Table 2 The spatial correlation coefficients of the first and second dominant mode of interannual variation by each model groups and observation
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Fig. 7 As in Fig. 5 except for the EOF1 of interdecadal variation
Fig. 7 As in Fig. 5 except for the EOF1 of interdecadal variation
Fig. 8 As in Fig. 7 except for EOF2
Fig. 8 As in Fig. 7 except for EOF2
Table 3 The spatial correlation coefficients of the first and second dominant mode of interdecadal variation by each mode model groups and observation
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Table 3 The spatial correlation coefficients of the first and second dominant mode of interdecadal variation by each mode model groups and observation
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