CMIP5模式对西北干旱区典型流域气温模拟能力评估——以开都-孔雀河为例

doi:10.18402/resci.2019.06.13

摘要/Abstract

摘要：

西北干旱区水资源问题突出,全球变暖将进一步加剧其水资源短缺,研究未来气候变化对流域水资源合理分配和使用具有重要意义。本文利用CRU(Climate Research Unit)数据和DCHP（Downscaled CMIP3 and CMIP5 Climate and Hydrology Projections）提供的32个经BCSD降尺度的CMIP5（全球耦合模式比较计划第五阶段）模式气温数据,采用线性倾向估计、滑动平均、M-K(Mann-Kendall)检验及滑动T（MMT）等检验法,以西北干旱区典型流域开都-孔雀河流域为例,通过对1950—2005年的年平均气温、年平均最高气温与年平均最低气温3个指标的变化趋势及突变年份进行检测,评估各模式及模式集合平均对气温变化的模拟能力。研究结果表明：①12个模式能够准确模拟出1950—2005年流域内各气温指标的显著增加趋势,8个模式能够模拟出部分气温指标的增温趋势,但均低估了增温速率,集合平均也存在同样问题;②除FIO-ESM与MPI-ESM-MR能够准确模拟出气温突变时间外,绝大多数模式不能够准确模拟出。基于优选模式的集合平均PM-PLS和PM-EE对突变的模拟能力总体上优于单个模式,其中PM-PLS模拟能力更优;③对PM-PLS模式集合平均进一步评价,发现其能较好地再现流域气温线性趋势的时空变化总体特征,但仍存在增温速率低估的问题。采用气候模式进行未来气候预估仍需加强模式优选及多模式集合平均方法的深入研究。

关键词: 气温, 泰勒图, 多模式集合平均, Mann-Kendall, 突变检验, 开都-孔雀河流域

Abstract:

Global warming will result in serve water shortage, aggravating the existing outstanding water problem in the Kaidu-Kongqi River Basin. Studies on the future climate change will contribute to the rational distribution and utilization of water in the basin. Based on the CRU(Climate Research Unit) dataset and 32 BCSD-downscaled CMIP5 model air temperature dataset from DCHP (Downscaled CMIP3 and CMIP5 Climate and Hydrology Projections), the paper assessed the simulation ability of both 32 models and multi-model ensemble mean through the test of long-term trend and abrupt change of annual average, maximum and minimum air temperature in the Kaidu-Kongqi River Basin over the period of 1950-2005 by using the methods of linear trend calculation, moving average, Mann-Kendall (M-K) test and moving T-test (MMT). Results show that (1) 12 of 32 models are capable of reproducing the significant warming trend of three temperature indicators during 1950-2005, 8 of 32 models can only simulate that of some temperature indicators, but all of them underestimate the warming rate, so does the multi-model ensemble mean. (2) Most models failed to simulate the time of abrupt change accurately except two, FIO-ESM and MPI-ESM-MR. The ensemble mean of preferred models, PM-PLS and PM-EE, are superior to the individual model in simulating abrupt change. Between them, PM-PLS is better. (3) The further evaluation indicates that the multi-model ensemble PM-PLS can better capture the linear trend of spatio-temporal characteristics, but the problem of underestimating the warming rate still exists. It appeals to strengthen the study of model optimum selection and multiple models assemble in the future climate prediction using climate models.

Key words: air temperature, Taylor diagram, multi-model ensemble mean, Mann-Kendall, abrupt change, Kaidu-Kongqi River Basin

李晓菲, 徐长春, 李路, 罗映雪, 杨秋萍, 杨媛媛. CMIP5模式对西北干旱区典型流域气温模拟能力评估——以开都-孔雀河为例[J]. 资源科学, 2019, 41(6): 1141-1153.

Xiaofei LI, Changchun XU, Lu LI, Yingxue LUO, Qiuping YANG, Yuanyuan YANG. Evaluation of air temperature of the typical river basin in desert area of Northwest China by the CMIP5 models:A case of the Kaidu-Kongqi River Basin[J]. Resources Science, 2019, 41(6): 1141-1153.

图/表 9

图1

图2

表1

表2

基于BCSD的降尺度模式及其模拟分析结果"

序号	模式名称	研究机构简称及所属国家	年平均气温			年平均最高气温			年平均最低气温
序号	模式名称	研究机构简称及所属国家	线性趋势	相关系数	是否较优模式	线性趋势	相关系数	是否较优模式	线性趋势	相关系数	是否较优模式
1	ACCESS1-0	CSIRO-BOM（澳大利亚）	0.26**	0.56**	√	0.29**	0.51**	√	0.24**	0.54**	√
2	BCC-CSM1-1	BCC（中国）	0.22**	0.49**	√	0.20**	0.39**	√	0.25**	0.54**	√
3	BCC-CSM1-1-M	BCC（中国）	0.24**	0.57**	√	0.25**	0.52**	√	0.25**	0.57**	√
4	BNU-ESM	GCESS（中国）	0.20**	0.38**	√	0.21**	0.30*	\	0.23**	0.45**	√
5	CanESM2	CCCma(加拿大)	0.25**	0.62**	√	0.21**	0.49**	√	0.28**	0.66**	√
6	CCSM4	NCAR（美国）	0.18**	0.35**	√	0.17**	0.25	\	0.19**	0.40**	√
7	CESM1-BGC	NSF-DOE-NCAR（美国）	0.24**	0.52**	√	0.24**	0.39**	√	0.26**	0.58**	√
8	CESM1-CAM5	NSF-DOE-NCAR（美国）	0.13**	0.30*	\	0.13*	0.27*	\	0.14**	0.32*	\
9	CMCC-CM	CMCC（意大利）	0.19**	0.30*	\	0.18**	0.22	\	0.18**	0.32*	\
10	CNRM-CM5	CNRM-CERFACS（法国）	0.10*	0.39**	\	0.07	0.36**	\	0.14**	0.39**	√
11	CSIRO-Mk3-6-0	CSIRO-QCCCE（澳大利亚）	0.05	0.30*	\	0.03	0.24	\	0.06	0.33*	\
12	FGOALS-g2	LASG-CESS（中国）	0.24**	0.43**	√	0.23**	0.27*	\	0.25**	0.53**	√
13	FIO-ESM	FIO（中国）	0.20**	0.38**	√	0.21**	0.34*	\	0.20**	0.39**	√
14	GFDL-CM3	NOAA GFDL（美国）	0.08	0.23	\	0.08	0.19	\	0.08	0.27*	\
15	GFDL-ESM2G	NOAA GFDL（美国）	0.21**	0.45**	√	0.21**	0.36**	√	0.22**	0.49**	√
16	GFDL-ESM2M	NOAA GFDL（美国）	0.19**	0.59**	√	0.18**	0.56**	√	0.21**	0.59**	√
17	GISS-E2-R	NOAA GISS（美国）	0.12*	0.28*	\	0.07	0.18	\	0.17**	0.34**	\
18	GISS-E2-R-CC	NOAA GISS（美国）	0.20**	0.52**	√	0.16**	0.39**	√	0.24**	0.61**	√
19	HadCM3	MOHC(英国)	0.12*	0.32*	\	0.11	0.22	\	0.13*	0.38**	\
20	HadGEM2-AO	NIMR/KMA（韩国/英国）	0.22**	0.51**	√	0.19**	0.41**	√	0.26**	0.57**	√
21	INMCM4	INM（俄罗斯）	0.12**	0.22	\	0.04	0.03	\	0.16**	0.28*	\
22	IPSL-CM5A-LR	IPSL（法国）	0.23**	0.45**	√	0.21**	0.42**	√	0.14**	0.28*	\
23	IPSL-CM5A-MR	IPSL（法国）	0.26**	0.42**	√	0.18**	0.34**	√	0.19**	0.37**	\
24	IPSL-CM5B-LR	IPSL（法国）	0.11*	0.26	\	0.13**	0.29*	\	0.06	0.12	\
25	MIROC4h	MIROC（日本）	0.24**	0.49**	√	0.23**	0.38**	√	0.25**	0.56**	√
26	MIROC5	MIROC（日本）	0.09	0.32*	\	0.08	0.20	\	0.11	0.40**	\
27	MIROC-ESM	MIROC（日本）	0.10*	0.37**	\	0.10	0.28*	\	0.11*	0.43**	\
28	MIROC-ESM-CHEM	MIROC（日本）	0.15*	0.18	\	0.13*	0.04	\	0.18**	0.31*	\
29	MPI-ESM-LR	MPI-M（德国）	0.23**	0.35**	√	0.22**	0.30*	\	0.24**	0.38**	√
30	MPI-ESM-MR	MPI-M（德国）	0.24**	0.48**	√	0.22**	0.37**	√	0.26**	0.54**	√
31	MRI-CGCM3	MRI（日本）	0.10	0.18	\	0.09	0.10	\	0.11*	0.23	\
32	NorESM1-M	NCC（挪威）	0.23**	0.55**	√	0.24**	0.45**	√	0.24**	0.57**	√
33	EE		0.18**	0.73**		0.17**	0.62**		0.19**	0.80**
34	PM-EE		0.23**	0.77**		0.21**	0.68**		0.23**	0.83**
35	PLS		0.21**	0.80**		0.19**	0.69**		0.22**	0.85**
36	PM-PLS		0.23**	0.81**		0.22**	0.69**		0.25**	0.86**
	CRU		0.34**			0.27**			0.40**

表2

图3

表3

图4

图5

图6

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站点	巴音布鲁克	巴伦台	焉耆	库尔勒	铁干里克
月平均气温	0.983**	0.983**	0.995**	0.997**	0.998**
月平均最高气温	0.973**	0.974**	0.986**	0.997**	0.993**
月平均最低气温	0.974**	0.950**	0.979**	0.996**	0.997**

序号	模式名称	年平均气温	年平均最高气温	年平均最低气温
1	ACCESS1-0	1997	1997	1997
2	BCC-CSM1-1	1984	1982	1984
3	BCC-CSM1-1-M	1985	1975	1977
4	BNU-ESM	1984	1984	1983
5	CanESM2	1996	1997	1995
6	CCSM4	1995	1995	1997
7	CESM1-BGC	1980	1980	1980
8	CESM1-CAM5	1994	1985	1993
9	CMCC-CM	1996	2000	1986
10	CNRM-CM5	1997	1998	1996
11	CSIRO-Mk3-6-0	1956,2003	1955,2002	1951,1956,2003
12	FGOALS-g2	1993	1993	1990
13	FIO-ESM	1986	1986	1985
14	GFDL-CM3	2000	1999	2001
15	GFDL-ESM2G	1993	1994	1996
16	GFDL-ESM2M	1995	1995	1994
17	GISS-E2-R	1996	1997,2001,2004	1993
18	GISS-E2-R-CC	1997	1997	1982
19	HadCM3	1954,1958,2003	1952,1959,2004	2004
20	HadGEM2-AO	1995	1993	1996
21	INMCM4	1984	1997	1980
22	IPSL-CM5A-LR	1992	1993	1993
23	IPSL-CM5A-MR	1982	1982	1979
24	IPSL-CM5B-LR	1983	1971	1993
25	MIROC4h	1993	1986	1993
26	MIROC5	2004	1952,1954,2004	2004
27	MIROC-ESM	2003	1998	1999,2000,2004
28	MIROC-ESM-CHEM	1984	1991,1998	1987
29	MPI-ESM-LR	1978	1981	1975
30	MPI-ESM-MR	1987	1987	1985
31	MRI-CGCM3	1975	1977	1975
32	NorESM1-M	1992	1992	1992
33	EE	1994	1995	1994
34	PM-EE	1986	1987	1988
35	PLS	1994	1995	1993
36	PM-PLS	1987	1990	1987
	CRU	1987	1987	1987