IPCC AR5全球气候模式对1996-2005年中国气温模拟精度评价

doi:10.18306/dlkxjz.2015.10.003

摘要/Abstract

摘要：

本文利用中国660个站点逐日地面温度资料,评估了参与政府间气候变化专门委员会第五次报告(IPCC AR5)的9个全球气候模式(Global Climate Models, GCMs)及多模式集合(Multi-Model Ensemble, MME)对中国地区气温的模拟精度。结果表明：9个IPCC AR5全球气候模式和MME模拟的中国地区1996-2005年日平均气温与气象站点观测值的相关系数都大于0.86,表明相关性较好;气候模式模拟的中国东南部地区1996-2005年日平均气温的模拟精度较高,模拟值的偏差、平均相对误差、平均绝对误差和均方根误差都比较小;而西部地区的模拟效果较差,模拟精度较低。综合考虑模式模拟值与站点观测值的相关系数、偏差、平均相对误差、平均绝对误差和均方根误差发现,MME在中国地区的气温模拟精度优于大部分单个模式。

关键词: IPCC AR5, 全球气候模式, 气温, 精度, 日尺度

Abstract:

This article evaluates the precision of the temperature simulated by nine IPCC AR5 (the Fifth Assessment Report of the Intergovernmental Panel on Climate Change) GCMs (Global Climate Models) and the multi-model ensemble (MME), based on the observed temperature of 660 stations in China from 1996 to 2005. The results show that the correlation coefficients between the average daily temperature simulated by GCMs and station observations in China during 1996-2005 were very high, all above 0.86. The precision of the simulated average daily temperature in the southeast by the 10 models was higher than that in the west, judged by the lower Biases, mean relative errors (MREs), mean absolute errors (MAEs), and root mean square errors (RMSEs) in the southeast as compared to those in the west. The precision of the simulated temperature by IPSL-CM5A-LR, MRI-CGCM3, and NorESM1-M was poorer than that of the others—specially, the Biases, MREs, and RMSEs of the simulation result by IPSL-CM5A-LR , the Biases and RMSEs of the simulation result by MRI-CGCM3, and MREs and RMSEs of the simulation result by NorESM1-M, were larger. Taken into account the Biases, MREs, MAEs, and RMSEs, the simulation precision of MME was the highest.

Key words: IPCC AR5, Global Climate Models, temperature, precision, daily scale

孙侦, 贾绍凤, 吕爱锋, 朱文彬, 高彦春. IPCC AR5全球气候模式对1996-2005年中国气温模拟精度评价[J]. 地理科学进展, 2015, 34(10): 1229-1240.

Zhen SUN, Shaofeng JIA, Aifeng LV, Wenbin ZHU, Yanchun GAO. Assesment on precision of temperature simulated by the IPCC AR5 GCMs in China, 1996-2005[J]. PROGRESS IN GEOGRAPHY, 2015, 34(10): 1229-1240.

图/表 7

表1

图1

图2

表2

1996-2005年IPCC AR5全球气候模式模拟逐日平均气温精度的评估结果/%"

Models	$r > 0.98$	$r < 0.92$	$\| Bias \| < 0.5$	$\| Bias \| > 1.5$	$MRE < 0.2$	$MRE > 0.6$	$MAE < 2$	$MAE > 4$	$RMSE < 2$	$RMSE > 6$
BCC	67.9	0.9	70.2	6.2	70.9	1.1	24.5	31.4	11.7	16.4
BNU	44.8	0	73.9	5.6	79.4	0.9	31.7	24.5	18.5	12.4
CanESM2	56.4	1.2	77.4	6.2	82.9	1.1	38.8	23.6	14.5	14.2
CCSM4	68.5	0.3	81.7	7.3	82.9	2.9	40.8	19.8	16.5	11.4
MPI-ESM-LR	63.8	3.0	82.3	7.1	82.1	2.9	54.7	16.1	31.2	10.3
MRI-CGCM3	68.2	0	69.2	10.8	78.6	3.5	16.1	28.8	8.0	17.1
NorESM1-M	69.1	0.3	71.4	7.7	76.5	2.3	17.1	30.8	7.4	17.6
GISS-E2-R	36.8	0.5	82.3	7.0	73.8	3.9	33.5	22.4	13.2	14.5
IPSL-CM5A-LR	55.5	0.2	62.1	9.7	74.5	3.6	26.1	36.1	10.5	20.0
MME	88.0	0	78.6	6.4	80.6	1.8	47.9	22.0	37.0	12.0

表2

图3

图4

图5

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模式名称	国家	研究机构	空间分辨率(纬向格点数×经向格点数)
BCC	中国	国家气候中心	64×128
BNU	中国	北京师范大学	64×128
CanESM2	加拿大	CCCma	64×128
CCSM4	美国	NCAR	192×288
GISS-E2-R	美国	GISS/ NASA	90×144
IPSL-CM5A-LR	法国	IPSL	96×96
MPI-ESM-LR^*	德国	MPI	96×192
MRI-CGCM3^*	日本	MRI	160×320
NorESM1-M	挪威	NCC	96×144

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