CMIP6模式对中国气温日较差的模拟能力评估

王双双; 谢文强; 延晓冬

doi:10.3878/j.issn.1006-9585.2021.21063

CMIP6模式对中国气温日较差的模拟能力评估

doi: 10.3878/j.issn.1006-9585.2021.21063

北京师范大学地理科学学部地表过程与资源生态国家重点实验室，北京100875

基金项目: 国家重点研发计划2018YFC509003、2019YFA0606904

详细信息

作者简介:
王双双，女，1995年出生，硕士研究生，从事气候变化相关研究。E-mail: wangss@mail.bnu.edu.cn

通讯作者:
延晓冬, E-mail: yxd@bnu.edu.cn

中图分类号: P467
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- 被引次数: 0
出版历程
- 收稿日期: 2021-04-05
- 网络出版日期: 2021-08-30
- 刊出日期: 2022-01-25

Evalution on CMIP6 Model Simulation of the Diurnal Temperature Range over China

State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875

Funds: National Key Research and Development Project (Grants 2018YFC509003 and 2019YFA0606904)

摘要

摘要: 利用CRU_TS v4.04观测数据作为验证，对28个CMIP6 (Coupled Model Intercomparison Project 6) 模式模拟中国区域内气温日较差（Diurnal Temperature Range, DTR）年际变化、气候平均态变化以及不同区域和不同季节尺度变化的能力进行评估。结果表明：在百年尺度上，CMIP6模式能够反映出年际变化中DTR下降的演变趋势，模式与观测之间的相关系数在0.1～0.7，均方根误差在0.6～1.5，Taylor 评分（Taylor Score, TS）在0.2～0.7，MRI-ESM2-0模式与观测之间的相关系数（0.65）最大，均方根误差（0.8）最小，TS（0.67）最高，模拟能力最好；在30年气候平均态尺度上，CMIP6模式符合观测呈现的DTR北方地区高、南方地区低，西部地区高、东部地区低，内陆地区高、沿海地区低，高原地区高、平原盆地地区低的空间分布特征，基本可以再现中国大范围区域内DTR下降的空间分布特征，对不同区域和不同季节DTR变化也有较好的模拟，以EC-Earth3模式的模拟能力最好。然而，单模式存在不同程度的高估或低估DTR变化的现象，多模式中位数集合能够模拟出DTR在年际变化和气候平均态变化中的一些特征，对于春季和冬季的模拟，多模式集合优于单模式模拟。
- CMIP6模式 /
- 气温日较差 /
- 模式评估 /
- 气候态 /
- 年际变化
Abstract: The ability of 28 CMIP6 (Coupled Model Intercomparison Project 6) models that simulate the interannual variation and change of the climate mean state of the Diurnal Temperature Range (DTR) in China and different regional and seasonal scales was evaluated by using the CRU_TS v4.04 observation data as the benchmark. The results showed that the CMIP6 models can reflect the declining trend of the DTR at a centennial time scale in the interannual variation. The correlation coefficient between the model and the observation is 0.1–0.7, root-mean-square error is 0.6–1.5, and Taylor Score (TS) is 0.2–0.7. The correlation coefficient between the MRI-ESM2-0 model and the observation is the highest (0.65), root-mean-square error (0.8) is the lowest, and TS (0.67) is the highest. This indicates that the MRI-ESM2-0 model has the best simulation ability. At a 30-year climate mean scale, the CMIP6 models accord with the observed spatial distribution characteristics of the DTR, which is high in northern China, low in southern China, high in western China, high in eastern China, high in inland China, low in coastal areas, high in the plateau, and low in the plain basin. CMIP6 models can basically reproduce the declining trend over a large area of China in the climate mean state, and the DTR variation in different regions and seasons are also well simulated, with the EC-Earth3 model exhibiting the best performance. However, the individual model is easy to overestimate or underestimate the DTR variation to some extent. The multi-model ensemble can simulate some characteristics of the DTR in the interannual variation and change of the climate mean state, which is better than the single model for the spring and winter simulation.
- CMIP6 models /
- Diurnal temperature range /
- Model evaluation /
- Climatology /
- Interannual variation

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图 1 中国六大区域分布

Figure 1. Six regional distributions in China

下载: 全尺寸图片幻灯片

图 2 CRU观测、多模式集合和28个气候模式在1901~2014年均气温日较差距平值的年际变化

Figure 2. Interannual variations of the CRU observation dataset, ensemble, and 28 climate models about annual Diurnal Temperature Range (DTR) anomalies from 1901 to 2014

下载: 全尺寸图片幻灯片

图 3 CMIP6模式模拟的1901～2014年气温日较差年际变化的泰勒图（红点Ref表示观测，扇形半径上的值表示模式相较于观测的标准差，扇形弧上的值表示模式与观测的相关系数，扇形内绿色虚线圆弧上的值表示模式与观测之间的均方根误差）

Figure 3. Taylor diagram of the interannual variation of the DTR simulated by CMIP6 models from 1901 to 2014. The red dot Ref represents the observation, the value on the fan-shaped radius represents the standard deviation of the model compared to the observation, the value on the fan-shaped arc represents the correlation coefficient between the model and the observation, and the value on the green dotted arc inside the fan-shaped represents the root-mean-square error between the model and the observation

下载: 全尺寸图片幻灯片

图 4 CMIP6模式模拟的1901～2014年气温日较差年际变化的TS评分（虚线表示多模式集合的评分线，可以直观地与单模式进行比较）

Figure 4. Taylor score of the interannual variation of the DTR simulated by CMIP6 models from 1901 to 2014. The dotted line represents the scoring line for the ensemble and can be compared intuitively with the single model

下载: 全尺寸图片幻灯片

5 CMIP6模式模拟与CRU观测的1941～1970年气温日较差气候平均态的空间分布

5. Climatology of the annual mean DTR from 1941 to 1970 simulated by CMIP6 models and CRU over China

下载: 全尺寸图片幻灯片

6 CMIP6模式模拟与CRU观测1985～2014年相较1955～1984年气温日较差气候平均态变化的空间分布（带点区域即为通过95%信度检验）

6. Change of the annual mean DTR from 1955–1984 to 1985–2014 simulated by CMIP6 models and CRU data over China. The dotted areas pass the 95% confidence test

下载: 全尺寸图片幻灯片

图 7 CMIP6模式模拟1941～1970年中国六大区域不同季节气温日较差变化的小提琴图（黄色五角星代表观测值，白色圆点代表中位数，上下边界代表最大、最小值，箱体的宽窄表示模式数据的分布密度，越宽表示数据越集中，越窄表示数据越稀疏）

Figure 7. Violin plot of the DTR variation in different seasons during 1941–1970 simulated by CMIP6 models over six regions of China (yellow five-pointed star represents the observed value, white dot represents the median, and the upper and lower boundaries represent the maximum and minimum values, respectively. The width of the box represents the distribution density of the model data. The wider the box is, the more concentrated the data are. The narrower the box is, the sparser the data are)

下载: 全尺寸图片幻灯片

表 1 28个CMIP6模式简介

Table 1. Description of the 28 CMIP6 models used in the study

	国家	机构	分辨率（纬度格点数×经度格点数）
ACCESS-CM2	澳大利亚	CSIRO-ARCCSS	144×192
ACCESS-ESM1-5	澳大利亚	CSIRO	145×192
AWI-CM-1-1-MR	德国	AWI	192 × 384
AWI-ESM-1-1-LR	德国	AWI	96×192
BCC-CSM2-MR	中国	BCC	160×320
BCC-ESM1	中国	BCC	64×128
CanESM5	加拿大	CCCma	64×128
EC-Earth3	瑞典	EC-Earth-Consortium	256×512
EC-Earth3-AerChem	瑞典	EC-Earth-Consortium	256×512
EC-Earth3-Veg	瑞典	EC-Earth-Consortium	256×512
EC-Earth3-Veg-LR	瑞典	EC-Earth-Consortium	160×320
FGOALS-f3-L	中国	CAS	180×288
FGOALS-g3	中国	CAS	80×180
GFDL-CM4	美国	NOAA-GFDL	180×288
GFDL-ESM4	美国	NOAA-GFDL	180×288
GISS-E2-1-G	美国	NASA-GISS	90×144
INM-CM4-8	俄罗斯	INM	120×180
INM-CM5-0	俄罗斯	INM	120×180
IPSL-CM6A-LR	法国	IPSL	143×144
KACE-1-0-G	韩国	NIMS-KMA	144×192
KIOST-ESM	韩国	KIOST	96×192
MIROC6	日本	MIROC	128×256
MPI-ESM-1-2-HAM	德国	HAMMOZ-Consortium	96×192
MPI-ESM1-2-HR	德国	MPI-M	192×384
MPI-ESM1-2-LR	德国	MPI-M	96×192
MRI-ESM2-0	日本	MRI	160×320
NorESM2-MM	挪威	NCC	192×288
SAM0-UNICON	韩国	SNU	192×288

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