地理学报 ›› 2017, Vol. 72 ›› Issue (9): 1555-1568.doi: 10.11821/dlxb201709002
收稿日期:
2017-05-10
修回日期:
2016-07-18
出版日期:
2017-09-30
发布日期:
2017-09-30
作者简介:
作者简介:张学珍(1981-), 博士, 副研究员, 主要从事地—气相互作用研究。E-mail:
基金资助:
Xuezhen ZHANG1(), Xiaxiang LI2, Xinchuang XU3(
), Lijuan ZHANG2
Received:
2017-05-10
Revised:
2016-07-18
Published:
2017-09-30
Online:
2017-09-30
Supported by:
摘要:
未来气候变化情景预估是制定气候变化应对和适应策略的科学基础。本文利用参与耦合模式比较计划第五阶段(CMIP5)的30个气候模式的模拟数据,通过评估各模式对历史气候变化的模拟能力,筛选出模拟区域气候变化的最优模式组合,进而建立偏最小二乘回归(PLS)集合预估模型,据此利用最优模式模拟结果预估区域温度和降水变化情景。通过与历史数据的对比,研究发现本文基于最优模式建立的PLS集合预估模型不仅优于传统的多模式集合平均,而且也优于利用全部模式建立的PLS集合预估模型,体现了模式优选过程的重要性。本文基于优选模式的PLS集合预估模型预估结果表明:① 21世纪各区域温度将持续上升,且冬半年升温速率总体大于夏半年,北方地区升温速率总体高于南方地区;RCP 4.5排放情景下温度上升先快后慢,转折点出现在21世纪中期,RCP 8.5排放情景下,呈持续增加趋势,至21世纪末的升温幅度约为RCP 4.5情景的2倍。② 21世纪各区降水变化均呈显著增加趋势,并表现出高排放情景大于低排放情景,少雨区大于多雨区的特征,但是降水增加过程伴有明显的年代际波动。对比发现,传统的等权重集合平均全部模式(EMC)方法预估的中国夏季变暖速率高于冬季,且降水基本呈线性增加,有悖于全球变暖的基本特征及中国降水具有鲜明的年代际变化特征的基本认识。因而,本文预估的温度和降水变化特征均更符合中国气候变化的基本规律。
张学珍, 李侠祥, 徐新创, 张丽娟. 基于模式优选的21世纪中国气候变化情景集合预估[J]. 地理学报, 2017, 72(9): 1555-1568.
Xuezhen ZHANG, Xiaxiang LI, Xinchuang XU, Lijuan ZHANG. Ensemble projection of climate change scenarios of China in the 21st century based on the preferred climate models[J]. Acta Geographica Sinica, 2017, 72(9): 1555-1568.
表1
30个CMIP5模式的空间分辨率和所属机构
编号 | 模式名称 | 分辨率 | 所属国家、研究中心 |
---|---|---|---|
1 | CCSM4 | 1.250°×0.942° | 美国国家大气研究中心 |
2 | CESM1-BGC | 1.250°×0.942° | 美国国家大气研究中心 |
3 | CESM1-CAM5 | 1.250°×0.942° | 美国国家大气研究中心 |
4 | CMCC-CM | 0.750°×0.750° | 意大利欧洲-地中海气候中心 |
5 | CMCC-CMS | 1.875°×1.875° | 意大利地中海气候中心 |
6 | CNRM-CM5 | 1.406°×1.401° | 法国气象研究中心 |
7 | CSIRO-Mk3-6-0 | 1.875°×1.875° | 澳大利亚联邦科学与工业研究组织 |
8 | CanESM2 | 2.813°×2.791° | 加拿大气候模拟与分析中心 |
9 | FGOALS-g2 | 2.813°×3.000° | 中国科学院大气物理研究所 |
10 | GFDL-CM3 | 2.500°×2.000° | 美国地球物理流体动力学实验室 |
11 | GFDL-ESM2G | 2.500°×2.000° | 美国地球物理流体动力学实验室 |
12 | GFDL-ESM2M | 2.500°×2.000° | 美国地球物理流体动力学实验室 |
13 | GISS-E2-H | 2.500°×2.000° | 美国国家航空与太空总署 |
14 | GISS-E2-H-CC | 2.500°×2.000° | 美国国家航空与太空总署 |
15 | GISS-E2-R | 2.500°×2.000° | 美国地球物理流体动力学实验室 |
16 | GISS-E2-R-CC | 2.500°×2.000° | 美国国家航空与太空总署 |
17 | IPSL-CM5A-LR | 2.500°×1.268° | 法国Pierre-Simon物理学研究所 |
18 | IPSL-CM5A-MR | 3.750°×1.895° | 法国Pierre-Simon物理学研究所 |
19 | IPSL-CM5B-LR | 3.750°×1.895° | 法国Pierre-Simon物理学研究所 |
20 | MIROC-ESM | 2.813°×2.790° | 日本海洋地球科学与技术局、大气海洋研究所和国家环境变化研究所 |
21 | MIROC-ESM-CHEM | 2.813°×2.790° | 日本海洋地球科学与技术局、大气海洋研究所和国家环境变化研究所 |
22 | MIROC5 | 1.406°×1.400° | 日本气候系统研究中心、国家环境研究所和全球变化研究中心 |
23 | MPI-ESM-LR | 1.875°×1.865° | 德国普朗克气象研究所 |
24 | MPI-ESM-MR | 1.875°×1.865° | 德国普朗克气象研究所 |
25 | MRI-CGCM3 | 1.125°×1.121° | 日本气象研究所 |
26 | NorESM1-M | 2.500°×1.895° | 挪威气候中心 |
27 | NorESM1-ME | 2.500°×1.895° | 挪威气候中心 |
28 | bcc-csm1-1 | 1.250°×1.250° | 中国气象局,北京气候中心 |
29 | bcc-csm1-1-m | 2.800°×2.800° | 中国气象局,北京气候中心 |
30 | inmcm4 | 2.000°×1.500° | 俄罗斯数值模拟研究所 |
表2
不同模式组合、不同集合方法的性能对比
变量 | 区域 | 季节 | 最佳模式PLS模型外推序列与同期CRU序列相关性 | 全部模式PLS模型外推序列与同期CRU序列相关性 | 等权集合平均序列与CRU序列相关性,1931-2005年 | 最佳模式PLS模拟与CRU相关性 | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
F30 ≥ L45 | L30 ≥ F45 | F30 ≥ L45 | L30 ≥ F45 | 最佳模式 | 全模式 | 1931-2005年 | ||||||
温度 | 东北区 | 夏 | 0.64**** | 0.52**** | 0.45*** | 0.28* | 0.60**** | 0.51**** | 0.64**** | |||
冬 | 0.43*** | 0.34** | 0.21 | 0.08 | 0.58**** | 0.48**** | 0.59**** | |||||
农牧交错带 | 夏 | 0.65**** | 0.37** | 0.22 | 0.12 | 0.64**** | 0.52**** | 0.67**** | ||||
冬 | 0.64**** | 0.31** | 0.34** | 0.22 | 0.66**** | 0.56**** | 0.67**** | |||||
西北区 | 夏 | 0.58**** | 0.30** | -0.06 | 0.07 | 0.52**** | 0.46**** | 0.54**** | ||||
冬 | 0.50**** | 0.32** | 0.33** | 0.22 | 0.55**** | 0.46**** | 0.56**** | |||||
华北区 | 夏 | 0.63**** | 0.28* | -0.03 | 0.15 | 0.47**** | 0.37**** | 0.49**** | ||||
冬 | 0.68**** | 0.30* | 0.53**** | 0.19 | 0.62**** | 0.56**** | 0.65**** | |||||
江淮区 | 夏 | 0.40*** | 0.35** | 0.28* | 0.12 | 0.40**** | 0.25** | 0.42**** | ||||
冬 | 0.71**** | 0.55**** | 0.44*** | 0.37** | 0.70**** | 0.50**** | 0.71**** | |||||
长江中下游区 | 夏 | 0.30* | 0.35** | 0.18 | 0.05 | 0.32** | 0.03 | 0.35*** | ||||
冬 | 0.55**** | 0.42*** | 0.48**** | 0.36** | 0.54**** | 0.35*** | 0.57**** | |||||
华南区 | 夏 | 0.35** | 0.35** | -0.04; | 0.21; | 0.56**** | 0.34*** | 0.51**** | ||||
冬 | 0.48*** | 0.35** | 0.24 | 0.21 | 0.53**** | 0.33*** | 0.54**** | |||||
降水 | 少雨 | 年 | - | - | - | - | 0.27** | 0.05 | - | |||
多雨 | 年 | 0.43** | 0.44** | 0.32** | 0.27* | 0.40**** | -0.12 | 0.43**** |
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