基于CMIP5模式的2006—2017年中亚降水预估误差分析

doi:10.7523/j.issn.2095-6134.2021.03.006

中国科学院大学学报 ›› 2021, Vol. 38 ›› Issue (3): 333-340.DOI: 10.7523/j.issn.2095-6134.2021.03.006

基于CMIP5模式的2006—2017年中亚降水预估误差分析

黄芳^1,2, 甘淼¹, 于洋^1,2, 他志杰³, 张海燕^1,2, 皮原月^1,2, 孙凌霄^1,2, 于瑞德^1,2

1. 中国科学院新疆生态与地理研究所荒漠与绿洲生态国家重点实验室, 乌鲁木齐 830011;
2. 中国科学院大学, 北京 100049;
3. 西北农林科技大学, 西安 712100

收稿日期:2019-07-25 修回日期:2019-11-21 发布日期:2021-05-17
通讯作者: 甘淼
基金资助:
中国科学院百人计划C类（Y931201）和中国科学院新疆生态与地理研究所高层次人才培育计划专项（Y871171）资助

Error analysis concerning 2006-2017 Central Asia precipitation estimation based on CMIP5 model

HUANG Fang^1,2, GAN Miao¹, YU Yang^1,2, TA Zhijie³, ZHANG Haiyan^1,2, PI Yuanyue^1,2, SUN Lingxiao^1,2, YU Ruide^1,2

1. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China;
2. University of Chinese Academy of Sciences, Beijing 100049, China;
3. Northwest Agriculture and Forestry University, Xian 712100, China

Received:2019-07-25 Revised:2019-11-21 Published:2021-05-17

摘要/Abstract

摘要： 利用第5次耦合模式计划（CMIP5）的24个模式模拟数据，与英国East Anglia大学气候研究中心Climatic Research Unit（CRU）提供的2006—2017年的月降水格点数据进行比较，通过误差空间分布、误差百分率、标准差以及误差趋势分析，对多模式集合下的中亚降水预估误差进行评估。结果表明：模式集合对中亚大部分地区的年均降水预估偏多，尤其是东南部帕米尔高原与西天山的少数区域，误差偏大明显；夏半年（6—11月）在中亚东南及南部部分地区降水预估明显偏多，对中亚东北大部分区域降水预估偏少但不明显；冬半年（12及1—5月）中亚大部分区域降水量预估偏多，帕米尔高原西部部分区域以及巴尔喀什湖东部降水预估偏少，预估偏多与偏少均不明显。同时发现，中亚西部与西北部年、夏半年、冬半年模式间标准差均小于中亚东部及东南部；中亚大部分地区尤其中部的年、夏半年与冬半年降水预估误差均呈现减小趋势；厄尔尼诺年以及拉尼娜年的降水预估误差的空间分布决定多年平均预估误差分布特征。各种误差分析表明，直接使用CMIP5模式预估未来降水存在较大的不确定性，可能多来自模式本身存在的问题，如分辨率及地形处理、积云对流参数化方案、降水物理过程等描述不完善。

关键词: CMIP5, 中亚降水, 多模式集合, 误差分析

Abstract: The 24-model simulated data of the coupled model intercomparison project phase 5 (CMIP5) are used to compare with the 2006-2017 monthly precipitation grid data provided by the Climatic Research Unit (CRU) of the University of East Anglia from UK, and the evaluation of the precipitation estimation error concerning Central Asia under the multi-model ensemble is conducted through analysis of error spatial distribution, percentage errors, standard deviations and error trends. The results show that the model-ensemble precipitation is overestimated in most part of Central Asia, and it is obvious in the south-east Pamirs and West Tianshan Mountains; in the summer-half year, it is obviously overestimated in some regions of the south-eastern and southern Central Asia, but underestimated in north-east Central Asia; while in the winter-half year, it is overestimated in most part of Central Asia, and the precipitation is underestimated in the eastern Balkhash Lake and some regions in western Pamirs Plateau, with both the estimations errors are not obvious. Meanwhile, it is discovered that, the standard deviations in western and north-western parts of Central Asia among the annual, summer-half year and winter-half year are less than those in eastern and south-eastern parts of Central Asia; and the annual, summer-half year and winter-half year precipitation errors concerning most regions in Central Asia especially its middle part all show a declining trend; the spatial distribution of precipitation estimation error in El Nino and La Nina years determined the characteristics of the multi-year average estimated error distribution. The different error analysis shows that there would be severe larger uncertainty if estimating Central Asia precipitation directly using the CMIP5 outputs, and such uncertainty is most probably the result of the model's inherent problems, such as the defective descriptions of resolution ratio and topographic treatment, cumulus convection parameterization scheme, physical process of precipitation.

Key words: CMIP5, precipitation in Central Asia, multi-model ensemble, error analysis

中图分类号:

K903

黄芳, 甘淼, 于洋, 他志杰, 张海燕, 皮原月, 孙凌霄, 于瑞德. 基于CMIP5模式的2006—2017年中亚降水预估误差分析[J]. 中国科学院大学学报, 2021, 38(3): 333-340.

HUANG Fang, GAN Miao, YU Yang, TA Zhijie, ZHANG Haiyan, PI Yuanyue, SUN Lingxiao, YU Ruide. Error analysis concerning 2006-2017 Central Asia precipitation estimation based on CMIP5 model[J]. Journal of University of Chinese Academy of Sciences, 2021, 38(3): 333-340.

参考文献

[1] Stocker T F, Qin D, Plattner G K, et al. IPCC. Climate Change 2013:the physical science basis[M]. Cambridge, UK and New York, NY, USA:Cambridge University Press, 2013.
[2] 赵天保,陈亮,马柱国.CMIP5多模式对全球典型干旱半干旱区气候变化的模拟与预估[J].科学通报,2014, 59(12):1148-1163.
[3] 姚遥,罗勇,黄建斌.8个CMIP5模式对中国极端气温的模拟和预估[J].气候变化研究进展,2012, 8(4):250-256.
[4] 张芳,董敏,吴统文.CMIP5模式对ENSO现象的模拟能力评估[J].气象学报,2014, 72(1):30-48.
[5] Grotch S L, MacCracken M C. The use of general circulation models to predict regional climate change[J]. Journal of Climate, 1991, 4(3):286-303.
[6] 董文杰,周天军,郭彦,等.气候现象及其与未来区域气候变化的联系[J]. 气候变化研究进展,2014, 10(1):60-64.
[7] 姜燕敏,吴昊旻.20个CMIP5模式对中亚地区年平均气温模拟能力评估[J].气候变化研究进展,2013, 9(2):110-116.
[8] 任余龙,王劲松,石彦军,等.NCAR CAM3全球气候模式对亚洲中部干旱区气候变化的模拟检验[J].干旱气象,2013, 31(2):231-239.
[9] 陈鹏翔,江志红,彭冬梅.基于BP-CCA统计降尺度的中亚春季降水的多模式集合模拟与预估[J].气象学报,2017, 75(2):236-247.
[10] 姜燕敏,吴昊旻.20个CMIP5模式对中亚地区年平均气温模拟能力评估[J].气候变化研究进展,2013, 9(2):110-116.
[11] 吴昊旻,黄安宁,何清,等.10个CMIP5模式预估中亚地区未来50a降水时空变化特征[J].干旱区地理,2013, 36(4):669-679.
[12] 王劲松,陈发虎,张强,等.亚洲中部干旱半干旱区近100年来的气温变化研究[J].高原气象,2008, 27(5):1035-1045.
[13] Chen F H, Huang W, Jin L Y, et al. Spatiotemporal precipitation variations in the arid Central Asia in the context of global warming[J]. Science China:Earth Sciences, 2011, 54(12):1812-1821.
[14] 黄伟,吴娴,陈建徽,等.中亚干旱区降水准两年周期振荡及突变特征[J].气候变化研究进展,2012, 8(6):448-455.
[15] 黄秋霞,赵勇,何清.基于CRU资料的中亚地区气候特征[J].干旱区研究,2013, 30(3):396-403.
[16] Meinshausen M, Smith S J, Calvin K, et al. The RCP greenhouse gas concentrations and their extensions from 1765 to 2300[J]. Climatic Change, 2011, 109(1-2):213-241.
[17] Vuuren D P V, Stehfest E, Elzen M G J D, et al. RCP2.6:exploring the possibility to keep global mean temperature increase below 2℃[J]. Climatic Change, 2011, 109(1-2):95-116.
[18] Thomson A M, Calvin K V, Smith S J, et al. RCP4.5:a pathway for stabilization of radiative forcing by 2100[J]. Climatic Change, 2011, 109(1-2):77-94.
[19] Riahi K, Rao S, Krey V, et al. RCP8.5:a scenario of comparatively high greenhouse gas emissions[J]. Climatic Change, 2011, 109(1-2):33-57.
[20] Wang J, Chen F, Jin L, et al. Characteristics of the dry/wet trend over arid central Asia over the past 100 years[J]. Climate Research, 2010, 41(1):51-59.
[21] 陈曦,姜逢清,王亚俊,等.亚洲中部干旱区生态地理格局研究[J].干旱区研究,2013, 30(3):385-390.
[22] 陈发虎,黄伟,靳立亚,等.全球变暖背景下中亚干旱区降水变化特征及其空间差异[J].中国科学:地球科学,2011, 41(11):1647-1657.
[23] 迪丽努尔·托列吾别克,李栋梁.近115a中亚干湿气候变化研究[J].干旱气象,2018, 36(2):185-195.
[24] 杨莲梅,关学锋,张迎新.亚洲中部干旱区降水异常的大气环流特征[J].干旱区研究,2018, 35(2):249-259.
[25] 王小玲,宋文玲.ENSO与登陆我国热带气旋的关系研究[J].热带气象学报,2009, 25(5):576-580.
[26] 张蓓.基于CMIP5模式21世纪前期中国气温和降水的统计订正与预估[D].兰州:兰州大学,2016.
[27] 徐利岗,杜历,姚海娇,等.中亚干旱区降水时空变化特征及趋势分析[J].干旱区资源与环境,2015, 29(11):121-127.
[28] 黄伟,陈建徽,张肖剑,等.现代气候条件下降水变化的"西风模态"空间范围及其影响因子初探[J].中国科学:地球科学,2015, 45(4):379-388.
[29] 卫翔谦.干旱半干旱区下垫面参数变化对东亚气候的敏感性研究[D].兰州:兰州大学,2016.

基于CMIP5模式的2006—2017年中亚降水预估误差分析

Error analysis concerning 2006-2017 Central Asia precipitation estimation based on CMIP5 model

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 4

编辑推荐

Metrics

本文评价

访问统计

联系我们

[1]	周建卫, 李道京, 胡烜. 基于波束扫描的DBF天线方向图测试方法[J]. 中国科学院大学学报, 2016, 33(4): 542-547.
[2]	苟斐斐, 刘建军, 刘卫东, 罗莉涛. 求解非线性伏尔泰拉积分方程的有限差分方法[J]. 中国科学院大学学报, 2016, 33(3): 329-333.
[3]	张清娟, 李道京. 干涉SAR图像数据压缩[J]. 中国科学院大学学报, 2013, 30(3): 380-386.
[4]	徐曦煜，刘和光. 高度计姿态角估计算法误差分析[J]. 中国科学院大学学报, 2008, 25(1): 54-60.