地球科学进展 ›› 2013, Vol. 28 ›› Issue (10): 1144 -1153. doi: 10.11867/j.issn.1001-8166.2013.10.1144

研究论文 上一篇    下一篇

误差订正空间分解法在中国的应用
王林 1, 2, 陈文 1   
  1. 1.中国科学院大气物理研究所季风系统研究中心, 北京, 100190; 2.中国科学院大学, 北京, 100049
  • 收稿日期:2013-04-25 出版日期:2013-10-10
  • 基金资助:

    国家自然科学基金项目“东亚冬季风系统变异及其内动力学机理研究”(编号:41025017)和“全球变暖背景下两类太平洋增温型对东亚冬、夏季风和台风活动的影响及其机理”(编号:41230527)资助.

Application of Bias Correction and Spatial Disaggregation in Removing Model Biases and Downscaling over China

Wang Lin 1, 2, Chen Wen 1   

  1. 1. Center for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100190; 2. University of Chinese Academy of Sciences, Beijing, 100049
  • Received:2013-04-25 Online:2013-10-10 Published:2013-10-10

目前全球气候模式在区域尺度上存在较大的模拟系统偏差和空间分辨率低的缺陷, 误差订正空间分解法(BCSD)可以有效去除其系统误差, 并能应用到降尺度研究中, 在国际上得到了广泛应用。在系统介绍BCSD方法基本理论和步骤的基础上, 基于耦合模式比较计划第五阶段(CMIP5)的多模式数据集研究了该方法在中国区域降水模拟订正和降尺度的适用性。结果表明, 该方法能够很好地降低全球气候模式在中国区域降水的模拟误差, 并且该方法不具有模式依赖性, 对34个模式的模拟都有很好的改进, 显示出很好的应用前景。进一步讨论了BCSD方法的适用范围, 并利用该方法和CMIP5模拟资料构建了一套经过误差订正和降尺度的未来中国区域降水多模式、多情景的数据集。

Global Climate Models (GCM) are the primary tools for studying past climate change and evaluating the projected future response of climate system to changing atmospheric composition. However, the stateofart GCMs contain large biases in regional or local scales and are often characterized by low resolution which is too coarse to provide the regionalscale information required for regional climate change impact assessment. A popular technique, Bias Correction and Spatial Disaggregation (BCSD), are widespreadly employed to improve the quality of the raw model output and downscaling throughout the world. Unfortunately, this method has not been applied in China. Consequently, the detailed principle and procedure of BCSD are introduced systematically in this study. Furthermore, the applicability of BCSD over China is also examined based on an ensemble of climate models from phase five of the Coupled Model Intercomparison Project (CMIP5), though the excellent performance of it has been validated for other parts of the world in many works. The result shows that BCSD is an effective, modelindependent approach to removing biases of model and downscaling. Finally, application scope of BCSD is discussed, and a suite of fineresolution multimodel climate projections over China is developed based on 34 climate models and two emissions scenarios (RCP4.5 and RCP8.5) from CMIP5.

中图分类号: 

[1]Wang Chenghai, Li Jian, Li Xiaolan, et al. Analysis on quasi-periodic characteristics of precipitation in recent 50 years and trend in next 20 years in China[J]. Arid Zone Research, 2012, 29(1): 1-10.[王澄海, 李健, 李小兰, 等. 近50a中国降水变化的准周期性特征及未来的变化趋势[J]. 干旱区研究, 2012, 29(1): 1-10.]
[2]Wang Yuanhao, Chen Wen, Zhang Jingyong. Interannual variations of summer rainfall and their causes in the mid-latitude arid/semi-arid areas of East Asia[J]. Climatic and Environmental Research, 2012, 17(4): 444-456.[王远皓, 陈文, 张井勇. 东亚中纬度干旱/半干旱区降水年际变化及其可能成因[J]. 气候与环境研究, 2012, 17(4): 444-456.]
[3]Qu Yingle, Gao Xiaoqing, Chen Wen, et al. Comparison of surface air temperatures and precipitation in Eastern and Western China during 1951-2003[J]. Plateau Meteorology, 2008, 27(3): 524-529.[曲迎乐, 高晓清, 陈文, 等. 近50年来我国东、西部地面气温和降水变化对比的初步分析[J]. 高原气象, 2008, 27(3): 524-529.]
[4]Ma Yin, Chen Wen, Feng Ruiquan, et al. Interannual and interdecadal variations of precipitation over Eastern China during Meiyu season and their relationship with the atmospheric circulation and SST[J]. Chinese Journal of Atmospheric Sciences, 2012, 36(2): 397-410.[马音, 陈文, 冯瑞权, 等. 我国东部梅雨期降水的年际和年代际变化特征及其与大气环流和海温的关系[J]. 大气科学, 2012, 36(2): 397-410.]
[5]Ma Jingjin, Gao Xiaoqing, Qu Yingle. The character of precipitation and its relation to climate change over North China in spring and summer[J]. Climatic and Environmental Research, 2006, 11(3): 321-329.[马京津, 高晓清, 曲迎乐. 华北地区春季和夏季降水特征及与气候相关的分析[J]. 气候与环境研究, 2006, 11(3): 321-329.]
[6]Wang S, Li W. Climate of China[M]. Beijing: China Meteorological Press, 2007.
[7]Zhou W, Li C, Chan J C L. The interdecadal variations of the summer monsoon rainfall over South China[J]. Meteorology and Atmospheric Physics, 2006, 93(3/4): 165-175.
[8]Chen Wen, Kang Lihua, Wang Ding. The coupling relationship between summer rainfall in China and global sea surface temperature[J]. Climatic and Environmental Research, 2006, 11(3): 259-269.[陈文, 康丽华, 王玎. 我国夏季降水与全球海温的耦合关系分析[J]. 气候与环境研究, 2006, 11(3): 259-269.]
[9]Zhang Guocai. Extreme events under climate change condition[M]∥
[10]Wang Lin, Chen Wen. Characteristics of multi-timescale variabilities of the drought over last 100 years in Southwest China[J]. Advances in Meteorological Science and Technology, 2012, 2(4): 21-26.[王林, 陈文. 近百年西南地区干旱的多时间尺度演变特征[J]. 气象科技进展, 2012, 2(4): 21-26.]
[11]Solomon S, Qin D, Manning M, et al. The Physical Basis, Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change[M]. Cambridge: Cambridge University Press, 2007.
[12]Fu Congbin, Dong Wenjie, Wen Gang, et al. Regional responses and adaptation to global change[J]. Acta Meteorologica Sinica, 2003, 61(2): 245-250.[符淙斌, 董文杰, 温刚, 等. 全球变化的区域响应和适应[J]. 气象学报, 2003, 61(2): 245-250.]
[13]Seneviratne S, Nicholls N, Easterling D, et al. Changes in climate extremes and their impacts on the natural physical environment[C]∥Christopher B F, Vicente B, Thomas F S, et al, eds. Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. Cambridge: Cambridge University Press, 2012: 109-230.
[14]Giorgi F, Mearns L O. Approaches to the simulation of regional climate change: A review[J]. Reviews of Geophysics, 1991, 29(2): 191-216.
[15]Wilby R L, Wigley T M L. Downscaling general circulation model output: A review of methods and limitations[J]. Progress in Physical Geography, 1997, 21(4): 530-548.
[16]Wood A W, Maurer E P, Kumar A, et al. Long-range experimental hydrologic forecasting for the eastern United States[J]. Journal of Geophysical Research, 2002, 107(D20): 4 429.
[17]Wood A W, Leung L R, Sridhar V, et al. Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs[J]. Climatic Change, 2004, 62(1): 189-216.
[18]Widmann M, Bretherton C S, Salathé E P. Statistical precipitation downscaling over the northwestern United States using numerically simulated precipitation as a predictor[J]. Journal of Climate, 2003, 16(5): 799-816.
[19]Maurer E P, Hidalgo H G. Utility of daily vs. monthly large-scale climate data: An intercomparison of two statistical downscaling methods[J]. Hydrology and Earth System Sciences, 2008, 12(2): 551-563.
[20]Hayhoe K, Wake C, Anderson B, et al. Regional climate change projections for the Northeast USA[J]. Mitigation and Adaptation Strategies for Global Change, 2008, 13(5): 425-436.
[21]Sharma D, Das Gupta A, Babel M S. Spatial disaggregation of bias-corrected GCM precipitation for improved hydrologic simulation: Ping River Basin, Thailand[J]. Hydrology and Earth System Sciences, 2007, 11(4): 1 373-1 390.
[22]Vidal J P, Wade S. A framework for developing high-resolution multi-model climate projections: 21st century scenarios for the UK[J]. International Journal of Climatology, 2008, 28(7): 843-858.
[23]Maurer E P, Brekke L, Pruitt T, et al. Fine-resolution climate projections enhance regional climate change impact studies[J]. Eos Transactions American Geophysical Union, 2007, 88(47): 504.
[24]Wang Chenghai, Wu Yongping, Cui Yang. Evaluating the progress of the CMIP and its application prospect in China[J]. Advances in Earth Science, 2009, 24(5): 461-468.[王澄海, 吴永萍, 崔洋. CMIP研究计划的进展及其在中国地区的检验和应用前景[J]. 地球科学进展, 2009, 24(5): 461-468.]
[25]Taylor K E, Stouffer R J, Meehl G A. An overview of CMIP5 and the experiment design[J]. Bulletin of the American Meteorological Society, 2012, 93(4): 485-498.
[26]Gudmundsson L, Bremnes J B, Haugen J E, et al. Technical note: Downscaling RCM precipitation to the station scale using statistical transformations—A comparison of methods[J]. Hydrology Earth System Sciences, 2012, 16(9): 3 383-3 390.
[27]Hastie T, Tibshirani R, Friedman J H. The Elements of Statistical Learning (Second Edition) [M].Berlin: Springer, 2011.
[28]Givens G H, Hoeting J A. Computational Statistics[M]. New York: John Wiley & Sons, 2005.[Givers G H, Hoeting J A.计算统计[M].王兆军, 刘民千, 邹长亮, 等, 译. 北京: 人民邮电出版社, 2009.]
[29]Lafon T, Dadson S, Buys G, et al. Bias correction of daily precipitation simulated by a regional climate model: A comparison of methods[J]. International Journal of Climatology, 2012, doi: 10.1002/joc.3518.
[30]Piani C, Haerter J, Coppola E. Statistical bias correction for daily precipitation in regional climate models over Europe[J]. Theoretical and Applied Climatology, 2010, 99(1): 187-192.
[31]Department of Earth Sciences, NSFC. Earth Science Development Strategy in the “11th Five-Year Plan”[M]. Beijing: China Meteorological Press, 2006. [国家自然科学基金委员会地球科学部. 地球科学“十一五”发展战略[M]. 北京: 气象出版社, 2006.]
[32]Christensen N S, Wood A W, Voisin N, et al. The effects of climate change on the hydrology and water resources of the Colorado River Basin[J]. Climatic Change, 2004, 62(1): 337-363.
[33]Vidal J P, Wade S D. Multimodel projections of catchment-scale precipitation regime[J]. Journal of Hydrology, 2008, 353(1/2): 143-158.
[1] 魏梦美,符素华,刘宝元. 青藏高原水力侵蚀定量研究进展[J]. 地球科学进展, 2021, 36(7): 740-752.
[2] 范成新, 刘敏, 王圣瑞, 方红卫, 夏星辉, 曹文志, 丁士明, 侯立军, 王沛芳, 陈敬安, 游静, 王菊英, 盛彦清, 朱伟. 20年来我国沉积物环境与污染控制研究进展与展望[J]. 地球科学进展, 2021, 36(4): 346-374.
[3] 吴佳梅,彭秋志,黄义忠,黄亮. 中国植被覆盖变化研究遥感数据源及研究区域时空热度分析[J]. 地球科学进展, 2020, 35(9): 978-989.
[4] 李侠祥, 刘昌新, 王芳, 郝志新. 中国投资对“一带一路”地区经济增长和碳排放强度的影响[J]. 地球科学进展, 2020, 35(6): 618-631.
[5] 张宏文,续昱,高艳红. 19822005年青藏高原降水再循环率的模拟研究[J]. 地球科学进展, 2020, 35(3): 297-307.
[6] 王冰笛, 李清泉, 沈新勇, 董李丽, 汪方, 王涛, 梁信忠. 区域气候模式 CWRF对东亚冬季风气候特征的模拟[J]. 地球科学进展, 2020, 35(3): 319-330.
[7] 刘凯,聂格格,张森. 中国 19512018年气温和降水的时空演变特征研究[J]. 地球科学进展, 2020, 35(11): 1113-1126.
[8] 谢彦君, 任福民, 李国平, 王铭杨, 杨慧. 影响中国双台风活动气候特征研究[J]. 地球科学进展, 2020, 35(1): 101-108.
[9] 郝志新,吴茂炜,张学珍,刘洋,郑景云. 过去千年中国年代和百年尺度冷暖阶段的干湿格局变化研究[J]. 地球科学进展, 2020, 35(1): 18-25.
[10] 蒋诗威,周鑫. 中国东南地区中世纪暖期和小冰期夏季风降水研究进展[J]. 地球科学进展, 2019, 34(7): 697-705.
[11] 高峰,赵雪雁,宋晓谕,王宝,王鹏龙,牛艺博,王伟军,黄春林. 面向 SDGs的美丽中国内涵与评价指标体系[J]. 地球科学进展, 2019, 34(3): 295-305.
[12] 张宸嘉, 方一平, 陈秀娟. 基于文献计量的国内可持续生计研究进展分析[J]. 地球科学进展, 2018, 33(9): 969-982.
[13] 易雪, 李得勤, 赵春雨, 沈历都, 敖雪, 刘鸣彦. 分析Nudging对辽宁地区降尺度的影响[J]. 地球科学进展, 2018, 33(5): 517-531.
[14] 陈亮, 段建平, 马柱国. 大气环流形势客观分型及其与中国降水的联系[J]. 地球科学进展, 2018, 33(4): 396-403.
[15] 王建, 车涛, 李震, 李弘毅, 郝晓华, 郑照军, 肖鹏峰, 李晓峰, 黄晓东, 钟歆玥, 戴礼云, 李红星, 柯长青, 李兰海. 中国积雪特性及分布调查[J]. 地球科学进展, 2018, 33(1): 12-15.
阅读次数
全文


摘要