Mean and extreme precipitation projection over land area of East Asia based on multiple regional climate models
-
摘要:
利用东亚区域联合降尺度计划(CORDEX-EA)15个区域模式的模拟结果，集合预估了高排放情景RCP8.5下东亚陆地区域平均和极端降水的未来时空变化，并量化未来预估的不确定性.结果表明：区域模式基本上能够再现东亚及各个区域平均和极端降水的多年平均分布.未来多模式集合预估的平均和极端强降水在东亚各区域多表现为增加，连续无降水日数(CDD)表现为南增北减，且变幅多随时间增大.到21世纪末期，冬季和年平均降水的增幅大值都位于中国西部(WC)，冬季降水的变化在WC、蒙古(MG)、中国东北(NE)和中国华北及西北地区东部(NC)的确定性都较高，年降水的变化仅在WC和MG确定性较高.夏季降水增幅大值位于朝鲜半岛和日本(KJ)，且仅在这一区域确定性较高.最大5日降水量(Rx5day)和大雨日数(R20)以增加为主且变化的空间分布较为均匀，除去中国江南及华南(SC)和KJ的R20变化，其余区域两个变量的变化确定性都较高.CDD的增幅和减幅大值分别位于SC和MG，其变化在MG、NE和SC确定性较高.
Abstract:Using the simulation results from the 15 regional climate models under the framework of the CORDEX-EA (Coordinated Regional Climate Downscaling Experiment-East Asia) program,the future changes of mean and extreme precipitation over land area of East Asia under the high emission pathway of RCP8.5 are projected,and the uncertainties are also estimated quantitatively. The results show that the regional models can reasonably reproduce the spatial patterns of the mean state of mean and extreme precipitation over East Asia and its six subregions. Based on the ensemble mean,the mean precipitation and extreme heavy precipitation will increase over most regions of East Asia,and the consecutive dry days (CDD) will increase in the south but decrease in the north. Most of these changes will increase with time. By the end of the 21st century,the increase in both winter and annual precipitation will occur over western China (WC). The uncertainties on changes in winter precipitation over WC,Mongolia (MG),northeastern China (NE),and northern China (NC) are small. The low uncertainties on change in annual precipitation occur only over WC and MG. The maximum increase in summer precipitation is located in the Korean Peninsula and Japan (KJ),which are the only two subregions with low uncertainties. The spatial distributions of the increases in maximum 5-day precipitation (Rx5day) and heavy rain days (R20) are quite uniform. Except for the changes in R20 over southern China (SC) and KJ,the changes in both Rx5day and R20 over other subregions are highly robust. The maximum increase and decrease values of CDD are located in SC and MG,respectively,and the uncertainties are quite low in MG,NE,and SC.
-
Key words:
- Regional climate models /
- East Asia /
- Ensemble projection /
- Uncertainty /
- Precipitation extremes
-
-
图 2
不同模式集合成员对平均降水和极端降水指数多年平均值(1986-2005年)在各个区域模拟的泰勒评分
Figure 2.
The Taylor skills of the RCMs in simulating the spatial patterns of the mean state of precipitation and extreme precipitation indices over different regions during 1986-2005
图 3
东亚陆地区域和各分区的区域平均的PRdjf(蓝色)和PRjja(红色)相对于基准期的未来变化序列及对应的信噪比SNR(时间序列进行了9 a滑动平均；实线为集合平均值，填色为多模式集合范围，圆点表示未能超过80%的同号率；图中标注的两行文字分别是21世纪未来全部时段、中期和末期内通过同号率检验的比例及多年平均的SNR)
Figure 3.
Changes of the regionally averaged PRdjf (blue) and PRjja (red) relative to the reference period and the corresponding SNR (The values are smoothed by a 9-year running mean. The lines indicate the ensemble mean. Shading indicate the uncertainties among ensemble members. Solid dots cannot pass the agreement criteria. The strings in each panels indicate the percentage of time points in which changes can pass the agreement criteria and the mean SNR over the whole future periods, middle and end periods of the 21st century)
图 4
21世纪末期PRdjf和PRjja相对于基准期的变化(a-b，%)及信噪比(c-d；图a和图b中阴影表示集合成员中超过80%的集合成员预估未来变化符号一致且与集合平均的变化符号相同)
Figure 4.
Spatial patterns for the changes relative to the reference period (a-b) and the corresponding SNR (c-d) in PRdjf and PRjja over the end of 21st century (Hatched areas in Figs. a-b indicate that 80% or more of ensemble members agree on the sign of change.)
图 9
东亚陆地区域和各分区的平均和极端降水未来变化在21世纪中期和末期两个时段的空间相似度
Figure 9.
Spatial similarities of changes over middle and end of the 21st century for mean and extreme precipitation (The dots represent the calculation results based on each ensemble members. The box and whisker plots show the value of 25th, 75th and median. The asterisks represent the calculation results based on the ensemble mean)
图 10
东亚及不同分区区域平均的平均和极端降水的21世纪未来变化线性趋势及中期和末期的平均变化值
Figure 10.
Schematic diagram showing the changes in mean and extreme precipitation over East Asia and six subregions (The lower left table shows values over the whole land area of East Asia, and others show values over the six subregions. The asterisk indicates that changes can pass the criteria set for agreement, and the hash indicates that changes can pass the criteria set for SNR)
表 1
区域气候模式及提供驱动场的全球气候模式的概况
Table 1.
Basic information on RCM ensemble members and their corresponding driving GCMs
编号 区域模式 全球模式 分辨率/km 参考文献 1 RegCM4.4 CSIRO-Mk3-6-0 25 Gao et al., 2018 2 RegCM4.4 EC-EARTH 25 Gao et al., 2018 3 RegCM4.4 HadGEM2-ES 25 Gao et al., 2018 4 RegCM4.4 MPI-ESM-MR 25 Gao et al., 2018 5 RegCM4.4 NorESM1-M 25 Gao et al., 2018; Han et al., 2019 6 REMO2015 HadGEM2-ES 25 Remedio et al., 2019 7 REMO2015 MPI-ESM-LR 25 Remedio et al., 2019 8 REMO2015 NorESM1-M 25 Remedio et al., 2019 9 CCLM5.0 CNRM-CM5 50 Li et al., 2018 10 CCLM5.0 EC-EARTH 50 Li et al., 2018 11 CCLM5.0 HadGEM2-ES 50 Li et al., 2018 12 CCLM5.0 MPI-ESM-LR 50 Li et al., 2018 13 HIRHAM5 EC-EARTH 50 Christensen et al., 2006, 2015 14 RegCM4.0 BCC-CSM1-1 50 Gao et al., 2013 15 HadGEM3-RA HadGEM2-AO 50 Park et al., 2016 
下载: 导出CSV
表 2
使用的平均和极端降水指数
Table 2.
The mean and extreme precipitation indices employed in the study
名称 英文缩写 定义 单位 冬季降水量 PRdjf 每年冬季的总降水量 mm 夏季降水量 PRjja 每年夏季的总降水量 mm 年降水量 PRann 每年的总降水量 mm 最大5日降水量 Rx5day 每年最大的连续五天降水量 mm 大雨日数 R20 每年日降水量大于等于20 mm的天数 d 连续无降水日数 CDD 每年最长连续无降水日数(日降水量≤1 mm) d
下载: 导出CSV
表 3
东亚陆地区域平均的各变量未来变化在不同时段内通过同号率检验的比例(P)及多年平均的SNR
Table 3.
The percentage (P) of time points in which changes can pass the agreement criteria and the mean SNR over different future periods for the changes regionally avareged over the whole land area of East Asia
PRjja PRdjf PRann Rx5day R20 CDD 21世纪未来全部时段(2021-2098年) P/% 59 65 77 100 100 44 SNR 0.7 1.0 1.2 2.6 1.5 0.7 21世纪中期(2046-2065年) P/% 75 75 80 100 100 80 SNR 0.6 1.2 1.2 2.5 1.6 1.0 21世纪末期(2079-2098年) P/% 25 94 56 100 100 13 SNR 0.8 1.1 1.1 3.0 1.4 0.5
下载: 导出CSV
-
Christensen O B, Drews M, Christensen J H, et al. 2006. The HIRHAM regional climate model version 5 (beta). Tech Rep 06-17, Copenhagen: Danish Meteorological Institute.
Christensen O B, Yang S, Boberg F, et al. 2015. Scalability of regional climate change in Europe for high-end scenarios. Climate Research, 64(1): 25-38. doi: 10.3354/cr01286
Fu C, Wang S, Xiong Z, et al. 2005. Regional climate model intercomparison project for Asia. Bulletin of the American Meteorological Society, 86(2): 257-266. doi: 10.1175/BAMS-86-2-257
Gao X J, Xu Y, Zhao Z C, et al. 2006. On the role of resolution and topography in the simulation of East Asia precipitation. Theoretical and Applied Climatology, 86(1-4): 173-185. doi: 10.1007/s00704-005-0214-4
Gao X J, Wang M L, Giorgi F. 2013. Climate change over China in the 21st century as simulated by BCC_CSM1.1-RegCM4.0. Atmospheric and Oceanic Science Letters, 6(5): 381-386. doi: 10.1080/16742834.2013.11447112
Gao X J, Shi Y, Giorgi F. 2016. Comparison of convective parameterizations in RegCM4 experiments over China with CLM as the land surface model. Atmospheric and Oceanic Science Letters, 9(4): 246-254. doi: 10.1080/16742834.2016.1172938
Gao X J, Shi Y, Han Z Y, et al. 2017. Performance of RegCM4 over major river basins in China. Advances in Atmospheric Sciences, 34(4): 441-455. doi: 10.1007/s00376-016-6179-7
Gao X J, Wu J, Shi Y, et al. 2018. Future changes in thermal comfort conditions over China based on multi-RegCM4 simulations. Atmospheric and Oceanic Science Letters, 11(4): 291-299. doi: 10.1080/16742834.2018.1471578
Giorgi F, Jones C, Asrar G. 2009. Addressing climate information needs at the regional level: the CORDEX framework. WMO Bulletin, 58(3): 175-183. http://www.cabdirect.org/abstracts/20093263042.html
Gutowski W J Jr, Giorgi F, Timbal B, et al. 2016. WCRP coordinated regional downscaling experiment (CORDEX): a diagnostic MIP for CMIP6. Geoscientific Model Development, 9(11): 4087-4095. doi: 10.5194/gmd-9-4087-2016
Han Z Y, Shi Y, Wu J, et al. 2019. Combined dynamical and statistical downscaling for high-resolution projections of multiple climate variables in the Beijing-Tianjin-Hebei region of China. Journal of Applied Meteorology and Climatology, 58(11): 2387-2403. doi: 10.1175/JAMC-D-19-0050.1
Han Z Y, Zhou B T, Xu Y, et al. 2017. Projected changes in haze pollution potential in China: an ensemble of regional climate model simulations. Atmospheric Chemistry and Physics, 17(16): 10109-10123. doi: 10.5194/acp-17-10109-2017
Huang B, Polanski S, Cubasch U. 2015. Assessment of precipitation climatology in an ensemble of CORDEX-East Asia regional climate simulations. Climate Research, 64(2): 141-158. doi: 10.3354/cr01302
Hui P H, Tang J P, Wang S Y, et al. 2018. Climate change projections over China using regional climate models forced by two CMIP5 global models. Part Ⅱ: projections of future climate. International Journal of Climatology, 38(S1): e78-e94. http://www.researchgate.net/publication/321277473_Climate_change_projections_over_China_using_regional_climate_models_forced_by_two_CMIP5_global_models_Part_I_evaluation_of_historical_simulations_EVALUATION_OF_RCMS_FORCED_BY_TWO_CMIP5_GCMS_OVER_CHINA
Im E S, Choi Y W, Ahn J B. 2017. Robust intensification of hydroclimatic intensity over East Asia from multi-model ensemble regional projections. Theoretical and Applied Climatology, 129(3): 1241-1254. doi: 10.1007/s00704-016-1846-2
IPCC. 2000. Special Report on Emissions Scenarios. Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press, 570.
IPCC. 2013. Climate Change 2013-The Physical Science Basis. Contribution of Working Group Ⅰ to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press, 1535.
Jiang D B, Tian Z P. 2013. East Asian monsoon change for the 21st century: Results of CMIP3 and CMIP5 models. Chinese Science Bulletin, 58(12): 1427-1435. doi: 10.1007/s11434-012-5533-0
Jiang D B, Tian Z P, Lang X M. 2016. Reliability of climate models for China through the IPCC Third to fifth assessment reports. International Journal of Climatology, 36(3): 1114-1133. doi: 10.1002/joc.4406
Kim G, Cha D H, Park C, et al. 2021. Evaluation and projection of regional climate over East Asia in CORDEX-East Asia Phase Ⅰ experiment. Asia-Pacific Journal of Atmospheric Sciences, 57(1): 119-134, doi: 10.1007/s13143-020-00180-8.
Li B, Zhou T J. 2010. Projected climate change over China under SRES A1B scenario: Multi-model ensemble and uncertainties. Advances in Climate Change Research (in Chinese), 6(4): 270-276. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=qhbhyjjz201004007
Li H X, Chen H P, Wang H J, et al. 2018. Future precipitation changes over China under 1.5 ℃ and 2.0 ℃ global warming targets by using CORDEX regional climate models. Science of the Total Environment, 640-641: 543-554. doi: 10.1016/j.scitotenv.2018.05.324
Li Q, Wang S Y, Lee D K, et al. 2016. Building Asian climate change scenario by multi-regional climate models ensemble. Part Ⅱ: mean precipitation. International Journal of Climatology, 36(13): 4253-4264. doi: 10.1002/joc.4633
Niu X R, Wang S Y, Tang J P, et al. 2018. Ensemble evaluation and projection of climate extremes in China using RMIP models. International Journal of Climatology, 38(4): 2039-2055. doi: 10.1002/joc.5315
Niu X R, Tang J P, Wang S Y, et al. 2020. On the sensitivity of seasonal and diurnal precipitation to cumulus parameterization over CORDEX-EA-II. Climate Dynamics, 54(1): 373-393, doi: 10.1007/s00382-019-05010-w.
Park C, Min S K, Lee D, et al. 2016. Evaluation of multiple regional climate models for summer climate extremes over East Asia. Climate Dynamics, 46(7): 2469-2486. doi: 10.1007/s00382-015-2713-z
Park C, Min S K. 2019. Multi-RCM near-term projections of summer climate extremes over East Asia. Climate Dynamics, 52(7): 4937-4952. doi: 10.1007/s00382-018-4425-7
Peng D D, Zhou T J, Zhang L X, et al. 2020. Observationally constrained projection of the reduced intensification of extreme climate events in Central Asia from 0.5 C less global warming. Climate Dynamics, 54(1): 543-560. doi: 10.1007%2Fs00382-019-05014-6
Remedio A R, Teichmann C, Buntemeyer L, et al. 2019. Evaluation of New CORDEX simulations using an Updated Köppen-Trewartha climate classification. Atmosphere, 10(11): 726. doi: 10.3390/atmos10110726
Shi Y, Wang G L, Gao X J. 2018. Role of resolution in regional climate change projections over China. Climate Dynamics, 51(5): 2375-2396.
Taylor K E. 2001. Summarizing multiple aspects of model performance in a single diagram. Journal of Geophysical Research: Atmospheres, 106(D7): 7183-7192. doi: 10.1029/2000JD900719
Tebaldi C, Arblaster J M, Knutti R. 2011. Mapping model agreement on future climate projections. Geophysical Research Letters, 38(23): L23701, doi: 10.1029/2011GL049863.
Tebaldi C, Arblaster J M. 2014. Pattern scaling: its strengths and limitations, and an update on the latest model simulations. Climatic Change, 122(3): 459-471. doi: 10.1007/s10584-013-1032-9
Van Vuuren D P, Edmonds J, Kainuma M, et al. 2011. The representative concentration pathways: an overview. Climatic Change, 109(1): 5-31. http://plankt.oxfordjournals.org/external-ref?access_num=10.1007/s10584-011-0148-z&link_type=DOI
Wu H M, Huang A N, Jiang Y M, et al. 2016. Evaluation of the performance of BCC_CSM climate model with different horizontal resolution in simulating the summer precipitation over Central Asia. Arid Land Geography (in Chinese), 39(6): 1305-1318.
Wu J, Gao XJ, Shi Y, et al. 2011. Climate change over Xinjiang region in the 21st Century simulated by a high resolution regional climate model. Journal of Glaciology and Geocryology (in Chinese), 33(3): 479-487.
Wu J, Gao X J. 2013. A gridded daily observation dataset over China region and comparison with the other datasets. Chinese Journal of Geophysics (in Chinese), 56(4): 1102-1111. http://www.cnki.com.cn/Article/CJFDTotal-DQWX201304008.htm
Wu J, Gao X J, Xu Y L, et al. 2015. Regional climate change and uncertainty analysis based on four regional climate model simulations over China. Atmospheric and Oceanic Science Letters, 8(3): 147-152. doi: 10.1080/16742834.2015.11447252
Xu Y, Gao X J, Shen Y, et al. 2009. A daily temperature dataset over China and its application in validating a RCM simulation. Advances in Atmospheric Sciences, 26(4): 763-772. doi: 10.1007/s00376-009-9029-z
Yatagai A, Arakawa O, Kamiguchi K, et al. 2009. A 44-Year daily gridded precipitation dataset for Asia based on a dense network of rain gauges. SOLA, 5: 137-140. doi: 10.2151/sola.2009-035
Yu E T, Sun J Q. 2019. Extreme temperature projection over northwestern China based on multiple regional climate models. Transactions of Atmospheric Sciences (in Chinese), 42(1): 46-57. http://en.cnki.com.cn/Article_en/CJFDTotal-NJQX201901006.htm
Zhou B T, Wen Q H, Xu Y, et al. 2014. Projected changes in temperature and precipitation extremes in China by the CMIP5 multimodel ensembles. Journal of Climate, 27(17): 6591-6611. doi: 10.1175/JCLI-D-13-00761.1
Zhou B T, Wang Z Y, Shi Y, et al. 2018. Historical and future changes of snowfall events in China under a warming background. Journal of Climate, 31(15): 5873-5889. doi: 10.1175/JCLI-D-17-0428.1
Zhou B T, Wu J, Xu Y, et al. 2019. Projected changes in autumn rainfall over West China: results from an ensemble of dynamical downscaling simulations. International Journal of Climatology, 39(12): 4869-4882. doi: 10.1002/joc.6115
Zou L W, Zhou T J. 2016. Future summer precipitation changes over CORDEX-East Asia domain downscaled by a regional ocean-atmosphere coupled model: A comparison to the stand-alone RCM. Journal of Geophysical Research: Atmospheres, 121(6): 2691-2704. doi: 10.1002/2015JD024519
Zou L W, Zhou T J. 2017. Dynamical downscaling of East Asian winter monsoon changes with a regional ocean-atmosphere coupled model. Quarterly Journal of the Royal Meteorological Society, 143(706): 2245-2259. doi: 10.1002/qj.3082
姜大膀, 田芝平. 2013. 21世纪东亚季风变化: CMIP3和CMIP5模式预估结果. 科学通报, 58(8): 707-716. https://www.cnki.com.cn/Article/CJFDTOTAL-KXTB201308013.htm
李博, 周天军. 2010. 基于IPCC A1B情景的中国未来气候变化预估: 多模式集合结果及其不确定性. 气候变化研究进展, 6(4): 270-276. doi: 10.3969/j.issn.1673-1719.2010.04.007
吴昊旻, 黄安宁, 姜燕敏等. 2016. 不同水平分辨率BCC_CSM模式对中亚夏季降水模拟能力评估. 干旱区地理, 39(6): 1305-1318. https://www.cnki.com.cn/Article/CJFDTOTAL-GHDL201606023.htm
吴佳, 高学杰, 石英等. 2011. 新疆21世纪气候变化的高分辨率模拟. 冰川冻土, 33(3): 479-487. https://www.cnki.com.cn/Article/CJFDTOTAL-BCDT201103004.htm
吴佳, 高学杰. 2013. 一套格点化的中国区域逐日观测资料及与其它资料的对比. 地球物理学报, 56(4): 1102-1111. http://www.geophy.cn//CN/abstract/abstract9426.shtml
于恩涛, 孙建奇. 2019. 基于多区域模式集合的中国西部干旱区极端温度未来预估. 大气科学学报, 42(1): 46-57. https://www.cnki.com.cn/Article/CJFDTOTAL-NJQX201901006.htm
-
图(10)
表(3)
计量
- 文章访问数: 2654
- PDF下载数: 271
- 施引文献: 0