中等排放情景下中国未来不同强度降雨对总降雨贡献的区域差异（2006―2100年）

doi:10.13284/j.cnki.rddl.002962

Abstract

Abstract: Climatic condition is the important foundation for human subsistence and development and the key factor in sustainable development of economy and society. As one of the climatic elements, different intensity precipitation’s long-term trend change has been a global issue attracting great attentions of politicians, scientists, governments, and the public alike throughout the world. Here we use RCP6.0 emission scenarios WRF 30 km × 30 km daily precipitation data from 2006 to 2100, according to the rainfall intensity grading standards issue by China Meteorological Administration to diagnose different intensity rainfall and its contribution rate to the total rainfall around the overall and seven regions’ trend in China. The results show that: different intensity rainfall would show a different pattern of spatial differentiation under RCP6.0 emission scenarios from 2006 to 2100 in China. Light rainfall and moderate rainfall would have the distribution characteristics of “High - Low - High” from the northeast to the southwest in China. Heavy rainfall, storm rainfall, heavy storm rainfall and total storm rainfall would present the spatial pattern of “High in the Southeast - Low in the Northwest”. Super heavy storm rainfall would be only distributed in the southeast coastal areas. Total rainfall would present a spatial differentiation pattern of “High in the South - Moderate in the North - Low in the Northwest”. The contribution rate of heavy intensity rainfall to the total rainfall would show the characteristic of “High in the Southeast - Low in the Northwest”, while the contribution rate of light intensity rainfall to the total rainfall would be just the opposite. The contribution rate of different intensity storm rainfall to the total storm rainfall would present similar distribution characteristics. As for the change trend of rainfall, the trend of different intensity rainfall in China would show different spatial patterns, but the area of heavy intensity rainfall with increasing trend would be significantly more than that of decreasing trend. As for the change trend of rainfall contribution rate of heavy (light) intensity rainfall to total rainfall, the contribution rate with increasing (decreasing) trend would be dominated. The contribution rate of heavy intensity rainfall to the total rainfall with increasing trend would be more obviously than that of light intensity rainfall with increasing trend. As for the change trend of the contribution rate of different intensity storm rainfall to total storm rainfall, the contribution rate of heavy intensity storm rainfall with increasing trend to total storm rainfall would be more obvious than that of light intensity storm rainfall with increasing trend. Prediction results show that the precipitation in Eastern China would develop in the direction of extremalization.

Key words: RCP6.0, trend, rainfall contribution rate, spatial pattern, regional differences, China

KONG Feng，WANG Yifei，FANG Jian，LYU Lili，ZHANG Lili，WANG Zhuoni. Projected Regional Difference of the Rainfall with Different Intensities and Their Contribution to Total Rainfall under the RCP6.0 Scenario in China during 2006-2100[J].TROPICAL GEOGRAPHY, 2018, 38(1): 48-60.

References

ALEXANDER L，ZHANG X，PETERSON T，CAESAR J，GLEASON B，TANK A，2012．Global observed changes in daily climate extremes of temperature and precipitation．Journal of Geophysical Research Atmospheres，111（D5）：1042-1063．

BENISTON M，STEPHENSON D，CHRISTENSEN O，2007．Future extreme events in European climate： an exploration of regional climate model projections．Climatic Change，81（1）：71-95．

BROWN P，BRADLEY R，KEIMIG F，2010．Changes in extreme climate indices for the Northeastern United States，1870-2005．Journal of Climate，23（24）：6555-6572．

CHEN H，SUN J，2015．Assessing model performance of climate extremes in China：an intercomparison between CMIP5 and CMIP3．Climatic Change，129（1）：197-211．

陈威霖，2008．中国地区极端降水变化模拟评估及其未来情景预估．南京：南京信息工程大学．[CHEN Weilin，2008．Simulation assessment of extreme precipitation in China and its future scenario prediction．Nanjing：Nanjing University of Information Science and Technology．]

FISCHER E，KNUTTI R，2016．Observed heavy precipitation increase confirms theory and early models．Nature Climate Change，6：986-991．

方建，杜鹃，徐伟，史培军，孔锋，2014．气候变化对洪水灾害影响研究进展．地球科学进展，29（9）：1085-1093．[FANG Jian，DU Juan，XU Wei，SHI Peijun，KONG Feng．Progress of research on the effects of climate change on flood disaster．earth science progress，29（9）：1085-1093．]

GAO Y，FU J，DRAKE J，LIU Y，LAMARQUE J，2012．Projected changes of extreme weather events in the eastern United States based on a high resolution climate modeling system．Environmental Research Letters，7（4）：25-37．

HUANG G，WU C，LIU Z，CHEN Z，HU J，YIN Z，2015．Prediction of extreme floods of the Feilaixia reservoir in the Beijiang River basin under climate change．Advances in Water Science，22（1）：10-19．

IPCC SREX，2012．Managing the risks of extreme events and disasters to advance climate change adaptation．London Cambridge University Press．

IPCC AR5，2013．Intergovernmental panel on climate change climate change fifth assessment report（AR5）．London Cambridge University Press，Cambridge，UK.

JIANG Z，CHEN W，JIE S，2009．Projection and evaluation of the precipitation extremes Indices over China based on seven IPCC AR4 coupled climate models．Chinese Journal of Atmospheric Sciences，33（1）：109-120．

江志红，陈威霖，宋洁，王冀，2009．7个IPCC AR4模式对中国地区极端降水指数模拟能力的评估及其未来情景预估．大气科学，33（1）：109-120．[JIANG Zhihong，CHEN Weilin，SONG Jie，WANG Ji，2009．Assessment of simulation capability of 7 IPCC AR4 models for extreme precipitation in China and its future scenario prediction．Atmospheric Science，33（1）：109-120.]

孔锋，方佳毅，刘凡，方建，史培军，2015．1951-2012年中国降水集中度和集中期的时空格局．北京师范大学学报（自然科学版），51（4）：404-411．[KONG Feng，FANG Jian，LIU Fan，FANG Jian，SHI Peijun，2015．Spatial and temporal patterns of precipitation concentration and concentration period in China．Journal of Beijing Normal University（NATURAL SCIENCE EDITION），51（4）：404-411．]

孔锋，王铸，刘凡，方建，方佳毅，李孟阳，史培军，2016．全球、大洲、区域尺度暴雨时空格局变化（1981-2010年）[J]．北京师范大学学报（自然科学版），52（2）：228-234．[KONG Feng，WANG Zhu，LIU Fan，FANG Jian，FANG Jiayi，LI Mengyang，SHI Peijun，2016．Global，continental，regional scale changes in the spatial and temporal patterns of heavy rain（1981-2010）．Journal of Beijing Normal University （Natural Science Edition），52（2）：228-234．]

孔锋，吕丽莉，方建，刘凡，应卓蓉，郭建平，2017．基于日值和小时降水数据诊断中国暴雨时空变化差异的研究（1991-2010）．灾害学，32（1）：72-79．[KONG Feng，LU Lili，FANG Jian，LIU Fan，YING Zhuorong，GUO Jianping．The difference of the spatiotemporal pattern variation of heavy rainfall in China from 1991 to 2010 based on the daily precipitation dataset and hourly precipitation dataset．Journal of Catastrophology，32（1）：72-79．]

SHI P，SUN S，WANG M，LI N，WANG J，JIN Y，GU X，YIN W，2014．Climate change regionalization in China（1961-2010）．Science China Earth Sciences，57（11）：2676-2689.

史培军，孔锋，方佳毅，2014．中国年代际暴雨时空变化格局．地理科学，29（11）：1281-1290．[SHI Peijun，KONG Feng，FANG Jiayi．Spatiotemporal patterns of China decadal storm rainfall．Scientia Gengraphica Sinica，34（11）：1281-1290．]

史培军，孔锋，2016．1951-2010年中国年代际累积暴雨时空格局变化的相关因素研究．地理科学，36（10）：1457-1465．[SHI Peijun，KONG Feng，2016．Research on related factors to decadal accumulated heavy rainfall spatio-temporal patterns change in China during 1951-2010．Scientia Geographica Sinica，36（10）：1457-1465．]

TAO Y，WANG X，YU Z，KRYSANOVA V，CHEN X，SCHWARTZ F，2014．Climate change and probabilistic scenario of streamflow extremes in an alpine region．Journal of Geophysical Research Atmospheres，119（14）：8535-8551．

WANG A，LETTENMAIER D，SHEFFIELD J，2011．Soil moisture drought in China，1950-2006．Journal of Climate，24（13）：3257-3271．

WANG H，SUN J，CHEN H，ZHU Y，ZHANG Y，JIANG D，2012．Extreme climate in China：facts，simulation and projection．Meteorologische Zeitschrift，21（3）：279-304．

WANG L，RANASINGHE R，MASKET S，GELDER P，VRIJLING J，2015．Comparison of empirical statistical methods for downscaling daily climate projections from CMIP5 GCMs：a case study of the Huai River Basin，China．International Journal of Climatology，36（1）：1-11．

WU C，HUANG G，YU H，2015．Prediction of extreme floods based on CMIP5 climate models：a case study in the Beijiang River basin，South China．Hydrology & Earth System Sciences，19（3）：1385-1399．
WU C，XIAN Z，HUANG G，2016．Meteorological drought in the Beijiang River Basin，South China：current observations and future projections．Stochastic Environmental Research & Risk Assessment，30（7）：1-14．

XUAN W，MA C，KANG L，GU H，PAN S，XU Y，2015．Evaluating historical simulations of CMIP5 GCMs for key climatic variables in Zhejiang Province，China．Theoretical & Applied Climatology，29（6）：1-16．

YU E，SUN J，CHEN H，XIANG W，2014．Evaluation of a high-resolution historical simulation over China：climatology and extremes．Climate Dynamics，45：1-19．

杨绚，李栋梁，汤绪，2014．基于CMIP5多模式集合资料的中国气温和降水预估及概率分析．中国沙漠，34（3）：795-804．[YANG Xun，LI Dongliang，TANG Xu，2014．Prediction and probability analysis of temperature and precipitation in China based on CMIP5 multi model ensemble data．China Desert，34（3）：795-804．]

ZENG Z，WANG X，2011．How to evaluate the impacts of climate change on water resources and agriculture in China scientifically．Science & Technology Review，29（32）：71-75．

ZHOU B，WEN Q，XU Y，SONG L，ZHANG X，2014．Projected changes in temperature and precipitation extremes in China by the CMIP5 multimodel ensembles．Journal of Climate，27（17）：6591-6611．

[1]	Peihuan Huang, Gang Wang, Ziyin Huang, Dongsheng Guan. Evaluation of Coastal Water Quality and Influence Factors Identification in South China [J]. Tropical Geography, 2021, 41(1): 124-135.
[2]	Jinyue Tang, Yijun He, Na Ta. Spatial Distribution Patterns and Factors Influencing the Shanghai Catering Industry Based on POI Data [J]. Tropical Geography, 2020, 40(6): 1015-1025.
[3]	Ying Xiong, Kelun Hou, Sirui Zheng, Kun Zhang, Tianhao Yang, Dandan Zhao, Bing Sun, Lei Chen. Relationship between Farmer's Well-Being and Ecosystem Services in Hilly and Mountainous Areas of South China Based on Structural Equation Model: A Case Study of Lechang in Guangdong Province [J]. Tropical Geography, 2020, 40(5): 843-855.
[4]	Kaifu Min, Liang Cheng, Xiao Zhou, Nan Xia, Ning Li, Manchun Li. Strategic and Spatial Pattern Assessments of Spratly Islands Occupied by Foreign Countries [J]. Tropical Geography, 2020, 40(4): 684-693.
[5]	Zhenfa Li, Wensheng Lin, Yaling Ye, Canfei He. Regional Disparity of Financial Inclusion in China—Determining the Relationship between Geographical Inclusion and Business Inclusion [J]. Tropical Geography, 2020, 40(4): 709-720.
[6]	Jin Wanfu, He Guangjing, Chen Le. Spatio-Temporal Evolution, Influencing Factors, and Diffusion Model of Golf Courses in China [J]. Tropical Geography, 2020, 40(3): 515-524.
[7]	Wang Hui, Yan Junping, Peng Bangwen, Liu Dongmei, Lian Lijuan. Spatial Agglomeration and Factors Influencing of Secondary Vocational Education in China during 2000‒2016 [J]. Tropical Geography, 2020, 40(3): 525-538.
[8]	Zhuang Liang, Tian Na, Zhao Biao. Spatio-Temporal Characteristics and Impact Factors of Museums in Shanghai [J]. Tropical Geography, 2020, 40(3): 539-550.
[9]	Du Fangye, Wang Jiao'e, Wang Han. The Impacts of COVID-19 on the Connectivity of China's International Air Transport Network and the Spatial Differences [J]. Tropical Geography, 2020, 40(3): 386-395.
[10]	Zhang Kaihuang, Qian Qinglan. The Impact of COVID-19 on China’s Economy and Discussion of Policies‒Evidence from Listed Companies [J]. Tropical Geography, 2020, 40(3): 396-407.
[11]	Liu Xiaoju, Shi Qi, Yang Hongqiang, Zhou Shengnan. Reconstruction of Shipwreck and Surrounding Relief at a Coral Reef in the South China Sea Based on Side Scan Sonar Image [J]. Tropical Geography, 2020, 40(2): 278-288.
[12]	Chen Yiman, Li Lixun, Fu Tianlan. Spatial Heterogeneity in Chinese Urban Innovation Capabilities and Its Determinants: Approach Based on the Geographically Weighted Regression Model [J]. Tropical Geography, 2020, 40(2): 323-334.
[13]	Lin Danchun, Tan Min, Liu Kai, Liu Lin, Zhu Yuanhui. Accuracy Comparison of Four Gridded Population Datasets in Guangdong Province, China [J]. Tropical Geography, 2020, 40(2): 346-356.
[14]	Li Shan, Feng Pan, Song Yuru, Qin Xiaozhen, Li Xun. Evolution and Mechanism of China’s Exports in a Dynamic Product Space Network [J]. Tropical Geography, 2020, 40(1): 40-50.
[15]	Li Chansong, Hu Pingping, Yang Wangzhou. Impact of the Northern Myanmar Situation on the China-Myanmar Economic Corridor Construction [J]. Tropical Geography, 2019, 39(6): 823-832.

Projected Regional Difference of the Rainfall with Different Intensities and Their Contribution to Total Rainfall under the RCP6.0 Scenario in China during 2006-2100

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Metrics

Comments

Recommended 0