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1Trends in Monthly Temperature and Precipitation Extremes in the Zhujiang River Basin,South China(1961-2007)显示文摘Monthly temperature and precipitation time-series for the Zhujiang River Basin are analyzed in order to identify changes in climate extremes.Daily temperature and precipitation data from 1961 to 2007 of 192 meteorological stations are used.Two temperature indicators(monthly mean and monthly maximum mean) and three precipitation indicators (monthly total,monthly maximum consecutive 5-day precipitation,and monthly dry days) are analyzed.Tendencies in all five indicators can be observed.Many stations show significant positive trends(above the 90%confidence level) for monthly mean temperatures and monthly maximum mean temperatures.For all months,a significant increase in temperature from 1961 to 2007 can be observed in the entire basin with the coastal area in particular.Positive trends of precipitation extremes can be observed from January to March.Negative trends are detected from September to November. The number of dry days in October increased significantly at 40%of all meteorological stations.Stations with changes of monthly precipitation extremes are scattered over the Zhujiang River Basin.An aggregation of heat waves and droughts can be detected which is accompanied by significant increases of temperature extremes and the negative tendencies in precipitation extremes.The detection of tendencies in climate extremes essentially relies on a good data quality and high station density.Thomas Fischer Marco Gemmer Lliu Liu Buda Su 2010Advances in Climate Change Research2010,1,2:6
2Simulation and projection of climate change using CMIP6 Muti-models in the Belt and Road Region显示文摘Climate condition over a region is mostly determined by the changes in precipitation,temperature and evaporation as the key climate variables.The countries belong to the Belt and Road region are subjected to face strong changes in future climate.In this paper,we used five global climate models from the latest Sixth Phase of Coupled Model Intercomparison Project(CMIP6)to evaluate future climate changes under seven combined scenarios of the Shared Socioeconomic Pathways and the Representative Concentration Pathways(SSP1-1.9,SSP1-2.6,SSP2-4.5,SSP3-7.0,SSP4-3.4,SSP4-6.0 and SSP5-8.5)across the Belt and Road region.This study focuses on undertaking a climate change assessment in terms of future changes in precipitation,air temperature and actual evaporation for the three distinct periods as near-term period(2021−2040),mid-term period(2041−2060)and long-term period(2081−2100).To discern spatial structure,Köppen−Geiger Climate Classification method has been used in this study.In relative terms,the results indicate an evidence of increasing tendency in all the studied variables,where significant changes are anticipated mostly in the long-term period.In addition to,though it is projected to increase under all the SSP-RCP scenarios,greater increases will be happened under higher emission scenarios(SSP5-8.5 and SSP3-7.0).For temperature,robust increases in annual mean temperature is found to be 5.2°C under SSP3-7.0,and highest 7.0°C under SSP5-8.5 scenario relative to present day.The northern part especially Cold and Polar region will be even more warmer(+6.1°C)in the long-term(2081−2100)period under SSP5-8.5.Similarly,at the end of the twenty-first century,annual mean precipitation is inclined to increase largely with a rate of 2.1%and 2.8%per decade under SSP3-7.0 and SSP5-8.5 respectively.Spatial distribution demonstrates that the largest precipitation increases are to be pronounced in the Polar and Arid regions.Precipitation is projected to increase with response to increasing warming most of the regions.Finally,the actual evaporation is projected to increase significantly with rate of 20.3%under SSP3-7.0 and greatest 27.0%for SSP5-8.5 by the end of the century.It is important to note that the changes in evaporation respond to global mean temperature rise consistently in terms of similar spatial pattern for all the scenarios where stronger increase found in the Cold and Polar regions.The increase in precipitation is overruled by enhanced evaporation over the region.However,this study reveals that the CMIP6 models can simulate temperature better than precipitation over the Belt and Road region.Findings of this study could be the reliable basis for initiating policies against further climate induced impacts in the regional scale.YanRan Lü Tong Jiang YanJun Wang BuDa Su JinLong Huang Hui Tao 2020Research in Cold and Arid Regions2020,12,6:4
3Projection of temperature and precipitation under SSPs-RCPs Scenarios over northwest China显示文摘Climate change significantly affects the environmental and socioeconomic conditions in northwest China.Here we evaluate the ability of five general circulation models(GCMs)from 6th phase of the Coupled Model Inter-comparison Project(CMIP6)to reproduce regional temperature and precipitation over northwest China from 1961 to 2014,and project the future temperature and precipitation during 2021 to 2100 under SSPs-RCPs(SSP1-1.9,SSP1-2.6,SSP2-4.5,SSP3-7.0,SSP4-3.4,SSP4-6.0 and SSP5-8.5).The results show that the CMIP6 models can simulate temperature better than precipitation.Projections show that the annual mean temperature will further increase under different SSPs-RCPs scenarios in the 21st century.Future climate changes in the near-term(2021-2040),mid-term(2041-2060)and long-term(2081-2100)are analyzed relative to the reference period(1995-2014).In the long term,warming will be significantly higher than the near and mid-terms.In the long term,annual mean temperature will increase by 1.4℃,1.9℃,3.3℃,5.5℃,2.7℃,3.8℃ and 6.0℃ under SSP1-1.9,SSP1-2.6,SSP2-4.5,SSP3-7.0,SSP4-3.4,SSP4-6.0 and SSP5-8.5,respectively.Spatially,warming in the Junggar Basin will be higher than those in the Tarim Basin.Seasonally,the maximum warming zone will be in the mountainous areas of Tarim Basin during spring and autumn,in the southern basin during winter,and in the east during summer.Precipitation shows an increasing trend under different SSPs-RCPs in the 21st century.In the long term,increase in precipitation will be significantly higher than in the near and mid-terms.Increase in annual precipitation in the long term will be 4.1% under SSP1-1.9,13.9% under SSP1-2.6,28.4% under SSP2-4.5, 35.2% under SSP3-7.0, 6.9% under SSP4-3.4, 8.9% under SSP4-6.0, and 27.3% under SSP5-8.5 relative to the reference period of 1995-2014. Spatially, precipitation increase will be higher in the south than the north, especially higher in mountainous regions than the basin under SSP2-4.5, SSP3-7.0, and SSP5-8.5. Seasonally, highest increase can be expected for winter, followed by spring, with significant increase in mountainous regions of southern Tarim Basin. Summer precipitation will reduce in Tian Shan and basins but will significantly increase in the northern margin of the Kunlun Mountain.Jiancheng QIN Buda SU Hui TAO Yanjun WANG Jinlong HUANG Tong JIANG 2021Frontiers of Earth Science2021,15,1:3
4Synchronous Characteristics of Precipitation Extremes in the Yangtze and Murray–Darling River Basins and the Role of ENSO显示文摘The floods caused by the extreme precipitation in the Yangtze River basin(YRB)and Murray–Darling River basin(MDRB),the largest basins in China and Australia,have significant impacts on the society and regional economies.Based on the spatial–temporal analysis of the daily precipitation extremes(DPEs)during 1982–2016,we found that for both basins,the whole-basin-type DPEs have the highest proportion and a synchronous DPE interannual variation characteristic exists in the two basins,with the 3-yr running correlation coefficient of the annual DPE days(DPEDs)reaching almost 0.7(significant at the 0.01 level).The El Ni?o–Southern Oscillation(ENSO),which is one of the most significant climate disturbance factors in the world,plays an important role in modulating the variability of the DPEs in the two basins.Singular value decomposition(SVD)analysis revealed that both the YRB and the MDRB’s whole-basin-type DPEs are closely coupled with the procedure that the preceding winter eastern Pacific(EP)-type El Ni?o faded to a central Pacific(CP)-type La Nina.This means that the DPEs in the YRB and MDRB may synchronously occur more frequently when the above process occurs.Owing to the atmosphere–ocean interaction from the east–west dipole sea surface temperature(SST)anomaly pattern,the atmospheric circulation disturbance exhibits a pattern in which the equatorial eastern Pacific region is a mass source anomaly with a higher pressure,drier air,and weaker convection,while the equatorial western Pacific region is a mass sink anomaly with a lower pressure,wetter air,and stronger convection.Moreover,two wave trains that originated from the tropical western Pacific were found to extend to the YRB and MDRB.The interaction between the wave train’s interphase dynamics and water vapor transport disturbance results in the ascent conditions and enhanced water vapor transport,which leads to the synchronous occurrence of DPEs in the YRB and MDRB on an interannual scale.Yu GONG Tong JIANG Buda SU Jinlong HUANG Zbigniew WKUNDZEWICZ Cheng JING Hemin SUN 2021Journal of Meteorological Research2021,35,2:2
5Regional Frequency Analysis of Observed Sub-Daily Rainfall Maxima over Eastern China显示文摘Based on hourly rainfall observational data from 442 stations during 1960–2014, a regional frequency analysis of the annual maxima(AM) sub-daily rainfall series(1-, 2-, 3-, 6-, 12-, and 24-h rainfall, using a moving window approach) for eastern China was conducted. Eastern China was divided into 13 homogeneous regions: Northeast(NE1, NE2), Central(C), Central North(CN1, CN2), Central East(CE1, CE2, CE3), Southeast(SE1, SE2, SE3, SE4), and Southwest(SW).The generalized extreme value performed best for the AM series in regions NE, C, CN2, CE1, CE2, SE2, and SW, and the generalized logistic distribution was appropriate in the other regions. Maximum return levels were in the SE4 region, with value ranges of 80–270 mm(1-h to 24-h rainfall) and 108–390 mm(1-h to 24-h rainfall) for 20- and 100 yr, respectively.Minimum return levels were in the CN1 and NE1 regions, with values of 37–104 mm and 53–140 mm for 20 and 100 yr,respectively. Comparing return levels using the optimal and commonly used Pearson-III distribution, the mean return-level differences in eastern China for 1–24-h rainfall varied from-3–4 mm to-23–11 mm(-10%–10%) for 20-yr events, reaching-6–26 mm(-10%–30%) and-10–133 mm(-10%–90%) for 100-yr events. In view of the large differences in estimated return levels, more attention should be given to frequency analysis of sub-daily rainfall over China, for improved water management and disaster reduction.Hemin SUN Guojie WANG Xiucang LI Jing CHEN Buda SU Tong JIANG 2017Advances in Atmospheric Sciences2017,34,2:2
6Prebability distribution of precipitation extremes for weather index-based insurance in the Zhuji- ang River Basin, South China 显示文摘Thomas Fischer Buda Su Yong Luo 2012Journal of Hydromcteorolngy2012,13,3:1
7Temporal and spatial trends of precipitation and river flow in the Yangtze River Basin, 1961–2000显示文摘Tong Jiang Buda Su Heike Hartmann 2006Geomorphology2006,,3:1
8Spatial and temporal variation of extreme precipitation over the Yangtze River Basin显示文摘Buda Su Marco Gemmer Tong Jiang 2007Quaternary International2007,,1:1
9Temporal and spatial trends of precipitation and river flow in the Yangtze River Basin, 1961 - 2000显示文摘Jiang Tong Su Buda Hartmann H 2007Geomorphology2007,85,3:1
10Spatialvariation and trends in PDSI and SPI indices andtheir relation to streamflow in 10 large regions of China显示文摘ZHAI Jianqing SU Buda GAO Chao 0,,:1
11Probability Distribution of Precipitation Extremes for Weather Index-Based Insurance in the Zhujiang River Basin, South China显示文摘Fischer Thomas Su Buda Luo Yong Scholten Thomas 2012Journal of Hydrometeorology2012,13,3:1
12Temperature and precipitation trends and dryness/wetness pattern in the Zhujiang River Basin, South China, 1961–2007显示文摘Thomas Fischer Marco Gemmer Liu Lüliu Su Buda 2010Quaternary International2010,,2:1
13Simulated and projected climate extremes in the Zhujiang River Basin, South China, using the regional climate model COSMO‐CLM显示文摘Thomas Fischer Christoph Menz Buda Su Thomas Scholten 2013Climatol2013,,14:1
14Spatial and temporal vari-ation of extreme precipitation over the Yangtze River Basin 显示文摘Buda Su Marco Gemmer Tong Jiang 2008Quaternary International2008,,186:1
15Spatial and tempo-ral variation of extreme precipitation over the Yangtze River Basin显示文摘Su Buda Gemmer M Jiang Tong 2008Quaternary International2008,186,1:1
16Runoff components and the contributions of precipitation and temperature in a highly glacierized river basin in Central As显示文摘Understanding the main drivers of runoff components and contributions of precipitation and temperature have important implications for water-limited inland basins,where snow and glacier melt provide essential inputs to surface runoff.To quantify the impact of temperature and precipitation changes on river runoff in the Tarim River basin(TRB),the Hydrologiska Byrans Vattenbalansavdelning(HBV)-light model,which contains a glacier routine process,was applied to analyze the change in runoff composition.Runoff in the headstream parts of the TRB was more sensitive to temperature than to precipitation.In the TRB,overall,rainfall generated 41.22%of the total runoff,while snow and glacier meltwater generated 20.72%and 38.06%,respectively.These values indicate that temperature exerted more major effects on runoff than did precipitation.Runoff compositions were different in the various subbasins and may have been caused by different glacier coverages.The runoff volumes generated by rainfall,snowmelt,glacier melt was almost equal in the Aksu River subbasin.In the Yarkand and Hotan River subbasins,glacier meltwater was the main supplier of runoff,accounting for 46.72%and 58.73%,respectively.In the Kaidu-Kongque River subbasin,80.86%was fed by rainfall and 19.14%was fed by snowmelt.In the TRB,runoff generated by rainfall was the dominant component in spring,autumn,winter,while glacier melt runoff was the dominant component in summer.Runoff in the TRB significantly increased during 1961–2016;additionally,56.49%of the increase in runoff was contributed by temperature changes,and 43.51%was contributed by precipitation changes.In spring,the runoff increase in the TRB was mainly caused by the precipitation increase,opposite result in summer and autumn.Contribution of temperature was negative in winter.Our findings have important implications for water resource management in high mountainous regions and for similar river basins in which melting glaciers strongly impact the hydrological cycle.Anqian WANG Buda SU Jinlong HUANG Cheng JING Zbigniew WKUNDZEWICZ Hui TAO Mingjin ZHAN Tong JIANG 2023Frontiers of Earth Science2023,17,2:1
17Spatial and temporal variation of extreme precipitation over the Yangtze River Basin显示文摘Buda Su Marco Gemmer Tong Jiang 2007Quaternary International2007,,1:1
18Temporal and spatial trends of precipitation and river flow in the Yangtze River Basin, 1961–2000显示文摘Tong Jiang Buda Su Heike Hartmann 2006Geomorphology2006,,3:1
19Spatial Variation and Trends in PDSI and SPI Indices and Their Relation to Streamflow in 10 Large Regions of China显示文摘Zhai Jianqing Su Buda Krysanova Valentina Vetter Tobias Gao Chao Jiang Tong 2010Journal of Climate2010,,3:1
20Projected land use changes in the Qinghai-Tibet Plateau at the carbon peak and carbon neutrality targets显示文摘Based on historical land use for eight periods from 1980 to 2020 and the projected land use under seven Shared Socioeconomic Pathways(SSPs:SSP1-1.9,SSP1-2.6,SSP2-4.5,SSP3-7.0,SSP4-3.4,SSP4-6.0,and SSP5-8.5)from 2021 to 2100,we conducted a study on past and future land use changes in the Qinghai-Tibet Plateau(QTP).This work aims to reveal the land use changes during the carbon peak(2021-2040)and carbon neutrality(2051-2070)periods and at the end of the 21st century(2081-2100).The results show that:(1)in the historical period(1980-2020),the land use types in the QTP were grassland(1475×10^(3)km^(2),58.2%),barren land(685×10^(3)km^(2),27.0%),forest land(243×10^(3)km^(2),9.6%),water(114×10^(3)km^(2),4.5%),cropland(18.6×10^(3)km^(2),0.7%)and urban land(0.3×10^(3)km^(2),0.01%).(2)Relative to the baseline period(1995-2014),the area of grassland is projected to decrease by 0.7%(SSP4-6.0)-5.4%(SSP2-4.5)(0.5-3.9%of the total area of the QTP),2.8%(SSP4-6.0)-12.5%(SSP3-7.0)(2.1-9.4%of the total area of the QTP)and 6.1%(SSP4-6.0)-21.7%(SSP4-3.4)(4.6-16.4%of the total area of the QTP)in the future three periods.In contrast,the forest land area is projected to increase,by approximately 2.5%(SSP4-6.0)to 30.1%(SSP3-7.0)(0.3-4.3%of the total area of the QTP),9.2%(SSP4-6.0)to 56.5%(SSP2-4.5)(1.3-8.0%of the total area of the QTP),and 21.2%(SSP4-6.0)to 72.8%(SSP2-4.5)(3.0-10.2%of the total area of the QTP)in the future three periods,respectively.(3)Approximately 0.4(SSP4-6.0)to 6.9%(SSP5-8.5),0.9(SSP4-6.0)to 2.7%(SSP4-3.4),and 0.04(SSP5-8.5)to 3.5%(SSP1-1.9)of land is expected to convert from grassland to forest land in the future three periods,respectively.The shift from grassland to forest land area is likely to enhance the carbon sink potential of the QTP in the future period.Runhong XU Peijun SHI Miaoni GAO Yanjun WANG Guojie WANG Buda SU Jinlong HUANG Qigen LIN Tong JIANG 2023Science China Earth Sciences2023,66,6:0
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