Based on integrated simulations of 26 global climate models provided by the Coupled Model Intercomparison Project(CMIP), this study predicts changes in temperature and precipitation across China in the 21 st century u...Based on integrated simulations of 26 global climate models provided by the Coupled Model Intercomparison Project(CMIP), this study predicts changes in temperature and precipitation across China in the 21 st century under different representative concentration pathways(RCPs), and analyzes uncertainties of the predictions using Taylor diagrams. Results show that increases of average annual temperature in China using three RCPs(RCP2.6, RCP4.5,RCP8.5) are 1.87 ℃, 2.88 ℃ and 5.51 ℃, respectively. Increases in average annual precipitation are 0.124, 0.214, and 0.323 mm/day, respectively. The increased temperature and precipitation in the 21 st century are mainly contributed by the Tibetan Plateau and Northeast China. Uncertainty analysis shows that most CMIP5 models could predict temperature well, but had a relatively large deviation in predicting precipitation in China in the 21 st century. Deviation analysis shows that more than 80% of the area of China had stronger signals than noise for temperature prediction;however, the area proportion that had meaningful signals for precipitation prediction was less than 20%. Thus, the multi-model ensemble was more reliable in predicting temperature than precipitation because of large uncertainties of precipitation.展开更多
A Bayesian multi-model inference framework was used to assess the changes in the occurrence of extreme hydroclimatic events in four major river basins in China （i.e., Liaohe River Basin, Yellow River Basin, Yangtze R...A Bayesian multi-model inference framework was used to assess the changes in the occurrence of extreme hydroclimatic events in four major river basins in China （i.e., Liaohe River Basin, Yellow River Basin, Yangtze River Basin, and Pearl River Basin） under RCP2.6, RCP4.5, and RCP8.5 scenarios using multiple global climate model projections from the IPCC Fifth Assessment Report. The results projected more summer days and fewer frost days in 2006-2099. The ensemble prediction shows the Pearl River Basin is projected to experience more summer days than other basins with the increasing trend of 16.3, 38.0, and 73.0 d per 100 years for RCP2.6, RCP4.5 and RCP8.5, respectively. Liaohe River Basin and Yellow River Basin are forecasted to become wetter and warmer with the co-occurrence of increases in summer days and wet days. Very heavy precipitation days （R20, daily precipitation ≥20 mm） are projected to increase in all basins. The R20 in the Yangtze River Basin are projected to have the highest change rate in 2006-2099 of 1.8, 2.5, and 3.8 d per 100 years for RCP2.6, RCP4.5 and RCP8.5, respectively.展开更多
目的:通过计算环切缘的最佳截断值,分析食管鳞状细胞癌患者环周切缘情况与术后生存预后的相关性。方法:本研究回顾性纳入2012年04月至2018年01月期间在我院接受手术治疗的200例食管鳞状细胞癌患者。所有患者术后病理结果均显示为pT_(3)N...目的:通过计算环切缘的最佳截断值,分析食管鳞状细胞癌患者环周切缘情况与术后生存预后的相关性。方法:本研究回顾性纳入2012年04月至2018年01月期间在我院接受手术治疗的200例食管鳞状细胞癌患者。所有患者术后病理结果均显示为pT_(3)N_(0)M_(0)期。通过测量肿瘤细胞距离垂直切缘的最小距离,并使用X-tile软件计算影响肿瘤预后的环切缘最佳截断值。我们根据最佳截断值自定义了改进型环切缘标准,并将其与传统的美国病理学家学院(College of American Pathologists,CAP)和英国皇家病理学家学院(Royal College of Physicians,RCP)标准进行卡方检验和对比分析。与此同时,利用单因素和多因素COX回归分析研究影响食管鳞状细胞癌预后的因素。结果:通过使用X-tile软件计算得出的结果显示,环切缘的最佳截断值为0.65 mm。根据此值,我们自定义改进型环切缘标准,并能够区分不同组别之间的生存差异(P<0.05)。卡方检验分析结果显示,对患者年龄、性别、肿瘤位置、肿瘤长度、肿瘤分化程度和术后辅助治疗等临床病理参数进行校正后,三种环切缘分型之间没有显著差异;单因素和多因素COX回归分析结果显示,本研究自定义的改进型环切缘标准在不同手术分组中均是影响食管鳞状细胞癌预后的独立危险因素。结论:环切缘状态是影响食管鳞状细胞癌患者预后的独立影响因素,本研究所得出的改进型环切缘标准相比传统标准能够更好地评估食管鳞状细胞癌术后患者的预后。展开更多
Afghanistan has faced extreme climatic crises such as drought,rising temperature,and scarce precipitation,and these crises will likely worsen in the future.Reduction in crop yield can affect food security in Afghanist...Afghanistan has faced extreme climatic crises such as drought,rising temperature,and scarce precipitation,and these crises will likely worsen in the future.Reduction in crop yield can affect food security in Afghanistan,where the majority of population and economy are completely dependent on agriculture.This study assessed the interaction between climate change and crop yield in Kabul of Afghanistan during the reference(1990–2020)and future(2025–2100)periods.Climate data(1990–2020)were collected from four meteorological stations and three local organizations,and wheat yield data(1990–2020)were acquired from the United States Agriculture Department.Data during the reference period(1990–2020)were used for the validation and calibration of the statistical downscaling models such as the Statistical Downscaling Model(SDSM)and Long Ashton Research Station Weather Generator(LARS-WG).Furthermore,the auto-regression model was used for trend analysis.The results showed that an increase in the average annual temperature of 2.15℃,2.89℃,and 4.13℃will lead to a reduction in the wheat yield of 9.14%,10.20%,and 12.00%under Representative Concentration Pathway(RCP)2.6,RCP4.5,and RCP8.5 during the future period(2025–2100),respectively.Moreover,an increase in the annual maximum temperature of 1.79℃,2.48℃,and 3.74℃also causes a significant reduction in the wheat yield of 2.60%,3.60%,and 10.50%under RCP2.6,RCP4.5,and RCP8.5,respectively.Furthermore,an increase in the annual minimum temperature of 2.98℃,2.23℃,and 4.30℃can result in an increase in the wheat yield of 6.50%,4.80%,and 9.30%under RCP2.6,RCP4.5,and RCP8.5,respectively.According to the SDSM,the decrease of the average monthly precipitation of 4.34%,4.10%,and 5.13%results in a decrease in the wheat yield of 2.60%,2.36%,and 3.18%under RCP2.6,RCP4.5,and RCP8.5,respectively.This study suggests that adaptation strategies can be applied to minimize the consequences of climate change on agricultural production.展开更多
This study assessed the contribution of climate projections to improving rainfall information for cocoa crops in the central and southern regions of Côte d’Ivoire. Particular attention was paid to fourteen local...This study assessed the contribution of climate projections to improving rainfall information for cocoa crops in the central and southern regions of Côte d’Ivoire. Particular attention was paid to fourteen localities in these two climatic zones. Simulation data were obtained from the CORDEX ensemble and observation data from CHIRPS. They cover the period 1991-2005 for the reference period and the future period from 2021 to 2050 for the RCP4.5 and RCP8.5 scenarios. In addition, the study was based on the water requirements necessary during the critical phase of the cocoa tree (the flowering phase) for a good yield from the cocoa production chain on the one hand, and on a selection of three climate indices CDD, CWD and r95PTOT to study their spatio-temporal changes over two future periods 2021-2035 (near future) and 2036-2050 (medium-term) on the other. These climatic indices influence cocoa cultivation and their use in studies of climatic impacts on agriculture is of prime importance. The analysis of their spatio-temporal changes in this work also contributes to providing climate services based on rainfall, to which cocoa crops are highly sensitive. Our results show that the CDD and CWD indices vary from one region to another depending on latitude. For the fourteen localities studied, the number of consecutive dry days (CDD) could increase between now and 2050, while the number of consecutive wet days (CWD) could decrease over the period 2021-2035 and then increase over the period 2036-2050. The localities of Tabou, Aboisso and San-Pedro record high numbers of CDD index and CWD index for both projection scenarios. In comparison with the RCP4.5 and RCP8.5 scenarios, these results show that the RCP8.5 scenarios are having an impact on cocoa growing in Côte d’Ivoire.展开更多
基金Science and Technology Program of Nanning,Guangxi,China(20153257)Major Science and Technology Program of Guangxi,China(GKAB16380267)+2 种基金National Natural Science Foundation of Guangxi(2014GXNSFBA118094,2015GXNSFAA139243)National Natural Science Foundation of China(41565005)Guangxi Refined Forecast Service Innovation Team
文摘Based on integrated simulations of 26 global climate models provided by the Coupled Model Intercomparison Project(CMIP), this study predicts changes in temperature and precipitation across China in the 21 st century under different representative concentration pathways(RCPs), and analyzes uncertainties of the predictions using Taylor diagrams. Results show that increases of average annual temperature in China using three RCPs(RCP2.6, RCP4.5,RCP8.5) are 1.87 ℃, 2.88 ℃ and 5.51 ℃, respectively. Increases in average annual precipitation are 0.124, 0.214, and 0.323 mm/day, respectively. The increased temperature and precipitation in the 21 st century are mainly contributed by the Tibetan Plateau and Northeast China. Uncertainty analysis shows that most CMIP5 models could predict temperature well, but had a relatively large deviation in predicting precipitation in China in the 21 st century. Deviation analysis shows that more than 80% of the area of China had stronger signals than noise for temperature prediction;however, the area proportion that had meaningful signals for precipitation prediction was less than 20%. Thus, the multi-model ensemble was more reliable in predicting temperature than precipitation because of large uncertainties of precipitation.
基金Acknowledgments Funding for this research was provided by the National Key Basic Special Foundation Project of China （2010CB428400）, and the National Natural Science Foundation of China （41375139）. We are grateful to the Program for Climate Model Diagnosis and Intercomparison for collecting and archiving the model data.
文摘A Bayesian multi-model inference framework was used to assess the changes in the occurrence of extreme hydroclimatic events in four major river basins in China （i.e., Liaohe River Basin, Yellow River Basin, Yangtze River Basin, and Pearl River Basin） under RCP2.6, RCP4.5, and RCP8.5 scenarios using multiple global climate model projections from the IPCC Fifth Assessment Report. The results projected more summer days and fewer frost days in 2006-2099. The ensemble prediction shows the Pearl River Basin is projected to experience more summer days than other basins with the increasing trend of 16.3, 38.0, and 73.0 d per 100 years for RCP2.6, RCP4.5 and RCP8.5, respectively. Liaohe River Basin and Yellow River Basin are forecasted to become wetter and warmer with the co-occurrence of increases in summer days and wet days. Very heavy precipitation days （R20, daily precipitation ≥20 mm） are projected to increase in all basins. The R20 in the Yangtze River Basin are projected to have the highest change rate in 2006-2099 of 1.8, 2.5, and 3.8 d per 100 years for RCP2.6, RCP4.5 and RCP8.5, respectively.
文摘目的:通过计算环切缘的最佳截断值,分析食管鳞状细胞癌患者环周切缘情况与术后生存预后的相关性。方法:本研究回顾性纳入2012年04月至2018年01月期间在我院接受手术治疗的200例食管鳞状细胞癌患者。所有患者术后病理结果均显示为pT_(3)N_(0)M_(0)期。通过测量肿瘤细胞距离垂直切缘的最小距离,并使用X-tile软件计算影响肿瘤预后的环切缘最佳截断值。我们根据最佳截断值自定义了改进型环切缘标准,并将其与传统的美国病理学家学院(College of American Pathologists,CAP)和英国皇家病理学家学院(Royal College of Physicians,RCP)标准进行卡方检验和对比分析。与此同时,利用单因素和多因素COX回归分析研究影响食管鳞状细胞癌预后的因素。结果:通过使用X-tile软件计算得出的结果显示,环切缘的最佳截断值为0.65 mm。根据此值,我们自定义改进型环切缘标准,并能够区分不同组别之间的生存差异(P<0.05)。卡方检验分析结果显示,对患者年龄、性别、肿瘤位置、肿瘤长度、肿瘤分化程度和术后辅助治疗等临床病理参数进行校正后,三种环切缘分型之间没有显著差异;单因素和多因素COX回归分析结果显示,本研究自定义的改进型环切缘标准在不同手术分组中均是影响食管鳞状细胞癌预后的独立危险因素。结论:环切缘状态是影响食管鳞状细胞癌患者预后的独立影响因素,本研究所得出的改进型环切缘标准相比传统标准能够更好地评估食管鳞状细胞癌术后患者的预后。
文摘Afghanistan has faced extreme climatic crises such as drought,rising temperature,and scarce precipitation,and these crises will likely worsen in the future.Reduction in crop yield can affect food security in Afghanistan,where the majority of population and economy are completely dependent on agriculture.This study assessed the interaction between climate change and crop yield in Kabul of Afghanistan during the reference(1990–2020)and future(2025–2100)periods.Climate data(1990–2020)were collected from four meteorological stations and three local organizations,and wheat yield data(1990–2020)were acquired from the United States Agriculture Department.Data during the reference period(1990–2020)were used for the validation and calibration of the statistical downscaling models such as the Statistical Downscaling Model(SDSM)and Long Ashton Research Station Weather Generator(LARS-WG).Furthermore,the auto-regression model was used for trend analysis.The results showed that an increase in the average annual temperature of 2.15℃,2.89℃,and 4.13℃will lead to a reduction in the wheat yield of 9.14%,10.20%,and 12.00%under Representative Concentration Pathway(RCP)2.6,RCP4.5,and RCP8.5 during the future period(2025–2100),respectively.Moreover,an increase in the annual maximum temperature of 1.79℃,2.48℃,and 3.74℃also causes a significant reduction in the wheat yield of 2.60%,3.60%,and 10.50%under RCP2.6,RCP4.5,and RCP8.5,respectively.Furthermore,an increase in the annual minimum temperature of 2.98℃,2.23℃,and 4.30℃can result in an increase in the wheat yield of 6.50%,4.80%,and 9.30%under RCP2.6,RCP4.5,and RCP8.5,respectively.According to the SDSM,the decrease of the average monthly precipitation of 4.34%,4.10%,and 5.13%results in a decrease in the wheat yield of 2.60%,2.36%,and 3.18%under RCP2.6,RCP4.5,and RCP8.5,respectively.This study suggests that adaptation strategies can be applied to minimize the consequences of climate change on agricultural production.
文摘This study assessed the contribution of climate projections to improving rainfall information for cocoa crops in the central and southern regions of Côte d’Ivoire. Particular attention was paid to fourteen localities in these two climatic zones. Simulation data were obtained from the CORDEX ensemble and observation data from CHIRPS. They cover the period 1991-2005 for the reference period and the future period from 2021 to 2050 for the RCP4.5 and RCP8.5 scenarios. In addition, the study was based on the water requirements necessary during the critical phase of the cocoa tree (the flowering phase) for a good yield from the cocoa production chain on the one hand, and on a selection of three climate indices CDD, CWD and r95PTOT to study their spatio-temporal changes over two future periods 2021-2035 (near future) and 2036-2050 (medium-term) on the other. These climatic indices influence cocoa cultivation and their use in studies of climatic impacts on agriculture is of prime importance. The analysis of their spatio-temporal changes in this work also contributes to providing climate services based on rainfall, to which cocoa crops are highly sensitive. Our results show that the CDD and CWD indices vary from one region to another depending on latitude. For the fourteen localities studied, the number of consecutive dry days (CDD) could increase between now and 2050, while the number of consecutive wet days (CWD) could decrease over the period 2021-2035 and then increase over the period 2036-2050. The localities of Tabou, Aboisso and San-Pedro record high numbers of CDD index and CWD index for both projection scenarios. In comparison with the RCP4.5 and RCP8.5 scenarios, these results show that the RCP8.5 scenarios are having an impact on cocoa growing in Côte d’Ivoire.
