Studying the abrupt change of winter temperature(ACWT)over the Mongolian Plateau(MP,including Inner Mongolia Autonomous Region and State of Mongolia)is of great significance for understanding the spatiotemporal distri...Studying the abrupt change of winter temperature(ACWT)over the Mongolian Plateau(MP,including Inner Mongolia Autonomous Region and State of Mongolia)is of great significance for understanding the spatiotemporal distribution of temperature and the mechanism of global climate change.Monthly temperature data during 1961–2017was collected,and the abrupt change point was determined by the Mann–Kendall test and sliding ttest,to analyze the characteristics and causes of ACWT.The results showed that(a)The winter temperature has rapidly increased with a trend of 0.41℃/10a,which was significantly higher than that of the rest area of Chinese mainland,indicating that climate change in the MP was more sensitive to global warming.(b)The abrupt change point occurred in 1988,with temperature of-15.5℃and-14.1℃before and after abrupt change,respectively.The ACWT in 50°N was 1–3 years later than that in 40°N,and the isotherms of different temperatures moved northward by 10–200 km,especially-16℃isotherms moved approximately 200 km northward after 1988.(c)The Arctic Oscillation(AO)and Mongolian High(MH)anomaly affects winter temperature over the MP.When the AO is unusually strong,the MH and East Asian winter monsoon are weak,and southerly winds prevail in most regions,which is not conducive to the cold air developing southward,leading to higher winter temperature in the MP.Overwise,abnormally northerly winds prevail and temperature is low.Meanwhile,the abrupt change time of AO occurred in 1987 before winter temperature.It shows that the AO indirectly causes winter temperatures to rise by influencing the MH and is also the main driving factor of ACWT.展开更多
工程设计中往往需要同时处理固有不确定性与认知不确定性。对于固有不确定性分析与量化,国内外已有诸多研究,例如 Monte Carlo 方法、正交多项式展开理论和概率密度演化理论等。而对认知不确定性、特别是固有不确定性与认知不确定性耦...工程设计中往往需要同时处理固有不确定性与认知不确定性。对于固有不确定性分析与量化,国内外已有诸多研究,例如 Monte Carlo 方法、正交多项式展开理论和概率密度演化理论等。而对认知不确定性、特别是固有不确定性与认知不确定性耦合情况下的研究,则还相对缺乏。该文中,针对数据稀缺与数据更新导致的认知不确定性,首先分别引入 Bootstrap 方法和 Bayes 更新方法进行不确定性表征。在此基础上,结合基于概率密度演化-测度变换的两类不确定性量化统一理论新框架,提出了存在认知不确定性情况下的不确定性传播与可靠性分析高效方法及其具体数值算法。由此,给出了基于数据进行工程系统不确定性量化、传播与可靠性分析的基本途径。通过具有工程实际数据的 3 个工程实例分析,包括无限边坡稳定性分析、挡土墙稳定性分析和屋面桁架结构可靠性分析,验证了该文方法的精度和效率。展开更多
The Huolin River catchment(HRC)is located in the semi-arid region of Northeast China,which is very sensitive to climate change.The runoff in HRC is closely related to the recovery of local vegetation in the Greater Kh...The Huolin River catchment(HRC)is located in the semi-arid region of Northeast China,which is very sensitive to climate change.The runoff in HRC is closely related to the recovery of local vegetation in the Greater Khingan Mountains and the survival of downstream wetlands.Dramatic runoff fluctuations and increasing no-flow days confirmed the water crisis in this area.Hence,it is extremely urgent to study the current situation and characteristics of runoff.In this study,hydrological and meteorological data of HRC during 1956-2018 were analyzed to elucidate the processes,characteristics,trends of the river runoff and revealed its response to climate change.The Mann-Kendall test and linear regression method showed that runoff in the HRC demonstrated a downward trend over the study period with a marked annual variation.The runoff in the high flow years was 100 times that of the low flow years,showing a typical continental climatic river characteristic.There are two runoff peak flows in the intra-annual runoff distribution in March and July,whereas two runoff valleys occurred around May and September to February.The runoff positively correlates with precipitation in summer and temperature in early spring.Snowmelt influenced by rising temperatures in April and precipitation in July is the main driving factor for the two peaks flow.Evaporation rose with precipitation decline and temperature increased,which may influence the runoff decrease.The annual runoff is well synchronized with the annual precipitation,and precipitation change is the main driving factor of variation and abrupt change points of annual runoff in the catchment.This study would be beneficial for water resource management in developing adaptation strategies to offset the negative impact of climate change in HRC.展开更多
基金financially sponsored by the National Natural Science Foundation of China(41967052)the Graduate Students’Research&Innovation Fund of Inner Mongolia Normal University(CXJJS20117)the Graduate Education Innovation Program Funded Project of Inner Mongolia Autonomous Region(SZ2020119)。
文摘Studying the abrupt change of winter temperature(ACWT)over the Mongolian Plateau(MP,including Inner Mongolia Autonomous Region and State of Mongolia)is of great significance for understanding the spatiotemporal distribution of temperature and the mechanism of global climate change.Monthly temperature data during 1961–2017was collected,and the abrupt change point was determined by the Mann–Kendall test and sliding ttest,to analyze the characteristics and causes of ACWT.The results showed that(a)The winter temperature has rapidly increased with a trend of 0.41℃/10a,which was significantly higher than that of the rest area of Chinese mainland,indicating that climate change in the MP was more sensitive to global warming.(b)The abrupt change point occurred in 1988,with temperature of-15.5℃and-14.1℃before and after abrupt change,respectively.The ACWT in 50°N was 1–3 years later than that in 40°N,and the isotherms of different temperatures moved northward by 10–200 km,especially-16℃isotherms moved approximately 200 km northward after 1988.(c)The Arctic Oscillation(AO)and Mongolian High(MH)anomaly affects winter temperature over the MP.When the AO is unusually strong,the MH and East Asian winter monsoon are weak,and southerly winds prevail in most regions,which is not conducive to the cold air developing southward,leading to higher winter temperature in the MP.Overwise,abnormally northerly winds prevail and temperature is low.Meanwhile,the abrupt change time of AO occurred in 1987 before winter temperature.It shows that the AO indirectly causes winter temperatures to rise by influencing the MH and is also the main driving factor of ACWT.
文摘工程设计中往往需要同时处理固有不确定性与认知不确定性。对于固有不确定性分析与量化,国内外已有诸多研究,例如 Monte Carlo 方法、正交多项式展开理论和概率密度演化理论等。而对认知不确定性、特别是固有不确定性与认知不确定性耦合情况下的研究,则还相对缺乏。该文中,针对数据稀缺与数据更新导致的认知不确定性,首先分别引入 Bootstrap 方法和 Bayes 更新方法进行不确定性表征。在此基础上,结合基于概率密度演化-测度变换的两类不确定性量化统一理论新框架,提出了存在认知不确定性情况下的不确定性传播与可靠性分析高效方法及其具体数值算法。由此,给出了基于数据进行工程系统不确定性量化、传播与可靠性分析的基本途径。通过具有工程实际数据的 3 个工程实例分析,包括无限边坡稳定性分析、挡土墙稳定性分析和屋面桁架结构可靠性分析,验证了该文方法的精度和效率。
基金This article was financially supported by the Natural Science Plan of Inner Mongolia(2019GG020)the Postgraduate Research and Innovation Foundation of Inner Mongolia Normal University(Grant Nos.CXJJB20013).
文摘The Huolin River catchment(HRC)is located in the semi-arid region of Northeast China,which is very sensitive to climate change.The runoff in HRC is closely related to the recovery of local vegetation in the Greater Khingan Mountains and the survival of downstream wetlands.Dramatic runoff fluctuations and increasing no-flow days confirmed the water crisis in this area.Hence,it is extremely urgent to study the current situation and characteristics of runoff.In this study,hydrological and meteorological data of HRC during 1956-2018 were analyzed to elucidate the processes,characteristics,trends of the river runoff and revealed its response to climate change.The Mann-Kendall test and linear regression method showed that runoff in the HRC demonstrated a downward trend over the study period with a marked annual variation.The runoff in the high flow years was 100 times that of the low flow years,showing a typical continental climatic river characteristic.There are two runoff peak flows in the intra-annual runoff distribution in March and July,whereas two runoff valleys occurred around May and September to February.The runoff positively correlates with precipitation in summer and temperature in early spring.Snowmelt influenced by rising temperatures in April and precipitation in July is the main driving factor for the two peaks flow.Evaporation rose with precipitation decline and temperature increased,which may influence the runoff decrease.The annual runoff is well synchronized with the annual precipitation,and precipitation change is the main driving factor of variation and abrupt change points of annual runoff in the catchment.This study would be beneficial for water resource management in developing adaptation strategies to offset the negative impact of climate change in HRC.
