增暖背景下基于概率理论与过程性原理极端天气气候事件的检测及其特征研究
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摘要
极端天气气候事件是小概率事件,IPCC评估报告从概率角度对极端天气气候事件做了明确的定义,因此从概率角度定义极端天气气候事件具有较好的理论意义。本文利用Box-Cox变换改善数据的正态性的特性,通过变换后数据呈较好的正态性反演推导获得气象要素的偏态概率密度函数,为极端天气气候事件从概率角度定义、检测提供理论依据；根据概率密度函数定义了具有明确物理含义的最概然温度,以最概然温度的变化反映中国各区域背景场温度的变化趋势；根据概率密度函数定义了极端天气气候事件,分别从强度、频次角度研究中国极端温度事件的空间分布及其时间演化规律,为回答在全球增暖背景下极端天气气候事件是否越来越频繁、是否越来越趋于极端化提供事实依据。在检测出的一系列天气极值事件的基础上,根据共相同步化原理从事件发生的过程性来确定极端事件的过程,致力于提出一种行之有效的客观检测过程性极端事件的新方法,并将其应用于2009年的西南干旱事件的观测资料的检测中,为西南干旱事件的研究提供一个新视角。以下是本文主要结论：
(1)偏态概率密度函数较正态分布函数更精确地拟合了温度分布。Box-Cox变换指数λ大小反映了序列分布的偏态情况,即要素分布对正态分布的适合度。以正态分布λ=1为基准,变换指数越大,右偏越明显,越小说明左偏越明显。变换指数的变化也能间接反映中国温度变化的背景、趋势。
(2)由概率密度函数定义的最概然温度具有明确的物理含义,代表了某地区的背景场温度。就年际而言,在20世纪90年代中期之前中国夏季年最概然温度以相对低温为主,随后呈现波动增温趋势,但自2005年增温趋势有所减缓；冬季年最概然温度在1961-1986年这一时段以相对低温为主,1987年到21世纪初显著变暖,但2000年后增温趋势减缓。总体而言,冬季增温幅度较夏季强,且增温时间早于夏季5-10年。定义1961-1990年、1971-2000年和1981-2008年分别为Ⅰ、Ⅱ、Ⅲ态(下同),不同气候态的研究表明,夏季最概然温度在Ⅲ态增温明显,而冬季在Ⅱ态间增温显著,Ⅲ态增温趋势减弱,尤其值得注意的是,近年来在四川、广东和广西部分地区最概然温度具有下降趋势,是否预示着中国气候态的转型有待深入研究。
(3)基于偏态概率密度函数定义的极端温度事件,分别从频次、强度两个角度研究了不同气候态下日最高温资料中国夏季和冬季极端温度事件的时空变化特征。空间分布上,夏季极端高温的频次、强度在Ⅰ态黄淮、江淮流域显著减小,在Ⅲ态,干旱半干旱以及经济发达的长江沿岸、长江三角洲以及东南沿海地区显著增加；冬季极端高温频次在Ⅱ态中的北方、长江三角洲以及Ⅲ态中的高原、东北东南部、长江三角洲显著降低。冬季极端低温强度整体呈降低趋势,但区域特征不明显。极端温度频次和强度在空间上一致性较好；时间演化上,夏季极端高温频次、强度均在Ⅱ、Ⅲ态显著增加,冬季极端低温频次、强度降低的趋势有所减缓。在当前气候态(Ⅲ态)夏季极端高温在经济发达地区发生比较频繁且极端性在增强；冬季极端低温的发生维持在一个稳定状态且极端性也相对比较稳定。极端温度事件的频次与强度在时间变化趋势上存在较好的一致性。
(4)在Ⅰ、Ⅱ、Ⅲ态共同时段内,后一气候态检测出的极端高温频次均比前一气候态少,极端低温频次均比前一气候态多,这与背景温度随气候态逐渐升高是相一致的；后一气候态检测出的极端高温强度均比前一气候态小,极端低温强度均比前一气候态大。在20世纪70年代末80年代初全球气候系统突变前,极端高温频次具有明显的下降趋势,突变后显著上升；极端低温频次在突变前后变化不明显。极端高温强度突变前表现出轻微的下降趋势,在突变后上升趋势明显；极端低温强度在突变前后大致相当,突变后的整体强度稍低于突变前。极端高温事件的逐渐增强以及极端低温事件的逐渐减少在日最低温资料中体现更明显,这从另一方面表明逐渐增暖主要表现在日最低温中。
(5)夏季高温极值的概率分布规律及变化特征表现为：中国高温极值只在一定的区域呈现高斯分布,大部分台站处于左偏分布型,西南东南部左偏尤为明显；而长江中下游以南地区及东南沿海地区呈较明显的右偏；以偏态指数和最概然高温极值作为研究中国夏季高温极值概率分布特征的关键指标,经验表明最概然极端高温是一个比较稳定的量,可将其作为定义极端高温事件阈值的一种可能方法。
(6)在通过概率理论检测获得一系列天气极值事件的基础上,从事件发生、发展、消亡的角度利用共相同步化原理,将具有一定关联的极值天气事件客观地归属为一个具有实际应用意义上的极端气候事件。共相同步化原理数值检验结果表明,聚类质量评估peff、△peff为K均值聚类分析提供了判别最优聚类数目K的极好依据,而相位概念的引入则将系统所处的不同状态分离开来,相位聚类分析运用于事件过程的检测在理论上是可行的。
(7)共相同步化原理应用于西南干旱事件的干旱指数与降水量距平过程性检测结果表明,西南地区干旱指数MSPI过程性检测出了选择观测站自2009年1月开始由干旱指数表征的干旱程度的变化过程,涉及由旱-湿、湿-旱或者一直干旱抑或一直湿润的几个状态过程的转换情况。有别于气象部门利用干旱指数值大小表征干旱的严重程度,过程性检测不仅仅鉴别出干旱抑或湿润的状态,还鉴别出旱转为湿或者湿润趋于干旱的过程,给过程赋予趋势变化的含义,而转变所处的时间段是状态与状态转变的转折阶段,通常为湿润或者干旱的极值处或者是与前后状态相反的过渡状态。
(8)干旱指数时间过程性检测结果表明,自2009年1月开始西南大部分地区以及开始显示一定程度的气象干旱,干旱一直持续至2010年冬与2010年春,之后干旱严重程度开始缓解。若考虑此次事件的前期产生过程,从干旱指数的角度西南干旱自2009年1月就开始趋于干旱,从时间过程性的角度而言,比从观测资料本身大小界定的事件开始时间要早,这从另一个角度验证了关于过程的定义的意义——包含事件的产生过程,因此将极端事件的产生阶段作为预警阶段不失为一个具有实际意义的可能应用。
降水量距平过程性检测结果与干旱指数检测结果不是一一对应的关系,这是由于降水偏少与干旱响应的时间滞后以及干旱形成原因比较复杂造成的,与降水在干旱形成过程中的重要作用并不矛盾。西南干旱事件过程性的检测为再次认识干旱事件提供一个新的视角,而过程的确定给出了气候背景变化的阶段,为干旱事件的气候背景分析提供时间阶段节点。
Extreme climate events are of small probability and were given definitely definition in AR4according to probability. So it has rather theoretical significance to define extreme climate events from the point of probability. Because Box-Cox transformation can improve data normality and the data by Box-Cox transformation are normal, the skewed probability function is derived, which provides theory basis to define extreme events based on probability. According to the skewed probability function, most probable temperature (MPT) is defined and it has definite physics meaning and can reflect the changing trends of background temperature in different regions over China. Extreme temperature events are defined in terms of skewed function and the temporal-spatial distribution characteristics and time evolution laws of frequencies and strength of them are found, which provide fact foundations to try to answer the question whether extreme events are becoming more and more frequent and extremity. Basing on a series of detected extremum events, the processes of extreme events can be detected by phase synchronization. A new method to detect process of extreme events objectively is raised and it is applied in drought events from2009over Southwest China trying to supply a new angle of view to know the drought events. The following are the major conclusions about above all research:
(1) Compared to normal distribution, the skewed probability function can fit temperature distribution better. The values of Box-Cox transformation index λ reflect the skewed degree of distribution.λ=1is a standard of reference, more big of Box-Cox transformation index, more right skewed of the distribution; more small of index, more left skewed. The changes of index also reflect indirectly the temperature changing trends.
(2) MPT defined by skewed probability function has a definite signification and represent the background temperature fields of some region. MPT interannual variations show that in summer MPT was relative low-temperature-major before the mid-1990s and from then was warming with fluctuation but since2005the trend slowed down and that in winter MPT was relative low-temperature-major1961-1986and from1987to the beginning of the21st century was warming obviously, but since2000the warming trend slowed down. The warming amplitude of winter was stronger than of summer and the time of beginning warming of winter was earlier than of summer about5-10years. Studying three climate state MPT changes of1961-1990、1971-2000.1981-2008found that in summer MPT got warmer obviously in the third climate state while in winter in the second state. MPT' warming trend was slowing down in the third state. It's worthy of note that in Sichuan, Guangdong and Guangxi MPT even began to decline in the last few years. Whether it means climatic transformation needs further research.
(3) Extreme temperature events are defined according to the skewed function. The temporal-spatial distribution characteristics of frequencies and strength of extreme temperature events over China in different climate sates against the backdrop of MPT (Most Probable Temperature) are analyzed. Spatially, frequencies and strength of Extreme high temperature in summer decreased significantly in the Yangtze-Huaihe river valley and Yellow River and Huaihe River valley in State Ⅰ and increased significantly in arid-semiarid region and developed Yangtze River delta in State Ⅲ. Frequencies of Extreme low temperature in winter reduced remarkably in the north and Yangtze River delta in State Ⅱ and in The Qinghai-Tibet Plateau, the southeast of northeast China, Yangtze River delta in State Ⅲ. The strength of extreme low temperature in winter reduced wholly and provincial characteristics were not obvious. The frequencies and strength of extreme temperature events were agreed in spatial. Temporally, frequencies and strength of extreme high temperature in summer increased obviously both in State Ⅱ and State Ⅲ. Frequencies and strength of extreme low temperature in winter reduced obviously in State Ⅱ and the reducing trend was slowing down in State Ⅲ. Extreme high temperature in summer occurred frequently and extreme low temperature in winter remained stably. Extremity of extreme high temperature in summer was more stronger while in winter was stable relatively. The frequencies and strength of extreme temperature events were agreed in temporal.
(4) During the common time period of State Ⅰ, Ⅱ,Ⅲ, the frequencies of extreme high temperature events in the last state were always fewer than the former while the low temperature events were more, which is agreed with the fact that the background temperature steps up with the states; the strength of extreme high temperature events in the latter state was less than the former while of extreme low temperature events was stronger. For the abrupt change of climate at the end of1970s and the beginning of1980s, the frequencies of extreme high temperature events decreased before the change and increased obviously after the change while the ones of extreme low temperature did not change significantly for the change; the strength of extreme high temperature events decreased slightly before the change and increased obviously after the change while the one of extreme low temperature did not change significantly for the change but the whole strength after the change was slightly lower than the one before the change.
(5) The distribution probability of extreme high temperature in summer is mainly left skewed in most regions in China especially in southeast of Southwest while in south of the middle and lower reaches of Changjiang River and China's South-East coastal areas are obviously right skewed. The skewed index and the most probable high extreme temperature are regarded as the key marks about the distribution. The most probable high extreme temperature is rather stable and can be defined as the threshold of extreme temperature.
(6) Basing on a series of detected extremum events, the processes of extreme events are detected by phase synchronization. Numerical modeling of phase synchronization showed that clustering measure Peff and the differences△peff can give the criterion about the proper number of clusters and phases can distinguish different stats of the system. So phase clustering applied to detect processes of extreme climate events is doable.
(7) Drought index MSPI and precipitation anomaly of Southwest drought events in China are used to detect processed by phase synchronization. Drought index from2009presenting different degrees of drought is detected several states, including drought-wetness, wetness-drought, persistent drought or wetness. Processes detection can tell not only persistent drought and wetness state but also the changing state, i.e., from wetness to drought or from drought to wetness, which is different from drought index that can only reflect drought degree according to the values. So process here means changing state as well as stable state. The period of changing state is usually extreme value of drought or wetness or changing period between wetness and drought.
(8) As far as drought index is concerned, drought process began from January2009and persisted to winter and spring in2010. From then, drought began to relive. Considering previous generating process, southwest drought events began from January2009, which is earlier than the result from drought index values. This interprets the meaning about process-including generating process.
The results of precipitation anomaly are not one-to-one correspondence, which was caused by time response lagging of drought to less precipitation and complexity of drought formation cause. This does not contradict the fact that precipitation plays an important role in the formation of drought. The processes detection of southwest drought events provide a new angle of view on the drought events and the processes give the stage of climatic background changing, which provides critical period of climatic background changing about drought events.
(1)偏态概率密度函数较正态分布函数更精确地拟合了温度分布。Box-Cox变换指数λ大小反映了序列分布的偏态情况,即要素分布对正态分布的适合度。以正态分布λ=1为基准,变换指数越大,右偏越明显,越小说明左偏越明显。变换指数的变化也能间接反映中国温度变化的背景、趋势。
(2)由概率密度函数定义的最概然温度具有明确的物理含义,代表了某地区的背景场温度。就年际而言,在20世纪90年代中期之前中国夏季年最概然温度以相对低温为主,随后呈现波动增温趋势,但自2005年增温趋势有所减缓；冬季年最概然温度在1961-1986年这一时段以相对低温为主,1987年到21世纪初显著变暖,但2000年后增温趋势减缓。总体而言,冬季增温幅度较夏季强,且增温时间早于夏季5-10年。定义1961-1990年、1971-2000年和1981-2008年分别为Ⅰ、Ⅱ、Ⅲ态(下同),不同气候态的研究表明,夏季最概然温度在Ⅲ态增温明显,而冬季在Ⅱ态间增温显著,Ⅲ态增温趋势减弱,尤其值得注意的是,近年来在四川、广东和广西部分地区最概然温度具有下降趋势,是否预示着中国气候态的转型有待深入研究。
(3)基于偏态概率密度函数定义的极端温度事件,分别从频次、强度两个角度研究了不同气候态下日最高温资料中国夏季和冬季极端温度事件的时空变化特征。空间分布上,夏季极端高温的频次、强度在Ⅰ态黄淮、江淮流域显著减小,在Ⅲ态,干旱半干旱以及经济发达的长江沿岸、长江三角洲以及东南沿海地区显著增加；冬季极端高温频次在Ⅱ态中的北方、长江三角洲以及Ⅲ态中的高原、东北东南部、长江三角洲显著降低。冬季极端低温强度整体呈降低趋势,但区域特征不明显。极端温度频次和强度在空间上一致性较好；时间演化上,夏季极端高温频次、强度均在Ⅱ、Ⅲ态显著增加,冬季极端低温频次、强度降低的趋势有所减缓。在当前气候态(Ⅲ态)夏季极端高温在经济发达地区发生比较频繁且极端性在增强；冬季极端低温的发生维持在一个稳定状态且极端性也相对比较稳定。极端温度事件的频次与强度在时间变化趋势上存在较好的一致性。
(4)在Ⅰ、Ⅱ、Ⅲ态共同时段内,后一气候态检测出的极端高温频次均比前一气候态少,极端低温频次均比前一气候态多,这与背景温度随气候态逐渐升高是相一致的；后一气候态检测出的极端高温强度均比前一气候态小,极端低温强度均比前一气候态大。在20世纪70年代末80年代初全球气候系统突变前,极端高温频次具有明显的下降趋势,突变后显著上升；极端低温频次在突变前后变化不明显。极端高温强度突变前表现出轻微的下降趋势,在突变后上升趋势明显；极端低温强度在突变前后大致相当,突变后的整体强度稍低于突变前。极端高温事件的逐渐增强以及极端低温事件的逐渐减少在日最低温资料中体现更明显,这从另一方面表明逐渐增暖主要表现在日最低温中。
(5)夏季高温极值的概率分布规律及变化特征表现为：中国高温极值只在一定的区域呈现高斯分布,大部分台站处于左偏分布型,西南东南部左偏尤为明显；而长江中下游以南地区及东南沿海地区呈较明显的右偏；以偏态指数和最概然高温极值作为研究中国夏季高温极值概率分布特征的关键指标,经验表明最概然极端高温是一个比较稳定的量,可将其作为定义极端高温事件阈值的一种可能方法。
(6)在通过概率理论检测获得一系列天气极值事件的基础上,从事件发生、发展、消亡的角度利用共相同步化原理,将具有一定关联的极值天气事件客观地归属为一个具有实际应用意义上的极端气候事件。共相同步化原理数值检验结果表明,聚类质量评估peff、△peff为K均值聚类分析提供了判别最优聚类数目K的极好依据,而相位概念的引入则将系统所处的不同状态分离开来,相位聚类分析运用于事件过程的检测在理论上是可行的。
(7)共相同步化原理应用于西南干旱事件的干旱指数与降水量距平过程性检测结果表明,西南地区干旱指数MSPI过程性检测出了选择观测站自2009年1月开始由干旱指数表征的干旱程度的变化过程,涉及由旱-湿、湿-旱或者一直干旱抑或一直湿润的几个状态过程的转换情况。有别于气象部门利用干旱指数值大小表征干旱的严重程度,过程性检测不仅仅鉴别出干旱抑或湿润的状态,还鉴别出旱转为湿或者湿润趋于干旱的过程,给过程赋予趋势变化的含义,而转变所处的时间段是状态与状态转变的转折阶段,通常为湿润或者干旱的极值处或者是与前后状态相反的过渡状态。
(8)干旱指数时间过程性检测结果表明,自2009年1月开始西南大部分地区以及开始显示一定程度的气象干旱,干旱一直持续至2010年冬与2010年春,之后干旱严重程度开始缓解。若考虑此次事件的前期产生过程,从干旱指数的角度西南干旱自2009年1月就开始趋于干旱,从时间过程性的角度而言,比从观测资料本身大小界定的事件开始时间要早,这从另一个角度验证了关于过程的定义的意义——包含事件的产生过程,因此将极端事件的产生阶段作为预警阶段不失为一个具有实际意义的可能应用。
降水量距平过程性检测结果与干旱指数检测结果不是一一对应的关系,这是由于降水偏少与干旱响应的时间滞后以及干旱形成原因比较复杂造成的,与降水在干旱形成过程中的重要作用并不矛盾。西南干旱事件过程性的检测为再次认识干旱事件提供一个新的视角,而过程的确定给出了气候背景变化的阶段,为干旱事件的气候背景分析提供时间阶段节点。
Extreme climate events are of small probability and were given definitely definition in AR4according to probability. So it has rather theoretical significance to define extreme climate events from the point of probability. Because Box-Cox transformation can improve data normality and the data by Box-Cox transformation are normal, the skewed probability function is derived, which provides theory basis to define extreme events based on probability. According to the skewed probability function, most probable temperature (MPT) is defined and it has definite physics meaning and can reflect the changing trends of background temperature in different regions over China. Extreme temperature events are defined in terms of skewed function and the temporal-spatial distribution characteristics and time evolution laws of frequencies and strength of them are found, which provide fact foundations to try to answer the question whether extreme events are becoming more and more frequent and extremity. Basing on a series of detected extremum events, the processes of extreme events can be detected by phase synchronization. A new method to detect process of extreme events objectively is raised and it is applied in drought events from2009over Southwest China trying to supply a new angle of view to know the drought events. The following are the major conclusions about above all research:
(1) Compared to normal distribution, the skewed probability function can fit temperature distribution better. The values of Box-Cox transformation index λ reflect the skewed degree of distribution.λ=1is a standard of reference, more big of Box-Cox transformation index, more right skewed of the distribution; more small of index, more left skewed. The changes of index also reflect indirectly the temperature changing trends.
(2) MPT defined by skewed probability function has a definite signification and represent the background temperature fields of some region. MPT interannual variations show that in summer MPT was relative low-temperature-major before the mid-1990s and from then was warming with fluctuation but since2005the trend slowed down and that in winter MPT was relative low-temperature-major1961-1986and from1987to the beginning of the21st century was warming obviously, but since2000the warming trend slowed down. The warming amplitude of winter was stronger than of summer and the time of beginning warming of winter was earlier than of summer about5-10years. Studying three climate state MPT changes of1961-1990、1971-2000.1981-2008found that in summer MPT got warmer obviously in the third climate state while in winter in the second state. MPT' warming trend was slowing down in the third state. It's worthy of note that in Sichuan, Guangdong and Guangxi MPT even began to decline in the last few years. Whether it means climatic transformation needs further research.
(3) Extreme temperature events are defined according to the skewed function. The temporal-spatial distribution characteristics of frequencies and strength of extreme temperature events over China in different climate sates against the backdrop of MPT (Most Probable Temperature) are analyzed. Spatially, frequencies and strength of Extreme high temperature in summer decreased significantly in the Yangtze-Huaihe river valley and Yellow River and Huaihe River valley in State Ⅰ and increased significantly in arid-semiarid region and developed Yangtze River delta in State Ⅲ. Frequencies of Extreme low temperature in winter reduced remarkably in the north and Yangtze River delta in State Ⅱ and in The Qinghai-Tibet Plateau, the southeast of northeast China, Yangtze River delta in State Ⅲ. The strength of extreme low temperature in winter reduced wholly and provincial characteristics were not obvious. The frequencies and strength of extreme temperature events were agreed in spatial. Temporally, frequencies and strength of extreme high temperature in summer increased obviously both in State Ⅱ and State Ⅲ. Frequencies and strength of extreme low temperature in winter reduced obviously in State Ⅱ and the reducing trend was slowing down in State Ⅲ. Extreme high temperature in summer occurred frequently and extreme low temperature in winter remained stably. Extremity of extreme high temperature in summer was more stronger while in winter was stable relatively. The frequencies and strength of extreme temperature events were agreed in temporal.
(4) During the common time period of State Ⅰ, Ⅱ,Ⅲ, the frequencies of extreme high temperature events in the last state were always fewer than the former while the low temperature events were more, which is agreed with the fact that the background temperature steps up with the states; the strength of extreme high temperature events in the latter state was less than the former while of extreme low temperature events was stronger. For the abrupt change of climate at the end of1970s and the beginning of1980s, the frequencies of extreme high temperature events decreased before the change and increased obviously after the change while the ones of extreme low temperature did not change significantly for the change; the strength of extreme high temperature events decreased slightly before the change and increased obviously after the change while the one of extreme low temperature did not change significantly for the change but the whole strength after the change was slightly lower than the one before the change.
(5) The distribution probability of extreme high temperature in summer is mainly left skewed in most regions in China especially in southeast of Southwest while in south of the middle and lower reaches of Changjiang River and China's South-East coastal areas are obviously right skewed. The skewed index and the most probable high extreme temperature are regarded as the key marks about the distribution. The most probable high extreme temperature is rather stable and can be defined as the threshold of extreme temperature.
(6) Basing on a series of detected extremum events, the processes of extreme events are detected by phase synchronization. Numerical modeling of phase synchronization showed that clustering measure Peff and the differences△peff can give the criterion about the proper number of clusters and phases can distinguish different stats of the system. So phase clustering applied to detect processes of extreme climate events is doable.
(7) Drought index MSPI and precipitation anomaly of Southwest drought events in China are used to detect processed by phase synchronization. Drought index from2009presenting different degrees of drought is detected several states, including drought-wetness, wetness-drought, persistent drought or wetness. Processes detection can tell not only persistent drought and wetness state but also the changing state, i.e., from wetness to drought or from drought to wetness, which is different from drought index that can only reflect drought degree according to the values. So process here means changing state as well as stable state. The period of changing state is usually extreme value of drought or wetness or changing period between wetness and drought.
(8) As far as drought index is concerned, drought process began from January2009and persisted to winter and spring in2010. From then, drought began to relive. Considering previous generating process, southwest drought events began from January2009, which is earlier than the result from drought index values. This interprets the meaning about process-including generating process.
The results of precipitation anomaly are not one-to-one correspondence, which was caused by time response lagging of drought to less precipitation and complexity of drought formation cause. This does not contradict the fact that precipitation plays an important role in the formation of drought. The processes detection of southwest drought events provide a new angle of view on the drought events and the processes give the stage of climatic background changing, which provides critical period of climatic background changing about drought events.
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