近50a江淮梅雨期暴雨的区域特征

利用江淮地区44个站1954—2003年近50 a逐日降水资料,采用模糊聚类和经验正交函数分解(EOF)方法分析了江淮梅雨期暴雨的时空变化特征。结果表明:梅雨期暴雨量存在显著的区域差异,可以分为南、北两个区;梅雨期暴雨量具有显著的候际、月际、年际和年代际变化特征,南区暴雨量峰值出现在6月第5候,北区峰值出现在6月第5候和7月第1候;南区暴雨贡献率大于北区,而北区暴雨集中率大于南区;南区暴雨量长期变化呈显著的上升趋势,而北区变化不明显;南北两区暴雨量均存在不同时间尺度的振荡周期。

近116年江淮梅雨异常及其环流特征分析

利用江淮地区1885—2000年近116a梅雨特征量资料和NCEP/NCAR逐日再分析资料,采用谐波分析、最大熵谱分析、小波分析、合成分析等方法讨论了江淮梅雨特征量的年际-年代际变化特征及梅雨异常的环流特征。结果表明:江淮梅雨特征量存在显著的年际和年代际变化特征。入梅日期、出梅日期、梅雨期长度呈显著上升的长期变化趋势,梅雨量和梅雨强度长期趋势变化不明显;梅雨特征量均存在多时间尺度的振荡周期,入梅日期具有准24a、准5a和准3a的显著周期;出梅日期具有准35a、准22a和准5a的显著周期;梅雨量具有准40a、准15a、准9a和准3a的显著周期。丰梅年南亚高压中心强度和西太平洋副热带高压增强。枯梅年则反之。

江淮梅雨异常的大气环流特征

江淮梅雨是我国夏季风雨带向北推进期中的一个重要阶段。利用江苏省气象局提供的江淮地区1954-2001年人梅日期、冉梅日期和梅雨量资料，详细讨论了江淮梅雨丰、枯梅年同期大气环流的差异。结果表明：丰梅年高层100hPa南亚高压呈纬向分布，高压强度增强。中层500hPa极涡强度增强，乌拉尔山高压脊强度增强，鄂霍茨克海阻塞高压强度增强，蒙古高压增强，东亚大槽位置较常年偏东偏南，120°E副热带高压脊线位于20°～25°N之间。低层850hPa南半球越赤道气流抵达北半球后向北偏西方向伸展，与来自阿拉伯海、盂加拉湾的西南气流和副热带高压西南侧的东南气流在南海北部汇合，在我国江淮流域形成一条准东西向的强风速辐合带，一直延伸到国际日界线附近。丰梅年低层辐合增强，高层辐散增强，高低层抽吸作用增强，垂直运动增强，对流旺盛，有利于梅雨的异常偏多；枯梅年则反之。

近50a江淮梅雨的区域特征

利用江淮地区44个站1954—2003年50a逐日降水资料,采用模糊聚类、经验正交函数分解(EOF)、谐波分析和小波分析等方法分析了江淮梅雨期梅雨量的时空变化特征。结果表明:江淮地区梅雨量的空间分布存在显著不同的区域差异,可以分为南、北两个区。梅雨量具有显著的年际和年代际变化特征,南区候平均雨量峰值出现在6月第5候,北区峰值出现在7月第1候,副高脊线的两次北跳分别与江淮梅雨的平均入梅日期(6月第4候)和平均出梅日期(7月第2候)密切有关;南区梅雨量长期变化呈显著的上升趋势,而北区变化不明显;南北两区梅雨量具有显著不同的年际和年代际方差构成。南北两区梅雨量均存在多时间尺度的振荡周期。副热带高压和季风环流的异常直接影响到江淮梅雨期梅雨量的丰枯。

江淮梅雨丰、枯梅年水汽输送差异特征

利用江淮流域1954—2001年梅雨量资料和美国NCEP/NCAR 1954—2001年逐日高度场、风场、比湿场和地面气压场资料,网格距2.5°×2.5°,采用模糊聚类、合成分析等方法,详细讨论了江淮梅雨丰、枯梅年垂直积分的整层纬向、经向和水汽通量输送差异特征。结果表明:区域梅雨量指数能很好地揭示出江淮流域梅雨量的丰枯;丰梅年西太平洋副高南侧的偏南气流和其北侧的偏北气流水汽输送显著增强,越赤道气流抵达北半球后,集中在10°N附近,40～130°E范围内的阿拉伯海和孟加拉湾向北偏东方向伸展,与来自南海和西太平洋的水汽输送相汇合,在我国的江淮流域-日本列岛南部形成一条水汽通量距平≥55 kg/(m.s)的强水汽输送带;丰梅年水汽通量散度距平表明:整层水汽通量辐合比枯梅年明显加强,为江淮梅雨提供了充沛的水汽来源,有利于江淮梅雨的异常偏多;枯梅年则反之。

青藏高原大气热源与江淮梅雨异常的关系

利用江淮流域1954—2001年梅雨量资料和同期内美国NCEP/NCAR逐日高度场、风场、比湿场和地面气压场再分析资料,网格距为2.5°×2.5°。采用模糊聚类、EOF分解、合成分析、SVD分解等方法,详细讨论了青藏高原大气热源与江淮梅雨的关系。结果表明:梅雨量区域指数能很好地揭示江淮流域梅雨量的丰枯,高原大气热源大致以90°E为界,可分为高原东部型和西部型;高原大气热源与梅雨量存在显著相关关系,高原大气热源东部型与江淮梅雨量呈显著正相关关系,西部型与梅雨量呈显著负相关关系。说明高原大气热源东部型增强,西部型减弱,江淮梅雨量异常偏多;高原大气热源东部型减弱,西部型增强,江淮梅雨量异常偏少;反之亦然。SVD分解结果与合成分析的结果完全一致。

江淮梅雨的时空变化特征

利用江淮地区37站1954—2001年48 a梅雨特征量资料,采用谐波分析、EOF和最大熵谱分析等方法讨论了江淮梅雨的时空变化特征。结果表明:江淮梅雨时空分布不均,梅雨特征量存在显著的年际—年代际变化特征,梅雨特征量年代际变化之间存在明显的负相关或正相关关系;梅雨特征量存在显著不同的多时间尺度振荡周期和长期演变趋势且江淮地区雨季也呈不同的年际和年代际变化特征。

江淮梅雨特征及其与北太平洋海温的SVD分析

利用江淮地区1954～2001年48年梅雨量资料,采用谐波分析、EOF、合成分析和SVD分解等方法讨论了江淮梅雨的时空变化特征以及与北太平洋海温的关系。结果表明:江淮梅雨量时空分布不均,存在显著的年际和年代际变化特征。影响江淮梅雨的海温关键区是北太平洋西风飘流区,关键影响时段是当年的1～3月;当年1～3月北太平洋西风飘流区海温异常偏高,同年江淮大部地区梅雨量异常偏多,反之亦然。SVD分解结果与合成分析的结果相吻合,通过0.05的Monte-Carlo显著性检验。

江淮梅雨与冬季西太平洋海温的SVD分析

利用江淮流域1954—2001年48年梅雨量资料和美国NCEP/NCAR1953—2001全球逐月海温再分析格点资料,网格距为2°×2°,采用EOF、合成分析和SVD分解等方法讨论了江淮梅雨与西太平洋海温的关系。结果表明:影响江淮梅雨的海温关键区是西太平洋暖池区,关键影响时段是前1年的12月至当年的2月(以下简称冬季);当年冬季西太平洋暖池区海温异常偏高,同年江淮大部地区梅雨量异常偏多,反之亦然。SVD分解结果与合成分析的结果相吻合,通过信度0.05的Monte-Carlo显著性检验。

长江中下游梅雨与北太平洋大气热源诊断分析

利用长江中下游1954—2001年梅雨量资料和NCEP/NCAR 1954—2001年逐日高度场、风场、比湿场和地面气压场资料,采用EOF分解、合成分析、SVD分解等方法,详细讨论了北太平洋大气热源与长江中下游梅雨的关系。结果表明:西北太平洋大气热源与长江中下游梅雨量存在显著负相关,东太平洋大气热源与长江中下游梅雨量存在显著正相关,通过信度为95%的Monte-Carlo检验,具体表现为当菲律宾群岛附近洋面、西太平洋暖池区及西北太平洋西风飘流区大气热源异常增加(减少)时,赤道中东太平洋大气热源异常偏低(偏高),会造成长江中下游梅雨异常偏少(偏多),反之亦然,合成分析、点相关分析和SVD的分析结果完全一致。

西南地区夏季降水变化与青藏高原大气热源的关系

为进一步研究青藏高原大气热源对西南地区夏季降水的影响,用NCEP/NCAR1961~2022年的月平均再分析资料,网格距2.5˚ × 2.5˚、采用点相关分析、SVD分解、合成分析法及热源计算倒算法对西南地区62年夏季降水的时空分布特征及其与青藏高原大气热源的关系进行了详细研究,结果表明:1) 62年来,整个西南地区的夏季降水有减小的趋势,且西南地区的夏季降水存在三个高值区,高值区分别位于云南的南部地区、四川东部地区和贵州东南部地区,并且在降水高值区附近降水量的梯度也更大。降水量自东向西,自南向北逐渐减少,可以明显看出海拔较高的地区降水量较少。这与西南季风、复杂的地形地貌以及影响西南地区的环流系统等因素有关。2) 在青藏高原在1961~2022年均为大气热源,可以看出大气热源在1961年开始时较弱,随着时间逐渐增强,在70年代中期和80年代末期分别达到强度的最大值,之后大气热源逐渐减弱呈下降趋势,在2020年达到最低值。总体来看,从1961到2022年,青藏高原的大气热源强度呈现由强到弱的变化趋势,且存在一定的年际变化特征。3) 青藏高原地区(26˚00'~39˚47'N,73˚19'~104˚47'E),除东北部的少部分地区为较强冷源外和北部地区为较弱冷源之外,其余大部分地区全年平均均为大气热源,中部地区为较强的大气热源。4) 在青藏高原范围内,与西南地区夏季降水存在显著正相关的地区是高原东部地区的大气热源和高原西部地区大气热源,与西南地区夏季降水存在显著负相关的地区是高原北部地区。总体来说西南地区夏季降水与青藏高原大气热源存在显著的相关性且西南地区夏季降水与青藏高原大气热源具有较高的年际线性相关性。5) 青藏高原大气热源的异常增加会影响西南地区夏季降水的不均变化,部分地区夏季降水量异常增多且存在大值区,部分地区夏季降水量异常减少且存在大值区;而青藏高原大气热源的异常减小时,西南地区夏季降水的增加较均匀。

西南雨季降水变化的区域特征

为了更好地对西南雨季降水的时空变化特征进行研究,利用中国西南地区1960~2022年81个气象站点共63年的逐日降水量气象观测资料,通过旋转经验正交函数分解(REOF)、Mann-Kendall突变检验和Morlet小波分析等研究方法,揭示西南地区降水的时空分布特征、长期变化趋势以及周期变化特征。分析结果表明:1) 西南地区1960~2022年来主要有3个降水大值区,分别为云南南部、贵州西南部以及四川中东部地区,降水量分布自东、南向西、北逐渐递减。2) 在EOF分析的基础上进行REOF分解,将西南地区分为5个区:1区为云南区,2区为川西高原区,3区为川中区,4区为贵州区,5区为川东区。3) 5个区域的雨季降水除2区呈现缓慢上升趋势外,其余区域均呈现程度不同的下降趋势,5个区域的雨季降水突变主要集中在21世纪初期,且突变后呈现不同的变化趋势。变化周期主要以5~10a、准5a周期为主。In order to better study the spatio-temporal variation characteristics of rainy season precipitation in Southwest China, the day-by-day precipitation meteorological observations of 81 meteorological stations in Southwest China for a total of 63 years from 1960 to 2022 are utilized to reveal the spatio-temporal precipitation in Southwest China through the Rotated Empirical Orthogonal Function Decomposition (REOF), the Mann-Kendall Mutation Test, and the Morlet wavelet analysis and other research methods to reveal the spatial and temporal distribution characteristics of precipitation, long-term trends and cycle change characteristics in Southwest China. The analysis results show that: 1) there are three major precipitation areas in Southwest China from 1960 to 2022, namely, southern Yunnan, southwestern Guizhou, and east-central Sichuan, and the distribution of precipitation gradually decreases from east and south to west and north. 2) REOF decomposition is carried out on the basis of EOF analysis, and the southwest region is divided into 5 zones: zone 1 is Yunnan, zone 2 is the western Sichuan plateau zone, zone 3 is the central Sichuan zone, zone 4 is the Guizhou zone, and zone 5 is the eastern Sichuan zone. 3) The rainy season precipitation in the five regions shows a decreasing trend in varying degrees, except for region 2, which shows a slowly increasing trend. The sudden changes in rainy season precipitation in the five regions are mainly concentrated at the beginning of the 21st century and show different trends after the sudden changes. The change cycles are mainly 5~10a and quasi 5a cycles.

西南雨季降水变化与海温的关系

为了研究中国西南雨季降水变化和海温的关系,利用西南地区1960~2022年81站共63年的逐日气象观测降水量资料、同期英国哈德莱中心月平均海表温度(SST)资料(格点分辨率为1˚ × 1˚)、欧洲气象资料中心(ERA-interim)的月平均降水再分析资料(格点分辨率为0.25˚ × 0.25˚)。通过相关分析、经验正交函数分解(EOF)和奇异值分解(SVD)等方法,对西南雨季降水变化与全球SST之间的关系进行了研究分析,结果表明:1) 西南地区63年的雨季降水空间分布不均,呈现东多西少,南多北少的态势,同时,其与前冬、春季澳大利亚东北部太平洋,夏、秋季北印度洋和同期5⁓10月份的北印度洋海温呈现显著负相关关系,即关键区海温异常偏暖(冷),西南雨季降水偏少(多)。2) EOF分析表明:在第1模态下,前一年冬季和当年春季关键区海域海温的分布形式多呈现出西高东低的形式,包括了东太平洋冷舌和西太平洋暖池形态,并且在千禧年之前大部分都是海温多为偏冷状态;而千禧年之后关键区海温由偏冷转为偏暖状态。而当年夏秋季和雨季同期关键区海域海温呈现出全区一致偏暖状态,并且在90年代之后海温从偏冷转变为偏暖状态,其第2空间模态为印度洋正偶极子分布形式。3) SVD分解表明:关键区海温与川西高原地区雨季降水存在正相关关系,而与川东、黔南和云南呈现出一个显著的负相关性,不同季节的海温关键区影响的降水大值区域可能略有不同,但总体来说,当关键区海温异常偏高(低),川西高原的雨季降水异常偏多(少),而其余大部分地区降水异常偏少(多);其分解结果与相关系数的分析结果基本一致并且近年来西南地区的雨季降水呈现出逐年减少的态势。In order to study the relationship between precipitation change and sea surface temperature in the rainy season in southwest China, the daily meteorological observations of 81 stations in Southwest China from 1960 to 2022 for a total of 63 years were used measured precipitation data, the monthly mean sea surface temperature (SST) data of the Hadley Center in the United Kingdom (grid resolution of 1˚ × 1˚) and the monthly mean precipitation reanalysis data of the European Meteorological Data Center (ERA-interim) (grid resolution of 0.25˚ × 0.25˚). The relationship between precipitation change in the rainy season in southwest China and global SST was analyzed by correlation analysis, empirical orthogonal function decomposition (EOF) and singular value decomposition (SVD). The results shows: 1) The spatial distribution of rainy season precipitation in southwest China in 63 years was uneven, showing a trend of more precipitation in the east and less in the west, and more in the south and less in the north, and at the same time, it was significantly negatively correlated with the sea surface temperature in the Pacific Ocean in northeast Australia in the early winter and spring, the northern Indian Ocean in summer and autumn, and the northern Indian Ocean in May and October in the same period, that is, the SST in the key areas was abnormally warm (cold), and the precipitation in the southwest rainy season was less (more). 2) EOF analysis shows that in the first mode, the distribution of sea surface temperature in the key areas in the winter and spring of the previous year mostly shows the form of high in the west and low in the east, including the cold tongue of the eastern Pacific and the warm pool of the western Pacific, and most of the SST is in a cold state before the millennium. After the turn of the millennium, the sea surface temperature in key areas changed from cold to warm. However, the SST in the key areas of the key area in the same period of summer, autumn and rainy season showed a uniform warming state in the whole region, and after the 90s, the SST changed from cold to warm, and the second spatial mode was the normal dipole distribution of the Indian Ocean. 3) SVD decomposition showed that the sea surface temperature in the key area and the rainy season in the western Sichuan Plateau. There is a positive correlation with precipitation, and there is a significant negative correlation with eastern Sichuan, southern Guizhou and Yunnan, and the influence of key areas of SST in different seasons is positive. The precipitation area may be slightly different, but in general, when the sea surface temperature in the key area is abnormally high (low), the rainy season precipitation in the western Sichuan Plateau is abnormally biased more (less), while most of the rest of the precipitation is abnormally low (more). The decomposition results are basically consistent with the analysis results of the correlation coefficient and in recent years. The rainy season precipitation in southwest China shows a decreasing trend year by year.

西南雨季降水异常水汽输送变化特征

为了研究西南地区存在的异常水汽输送的变化特征,利用西南地区81个气象台站点1960~2022年共63年的逐日气象降水量观测资料和同期ERA5逐月再分析资料,数据的网格分辨率0.25˚ × 0.25˚,通过天气学诊断分析、径向基函数插值算法、t检验法和显著性检验等方法,对西南地区的雨季异常水汽输送特征进行了详细研究,其研究结论表明:1) 西南地区雨季降水量自1960年起呈现显著下降趋势,具有约11年的周期性变化周期内分布并不均匀,多为上升慢,跌落快。当前正处于新周期的起始阶段,预计将经历一个缓慢的上升期。2) 每30划分一个年际为统计口径,越靠近当下的年际的雨季降水量越低,水汽输送也越弱,代表水汽输送的水汽通量散度和垂直积分都会越低,垂直积分的下降趋势略弱于散度。3) 西南地区还存在一个异常区域位于103˚E~106˚E区域,该区域内站点之间存在水汽输送的共通性,水汽输送和异常降水都与整体相反,拥有相对独立水汽输送通道,根据四轮30年际统计发现异常带将逐渐扩大,空间上沿向外扩散,伴随整体周期性的上升,除异常带外的其他地区将经历水汽输送和雨季降水的增长,而异常带地区将呈现与整体趋势相反的异常低值。To investigate the characteristics of anomalous water vapor transport in Southwest China, we utilized daily precipitation observations from 81 meteorological stations in Southwest China spanning 63 years (1960~2022) and monthly ERA5 reanalysis data with a grid resolution of 0.25˚ × 0.25˚. Through synoptic diagnostic analysis, radial basis function interpolation, t-test, and significance testing, we conducted a detailed study on the characteristics of anomalous moisture transport during the rainy season in Southwest China. The study concluded that: 1) Since 1960, the rainy season precipitation in Southwest China has shown a significant downward trend, characterized by an approximately 11-year periodic cycle. Within this cycle, the distribution is uneven, with a slow rise and a rapid fall. Currently, it is at the beginning of a new cycle, expected to experience a slow upward trend. 2) When dividing into 30-year intervals for statistical purposes, the closer to the present, the lower the rainy season precipitation and the weaker the moisture transport. This is reflected in lower moisture flux divergence and vertically integrated moisture transport, with the decline in vertical integration being slightly less pronounced than that in divergence. 3) An anomalous region exists between 103˚E and 106˚E, where the meteorological stations exhibit commonality in moisture transport. Both moisture transport and anomalous precipitation in this region are contrary to the overall trend, indicating a relatively independent moisture transport channel. Statistical analysis over four 30-year intervals reveals that this anomalous belt is gradually expanding spatially, with the anomaly spreading outward. As the overall periodic rise continues, regions outside the anomalous belt will experience growth in moisture transport and rainy season precipitation, while the anomalous belt will exhibit anomalously low values opposite to the general trend.

西南雨季降水不同年代水汽输送对比分析

为了研究西南地区雨季降水不同年代水汽输送的对比,选取了云南和四川的全部地区,以及贵州和重庆的部分地区共81个气象台站资料,从1960年伊始,到2022年的每年雨季的观测资料,还采用了ERA5从1940年至今的压力水平和单一水平的月平均数据,数据的分辨率是0.25˚ × 0.25˚。凭借天气学诊断分析、multiquadric插值算法、相关系数的显著性检验等方法,对西南地区的雨季不同年代水输送进行了详尽的对比分析,其研究结论表明:1) 西南地区整体水汽输送与全球气候变化紧密相关,水汽输送的基本形势是地形上西北方位弱,正东和正南方位强。拥有的若干传统高值区在近30年来均呈减弱趋势,其中云贵交界减弱最为明显,而传统低值区的水汽输送趋势与整体保持一致。2) 对于传统的高值区,水汽输送情况并不一致。对于传统高值区,近30年来减弱程度从高到低分别为云贵交界,雅安周边,云南南部,雅安周边和以及云南南部还将维持稳定的高值降水。3) 存在一个异常带,约位于104˚E附近,这些区域常与西南地区整体呈相反趋势,拥有独立的水汽输送通道,是异常水汽输送的高发区。异常带有向周围扩散的趋势,表现为沿104˚E线向外扩散,这一异常带更多受到来自孟湾向北方向的水汽输送,并引导产生异常降水,伴随西南整体周期性的水汽输送增强和异常降水增多,104˚E周边地区将易发异常低值。To study the contrast of water transport during the rainy season across different decades in Southwest China, data from 81 meteorological stations in Yunnan and Sichuan provinces, as well as parts of Guizhou and Chongqing, were selected. The observation data span from the rainy seasons of 1960 to 2022, and ERA5 monthly average data from pressure levels and single levels, with a resolution of 0.25˚ × 0.25˚, were used from 1940 to the present. Using synoptic diagnostic analysis, multiquadric interpolation algorithm, and significance tests of correlation coefficients, a detailed comparative analysis of water transport during the rainy seasons in different decades in Southwest China was conducted. The study concluded that: 1) The overall moisture transport in Southwest China is closely related to global climate change, with a basic pattern of weak transport in the northwest and strong transport in the east and south directions due to topography. Traditional high-value areas have shown a weakening trend in the past 30 years, with the Yunnan-Guizhou border weakening the most significantly, while the trend in traditional low-value areas remains consistent with the overall pattern. 2) For traditional high-value areas, the moisture transport situation is not uniform. In the past 30 years, the degree of weakening from highest to lowest is as follows: Yunnan-Guizhou border, around Ya’an, and southern Yunnan. Both around Ya’an and southern Yunnan will maintain stable high-value precipitation. 3) There is an anomalous belt approximately located near 104˚E, where these regions often show a trend opposite to the overall trend in Southwest China, having independent moisture transport channels and being high-incidence areas of anomalous moisture transport. This anomalous belt shows a tendency to spread outward along the 104˚E line, more influenced by moisture transport from the north of the Bay of Bengal, leading to anomalous precipitation. Accompanied by the periodic enhancement of moisture transport and increased anomalous precipitation in Southwest China, the areas around 104˚E are prone to anomalously low values.

西南雨季降水异常大气环流特征

为了研究造成西南雨季降水异常的大气环流特征,利用西南地区81个气象站1960~2022年的逐日气象降水量观测数据和同期NCEP/NCAR逐月再分析数据集,水平分辨率为2.5˚ × 2.5˚,运用合成分析和显著性检验等现代气候统计诊断分析方法对西南地区63年来雨季降水异常的高低层大气环流场、其他物理量场以及水汽输送场进行了研究,结果表明:1) 西南雨季降水空间分布不均,雨季降水三个大值区,分别位于四川省中部雅安、峨眉山和乐山一带,云南南部地区以及云南西部地区,且多雨区和少雨区呈交替分布。西南雨季降水长期变化趋势呈微弱递减的趋势,且存在明显的年际变化特征,总的来说降水偏多年主要集中在70年代以前,偏少年集中在2005年以后,西南地区降水有一定的年代际变化特征。2) 多雨年南亚高压较常年偏弱,南支槽活跃,贝加尔湖高压增强,整体为经向环流,西南地区产生显著的西南风异常,有利于对西南地区的水汽输送,有利于降水。少雨年南亚高压较往年偏强,高压中心偏东,整体为纬向环流,中南半岛西北风异常风场形势不利于孟加拉湾水汽向西南地区的输送,会导致降水偏少。西南雨季的垂直运动具有区域性,多雨年在云南西南部和四川东部垂直运动较强。少雨年在四川东部垂直运动较强。3) 多雨年孟加拉湾中部存在一气旋性距平水汽输送,其南侧有显著的西南向水汽通量输送带,说明孟加拉湾南部对西南地区的水汽输送加强。在两广和湖南一带有反气旋性距平水汽输送,南侧存在东南向水汽通量距平,表明来自南海的水汽向贵州、重庆及四川东部输送加强。西南地区多雨年的水汽通量散度距平从南向北表现为“辐合–辐散–辐合”的空间分布,水汽汇集的大值区位于四川东部和云南的南部。少雨年云南存在气旋性水汽通量距平,印度半岛东部有反气旋性水汽通量距平,前者后部和后者前部的北向水汽通量距平在中南半岛汇合,减弱了孟加拉湾北部对西南地区的输送。从孟加拉湾南部来的西南向水汽通量距平在中南半岛转为自西向东的水汽通量距平,不利于水汽向西南地区输送。少雨年西南地区水汽汇集的主要地带分别位于四川东部、重庆一带和云南的东部和南部。在云南西部和贵州的水汽通量散度距平很小,虽有水汽的汇集和辐散,但造成当地水汽变化不是很明显。多、少雨年的水汽辐合区均在云南中部和南部、四川东部,但多雨年在这两地水汽辐合强度远远大于少雨年。In order to study the characteristics of atmospheric circulation that cause precipitation anomalies in the rainy season in Southwest China, daily meteorological precipitation observation data from 81 meteorological stations in Southwest China during 1960⁓2022 and monthly NCEP/NCAR reanalysis data set of the same period were used, with a horizontal resolution of 2.5˚ × 2.5˚. By using the modern climate statistical diagnostic analysis methods such as synthesis analysis and significance test, the high and low layer atmospheric circulation field, other physical quantity field and water vapor transport field of the rainy season precipitation anomaly in Southwest China in the past 63 years are studied. The results show that: 1) The spatial distribution of rainy season precipitation is uneven in southwest China. The three regions with high rainfall value are located in Ya’an, Mount Emei and Leshan in central Sichuan Province, southern Yunnan and western Yunnan respectively, and the regions with heavy rainfall and low rainfall are alternately distributed. The long-term variation trend of rainy season precipitation in southwest China showed a weak decreasing trend, and there were obvious inter-annual variation characteristics. In general, the precipitation was mainly concentrated before 1970s, and the precipitation was mainly concentrated after 2005. The precipitation in Southwest China had certain inter-decadal variation characteristics. 2) In rainy years, the South Asian high is weaker than the usual, the south branch trough is active, the Baikal high is strengthened, and the overall meridonal circulation, the southwest region produces a significant southwest wind anomaly, which is conducive to water vapor transport to the southwest region and conducive to precipitation. In the year of low rainfall, the South Asian high pressure is stronger than in previous years, the high pressure center is eastward, and the overall zonal circulation is present. The abnormal wind field situation of northwest wind over Indochina Peninsula is not conducive to the transport of water vapor from the Bay of Bengal to the southwest, resulting in less precipitation. The vertical movement of rainy season in southwest China is regional, and the vertical movement is stronger in southwest Yunnan and eastern Sichuan in rainy years. The vertical movement is stronger in the eastern part of Sichuan in the year of low rainfall. 3) There is a cyclonic anomaly water vapor transport in the middle of the Bay of Bengal in rainy years, and there is a significant southwest water vapor flux conveyor belt In the south side, indicating that the water vapor transport from the south of the Bay of Bengal to the southwest is strengthened. There is an anticyclonic anomaly of water vapor transport in Guangxi, Guangdong and Hunan, and a southeastward anomaly of water vapor flux in the south, indicating that water vapor from the South China Sea is transported to Guizhou, Chongqing and eastern Sichuan. The divergence anomaly of water vapor flux in rainy years in southwest China shows the spatial distribution of “convergence-divergence-convergence” from south to north, and the large value area of water vapor convergence is located in eastern Sichuan and southern Yunnan. There are cyclonic water vapor flux anomalies in Yunnan and anticyclonic water vapor flux anomalies in the eastern part of the Indian Peninsula. The northward water vapor flux anomalies in the rear part of the former and the front part of the latter converge, which weakens the transport of water vapor from the northern part of the Bay of Bengal to the southwest. The southwesterly water vapor flux anomaly from the south of the Bay of Bengal turns to the west-east water vapor flux anomaly in Indochina Peninsula, which is not conducive to the transport of water vapor to the southwest. The main areas of water vapor accumulation in southwest China are located in eastern Sichuan, Chongqing and eastern and southern Yunnan respectively. In western Yunnan and Guizhou, the divergence anomaly of water vapor flux is very small, although there is water vapor convergence and divergence, but the local water vapor change is not obvious. The convergence areas of water vapor in both rainy and rainy years are in central and southern Yunnan and eastern Sichuan, but the convergence intensity of water vapor in rainy years is much greater than that in rainy years.

西南地区夏季降水变化与南亚高压的关系

为进一步研究西南地区夏季降水变化与南亚高压的关系,利用1961~2022年6~8月西南地区76个气象观测站的逐日气象观测降水量资料、同期NCEP/NCAR的月平均再分析资料(包括高度场、风场、地面气压场、相对湿度场、比湿场),网格距2.5˚ × 2.5˚,通过合成分析、EOF分解、SVD奇异值分解、南亚高压特征量等方法,详细探讨了西南地区夏季降水变化特征与南亚高压的关系其主要结论如下:(1) 西南地区1961~2022年夏季降水呈负趋势,每10年夏季平均降水量减少4.377 mm,降水量空间分布不均匀,大致为自西北向东南呈增加趋势。(2) 根据EOF分析,前三个模态累计方差贡献率达到了51.6%,能够较好地反映出夏季降水的空间分布类型。第一模态表明西南地区整个地区全年都呈现出多雨(少雨)的趋势。第二模态呈现出正距平区和负距平区交错分布的情况。第三模态呈现出夏季降水从北向南呈“正–负–正”分布类型的情况。(3) 1961~2022年南亚高压特征量不仅存在明显的年际变化,而且也存在明显的年代际变化,除脊线位置外。从1961~2022年,南亚高压的强度在逐渐增强,面积在逐渐增大,东脊点位置逐渐偏西,西脊点位置逐渐偏东,脊线位置逐渐偏南。(4) 从1961~2022年夏季南亚高压各特征参数与西南地区同期降水的点相关分布中可以看出,南亚高压脊线位置、面积指数、强度指数与西南地区同期降水关系最密切。从西南地区夏季降水与同期南亚高压的SVD分解表明:第一模态空间分布型反映了南亚高压偏弱(强)年与西南地区偏旱(涝)年对应关系一般。第二模态空间分布型反映了南亚高压偏弱(强)年与西南地区偏旱(涝)年对应关系较好。

西南雨季降水时空变化特征

为研究西南雨季降水的时空变化特征,利用1960~2022年西南地区81个气象站点的逐日气象降水量观测资料,通过EOF分解、Morlet小波分析和EEMD分析等方法,对西南地区雨季降水量的多尺度变化特征进行了详细研究。结果表明:1) 西南地区63年来雨季降水量空间分布不均匀,大体有由东向西逐渐递减,以及由南向北逐渐递减的变化趋势。川西高原为降水量低值区,雅安、峨眉以及云南南部为降水量高值区。西南地区趋势系数正值区和负值区交错分布,正值区主要在川西高原以及川东和贵州,负值区在云南地区。2) EOF分析表明:西南地区雨季降水量第1模态为全区一致型,大值中心位于云南地区以及四川中南部。西南地区雨季降水量第2模态显示为北负南正型,正值大值中心位于云南地区,负值大值区位于川西和川东。西南地区雨季降水量第3模态显示为东北到西南正负交错的分布类型。西南地区雨季降水量第4模态为西负东正的分布类型。西南地区雨季降水量第5模态显示为东北到西南呈正负交错的分布类型。3) 小波分析表明西南地区雨季降水量主要有3~4年、7~8年、10~14年、15~23年的变化周期;EEMD分解表明西南地区雨季降水量主要有2.66年、5.33年、10年、21.3年的变化周期。由此可知,西南地区主要存在4年、8年和20年左右的周期。In order to study the spatio-temporal variation of rainy season precipitation in Southwest China, the multi-scale variation of rainy season precipitation in Southwest China was studied in detail by means of EOF decomposition, Morlet wavelet analysis and EEMD analysis, based on the daily meteorological precipitation observation data of 81 meteorological stations in Southwest China during 1960~2022. The results show that: 1) The spatial distribution of rainy season precipitation in Southwest China in the past 63 years is uneven, with a gradual decline from east to west and from south to north. The West Sichuan Plateau has a low precipitation value, while Ya’an, E’mei and southern Yunnan have a high precipitation value. The positive and negative regions of the trend coefficient in Southwest China are interleaved, the positive regions are mainly in the west Sichuan Plateau, the east Sichuan and Guizhou, and the negative regions are in Yunnan. 2) The EOF analysis shows that the first mode of precipitation in the rainy season in southwest China is the uniform type in the whole region, and the large value center is located in Yunnan and central and southern Sichuan. The second mode of rainy season precipitation in Southwest China shows that the north is negative and the south is positive. The positive value center is located in Yunnan, and the negative value area is located in west and east Sichuan. The third mode of precipitation in the rainy season in Southwest China shows the distribution type of positive and negative interleaving from northeast to southwest. The fourth mode of precipitation in the rainy season in Southwest China is the distribution type of west negative and east positive. The fifth mode of precipitation of rainy season in Southwest China shows the distribution type of positive and negative from northeast to southwest. 3) Wavelet analysis shows that the rainy season precipitation in Southwest China mainly has a change cycle of 3~4 years, 7~8 years, 10-14 years and 15~23 years. The EEMD decomposition shows that the rainy season precipitation in Southwest China mainly has a change cycle of 2.66 years, 5.33 years, 10 years and 21.3 years. It can be seen that there are cycles of about 4 years, 8 years and 20 years in Southwest China.

基于EEMD的西南雨季降水的多尺度变化特征

利用1960~2022年西南地区81个气象站点共63年的逐日气象降水量观测资料,运用旋转经验正交函数分解(REOF)、Morlet小波分析和集合经验模态分析(EEMD)等方法,对西南地区63年雨季降水量的多尺度变化特征进行了详细研究。结果表明:根据REOF分析表明:第1模态高值区主要在云南地区,低值在川西高原及四川东部;第2模态高值区主要在云南东南部和四川东部,低值区在川西高原;第3模态高值区主要在四川中部及北部,第4模态高值区主要在贵州地区,第5模态高值区主要在四川东部。根据高荷载量以及各种因素可以把西南地区分为5个区域,分别为云南区、川西高原区、川东区、川中区以及贵州区。小波分析表明云南区主要存在准3a、准8a、准23a的降水周期;EEMD分解表明云南区主要有3.2年、6.4年、9.6年、21.3年的周期。小波分析表明川东地区主要存在准7a、准13a、准22a的降水周期;EEMD分解表明川东区主要有3.36年、8年、26.6年的周期。小波分析表明川西高原区主要存在准4a、准8a、准15a、准18a的降水周期;EEMD分解表明川西高原区具有3年、6.4年、8.6年、21.3年的周期。小波分析表明川中区主要有准4a、准6a、准10a、准16a、准27a的降水周期;EEMD分解表明川中区主要有2.78年、7.6年、16年的周期。小波分析表明贵州区主要有准7a、准11a、准15a和准20a的降水周期变化;EEMD分解表明贵州区具有4.15年、10年、20年的周期。由此可知,西南地区主要存在4年、8年和20年左右的周期。Utilizing day-by-day meteorological precipitation observations from 81 meteorological stations in Southwest China for a total of 63 years from 1960 to 2022, the multi-scale variation characteristics of precipitation during the 63-year rainy season in Southwest China were studied in detail by means of Rotation Empirical Orthogonal Function decomposition (REOF), Morlet wavelet analysis and Ensemble Empirical Mode Decomposition analysis (EEMD). The results show that: According to the REOF analysis, the high value of mode 1 is mainly in Yunnan, and the low value is in western Sichuan Plateau and eastern Sichuan. The high value area of mode 2 is mainly in southeast Yunnan and eastern Sichuan, and the low value area is in western Sichuan Plateau. The third mode high value area is mainly in the central and northern part of Sichuan, the fourth mode high value area is mainly in Guizhou, and the fifth mode high value area is mainly in the eastern part of Sichuan. According to the high load capacity and various factors, the southwest region can be divided into five regions, namely Yunnan region, western Sichuan Plateau region, eastern Sichuan region, central Sichuan region and Guizhou region. Wavelet analysis shows that there are mainly quasi-3a, quasi-8a and quasi-23a precipitation cycles in Yunnan. The EEMD decomposition shows that there are 3.2, 6.4, 9.6 and 21.3 years in Yunnan region. Wavelet analysis shows that there are quasi-7a, quasi-13a and quasi-22a precipitation cycles in eastern Sichuan. The EEMD decomposition shows that there are 3.36 years, 8 years and 26.6 years in eastern Sichuan. Wavelet analysis shows that the precipitation periods of quasi-4a, quasi-8a, quasi-15a and quasi-18a mainly exist in the western Sichuan Plateau. The EEMD decomposition shows that the western Sichuan Plateau has a period of 3 years, 6.4 years, 8.6 years and 21.3 years. Wavelet analysis shows that the main precipitation periods in central Sichuan are quasi-4a, quasi-6a, quasi-10a, quasi-16a and quasi-27a. The EEMD decomposition shows that there are 2.78 years, 7.6 years and 16 years in central Sichuan region. The wavelet analysis shows that there are mainly quasi-7a, quasi-11a, quasi-15a and quasi-20a precipitation cycles in Guizhou. The EEMD decomposition shows that the Guizhou region has 4.15-year, 10-year and 20-year cycles. It can be seen that there are cycles of about 4 years, 8 years and 20 years in southwest China.

西南雨季不同年代降水特征对比分析

为了更好地对西南雨季降水的时空变化特征进行研究,利用中国西南地区1960~2022年81个气象站点共63年的逐日降水量气象观测资料,通过经验正交函数分解(EOF)、线性趋势倾向分析和Morlet小波分析等研究方法,揭示西南地区降水的时空分布特征、长期变化趋势以及周期变化特征。分析结果表明:(1) 西南地区1960~2022年的雨季降水量总体呈现下降趋势,其年代际变率为−12.516/10a,降水距平值呈现下降趋势,且降水存在周期性变化。(2) 西南雨季降水量的EOF分析表明:第1模态表明西南地区降水呈全区一致型分布;第2模态呈现南北反位相的分布类型;第3模态降水为由南向北呈现“正–负–正”的分布类型;第4模态降水呈现西北–东南反向的分布类型。(3) 除川西高原地区外,年代降水距平值呈先增后减的趋势,其他区域的年代降水距平值无明显变化规律。西南地区雨季的年代降水距平百分率属于正常变化。In order to better study the spatio-temporal variation characteristics of rainy season precipitation in Southwest China, the day-by-day precipitation meteorological observations from 81 meteorological stations in Southwest China for a total of 63 years from 1960 to 2022 are utilized to reveal the spatio-temporal distribution characteristics of precipitation in Southwest China, the long-term trend by means of the empirical orthogonal function decomposition (EOF), the linear trend tendency analysis and the Morlet wavelet analysis, and the cyclic variation characteristics and cycle change characteristics. The analysis results show that: (1) The rainy season precipitation in Southwest China from 1960 to 2022 shows an overall decreasing trend, and its interdecadal variability is −12.516/10a, the precipitation distance level shows a decreasing trend, and there are cyclic changes in precipitation. (2) The EOF analysis of the rainy season precipitation in Southwest China shows that: mode 1 indicates that the precipitation in Southwest China is uniformly distributed throughout the region;mode 2 shows a north-south antipodal distribution;mode 3 shows a “positive-negative-positive” distribution from the south to the north;and mode 4 shows a northwesterly-southeasterly inverse distribution. (3) Except for the Western Sichuan Plateau area, the distance level of the chronological precipitation shows a tendency of increasing and then decreasing, and there is no obvious pattern of change in the distance level of the chronological precipitation in other areas. The percentage of chronological precipitation distance level in the rainy season in the southwestern region belongs to the normal change.