东北春季极端低温的变化特征及其与大西洋海温的关系

利用1958—2007年全球海温、位势高度场月平均资料和我国东北地区64个测站的春季地面气温资料,分析了我国东北地区春季极端低温的时空变化特征及其与大气环流和海温异常的关系。结果表明：近50a来,我国东北春季极端低温事件频数整体呈减少趋势;极端低温频数主要存在全区一致变化型和南北反相变化型两种模态;极端低温事件频数与北极涛动存在显著负相关关系,同时在极端低温多年,极涡较弱,乌拉尔山阻塞高压偏强,东北冷涡较强,反之亦然;影响我国东北地区春季极端低温的关键海区为中北大西洋海区,极端低温多年,中北大西洋海温较常年偏冷,反之则中北大西洋海温较常年偏暖。这对于预测东北春季极端低温事件的年际变化具有很好的指示意义。数值试验结果表明,中北大西洋海温异常可激发欧亚波列,致使中国东北温度异常。     

四川盆地短历时强降水极值分布的研究

运用广义帕雷托分布(GPD)和广义极值分布(GEV),借助于L-矩的参数估计方法,对四川盆地12站的小时极端降水量进行拟合,并对两种模型的拟合效果进行比较。运用Hill图,结合统计量D*来确定GPD的最佳门限值是合适的,选出的样本是独立的。各站的小时极端降水概率分布均符合GPD和GEV,但GPD模型的拟合精度要优于GEV模型。利用两种模型推算出各站给定重现期的最大小时降水量,其中泸州50 a一遇和100 a一遇的降水极值分位数都超过了100 mm,除了遂宁站外,两种模型估计出的极值分位数的相对误差基本都在10%以下。通过分析,GPD推算的结果更加可靠。     

中国地区极端事件预估研究

简要介绍了极端气候事件预估的基本方法,概述了东亚和中国地区关于气候和极端气候事件预估研究的进展。针对极端事件变化预估研究中的重要问题,如高分辨率、长时间尺度的区域气候变化模拟和预估,高时空分辨率的网格化观测资料,除温室效应外的土地利用和气溶胶的作用,使用合理方法进行多模式结果的集合,以及统计降尺度方法的应用等,进行了讨论。     

近32年长沙市短时强降水的气候变化研究

利用长沙市近32 a的1 h、3 h雨量资料,分析了长沙短时强降水年发生次数、月际分布、时段分布、极值分布等气候特征及1 h、3 h雨量极值趋势分析、突变检验。结果表明,长沙市1 h、3 h短时强降水年发生次数的多年平均值为4.4、3.7次,雨强平均为29.2 mm/h、14.8 mm/h。长沙发生1 h短时强降水高峰期为6-8月,3 h短时强降水高峰期为6-7月。1 h短时强降水容易发生在15-17时及20时等时段,3 h短时强降水容易发生在04-08时及01时等时段。1 h、3 h短时强降水年雨量极值大多出现在主汛期。年1 h雨量极值发生在7月最多,6、8月次之;年3h雨量极值发生在6月最多,7月次之。长沙市1 h、3 h短时强降水年雨量极值整体呈弱增加趋势,其长期趋势变化存在明显年代际变化特征和阶段性特征,无突变现象。     

Relationship between the Late Spring NAO and Summer Extreme Precipitation Frequency in the Middle and Lower Reaches of the Yangtze River

The relationship between the late spring North Atlantic Oscillation (NAO) and the summer extreme precipitation frequency (EPF) in the middle and lower reaches of the Yangtze River Valley (MLYRV) is examined using an NECP/NCAR reanalysis dataset and daily precipitation data from 74 stations in the MLYRV. The results show a significant negative correlation between the May NAO index and the EPF over the MLYRV in the subsequent summer. In positive EPF index years, the East Asian westerly jet shifts farther southward, and two blocking high positive anomalies appear over the Sea of Okhotsk and the Ural Mountains. These anomalies are favorable to the cold air from the mid-high latitudes invading the Yangtze River Valley (YRV). The moisture convergence and the ascending motion dominate the MLYRV. The above patterns are reversed in negative EPF index years. A wave train pattern that originates from the North Atlantic extends eastward to the Mediterranean and then moves to the Tibetan Plateau and from there to the YRV, which is an important link in the May NAO and the summer extreme precipitation in the MLYRV. The wave train may be aroused by the tripole pattern of the SST, which can explain why the May NAO affects the summer EPF in the MLYRV.     

强台风“黑格比”实测海上风电机组极端风况特征参数分析和讨论

利用广东近海海上一座100 m高气象塔上设置的三维超声测风仪获取的强台风“黑格比”过程实测数据，分析研究海上风电机组在强台风影响下极端载荷参数的变化特征，通过仪器直接测量的参数与IEC 61400-1规范(由国际电工委员会制定)推荐方法计算结果的对比，研究该规范推荐的风电机组极端载荷参数计算方法在台风条件下的适用性。研究结果表明：(1) 强台风“黑格比”在近海海面上产生的极端操作阵风风速和极端风向变幅的过程变化均呈“M”型双峰分布，最大值均出现在台风眼壁强风区；(2) 由仪器直接测量的极端操作阵风风速和极端风向变幅值与根据IEC公式计算结果差别明显；(3) 台风强风影响产生的极端操作阵风和极端风向变幅参数均出现超越IEC给出的三种标准类型风电机组的设计上限标准；并且IEC公式计算值比仪器直接测量值显著偏大；(4) 在风电机组处于满发、切出和停机生存等工况下，IEC公式计算和仪器直接测量的极端操作阵风基本一致，但IEC公式对极端风向变幅的计算值要比仪器直接测量值大。与IEC的风电机组设计标准相比，仪器直接测量的极端操作阵风在时间周期1～3.5 s和7～10 s区间超出标准，但极端风向变幅一般不会突破IEC的风电机组设计标准。     

Toward Understanding the Extreme Floods over Yangtze River Valley in June?July 2020: Role of Tropical Oceans※

The extreme floods in the Middle/Lower Yangtze River Valley (MLYRV) during June?July 2020 caused more than 170 billion Chinese Yuan direct economic losses. Here, we examine the key features related to this extreme event and explore relative contributions of SST anomalies in different tropical oceans. Our results reveal that the extreme floods over the MLYRV were tightly related to a strong anomalous anticyclone persisting over the western North Pacific, which brought tropical warm moisture northward that converged over the MLYRV. In addition, despite the absence of a strong El Ni?o in 2019/2020 winter, the mean SST anomaly in the tropical Indian Ocean during June?July 2020 reached its highest value over the last 40 years, and 43％ (57％) of it is attributed to the multi-decadal warming trend (interannual variability). Based on the NUIST CFS1.0 model that successfully predicted the wet conditions over the MLYRV in summer 2020 initiated from 1 March 2020 (albeit the magnitude of the predicted precipitation was only about one-seventh of the observed), sensitivity experiment results suggest that the warm SST condition in the Indian Ocean played a dominant role in generating the extreme floods, compared to the contributions of SST anomalies in the Maritime Continent, central and eastern equatorial Pacific, and North Atlantic. Furthermore, both the multi-decadal warming trend and the interannual variability of the Indian Ocean SSTs had positive impacts on the extreme floods. Our results imply that the strong multi-decadal warming trend in the Indian Ocean needs to be taken into consideration for the prediction/projection of summer extreme floods over the MLYRV in the future.     

中国20年一遇气温和降水极值变化的高分辨率模拟

基于25 km高分辨率区域气候模式（RegCM3）嵌套MIROC3.2_hires全球气候模式结果,进行IPCC SRES A1B情景下21世纪气候变化的模拟,分析中国区域未来气温和降水极值重现期的变化。首先检验模式对当代（1981-2000年）极端事件重现期的模拟能力,结果表明,模式能够较好地再现中国地区20年一遇极端事件的基本分布型,但所模拟的数值与观测相比还有一定偏差,特别是在极端降水方面。21世纪中期（2041-2060年）和末期（2081-2100年）20年一遇的高温极值在整个区域内均将升高,东北地区增幅最大;低温极值将增大,中心位于内蒙古、新疆及青藏高原南麓;降水极值也将普遍增大。气温和降水极值在21世纪末期的增加幅度均比中期要大。在未来全球变暖背景下,中国地区极端高温事件将明显增多,面积增大;极端低温事件将大幅度减少,面积减少;强降水事件也将增多,面积不断扩大。     

2008年：气候持续变暖，极端事件频发

 2008年可能是自1850年开始有器测记录以来全球第10个最暖的年份,全球海面和陆面综合气温比1961-1990年的年平均高0.31℃,150 a来最热的10个年份都集中在最近12 a里,全球气候变暖的趋势仍在持续。北极的海冰面积在融化期降至自1979年卫星测量以来的第2个最低点;同时,2008年极端天气气候事件频发,世界许多地方出现了洪灾、持续性严重干旱、冰雪风暴、热浪和寒潮等;拉尼娜现象在2月份呈峰值状态,以后逐渐减弱至近中性状态;南极臭氧洞进一步增大。     

The 2020 Summer Floods and 2020/21 Winter Extreme Cold Surges in China and the 2020 Typhoon Season in the Western North Pacific

China experienced significant flooding in the summer of 2020 and multiple extreme cold surges during the winter of 2020/21. Additionally, the 2020 typhoon season had below average activity with especially quiet activity during the first half of the season in the western North Pacific(WNP). Sea surface temperature changes in the Pacific, Indian, and Atlantic Oceans all contributed to the heavy rainfall in China, but the Atlantic and Indian Oceans seem to have played dominant roles. Enhancement and movement of the Siberian High caused a wavier pattern in the jet stream that allowed cold polar air to reach southward, inducing cold surges in China. Large vertical wind shear and low humidity in the WNP were responsible for fewer typhoons in the first half of the typhoon season. Although it is known that global warming can increase the frequency of extreme weather and climate events, its influences on individual events still need to be quantified.Additionally, the extreme cold surge during 16–18 February 2021 in the United States shares similar mechanisms with the winter 2020/21 extreme cold surges in China.