Influence of the pace of El Niño decay on tropical cyclone frequency over the western north pacific during decaying El Niño summers

This study investigated the distinct responses of western North Pacific (WNP) tropical cyclone (TC) activity during different decaying El Niño summers. The El Niño events were classified into two types according to the periodicity of the ENSO cycle, with positive SST anomalies in the equatorial central-eastern Pacific maintaining positive values into the following summer as the slow decaying (SD) cases, but transforming to negative values in the following summer as the rapid decaying (RD) cases. Compared with that in SD El Niño summers, the TC occurrence frequency over the WNP is significantly lower in RD El Niño summers, led by a much weaker WNP monsoon trough with more unfavorable environmental factors for TC genesis and development. Further examination showed that the apparent warming over the tropical Indian Ocean basin and cooling over the equatorial central-eastern Pacific contribute together to an enhanced lower-tropospheric anticyclone through modulation of the descending branch of the large-scale Walker circulation over the WNP, which may play a crucial role in suppressing the TC activity during the decaying summer of RD El Niño cases. In contrast, the warming equatorial central-eastern Pacific and remote western Indian Ocean induce a weakening WNP anticyclone and less suppressed deep convection during the decaying summer of SD El Niño cases. Thus, the different evolution of SST anomalies associated with different paces of El Niño decay results in the linkage between the preceding winter El Niño and the decreased WNP TC frequency in summer being more (less) robust for RD (SD) El Niño cases.摘要本文分析了El Niño事件衰减速度的差异对衰退年夏季西北太平洋热带气旋 (tropical cyclone, TC) 频数的不同影响. 按照El Niño事件衰减速度不同, 将其划分为迅速衰减 (rapid decaying, RD) 和缓慢衰减 (slow decaying, SD) 的El Niño事件. SD (RD) El Niño事件的衰退年夏季, 赤道中东太平洋海温仍维持正异常 (衰减为负异常) . 与SD El Niño事件相比, RD El Niño事件衰退年夏季西北太平洋TC频数显著减少. 进一步的分析揭示了导致TC频数差异的大尺度环境要素, 指出热带印度洋-太平洋海温异常密切相关的西北太平洋低层反气旋异常在其中起到了关键作用.     

A spatiotemporal 3D convolutional neural network model for ENSO predictions: A test case for the 2020/21 La Niña conditions

Many coupled models are unable to accurately depict the multi-year La Niña conditions in the tropical Pacific during 2020–22, which poses a new challenge for real-time El Niño–Southern Oscillation (ENSO) predictions. Yet, the corresponding processes responsible for the multi-year coolings are still not understood well. In this paper, reanalysis products are analyzed to examine the ocean–atmosphere interactions in the tropical Pacific that have led to the evolution of sea surface temperature (SST) in the central-eastern equatorial Pacific, including the strong anomalous southeasterly winds over the southeastern tropical Pacific and the related subsurface thermal anomalies. Meanwhile, a divided temporal and spatial (TS) 3D convolution neural network (CNN) model, named TS-3DCNN, was developed to make predictions of the 2020/21 La Niña conditions; results from this novel data-driven model are compared with those from a physics-based intermediate coupled model (ICM). The prediction results made using the TS-3DCNN model for the 2020–22 La Niña indicate that this deep learning–based model can capture the two-year La Niña event to some extent, and is comparable to the IOCAS ICM; the latter dynamical model yields a successful real-time prediction of the Niño3.4 SST anomaly in late 2021 when it is initiated from early 2021. For physical interpretability, sensitivity experiments were designed and carried out to confirm the dominant roles played by the anomalous southeasterly wind and subsurface temperature fields in sustaining the second-year cooling in late 2021. As a potential approach to improving predictions for diversities of ENSO events, additional studies on effectively combining neural networks with dynamical processes and mechanisms are expected to significantly enhance the ENSO prediction capability.摘要2020–22年间热带太平洋经历了持续性多年的拉尼娜事件, 多数耦合模式都难以准确预测其演变过程, 这为厄尔尼诺-南方涛动(ENSO)的实时预测带来了很大的挑战. 同时, 目前学术界对此次持续性双拉尼娜事件的发展仍缺乏合理的物理解释, 其所涉及的物理过程和机制有待于进一步分析. 本研究利用再分析数据产品分析了热带东南太平洋东南风异常及其引起的次表层海温异常在此次热带太平洋海表温度(SST)异常演变中的作用, 并构建了一个时空分离(Time-Space)的三维(3D)卷积神经网络模型(TS-3DCNN)对此次双拉尼娜事件进行实时预测和过程分析. 通过将TS-3DCNN与中国科学院海洋研究所(IOCAS)中等复杂程度海气耦合模式(IOCAS ICM)的预测结果对比, 表明TS-3DCNN模型对2020–22年双重拉尼娜现象的预测能力与IOCAS ICM相当, 二者均能够从2021年初的初始场开始较好地预测2021年末 El Niño3.4区SST的演变. 此外, 基于TS-3DCNN和IOCAS ICM的敏感性试验也验证了赤道外风场异常和次表层海温异常在2021年末赤道中东太平洋海表二次变冷过程中的关键作用. 未来将神经网络与动力 模式模式间的有效结合, 进一步发展神经网络与物理过程相结合的混合建模是进一步提高ENSO事件预测能力的有效途径.     

Sea surface temperature anomaly in the tropical North Atlantic during El Niño decaying years

Based on reanalysis data from 1979 to 2016, this study focuses on the sea surface temperature (SST) anomaly of the tropical North Atlantic (TNA) in El Niño decaying years. The TNA SST exhibits a clear warm trend during this period. The composite result for 10 El Niño events shows that the TNA SST anomaly reaches its maximum in spring after the peak of an El Niño event and persists until summer. In general, the anomaly is associated with three factors—namely, El Niño, the North Atlantic Oscillation (NAO), and a long-term trend, leading to an increase in local SST up to 0.4°C, 0.3°C, and 0.35°C, respectively. A comparison between 1983 and 2005 indicates that the TNA SST in spring is affected by El Niño, as well as the local SST in the preceding winter, which may involve a long-term trend signal. In addition, the lead–lag correlation shows that the NAO leads the TNA SST by 2–3 months. By comparing two years with an opposite phase of the NAO in winter (i.e., 1992 and 2010), the authors further demonstrate that the NAO is another important factor in regulating the TNA SST anomaly. A negative phase of the NAO in winter will reinforce the El Niño forcing substantially, and vise versa. In other words, the TNA SST anomaly in the decaying years is more evident if the NAO is negative with El Niño. Therefore, the combined effects of El Niño and the NAO must be considered in order to fully understand the TNA SST variability along with a long-term trend.摘要基于1979年到2016年多种再分析资料, 本文分析了El Niño衰减年热带北大西洋的海温异常. 结果表明, 热带北大西洋海温在此期间呈显著变暖趋势. 10次El Niño事件的合成结果表明热带北大西洋海温异常在El Niño事件峰值之后的春季达到最大值, 并持续到夏季. 一般而言, 这种异常与三个因子有关, 即El Niño, 北大西洋涛动和长期趋势, 能分别导致局地海温上升0.4°C, 0.3°C和0.35°C. 1983年和2005年的对比分析表明, 尽管El Niño强度对春季北大西洋海温起到决定性作用, 与长期趋势密切相关的前冬海温也很重要. 此外, 超前-滞后相关结果表明北大西洋涛动超前海温约2–3个月. 比较两个冬季相反位相北大西洋涛动的年份 (即1992年和2010年) , 表明北大西洋涛动也能调制北大西洋海温异常. 冬季负位相北大西洋涛动能显著增强El Niño的强迫影响, 反之亦然. 换言之, 如果北大西洋涛动与El Niño位相相合, 衰减年北大西洋海温异常才更为显著. 因此, 为全面理解热带北大西洋海温变化, 除长期趋势外, 还必须考虑El Niño和北大西洋涛动的综合影响.     

Impacts of ENSO on wintertime PM2.5 pollution over China during 2014–2021

China has implemented a series of emission reduction policies since 2013, and the concentration of air pollutants has consequently decreased significantly. However, PM_2.5 (particulate matter with an aerodynamic diameter less than 2.5 µm) pollution still occurs in China in relation to the interannual variations in meteorological conditions. Considering that El Niño–Southern Oscillation (ENSO) is the strongest signal modulating the interannual variation in the atmosphere–ocean system, in this study the authors investigate the variations in PM_2.5 concentrations in four megacity clusters of China during the winter season associated with four individual ENSO events from 2014 to 2021. Results show that the wintertime PM_2.5 concentrations in the Beijing–Tianjin–Hebei and Fenwei Plain regions during El Niño years are higher than those during La Niña years, which can be explained by the anomalous southerly (northerly) winds during El Niño (La Niña) favoring PM_2.5 accumulation (diffusion). In the Pearl River Delta region, PM_2.5 concentrations decrease in El Niño relative to La Niña years owing to the enhanced water vapor flux and precipitation, removing more PM_2.5 from the atmosphere. The comprehensive effects of wind and precipitation anomalies lead to the unpredictability of the impacts of ENSO on PM_2.5 over the Yangtze River Delta region, which should be analyzed case by case.摘要2013年以来中国实施了一系列减排政策, 大气污染物浓度明显下降, 但由于气象条件的年际变化, 中国PM_2.5 (空气动力学直径小于2.5 µm的颗粒物) 污染仍然存在. 厄尔尼诺–南方涛动 (ENSO) 是调节大气–海洋系统年际变化的最强信号. 本文研究了2014–2021年四次ENSO事件期间, 中国四个特大城市群冬季PM_2.5浓度的变化. 结果表明, 在京津冀和汾渭平原地区, 由于厄尔尼诺 (拉尼娜) 期间的偏南风 (偏北风) 异常有利于 PM_2.5 的积累 (扩散), 冬季PM_2.5浓度在厄尔尼诺年高于拉尼娜年. 在珠三角地区, 由于厄尔尼诺冬季水汽通量和降水的增加有利于大气中PM_2.5的湿清除, 冬季PM_2.5浓度在厄尔尼诺年低于拉尼娜年. 在环流和降水异常的综合作用下, ENSO对长三角地区PM_2.5浓度的影响难以预测, 应逐案分析.     

Impacts of strong El Niño on summertime near-surface ozone over China

The influences of strong El Niño events (1997/98 and 2015/16) on summertime near-surface ozone (O₃) concentrations over China are investigated using the GEOS-Chem model. The results show that near-surface O₃ concentrations increased by a maximum of 6 ppb (parts per billion) during the summer of the developing phase of the 1997/98 El Niño in northeastern China, mainly due to the increased chemical production related to the hot and dry conditions. Besides, the O₃ concentration increased by 3 ppb during the developing summer of both the 1997/98 and 2015/16 El Niño in southern China. It was linked to the weakened prevailing monsoon winds, which led to the accumulation of O₃ in southern China. In contrast, in the summer of the decaying phase of the two El Niño events, O₃ concentrations decreased over many regions of China when the El Niño reversed to the cooling phase. This highlights that El Niño plays an important role in modulating near-surface O₃ concentrations over China.摘要利用全球大气化学三维模式 (GEOS-Chem) 模拟研究两次强厄尔尼诺事件 (1997/98和2015/16) 对中国夏季近地面臭氧 (O₃₎ 浓度的影响. 结果表明1997/98年厄尔尼诺事件发展期夏季中国东北区域O₃浓度升高, 最大值超过6ppb, 这主要归因于高温晴朗低湿等气象因素导致O₃化学生成升高. 此外, 两次厄尔尼诺事件发展期夏季O₃浓度在中国南部均增加了3ppb, 这与盛行季风减弱导致中国南方O₃局地积累有关. 相反, 在两次强厄尔尼诺衰减期夏季, 中国大部分地区O₃浓度下降伴随着海温模态转变为拉尼娜事件. 这表明厄尔尼诺在调节中国近地面O₃浓度中发挥着重要作用.     

Distribution of lightning spatial modes and climatic causes in China

This paper investigates the distribution of spatial modes of cloud-to-ground (CG) lightning activity across China's land areas during the period 2010–20 and their possible causes based on the CG lightning dataset of the China National Lightning Detection Network. It is found that the first empirical orthogonal function mode (EOF1) occupies 32.86% of the total variance of the summer CG lightning anomaly variation. Also, it exhibits a negative–positive–negative meridional seesaw pattern from north to south. When the SST of the East Pacific and Indian Ocean warms abnormally and the SST of the Northwest Pacific becomes abnormally cold, a cyclonic circulation is stimulated in the Yellow Sea, East China Sea, and tropical West Pacific region of China. As the water vapor continues to move southwards, it converges with the water vapor deriving from the Bay of Bengal in South China, and ascending motion strengthens here, thus enhancing the CG lightning activity of this area. Affected by the abnormal high pressure, the corresponding CG lightning activities in North China and Northeast China are relatively weak. The ENSO phenomenon is the climate driver for the CG lightning activity occurring in land areas of China.摘要本文利用中国气象局国家雷电监测网 (CNLDN) 的地闪观测数据集, 分析了2010–2020年中国陆地区域地闪空间模态分布特征及其可能的气候成因. 研究发现, 夏季地闪第一模态的方差贡献率为32.86%, 其分布从北到南呈现出“−+−”的经向跷跷板模式. 当东太平洋和印度洋的海温异常增暖, 西北太平洋的海温异常变冷时, 在中国黄海, 东海及热带西太平洋地区激发出气旋性环流. 随着水汽南下至华南地区, 与来自孟加拉湾的水汽汇合, 上升运动在此加强, 从而使得该地区的雷电活动增强. 表明厄尔尼诺-南方涛动 (ENSO) 现象, 是发生在中国陆地区域的地闪活动的气候驱动因子.     

Possible contribution of the PDO to the eastward retreat of the western pacific subtropical high: PDO对西太平洋副热带高压年代际东退的可能贡献

Previous studies have demonstrated that the western Pacific subtropical high (WPSH) has experienced an eastward retreat since the late 1970s. In this study, the authors propose that this eastward retreat of the WPSH can be partly attributed to atmospheric responses to the positive phase of the Pacific decadal oscillation (PDO), based on idealized SST forcing experiments using the Community Atmosphere Model, version 4. Associated with the positive phase of the PDO, convective heating from the Indian Peninsula to the western Pacific and over the eastern tropical Pacific has increased, which has subsequently forced a Gill-type response to modulate the WPSH. The resulting cyclonic gyre over the Asian continent and the western Pacific in the lower troposphere is favorable for the eastward retreat of the WPSH. Additionally, the resulting anticyclonic gyre in the upper troposphere is favorable for the strengthening and southward expansion of the East Asian westerly jet, which can modulate the jet-related secondary meridional–vertical circulation over the western Pacific and promote the eastward retreat of the WPSH.摘要以往的研究已证实, 西太平洋副热带高压 (副高) 在1970s后期减弱东退.基于大气模式 (CAM4) 的理想型海温强迫试验, 结果表明:副高的东退可能是大气对于正位相太平洋年代际振荡 (PDO) 的相应.伴随着PDO转变为正位相, 西太平洋至印度半岛以及热带东太平洋的对流加热增强, 大气表现为Gill型响应, 在亚洲大陆至西太平洋上空低层产生气旋性异常, 有利于副高东退.同时, 高层产生反气旋异常, 使得东亚西风急流加强和向南扩展, 进而调节西太平洋上空的次级环流, 进一步有利于副高东退.     

A tripole winter precipitation change pattern around the Tibetan Plateau in the late 1990s

Classical monsoon dynamics considers the winter/spring snow amount on the Tibetan Plateau (TP) as a major factor driving the East Asian summer monsoon (EASM) for its direct influence on the land–sea thermal contrast. Actually, the TP snow increased and decreased after the late 1970s and 1990s, respectively, accompanying the two major interdecadal changes in the EASM. Although studies have explored the possible mechanisms of the EASM interdecadal variations, and change in TP snow is considered as one of the major drivers, few studies have illustrated the underlying mechanisms of the interdecadal changes in the winter TP snow. This study reveals a tripole pattern of change, with decreased winter precipitation over the TP and an increase to its north and south after the late 1990s. Further analyses through numerical experiments demonstrate that the tropical Pacific SST changes in the late 1990s can robustly affect the winter TP precipitation through regulating the Walker and regional Hadley circulation. The cooling over the tropical central-eastern Pacific can enhance the Walker circulation cell over the Pacific and induce ascending motion anomalies over the Indo-Pacific region. These anomalies further drive descending motion anomalies over the TP and ascending motion anomalies to the north through regulating the regional Hadley circulation. Therefore, the positive–negative–positive winter precipitation anomalies around the TP are formed. This study improves the previously poor understanding of TP climate variation at interdecadal timescales.摘要在20世纪70年代和90年代末, 伴随着东亚夏季风的两次主要年代际变化, 高原积雪分别显著增加和减少. 尽管很多学者研究了东亚夏季风年代际变化的可能机制, 高原积雪变化也被认为是主要因素之一, 但是关于高原冬季积雪本身发生年代际变化的潜在机制尚鲜有研究. 本文揭示了20世纪90年代末高原及周边冬季降水的三极子变化特征: 高原主体上空主要为降水减少, 其南北两侧区域降水增加. 数值试验结果表明, 热带太平洋海温变化可以通过调节沃克环流和局地哈德莱环流, 对上述三极子降水变化型态产生显著影响.     

The exceptionally strong and persistent Arctic stratospheric polar vortex in the winter of 2019–2020: 2019-2020冬季北半球超强极涡事件

The Arctic stratospheric polar vortex was exceptional strong, cold and persistent in the winter and spring of 2019–2020. Based on reanalysis data from the National Centers for Environmental Prediction/National Center for Atmospheric Research and ozone observations from the Ozone Monitoring Instrument, the authors investigated the dynamical variation of the stratospheric polar vortex during winter 2019–2020 and its influence on surface weather and ozone depletion. This strong stratospheric polar vortex was affected by the less active upward propagation of planetary waves. The seasonal transition of the stratosphere during the stratospheric final warming event in spring 2020 occurred late due to the persistence of the polar vortex. A positive Northern Annular Mode index propagated from the stratosphere to the surface, where it was consistent with the Arctic Oscillation and North Atlantic Oscillation indices. As a result, the surface temperature in Eurasia and North America was generally warmer than the climatology. In some places of Eurasia, the surface temperature was about 10 K warmer during the period from January to February 2020. The most serious Arctic ozone depletion since 2004 has been observed since February 2020. The mean total column ozone within 60°–90°N from March to 15 April was about 80 DU less than the climatology.摘要2019-2020冬季北极平流层极涡异常并且持续的偏强,偏冷.利用NCEP再数据和OMI臭氧数据, 本文分析了此次强极涡事件中平流层极涡的动力场演变及其对地面暖冬天气和臭氧低值的影响.此次强极涡的形成是由于上传行星波不活跃.持续的强极涡使得2020年春季的最后增温出现时间偏晚.平流层正NAM指数向下传播到地面, 与地面AO指数和NAO指数相一致, 欧亚大陆和北美地面气温均比气候态偏暖, 在欧亚大陆的一些地区, 2020年1月和2月的气温甚至偏高了10K.2020年2月以来北极臭氧出现了2004年以来的最低值, 2020年3-4月60°–90°N的平均臭氧柱总量比气候态偏低了80DU.     

Predicting climate anomalies:A real challenge

过去几十年,气候变化和极端气候事件造成的经济损失和灾害显著增加.虽然全球的科学家在理解和预测气候变异方面做出了巨大的努力,但当前在气候预测领域仍然存在几个重大难题.2020年,依托于国家自然科学基金基础科学中心项目的气候系统预测研究中心(CCSP)成立了,该中心旨在应对和处理气候预测领域的三大科学难题:厄尔尼诺-南方涛动(ENSO)预测,延伸期天气预报,年际-年代际气候预测,并为更加准确的气候预测和更加有效的灾害防御提供科学依据.因此,本文介绍了CCSP的主要目标和面对的科学挑战,回顾了CCSP在季风动力过程,陆-气相互作用和模式开发,ENSO变率,季节内振荡,气候预测等方面已取得的重要研究成果.未来CCSP将继续致力于解决上述领域的关键科学问题.     

Different response of North Pacific storm tracks in the upper and lower troposphere to jet strength

The midwinter suppression of North Pacific storm tracks (NPSTs) reflects that the linear relationship between the NPST and baroclinicity breaks in winter. Based on the reanalysis data during the cold seasons of 1979–2019 and a tracking algorithm, this study analyzes the eddy growth process and shows that an enhanced upper-tropospheric jet favors the generation of upper-level eddies on the northeast side of the Pacific jet, but increasingly suppresses the generation of those in the Northwest Pacific. The upper-level eddies generated upstream of the jet core are unable to grow sufficiently throughout the whole cold season, and only those generated downstream of the jet core can grow normally and constitute the main body of the upper-level NPST. By contrast, the main lower-level eddy genesis area and growth area coincide with the baroclinic zone, with the genesis number and local growth rate increasing with the baroclinicity.摘要北太平洋风暴轴的深冬抑制表明风暴轴强度与斜压性之间的线性关系在冬季破裂. 本研究基于1979–2019年冷季的再分析数据和拉格朗日跟踪算法, 对比分析了高低层扰动的具体生长过程. 结果表明太平洋急流的增强有利于高层扰动在急流核东北侧产生, 但却抑制其在西北太平洋的生成. 在急流核上游产生的高层扰动在整个冷季都无法充分发展, 只有在急流核下游产生的高层扰动才能正常生长且它们是构成高层太平洋风暴轴的主体. 相比之下, 低层扰动的生成区和生长区都与斜压区重合, 并且它们的生成数量和局部增长率随着斜压性的增强而增强.     

A deep learning–based U-Net model for ENSO-related precipitation responses to sea surface temperature anomalies over the tropical Pacific

SST–precipitation feedback plays an important role in ENSO evolution over the tropical Pacific and thus it is critically important to realistically represent precipitation-induced feedback for accurate simulations and predictions of ENSO. Typically, in hybrid coupled modeling for ENSO predictions, statistical atmospheric models are adopted to determine linear precipitation responses to interannual SST anomalies. However, in current coupled climate models, the observed precipitation–SST relationship is not well represented. In this study, a data-driven deep learning-based U-Net model was used to construct a nonlinear response model of interannual precipitation variability to SST anomalies. It was found that the U-Net model outperformed the traditional EOF-based method in calculating the precipitation variability. Particularly over the western-central tropical Pacific, the mean-square error (MSE) of the precipitation estimates in the U-Net model was smaller than that in the EOF model. The performance of the U-Net model was further improved when additional tendency information on SST and precipitation variability was also introduced as input variables, leading to a pronounced MSE reduction over the ITCZ.摘要SST–降水反馈过程在热带太平洋ENSO演变过程中起着重要作用, 能否真实地在数值模式中表征SST–降水年际异常之间的关系及相关反馈过程, 对于准确模拟和预测ENSO至关重要. 例如, 在一些模拟ENSO的混合型耦合模式中, 通常采用大气统计模型 (如经验正交函数; EOF) 来表征降水 (海气界面淡水通量的一个重要分量) 对SST年际异常的线性响应. 然而在当前的耦合模式中, 真实观测到的降水–SST统计关系还不能被很好地再现出来, 从而引起 ENSO模拟误差和不确定性. 在本研究中, 使用基于深度学习的U-Net模型来构建热带太平洋降水异常场对SST年际异常的非线性响应模型. 研究发现: U-Net模型的性能优于传统的基于EOF方法的模型. 特别是在热带西太平洋海区, U-Net模型估算的降水误差远小于EOF模型的模拟. 此外, 当SST和降水异常的趋势信息作为输入变量也被同时引入以进一步约束模式训练时, U-Net模型的性能可以进一步提高, 如能使热带辐合带区域的误差显著降低.     

Association between tropospheric temperature and tropical cyclone peak intensity over the North Pacific and North Atlantic

台风作为一种灾害性天气,其破坏性大小与自身强度有很大的关系.因此,本项研究利用NCEP-NCAR和MERRA再分析数据,考查了北大西洋,西北太平洋,东北太平洋台风强度峰值与对流层温度的关系.台风强度峰值与大气温度的相关系数,以及极大和极小台风强度峰值下大气温度的差值,共同显示:北大西洋台风强度峰值受到对流层顶低温和对流...     

Decadal–centennial hydroclimate variability over eastern China during the last millennium: Results from the product of Paleo Hydrodynamics Data Assimilation: 过去千年中国东部年代际-百年尺度干湿变化特征:基于古水文动力同化数据

Decadal–centennial hydroclimate variability over eastern China during the last millennium is investigated using the product of Paleo Hydrodynamics Data Assimilation (PHYDA). Results reveal that the PHYDA depicts a more homogeneous temporal pattern during the early part of the Little Ice Age with other reconstructions than those during the other periods, and could also identify the droughts of 1352–90 AD, 1445–98 AD, 1580–94 AD, and 1626–65 AD during this period. On centennial time scales, the PHYDA shows that the linkage between the Palmer drought severity index over eastern China and the Atlantic Multidecadal Oscillation (AMO) index is more marked than that with the El Niño–Southern Oscillation and the location of the intertropical convergence zone over the Asian–Australian monsoon area during the period after the 1350s. For the decadal droughts, the PHYDA suggests most of the drought events during the last millennium were linked to the El Niño–like mean states and the negative AMO states.摘要利用古水文动力同化数据 (PHYDA) 研究了过去千年中国东部年代际-百年尺度干湿变化特征.结果表明, 对比其它重建数据PHYDA在百年尺度上对小冰期前期中国东部干湿变化的再现能力最好, 其对这一时期发生的年代际干旱事件包括1352–90年,1445–98年,1580–94年和1626–65年干旱事件的再现能力也最强.通过与强迫因子的对比和回归分析, 发现1350年后中国东部百年尺度干事变化主要受北大西洋年代际振荡影响, 而年代际干旱事件的主导因子则是厄尔尼诺和负位相的北大西洋年代际振荡.     

Evaluation of the interannual variability in the East Asian summer monsoon in AMIP and historical experiments of CAS FGOALS-f3-L

The evaluation of East Asian summer monsoon (EASM) simulations could improve our understanding of Asian monsoon dynamics and climate simulations. In this study, by using Phase 6 of the Coupled Model Intercomparison Project (CMIP6) experiments of the Atmospheric Model Intercomparison Project (AMIP) and historical runs of the Chinese Academy of Sciences (CAS) Flexible Global Ocean–Atmosphere–Land System (FGOALS-f3-L) model, the model simulation skill for the interannual variability in the EASM was determined. According to multivariate empirical orthogonal function (MV-EOF) analysis, the major mode of the EASM mainly emerged as a Pacific-Japan pattern in the western Pacific accompanied by a local anticyclonic anomaly with a total variance of 24.6%. The historical experiment could suitably reproduce this spatial pattern and attained a closer total variance than that attained by the AMIP experiment. The historical experiment could also better simulate the time frequency of the EASM variability than the AMIP experiment. However, the phase of principal component 1 (PC1) was not suitably reproduced in the historical experiment since no initialization procedure was applied at the beginning of the integration in the historical simulation process, whereas the sea surface temperature (SST) was preset in the AMIP experiment. Further analysis revealed that air–sea interactions in the Indian Ocean and tropical western Pacific were important for the model to provide satisfactory EASM simulations, while El Niño–Southern Oscillation (ENSO) simulation was possibly related to the climate variability in the EASM simulations, which should be further analyzed.摘要对东亚夏季季风(EASM)模拟的评估可以提高我们对亚洲季风动力和气候模拟的理解. 在这项研究中, 通过使用中国科学院(CAS)全球海洋-大气-陆地系统(FGOALS-f3-L)模式参加的第六次耦合模式相互比较计划(CMIP6)中的大气模式相互比较计划(AMIP)和历史(historical)试验, 明确了EASM的年际变率的模拟能力. 通过多变量经验正交函数(MV-EOF)分析发现, 观测的EASM的主导模态为西太平洋上的太平洋-日本模态, 并伴有局部反气旋异常. 主导模态的方差贡献率为24.6%. 历史(historical)试验可以基本再现这种空间模态, 其方差贡献率较AMIP试验更接近于观测. 与AMIP试验相比, 历史(historical)试验还能更好地模拟EASM变率的时间频率. 然而, 由于历史(historical)模拟没有在积分开始时应用初始化过程, 而AMIP试验受到海表面温度(SST)的约束, 因此主成分(PC1)的位相在历史(historical)试验中没有得到较好地再现. 进一步分析发现, 印度洋和西太平洋热带地区的海气相互作用对EASM的模拟非常重要, 而EASM气候变率的模拟可能与厄尔尼诺-南方涛动(ENSO)的模拟能力有关, 这值得进一步分析.     

Strong heatwaves with widespread urban-related hotspots over Africa in 2019

2019 was one of the hottest years in recent decades, with widespread heatwaves over many parts of the world, including Africa. However, as a developing and vulnerable region, the understanding of recent heatwave events in Africa is limited. Here, the authors incorporated different climate datasets, satellite observations, and population estimates to investigate patterns and hotspots of major heatwave events over Africa in 2019. Overall, 2019 was one of the years that experienced the strongest heatwaves in terms of intensity and duration since 1981 in Africa. Heatwave hotspots were clearly identified across western-coastal, northeastern, southern, and equatorial Africa, where major cities and human populations are located. The proportion of urban agglomerations (population) exposed to extreme (99th percentile) heatwaves in the Northern Hemisphere and Southern Hemisphere rose from 4% (5 million people) and 15% (17 million people), respectively, in the baseline period of 1981–2010 to 36% (43 million people) and 57% (53 million people), respectively, in 2019. Heatwave patterns and hotspots in 2019 were related to anomalous seasonal change in atmospheric circulation and above-normal sea surface temperature. Without adaptation to minimize susceptibility to the effects of heatwave events, the risks they pose in populated areas may increase rapidly in Africa.摘要2019 年是近几十年来最热的年份之一, 包括非洲在内的全球许多地区都受到大范围的热浪侵袭. 然而, 非洲作为脆弱的发展中地区, 我们对其近年热浪事件的了解非常有限. 本研究中, 我们结合了不同的气候数据集, 卫星观测资料和人口数据, 研究了 2019 年非洲地区主要热浪事件发生的时空特征和热点分布区. 总体而言, 2019 年是非洲地区自 1981 年以来热浪强度最强, 持续时间最久的年份之一. 在主要城市和人口所在的非洲西海岸, 东北部, 南部和赤道地区是热浪发生的热点区. 位于赤道以北的非洲地区, 暴露于极端 (第 99 个百分位) 热浪的城市人口比例从 1981–2010 年基准期的 4% (500 万人) 上升至2019 年的 36% (4300 万人). 位于赤道以南地区, 暴露于极端热浪的城市人口则从基准期的15% (1700 万人) 上升至57% (5300 万人). 2019 年的热浪时空特征和热点分布与大气环流的季节变化异常和海温的暖异常有关. 如果不及时采取适应措施以尽量减少人口对热浪事件影响的敏感性, 热浪对非洲人口稠密地区构成的风险可能会迅速增加.     

Dominant patterns of winter surface air temperature over Central Asia and their connection with atmospheric circulation

The dominant patterns of the winter (December–February) surface air temperature anomalies (SATAs) over Central Asia (CA) are investigated in this study. The first two leading modes revealed by empirical orthogonal function (EOF) analysis represent the patterns by explaining 74% of the total variance. The positive phase of EOF1 is characterized by a monopole pattern, corresponding to cold SATAs over CA, while the positive phase of EOF2 shows a meridional dipole pattern with warm and cold SATAs over northern and southern CA. EOF1 is mainly modulated by the negative phase of the Arctic Oscillation (AO) in the troposphere, and the negative AO phase may be caused by the downward propagation of the precursory anomalies of the stratospheric polar vortex. EOF2 is mainly influenced by the Ural blocking pattern and the winter North Atlantic Oscillation (NAO). The SATAs associated with EOF2 can be attributed to a dipole-like pattern of geopotential height anomalies over CA. The dipole-like pattern is mainly caused by the Ural blocking pattern, and the NAO can also contribute to the northern part of the dipole.摘要本文利用经验正交函数分解方法 (Empirical orthogonal function, EOF) , 针对1979–2019年冬季 (12月–2月) 中亚地区地面气温异常进行了研究. 结果表明, 中亚地区冬季地面气温异常的前两个EOF模态解释方差总占比可达74%. 其中, 第一模态 (EOF1) 正位相为一致型变化, 对应中亚地区气温冷异常; 第二模态 (EOF2) 正位相则为南北偶极型变化, 对应于中亚地区南冷北暖型气温异常. EOF1可能受到冬季北极涛动 (Arctic Oscillation, AO) 负位相的调制, 而AO的负位相则可能来自于前期平流层极涡正位势高度异常下传. EOF2则可能受到乌拉尔山阻塞及冬季北大西洋涛动 (North Atlantic Oscillation, NAO) 的共同调制. 乌拉尔山阻塞可引起中亚区域南北偶极型气温异常, 而冬季NAO可对该偶极型气温异常的北侧产生贡献.     

Prediction of ENSO using multivariable deep learning

A novel multivariable prediction system based on a deep learning (DL) algorithm, i.e., the residual neural network and pure observations, was developed to improve the prediction of the El Niño–Southern Oscillation (ENSO). Optimal predictors are automatically determined using the maximal information for spatial filtering and the Taylor diagram criteria, enabling the best prediction skills at lead times of eight months compared with most operational prediction models. The hindcast skill for the most challenging decade (2011–18) outperforms the multi-model ensemble operational forecasts. At the six-month lead, the correlation (COEF) skill of the DL model reaches 0.82 with a normalized root-mean-square error (RMSE) of 0.58 °C, which is significantly better than the average multi-model performance (COEF = 0.70 and RMSE = 0.73°C). DL prediction can effectively alleviate the long-standing spring predictability barrier problem. The automatically selected optimal precursors can explain well the typical ENSO evolution driven by both tropical dynamics and extratropical impacts.摘要本文基于残差神经网络和观测数据构建了一套深度学习多因子预报测模型, 以改进厄尔尼诺-南方涛动(ENSO)的预报. 该模型基于最大信息系数进行因子时空特征提取, 并根据泰勒图的评估标准可自动确定关键预报因子进行预报. 该模型在超前8个月以内的预报性能要优于当前传统的业务预报模式. 2011–2018年间, 该模型的预报性能优于多模式集成预报的结果. 在超前6个月预报时效上, 模型预报相关性可达0.82, 标准化后的均方根误差仅为0.58°C, 多模式集成预报的相关性和标准化后的均方根误差分别为0.70和0.73°C. 该模型春季预报障碍问题有所缓解, 并且自动选取的关键预报因子可用于解释热带和副热带热动力过程对于ENSO变化的影响.     

Analysis of lower-boundary climate factors contributing to the summer heatwave frequency over eastern Europe using a machine-learning model

A machine-learning (ML) model, the light gradient boosting machine (LightGBM), was constructed to simulate the variation in the summer (June–July–August) heatwave frequency (HWF) over eastern Europe (HWF_EUR) and to analyze the contributions of various lower-boundary climate factors to the HWF_EUR variation. The examined lower-boundary climate factors were those that may contribute to the HWF_EUR variation—namely, the sea surface temperature, soil moisture, snow-cover extent, and sea-ice concentration from the simultaneous summer, preceding spring, and winter. These selected climate factors were significantly correlated to the summer HWF_EUR variation and were used to construct the ML model. Both the hindcast simulation of HWF_EUR for the period 1981–2020 and its real-time simulation for the period 2011–2020, which used the constructed ML model, were investigated. To evaluate the contributions of the climate factors, various model experiments using different combinations of the climate factors were examined and compared. The results indicated that the LightGBM model had comparatively good performance in simulating the HWF_EUR variation. The sea surface temperature made more contributions to the ML model simulation than the other climate factors. Further examination showed that the best ML simulation was that which used the climate factors in the preceding winter, suggesting that the lower-boundary conditions in the preceding winter may be critical in forecasting the summer HWF_EUR variation.摘要本文使用LightGBM机器学习模型模拟了欧洲东部夏季热浪频率的变化, 并分析了多个底边界层气候因子的贡献. 所选取的气候因子包括前期冬季, 前期春季以及同期夏季的下垫面海温, 土壤湿度, 积雪以及海冰. 分析结果说明LightGBM模型能够较好的模拟出欧洲东部夏季热浪频率的变化, 其中海温因子对模拟的贡献最大. 进一步的分析研究显示, 使用前期冬季的气候因子进行的模拟可以获得最佳模拟结果, 意味着前期冬季的下垫面气候因子可能对夏季欧洲东部热浪频率变化的预报能起到关键作用.     

Combined effect of El Niño-Southern Oscillation and Pacific Decadal Oscillation on the East Asian winter monsoon

Using long-term observational data and numerical model experiments, the combined effect of the El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) on the variability of the East Asian winter monsoon is examined. In the observations, it is found that when the ENSO and PDO are in-phase combinations (i.e., El Niño/positive PDO phase and La Niña/negative PDO phase), a negative relationship between ENSO and East Asian winter monsoon is significantly intensified. In other words, when El Niño (La Niña) occurs with positive (negative) PDO phase, anomalous warm (cold) temperatures are dominant over the East Asian winter continent. On the other hand, there are no significant temperature anomalies when the ENSO and PDO are out-of-phase combinations (i.e., El Niño/negative PDO phase and La Niña/positive PDO phase). Further analyses indicate that the anticyclone over the western North Pacific including the East Asian marginal seas plays an essential role in modulating the intensity of the East Asian winter monsoon under the changes of ENSO–PDO phase relationship. Long-lasting high pressure and warm sea surface temperature anomalies during the late fall/winter and following spring over the western North Pacific, which appear as the El Niño occurs with positive PDO phase, can lead to a weakened East Asian winter monsoon by transporting warm and wet conditions into the East Asian continent through the southerly wind anomalies along the western flank of the anomalous high pressure, and vice versa as the La Niña occurs with negative PDO phase. In contrast, the anomalous high pressure over the western North Pacific does not show a prominent change under the out-of-phase combinations of ENSO and PDO. Numerical model experiments confirm the observational results, accompanying dominant warm temperature anomalies over East Asia via strong anticyclonic circulation anomalies near the Philippine Sea as the El Niño occurs with positive PDO phase, whereas such warming is weakened as the El Niño occurs with negative PDO phase. This result supports the argument that the changes in the East Asian winter monsoon intensity with ENSO are largely affected by the strength of the anticyclone over the western North Pacific, which significantly changes according to the ENSO–PDO phase relationship.