Long-term ocean temperature trend and marine heatwaves

Marine heatwaves(MHWs)can cause irreversible damage to marine ecosystems and livelihoods.Appropriate MHW characterization remains difficult,because the choice of a sea surface temperature(SST)temporal baseline strongly influences MHW identification.Following a recent work suggesting that there should be a communicating baseline for long-term ocean temperature trends(LTT)and MHWs,we provided an effective and quantitative solution to calculate LTT and MHWs simultaneously by using the ensemble empirical mode decomposition(EEMD)method.The long-term nonlinear trend of SST obtained by EEMD shows superiority over the traditional linear trend in that the data extension does not alter prior results.The MHWs identified from the detrended SST data exhibited low sensitivity to the baseline choice,demonstrating the robustness of our method.We also derived the total heat exposure(THE)by combining LTT and MHWs.The THE was sensitive to the fixed-period baseline choice,with a response to increasing SST that depended on the onset time of a perpetual MHW state(identified MHW days equal to the year length).Subtropical areas,the Indian Ocean,and part of the Southern Ocean were most sensitive to the long-term global warming trend.

Decadal Changes in Dry and Wet Heatwaves in Eastern China:Spatial Patterns and Risk Assessment

Under global warming,understanding the long-term variation in different types of heatwaves is vital for China’s preparedness against escalating heat stress.This study investigates dry and wet heatwave shifts in eastern China over recent decades.Spatial trend analysis displays pronounced warming in inland midlatitudes and the Yangtze River Valley,with increased humidity in coastal regions.EOF results indicate intensifying dry heatwaves in northern China,while the Yangtze River Valley sees more frequent dry heatwaves.On the other hand,Indochina and regions north of 25°N also experience intensified wet heatwaves,corresponding to regional humidity increases.Composite analysis is conducted based on different situations:strong,frequent dry or wet heatwaves.Strong dry heatwaves are influenced by anticyclonic circulations over northern China,accompanied by warming SST anomalies around the coastal midlatitudes of the western North Pacific(WNP).Frequent dry heatwaves are related to strong subsidence along with a strengthened subtropical high over the WNP.Strong and frequent wet heatwaves show an intensified Okhotsk high at higher latitudes in the lower troposphere,and a negative circumglobal teleconnection wave train pattern in the upper troposphere.Decaying El Niño SST patterns are observed in two kinds of wet heatwave and frequent dry heatwave years.Risk analysis indicates that El Niño events heighten the likelihood of these heatwaves in regions most at risk.As global warming continues,adapting and implementing mitigation strategies toward extreme heatwaves becomes crucial,especially for the aforementioned regions under significant heat stress.

The Forecast Skills and Predictability Sources of Marine Heatwaves in the NUIST-CFS1.0 Hindcasts

Using monthly observations and ensemble hindcasts of the Nanjing University of Information Science and Technology Climate Forecast System(NUIST-CFS1.0) for the period 1983–2020, this study investigates the forecast skill of marine heatwaves(MHWs) over the globe and the predictability sources of the MHWs over the tropical oceans. The MHW forecasts are demonstrated to be skillful on seasonal-annual time scales, particularly in tropical oceans. The forecast skill of the MHWs over the tropical Pacific Ocean(TPO) remains high at lead times of 1–24 months, indicating a forecast better than random chance for up to two years. The forecast skill is subject to the spring predictability barrier of El Nino-Southern Oscillation(ENSO). The forecast skills for the MHWs over the tropical Indian Ocean(TIO), tropical Atlantic Ocean(TAO), and tropical Northwest Pacific(NWP) are lower than that in the TPO. A reliable forecast at lead times of up to two years is shown over the TIO, while a shorter reliable forecast window(less than 17 months) occurs for the TAO and NWP.Additionally, the forecast skills for the TIO, TAO, and NWP are seasonally dependent. Higher skills for the TIO and TAO appear in boreal spring, while a greater skill for the NWP emerges in late summer-early autumn. Further analyses suggest that ENSO serves as a critical source of predictability for MHWs over the TIO and TAO in spring and MHWs over the NWP in summer.

Evaluation and projection of marine heatwaves in the South China Sea: insights from CMIP6 multi-model ensemble

This study evaluates the performance of 16 models sourced from the coupled model intercomparison project phase 6(CMIP6)in simulating marine heatwaves(MHWs)in the South China Sea(SCS)during the historical period(1982−2014),and also investigates future changes in SCS MHWs based on simulations from three shared socioeconomic pathway(SSP)scenarios(SSP126,SSP245,and SSP585)using CMIP6 models.Results demonstrate that the CMIP6 models perform well in simulating the spatial-temporal distribution and intensity of SCS MHWs,with their multi-model ensemble(MME)results showing the best performance.The reasonable agreement between the observations and CMIP6 MME reveals that the increasing trends of SCS MHWs are attributed to the warming sea surface temperature trend.Under various SSP scenarios,the year 2040 emerges as pivotal juncture for future shifts in SCS MHWs,marked by distinct variations in changing rate and amplitudes.This is characterized by an accelerated decrease in MHWs frequency and a notably heightened increase in mean intensity,duration,and total days after 2040.Furthermore,the projection results for SCS MHWs suggest that the spatial pattern of MHWs remains consistent across future periods.However,the intensity shows higher consistency only during the near-term period(2021−2050),while notable inconsistencies are observed during the medium-term(2041−2070)and long-term(2071−2100)periods under the three SSP scenarios.During the nearterm period,the SCS MHWs are characterized by moderate and strong events with high frequencies and relatively shorter durations.In contrast,during the medium-term period,MHWs are also characterized by moderate and strong events,but with longer-lasting and more intense events under the SSP245 and SSP585 scenarios.However,in the long-term period,extreme MHWs become the dominant feature under the SSP585 scenario,indicating a substantial intensification of SCS MHWs,effectively establishing a near-permanent state.

Electricity Generation from Heatwaves

We chose a definition of heatwaves (HWs) that has ~4-year recurrence frequency at world hot spots. We first examined the 1940-2022 HWs climatology and trends in lifespan, severity, spatial extent, and recurrence frequency. HWs are becoming more frequent and more severe for extratropical mid- and low-latitudes. To euphemize HWs, we here propose a novel clean energy-tapping concept that utilizes the available nano-technology, micro-meteorology knowledge of temperature distribution within/without buildings, and radiative properties of earth atmosphere. The key points for a practical electricity generation scheme from HWs are defogging, insulation, and minimizing the absorption of infrared downward radiation at the cold legs of the thermoelectric generators. One sample realization is presented which, through relay with existing photovoltaic devices, provides all-day electricity supply sufficient for providing air conditioning requirement for a residence (~2000-watt throughput). The provision of power to air conditioning systems, usually imposes a significant stress on traditional city power grids during heatwaves.

Linkage Between European and East Asian Heatwaves on Synoptic Scales

Concurrent extreme weather events in geographically distant areas potentially cause high-end risks for societies.By using network analysis,the present study managed to identify significant nearly-simultaneous occurrences of heatwaves between the grid cells in East Asia and Eastern Europe,even though they are geographically far away from each other.By further composite analysis,this study revealed that hot events first occurred in Eastern Europe,typically with a time lag of3-4 days before the East Asian heatwave events.An eastward propagating atmospheric wave train,known as the circumglobal teleconnection(CGT)pattern,bridged the sequent occurrences of extreme events in these two remote regions.Atmospheric blockings,amplified by surface warming over Eastern Europe,not only enhanced local heat extremes but also excited a CGT-like pattern characterized by alternative anomalies of high and low pressures.Subsequent downstream anticyclones in the middle and upper troposphere reduced local cloud cover and increased downward solar radiation,thereby facilitating the formation of heatwaves over East Asia.Nearly half of East Asian heatwave events were preceded by Eastern European heatwave events in the 10-day time range before East Asian heatwave events.This investigation of heatwave teleconnection in the two distant regions exhibits strong potential to improve the prediction accuracy of East Asian heatwaves.

宁波市热浪对寿命损失年影响的总效应及附加效应

目的评估宁波市热浪对寿命损失年(YLL)影响的总效应及附加效应。方法收集2013—2019年宁波市死亡、人口、气象和空气质量监测资料,计算得到每日YLL率;根据日最高气温的百分位数和持续时间定义15种热浪类型,利用时间序列方法结合分布滞后非线性模型评估热浪对人群YLL率影响的总效应及附加效应,并按照性别和年龄(<65岁、≥65岁)进行分层分析。结果研究期间宁波市人群总YLL率为(19.74±3.14)人年/10万,热浪期的总YLL率均高于非热浪期(P<0.05)。随着热浪强度增加和持续时间延长,热浪的总效应均呈上升趋势。当热浪定义为日最高气温≥P97.5(37.2℃)且持续时间≥2d时,热浪累积10 d(Lag0-10 d)的总效应最大,总YLL率增加3.77(95%CI:2.25,5.29)人年/10万。热浪对男性和老年人影响的总效应高于女性和低年龄人群。仅部分热浪类型对男性和老年人YLL率影响的附加效应有统计学意义(P<0.05)。结论热浪导致宁波市人群YLL率增加,且对男性和老年人的影响更大;热浪的附加效应可能仅在男性和老年人等敏感人群中出现。

2024年4-6月我国区域性高温干旱特征及其影响因子

在全球气候变暖的严峻形势下,区域性高温干旱事件愈发频繁,对生态环境、粮食安全、经济发展和生命健康构成重大威胁。2024年4—6月,我国华北、西北及西南地区再度遭遇高温干旱侵袭,农业生产遭受明显损失。本研究综合多种数据资料剖析上述3个区域高温干旱事件的演变特征及成因。结果表明,西南地区干旱主要发生在4月,而华北和西北地区自4月起旱情显现、5—6月旱情逐渐加剧(强度增强、范围扩大)。伴随旱情加剧,区域最高气温异常范围明显扩展,西北地区高温日数创历史新高,5月最高气温达到峰值,较旱情最为严重的6月提前一个月;西南和华北地区高温接近历史极值。进一步分析表明,华北地区干旱主要受太平洋地区环流调控,而高温则主要受低纬度太平洋环流及西太平洋暖池影响;西北地区的干旱主要与西太平洋副热带高压及北半球极涡密切相关,高温则主要来自北大西洋的影响;西南地区高温干旱的成因更为复杂,但主要聚焦于北半球副热带高压和低纬度太平洋、印度洋。从大气环流和水汽输送的角度审视,华北和西北旱情的主导因素为大陆高压的发展和维持,而西南地区的干旱则受偏北的西太平洋副热带高压引导,致使来自印度大陆的干热气流控制这一区域,造成水汽辐散,进而引发高温干旱灾害。

基于CMIP6耦合WRF的黄河上游复合干旱热浪事件演变规律

复合干旱热浪事件较传统极端气候事件破坏性更强,近年来在全球范围内发展迅速,黄河上游作为气候敏感区受其影响尤其突出,刻画其特征并分析未来可能气候条件下的演变趋势对事件防控有重要意义。本文提出了一种基于第六次国际耦合模式比较计划CMIP6耦合天气预报研究模式WRF的未来气象数据动力降尺度方法。识别了黄河上游不同情景下的复合干旱热浪事件及其特征,揭示了复合事件与单一事件的区别,分析了复合干旱热浪事件的未来演变规律。结果表明:(1)历史期、SSP245和SSP585情景下复合干旱热浪事件较单一事件的温度升高3.8%、13.1%、13.5%,干旱指数降低5.8%、2.6%、2.6%,极端特征更加显著。(2)SSP245情景下复合干旱热浪事件特征呈西南高、东北低的空间分布形式,而在SSP585情景下以北部、东部区域分布最高。(3)未来各情景下区域整体复合干旱热浪事件特征呈显著上升趋势,其中SSP585的上升趋势高于SSP245。

气候变化背景下赣江流域复合高温干旱事件时空演变特征

【目的】在气候变化背景下,全球多区域复合高温干旱事件频率与强度呈现增加趋势。系统揭示赣江流域复合高温干旱事件的时空演变特征,为灾害风险防范提供参考。【方法】采用1961—2021年的日最高温度和表层土壤含水量数据,评估赣江流域热浪、农业干旱和复合高温干旱事件的时空变化趋势,对比分析复合高温干旱事件与单独极端事件的特征差异。【结果】结果表明:赣江流域农业干旱事件频次呈下降趋势(-0.027场/10 a),热浪事件及复合高温干旱事件的频次呈上升趋势(0.084场/10 a、0.013场/10 a)。与1961—2000年相比,2001—2021年赣江流域农业干旱的发生频率在北部大部分区域有所下降,南部地区大部分区域有所增加;热浪事件的发生频率在全流域均呈增加趋势;复合高温干旱的发生频率在东北部有所下降,南部显著上升。与单独热浪事件和单独农业干旱事件相比,复合高温干旱下的热浪事件历时和烈度分别增加16.87%和26.25%,农业干旱事件历时和烈度分别增加10.65%和26.86%。【结论】赣江流域南部地区复合高温干旱事件发生频率显著增加;相比于单独的极端事件,复合高温干旱事件的危险性有所增强,未来应加强该区域的复合高温干旱风险防范能力。

Correcting Climate Model Sea Surface Temperature Simulations with Generative Adversarial Networks:Climatology,Interannual Variability,and Extremes

Climate models are vital for understanding and projecting global climate change and its associated impacts.However,these models suffer from biases that limit their accuracy in historical simulations and the trustworthiness of future projections.Addressing these challenges requires addressing internal variability,hindering the direct alignment between model simulations and observations,and thwarting conventional supervised learning methods.Here,we employ an unsupervised Cycle-consistent Generative Adversarial Network(CycleGAN),to correct daily Sea Surface Temperature(SST)simulations from the Community Earth System Model 2(CESM2).Our results reveal that the CycleGAN not only corrects climatological biases but also improves the simulation of major dynamic modes including the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole mode,as well as SST extremes.Notably,it substantially corrects climatological SST biases,decreasing the globally averaged Root-Mean-Square Error(RMSE)by 58%.Intriguingly,the CycleGAN effectively addresses the well-known excessive westward bias in ENSO SST anomalies,a common issue in climate models that traditional methods,like quantile mapping,struggle to rectify.Additionally,it substantially improves the simulation of SST extremes,raising the pattern correlation coefficient(PCC)from 0.56 to 0.88 and lowering the RMSE from 0.5 to 0.32.This enhancement is attributed to better representations of interannual,intraseasonal,and synoptic scales variabilities.Our study offers a novel approach to correct global SST simulations and underscores its effectiveness across different time scales and primary dynamical modes.

AMO对ENSO与初夏西太平洋海洋热浪年际关系的年代际调制作用

海洋热浪是发生在海洋上的极端高温事件,对海洋环境和生态系统具有破坏性影响。文章采用1960—2020年第五代欧洲中期天气预报中心再分析资料(European centre for medium-range weather forecasts reanalysis v5,ERA5)和英国气象局哈德来中心全球海冰和海洋表面温度资料集(Hadley centre global sea ie and sea surface temperature,HadISST)以及地球系统模式(community Earth system model,CESM1)北大西洋理想试验数据等,通过相关、合成分析等多种统计方法,研究了厄尔尼诺–南方涛动(El Niño-Southern Oscillation,ENSO)与次年初夏西太平洋海洋热浪年际关系的变化特征,并进一步探讨了二者关系发生年代际变化的可能成因。研究结果表明:1)ENSO与次年初夏西太平洋海洋热浪月数的年际关系具有明显的年代际变化特征,北大西洋多年代际振荡(Atantic multidecadal oscillation,AMO)是二者年际关系发生年代际变化的主要成因。当AMO处于正位相时,ENSO与次年初夏西太平洋海洋热浪存在显著的正相关关系,而当AMO处于负位相时,上述二者相关关系不再显著;2)AMO主要通过调控ENSO事件的强度进而影响西北太平洋大气环流的异常响应,从而进一步影响ENSO与次年初夏西太平洋海洋热浪之间的关系。当AMO处于负(正)位相时,相对较强(弱)的ENSO事件通过强(弱)风–蒸发–海温正反馈过程,使得ENSO事件次年初夏西北太平洋地区产生位置相对偏东(西)、强度相对偏强(弱)的异常反气旋/气旋。异常反气旋/气旋的位置和强度导致初夏西太平洋海洋热浪的分布在AMO正、负位相存在显著差异。

海洋热浪背景下海气湍流热通量资料的评估——以2019年东北太平洋“Blob 2.0”事件为例

2019年夏季,东北太平洋地区经历了一次名为“Blob 2.0”的海洋热浪事件,对海洋生态系统造成了严重影响。利用美国国家数据浮标中心的浮标观测资料、全球客观分析通量产品OAFlux,以及大气再分析数据集ERA5、NCEP2和MERRA-2,综合分析了“Blob 2.0”事件期间海气湍流热通量的特征,并研究了其物理因素。浮标观测显示,在“Blob 2.0”事件期间,潜热通量呈现正增长趋势,而感热通量呈现负增长趋势,这一现象可归因于海气比湿度差呈正增长,而风速和海气温差呈负增长。评估结果表明:4种通量数据产品都低估了潜热通量的增长,ERA5的增长率与浮标最为接近。对于感热通量,MERRA-2和NCEP2产品的增长趋势与浮标观测相同,其中MERRA-2的增长率更接近;而OAFlux和ERA5产品的增长趋势与观测相反。

基于深度学习的南海海表面温度的智能化预测研究

海表面温度(sea surface temperature,SST)是影响海洋和气候变化的重要因素之一,准确预测SST的变化对于海洋生态环境、气象和航行等至关重要。传统的SST预测方法通常依赖于数值模式,但是其计算成本较高。该文基于深度学习模型(3D U-Net),将SST、海表面高度异常(sea surface height anomalies,SSHA)以及海表面风(sea surface wind,SSW)作为输入变量成功构建了南海SST的快速化智能预报模型。结果表明,与卷积长短时记忆(convolutional long short-term memory,ConvLSTM)模型相比,3D U-Net模型在所有预测时间中均显示出更高的准确度,其均方根误差(RMSE)为0.53℃,皮尔逊相关系数(R)达到0.96。在不同季节和南海不同区域,3D U-Net模型均表现出较小的预测误差,而且在季风盛行期间也具有较强的鲁棒性。此外,3D U-Net模型在预测2021年南海的海洋热浪(marine heatwave,MHW)事件时,大部分海域的准确率达到了80%以上,总体上精确率和召回率分别为0.89和0.45。敏感性实验结果表明,SSHA和SSW对模型的预测性能有显著影响,并在不同的预报阶段中发挥着不同的作用。综上所述,结合多源海表数据的3D U-Net模型能够快速准确地预测出南海SST,并为预测MHW事件提供了新方法。

基于心血管疾病死亡效应的亚热带地区最佳热浪定义研究

目的本研究探索亚热带地区的热浪定义,系统评估热浪对福建省心血管疾病(cardiovascular disease,CVD)及其亚型死亡率的影响。方法收集2007-2015年福建省9个市66854例心血管疾病死亡数,联合分布滞后非线性模型(distributed lag non-linear model,DLNM)和类泊松回归模型评估热浪对各个市每日心血管疾病死亡的影响,然后用多元Meta分析计算综合效应。按CVD亚型、性别、年龄、婚姻和教育水平进行分层分析。结果热浪定义为连续≥4天日平均温度≥P 95拟合心血管疾病死亡的模型最佳。热浪效应是急剧的,热浪发生当天对CVD死亡的相对危险度为1.06(95%CI:1.01~1.12)、滞后1天为1.04(95%CI:1.00~1.07)、累计滞后0-1天相对危险度为1.10(95%CI:1.05~1.16)。热浪增加缺血性心脏病、慢性缺血性心脏病、脑血管疾病的死亡率,累计滞后0-1天的相对危险度分别为1.13(95%CI:1.04~1.23)、1.24(95%CI:1.08~1.43)和1.09(95%CI:1.02~1.16)。此外,≥65岁人群更容易受到热浪效应的影响。结论本研究认为在福建省热浪最佳定义为连续≥4天且日平均温度≥P 95,在该定义下热浪会增加CVD、缺血性心脏病、慢性缺血性心脏病、脑血管疾病的死亡率。此外,≥65岁人群是热浪对心血管疾病死亡效应的脆弱人群。

The 2022 Extreme Heatwave in Shanghai,Lower Reaches of the Yangtze River Valley:Combined Influences of Multiscale Variabilities

In the summer of 2022,China(especially the Yangtze River Valley,YRV)suffered its strongest heatwave(HW)event since 1961.In this study,we examined the influences of multiscale variabilities on the 2022 extreme HW in the lower reaches of the YRV,focusing on the city of Shanghai.We found that about 1/3 of the 2022 HW days in Shanghai can be attributed to the long-term warming trend of global warming.During mid-summer of 2022,an enhanced western Pacific subtropical high(WPSH)and anomalous double blockings over the Ural Mountains and Sea of Okhotsk,respectively,were associated with the persistently anomalous high pressure over the YRV,leading to the extreme HW.The Pacific Decadal Oscillation played a major role in the anomalous blocking pattern associated with the HW at the decadal time scale.Also,the positive phase of the Atlantic Multidecadal Oscillation may have contributed to regulating the formation of the double-blocking pattern.Anomalous warming of both the warm pool of the western Pacific and tropical North Atlantic at the interannual time scale may also have favored the persistency of the double blocking and the anomalously strong WPSH.At the subseasonal time scale,the anomalously frequent phases 2-5 of the canonical northward propagating variability of boreal summer intraseasonal oscillation associated with the anomalous propagation of a weak Madden-Julian Oscillation suppressed the convection over the YRV and also contributed to the HW.Therefore,the 2022 extreme HW originated from multiscale forcing including both the climate warming trend and air-sea interaction at multiple time scales.

The Drought of Amazonia in 2023-2024

The Amazon basin has experienced an extreme drought that started in the austral summer of 2022-23 and extends into 2024. This drought started earlier than other previous droughts. Although some rain fell during the austral summer, totals remained below average. Higher temperatures during austral winter and spring 2023, which affected most of Central South America, then aggravated drought conditions. This coincided with an intense El Niño and abnormally warm tropical North Atlantic Ocean temperatures since mid-2023. Decreased rainfall across the Amazon basin, negative anomalies in evapotranspiration (derived from latent heat) and soil moisture indicators, as well as increased temperatures during the dry-to-wet transition season, September-October-November (SON) 2023, combined to delay the onset of the wet season in the hydrological year 2023-24 by nearly two months and caused it to be uncharacteristically weak. SON 2023 registered a precipitation deficit of the order of 50 to 100 mm/month, and temperatures +3˚C higher than usual in Amazonia, leading to reduced evapotranspiration and soil moisture indicators. These processes, in turn, determined an exceptionally late onset and a lengthening of the dry season, affecting the 2023-2024 hydrological year. These changes were aggravated by a heat wave from June to December 2023. Drought-heat compound events and their consequences are the most critical natural threats to society. River levels reached record lows, or dried up completely, affecting Amazonian ecosystems. Increased risk of wildfires is another concern exacerbated by these conditions.

中国近海变暖和海洋热浪演变特征及气候成因研究进展

近几十年来,气候变化背景下中国近海海表面温度(SST)显著上升且极端高海温事件(海洋热浪)频发,时常造成海洋生物大规模死亡和赤潮暴发等生态灾害。为此,文章回顾分析了中国近海变暖及海洋热浪的相关研究进展,包括海温变化趋势和变率、海洋热浪演变特征和气候成因,以及相关影响,并探讨了应对策略。研究显示,1960~2022年,中国近海尤其是东中国海(渤海、黄海和东海)变暖趋势显著,SST分别上升了1.02℃±0.19℃、1.45℃±0.32℃,主要受到东亚季风减弱和黑潮入侵增强的影响;而SST年际和年代际变率还与厄尔尼诺与南方涛动(ENSO)和太平洋年代际涛动(PDO)等大尺度气候因子有关。中国近海变暖还引起地理等温线明显向北迁移,造成季节性物候发生变迁(春季提前和秋季滞后),并影响海洋生物生长节律、地理分布、群落结构和生态服务功能。自1982年以来,中国近海海洋热浪增多变强,最近十年(2010~2019年)尤其显著,其中,东中国海和南海(5~9月)海洋热浪平均发生频率分别是1980年代的20倍和4倍,并与热带印度洋偶极子和厄尔尼诺有较高的相关关系。趋频增强的海洋热浪对珊瑚礁等海洋生态系统和海水养殖业造成了灾难性的影响。研究还揭示,未来中国近海较高纬度海区将暴露于更强烈的升温、热浪、酸化、缺氧和生产力降低等综合影响下,海洋生态系统特别是南海珊瑚礁等生态系统面临突破气候临界点的风险。当前除应加强对中国近海变暖和海洋热浪物理过程、可预报性及预测预警等研究外,还亟需采取变革性和前瞻性的海洋气候行动与应对措施,增强海洋生态系统的气候恢复力,应对未来气候变化的影响。

长江中下游平原2022年高温干旱复合型极端事件的影响因子分析

基于ERA5和ERA5-LAND再分析资料,利用水量平衡分解法,将净降水量(降水量减蒸发量,P-E)的变化分解为热动力贡献、热力学贡献和涡动贡献,分析了2022年发生在长江中下游平原的极端干旱事件的机理和演变过程,并将其与2013年同样发生在长江中下游的高温干旱事件进行对比分析。净降水量分析表明,2022年长江中下游平原汛期前期(5—6月)干旱主要由降水量减小导致,水量平衡分解分析显示,湍流涡动与平均环流变化的贡献是早期干旱的主要因子;中期(7—8月)的高温增强了地表蒸散发,尤其是裸土蒸发的增强,加剧了干旱程度,水量平衡分解显示,表征温度升高引起的水汽含量变化的热力贡献对干旱加剧的贡献最大;后期(9—10月)高温进一步引发平均环流变化导致的热动力贡献延长了干旱持续时间。而2013年的高温干旱为高温引发的热力学贡献主导,持续事件短,干旱程度弱。本文对2022年发生在长江中下游平原的高温干旱复合型极端事件的发展和演变过程的剖析,可为湿润区极端高温干旱事件的预测预警提供参考。

Sources of Subseasonal Prediction Skill for Heatwaves over the Yangtze River Basin Revealed from Three S2S Models

Based on the reforecast data(1999–2010)of three operational models[the China Meteorological Administration(CMA),the National Centers for Environmental Prediction of the U.S.(NCEP)and the European Centre for Medium-Range Weather Forecasts(ECMWF)]that participated in the Subseasonal to Seasonal Prediction(S2S)project,we identified the major sources of subseasonal prediction skill for heatwaves over the Yangtze River basin(YRB).The three models show limited prediction skills in terms of the fraction of correct predictions for heatwave days in summer;the Heidke Skill Score drops quickly after a 5-day forecast lead and falls down close to zero beyond the lead time of 15 days.The superior skill of the ECMWF model in predicting the intensity and duration of the YRB heatwave is attributable to its fidelity in capturing the phase evolution and amplitude of high-pressure anomalies associated with the intraseasonal oscillation and the dryness of soil moisture induced by less precipitation via the land–atmosphere coupling.The effects of 10–30-day and 30–90-day circulation prediction skills on heatwave predictions are comparable at shorter forecast leads(10 days),while the biases in 30–90-day circulation amplitude prediction show close connection with the degradation of heatwave prediction skill at longer forecast leads(>15–20 days).The biases of intraseasonal circulation anomalies further affect precipitation anomalies and thus land conditions,causing difficulty in capturing extremely hot days and their persistence in the S2S models.