Assessing the Variability of Extreme Weather Events and Its Influence on Marine Accidents along the Northern Coast of Tanzania

The marine accidents are among the main components of the Zanzibar Disaster Management Policy (2011) and the Zanzibar Blue Economy Policy (2020). These policies aimed to institute legal frame works and procedures for reducing both the frequency of marine accidents and their associated fatalities. These fatalities include deaths, permanent disabilities and loss of properties which may result into increased poverty levels as per the sustainable development goal one (SDG1) which stipulates on ending the poverty in all its forms everywhere. Thus, in the way to support these Government efforts, the influence of climate and weather on marine accidents along Zanzibar and Pemba Channels was investigated. The study used the 10 years (2013-2022) records of daily rainfall and hourly wind speed acquired from Tanzania Meteorological Authority (TMA) (for the observation stations of Zanzibar, Pemba, Dares Salaam and Tanga), and the significant wave heights data, which was freely downloaded from Globally Forecasting System (GFS-World model of 13 km resolution). The marine accident records were collected from TASAC and Zanzibar Maritime Authority (ZMA), and the anecdotal information was collected from heads of quay and boat captains in different areas of Zanzibar. The Mann Kendal test, was used to determine the slopes and trends direction of used weather parameters, while the Pearson correlations analysis and t-tests were used to understand the significance of the underlying relationship between the weather and marine accidents. The paired t-test was used to evaluate the extent to which weather parameters affect the marine accidents. Results revealed that the variability of extreme weather events (rainfall, ocean waves and wind speed) was seen to be among the key factors for most of the recorded marine accidents. For instance, in Pemba high rainfall showed an increasing trend of extreme rainfall events, while Zanzibar has shown a decreasing trend of these events. As for extreme wind events, results show that Dar es Salaam and Tanga had an increasing trend, while Zanzibar and Pemba had shown a decreasing trend. As for the monthly variability of frequencies of extreme rainfall events, March to May (MAM) season was shown to have the highest frequencies over all stations with the peaks at Zanzibar and Pemba. On the other hand, high frequency of extreme wind speed was observed from May to September with peaks in June to July, and the highest strength was observed during 09:00 to 15:00 GMT. Moreover, results revealed an increasing trend of marine accidents caused by bad weather except during November. Also, results showed that bad weather conditions contributed to 48 (32%) of all 150 recorded accidents. Further results revealed significant correlation between the extreme wind and marine accidents, with the highest strong correlation of r = 0.71 (at p ≤ 0.007) and r = 0.75 (at p ≤ 0.009) at Tanga and Pemba, indicating the occurrence of more marine accidents at the Pemba channel. Indeed, strong correlation of r = 0.6 between extreme rainfall events and marine accidents was shown in Pemba, while the correlations between extremely significant wave heights and marine accidents were r = 0.41 (at p ≤ 0.006) and r = 0.34 (p ≤ 0.0006) for Pemba and Zanzibar Channel, respectively. In conclusion, the study has shown high influence between marine accidents and bad weather events with more impacts in Pemba and Zanzibar. Thus, the study calls for more work to be undertaken to raise the awareness on marine accidents as a way to alleviate the poverty and enhance the sustainable blue economy.

Crop Diversification in Coping with Extreme Weather Events in China

Apart from the long-term effects of climate change, the frequency and severity of extreme weather events have been increasing. Given the risks posed by climate change, particularly the changes in extreme weather events, the question of how to adapt to these changes and mitigate their negative impacts has received great attention from policy makers. The overall goals of this study are to examine whether farmers adapt to extreme weather events through crop diversification and which factors influence farmers＇ decisions on crop diversification against extreme weather events in China. To limit the scope of this study, we focus on drought and flood events only. Based on a unique large-scale household survey in nine provinces, this study finds that farmers respond to extreme weather events by increasing crop diversification. Their decision to diversify crops is significantly influenced by their experiences of extreme weather events in the previous year. Such results are understandable because farmers＇ behaviors are normally based on their expectations. Moreover, household characteristics also affect farmers＇ decisions on crop diversification strategy, and their effects differ by farmers＇ age and gender. This paper concludes with several policy implications.

Influence of the Arctic on the Predictability of Eurasian Winter Extreme Weather Events

The linkage between the Arctic and midlatitudes has received much attention recently due to the rapidly changing climate.Many investigations have been conducted to reveal the relationship between the Arctic and Eurasian extreme events from the perspective of climatological statistics.As a prediction source for extreme events in Eurasia,Arctic conditions are crucial for extreme event predictions.Therefore,it is urgent to explore the Arctic influence on the predictability of Eurasian extreme events due to the large uncertainties in Arctic conditions.Considering the sensitivity and nonlinearity of the atmospheric circulations in midlatitude to Arctic conditions,it is necessary to investigate the Arctic influences on Eurasian extreme weather events in case studies at weather time scales.Previous studies indicate that only perturbations in specific patterns have fast growth.Thus,the conditional nonlinear optimal perturbation approach is recommended for exploring the uncertainties in Arctic initial and boundary conditions and their synergistic effect on Eurasian extreme events.Moreover,the mechanism for extreme event formation may differ in different cases.Therefore,more extreme cases should be investigated to reach robust conclusions.

What determines irrigation efficiency when farmers face extreme weather events? A field survey of the major wheat producing regions in China

Water availability is a major constraint on grain production in China, therefore, improving irrigation efficiency is particularly important when agriculture faces extreme weather events. This paper first calculates irrigation efficiency with a translog stochastic frontier production function and then investigates what happens when extreme weather events occur via a Tobit model. The estimated results reveal several important features of irrigation practices: i) irrigation efficiency is lower when extreme weather events occur; ii) large variations in irrigation efficiency occur across irrigation facilities; iii) the farm plots exhibit an extreme distribution across efficiency levels; and iv) water-saving techniques, technology adoption, and the maintenance of farmers’ economic resilience are major determinants of irrigation efficiency. Based on these results we propose the following recommendations: i) farmers should balance crop yield and water use; undertake relevant training programs and adopt water-saving techniques; ii) local governments and researchers should help farmers to find the optimal level of irrigation water use based on their own circumstances and provide better water-saving techniques and training programs rather than simply encouraging farmers to invest in irrigation facilities in the most extreme weather years; and iii) the income level of farm households should be increased so as to improve their resilience to natural disasters.

Extreme Weather and Climate Events and Their Impacts on Island Countries in the Western Pacific: Cyclones, Floods and Droughts

Increases in the frequency of extreme weather and climate events and the severity of their impacts on the natural environment and society have been observed across the globe in recent decades. In addition to natural climate variability and greenhouse-induced climate change, extreme weather and climate events produce the most pronounced impacts. In this paper, the climate of three island countries in the Western Pacific: Fiji, Samoa and Tuvalu, has been analysed. Warming trends in annual average maximum and minimum temperatures since the 1950s have been identified, in line with the global warming trend. We present recent examples of extreme weather and climate events and their impacts on the island countries in the Western Pacific: the 2011 drought in Tuvalu, the 2012 floods in Fiji and a tropical cyclone, Evan, which devastated Samoa and Fiji in December 2012. We also relate occurrences of the extreme weather and climate events to phases of the El Niño-Southern Oscillation (ENSO) phenomenon. The impacts of such natural disasters on the countries are severe and the costs of damage are astronomical. In some cases, climate extremes affect countries to such an extent that governments declare a national state of emergency, as occurred in Tuvalu in 2011 due to the severe drought’s impact on water resources. The projected increase in the frequency of weather and climate extremes is one of the expected consequences of the observed increase in anthropogenic greenhouse gas concentration and will likely have even stronger negative impacts on the natural environment and society in the future. This should be taken into consideration by authorities of Pacific Island Countries and aid donors when developing strategies to adapt to the increasing risk of climate extremes. Here we demonstrate that the modern science of seasonal climate prediction is well developed, with current dynamical climate models being able to provide skilful predictions of regional rainfall two-three months in advance. The dynamic climate model-based forecast products are now disseminated to the National Meteorological Services of 15 island countries in the Western Pacific through a range of web-based information tools. We conclude with confidence that seasonal climate prediction is an effective solution at the regional level to provide governments and local communities of island nations in the Western Pacific with valuable assistance for informed decision making for adaptation to climate variability and change.

Characteristics of air pollution events over Hotan Prefecture at the southwestern edge of Taklimakan Desert, China

Hotan Prefecture is located at the southwestern edge of Taklimakan Desert, the world＇s largest shifting sand desert, of China. The desert is one of the main sources for frequent sand-dust weather events which strongly affect the air quality of Hotan Prefecture. Although this region is characterized by the highest annual mean PMlo concentration values that are routinely recorded by environmental monitoring stations across China, both this phenomenon and its underlying causes have not been adequately addressed in previous researches. Reliable pollutant PM_10 data are currently retrieved using a tapered element oscillating microbalance （TEOM） 1400a, a direct real-time monitor, while additional concentration values including for PM_2.5, sulfur dioxide （SO_2）, nitrogen dioxide （NO_2）, carbon monoxide （CO） and ozone （O_3） have been collected in recent years by the Hotan Environmental Monitoring Station. Based on these data, this paper presents a comparison of the influences of different kinds of sand-dust weather events on PM_10 （or PM_2.5） as well as the concentrations of other gaseous pollutants in Hotan Prefecture. It is revealed that the highest monthly average PM_10 concentrations are observed in the spring because of the frequent occurrence of three distinct kinds of sand-dust weather events at this time, including dust storms, blowing dust and floating dust. The floating dust makes the most significant contribution to PM_10 （or PM_2.5） concentration in this region, a result that differs from eastern Chinese cities where the heaviest PM_10 pollution occurs usually in winter and air pollution results from the excess emission of local anthropogenic pollutants. It is also shown that PM_10 concentration varies within wpical dust storms. PM_10 concentrations vary among 20 dust storm events within Hotan Prefecture, and the hourly mean concentrations tend to sharply increase initially then slowly decreasing over time. Data collected from cities in eastern China show the opposite with the hourly mean PM_10 （or PM_2.5） concentration tending to slowly increase then sharply decrease during heavy air pollution due to the excess emission of local anthropogenic pollutants. It is also found that the concentration of gaseous pollutants during sand-dust weather events tends to be lower than those cases under clear sky conditions. This indicates that these dust events effectively remove and rapidly diffuse gaseous pollutants. The analysis also shows that the concentration of SO_2 decreases gradually at the onset of all three kinds of sand-dust weather events because of rapidly increasing wind velocity and the development of favorable atmospheric conditions for diffusion. In contrast, changes in O_3 and NO_2 concentrations conformed to the opposite pattern during all three kinds of sand-dust weather events within this region, implying the inter transformation of these gas species during these events.

Extreme Cold Events from East Asia to North America in Winter 2020/21:Comparisons,Causes,and Future Implications

Three striking and impactful extreme cold weather events successively occurred across East Asia and North America during the mid-winter of 2020/21.These events open a new window to detect possible underlying physical processes.The analysis here indicates that the occurrences of the three events resulted from integrated effects of a concurrence of anomalous thermal conditions in three oceans and interactive Arctic-lower latitude atmospheric circulation processes,which were linked and influenced by one major sudden stratospheric warming(SSW).The North Atlantic warm blob initiated an increased poleward transient eddy heat flux,reducing the Barents-Kara seas sea ice over a warmed ocean and disrupting the stratospheric polar vortex(SPV)to induce the major SSW.The Rossby wave trains excited by the North Atlantic warm blob and the tropical Pacific La Nina interacted with the Arctic tropospheric circulation anomalies or the tropospheric polar vortex to provide dynamic settings,steering cold polar air outbreaks.The long memory of the retreated sea ice with the underlying warm ocean and the amplified tropospheric blocking highs from the midlatitudes to the Arctic intermittently fueled the increased transient eddy heat flux to sustain the SSW over a long time period.The displaced or split SPV centers associated with the SSW played crucial roles in substantially intensifying the tropospheric circulation anomalies and moving the jet stream to the far south to cause cold air outbreaks to a rarely observed extreme state.The results have significant implications for increasing prediction skill and improving policy decision making to enhance resilience in“One Health,One Future”.

A research progress review on regional extreme events

An extreme （weather and climate） event does not only mean that an extreme occurs at a location, but more generally it can impact a certainarea and last a certain period of time, which is defined as a regional extreme event （REE） with a certain impacted area and duration. The conceptof REE has been defined to allow mainly objective assessment of the events without a pre-determined boundary and duration. This paper reviewsthe studies on REEs published during the past 20 years, especially recent years. Mainly in view of methodology, these studies can be divided intothree types studies focusing on spatial simultaneity, studies focusing on temporal persistence, and studies identifying REEs. The methodsidentifying REEs include two kinds, e.g., type-I methods stressing REE＇s temporal persistence within a relatively certain area and type-IImethods focusing on catching a complete REE. Identification methods proposed in this paper could provide valuable information for variouspurposes, such as real-time monitoring, estimating long-term changes, mechanism diagnosis, forecasting study and even attribution analysis.Research on REEs is important for objectively defining extreme weather and climate events, which depends on the spatial and temporal scales ofinterest. Such an objective definition will support ongoing climate monitoring and improve the assessment of how regional extreme events havechanged over time.

Increases in Anthropogenic Heat Release from Energy Consumption Lead to More Frequent Extreme Heat Events in Urban Cities

With economic development and rapid urbanization,increases in Gross Domestic Product and population in fastgrowing cities since the turn of the 21st Century have led to increases in energy consumption.Anthropogenic heat flux released to the near-surface atmosphere has led to changes in urban thermal environments and severe extreme temperature events.To investigate the effects of energy consumption on urban extreme temperature events,including extreme heat and cold events,a dynamic representation scheme of anthropogenic heat release(AHR)was implemented in the Advanced Research version of the Weather Research and Forecasting(WRF)model,and AHR data were developed based on energy consumption and population density in a case study of Beijing,China.Two simulations during 1999−2017 were then conducted using the developed WRF model with 3-km resolution with and without the AHR scheme.It was shown that the mean temperature increased with the increase in AHR,and more frequent extreme heat events were produced,with an annual increase of 0.02−0.19 days,as well as less frequent extreme cold events,with an annual decrease of 0.26−0.56 days,based on seven extreme temperature indices in the city center.AHR increased the sensible heat flux and led to surface energy budget changes,strengthening the dynamic processes in the atmospheric boundary layer that reduce AHR heating efficiency more in summer than in winter.In addition,it was concluded that suitable energy management might help to mitigate the impact of extreme temperature events in different seasons.

Coordinating Preventive Strategies and Restoration under Extreme Weather Conditions

It has been well identified that the extreme events significantly impact the system operation. In this work, a comprehensive operating strategy, which coordinates the preventive strategies and system restoration, was proposed. A re-dispatch model that limits the potential loss under extreme events, as well as provides adequate resources for system restoration after the extreme events, was proposed. An optimal power flow based method was established to solve the proposed model. The availabilities of components and the remaining system due to the extreme events were restored by extending the EPRI’s System Restoration Navigator (SRN) with a little modification. Case studies demonstrate the proposed model and methods.

Numerical Simulation and Analysis of Storm Surges Under Different Extreme Weather Event and Typhoon Experiments in the South Yellow Sea

In this study,a coupled tide-surge-wave model was developed and applied to the South Yellow Sea.The coupled model simulated the evolution of storm surges and waves caused by extreme weather events,such as tropical cyclones,cold waves,extratropical cyclones coupled with a cold wave,and tropical cyclones coupled with a cold wave.The modeled surge level and significant wave height matched the measured data well.Simulation results of the typhoon with different intensities revealed that the radius to the maximum wind speed of a typhoon with 1.5 times wind speed decreased,and its influence range was farther away from the Jiangsu coastal region;moreover,the impact on surge levels was weakened.Thereafter,eight hypothetical typhoons based on Typhoon Chan-hom were designed to investigate the effects of varying typhoon tracks on the extreme value and spatial distribution of storm surges in the offshore area of Jiangsu Province.The typhoon along path 2 mainly affected the Rudong coast,and the topography of the Rudong coast was conducive to the increase in surge level.Therefore,the typhoon along path 2 induced the largest surge level,which reached up to 2.91 m in the radial sand ridge area.The maximum surge levels in the Haizhou Bay area and the middle straight coastline area reached up to 2.37 and 2.08 m,respectively.In terms of typhoons active in offshore areas,the radial sand ridge area was most likely to be threatened by typhoon-induced storm surges.

Relationship between sand-dust weather and water dynamics of desert areas in the middle reaches of Heihe River

Sand-dust weather has become an international social-environmental issue of common concern, and constitutes a serious threat to human lives and economic development. In order to explore the responses of natural desert sand and dust to the dynamics of water in desertification, we extracted long-term monitoring data related to precipitation, soil water, groundwater, and sand-dust weather. These data originated from the test stations for desertification control in desert areas of the middle reaches of the Heihe River. We used an algorithm of characteristic parameters, correlations, and multiple regression analysis to establish a regression model for the duration of sand-dust weather. The response char-acteristics of the natural desert sand and dust and changes of the water inter-annual and annual variance were also examined. Our results showed： （1） From 2006 to 2014 the frequency, duration, and volatility trends of sand-dust weather obviously increased, but the change amplitudes of precipitation, soil water, and groundwater level grew smaller. （2） In the vegetative growth seasons from March to November, the annual variance rates of the soil moisture content in each of four studied layers of soil samples were similar, and the changes in the frequency and duration of sand-dust weather were similar. （3） Our new regression equation for the duration of sand-dust weather passed the R test, F test, and t test. By this regression model we could predict the duration of sand-dust weather with an accuracy of 42.9%. This study can thus provide technological support and reference data for water resource management and re-search regarding sand-dust weather mechanisms.

Characteristics and spatial distribution of strong warming events in the central Arctic(2000-2019)

Arctic amplification in the context of global warming has received considerable attention,and mechanisms such as ice-albedo feedback and extratropical cyclone activity have been proposed to explain such abnormal warming.Since 2000,several short-term episodes of significant temperature rise have been observed in the Arctic;however,long-duration warming events in the central Arctic are less common and lack comprehensive research.Previous studies identified that amplified Rossbywaves could connect Arctic warming with extreme weather events in mid-latitude regions,and thus the recent increase in the frequency of mid-latitude extreme weather is also a subject of intensive research.With consideration of temperature anomalies,this study defined a continuous warming process as a warming event and selected strong warming events based on duration.Analysis of National Centers for Environmental Prediction Reanalysis-2 surface air temperature data found that nine strong warming events occurred during 2000-2019,which could be categorized into three types based on the area of warming.This study also investigated the relation between strong warming events and sea ice concentration reduction,sudden stratospheric warming,and extratropical cyclone activities.After full consideration and comparison,we believe that strong warming events in the central Arctic are induced primarily by continuous transport of warm air from mid-latitude ocean areas.

Correlation of icing events with meteorological variables,and two statistical models to discriminate freezing days

In this paper, the characteristics of meteorological variables are statistically correlated with icing events （i.e., glaze and rime） in China, using daily observations of air temperature, relative humidity, wind speed, and weather phenomena from 700 stations in China from 1954 to 2008. The weather conditions most favorable for icing events are investigated and two statistical models are developed to discriminate potential freezing days. Low air temperature, high relative humidity, and low wind speed are shown to be important conditions for occurrence of icing events; also, the favorable daily mean air temperature is shown to have a decreasing trend from north to south in China, while the favorable relative humidity and wind speed varies little across the country. The statistical model developed with the daily mean temperature combined with precipitation, fog, and mist weather phenomena proved to be well able to determine the possible occurrence of freezing days. The accuracy of model outputs is well above 60% for northwestem Yun- nan, Guizhou, northern Guangxi, southern Hunan, and southern Jiangxi, among other regions where icing events are more fre- quent, and the average false alarms are few. Using observations or forecast products of conventional meteorological variables, this model has high performance and is practical and applicable for early warning and monitoring of icing events.

2023年中国气候异常特征及主要天气气候事件

2023年,我国气候主要表现为暖干的特征,全国平均气温10.71℃,较1991—2020年气候平均偏高0.82℃,为1951年以来最暖;全国平均降水量615.0 mm,较常年偏少3.9%,为2012年以来第二少。四季气温均较常年同期偏高,其中夏、秋季分别为历史同期次高和最高;除秋季降水偏多外,其余三季降水均偏少。汛期(5—9月),全国平均降水量较常年同期偏少4.3%,为2012年以来第二少,我国中东部降水总体呈“中间多南北少”的分布。2023年,我国区域性气象干旱多发,西南地区遭遇冬春连旱;春季北方沙尘天气过程偏多;夏季前期,华北和黄淮遭受1961年以来最强高温过程;7月底至8月初,受台风杜苏芮影响,京津冀地区发生历史罕见极端强降水过程,华北地区出现“旱涝急转”;华西秋雨开始早、结束晚、雨量多;1月中旬发生年内最强寒潮过程;秋末冬初冷空气频繁入侵,12月华北和黄淮等地降雪日数偏多、积雪偏深。

中国极端天气气候研究——“地球系统与全球变化”重点专项项目简介及最新进展

全球变暖背景下,极端天气气候事件频发,并表现出群发性、持续性、复合性等特点,不可预测性增加;持续性强降水、极端低温、复合型极端高温干旱、群发性热浪和台风等极端天气气候事件对我国经济社会和可持续发展影响巨大。然而,上述极端天气气候事件的新特征、关键过程和机理尚不完全清楚,重大极端事件的预报预测水平亟待提升。文章首先简要介绍“地球系统与全球变化”重点专项项目“中国极端天气气候事件的形成机理及其预测和归因”的基本情况。项目拟在分析全球变化背景下对我国造成重大影响的极端天气气候事件新特征的基础上,深入研究多尺度海-陆-气耦合过程影响极端天气气候事件的机理,挖掘极端天气气候事件次季节-季节预测的前兆信号;发展动力与物理统计相结合的极端事件预测新方法,研制针对中国极端事件的新一代高分辨率数值预报与检测归因系统。文章重点总结了自2022年12月项目立项至今取得的最新研究成果和进展。

位涡源汇和位涡环流及其天气气候意义

在扼要回顾地表位涡研究进展的基础上,本文介绍了复杂地形下的位涡及位涡制造的计算及近年来关于位涡源汇和位涡环流(PVC)的研究进展,侧重介绍青藏高原表层位涡的特殊性及其对天气气候的重要影响。阐明对于绝热和无摩擦大气运动,由于位涡本身的结构重组(位涡重构)可以引起垂直涡度的发展,在夏季可以激发高原涡形成,冬季使青藏高原东部成为重要的表面涡源。基于导得的包括非绝热加热作用的、与等熵面的位移相联系的垂直运动(ωID)方程,进一步阐明青藏高原制造的正位涡沿西风气流东传会引起下游地区低空气旋性涡度、偏南风、和上升运动发展,导致位涡平流随高度增加,激发极端天气气候事件发生发展。指出青藏高原地表加热和云底的潜热释放的日变化显著地影响着地表层位涡的日变化,导致青藏高原的低涡降水系统多在午后至夜间发生发展。证明与传统的青藏高原感热加热指数相比,青藏高原地表层位涡指数能够更好地刻画关于降水的季节变化,与亚洲夏季风降水相关更密切。本文还简单介绍了PVC的概念。指出由于区域边界面的PVC的辐散辐合的变化直接与区域位涡的变化相关联,为保持北半球位涡总量的相对稳定,跨赤道面上的PVC变化与地表PVC的变化必须相互补充,因此跨赤道面上的位涡环流的变化可以成为监测近地表气候变化的窗口。近赤道的海气相互作用能够直接造成沿赤道垂直面上的纬向风垂直切变的变化,激发跨赤道位涡环流异常,从而通过大气内部PVC的变化和青藏高原的调控影响北半球近地表的气候变化。结果表明位涡环流分析为建立热带和热带外大气环流变化的联系开辟了新的蹊径,有着广阔的应用前景。

近60 a中国极端天气气候事件变化趋势及2023年特征分析

对不同区域极端天气气候事件变化规律的研究,有助于提高我国防灾减灾能力和有效应对气候变化风险。利用我国均一化的2254个气象观测站逐日观测资料,分析评估近60 a和2023年我国及其各区域(未包含港澳台地区)发生的极端高温、极端低温、极端干旱、极端降水和极端台风等极端天气气候事件(简称“极端事件”)的时空特征。结果表明,1961年以来,我国极端事件总体呈下降趋势,其中1970—1990年代初下降趋势明显,1990年代后期以来增加趋势明显;极端高温事件呈显著增加趋势,进入21世纪后增加趋势更加明显;极端低温事件呈减少趋势;极端降水事件总体呈增加趋势;极端干旱事件呈下降趋势且阶段性特征明显;近60 a来受台风影响出现的极端风速和降水事件呈减少趋势,主要由极端台风风速事件减少造成,而极端台风降水事件呈缓慢上升趋势。2023年我国极端事件每站平均发生139次,比气候平均值偏多28.3%。其中,极端高温事件平均发生79次(偏多76.8%),为1961年以来历史最多年;极端低温事件平均发生20次(偏少23.8%);极端降水事件平均发生14次,极端干旱事件平均发生26次,都接近常年平均值;极端台风事件平均发生0.41次(偏多4.2%),主要以极端台风降水事件为主。2023年极端事件主要出现在西南地区、江南西部、华南西部、西北地区中部和北部、内蒙西部、京津冀等地,其中四川东部、贵州南部、甘肃西部、内蒙西部等地超过200次。极端事件增多的主要原因是极端高温事件和极端干旱事件增多。综合等级指数分析表明,极端事件高危险区域主要位于南方地区,特别是东南沿海地区,近60 a综合等级指数增加的区域主要位于西南地区到东北地区南部这个过渡带上。2023年高危险区域主要出现在西南地区和西北地区中北部。

2023年全球重大天气气候事件

2023年,全球平均气温比工业化前高出约1.45℃(±0.12℃),是有观测记录以来最热的一年。全球海平面继续上升,且全球平均海平面达到了有卫星记录(1993年至今)以来的最高水平,反映了持续的海洋变暖以及冰川和冰盖的融化。北极海冰面积仍远低于常年值,南极海冰面积创下历史新低。巴基斯坦、中国京津冀地区、意大利、巴西圣保罗州北部沿海地区、新西兰北岛等地遭受暴雨洪涝灾害,非洲西北部、中国云南、中美洲和南美洲北部发生严重干旱,南欧、北美、南美、东亚和南亚等地遭遇创纪录高温热浪,欧洲和北美等地遭遇寒流和暴风雪侵袭,强对流天气频繁袭击世界各处,全球热带气旋活动频繁。

北极—中纬度联系与北极海冰变化的关系研究新进展

本文概要介绍了近年来(2018~2023年),北极—中纬度联系与北极海冰变化的关系研究新进展。主要包括以下几个方面:(1)对北极海冰融化在欧洲极端降雪个例中的贡献有了实质性的认识,这是以往研究提出的北极海冰影响大气环流的机制所无法解释的。(2)冬季亚洲区域气温对北极海冰持续融化的响应有显著的低频振荡特征。北极海冰持续融化,有利于冬季暖北极—冷欧亚(2004/2005~2012/2013年)和暖北极—暖欧亚(2013/2014~2016/2017年)交替出现。前一阶段北极—中纬度联系加强,而暖北极—暖欧亚阶段北极与东亚的联系减弱了,但海冰融化影响北极—欧亚大陆联系强弱变化的机理不清楚。(3)在夏季平均和季节内时间尺度上,东亚中、低纬度区域夏季高温热浪极端天气事件与同期北极对流层中、低层冷异常有直接的动力联系。北极夏季对流层中、低层冷异常不仅有利于减缓北极海冰融化,而且成为预测后期东亚冬季风趋势的前兆因子。(4)北极夏季海冰融化异常,对我国华北以南区域夏季降水并无实质性影响。(5)尽管诸多研究强调了平流层—对流层相互作用,在连接北极海冰融化与中纬度天气气候中起重要作用,但因果联系依然偏弱,不确定性大于对流层过程。(6)区分北极海冰强迫与大气内部变率在天气事件和气候变率中的不同作用已无实际意义。未来关注北极海冰融化的影响,更应注重其在大气环流低频变化中的作用,以及北极海冰异常空间分布差异和不同异常振幅的影响,同时需要定量化研究北极海冰融化在极端天气和气候事件中的作用。