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.

Effects of Extreme Weather Conditions on the Growth of Gongcheng Persimmon

The superior climate conditions gave birth to excellent GongCheng per- simmon, and persimmon industry has become a pillar industry of Gongcheng farm- ers. In order to study the effects of extreme weather conditions on the growth of GongCheng persimmon, 60 years of meteorological data and the basic cultivation information of persimmon over the years in Gongcheng County were collected and analyzed using factor corresponding analysis method, so as to study the extreme weather conditions, the influence mechanism on persimmon industry and the de- fense measures. The extreme weather conditions that have great effects are the continuous low temperature in spring, high temperature in summer, strong wind, hail, rainstorm, drought, and frost, which can affect the persimmon tree vigor, fruit bearing rate, plant diseases and pests as well as the quality of fruit. Focusing on mete- orological service, it needs to avoid the meteorological disasters as far as possible from orchard construction to management to ensure high quality and yield of persimmon.

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.

Urbanization Impact on Regional Climate and Extreme Weather:Current Understanding,Uncertainties,and Future Research Directions

Urban environments lie at the confluence of social,cultural,and economic activities and have unique biophysical characteristics due to continued infrastructure development that generally replaces natural landscapes with built-up structures.The vast majority of studies on urban perturbation of local weather and climate have been centered on the urban heat island(UHI)effect,referring to the higher temperature in cities compared to their natural surroundings.Besides the UHI effect and heat waves,urbanization also impacts atmospheric moisture,wind,boundary layer structure,cloud formation,dispersion of air pollutants,precipitation,and storms.In this review article,we first introduce the datasets and methods used in studying urban areas and their impacts through both observation and modeling and then summarize the scientific insights on the impact of urbanization on various aspects of regional climate and extreme weather based on more than 500 studies.We also highlight the major research gaps and challenges in our understanding of the impacts of urbanization and provide our perspective and recommendations for future research priorities and directions.

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.

Sustainable city development challenged by extreme weather in a warming world

The year of 2021 has witnessed many extreme weather events across the world that have shocked and challenged human society,in particular for the populous cities,challenging progress on sustainable city development.In the comment we highlighted the record-breaking rainstorm that is considered to happen only“once-in-a-thousand-years”on 20 July 2021 in Zhengzhou,China;and a series of short and long-term resilience enhancement and risk reducing measures to climate change and natural hazard risks.We found that increasing frequency and intensity of extreme weather events caused by human-induced climate change challenges progress on sustainable city development,but could also accelerate activities to enable cities to become more resilient.This comment is essential to advance towards the sustainable city development goal(SDG 11)in China’s mega cities,as well as informing progress for other global cities.

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.

Extreme Weather Disruptions and Emergency Preparedness Among Older Adults in Ohio: An Eight-County Assessment

The disproportionate risks and impacts of climate change and extreme weather on older adults are increasingly evident. While especially true in disaster-prone areas, human-caused climate change introduces an element of uncertainty even in previously identified “safe” regions such as the Midwestern United States. Using a cumulative disadvantage and vulnerability-informed framework and descriptive statistics from multiple data sources, this article provides an overview of climate impacts, vulnerabilities, and county-level characteristics, focusing on older adults living in Central Ohio. A comparative multiple-case study methodology was used to triangulate regionally representative primary and secondary data sources to examine state and county-level measures of vulnerability, emergency preparedness, and disruptions caused by extreme weather among older adults across eight counties in Central Ohio. Seventy-eight percent of older adults in the sample reported being prepared for emergencies per Federal Emergency Management Agency guidelines. Older adults in Union County reported the highest rates of preparedness, while those in Fayette County reported the lowest. County-level rates of disruption of life activities by extreme weather ranged widely. Among the most rural in the region, Fayette County emerged as uniquely disadvantaged, with the lowest median income, the most vulnerable across multiple social vulnerability dimensions, and the most reported disruptions to life activities from extreme weather. County profiles offer a snapshot of existing vulnerabilities, socioeconomic conditions, special needs, preparedness, and current disruptions among older adults in the region and can inform resource mobilization across community and policy contexts.

2023: Weather and Climate Extremes Hitting the Globe with Emerging Features

Globally,2023 was the warmest observed year on record since at least 1850 and,according to proxy evidence,possibly of the past 100000 years.As in recent years,the record warmth has again been accompanied with yet more extreme weather and climate events throughout the world.Here,we provide an overview of those of 2023,with details and key background causes to help build upon our understanding of the roles of internal climate variability and anthropogenic climate change.We also highlight emerging features associated with some of these extreme events.Hot extremes are occurring earlier in the year,and increasingly simultaneously in differing parts of the world(e.g.,the concurrent hot extremes in the Northern Hemisphere in July 2023).Intense cyclones are exacerbating precipitation extremes(e.g.,the North China flooding in July and the Libya flooding in September).Droughts in some regions(e.g.,California and the Horn of Africa)have transitioned into flood conditions.Climate extremes also show increasing interactions with ecosystems via wildfires(e.g.,those in Hawaii in August and in Canada from spring to autumn 2023)and sandstorms(e.g.,those in Mongolia in April 2023).Finally,we also consider the challenges to research that these emerging characteristics present for the strategy and practice of adaptation.

Photovoltaic Power Generation Power Prediction under Major Extreme Weather Based on VMD-KELM

The output of photovoltaic power stations is significantly affected by environmental factors,leading to intermittent and fluctuating power generation.With the increasing frequency of extreme weather events due to global warming,photovoltaic power stations may experience drastic reductions in power generation or even complete shutdowns during such conditions.The integration of these stations on a large scale into the power grid could potentially pose challenges to systemstability.To address this issue,in this study,we propose a network architecture based on VMDKELMfor predicting the power output of photovoltaic power plants during severe weather events.Initially,a grey relational analysis is conducted to identify key environmental factors influencing photovoltaic power generation.Subsequently,GMM clustering is utilized to classify meteorological data points based on their probabilities within different Gaussian distributions,enabling comprehensive meteorological clustering and extraction of significant extreme weather data.The data are decomposed using VMD to Fourier transform,followed by smoothing processing and signal reconstruction using KELM to forecast photovoltaic power output under major extreme weather conditions.The proposed prediction scheme is validated by establishing three prediction models,and the predicted photovoltaic output under four major extreme weather conditions is analyzed to assess the impact of severe weather on photovoltaic power station output.The experimental results show that the photovoltaic power output under conditions of dust storms,thunderstorms,solid hail precipitation,and snowstorms is reduced by 68.84%,42.70%,61.86%,and 49.92%,respectively,compared to that under clear day conditions.The photovoltaic power prediction accuracies,in descending order,are dust storms,solid hail precipitation,thunderstorms,and snowstorms.

Resilience Building and Collaborative Governance for Climate Change Adaptation in Response to a New State of More Frequent and Intense Extreme Weather Events

The weather conditions of the summer of 2022 were very unusual,particularly in Eastern Asia,Europe,and North America.The devasting impact of climate change has come to our attention,with much hotter and drier conditions,and with more frequent and intense flooding events.Some extreme events have reached a dangerous level,increasingly threatening human lives.The interconnected risks caused by these extreme disaster events are triggering a chain effect,forcing us to respond to these crises through changes in our living environment,which affect the atmosphere,the biosphere,the economy including the availability of energy,our cities,and our global society.Moreover,we have to confront the abnormal consequences of untypical,rapid changes of extreme events and fast switches between extreme states,such as from severe drought to devastating flooding.Recognizing this new situation,it is crucial to improve the adaptation capacity of our societies in order to reduce the risks associated with climate change,and to develop smarter strategies for climate governance.High-quality development must be science-based,balanced,safe,sustainable,and climate-resilient,supported by the collaborative governance of climate mitigation and adaptation.This article provides some recommendations and suggestions for resilience building and collaborative governance with respect to climate adaptation in response to a new planetary state that is characterized by more frequent and severe extreme weather events.

Extreme weather as a window:Exploring the seek and supply of climate change information during meteorological disasters in China

Public engagement is essential for China to address climate change;however,few studies have explored how to encourage climate awareness among Chinese residents.The objective of this study is to explore the role of local extreme weather in advancing Chinese people's climate change awareness.Whether local extreme weather functions as an opportunity to trigger the public's interest in climate change across China and whether the local online information environment resonances with extreme weather by providing climate change news feeds have been examined by a combination of city-level meteorological warnings and search engine data.The results have verified that residents from 50 of the 360 cities show increasing concern for climate change when an extreme weather event occurs locally;however,only the online information environment of two cities echoes local extreme weather by providing more information about climate change or global warming.Correlations between extreme weather events such as heavy rain,an extreme weather event that has occurred in China,and climate change are underestimated.The effect of extreme cold events and snowfall on climate change awareness should also be noted more in China.This study suggests there is still a lot of room for improvement regarding both increasing and satisfying the public's pre-existing climate change-related concerns.A promising approach would be adopting climate change prevention and adaptation as a news report framework for extreme weather events.

Coastal hypoxia response to the coupling of catastrophic flood,extreme marine heatwave and typhoon:a case study off the Changjiang River Estuary in summer 2020

Massive bodies of low-oxygen bottom waters are found in coastal areas worldwide,which are detrimental to coastal ecosystems.In summer 2020,the response of coastal hypoxia to extreme weather events,including a catastrophic flooding,an extreme marine heatwave,and Typhoon Bavi,is investigated based on multiple satellite,four cruises,and mooring observations.The extensive fan-shaped hypoxia zone presents significant northward extension during July-September 2020,and is estimated as large as 13 000 km^(2) with rather low oxygen minimum(0.42 mg/L) during its peak in 28-30 August.This severe hypoxia is attributed to the persistent strong stratification,which is indicated by flood-induced larger amount of riverine freshwater input and subsequent marine heatwave off the Changjiang River Estuary.Moreover,the Typhoon Bavi has limited effect on the marine heatwave and coastal hypoxia in summer 2020.

Analysis of Extreme Precipitation Weather Process in Henan during July 17-22, 2021

To learn more about the unusually heavy rainfall in central China, this research uses the monthly climatic data, weather map information and US NCEP re-analysis data to analyze the atmospheric circulation, precipitation and weather situation of this extreme precipitation weather process in Henan during July 17-22, 2021. The results show that the precipitation process is affected by the joint action of the subtropical high, the continental high, the low vortex, the low-level jet, the typhoon “In-fa” and other multi-scale systems in the middle and low latitudes. This precipitation process was also affected by the topographic uplift and blocking of Taihang Mountain and Funiu Mountain.

Extreme Weather Loss and Damage Estimation Using a Hybrid Simulation Technique

History has shown that occurrences of extreme weather are becoming more frequent and with greater impact,regardless of one's geographical location.In a risk analysis setting,what will happen,how likely it is to happen,and what are the consequences,are motivating questions searching for answers.To help address these considerations,this study introduced and applied a hybrid simulation model developed for the purpose of improving understanding of the costs of extreme weather events in the form of loss and damage,based on empirical data in the contiguous United States.Model results are encouraging,showing on average a mean cost estimate within 5%of the historical cost.This creates opportunities to improve the accuracy in estimating the expected costs of such events for a specific event type and geographic location.In turn,by having a more credible price point in determining the cost-effectiveness of various infrastructure adaptation strategies,it can help in making the business case for resilience investment.

Extreme Measures for Extreme Weather

Effective disaster prevention and response have become top priorities for local governments across China For three days,a torrential downpour pounded Wangmo,a small mountainous county in southwest China’s Guizhou Province.The June 3-5

Extreme Weather Marks 2010

Most unusual weather of new century during last year Last year’s weather was the most unusual so far this century, according to

Detecting Climate Change in Using Extreme Data from Two Surface Weather Stations: Case Study Valle of Comitan and La Esperanza, Chiapas, Mexico

The study area is located between the cities of Comitan (16°10'43"N and 92°04'20''W) a city with 150,000 inhabitants and La Esperanza (16°9'15''N and 91°52'5''W) a town with 3000 inhabitants. Both weather stations are 30 km from each other in the Chiapas State, México. 54 years of daily records of the series of maximum (tmax) and minimum temperatures (tmin) of the weather station 07205 Comitan that is on top of a house and 30 years of daily records of the weather station 07374 La Esperanza were analyzed. The objective is to analyze the evidence of climate change in the Comitan valley. 2.07% and 19.04% of missing data were filled, respectively, with the WS method. In order to verify homogeneity three methods were used: Standard Normal Homogeneity Test (SNHT), the Von Neumann method and the Buishand method. The heterogeneous series were homogenized using climatol. The trends of tmax and tmin for both weather stations were analyzed by simple linear regression, Sperman’s rho and Mann-Kendall tests. The Mann-Kendal test method confirmed the warming trend at the Comitan station for both variables with ZMK statistic values equal to 1.57 (statistically not significant) and 4.64 (statistically significant). However, for the Esperanza station, it determined a cooling trend for tmin and a slight non-significant warming for tmax with a ZMK statistic of -2.27 (statistically significant) and 1.16 (statistically not significant), for a significance level α = 0.05.

Farmers’ Knowledge and Perceptions of the Effects of Climate Variability and Pollution on Crop Production and Their Varying Adaptation Strategies in The Gambia

Crop and livestock production is critical to food security in The Gambia. Over the years, the country has experienced a reduced yield due to perceived climate change events with limited studies on how climate change and pollution affect crop production. This study assesses farmers’ knowledge and perceptions of the effects of climate variability and pollution on crop production and their varying adaptation strategies in The Gambia. Both quantitative and qualitative methods were used in this study. The sample size for quantitative data collection was calculated as 432 while the qualitative data involves both the focus group discussions and key informant interviews. The focus group discussions comprised two districts in each of the six agricultural regions and two farming communities engaged in crop production were chosen from each district. Furthermore, eight key informant interviews from relevant institutions were conducted. The study shows that The Gambia is highly vulnerable to extreme climatic events. Although most farmers opined that agricultural land contamination emanates from farm runoff and indiscriminate waste dumping, they had little knowledge of heavy metal pollution and bioremediation. The results showed that farmers experienced constraints such as inadequate access to credit, water, and irrigation facilities, insufficient access to efficient inputs, salt intrusion, etc. which threatened food security. The study concludes that crop farmers acknowledged the existence and impacts of climate change, and therefore recommend the availability and affordability of climate change resilient crops and promote variability awareness campaigns to address climate change impacts in The Gambia.

Eternal Climate Change Patterns and the Causes and Countermeasures of Global Climate Change

It is an objective fact that the weather is unpredictable.Even the famous meteorologist,Academician Chu Ko Chen,has only a partial understanding of the changing laws of wind and rain.Even though ancient people summarized the 24 solar terms by observing the annual activities of the sun for a long time,because they ignored the impact of the activities of the moon on the Earth’s climate change on a small scale,the 24 solar terms they summarized often could not accurately predict the change of the Earth’s climate.Therefore,the author studied the influence of lunar activities on the Earth’s climate change,finds out the law of the influence of lunar activities on the Earth’s climate change on a small scale,and summarizes the eternal climate change pattern determined by the activities of the sun and the moon.In addition,the author also reveals the causes and countermeasures of global warming and the frequent occurrence of extreme weather as well as environmental change.