Impact Of Extreme Weather Research Articles

Extreme Climate Risk and Financial Performance in the Construction Industry: Empirical Evidence from Listed Companies in China

Climate change has led to frequent occurrence of extreme weather events, which seriously affect human life and production in terms of frequency, intensity and duration. It has become one of the important risk factors faced by enterprises, and the construction industry occupies an important position in China's national economy, which is inevitably affected by extreme weather. Therefore, based on the panel data of Chinese A-share construction enterprises from 2010 to 2022, this article studies the impact of extreme climate on corporate financial performance. It is found that the extreme low temperature climate significantly improves the financial performance risk of the construction industry, while the extreme high temperature climate and extreme rainfall climate have no significant impact on the financial performance of the construction industry. This study expands the literature on the impact of extreme weather on the performance of listed companies, encourages enterprises to further recognize the importance of extreme climate, and provides suggestions for corporate managers on how to deal with extreme climate.

How climate changes affects children: Promoting hope

In a recent JAMA Health Forum article, nurses wrote about the stress facing teens due to climate change. “Growing up in an era of storms and stress — promoting hope among adolescents in the face of climate change” by Allison McCord Stafford, Ph.D., RN and colleagues from Duke University noted that the landmark court case, Held v. Montana, showed the impact of extreme weather on the livelihoods and health of young people. Young people brought the lawsuit. And their testimony — about the damages to the land, farm animals, health, finances, and their worries about their future — was eloquent. It is the older generation that has brought this stress upon them.

Relationships between weather and yield anomalies vary with crop type and latitude in Sweden

CONTEXTInformation on how crop yields are affected by weather variations and extreme weather is needed to develop climate adaptation measures for arable cropping systems. Here, we analysed the effects of weather anomalies and soil texture on crop yield anomalies across Sweden from 1965 to 2020. OBJECTIVEThe aims of this study were to (i) assess the effects of temperature and precipitation anomalies and extreme weather on crop yield anomalies for major field crops across Sweden, (ii) quantify how crop responses to weather anomalies vary along the north-south climate gradient across Sweden, and (iii) elucidate the impacts of soil texture on yield responses to weather anomalies. METHODSWe used daily mean air temperature, daily total precipitation, soil texture and crop yield data from public databases covering all 21 counties in Sweden. Yield data was detrended to account for the effects of agricultural intensification on crop productivity. To assess seasonal weather influences on crop yields, temporal trends of daily average temperature and daily total precipitation were detrended for each season containing a three-month period. We also used a water balance index and a heat wave index to evaluate the impact of extreme weather. RESULTS AND CONCLUSIONSOur analyses showed that years with extreme weather during summer (i.e. heat waves, drought or water excess) resulted in the largest negative yield anomalies. Spring-sown crops were more negatively affected by extreme weather compared to autumn-sown crops, which we associate with differences in the lengths of the growth period for autumn- and spring-sown crops. Effects of soil texture on yield anomalies were found for spring-sown cereals, where negative effects of drought were exacerbated with increasing sand content. Moreover, we showed that the effects of weather conditions on crop yield anomalies differed between different regions within the country. In northern Sweden, crop yields were more sensitive to excess water, while drought effects were more pronounced in southern Sweden. Similarly, increased summer temperatures favoured crop yields in northern Sweden but had a negative impact on crop yields in the southern part of the country. SIGNIFICANCEOur study demonstrates that weather impacts on yields vary between crops and locations, and that adaptation to future climate will require crop- and site-specific strategies.

‘What if it rains? What if there are bushfires?’: Extreme weather, climate change and music festivals in Australia

Increasingly, music festivals in Australia are being cancelled, postponed or otherwise impacted by extreme weather events, including floods throughout 2022 and bushfires in 2018–2019. These and other forms of extreme weather, such as dangerous heat and drought, are predicted to increase in frequency and severity due to climate change. However, relative to the size of the problem, there is a lack of attention in both public discussion and scholarly literature to the impacts of extreme weather and climate change on the festival sector, and the need to adapt in response. This study explores this issue in the context of Australian music festivals. The threat of extreme weather to the Australian music festival sector and its benefits is outlined, with reference to climate science predictions as against known festival activity, as well as a detailed overview of recent impacts. This is followed by an examination of how music festival stakeholders in industry and government are responding to this challenge, through the analysis of policy submissions, media comments and changes of practice. This article concludes by proposing a set of questions and issues for research, policy and action concerning the escalating impact of extreme weather on music festivals in Australia, with relevance to other places.

Extreme weather raises the prices of regional emission allowances in China.

Extreme weather is an unexpected shock to the socioeconomic, which is likely to create climate risks in the process of global warming mitigation. The aim of this study is to investigate the impact of extreme weather on prices of China's regional emission allowances, by using the panel data of four representative pilots in China (Beijing, Guangdong, Hubei, and Shanghai) from April 2014 to December 2020. The overall findings reveal that extreme weather, especially extreme heat, has a short-term lagged positive impact on carbon prices. In particular, the specific performance of extreme weather under different conditions is as follows: (i) carbon prices in tertiary-dominated markets are more sensitive to extreme weather, (ii) extreme heat has a positive effect on carbon prices while extreme cold does not, and (iii) the positive impact of extreme weather on carbon market is significantly stronger during compliance periods. This study provides the decision-making basis for emission traders to avoid losses caused by market fluctuations.

Performance of regional water purification plants during extreme weather events: three case studies from New South Wales, Australia.

Climate change is altering weather patterns, which affects water supply systems globally. More frequent extreme weather events like floods, droughts, and heatwaves are impacting the availability of raw water sources that supply cities. These events can lead to less water, higher demand, and potential infrastructure damage. Water agencies and utilities must develop resilient and adaptable systems to withstand shocks and stresses. Case studies demonstrating the impact of extreme weather on water quality are important for developing resilient water supply systems. This paper documents the challenges faced by regional New South Wales (NSW) in managing water quality and supply during extreme weather events. Effective treatment processes, such as ozone treatment and adsorption, are used to maintain drinking water standards during extreme weather. Water-efficient alternatives are provided, and critical water networks are inspected to identify leaks and reduce system demand. Local government areas must collaborate and share resources to ensure that towns can cope with future extreme weather events. Systematic investigation is needed to understand system capacity and identify surplus resources to be shared when demand cannot be met. Pooling resources could benefit regional towns experiencing both floods and droughts. With expected population growth in the area, regional NSW councils will require a significant increase in water filtration infrastructure to handle increased system loading. Continuous research, regular strategy reviews, and innovative approaches are essential to ensure a secure and reliable water supply during future extreme weather events.

Resilience assessment and recovery of distribution network considering the influence of communication network

Aiming at the existing research ignoring the influence of communication network (CN) on resilience recovery strategy and evaluation of distribution network (DN), this paper will discuss the impact of communication network state on resilience recovery and construct corresponding quantitative evaluation indexes. Firstly, a comprehensive importance evaluation index is constructed for communication failures to determine the order of communication restoration in the failure area. Then the emergency communication recovery in the fault area is carried out by using 5G micro base station. Second, a quantitative evaluation index of the impact of communication on distribution network status recovery is established, considering the fluctuation of distributed power output and load. At the same time, thermal rating constraints are considered in load transfer and island formation, and the effects of static and dynamic thermal rating (DTR) on load recovery are compared. Considering the influence of emergency resource warehouse location on repair time during fault repair, the location of the resource warehouse is determined through spectral clustering to improve repair efficiency. At the same time, the average headway time is introduced to quantify the impact of extreme weather on traffic, modify the road resistance model, and then use the minimum road method to establish an emergency recovery strategy that considers the effects of extreme weather. The IEEE-123 node system is used as an example to verify the rationality of the resilience recovery strategy and the resilience assessment with communication impact.

Widening the lens of population-based health research to climate change impacts and adaptation: the climate change and health evaluation and response system (CHEERS).

Climate change significantly impacts health in low-and middle-income countries (LMICs), exacerbating vulnerabilities. Comprehensive data for evidence-based research and decision-making is crucial but scarce. Health and Demographic Surveillance Sites (HDSSs) in Africa and Asia provide a robust infrastructure with longitudinal population cohort data, yet they lack climate-health specific data. Acquiring this information is essential for understanding the burden of climate-sensitive diseases on populations and guiding targeted policies and interventions in LMICs to enhance mitigation and adaptation capacities. The objective of this research is to develop and implement the Change and Health Evaluation and Response System (CHEERS) as a methodological framework, designed to facilitate the generation and ongoing monitoring of climate change and health-related data within existing Health and Demographic Surveillance Sites (HDSSs) and comparable research infrastructures. CHEERS uses a multi-tiered approach to assess health and environmental exposures at the individual, household, and community levels, utilizing digital tools such as wearable devices, indoor temperature and humidity measurements, remotely sensed satellite data, and 3D-printed weather stations. The CHEERS framework utilizes a graph database to efficiently manage and analyze diverse data types, leveraging graph algorithms to understand the complex interplay between health and environmental exposures. The Nouna CHEERS site, established in 2022, has yielded significant preliminary findings. By using remotely-sensed data, the site has been able to predict crop yield at a household level in Nouna and explore the relationships between yield, socioeconomic factors, and health outcomes. The feasibility and acceptability of wearable technology have been confirmed in rural Burkina Faso for obtaining individual-level data, despite the presence of technical challenges. The use of wearables to study the impact of extreme weather on health has shown significant effects of heat exposure on sleep and daily activity, highlighting the urgent need for interventions to mitigate adverse health consequences. Implementing the CHEERS in research infrastructures can advance climate change and health research, as large and longitudinal datasets have been scarce for LMICs. This data can inform health priorities, guide resource allocation to address climate change and health exposures, and protect vulnerable communities in LMICs from these exposures.

An Overview of Extreme Storm Trends in Java Island using Storm Severity Index (SSI)

Extreme winds can lead to extreme storms, which are among the most frequent forms of extreme weather in Indonesia. With climate change predicted to increase the adverse impact of extreme weather, it is crucial to keep track of and gauge the severity of storm events. Storm Severity Index (SSI) can be used to measure the severity of storms, which is defined by their intensity, duration, and extent. SSI has been used in continental areas. However, the application of SSI in the maritime continent is still limited. This study explores the application of SSI to measure extreme storms in Indonesia based on wind gust speed. This study uses wind gust data in 1959-2021 from ERA5 reanalysis data and calculates the SSI based on the 98th percentile and the 50-year return value of the wind data. This study also explores the meteorological events that coincide with high SSI values. This study found the SSI able to capture high wind gust events in Java Island. This study finds high SSI value coincides with tropical cyclone events in the Indian Ocean. Topography affects the area on Java Island that has a high SSI value. Further study should evaluate the impact of the coastal and non-coastal areas to reduce the significant effect of sea-land breeze or mountain-valley breeze. In addition, future research also needs to address the significance level of the duration of events in a severe storm to enhance the information on severity.

AN ECONOMETRIC ANALYSIS FORTHE IMPACT OF CLIMATIC CONDITIONS ON THE PRODUCTIVITY OF MANGO CROPS IN EGYPT BY USING PANEL DATA MODELS

Horizontal agricultural expansion is one of the most important pillars of the national economy in Egypt, so the country makes strenuous efforts to make optimal use of agricultural resources, and despite these efforts, the climate prevents it.Recently, global warming has increased and climate change is expected to worsen the frequency, intensity, and impacts of some types of extreme weather events that affected mango productivity during the last years, which led to a decrease in productivity by about 37%, with a value of financial losses amounting to 4.8 billion pounds in 2021.Therefore, the research aims to estimate the impact of extreme weather on mango productivity during the last three years (2021-2019) at four studied governorates representing 75% of the total area of mango in Egypt. The Fixed Effect Cross of Panel Data Model was adopted as the appropriate model, to illustrate the impact of the phenomena on the productivity of mangoes. The results show that there is a statistical significance and a negative effect for both the minimum and maximum temperatures, as productivity decreases by about 1.05%, and 1.79% with an increase in each of the minimum and maximum temperatures by 1%, respectively. The negative impact has been shown on the governorates of Buhaira and Ismailia. Also, the individual effect was studied for each month,it was found that there was a statistically significant negative effect of the minimum and maximum temperatures for the months of flowering and fruiting.

Impact of extreme weather in production economics: Extracting evidence from user-generated content

The last decade has witnessed an increase in the number of extreme weather events globally. In addition, the economic output around the world is at all-time high in terms of production and profitability. However, global warming and extreme weather are modifying the natural ecosystem and the human social system, leading to the appearance of extreme climate events that have an adverse impact on the world economy. To address this challenge, the present study identifies the main impacts of extreme weather on production economics based on the analysis of user-generated content (UGC) on the social network Twitter. Methodologically, a sentiment analysis with machine learning is developed and applied to analyze a sample of 1.4 m tweets; in addition, computing experiments to calculate the accuracy with Support Vector Classifier, Multinomial Naïve Bayes, Logistic Regression, and Random Forest Classifier are conducted. Second, a topic modeling known as latent Dirichlet allocation is applied to divide sentiment-classified tweets into topics. To complement these approaches, we also use the technique of textual analysis. These approaches are used under the framework of computer-aided test analysis system and natural language processing. The results are discussed and linked to appraisal theory. A total of 7 topics are identified, including positive (Sustainable energies and Green Entrepreneurs), neutral (Climate economy, Producer's productivity and Stock market), and negative (Economy and policy and Climate emergence). Finally, the present study discusses how the recent trend of an increase in extreme weather conditions has significantly impacted international markets, leading companies to adapt their business models and production systems accordingly. The results show that the climate economy and policy, producers' productivity, and the stock market are all heavily influenced by extreme weather and can have significant effects on the global economy.

Climate Change, Farm Irrigation Facilities, and Agriculture Total Factor Productivity: Evidence from China

Due to the trend of global warming, individuals from all walks of life have paid close attention to how climate change affects food security. China is a sizable nation with a rich climate and a diverse range of food crops that are of interest to researchers. Additionally, there is little mention of agricultural technology and farm irrigation facilities in academic research on climate change and agricultural economic growth in China. As a result, this study uses the SBM model, panel fixed effect model, and SYS-GMM model to examine the development trend of climate change and food security based on the panel data of Chinese provinces from 2000 to 2020. The study found that China has maintained an average annual growth rate of 4.3% in agricultural total factor productivity (TFP) in recent years, despite the impact of extreme weather. The average annual precipitation has a depressing influence on the TFP in agriculture, while the average annual temperature has the opposite effect. The farm irrigation facilities and agricultural technology’s moderating impact is mostly shown in how well they attenuate the impact of climate change on the TFP in agriculture. Food crops have thereby improved their ability to survive natural risks and attain higher yields as a result of advancements in agricultural technology and increasing investment in contemporary farm irrigation facilities. The study’s conclusions are used in the article to make the suggestion that strengthening climate change adaptation is necessary to ensure food security. The strategic policy of “storing grain in technology and storing grain in the soil” and the advancement of contemporary agricultural technology must be put into reality while the management system for grain reserves is being improved.

Renewable Energy in Indonesia: Current Status, Potential, and Future Development

The current use of fossil fuels has a significant impact on increasing greenhouse gas (GHG) emissions. Subsequently, renewable energy is significantly needed to reduce GHG, thereby limiting the impact of extreme weather and climate while ensuring reliable, timely, and cost-effective supply. As a big country with a huge amount natural resource, the demand for renewable energy in Indonesia has increased along with the rise in consumption. Following this, energy consumption increased by 0.99%, which was approximately 939.100 million BOE in 2021 for biogas, oil, electricity, natural gas, coal, LPG, biodiesel, and biomass. Energy consumption in several sectors including transportation has the largest energy consumption with approximately 45.76% of oil. In industries and households sector, the consumption rates are 31.11% for boiler steam generation purposes and 16.89% for electricity as well as LPG. Furthermore, the commercial sector consumes 4.97% of energy for lighting and air conditioning, while the remaining 1.27% is used for other sectors. Meanwhile, Indonesia has high potential for renewable energy at 419 GW including 75 GW of hydro energy, 23.7 GW of geothermal, 32.6 GW of bioenergy, 207.8 GW of solar, 60.6 GW of wind, and 19.3 GW of micro-hydro. Therefore, the main focus of this paper is to provide a detailed analysis of the current status, prospects, and information on Indonesia’s renewable and sustainable energy sources. Furthermore, the novelty of this research entails updating the latest data related to renewable energy and its availability in Indonesia. The essence is to portray a picture of its potential development in the future.

Lockdown effects of the COVID-19 on the spatio-temporal distribution of air pollution in Beijing, China

To prevent the spread of COVID-19, China enacted a series of strict policies, which reduced anthropogenic activities to a near standstill. This provided a precious window to explore its effects on the spatio-temporal distribution of air pollution in Beijing, China. In this study, continuous wavelet transforms and spatial interpolation methods were used to explore the spatiotemporal variations in air pollutants and their lockdown effects. The results indicate that except O3, the annual average concentration of NO2, PM2.5 and SO2 showed a decreasing trend during 2016 and 2019; NO2, PM2.5 and SO2 show a trend of “low in summer and high in winter”; the diurnal variation of NO2 concentration was mainly related to the rush hours of traffic volume, with the first peak at the morning peak (7:00), and then accumulating gradually to second peak (22:00). The continuous wavelet analysis shows that PM2.5, SO2 and NO2 had four primary periods, while O3 only had two primary periods. The high NO2 concentration areas were mainly in Dongcheng, Xicheng, Chaoyang and Fengtai, while the low concentration areas were located in the northern areas, such as Miyun and Huairou; the PM2.5 concentration decreased from south to north; this characteristic presented more obviously in winter. Compared to the pre-lockdown, NO2 and SO2 decreased considerably during lockdown, whereas PM2.5 and O3 increased dramatically. The contribution rates of transportation activities to the NO2, O3, PM2.5 and SO2 were estimated be 9.4 % ∼ 17.2 %, −76.4 % ∼ −42.9 %, −39.5 % ∼ –22.8 % and 5.7 % ∼ 43.7 %, respectively; the contribution rates of industrial activities were 19.9 % ∼ 26.7 %, 7.8 % ∼ 30.9 %, 1.6 % ∼ 36.2 % and −10.5 % ∼ 15.9 %, respectively. Considering meteorological factors, we inferred that pauses in anthropogenic activities indeed help improving air pollution, but it is difficult to offset the impact of extreme weather. These findings can enhance our understanding on the sources of air pollution, and can therefore provide insights on urban air pollution mitigation.

Advances in influencing mechanism and model of total climatic production factors of plant phenology change

<p indent="0mm">Phenology is an important indicator of climate change. It is not only the key to vegetation dynamic simulation, but also directly affects the simulation accuracy of terrestrial carbon cycle and atmospheric general circulation model. This paper summarizes the research status of plant phenology from two aspects: phenological change mechanism and phenological simulation model, and analyzes the research trend of phenology. It points out that most of the current phenological studies only consider the impact of a single climate factor or a few climate factors, and there are still few studies involved in the interaction of multiple climate factors, let alone the interaction of total climate production factors determining plant phenology. Due to the limitation of the understanding of phenological change mechanism and the study of species, the existing phenological models cannot reflect the authenticity of vegetation growth, nor can they effectively simulate the phenological period. The paper points out that it is essential to study the relationship between phenology and total climatic production factors in order to comprehensively understand the mechanism of phenological change. Based on the fact that plant photosynthesis is the most important phenological influencing factor, this paper puts forward the viewpoint of using climate production potential as the driving factor of plant phenological change. Climate production potential not only reflects the comprehensive effect of climate and environmental factors on plant production and their consistency of these factors in the whole process of plant growth, but also includes the interaction between biological factors and environmental factors and the impact of extreme weather and climate events, which is able to realize the accurate simulation of phenology. The future phenological research directions proposed in this paper will help enrich phenological knowledge and improve the simulation accuracy of land carbon cycle model and atmospheric circulation model.

Impact of extreme weather on dengue fever infection in four Asian countries: A modelling analysis

The rapid spread of dengue fever (DF) infection has posed severe threats to global health. Environmental factors, such as weather conditions, are believed to regulate DF spread. While previous research reported inconsistent change of DF risk with varying weather conditions, few of them evaluated the impact of extreme weather conditions on DF infection risk. This study aims to examine the short-term associations between extreme temperatures, extreme rainfall, and DF infection risk in South and Southeast Asia. A total of 35 locations in Singapore, Malaysia, Sri Lanka, and Thailand were included, and weekly DF data, as well as the daily meteorological data from 2012 to 2020 were collected. A two-stage meta-analysis was used to estimate the overall effect of extreme weather conditions on the DF infection risk. Location-specific associations were obtained by the distributed lag nonlinear models. The DF infection risk appeared to increase within 1–3 weeks after extremely high temperature (e.g. lag week 2: RR = 1.074, 95 % CI: 1.022–1.129, p = 0.005). Compared with no rainfall, extreme rainfall was associated with a declined DF risk (RR = 0.748, 95 % CI: 0.620–0.903, p = 0.003), and most of the impact was across 0–3 weeks lag. In addition, the DF risk was found to be associated with more intensive extreme weathers (e.g. seven extreme rainfall days per week: RR = 0.338, 95 % CI: 0.120–0.947, p = 0.039). This study provides more evidence in support of the impact of extreme weather conditions on DF infection and suggests better preparation of DF control measures according to climate change.

A study on the impact of extreme weather on the poverty vulnerability of farming households—evidence from six counties in the hubei and yunnan provinces of china

By using micro-farm household survey data from six counties in the Hubei and Yunnan provinces, warm days, heavy precipitation, and consecutive dry days were selected as extreme weather measures, and the RClimDex software was used to empirically examine the impacts of extreme weather on farm household poverty vulnerability by setting percentile thresholds to measure extreme weather indicators in each district and county in 2017. Based on the improved Department for International Development sustainable livelihoods analysis framework, the entropy value method was used to synthesize the variables in the farm household sustainable livelihood capacity to examine their mediating effects. The results were as follows: 1) Extreme weather significantly affected farm household poverty vulnerability. Warm days were significantly and negatively related to farmers’ poverty vulnerability, while total heavy precipitation and consecutive dry days were significantly and positively related to farmers’ poverty vulnerability. 2) The impacts of extreme weather on farmers with different vulnerability characteristics varied. 3) The sustainable livelihood capacity of farm households played a partially mediating role in the process of extreme weather indicators of persistent drought index affecting the poverty vulnerability of farm households. 4) As compared to rural households engaged in non-agricultural industries, agricultural production and operation-based farming households were more vulnerable to shocks from extreme weather. Accordingly, we recommended that to improve farmers’ climate resilience, differentiated policies should be adopted according to local conditions; climate-sensitive vulnerable groups should be identified; agricultural insurance coverage should be expanded; farmers should be guided into entrepreneurship; and equalization of public services should be equalized so as to avoid farmers becoming impoverished due to extreme weather.

The impact of extreme weather on student online learning participation

In March 2020, the COVID-19 pandemic forced over 1 billion learners to shift from face-to-face instruction to online learning. Seven months after it began, this transition became even more challenging for Filipino online learners. Eight typhoons struck the Philippines from October to November 2020. Two of these typhoons caused widespread flooding, utilities interruptions, property destruction, and loss of life. We examine how these severe weather conditions affected online learning participation of Filipino students pursuing their undergraduate and graduate studies. We used CausalImpact analysis to explore September 2020 to January 2021 data collected from the Moodle Learning Management System data of one university in the Philippines. We found that overall student online participation was significantly negatively affected by typhoons. However, the effect on participation in Assignments and Quizzes was not significant. These findings suggested that students continued to participate in activities that have a direct bearing on their final grades, rather than activities that had no impact on their course outcomes.

Disparities in self-reported extreme weather impacts by race, ethnicity, and income in the United States

Extreme weather events are expected to increase in frequency and severity due to climate change. However, we lack an understanding of how recent extreme weather events have impacted the U.S. population. We surveyed a representative sample of the U.S. public (n = 1071) in September 2021 about self-reported impacts they experienced from six types of extreme weather events within the past three years. We find that an overwhelming majority (86%) of the U.S. public reported being at least slightly impacted by an extreme weather event, and one-third (34%) reported being either very or extremely impacted by one or more types of extreme weather events. We clustered respondents into four impact groups, representing a composite of self-reported impacts from multiple types of extreme weather events. Respondents in the highest extreme weather impact group are more than 2.5 times as likely to identify as Black or Hispanic and 1.89 times more likely to live in a household with income levels below the Federal poverty level. We also observe reports of higher extreme weather impacts from respondents who are female, do not have a bachelor’s degree and live in a rural area. Our results indicate that extreme weather impacts are being felt by a broad cross-section of the U.S. public, with the highest impacts being disproportionately reported by populations that have previously been found to be more vulnerable to natural disasters and other extreme events.

Assessing the Effectiveness of the Actuaries Climate Index for Estimating the Impact of Extreme Weather on Crop Yield and Insurance Applications

This paper investigates the effectiveness of the Actuaries Climate Index (ACI), a climate index jointly launched by multiple actuarial societies in North America in 2016, on predicting crop yields and (re)insurance ratemaking. The ACI is created using a variety of climate variables reflecting extreme weather conditions in 12 subregions in the US and Canada. Using data from eight Midwestern states in the US, we find that the ACI has significant predictive power for crop yields. Moreover, allowing the constituting variables of the ACI to have data-driven rather than pre-determined weights could further improve the predictive accuracy. Furthermore, we create the county-level ACI index using high-resolution climate data and investigate its predictive power on county-level corn yields, which are more relevant to insurance practices. We find that although the self-constructed ACI index leads to a slightly worse fit due to noisier county-specific yield data, the predictive results are still reasonable. Our findings suggest that the ACI index is promising for crop yield forecasting and (re)insurance ratemaking, and its effectiveness could be further improved by allowing for the data-driven weights of the constituting variables and could be created at higher resolution levels.