Wesam H. Beitelmal, S. C. Nwokolo, Edson L. Meyer, C. C. Ahia
This study aims to explore innovative adaptation strategies that can effectively mitigate the climate threats faced by transportation infrastructure in Lagos, Nigeria. The study highlights the urgent need for innovative approaches to address the challenges posed by climate change to transportation systems. By analyzing the current vulnerabilities and potential impacts of climate change on transportation infrastructure, the authors identify and propose four current challenges facing transportation infrastructure as a result of climate change. These threats include the impact of rising sea levels on coastal roads and bridges, the vulnerability of inland transportation systems to extreme weather events such as floods and heavy rainfall, the potential disruption of transportation networks as storms become more frequent and intense, and the implications of temperature changes on road surfaces and their structural integrity. The study also identified and proposed ten potential adaptation measures that can enhance the resilience of transportation systems in Lagos, Nigeria. The adaptive measures ranged from increasing the resilience of road networks through the implementation of proper drainage systems and slope stabilization measures to forming partnerships with private sector companies to promote sustainable practices and the development of green transportation initiatives. To facilitate these adaptive measures, the authors used them to develop various policy frameworks for transportation resilience in Lagos, Nigeria. These policy frameworks aimed to provide guidelines and regulations for the implementation of adaptive measures, ensuring their effective integration into the transportation system. The authors emphasized the importance of stakeholder engagement and public participation in decision-making processes to foster a sense of ownership and collective responsibility towards building resilient transportation systems. By adapting to these measures, Lagos, Nigeria, can enhance its ability to withstand and recover from transportation disruptions caused by various hazards, such as extreme weather events, infrastructure failures, or security threats.
{"title":"Exploring Adaptation Strategies to Mitigate Climate Threats to Transportation Infrastructure in Nigeria: Lagos City, as a Case Study","authors":"Wesam H. Beitelmal, S. C. Nwokolo, Edson L. Meyer, C. C. Ahia","doi":"10.3390/cli12080117","DOIUrl":"https://doi.org/10.3390/cli12080117","url":null,"abstract":"This study aims to explore innovative adaptation strategies that can effectively mitigate the climate threats faced by transportation infrastructure in Lagos, Nigeria. The study highlights the urgent need for innovative approaches to address the challenges posed by climate change to transportation systems. By analyzing the current vulnerabilities and potential impacts of climate change on transportation infrastructure, the authors identify and propose four current challenges facing transportation infrastructure as a result of climate change. These threats include the impact of rising sea levels on coastal roads and bridges, the vulnerability of inland transportation systems to extreme weather events such as floods and heavy rainfall, the potential disruption of transportation networks as storms become more frequent and intense, and the implications of temperature changes on road surfaces and their structural integrity. The study also identified and proposed ten potential adaptation measures that can enhance the resilience of transportation systems in Lagos, Nigeria. The adaptive measures ranged from increasing the resilience of road networks through the implementation of proper drainage systems and slope stabilization measures to forming partnerships with private sector companies to promote sustainable practices and the development of green transportation initiatives. To facilitate these adaptive measures, the authors used them to develop various policy frameworks for transportation resilience in Lagos, Nigeria. These policy frameworks aimed to provide guidelines and regulations for the implementation of adaptive measures, ensuring their effective integration into the transportation system. The authors emphasized the importance of stakeholder engagement and public participation in decision-making processes to foster a sense of ownership and collective responsibility towards building resilient transportation systems. By adapting to these measures, Lagos, Nigeria, can enhance its ability to withstand and recover from transportation disruptions caused by various hazards, such as extreme weather events, infrastructure failures, or security threats.","PeriodicalId":504716,"journal":{"name":"Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141928679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In Vanuatu, communities are predicted to be at high risk of more frequent and severe Marine Heat Wave (MHW) impacts in the future, as a result of climate change. A critical sector at risk in Vanuatu is fisheries, which vitally support food security and livelihoods. To sustain local communities, the MHW risk for Vanuatu fisheries must be extensively explored. In this study, an efficient MHW risk assessment methodology is demonstrated specifically for assessing MHW risk to Vanuatu fisheries. The fisheries specific MHW risk assessment was conducted on the local area council scale for two retrospective case study periods: 2015–2017 and 2020–2022. An integrated GIS-based approach was taken to calculating and mapping monthly hazard, vulnerability, exposure, and overall risk indices. Key areas and time periods of concern for MHW impacts are identified. Area councils in the Shefa province area are particularly concerning, displaying consistently high-risk levels throughout both case studies. Risk levels in 2022 were the most concerning, with most months displaying peak risk to MHW impacts. A sensitivity analysis is employed to validate the selection and weighting of the indicators used. However, it is recommended that a more comprehensive validation of the retrospective risk assessment results, using multiple ground-truth sources, be conducted in the future. Once results are sufficiently validated, management recommendations for fisheries resilience can be made.
{"title":"Conducting a Tailored and Localised Marine Heat Wave Risk Assessment for Vanuatu Fisheries","authors":"I. Aitkenhead, Yuriy Kuleshov, Chayn Sun, S. Choy","doi":"10.3390/cli12080108","DOIUrl":"https://doi.org/10.3390/cli12080108","url":null,"abstract":"In Vanuatu, communities are predicted to be at high risk of more frequent and severe Marine Heat Wave (MHW) impacts in the future, as a result of climate change. A critical sector at risk in Vanuatu is fisheries, which vitally support food security and livelihoods. To sustain local communities, the MHW risk for Vanuatu fisheries must be extensively explored. In this study, an efficient MHW risk assessment methodology is demonstrated specifically for assessing MHW risk to Vanuatu fisheries. The fisheries specific MHW risk assessment was conducted on the local area council scale for two retrospective case study periods: 2015–2017 and 2020–2022. An integrated GIS-based approach was taken to calculating and mapping monthly hazard, vulnerability, exposure, and overall risk indices. Key areas and time periods of concern for MHW impacts are identified. Area councils in the Shefa province area are particularly concerning, displaying consistently high-risk levels throughout both case studies. Risk levels in 2022 were the most concerning, with most months displaying peak risk to MHW impacts. A sensitivity analysis is employed to validate the selection and weighting of the indicators used. However, it is recommended that a more comprehensive validation of the retrospective risk assessment results, using multiple ground-truth sources, be conducted in the future. Once results are sufficiently validated, management recommendations for fisheries resilience can be made.","PeriodicalId":504716,"journal":{"name":"Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141803554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rudolf van der Walt, G. V. Van Vuuren, Janette Larney, T. Verster, Helgard Raubenheimer
Scenario analysis is a comprehensive approach to assess the impact of climate-related transition risk on businesses. Environmental, social, and governance (ESG) scores are popular tools with financial institutions (FI’s) for green-scoring practices and since they characterise a company’s performance from an ESG perspective, they have been criticised for enabling “greenwashing” when used within the context of climate risk. Commercially available ESG scores are also available for listed entities, while FI counterparties are often unlisted. This study develops a methodology for creating in-house environmental scores (E-scores), which are then used to effectively choose appropriate transition pathways to be used in company-specific forward-looking scenario analysis. Such scenario analysis can be used to forecast the company’s financial position, including the cost of its greenhouse gas (GHG) emissions, and quantify the impact of transition climate risk on specified metrics. The choice of metrics depends on what the results of the analysis are used for. Two metrics are identified for being useful for risk management and credit decisions: future profitability and weighted average carbon intensity. Finally, the study demonstrates how this process can be implemented with a practical worked example, using only publicly available data.
{"title":"Combining E-Scores with Scenario Analysis to Evaluate the Impact of Transition Risk on Corporate Client Performance","authors":"Rudolf van der Walt, G. V. Van Vuuren, Janette Larney, T. Verster, Helgard Raubenheimer","doi":"10.3390/cli12070107","DOIUrl":"https://doi.org/10.3390/cli12070107","url":null,"abstract":"Scenario analysis is a comprehensive approach to assess the impact of climate-related transition risk on businesses. Environmental, social, and governance (ESG) scores are popular tools with financial institutions (FI’s) for green-scoring practices and since they characterise a company’s performance from an ESG perspective, they have been criticised for enabling “greenwashing” when used within the context of climate risk. Commercially available ESG scores are also available for listed entities, while FI counterparties are often unlisted. This study develops a methodology for creating in-house environmental scores (E-scores), which are then used to effectively choose appropriate transition pathways to be used in company-specific forward-looking scenario analysis. Such scenario analysis can be used to forecast the company’s financial position, including the cost of its greenhouse gas (GHG) emissions, and quantify the impact of transition climate risk on specified metrics. The choice of metrics depends on what the results of the analysis are used for. Two metrics are identified for being useful for risk management and credit decisions: future profitability and weighted average carbon intensity. Finally, the study demonstrates how this process can be implemented with a practical worked example, using only publicly available data.","PeriodicalId":504716,"journal":{"name":"Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141820706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Andrew Russell, Adam James McCue, Aakash Dipak Patel
Here, we investigate whether England’s 152 local flood risk management strategies (LFRMSs) satisfy minimal legislative criteria and address the growing surface water flood (SWF) risk caused by climate change. A systematic audit was used to assess the alignment of the LFRMSs with national climate change legislation and other relevant national strategies. An objective method to identify inclusion of a range of factors that good strategies should include was applied. LFRMSs are mostly meeting their minimum statutory requirements. However, there is a widespread issue across most LFRMSs regarding inadequate consideration of increasing SWF risk from climate changes, which highlights the need for enhanced LFRMSs by improved planning and climate change adaptation plans. There is some evidence of good practice within the LFRMS portfolio, which is discussed in the context of the ongoing LFRMS update process. Beyond England, there are implications for developing FRM processes at a local level that can be objectively assessed against national requirements. Communities in England face inadequately managed SWF risk in the future because of the range in plan quality across the LFRMSs. This research contributes to the ongoing examination of the full suite of 152 LFRMSs and, therefore, builds towards a complete assessment of the SWF management approach in England. This will help inform local climate change adaptation strategies that cater to the escalating threat of SWF due to climate change.
{"title":"Developing an Audit Framework for Local Flood Risk Management Strategies: Is Increasing Surface Water Flood Risk in England Being Adequately Managed?","authors":"Andrew Russell, Adam James McCue, Aakash Dipak Patel","doi":"10.3390/cli12070106","DOIUrl":"https://doi.org/10.3390/cli12070106","url":null,"abstract":"Here, we investigate whether England’s 152 local flood risk management strategies (LFRMSs) satisfy minimal legislative criteria and address the growing surface water flood (SWF) risk caused by climate change. A systematic audit was used to assess the alignment of the LFRMSs with national climate change legislation and other relevant national strategies. An objective method to identify inclusion of a range of factors that good strategies should include was applied. LFRMSs are mostly meeting their minimum statutory requirements. However, there is a widespread issue across most LFRMSs regarding inadequate consideration of increasing SWF risk from climate changes, which highlights the need for enhanced LFRMSs by improved planning and climate change adaptation plans. There is some evidence of good practice within the LFRMS portfolio, which is discussed in the context of the ongoing LFRMS update process. Beyond England, there are implications for developing FRM processes at a local level that can be objectively assessed against national requirements. Communities in England face inadequately managed SWF risk in the future because of the range in plan quality across the LFRMSs. This research contributes to the ongoing examination of the full suite of 152 LFRMSs and, therefore, builds towards a complete assessment of the SWF management approach in England. This will help inform local climate change adaptation strategies that cater to the escalating threat of SWF due to climate change.","PeriodicalId":504716,"journal":{"name":"Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141825993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Berdimbetov, Buddhi Pushpawela, Nikita Murzintcev, S. Nietullaeva, Khusen Gafforov, Asiya Tureniyazova, Dauranbek Madetov
The Aral Sea is an indispensable component of the socio-economic progress of Central Asia but has undergone substantial ecological transformations over the last few decades, primarily due to global warming and human activities. Among these changes, the basin area has decreased, and water levels have dropped. This paper focuses on a comprehensive analysis of the spatial variation of key climate parameters, such as temperature, precipitation, and potential evapotranspiration over the Aral Sea. Moreover, we examined the transformation of seasonal water areas in the Aral Sea during the growing and non-growing seasons between 2002 and 2017 and the influence of climate and human factors on these changes using Landsat satellite data. Our results indicate that the western section of the Aral Sea has experienced a reduction in water area by 2.41 km2 and 1.83 km2 during the warm (R2 = 0.789) and cold (R2 = 0.744) seasons, respectively, over the investigated period. The decrease in lake water volume during the warm season can be attributed to local climate variations, as a strong negative correlation exists between seasonal water storage change and temperature (potential evapotranspiration). The correlation analysis shows that the water change in the northern part of the Aral Sea during the growing season has a significant positive correlation with temperature (R = 0.52) and an insignificant negative correlation with precipitation (R = −0.22). On the contrary, in the west and east parts of the Aral Sea, there is a significant negative correlation with temperature (R = −0.71 and −0.62) and a high positive correlation with precipitation (R = 0.71 and 0.55) during the growing season.
{"title":"Unraveling the Intricate Links between the Dwindling Aral Sea and Climate Variability during 2002–2017","authors":"T. Berdimbetov, Buddhi Pushpawela, Nikita Murzintcev, S. Nietullaeva, Khusen Gafforov, Asiya Tureniyazova, Dauranbek Madetov","doi":"10.3390/cli12070105","DOIUrl":"https://doi.org/10.3390/cli12070105","url":null,"abstract":"The Aral Sea is an indispensable component of the socio-economic progress of Central Asia but has undergone substantial ecological transformations over the last few decades, primarily due to global warming and human activities. Among these changes, the basin area has decreased, and water levels have dropped. This paper focuses on a comprehensive analysis of the spatial variation of key climate parameters, such as temperature, precipitation, and potential evapotranspiration over the Aral Sea. Moreover, we examined the transformation of seasonal water areas in the Aral Sea during the growing and non-growing seasons between 2002 and 2017 and the influence of climate and human factors on these changes using Landsat satellite data. Our results indicate that the western section of the Aral Sea has experienced a reduction in water area by 2.41 km2 and 1.83 km2 during the warm (R2 = 0.789) and cold (R2 = 0.744) seasons, respectively, over the investigated period. The decrease in lake water volume during the warm season can be attributed to local climate variations, as a strong negative correlation exists between seasonal water storage change and temperature (potential evapotranspiration). The correlation analysis shows that the water change in the northern part of the Aral Sea during the growing season has a significant positive correlation with temperature (R = 0.52) and an insignificant negative correlation with precipitation (R = −0.22). On the contrary, in the west and east parts of the Aral Sea, there is a significant negative correlation with temperature (R = −0.71 and −0.62) and a high positive correlation with precipitation (R = 0.71 and 0.55) during the growing season.","PeriodicalId":504716,"journal":{"name":"Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141827023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To mitigate the effects of climate change and increase the resilience of cities, climate risks in urban areas are crucial issues to be addressed. This study analyzes the risks, vulnerability, capacity, degree of exposure, and characteristics of the threats to Panama’s urban areas that result from climate change. Data from DesInventar—a conceptual and methodological tool developed for the construction of databases regarding losses, damages, or effects caused by emergencies or disasters—were analyzed. The main current impacts are floods, landslides, and extreme winds in that order. From 1933 to 2019, Panama recorded 1903 flood reports, 625 landslide reports, and numerous extreme wind events. The affected population totaled 527,394 people, with 101,738 homes impacted. The most affected provinces are Panama, Panama Oeste, and Chiriquí, based on the number of reports. It is expected that in the future, the current effects will increase, and the country’s energy and water security will be put at risk. Strategies to address climate change include enhancing early warning systems and investing in climate-resilient infrastructure. Key measures involve developing public policies for renewable energy and sustainable transportation, preserving ecosystems, and financial mechanisms to support a transition to a sustainable economy.
{"title":"Analysis of Climate Risk in Panama’s Urban Areas","authors":"Michelle A. Ruíz, Y. Mack-Vergara","doi":"10.3390/cli12070104","DOIUrl":"https://doi.org/10.3390/cli12070104","url":null,"abstract":"To mitigate the effects of climate change and increase the resilience of cities, climate risks in urban areas are crucial issues to be addressed. This study analyzes the risks, vulnerability, capacity, degree of exposure, and characteristics of the threats to Panama’s urban areas that result from climate change. Data from DesInventar—a conceptual and methodological tool developed for the construction of databases regarding losses, damages, or effects caused by emergencies or disasters—were analyzed. The main current impacts are floods, landslides, and extreme winds in that order. From 1933 to 2019, Panama recorded 1903 flood reports, 625 landslide reports, and numerous extreme wind events. The affected population totaled 527,394 people, with 101,738 homes impacted. The most affected provinces are Panama, Panama Oeste, and Chiriquí, based on the number of reports. It is expected that in the future, the current effects will increase, and the country’s energy and water security will be put at risk. Strategies to address climate change include enhancing early warning systems and investing in climate-resilient infrastructure. Key measures involve developing public policies for renewable energy and sustainable transportation, preserving ecosystems, and financial mechanisms to support a transition to a sustainable economy.","PeriodicalId":504716,"journal":{"name":"Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141828204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Krikken, G. Geertsema, Kristian Nielsen, Alberto Troccoli
Seasonal climate predictions can assist with timely preparations for extreme episodes, such as dry or wet periods that have associated additional risks of droughts, fires and challenges for water management. Timely warnings for extreme warm summers or cold winters can aid in preparing for increased energy demand. We analyse seasonal forecasts produced by three different methods: (1) a multi-linear statistical forecasting system based on observations only; (2) a non-linear random forest model based on observations only; and (3) process-based dynamical forecast models. The statistical model is an empirical system based on multiple linear regression that is extended to include the trend over the previous 3 months in the predictors, and overfitting is further reduced by using an intermediate multiple linear regression model. This results in a significantly improved El Niño forecast skill, specifically in spring. Also, the Indian Ocean dipole (IOD) index forecast skill shows improvements, specifically in the summer and autumn months. A hybrid multi-model ensemble is constructed by combining the three forecasting methods. The different methods are used to produce seasonal forecasts (three-month means) for near-surface air temperature and monthly accumulated precipitation seasonal forecast with a lead time of one month. We find numerous regions with added value compared with multi-model ensembles based on dynamical models only. For instance, for June, July and August temperatures, added value is observed in extensive parts of both Northern and Southern America, as well as Europe.
{"title":"The Added Value of Statistical Seasonal Forecasts","authors":"F. Krikken, G. Geertsema, Kristian Nielsen, Alberto Troccoli","doi":"10.3390/cli12060083","DOIUrl":"https://doi.org/10.3390/cli12060083","url":null,"abstract":"Seasonal climate predictions can assist with timely preparations for extreme episodes, such as dry or wet periods that have associated additional risks of droughts, fires and challenges for water management. Timely warnings for extreme warm summers or cold winters can aid in preparing for increased energy demand. We analyse seasonal forecasts produced by three different methods: (1) a multi-linear statistical forecasting system based on observations only; (2) a non-linear random forest model based on observations only; and (3) process-based dynamical forecast models. The statistical model is an empirical system based on multiple linear regression that is extended to include the trend over the previous 3 months in the predictors, and overfitting is further reduced by using an intermediate multiple linear regression model. This results in a significantly improved El Niño forecast skill, specifically in spring. Also, the Indian Ocean dipole (IOD) index forecast skill shows improvements, specifically in the summer and autumn months. A hybrid multi-model ensemble is constructed by combining the three forecasting methods. The different methods are used to produce seasonal forecasts (three-month means) for near-surface air temperature and monthly accumulated precipitation seasonal forecast with a lead time of one month. We find numerous regions with added value compared with multi-model ensembles based on dynamical models only. For instance, for June, July and August temperatures, added value is observed in extensive parts of both Northern and Southern America, as well as Europe.","PeriodicalId":504716,"journal":{"name":"Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141267818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Farm households along the coastlines of Myanmar and Vietnam are becoming increasingly vulnerable to flooding, saltwater intrusion, and rising sea levels. There is little information available on the relative vulnerability of men- and women-headed households, and the governments of Myanmar and Vietnam have not identified or implemented any adaptive measures aimed specifically at vulnerable peoples. This study aims to fill these gaps and assess the relative climate change vulnerability of men- and women-headed farm households. This study considers 599 farm households from two regions of Myanmar and 300 households from Thua Thien Hue province of Vietnam for the period 2021–2022. We offer a livelihood vulnerability index (LVI) analysis of men- and women-headed farm households using 46 indicators arranged into seven major components. The aggregate LVI scores indicate that farm households in Myanmar are more vulnerable (scores of 0.459 for men and 0.476 for women) to climate-related natural disasters than farm households in Vietnam (scores of 0.288 for men and 0.292 for women), regardless of the gender of the head of household. Total vulnerability indexing scores indicate that women-headed households are more vulnerable than men-headed households in both countries. Poor adaptive capacity and highly sensitive LVI dimensional scores explain the greater vulnerability of women-headed farm households. The findings also highlight the importance of the adaptive capacity components reflected in the LVI analysis in reducing farm households’ vulnerability.
{"title":"Assessment of the Vulnerability of Households Led by Men and Women to the Impacts of Climate-Related Natural Disasters in the Coastal Areas of Myanmar and Vietnam","authors":"Aung Tun Oo, Ame Cho, Dao Duy Minh","doi":"10.3390/cli12060082","DOIUrl":"https://doi.org/10.3390/cli12060082","url":null,"abstract":"Farm households along the coastlines of Myanmar and Vietnam are becoming increasingly vulnerable to flooding, saltwater intrusion, and rising sea levels. There is little information available on the relative vulnerability of men- and women-headed households, and the governments of Myanmar and Vietnam have not identified or implemented any adaptive measures aimed specifically at vulnerable peoples. This study aims to fill these gaps and assess the relative climate change vulnerability of men- and women-headed farm households. This study considers 599 farm households from two regions of Myanmar and 300 households from Thua Thien Hue province of Vietnam for the period 2021–2022. We offer a livelihood vulnerability index (LVI) analysis of men- and women-headed farm households using 46 indicators arranged into seven major components. The aggregate LVI scores indicate that farm households in Myanmar are more vulnerable (scores of 0.459 for men and 0.476 for women) to climate-related natural disasters than farm households in Vietnam (scores of 0.288 for men and 0.292 for women), regardless of the gender of the head of household. Total vulnerability indexing scores indicate that women-headed households are more vulnerable than men-headed households in both countries. Poor adaptive capacity and highly sensitive LVI dimensional scores explain the greater vulnerability of women-headed farm households. The findings also highlight the importance of the adaptive capacity components reflected in the LVI analysis in reducing farm households’ vulnerability.","PeriodicalId":504716,"journal":{"name":"Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141273675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vanessa Ferreira, O. Bonfim, Rafael Maroneze, L. Mortarini, R. H. Valdes, Felipe Denardin Costa
This study analyzes the spatial distribution and trends in five extreme daily rainfall indices in the Uruguay River Basin (URB) from 1993 to 2022 using the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) dataset. The main findings reveal a predominantly positive trend in heavy precipitation (R95p) and extreme precipitation (R99p) events over the mid URB, while a negative trend is observed in the upper and low URB. Significant trends in the frequency of heavy and extreme rainfall were observed during autumn (MAM), with positive trends across most of the mid and upper URB and negative trends in the low URB. In the upper URB, negative trends in the frequency of extremes were also found during spring (SON) and summer (DJF). Overall, there was a reduction in the number of consecutive wet days (CWD), particularly significant in the upper URB and the northern half of the mid URB. Additionally, the upper URB experienced an overall increase in the duration of consecutive dry days (CDD).
{"title":"Precipitation Extremes and Trends over the Uruguay River Basin in Southern South America","authors":"Vanessa Ferreira, O. Bonfim, Rafael Maroneze, L. Mortarini, R. H. Valdes, Felipe Denardin Costa","doi":"10.3390/cli12060077","DOIUrl":"https://doi.org/10.3390/cli12060077","url":null,"abstract":"This study analyzes the spatial distribution and trends in five extreme daily rainfall indices in the Uruguay River Basin (URB) from 1993 to 2022 using the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) dataset. The main findings reveal a predominantly positive trend in heavy precipitation (R95p) and extreme precipitation (R99p) events over the mid URB, while a negative trend is observed in the upper and low URB. Significant trends in the frequency of heavy and extreme rainfall were observed during autumn (MAM), with positive trends across most of the mid and upper URB and negative trends in the low URB. In the upper URB, negative trends in the frequency of extremes were also found during spring (SON) and summer (DJF). Overall, there was a reduction in the number of consecutive wet days (CWD), particularly significant in the upper URB and the northern half of the mid URB. Additionally, the upper URB experienced an overall increase in the duration of consecutive dry days (CDD).","PeriodicalId":504716,"journal":{"name":"Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141112939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Psychological distance from climate change has emerged as an important construct in understanding sustainable behavior and attempts to mitigate and/or adapt to climate change. Yet, few measures exist to assess this construct and little is known about the properties of the existing measures. In this article, the author conducted two studies of a psychological distance measure developed by Wang and her colleagues. In Study 1, the author assessed the test–retest reliability of the measure over a two-week interval and found the scores to be acceptably stable over time. In Study 2, the author conducted two exploratory factor analyses, using different approaches to the correlation and factor extraction. Similar results were observed for each factor analysis: one factor was related to items that specified greater psychological distance from climate change; a second factor involved items that specified closeness to climate change; and a third involved the geographic/spatial distance from climate change. The author discussed the results and provided recommendations on ways that the measure may be used to research the construct of psychological distance from climate change.
{"title":"Reliability and Exploratory Factor Analysis of a Measure of the Psychological Distance from Climate Change","authors":"Alan E. Stewart","doi":"10.3390/cli12050076","DOIUrl":"https://doi.org/10.3390/cli12050076","url":null,"abstract":"Psychological distance from climate change has emerged as an important construct in understanding sustainable behavior and attempts to mitigate and/or adapt to climate change. Yet, few measures exist to assess this construct and little is known about the properties of the existing measures. In this article, the author conducted two studies of a psychological distance measure developed by Wang and her colleagues. In Study 1, the author assessed the test–retest reliability of the measure over a two-week interval and found the scores to be acceptably stable over time. In Study 2, the author conducted two exploratory factor analyses, using different approaches to the correlation and factor extraction. Similar results were observed for each factor analysis: one factor was related to items that specified greater psychological distance from climate change; a second factor involved items that specified closeness to climate change; and a third involved the geographic/spatial distance from climate change. The author discussed the results and provided recommendations on ways that the measure may be used to research the construct of psychological distance from climate change.","PeriodicalId":504716,"journal":{"name":"Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141125067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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