Pub Date : 2024-05-16DOI: 10.3389/fclim.2024.1346677
P. Mugabe, H. Kipkulei, Stefan Sieber, Emmanuel Mhache, K. Löhr
Climate variability impacts various global challenges, including food security, biodiversity loss, water scarcity, and human well-being. However, climate patterns and trends and community perceptions at spatially-explicit levels have been minimally addressed. The spatial and temporal trends of climate conditions in Bagamoyo District in Tanzania were examined using historical (1983–2010) and projected (2022–2050) meteorological and climate model data, respectively. Community knowledge and experiences of past climate occurrences were included. The implications of projected climate change for regional agricultural production and food security were assessed. The study drew on empirical data obtained from household surveys conducted in seven villages in the district. Effectively, 309 households were randomly sampled across the villages to provide the perception of climate change and associated impacts on agriculture and livelihoods. Both qualitative and quantitative statistical techniques were employed to analyse the incidence, frequency, and intensity of regional extreme climate events. The meteorological and climate modelling data were subjected to trend analysis using the Mann–Kendall and Sen’s slope estimator tests, and the present and projected spatial and temporal trends of climatic variables in the region were analysed. The household-based questionnaire results were combined with climate modelling and the literature to determine the implications of climate change for regional agricultural production and food security. The results revealed that local knowledge and climate model data strongly concur on regional climate changes. Furthermore, the region is highly likely to experience increased warming and decreased precipitation at varying magnitudes. The shifts in climate trends and patterns are anticipated to greatly impact agricultural production, affecting livelihoods and hampering food security efforts. Recommendations include adopting context-specific measures and tailored strategies for enhancing resilience throughout the entire region.
气候多变性影响着各种全球性挑战，包括粮食安全、生物多样性丧失、水资源短缺和人类福祉。然而，在空间明确层面上的气候模式和趋势以及社区感知却鲜有涉及。本文分别利用历史（1983-2010 年）和预测（2022-2050 年）气象和气候模型数据，研究了坦桑尼亚巴加莫约区气候条件的空间和时间趋势。研究还包括社区对过去气候事件的了解和经验。评估了预测气候变化对地区农业生产和粮食安全的影响。研究利用了在该地区七个村庄进行的家庭调查所获得的经验数据。实际上，各村随机抽样了 309 户家庭，以了解他们对气候变化的看法以及气候变化对农业和生计的相关影响。采用定性和定量统计技术分析了区域极端气候事件的发生率、频率和强度。利用 Mann-Kendall 和 Sen 的斜率估计检验对气象和气候模型数据进行了趋势分析，并分析了该地区气候变量目前和预计的空间和时间趋势。家庭问卷调查结果与气候模型和文献相结合，确定了气候变化对地区农业生产和粮食安全的影响。结果显示，当地知识和气候模型数据在区域气候变化方面高度一致。此外，该地区极有可能经历不同程度的升温和降水减少。气候趋势和模式的变化预计将极大地影响农业生产，影响生计，阻碍粮食安全工作。建议包括采取针对具体情况的措施和有针对性的战略，以提高整个地区的抗灾能力。
{"title":"Examining climate trends and patterns and their implications for agricultural productivity in Bagamoyo District, Tanzania","authors":"P. Mugabe, H. Kipkulei, Stefan Sieber, Emmanuel Mhache, K. Löhr","doi":"10.3389/fclim.2024.1346677","DOIUrl":"https://doi.org/10.3389/fclim.2024.1346677","url":null,"abstract":"Climate variability impacts various global challenges, including food security, biodiversity loss, water scarcity, and human well-being. However, climate patterns and trends and community perceptions at spatially-explicit levels have been minimally addressed. The spatial and temporal trends of climate conditions in Bagamoyo District in Tanzania were examined using historical (1983–2010) and projected (2022–2050) meteorological and climate model data, respectively. Community knowledge and experiences of past climate occurrences were included. The implications of projected climate change for regional agricultural production and food security were assessed. The study drew on empirical data obtained from household surveys conducted in seven villages in the district. Effectively, 309 households were randomly sampled across the villages to provide the perception of climate change and associated impacts on agriculture and livelihoods. Both qualitative and quantitative statistical techniques were employed to analyse the incidence, frequency, and intensity of regional extreme climate events. The meteorological and climate modelling data were subjected to trend analysis using the Mann–Kendall and Sen’s slope estimator tests, and the present and projected spatial and temporal trends of climatic variables in the region were analysed. The household-based questionnaire results were combined with climate modelling and the literature to determine the implications of climate change for regional agricultural production and food security. The results revealed that local knowledge and climate model data strongly concur on regional climate changes. Furthermore, the region is highly likely to experience increased warming and decreased precipitation at varying magnitudes. The shifts in climate trends and patterns are anticipated to greatly impact agricultural production, affecting livelihoods and hampering food security efforts. Recommendations include adopting context-specific measures and tailored strategies for enhancing resilience throughout the entire region.","PeriodicalId":33632,"journal":{"name":"Frontiers in Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140971176","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}
Pub Date : 2024-05-15DOI: 10.3389/fclim.2024.1380382
Luis Victor-Gallardo, Susana Solórzano-Jiménez, Lucía Rodríguez-Delgado, Jessica Roccard, Jairo Quirós-Tortós, Rafael Gómez, Maribel Dionicio, Hector Baldivieso, Benoit Lefevre
This paper presents an in-depth analysis of decarbonizing the electricity sector in the Dominican Republic, pivotal for addressing climate change and fostering economic growth. Employing the robust-decision making methodology, we studied multiple scenarios via computational models, capturing inputs from stakeholders and evaluating each scenario across 1,000 futures to capture deep uncertainty. Four scenarios were examined: baseline, reference, natural gas, and renewable. The renewable scenario emerged as the most advantageous, proposing the replacement of coal-fired power generation with renewable sources, primarily solar and wind, coupled with batteries. A significant investment, averaging US$3.3 billion, is necessary for this shift toward renewable energy; however, these investments are overcompensated by savings in operational costs. Crucially, this transition promises substantial benefits by 2050: an estimated cumulative average net economic gain of US$2.7 billion, an 8% reduction in average generation costs in 2050, the creation of 160,000 direct jobs, and the avoidance of circa 140 million tons of CO2. The findings underscore the feasibility and economic viability of transitioning to a 55% renewable energy generation by 2050. The study offers a critical roadmap for policymakers, highlighting renewable energy expansion, transmission grid strengthening, and strategic coal generation replacement, thus offering a comprehensive blueprint for the nation's energy transition.
{"title":"Economic evaluation of decarbonizing the electricity sector in the Dominican Republic","authors":"Luis Victor-Gallardo, Susana Solórzano-Jiménez, Lucía Rodríguez-Delgado, Jessica Roccard, Jairo Quirós-Tortós, Rafael Gómez, Maribel Dionicio, Hector Baldivieso, Benoit Lefevre","doi":"10.3389/fclim.2024.1380382","DOIUrl":"https://doi.org/10.3389/fclim.2024.1380382","url":null,"abstract":"This paper presents an in-depth analysis of decarbonizing the electricity sector in the Dominican Republic, pivotal for addressing climate change and fostering economic growth. Employing the robust-decision making methodology, we studied multiple scenarios via computational models, capturing inputs from stakeholders and evaluating each scenario across 1,000 futures to capture deep uncertainty. Four scenarios were examined: baseline, reference, natural gas, and renewable. The renewable scenario emerged as the most advantageous, proposing the replacement of coal-fired power generation with renewable sources, primarily solar and wind, coupled with batteries. A significant investment, averaging US$3.3 billion, is necessary for this shift toward renewable energy; however, these investments are overcompensated by savings in operational costs. Crucially, this transition promises substantial benefits by 2050: an estimated cumulative average net economic gain of US$2.7 billion, an 8% reduction in average generation costs in 2050, the creation of 160,000 direct jobs, and the avoidance of circa 140 million tons of CO2. The findings underscore the feasibility and economic viability of transitioning to a 55% renewable energy generation by 2050. The study offers a critical roadmap for policymakers, highlighting renewable energy expansion, transmission grid strengthening, and strategic coal generation replacement, thus offering a comprehensive blueprint for the nation's energy transition.","PeriodicalId":33632,"journal":{"name":"Frontiers in Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140971678","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}
Pub Date : 2024-05-14DOI: 10.3389/fclim.2024.1361511
Yan Ma, Lina Guo, Yan Hao
The climatic characteristics of tropical cyclones affecting Qingdao, China, were analyzed from the aspects of frequency, period, and intensity of the tropical cyclones and their impact on rainfall in Qingdao by referring to the Typhoon Yearbook, the tropical cyclone data of China during 1949–2020 as well as surface meteorological observations. The results showed that the frequency of tropical cyclones affecting Qingdao during 1949–2020 took on an overall decreasing trend and mostly exhibited a significant variation period of 2–4 year. Tropical cyclones with the track of turning after landfall and continuing northward after landfall accounted for 47.9%. In July, there were tropical cyclones mainly followed tracks of continuing northward after landfall, and tracks turning after landfall mostly occurred in September. The intensity of the tropical cyclones showed an overall weakening feature with distinct inter-decadal variations, and it did not change much when the northward tropical cyclones close affecting Qingdao. The different track of tropical cyclones had spatially heterogeneous, strong rainfall in Qingdao with the track of continuing northward after landfall brought the highest daily and process rainfall to Qingdao, while the tropical cyclones turning nearshore or advancing offshore before landfall had relatively little rainfall.
{"title":"Climatic characteristics of various tracks of tropical cyclones and their impact on rainfall in Qingdao during 1949–2020","authors":"Yan Ma, Lina Guo, Yan Hao","doi":"10.3389/fclim.2024.1361511","DOIUrl":"https://doi.org/10.3389/fclim.2024.1361511","url":null,"abstract":"The climatic characteristics of tropical cyclones affecting Qingdao, China, were analyzed from the aspects of frequency, period, and intensity of the tropical cyclones and their impact on rainfall in Qingdao by referring to the Typhoon Yearbook, the tropical cyclone data of China during 1949–2020 as well as surface meteorological observations. The results showed that the frequency of tropical cyclones affecting Qingdao during 1949–2020 took on an overall decreasing trend and mostly exhibited a significant variation period of 2–4 year. Tropical cyclones with the track of turning after landfall and continuing northward after landfall accounted for 47.9%. In July, there were tropical cyclones mainly followed tracks of continuing northward after landfall, and tracks turning after landfall mostly occurred in September. The intensity of the tropical cyclones showed an overall weakening feature with distinct inter-decadal variations, and it did not change much when the northward tropical cyclones close affecting Qingdao. The different track of tropical cyclones had spatially heterogeneous, strong rainfall in Qingdao with the track of continuing northward after landfall brought the highest daily and process rainfall to Qingdao, while the tropical cyclones turning nearshore or advancing offshore before landfall had relatively little rainfall.","PeriodicalId":33632,"journal":{"name":"Frontiers in Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140982022","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}
Pub Date : 2024-05-10DOI: 10.3389/fclim.2024.1339877
Fernando Esteves, E. Molina-Pérez, Nidhi Kalra, James Syme, Adrien Vogt-Schilb
This study employs an Input–Output simulation model to assess the potential employment effects resulting from investments in 40 sector-specific decarbonization transformations across Latin America and the Caribbean. Using a Multi-region Input–Output framework (Eora26), our findings indicate that investments in energy production and buildings sectors offer promising job creation opportunities, averaging 5.5 total jobs per $1 million invested. Similarly, in the waste, industry and agriculture, forestry, and land use sectors demonstrate significant potential, yielding approximately 5 total jobs per $1 million. The analysis models investments as demand vectors, producing results for 17 countries in the region. These estimates endogenize the diverse economic structure and state of development of these countries. We argue that country-level analysis is needed to identify climate strategies that maximize job creation while achieving net-zero emissions.
{"title":"Job creation and decarbonization synergies in Latin America: a simulation-based exploratory modeling analysis","authors":"Fernando Esteves, E. Molina-Pérez, Nidhi Kalra, James Syme, Adrien Vogt-Schilb","doi":"10.3389/fclim.2024.1339877","DOIUrl":"https://doi.org/10.3389/fclim.2024.1339877","url":null,"abstract":"This study employs an Input–Output simulation model to assess the potential employment effects resulting from investments in 40 sector-specific decarbonization transformations across Latin America and the Caribbean. Using a Multi-region Input–Output framework (Eora26), our findings indicate that investments in energy production and buildings sectors offer promising job creation opportunities, averaging 5.5 total jobs per $1 million invested. Similarly, in the waste, industry and agriculture, forestry, and land use sectors demonstrate significant potential, yielding approximately 5 total jobs per $1 million. The analysis models investments as demand vectors, producing results for 17 countries in the region. These estimates endogenize the diverse economic structure and state of development of these countries. We argue that country-level analysis is needed to identify climate strategies that maximize job creation while achieving net-zero emissions.","PeriodicalId":33632,"journal":{"name":"Frontiers in Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140992091","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}
Pub Date : 2024-05-09DOI: 10.3389/fclim.2024.1386061
Valeria Zambianchi, Katja Biedenkopf
The systems of policies impacting climate change mitigation are complex. Yet, to date, we have limited conceptual and empirical knowledge on the dynamics within these. We address this gap by employing a systems lens to untangle the interactions between the policies affecting climate change mitigation in the electricity generation space. We conceptualise climate policyscapesfor electricity generation as systems populated with policies whose means impact decarbonisation in the electricity generation space. The impacts under analysis include both support and obstruction of climate change mitigation. We analyse the evolution of the UK climate policyscape from 1956 to 2022. Methodologically, we combine qualitative content analysis and network analysis. We populate the policyscapes with pieces of legislation in the electricity generation space and employ qualitative content analysis to identify the policy means affecting climate change mitigation. Our network analysis of the 2022 climate policyscape reveals that policies hindering climate mitigation remain largely present, which renders the climate policyscape incoherent. We show that policies supporting mitigation are more likely to behave as a group than policies hindering climate mitigation. Climate policies tend to be adopted as packages, whilst fossil policies remain a steady process throughout the history of the UK climate policyscape.
{"title":"Interactions within climate policyscapes: a network analysis of the electricity generation space in the United Kingdom, 1956–2022","authors":"Valeria Zambianchi, Katja Biedenkopf","doi":"10.3389/fclim.2024.1386061","DOIUrl":"https://doi.org/10.3389/fclim.2024.1386061","url":null,"abstract":"The systems of policies impacting climate change mitigation are complex. Yet, to date, we have limited conceptual and empirical knowledge on the dynamics within these. We address this gap by employing a systems lens to untangle the interactions between the policies affecting climate change mitigation in the electricity generation space. We conceptualise climate policyscapesfor electricity generation as systems populated with policies whose means impact decarbonisation in the electricity generation space. The impacts under analysis include both support and obstruction of climate change mitigation. We analyse the evolution of the UK climate policyscape from 1956 to 2022. Methodologically, we combine qualitative content analysis and network analysis. We populate the policyscapes with pieces of legislation in the electricity generation space and employ qualitative content analysis to identify the policy means affecting climate change mitigation. Our network analysis of the 2022 climate policyscape reveals that policies hindering climate mitigation remain largely present, which renders the climate policyscape incoherent. We show that policies supporting mitigation are more likely to behave as a group than policies hindering climate mitigation. Climate policies tend to be adopted as packages, whilst fossil policies remain a steady process throughout the history of the UK climate policyscape.","PeriodicalId":33632,"journal":{"name":"Frontiers in Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140995242","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}
Pub Date : 2024-05-09DOI: 10.3389/fclim.2024.1322550
Mesay Hailu Gudina, E. Alemu
Adoption of climate-smart agriculture practices are believed to have significantly lessened the devastating impact of climate change on agriculture. However, in countries like Ethiopia, the adoption and use level of climate-smart agriculture practices remains low. The understanding of farmers’ levels of CSA practice adoption and influencing factors is therefore crucial. The goal of the study is to evaluate the degree to which various CSA practices were being used in the study area, as well as adoption determinants. The study was conducted in Welmera district, Oromia, Ethiopia. Three kebeles were chosen from the district, and a random sample of 306 farmers was picked. We used a cross-sectional household survey, a focus group discussion, and interviews with key informants. A multivariate probit model was employed to investigate the factors influencing the adoption of multiple climate-smart agriculture practices. According to the result, conservation agriculture, integrated soil fertility management, and crop diversification are the most often used CSA practices. The results also revealed that male farmers outperformed female farmers in terms of crop diversity and improved animal feed and feeding practice adoption. The age of farmers has a considerable and unfavorable impact on their likelihood of adopting improved soil fertility management and crop diversification practices. However, it has a positive and considerable impact on the adoption of agroforestry practices. With regards to economic factors, having a relatively big farmland area considerably enhances the adoption of conservation agriculture, enhances soil fertility management and crop diversity, and improves livestock feed and feeding methods and post-harvest technology practice. Improved livestock feed and feeding are more likely to be used with higher farm income. Having a significant number of animals strongly promotes the adoption of conservation agriculture, and access to financial services positively impacts agroforestry, diversification of crops, and postharvest technology practice adoption. Furthermore, institutional factors including access to agricultural extension services and training were discovered to be important and beneficial for crop diversification; similarly, access to field day participation was discovered to have a significant and positive impact on the adoption of conservation agriculture and improved soil fertility management practices. It is critical to raise awareness about climate change among farmers and experts, as well as to incorporate location-specific CSA practices into agricultural programs.
{"title":"Factors influencing small holder farmers adoption of climate SMART agriculture practices in Welmera Woreda, Central Ethiopia","authors":"Mesay Hailu Gudina, E. Alemu","doi":"10.3389/fclim.2024.1322550","DOIUrl":"https://doi.org/10.3389/fclim.2024.1322550","url":null,"abstract":"Adoption of climate-smart agriculture practices are believed to have significantly lessened the devastating impact of climate change on agriculture. However, in countries like Ethiopia, the adoption and use level of climate-smart agriculture practices remains low. The understanding of farmers’ levels of CSA practice adoption and influencing factors is therefore crucial. The goal of the study is to evaluate the degree to which various CSA practices were being used in the study area, as well as adoption determinants. The study was conducted in Welmera district, Oromia, Ethiopia. Three kebeles were chosen from the district, and a random sample of 306 farmers was picked. We used a cross-sectional household survey, a focus group discussion, and interviews with key informants. A multivariate probit model was employed to investigate the factors influencing the adoption of multiple climate-smart agriculture practices. According to the result, conservation agriculture, integrated soil fertility management, and crop diversification are the most often used CSA practices. The results also revealed that male farmers outperformed female farmers in terms of crop diversity and improved animal feed and feeding practice adoption. The age of farmers has a considerable and unfavorable impact on their likelihood of adopting improved soil fertility management and crop diversification practices. However, it has a positive and considerable impact on the adoption of agroforestry practices. With regards to economic factors, having a relatively big farmland area considerably enhances the adoption of conservation agriculture, enhances soil fertility management and crop diversity, and improves livestock feed and feeding methods and post-harvest technology practice. Improved livestock feed and feeding are more likely to be used with higher farm income. Having a significant number of animals strongly promotes the adoption of conservation agriculture, and access to financial services positively impacts agroforestry, diversification of crops, and postharvest technology practice adoption. Furthermore, institutional factors including access to agricultural extension services and training were discovered to be important and beneficial for crop diversification; similarly, access to field day participation was discovered to have a significant and positive impact on the adoption of conservation agriculture and improved soil fertility management practices. It is critical to raise awareness about climate change among farmers and experts, as well as to incorporate location-specific CSA practices into agricultural programs.","PeriodicalId":33632,"journal":{"name":"Frontiers in Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140997380","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}
Pub Date : 2024-05-06DOI: 10.3389/fclim.2024.1384753
Bálint Forgács
Innovative communication theories propose that we understand messages not by decoding their meaning but by inferring what speakers intend to express. However scientifically accurate the messages climate scientists have put forward, the appropriate inferences may not have been drawn by most of their audiences. One of the main reasons may be that scientific metaphors allow for multiple interpretations, yet, because of their expressive power, they impact discourses disproportionately. Climate communication took a path of euphemistic scientific expressions partially due to the noble scientific norms of self-restraint and modesty, but the hidden implications of climate jargon distort the way non-experts think about the heating climate. Consequently, the current climate jargon hinders informed decisions about Earth’s life support systems. Changing the softened expressions of climate language, from the cool of basic research to the heat and compassion of medical contexts, may allow for more productive public and political debates – which may lead to more powerful policy solutions. Speaking and thinking in medical terms could turn the perception of worst case scenarios from hypotheticals or doomism to life-saving interventions. We typically start reducing fever before it gets out of control, let alone crosses a threshold of potential death. Instead of putting on a positivist mascara, a calm and serious discussion of safety measures in medical terms, for example, talking about climatic tipping cascades as metastases, could foster a more honest evaluation of the required legal and regulatory steps to keep our home planet habitable.
{"title":"A medical language for climate discourse","authors":"Bálint Forgács","doi":"10.3389/fclim.2024.1384753","DOIUrl":"https://doi.org/10.3389/fclim.2024.1384753","url":null,"abstract":"Innovative communication theories propose that we understand messages not by decoding their meaning but by inferring what speakers intend to express. However scientifically accurate the messages climate scientists have put forward, the appropriate inferences may not have been drawn by most of their audiences. One of the main reasons may be that scientific metaphors allow for multiple interpretations, yet, because of their expressive power, they impact discourses disproportionately. Climate communication took a path of euphemistic scientific expressions partially due to the noble scientific norms of self-restraint and modesty, but the hidden implications of climate jargon distort the way non-experts think about the heating climate. Consequently, the current climate jargon hinders informed decisions about Earth’s life support systems. Changing the softened expressions of climate language, from the cool of basic research to the heat and compassion of medical contexts, may allow for more productive public and political debates – which may lead to more powerful policy solutions. Speaking and thinking in medical terms could turn the perception of worst case scenarios from hypotheticals or doomism to life-saving interventions. We typically start reducing fever before it gets out of control, let alone crosses a threshold of potential death. Instead of putting on a positivist mascara, a calm and serious discussion of safety measures in medical terms, for example, talking about climatic tipping cascades as metastases, could foster a more honest evaluation of the required legal and regulatory steps to keep our home planet habitable.","PeriodicalId":33632,"journal":{"name":"Frontiers in Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141007854","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}
Pub Date : 2024-05-03DOI: 10.3389/fclim.2024.1391634
Tiffany A Shaw, Paola A. Arias, Mat Collins, D. Coumou, A. Diedhiou, C. Garfinkel, Shipra Jain, M. Roxy, Marlene Kretschmer, L. R. Leung, S. Narsey, Olivia Martius, Richard Seager, Theodore G. Shepherd, Anna A. Sörensson, Tannecia S. Stephenson, Michael Taylor, Lin Wang
Climate change has emerged across many regions. Some observed regional climate changes, such as amplified Arctic warming and land-sea warming contrasts have been predicted by climate models. However, many other observed regional changes, such as changes in tropical sea surface temperature and monsoon rainfall are not well simulated by climate model ensembles even when taking into account natural internal variability and structural uncertainties in the response of models to anthropogenic radiative forcing. This suggests climate model predictions may not fully reflect what our future will look like. The discrepancies between models and observations are not well understood due to several real and apparent puzzles and limitations such as the “signal-to-noise paradox” and real-world record-shattering extremes falling outside of the possible range predicted by models. Addressing these discrepancies, puzzles and limitations is essential, because understanding and reliably predicting regional climate change is necessary in order to communicate effectively about the underlying drivers of change, provide reliable information to stakeholders, enable societies to adapt, and increase resilience and reduce vulnerability. The challenges of achieving this are greater in the Global South, especially because of the lack of observational data over long time periods and a lack of scientific focus on Global South climate change. To address discrepancies between observations and models, it is important to prioritize resources for understanding regional climate predictions and analyzing where and why models and observations disagree via testing hypotheses of drivers of biases using observations and models. Gaps in understanding can be discovered and filled by exploiting new tools, such as artificial intelligence/machine learning, high-resolution models, new modeling experiments in the model hierarchy, better quantification of forcing, and new observations. Conscious efforts are needed toward creating opportunities that allow regional experts, particularly those from the Global South, to take the lead in regional climate research. This includes co-learning in technical aspects of analyzing simulations and in the physics and dynamics of regional climate change. Finally, improved methods of regional climate communication are needed, which account for the underlying uncertainties, in order to provide reliable and actionable information to stakeholders and the media.
{"title":"Regional climate change: consensus, discrepancies, and ways forward","authors":"Tiffany A Shaw, Paola A. Arias, Mat Collins, D. Coumou, A. Diedhiou, C. Garfinkel, Shipra Jain, M. Roxy, Marlene Kretschmer, L. R. Leung, S. Narsey, Olivia Martius, Richard Seager, Theodore G. Shepherd, Anna A. Sörensson, Tannecia S. Stephenson, Michael Taylor, Lin Wang","doi":"10.3389/fclim.2024.1391634","DOIUrl":"https://doi.org/10.3389/fclim.2024.1391634","url":null,"abstract":"Climate change has emerged across many regions. Some observed regional climate changes, such as amplified Arctic warming and land-sea warming contrasts have been predicted by climate models. However, many other observed regional changes, such as changes in tropical sea surface temperature and monsoon rainfall are not well simulated by climate model ensembles even when taking into account natural internal variability and structural uncertainties in the response of models to anthropogenic radiative forcing. This suggests climate model predictions may not fully reflect what our future will look like. The discrepancies between models and observations are not well understood due to several real and apparent puzzles and limitations such as the “signal-to-noise paradox” and real-world record-shattering extremes falling outside of the possible range predicted by models. Addressing these discrepancies, puzzles and limitations is essential, because understanding and reliably predicting regional climate change is necessary in order to communicate effectively about the underlying drivers of change, provide reliable information to stakeholders, enable societies to adapt, and increase resilience and reduce vulnerability. The challenges of achieving this are greater in the Global South, especially because of the lack of observational data over long time periods and a lack of scientific focus on Global South climate change. To address discrepancies between observations and models, it is important to prioritize resources for understanding regional climate predictions and analyzing where and why models and observations disagree via testing hypotheses of drivers of biases using observations and models. Gaps in understanding can be discovered and filled by exploiting new tools, such as artificial intelligence/machine learning, high-resolution models, new modeling experiments in the model hierarchy, better quantification of forcing, and new observations. Conscious efforts are needed toward creating opportunities that allow regional experts, particularly those from the Global South, to take the lead in regional climate research. This includes co-learning in technical aspects of analyzing simulations and in the physics and dynamics of regional climate change. Finally, improved methods of regional climate communication are needed, which account for the underlying uncertainties, in order to provide reliable and actionable information to stakeholders and the media.","PeriodicalId":33632,"journal":{"name":"Frontiers in Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141016148","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}
Pub Date : 2024-05-02DOI: 10.3389/fclim.2024.1332233
Emily C. L. Black, Ross Maidment, Elizabeth Rees, Eleanor Nderitu
Drought poses a continual threat to both lives and livelihoods in the Global South. Although the impact on food security from drought could be reduced through early release of funds, the humanitarian sector typically reacts to crises rather than anticipates them. A significant challenge lies in devising a drought monitoring and forecasting system that can function across environmentally and economically diverse regions. This is particularly evident in Pakistan, which encompasses environments ranging from fertile riverbeds to arid deserts. This paper details the development, implementation, and operation of an anticipatory drought Disaster Risk Financing (DRF) programme for the provinces of Punjab, Sindh, and Baluchistan in Pakistan. Key to the DRF development are a new yield model for the primary crop in the target season (winter wheat), and a novel forecasting system for four seasonal drought indicators - namely winter wheat yield, precipitation, normalised difference vegetation index (NDVI) and vegetation health index (VHI). Formal evaluations demonstrate that the forecasts are skillful up to 2 months in advance of the end of the season – enabling anticipatory release of funds. The work presented here is applicable beyond Pakistan. Indeed, the model and the methodologies are sufficiently broad and adaptable to be utilised in arid and semi-arid regions across the Global South.
{"title":"A new drought model for disaster risk management in the Punjab, Sindh and Baluchistan provinces of Pakistan","authors":"Emily C. L. Black, Ross Maidment, Elizabeth Rees, Eleanor Nderitu","doi":"10.3389/fclim.2024.1332233","DOIUrl":"https://doi.org/10.3389/fclim.2024.1332233","url":null,"abstract":"Drought poses a continual threat to both lives and livelihoods in the Global South. Although the impact on food security from drought could be reduced through early release of funds, the humanitarian sector typically reacts to crises rather than anticipates them. A significant challenge lies in devising a drought monitoring and forecasting system that can function across environmentally and economically diverse regions. This is particularly evident in Pakistan, which encompasses environments ranging from fertile riverbeds to arid deserts. This paper details the development, implementation, and operation of an anticipatory drought Disaster Risk Financing (DRF) programme for the provinces of Punjab, Sindh, and Baluchistan in Pakistan. Key to the DRF development are a new yield model for the primary crop in the target season (winter wheat), and a novel forecasting system for four seasonal drought indicators - namely winter wheat yield, precipitation, normalised difference vegetation index (NDVI) and vegetation health index (VHI). Formal evaluations demonstrate that the forecasts are skillful up to 2 months in advance of the end of the season – enabling anticipatory release of funds. The work presented here is applicable beyond Pakistan. Indeed, the model and the methodologies are sufficiently broad and adaptable to be utilised in arid and semi-arid regions across the Global South.","PeriodicalId":33632,"journal":{"name":"Frontiers in Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141017912","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}
Pub Date : 2024-05-02DOI: 10.3389/fclim.2024.1332196
Inoussa Zagre, F. Akinseye, O. N. Worou, Mama Kone, Aliou Faye
In dryland agricultural systems, developing appropriate climate-smart technology (CST) options is important to adapt agriculture to climate change and transition toward sustainability, as well as increasing productivity and incomes. This study examines the impact of socio-economic and institutional support on community responses to climate change and the impact of changes in three selected regions of Senegal (Meouane, Thiel, and Daga Birame), which fall within different rainfall gradients. It captures community perceptions of climate change, compares them to long-term meteorological data, and identifies site-specific response strategies. Communities are randomly selected from a list of communities within the target sites. We used a two-stage stratified sampling method to select sample households. First, purposive sampling was conducted to select at least six (6) villages as a cluster within each rainfall gradient. Likewise, the selection of households in each cluster was based on the main value chains of crops grown in the study area, namely groundnut, millet, black pea, and livestock. A total of 145 households participated in this study. Data from surveys conducted during the 2022 post-harvest season were analyzed using descriptive statistics and logit models. The analysis found that smallholders have a comprehensive understanding of climate indicators, including annual rainfall, shortened crop seasons, and rising temperatures, compared to historical data trends. Additionally, the results highlight how farmers view the negative impacts of seasonal rainfall deficiencies (72%), delayed start of the growing season (88%), frequent dry spells (68%), and longer dry spells (76%), which ultimately lead to decreased grain and fodder yields. The logit model also highlights the importance of socio-economic and institutional factors such as access to credit, extension services, agricultural experience, frequency of interaction with extension workers, and access to government subsidies. These factors play a crucial role in farmers’ decision to adopt CST. Given the specificity of community contexts, these insights have important implications for guiding policymakers and making it easier to reduce climate risk among smallholder farmers.
{"title":"Climate change adaptation strategies among smallholder farmers in Senegal’s semi-arid zone: role of socio-economic factors and institutional supports","authors":"Inoussa Zagre, F. Akinseye, O. N. Worou, Mama Kone, Aliou Faye","doi":"10.3389/fclim.2024.1332196","DOIUrl":"https://doi.org/10.3389/fclim.2024.1332196","url":null,"abstract":"In dryland agricultural systems, developing appropriate climate-smart technology (CST) options is important to adapt agriculture to climate change and transition toward sustainability, as well as increasing productivity and incomes. This study examines the impact of socio-economic and institutional support on community responses to climate change and the impact of changes in three selected regions of Senegal (Meouane, Thiel, and Daga Birame), which fall within different rainfall gradients. It captures community perceptions of climate change, compares them to long-term meteorological data, and identifies site-specific response strategies. Communities are randomly selected from a list of communities within the target sites. We used a two-stage stratified sampling method to select sample households. First, purposive sampling was conducted to select at least six (6) villages as a cluster within each rainfall gradient. Likewise, the selection of households in each cluster was based on the main value chains of crops grown in the study area, namely groundnut, millet, black pea, and livestock. A total of 145 households participated in this study. Data from surveys conducted during the 2022 post-harvest season were analyzed using descriptive statistics and logit models. The analysis found that smallholders have a comprehensive understanding of climate indicators, including annual rainfall, shortened crop seasons, and rising temperatures, compared to historical data trends. Additionally, the results highlight how farmers view the negative impacts of seasonal rainfall deficiencies (72%), delayed start of the growing season (88%), frequent dry spells (68%), and longer dry spells (76%), which ultimately lead to decreased grain and fodder yields. The logit model also highlights the importance of socio-economic and institutional factors such as access to credit, extension services, agricultural experience, frequency of interaction with extension workers, and access to government subsidies. These factors play a crucial role in farmers’ decision to adopt CST. Given the specificity of community contexts, these insights have important implications for guiding policymakers and making it easier to reduce climate risk among smallholder farmers.","PeriodicalId":33632,"journal":{"name":"Frontiers in Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141022637","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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