Pub Date : 2024-07-16DOI: 10.1088/1748-9326/ad5b09
Jessica Hetzer, M. Forrest, Jaime Ribalaygua, Carlos Prado-López, T. Hickler
The climate over Europe has been recorded to be hotter, drier, and more fire-prone over the last decade than ever before, leading to concerns about how climate change will alter fire weather in the future. A typical measure to estimate fire weather severity based on climate is the Canadian fire weather index (FWI). In this study, we used high-resolution, bias-corrected climate model output (∼9 km) from six CMIP6 climate models and four shared socio-economic pathway projections (SSPs) to calculate consistent and comparable daily FWI datasets for Europe from 1950 to 2080. Our study aims to identify regional and large-scale shifts in fire weather severity and its predictability over time to support adaptive planning. We show that irrespective of the future SSP, fire weather will become more severe, but the increase is much stronger under high greenhouse gas emissions. This leads to new areas being exposed to severe fire weather, such as central Europe and rapidly warming mountainous areas. Already fire-prone regions in southern Europe will experience more extreme conditions. We conclude that only the low-emission SSP1-2.6 pathway can prevent strong increases in fire weather beyond the 2050s. Fire surveillance and management will become more important, even in areas and in seasons where they have not been in the focus so far.
{"title":"The fire weather in Europe: large-scale trends towards higher danger","authors":"Jessica Hetzer, M. Forrest, Jaime Ribalaygua, Carlos Prado-López, T. Hickler","doi":"10.1088/1748-9326/ad5b09","DOIUrl":"https://doi.org/10.1088/1748-9326/ad5b09","url":null,"abstract":"\u0000 The climate over Europe has been recorded to be hotter, drier, and more fire-prone over the last decade than ever before, leading to concerns about how climate change will alter fire weather in the future. A typical measure to estimate fire weather severity based on climate is the Canadian fire weather index (FWI). In this study, we used high-resolution, bias-corrected climate model output (∼9 km) from six CMIP6 climate models and four shared socio-economic pathway projections (SSPs) to calculate consistent and comparable daily FWI datasets for Europe from 1950 to 2080. Our study aims to identify regional and large-scale shifts in fire weather severity and its predictability over time to support adaptive planning. We show that irrespective of the future SSP, fire weather will become more severe, but the increase is much stronger under high greenhouse gas emissions. This leads to new areas being exposed to severe fire weather, such as central Europe and rapidly warming mountainous areas. Already fire-prone regions in southern Europe will experience more extreme conditions. We conclude that only the low-emission SSP1-2.6 pathway can prevent strong increases in fire weather beyond the 2050s. Fire surveillance and management will become more important, even in areas and in seasons where they have not been in the focus so far.","PeriodicalId":507917,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141640429","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 : 2024-07-16DOI: 10.1088/1748-9326/ad63bc
Jung Ok, Eun-Ji Song, Sinil Yang, Baek-Min Kim, Ki-Young Kim
Severe heatwaves have become increasingly frequent over the Indian subcontinent in recent decades. This study found that the increase in extreme heatwaves is related to a significant decadal change in surface temperatures over the Indian subcontinent, and revealed that the increase in convective activity in the Philippine Sea plays a crucial role in this decadal change in surface temperature. Specifically, the surface temperature over the Indian subcontinent in spring has increased significantly by approximately 0.64°C in recent years (1998–2022: post-1998) compared to the past (1959–1997: pre-1998), leading to more intense and frequent heatwaves, particularly in March and April. The difference in atmospheric changes between these two periods shows that the enhancement of convective activity over the Philippine Sea drives an anomalous elongated anticyclonic circulation over the Indian subcontinent. This circulation pattern, marked by clearer skies and increased incident solar radiation, significantly contributes to the heat extremes in the Indian subcontinent. Additionally, stationary wave model experiments demonstrate that local diabatic heating over the Philippine Sea is significantly linked to robust spring Indian heatwaves through the Matsuno-Gill response.
{"title":"Interdecadal changes and the role of Philippine Sea convection in the intensification of Indian spring heatwaves","authors":"Jung Ok, Eun-Ji Song, Sinil Yang, Baek-Min Kim, Ki-Young Kim","doi":"10.1088/1748-9326/ad63bc","DOIUrl":"https://doi.org/10.1088/1748-9326/ad63bc","url":null,"abstract":"\u0000 Severe heatwaves have become increasingly frequent over the Indian subcontinent in recent decades. This study found that the increase in extreme heatwaves is related to a significant decadal change in surface temperatures over the Indian subcontinent, and revealed that the increase in convective activity in the Philippine Sea plays a crucial role in this decadal change in surface temperature. Specifically, the surface temperature over the Indian subcontinent in spring has increased significantly by approximately 0.64°C in recent years (1998–2022: post-1998) compared to the past (1959–1997: pre-1998), leading to more intense and frequent heatwaves, particularly in March and April. The difference in atmospheric changes between these two periods shows that the enhancement of convective activity over the Philippine Sea drives an anomalous elongated anticyclonic circulation over the Indian subcontinent. This circulation pattern, marked by clearer skies and increased incident solar radiation, significantly contributes to the heat extremes in the Indian subcontinent. Additionally, stationary wave model experiments demonstrate that local diabatic heating over the Philippine Sea is significantly linked to robust spring Indian heatwaves through the Matsuno-Gill response.","PeriodicalId":507917,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141641841","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 : 2024-07-16DOI: 10.1088/1748-9326/ad63be
R. Vautard, Clair R. Barnes, S. Philip, S. Kew, Izidine Pinto, Friederike E. L. Otto
Heat extremes have been increasing both in frequency and in intensity in most land regions of the world, and this increase has been attributed to human activities. In the last decade, many outstanding and record shattering heat extremes have occurred worldwide, triggering fears of a nonlinear behaviour or an “acceleration” in the development of heat conditions, considering the warming level when the event occurred. Here we show that the evolution of yearly temperature maxima, with return periods above 10 years, consistently shifts with global temperatures and does not significantly depart from this behaviour in recent years or decades when considered globally or at the scale of continents. This result is obtained by using a classical statistical event attribution technique, where the assumption that the distribution of block-maxima extremes linearly shifts with global warming is tested across years and world land regions. However, the pace of frequency change is large, with the probability of heat extremes exponentially rising and nearly doubling every decade since 1979, particularly when considering events with a return period of about 10 to 50 years in 2000. This makes the climate of a decade ago unrepresentative of today’s climate. Our results overall mean that we do not expect events like the recent outstanding extremes to undergo nonlinear changes, despite fast changes. They also show that assumptions underlying attribution techniques used in many recent studies are consistent with recent temperature trends.
{"title":"Heat extremes linearly shift with global warming, with frequency doubling per decade since 1979","authors":"R. Vautard, Clair R. Barnes, S. Philip, S. Kew, Izidine Pinto, Friederike E. L. Otto","doi":"10.1088/1748-9326/ad63be","DOIUrl":"https://doi.org/10.1088/1748-9326/ad63be","url":null,"abstract":"\u0000 Heat extremes have been increasing both in frequency and in intensity in most land regions of the world, and this increase has been attributed to human activities. In the last decade, many outstanding and record shattering heat extremes have occurred worldwide, triggering fears of a nonlinear behaviour or an “acceleration” in the development of heat conditions, considering the warming level when the event occurred. Here we show that the evolution of yearly temperature maxima, with return periods above 10 years, consistently shifts with global temperatures and does not significantly depart from this behaviour in recent years or decades when considered globally or at the scale of continents. This result is obtained by using a classical statistical event attribution technique, where the assumption that the distribution of block-maxima extremes linearly shifts with global warming is tested across years and world land regions. However, the pace of frequency change is large, with the probability of heat extremes exponentially rising and nearly doubling every decade since 1979, particularly when considering events with a return period of about 10 to 50 years in 2000. This makes the climate of a decade ago unrepresentative of today’s climate. Our results overall mean that we do not expect events like the recent outstanding extremes to undergo nonlinear changes, despite fast changes. They also show that assumptions underlying attribution techniques used in many recent studies are consistent with recent temperature trends.","PeriodicalId":507917,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141643948","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 : 2024-07-16DOI: 10.1088/1748-9326/ad63bf
X. Qie, Y. Yair, Shaoxuan Di, Zifan Huang, Rubin Jiang
Lightning has profound social implications for public safety and usually causes casualties and significant damage to infrastructure. Due to the advancement of both ground-based and spaceborne detection technology, lightning has been monitored globally in recent decades as an essential vari¬able of climate change and an indicator of severe weather. This article reviews recent progress in the study of lightning variations and their response to temperature and aerosols, based on both spaceborne and ground-based lightning data. The responses of lightning to temperature and aerosol show large spatial and temporal heterogeneity, with relation to the meteorological and environmental conditions. The latest research show that lightning exhibited significant increase in some high altitude or high latitude regions, such as the Tibetan Plateau and Arctic regions, where undergone fast warming during the recent decades and the ecosystems there is fragile. Aerosol particles play an important role in modulating lightning variations under certain dynamical and thermodynamic conditions in some regions, even on a global scale. The projected lightning activity will generally increase in the future but may with very few exceptions. Continuous long-term lightning observations with consistent spatial and temporal detection efficiency remain crucial for tracking the response of lightning to climate change in the coming decades.
{"title":"Lightning response to temperature and aerosols","authors":"X. Qie, Y. Yair, Shaoxuan Di, Zifan Huang, Rubin Jiang","doi":"10.1088/1748-9326/ad63bf","DOIUrl":"https://doi.org/10.1088/1748-9326/ad63bf","url":null,"abstract":"\u0000 Lightning has profound social implications for public safety and usually causes casualties and significant damage to infrastructure. Due to the advancement of both ground-based and spaceborne detection technology, lightning has been monitored globally in recent decades as an essential vari¬able of climate change and an indicator of severe weather. This article reviews recent progress in the study of lightning variations and their response to temperature and aerosols, based on both spaceborne and ground-based lightning data. The responses of lightning to temperature and aerosol show large spatial and temporal heterogeneity, with relation to the meteorological and environmental conditions. The latest research show that lightning exhibited significant increase in some high altitude or high latitude regions, such as the Tibetan Plateau and Arctic regions, where undergone fast warming during the recent decades and the ecosystems there is fragile. Aerosol particles play an important role in modulating lightning variations under certain dynamical and thermodynamic conditions in some regions, even on a global scale. The projected lightning activity will generally increase in the future but may with very few exceptions. Continuous long-term lightning observations with consistent spatial and temporal detection efficiency remain crucial for tracking the response of lightning to climate change in the coming decades.","PeriodicalId":507917,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141644238","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 : 2024-07-16DOI: 10.1088/1748-9326/ad63bd
Shubham Goswami, Chirag Rajendra Ternikar, Rajsekhar Kandala, Netra S. Pillai, Vivek Kumar Yadav, Abhishek, Jisha Joseph, Subimal Ghosh, B. Vishwakarma
Evapotranspiration (ET) is one of the most important yet highly uncertain components of the water cycle. Available modelled ET products do not necessarily agree with each other at various spatiotemporal scales, either due to limitations on input data and/or due to model assumptions and simplifications. Therefore, using water budget equation to estimate ET has gained attention. However, a large number of water-budget combinations with large uncertainties are available that increases ambiguity in choosing the best ET estimate. Here, the Kalman filter is employed for ingesting 96 water-budget based ET estimates and produce a global ET product with uncertainty < 2 mm, and it captures the general spatiotemporal pattern of ET and the inter-annual variability over all continents. Since the water budget includes storage change due to human interventions, our ET estimates are superior over regions with strong irrigation signal, such as the Ganges basin. We verify our claim by using a modified variable infiltration capacity model that simulates irrigation activities as well. Our ET estimates have a global mean positive trend of 0.18 ± 0.02 mm/year with larger regional variations that are discussed.
{"title":"Water-budget based Evapotranspiration product captures natural and human-caused variability","authors":"Shubham Goswami, Chirag Rajendra Ternikar, Rajsekhar Kandala, Netra S. Pillai, Vivek Kumar Yadav, Abhishek, Jisha Joseph, Subimal Ghosh, B. Vishwakarma","doi":"10.1088/1748-9326/ad63bd","DOIUrl":"https://doi.org/10.1088/1748-9326/ad63bd","url":null,"abstract":"\u0000 Evapotranspiration (ET) is one of the most important yet highly uncertain components of the water cycle. Available modelled ET products do not necessarily agree with each other at various spatiotemporal scales, either due to limitations on input data and/or due to model assumptions and simplifications. Therefore, using water budget equation to estimate ET has gained attention. However, a large number of water-budget combinations with large uncertainties are available that increases ambiguity in choosing the best ET estimate. Here, the Kalman filter is employed for ingesting 96 water-budget based ET estimates and produce a global ET product with uncertainty < 2 mm, and it captures the general spatiotemporal pattern of ET and the inter-annual variability over all continents. Since the water budget includes storage change due to human interventions, our ET estimates are superior over regions with strong irrigation signal, such as the Ganges basin. We verify our claim by using a modified variable infiltration capacity model that simulates irrigation activities as well. Our ET estimates have a global mean positive trend of 0.18 ± 0.02 mm/year with larger regional variations that are discussed.","PeriodicalId":507917,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141642784","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 : 2024-07-15DOI: 10.1088/1748-9326/ad6339
Ankit Chandra
{"title":"The water-carbon nexus: is it worthwhile to generate carbon credits based on agricultural water management?","authors":"Ankit Chandra","doi":"10.1088/1748-9326/ad6339","DOIUrl":"https://doi.org/10.1088/1748-9326/ad6339","url":null,"abstract":"\u0000 <jats:p/>","PeriodicalId":507917,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141647639","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 : 2024-07-12DOI: 10.1088/1748-9326/ad627c
Maximilian Zachow, Harald Kunstmann, Daniel Miralles, S. Asseng
While multi-model ensembles (MMEs) of seasonal climate models (SCMs) have been used for crop yield forecasting, there has not been a systematic attempt to select the most skillful SCMs to optimize the performance of a MME and improve in-season yield forecasts. Here, we propose a statistical model to forecast regional and national wheat yield variability from 1993-2016 over the main wheat production area in Argentina. Monthly mean temperature and precipitation from the four months (Aug-Nov) before harvest were used as features. The model was validated for end-of-season estimation in December using reanalysis data (ERA) from the European Centre for Medium-Range Weather Forecasts (ECMWF) as well as for in-season forecasts from June to November using a MME of three SCMs from 10 SCMs analyzed. A benchmark model for end-of-season yield estimation using ERA data achieved a R2 of 0.33, a root-mean-square error (RMSE) of 9.8% and a receiver operating characteristic (ROC) score of 0.8 on national level. On regional level, the model demonstrated the best estimation accuracy in the northern sub-humid Pampas with a R2 of 0.5, a RMSE of 12.6% and a ROC score of 0.9. Across all months of initialization, SCMs from the National Centers for Environmental Prediction, the National Center for Atmospheric Research and the Geophysical Fluid Dynamics Laboratory had the highest mean absolute error of forecasted features compared to ERA data. The most skillful in-season wheat yield forecasts were possible with a 3-member-MME, combining data from the SCMs of the ECMWF, the National Aeronautics and Space Administration and the French national meteorological service. This MME forecasted wheat yield on national level at the beginning of November, one month before harvest, with a R2 of 0.32, a RMSE of 9.9% and a ROC score of 0.7. This approach can be applied to other crops and regions.
{"title":"Multi-model ensembles for regional and national wheat yield forecasts in Argentina","authors":"Maximilian Zachow, Harald Kunstmann, Daniel Miralles, S. Asseng","doi":"10.1088/1748-9326/ad627c","DOIUrl":"https://doi.org/10.1088/1748-9326/ad627c","url":null,"abstract":"\u0000 While multi-model ensembles (MMEs) of seasonal climate models (SCMs) have been used for crop yield forecasting, there has not been a systematic attempt to select the most skillful SCMs to optimize the performance of a MME and improve in-season yield forecasts. Here, we propose a statistical model to forecast regional and national wheat yield variability from 1993-2016 over the main wheat production area in Argentina. Monthly mean temperature and precipitation from the four months (Aug-Nov) before harvest were used as features. The model was validated for end-of-season estimation in December using reanalysis data (ERA) from the European Centre for Medium-Range Weather Forecasts (ECMWF) as well as for in-season forecasts from June to November using a MME of three SCMs from 10 SCMs analyzed. A benchmark model for end-of-season yield estimation using ERA data achieved a R2 of 0.33, a root-mean-square error (RMSE) of 9.8% and a receiver operating characteristic (ROC) score of 0.8 on national level. On regional level, the model demonstrated the best estimation accuracy in the northern sub-humid Pampas with a R2 of 0.5, a RMSE of 12.6% and a ROC score of 0.9. Across all months of initialization, SCMs from the National Centers for Environmental Prediction, the National Center for Atmospheric Research and the Geophysical Fluid Dynamics Laboratory had the highest mean absolute error of forecasted features compared to ERA data. The most skillful in-season wheat yield forecasts were possible with a 3-member-MME, combining data from the SCMs of the ECMWF, the National Aeronautics and Space Administration and the French national meteorological service. This MME forecasted wheat yield on national level at the beginning of November, one month before harvest, with a R2 of 0.32, a RMSE of 9.9% and a ROC score of 0.7. This approach can be applied to other crops and regions.","PeriodicalId":507917,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141652758","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 : 2024-07-12DOI: 10.1088/1748-9326/ad627d
Mohit Anand, Raed Hamed, Nora Linscheid, Patrícia S. Silva, Julie Andre, Jakob Zscheischler, Freya K. Garry, Ana Bastos
The impact of spring climate on the Northern Hemisphere's summer vegetation activity and extremes has been extensively researched, but less attention has been devoted to whether and how winter climate may additionally influence vegetation extremes in summer. Here, we provide insights into the influence of winter temperature and precipitation on summer vegetation extremes in the Northern Hemisphere. To do this, we identify positive and negative extremes in the summer Leaf Area Index (LAI, a proxy for vegetation activity) and assess winter effects on those extremes using logistic regression at the regional scale. Over a quarter of the regions in the Northern Hemisphere show strong winter climate preconditioning on summer LAI extremes, which is typically stronger for croplands than forests. In the regions with strong winter preconditioning, spring LAI mediates the link between winter climate and summer LAI extremes through the ecological memory in seasonal legacy effects. Our findings suggest that extremely low summer LAI in both croplands and forests is preconditioned by colder and drier winters, while extremely high summer LAI in forests is associated with warmer and wetter winters. For low summer LAI in croplands, warmer winters are associated with an increased likelihood of extremes in mid-latitude regions and a reduced likelihood in high latitude regions. Consideration of winter preconditioning effects may improve understanding of inter-annual variability of vegetation activity and support agricultural and land management practitioners in anticipating detrimental effects of winter on crop yields and forest conditions.
春季气候对北半球夏季植被活动和极端情况的影响已得到广泛研究，但对冬季气候是否以及如何额外影响夏季植被极端情况的研究关注较少。在此，我们将深入探讨冬季气温和降水对北半球夏季极端植被的影响。为此，我们确定了夏季叶面积指数（LAI，植被活动的替代指标）的正负极端值，并在区域范围内使用逻辑回归评估了冬季对这些极端值的影响。北半球超过四分之一的地区显示出冬季气候对夏季叶面积指数极端值的强预调作用，通常耕地的预调作用强于森林。在冬季预报条件较强的地区，春季 LAI 通过季节遗留效应中的生态记忆调节冬季气候与夏季 LAI 极端值之间的联系。我们的研究结果表明，耕地和森林中极度低的夏季LAI都是以较冷和较干的冬季为前提条件的，而森林中极度高的夏季LAI则与较暖和较湿的冬季有关。对于耕地的低夏季 LAI 来说，在中纬度地区，温暖的冬季与出现极端天气的可能性增加有关，而在高纬度地区则与出现极端天气的可能性降低有关。考虑冬季先决条件的影响可提高对植被活动年际变化的认识，并帮助农业和土地管理从业人员预测冬季对作物产量和森林状况的不利影响。
{"title":"Winter climate preconditioning of summer vegetation extremes in the northern hemisphere","authors":"Mohit Anand, Raed Hamed, Nora Linscheid, Patrícia S. Silva, Julie Andre, Jakob Zscheischler, Freya K. Garry, Ana Bastos","doi":"10.1088/1748-9326/ad627d","DOIUrl":"https://doi.org/10.1088/1748-9326/ad627d","url":null,"abstract":"\u0000 The impact of spring climate on the Northern Hemisphere's summer vegetation activity and extremes has been extensively researched, but less attention has been devoted to whether and how winter climate may additionally influence vegetation extremes in summer. Here, we provide insights into the influence of winter temperature and precipitation on summer vegetation extremes in the Northern Hemisphere. To do this, we identify positive and negative extremes in the summer Leaf Area Index (LAI, a proxy for vegetation activity) and assess winter effects on those extremes using logistic regression at the regional scale. Over a quarter of the regions in the Northern Hemisphere show strong winter climate preconditioning on summer LAI extremes, which is typically stronger for croplands than forests. In the regions with strong winter preconditioning, spring LAI mediates the link between winter climate and summer LAI extremes through the ecological memory in seasonal legacy effects. Our findings suggest that extremely low summer LAI in both croplands and forests is preconditioned by colder and drier winters, while extremely high summer LAI in forests is associated with warmer and wetter winters. For low summer LAI in croplands, warmer winters are associated with an increased likelihood of extremes in mid-latitude regions and a reduced likelihood in high latitude regions. Consideration of winter preconditioning effects may improve understanding of inter-annual variability of vegetation activity and support agricultural and land management practitioners in anticipating detrimental effects of winter on crop yields and forest conditions.","PeriodicalId":507917,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141654733","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 : 2024-07-11DOI: 10.1088/1748-9326/ad61ff
Seongeun Kim, Jooyoung Jeon, Hyungjun Kim
Amid increasing concerns about the impact of climate change on financial asset pricing, this paper investigates how drought risk affects stock returns in the U.S. energy sector over a thirty-year period (1990-2019). To this end, we ranked energy companies based on the long-term trend of the Palmer Drought Severity Index (PDSI) to compare stock performance between groups experiencing the most significant increases and decreases in drought risk. Our analysis indicates that firms located in drought-prone regions have lower stock returns than those in regions with decreasing drought risk, particularly since 2010. This finding is noteworthy, as the average PDSI trend gap between regions at high risk of drought and those at low risk has widened during this period. We further divide our sample of energy companies into two subsectors—fuel production and electric utility—and find that the stock prices of both subsectors have been negatively affected by drought risk since 2010. The study underscores the energy sector's dependency on water availability, suggesting novel implications for policymakers and investors in assessing the financial impacts of drought risks in their climate-related decision-making.
{"title":"Drought and energy stock markets in the United States","authors":"Seongeun Kim, Jooyoung Jeon, Hyungjun Kim","doi":"10.1088/1748-9326/ad61ff","DOIUrl":"https://doi.org/10.1088/1748-9326/ad61ff","url":null,"abstract":"\u0000 Amid increasing concerns about the impact of climate change on financial asset pricing, this paper investigates how drought risk affects stock returns in the U.S. energy sector over a thirty-year period (1990-2019). To this end, we ranked energy companies based on the long-term trend of the Palmer Drought Severity Index (PDSI) to compare stock performance between groups experiencing the most significant increases and decreases in drought risk. Our analysis indicates that firms located in drought-prone regions have lower stock returns than those in regions with decreasing drought risk, particularly since 2010. This finding is noteworthy, as the average PDSI trend gap between regions at high risk of drought and those at low risk has widened during this period. We further divide our sample of energy companies into two subsectors—fuel production and electric utility—and find that the stock prices of both subsectors have been negatively affected by drought risk since 2010. The study underscores the energy sector's dependency on water availability, suggesting novel implications for policymakers and investors in assessing the financial impacts of drought risks in their climate-related decision-making.","PeriodicalId":507917,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141657222","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 : 2024-07-11DOI: 10.1088/1748-9326/ad6201
A. Urfels, Alisher Mirzabaev, Stephen Bricx, P. Deb, Kumala Dewi, Gio Evangelista, R. Flor, Ben Harris, M.M.J.G.C.N. Jayasiri, Avinash Kishore, A. J. Mcdonald, Manoranjan Mondal, Emma Quicho, Kazuki Saito, Virender Kumar, Alice Laborte
{"title":"Economics of sustainable irrigation in smallholder agriculture: Implications for food security and climate action","authors":"A. Urfels, Alisher Mirzabaev, Stephen Bricx, P. Deb, Kumala Dewi, Gio Evangelista, R. Flor, Ben Harris, M.M.J.G.C.N. Jayasiri, Avinash Kishore, A. J. Mcdonald, Manoranjan Mondal, Emma Quicho, Kazuki Saito, Virender Kumar, Alice Laborte","doi":"10.1088/1748-9326/ad6201","DOIUrl":"https://doi.org/10.1088/1748-9326/ad6201","url":null,"abstract":"\u0000 <jats:p/>","PeriodicalId":507917,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141658351","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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