In the context of climate change, coastal flood risk is intensifying globally, particularly in China, where intricate coastlines and frequent tropical cyclones make storm surges a major concern. Despite local government's efforts to initiate coastal monitoring networks and qualitative risk guidelines, there remains a gap in detailed and efficient quantitative assessments for combinations of multiple sea-level components. To address this, we develop the Tropical Cyclone Storm Surge-based Flood Risk Assessment under Combined Scenarios (TCSoS-FRACS). This framework integrates impacts of storm surges, high tides, and sea-level rise using a hybrid of statistical and dynamic models to balance reliability and efficiency. By combining hazard, exposure, and vulnerability, it incorporates economic and demographic factors for a deeper understanding of risk composition. Applying TCSoS-FRACS to Hainan Island reveals that the combined effects of storm surges, high tides, and sea-level rise significantly amplify local coastal flood risk, increasing economic losses to 4.27–5.90 times and affected populations to 4.96–6.23 times. Additionally, transitioning from Fossil-fueled Development (SSP5-8.5) to Sustainability (SSP1-1.9) can reduce the risk increase by approximately half. The equivalence in flood hazard between current high tides and future sea level under a sustainable scenario boosts confidence in climate change adaptation efforts. However, coastal cities with low hazard but high exposure need heightened vigilance in flood defense, as future risk could escalate sharply. Our study provides new insights into coastal flood risk on Hainan Island and other regions with similar profiles, offering a transferable and efficient tool for disaster risk management and aiding in regional sustainable development.
{"title":"Tropical Cyclone Storm Surge-Based Flood Risk Assessment Under Combined Scenarios of High Tides and Sea-Level Rise: A Case Study of Hainan Island, China","authors":"Ziying Zhou, Saini Yang, Fuyu Hu, Bingrui Chen, Xianwu Shi, Xiaoyan Liu","doi":"10.1029/2023EF004236","DOIUrl":"https://doi.org/10.1029/2023EF004236","url":null,"abstract":"<p>In the context of climate change, coastal flood risk is intensifying globally, particularly in China, where intricate coastlines and frequent tropical cyclones make storm surges a major concern. Despite local government's efforts to initiate coastal monitoring networks and qualitative risk guidelines, there remains a gap in detailed and efficient quantitative assessments for combinations of multiple sea-level components. To address this, we develop the <span>T</span>ropical <span>C</span>yclone <span>S</span>t<span>o</span>rm <span>S</span>urge-based <span>F</span>lood <span>R</span>isk <span>A</span>ssessment under <span>C</span>ombined <span>S</span>cenarios (TCSoS-FRACS). This framework integrates impacts of storm surges, high tides, and sea-level rise using a hybrid of statistical and dynamic models to balance reliability and efficiency. By combining hazard, exposure, and vulnerability, it incorporates economic and demographic factors for a deeper understanding of risk composition. Applying TCSoS-FRACS to Hainan Island reveals that the combined effects of storm surges, high tides, and sea-level rise significantly amplify local coastal flood risk, increasing economic losses to 4.27–5.90 times and affected populations to 4.96–6.23 times. Additionally, transitioning from Fossil-fueled Development (SSP5-8.5) to Sustainability (SSP1-1.9) can reduce the risk increase by approximately half. The equivalence in flood hazard between current high tides and future sea level under a sustainable scenario boosts confidence in climate change adaptation efforts. However, coastal cities with low hazard but high exposure need heightened vigilance in flood defense, as future risk could escalate sharply. Our study provides new insights into coastal flood risk on Hainan Island and other regions with similar profiles, offering a transferable and efficient tool for disaster risk management and aiding in regional sustainable development.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"12 8","pages":""},"PeriodicalIF":7.3,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2023EF004236","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142013674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Donghui Xu, Gautam Bisht, Dongyu Feng, Zeli Tan, Lingcheng Li, Han Qiu, L. Ruby Leung
Sea-level rise (SLR) poses a severe threat to the coastal environment through seawater intrusion into freshwater aquifers. The rising groundwater table also exacerbates the risk of pluvial, fluvial, and groundwater flooding in coastal regions. However, current Earth system models (ESMs) commonly ignore the exchanges of water at the land-ocean interface. To address this gap, we developed a novel land-ocean hydrologic coupling scheme in a state-of-the-science ESM, the Energy Exascale Earth System Model version 2 (E3SMv2). The new scheme includes the lateral exchange between seawater and groundwater and the vertical infiltration of seawater driven by the SLR-induced inundation. Simulations were performed with the updated E3SMv2 for the global land-ocean interface to assess the impacts of SLR on coastal groundwater under a high CO2 emission scenario. By the middle of this century, seawater infiltration on the inundated areas will be the dominant component in the land-ocean coupling process, while the lateral subsurface flow exchange will be much smaller. The SLR-induced seawater infiltration will raise the groundwater levels, enhance evapotranspiration, and increase runoff with distinct spatial patterns globally in the future. Although the coupling process is induced by SLR, we found topography and warming temperature have more control on the coupling impacts, probably due to the relatively modest magnitude of SLR during the selected future period. Overall, our study suggests significant groundwater and seawater exchange at the land-ocean interface, which needs to be considered in ESMs.
{"title":"Impacts of Sea-Level Rise on Coastal Groundwater Table Simulated by an Earth System Model With a Land-Ocean Coupling Scheme","authors":"Donghui Xu, Gautam Bisht, Dongyu Feng, Zeli Tan, Lingcheng Li, Han Qiu, L. Ruby Leung","doi":"10.1029/2024EF004479","DOIUrl":"https://doi.org/10.1029/2024EF004479","url":null,"abstract":"<p>Sea-level rise (SLR) poses a severe threat to the coastal environment through seawater intrusion into freshwater aquifers. The rising groundwater table also exacerbates the risk of pluvial, fluvial, and groundwater flooding in coastal regions. However, current Earth system models (ESMs) commonly ignore the exchanges of water at the land-ocean interface. To address this gap, we developed a novel land-ocean hydrologic coupling scheme in a state-of-the-science ESM, the Energy Exascale Earth System Model version 2 (E3SMv2). The new scheme includes the lateral exchange between seawater and groundwater and the vertical infiltration of seawater driven by the SLR-induced inundation. Simulations were performed with the updated E3SMv2 for the global land-ocean interface to assess the impacts of SLR on coastal groundwater under a high CO<sub>2</sub> emission scenario. By the middle of this century, seawater infiltration on the inundated areas will be the dominant component in the land-ocean coupling process, while the lateral subsurface flow exchange will be much smaller. The SLR-induced seawater infiltration will raise the groundwater levels, enhance evapotranspiration, and increase runoff with distinct spatial patterns globally in the future. Although the coupling process is induced by SLR, we found topography and warming temperature have more control on the coupling impacts, probably due to the relatively modest magnitude of SLR during the selected future period. Overall, our study suggests significant groundwater and seawater exchange at the land-ocean interface, which needs to be considered in ESMs.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"12 8","pages":""},"PeriodicalIF":7.3,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF004479","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142013643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Leila Rahimi, Mushfiqul Hoque, Ebrahim Ahmadisharaf, Nasrin Alamdari, Vasubandhu Misra, Ana Carolina Maran, Shih-Chieh Kao, Amir AghaKouchak, Rocky Talchabhadel
Projecting future climate variables is essential for comprehending the potential impacts on hydroclimatic hazards like floods and droughts. Evaluating these impacts is challenging due to the coarse spatial resolution of global climate models (GCMs); therefore, bias correction is widely used. Here, we applied two statistical methods—standard empirical quantile mapping (EQM) and a hybrid approach, EQM with linear correction (EQM-LIN)—to bias correct precipitation and air temperature simulated by nine GCMs. We used historical observations from 20 weather stations across South Florida to project future climate under three shared socioeconomic pathways (SSPs). Compared to the EQM, the hybrid EQM-LIN method improved R2 of daily quantiles by up to 30% over the historical period and improved MAE up to 70% in months that contain most extreme values. Projected extreme precipitation at the weather stations showed that, compared to the EQM-LIN, the EQM method underestimates the high quantiles by up to 26% in SSP585. The projected changes in annual maximum precipitation from historical period (1985–2014) to near future (2040–2069) and far future (2070–2100) were between 2% and 16% across the study area. Projected future precipitation suggested a slight decrease during summer but an increase in fall. This, along with rising summer temperatures, suggested that South Florida can experience rapid oscillations from warmer summers and increased flooding in fall under future climate. Additionally, our comparative analyses with globally and nationally downscaled studies showed that such coarse scale studies do not represent the climatic extremes well, particularly for high quantile precipitation.
{"title":"Future Climate Projections for South Florida: Improving the Accuracy of Air Temperature and Precipitation Extremes With a Hybrid Statistical Bias Correction Technique","authors":"Leila Rahimi, Mushfiqul Hoque, Ebrahim Ahmadisharaf, Nasrin Alamdari, Vasubandhu Misra, Ana Carolina Maran, Shih-Chieh Kao, Amir AghaKouchak, Rocky Talchabhadel","doi":"10.1029/2024EF004531","DOIUrl":"https://doi.org/10.1029/2024EF004531","url":null,"abstract":"<p>Projecting future climate variables is essential for comprehending the potential impacts on hydroclimatic hazards like floods and droughts. Evaluating these impacts is challenging due to the coarse spatial resolution of global climate models (GCMs); therefore, bias correction is widely used. Here, we applied two statistical methods—standard empirical quantile mapping (EQM) and a hybrid approach, EQM with linear correction (EQM-LIN)—to bias correct precipitation and air temperature simulated by nine GCMs. We used historical observations from 20 weather stations across South Florida to project future climate under three shared socioeconomic pathways (SSPs). Compared to the EQM, the hybrid EQM-LIN method improved R<sup>2</sup> of daily quantiles by up to 30% over the historical period and improved MAE up to 70% in months that contain most extreme values. Projected extreme precipitation at the weather stations showed that, compared to the EQM-LIN, the EQM method underestimates the high quantiles by up to 26% in SSP585. The projected changes in annual maximum precipitation from historical period (1985–2014) to near future (2040–2069) and far future (2070–2100) were between 2% and 16% across the study area. Projected future precipitation suggested a slight decrease during summer but an increase in fall. This, along with rising summer temperatures, suggested that South Florida can experience rapid oscillations from warmer summers and increased flooding in fall under future climate. Additionally, our comparative analyses with globally and nationally downscaled studies showed that such coarse scale studies do not represent the climatic extremes well, particularly for high quantile precipitation.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"12 8","pages":""},"PeriodicalIF":7.3,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF004531","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142013642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nicolás A. Vásquez, Pablo A. Mendoza, Wouter J. M. Knoben, Louise Arnal, Miguel Lagos-Zúñiga, Martyn Clark, Ximena Vargas
Characterizing climate change impacts on water resources typically relies on Global Climate Model (GCM) outputs that are bias-corrected using observational data sets. In this process, two pivotal decisions are (a) the Bias Correction Method (BCM) and (b) how to handle the historically observed time series, which can be used as a continuous whole (i.e., without dividing it into sub-periods), or partitioned into monthly, seasonal (e.g., 3 months), or any other temporal stratification (TS). Here, we examine how the interplay between the choice of BCM, TS, and the raw GCM seasonality may affect historical portrayals and projected changes. To this end, we use outputs from 29 GCMs belonging to the CMIP6 under the Shared Socioeconomic Pathway 5–8.5 scenario, using seven BCMs and three TSs (entire period, seasonal, and monthly). The results show that the effectiveness of BCMs in removing biases can vary depending on the TS and climate indices analyzed. Further, the choice of BCM and TS may yield different projected change signals and seasonality (especially for precipitation), even for climate models with low bias and a reasonable representation of precipitation seasonality during a reference period. Because some BCMs may be computationally expensive, we recommend using the linear scaling method as a diagnostics tool to assess how the choice of TS may affect the projected precipitation seasonality of a specific GCM. More generally, the results presented here unveil trade-offs in how BCMs are applied, regardless of the climate regime, urging the hydroclimate community to carefully implement these techniques.
{"title":"The Key Role of Temporal Stratification for GCM Bias Correction in Climate Impact Assessments","authors":"Nicolás A. Vásquez, Pablo A. Mendoza, Wouter J. M. Knoben, Louise Arnal, Miguel Lagos-Zúñiga, Martyn Clark, Ximena Vargas","doi":"10.1029/2023EF004242","DOIUrl":"https://doi.org/10.1029/2023EF004242","url":null,"abstract":"<p>Characterizing climate change impacts on water resources typically relies on Global Climate Model (GCM) outputs that are bias-corrected using observational data sets. In this process, two pivotal decisions are (a) the Bias Correction Method (BCM) and (b) how to handle the historically observed time series, which can be used as a continuous whole (i.e., without dividing it into sub-periods), or partitioned into monthly, seasonal (e.g., 3 months), or any other temporal stratification (TS). Here, we examine how the interplay between the choice of BCM, TS, and the raw GCM seasonality may affect historical portrayals and projected changes. To this end, we use outputs from 29 GCMs belonging to the CMIP6 under the Shared Socioeconomic Pathway 5–8.5 scenario, using seven BCMs and three TSs (entire period, seasonal, and monthly). The results show that the effectiveness of BCMs in removing biases can vary depending on the TS and climate indices analyzed. Further, the choice of BCM and TS may yield different projected change signals and seasonality (especially for precipitation), even for climate models with low bias and a reasonable representation of precipitation seasonality during a reference period. Because some BCMs may be computationally expensive, we recommend using the linear scaling method as a diagnostics tool to assess how the choice of TS may affect the projected precipitation seasonality of a specific GCM. More generally, the results presented here unveil trade-offs in how BCMs are applied, regardless of the climate regime, urging the hydroclimate community to carefully implement these techniques.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"12 8","pages":""},"PeriodicalIF":7.3,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2023EF004242","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142007211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohammad Bizhanimanzar, Gabriel Rondeau-Genesse, Louis-Philippe Caron, Denis Lefaivre, Edouard Mailhot
In low-lying coastal regions, the joint occurrence of high river flow and high water levels can cause coastal flooding with substantial economic and social implications. Recent studies over Canada's coasts have shown that neglecting the interdependency between flood drivers can underestimate the risk of flooding by up to 50%. However, to date, such interdependency has not been investigated for the coasts of the St. Lawrence River, Estuary and Gulf system (StL), where Sea Level Rise (SLR), along with intensified river peaks, are already threatening these communities. In this study, a copula-based bivariate frequency analysis was applied to quantify the likelihood of occurrence of flooding events under dependent and independent assumptions, for 26 sites along the StL. Furthermore, to quantify the impact of anthropogenic climate change, the joint return period in historical period was compared with that of projected SLR associated with RCP 8.5 for the year 2100. Results show that (a) the independence assumption can underestimate the likelihood of occurrence of flooding event in the Fluvial Section of the StL by up to 30 times and (b) the SLR can increase the likelihood of occurrence of flooding event by up to 50 times in the Estuary and the Gulf and by up to 5 times in the Fluvial Section of the StL. This study highlights the need for explicit consideration of the dependence between flood drivers and of SLR in the delineation of flood maps along the coast of the St. Lawrence.
{"title":"Joint Occurrence of Extreme Water Level and River Flows in St. Lawrence River Coasts Under Present and Sea Level Rise Conditions","authors":"Mohammad Bizhanimanzar, Gabriel Rondeau-Genesse, Louis-Philippe Caron, Denis Lefaivre, Edouard Mailhot","doi":"10.1029/2023EF004027","DOIUrl":"https://doi.org/10.1029/2023EF004027","url":null,"abstract":"<p>In low-lying coastal regions, the joint occurrence of high river flow and high water levels can cause coastal flooding with substantial economic and social implications. Recent studies over Canada's coasts have shown that neglecting the interdependency between flood drivers can underestimate the risk of flooding by up to 50%. However, to date, such interdependency has not been investigated for the coasts of the St. Lawrence River, Estuary and Gulf system (StL), where Sea Level Rise (SLR), along with intensified river peaks, are already threatening these communities. In this study, a copula-based bivariate frequency analysis was applied to quantify the likelihood of occurrence of flooding events under dependent and independent assumptions, for 26 sites along the StL. Furthermore, to quantify the impact of anthropogenic climate change, the joint return period in historical period was compared with that of projected SLR associated with RCP 8.5 for the year 2100. Results show that (a) the independence assumption can underestimate the likelihood of occurrence of flooding event in the Fluvial Section of the StL by up to 30 times and (b) the SLR can increase the likelihood of occurrence of flooding event by up to 50 times in the Estuary and the Gulf and by up to 5 times in the Fluvial Section of the StL. This study highlights the need for explicit consideration of the dependence between flood drivers and of SLR in the delineation of flood maps along the coast of the St. Lawrence.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"12 8","pages":""},"PeriodicalIF":7.3,"publicationDate":"2024-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2023EF004027","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142007149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ocean warming and associated deoxygenation caused by anthropogenic global warming are impacting marine ecosystems. This article contextualizes and provides perspectives on key insights from a recently published study by Fröb et al. in Earth's Future (2024). The authors employ historical and high-emission scenario simulations through a state-of-the-art Earth system model to detect abrupt and persistent changes in the viability of marine habitats by leveraging an ecophysiological framework that quantifies how temperature and oxygen jointly limit the distribution of life in the ocean for a number of ecophysiotypes. A changepoint analysis is used to objectively detect shifts in decadal to multi-decadal mean states in potential marine habitats. They observe a decrease in the ocean volume capable of providing viable habitats for those ecophysiotypes with positive sensitivity to hypoxia. About half of these decreases occur abruptly, thus highlighting potential risks on the capacity of marine organisms to cope with a changing environment.
{"title":"Towards a Less Habitable Ocean","authors":"Yeray Santana-Falcón","doi":"10.1029/2024EF004879","DOIUrl":"https://doi.org/10.1029/2024EF004879","url":null,"abstract":"<p>Ocean warming and associated deoxygenation caused by anthropogenic global warming are impacting marine ecosystems. This article contextualizes and provides perspectives on key insights from a recently published study by Fröb et al. in Earth's Future (2024). The authors employ historical and high-emission scenario simulations through a state-of-the-art Earth system model to detect abrupt and persistent changes in the viability of marine habitats by leveraging an ecophysiological framework that quantifies how temperature and oxygen jointly limit the distribution of life in the ocean for a number of ecophysiotypes. A changepoint analysis is used to objectively detect shifts in decadal to multi-decadal mean states in potential marine habitats. They observe a decrease in the ocean volume capable of providing viable habitats for those ecophysiotypes with positive sensitivity to hypoxia. About half of these decreases occur abruptly, thus highlighting potential risks on the capacity of marine organisms to cope with a changing environment.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"12 8","pages":""},"PeriodicalIF":7.3,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF004879","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141991724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Meng Luo, Adam Daigneault, Xin Zhao, Dalei Hao, Min Chen
Anthropogenic land use and land cover change (LULCC) is projected to continue in the future. However, the influence of forest management on forest productivity change and subsequent LULCC projections remains under-investigated. This study explored the impacts of forest management-induced change in forest productivity on LULCC throughout the 21st century. Specifically, we developed a framework to softly couple the Global Change Analysis Model and Global Timber Model to consider forest management-induced forest productivity change and projected future LULCC across the five Shared Socioeconomic Pathways (SSPs). We found future increases in forest management intensity overall drive the increase of forest productivity. The forest management-induced forest productivity change shows diverse responses across all SSPs, with a global increase from 2015 to 2100 ranging from 3.9% (SSP3) to 8.8% (SSP1). This further leads to an overall decrease in the total area with a change of land use types, with the largest decrease under SSP1 (−7.5%) and the smallest decrease under SSP3 (−0.7%) in 2100. Among land use types, considering forest management-induced change significantly reduces the expansion of managed forest and also reduces the loss of natural land in 2100 across SSPs. This suggests that ignoring forest management-induced forest productivity change underestimates the efficiency of wood production, overestimates the managed forest expansion required to meet the future demand, and consequently, potentially introduces uncertainties into relevant analyses, for example, carbon cycle and biodiversity. Thus, we advocate to better account for the impacts of forest management in future LULCC projections.
{"title":"Impacts of Forest Management-Induced Productivity Changes on Future Land Use and Land Cover Change","authors":"Meng Luo, Adam Daigneault, Xin Zhao, Dalei Hao, Min Chen","doi":"10.1029/2024EF004878","DOIUrl":"https://doi.org/10.1029/2024EF004878","url":null,"abstract":"<p>Anthropogenic land use and land cover change (LULCC) is projected to continue in the future. However, the influence of forest management on forest productivity change and subsequent LULCC projections remains under-investigated. This study explored the impacts of forest management-induced change in forest productivity on LULCC throughout the 21st century. Specifically, we developed a framework to softly couple the Global Change Analysis Model and Global Timber Model to consider forest management-induced forest productivity change and projected future LULCC across the five Shared Socioeconomic Pathways (SSPs). We found future increases in forest management intensity overall drive the increase of forest productivity. The forest management-induced forest productivity change shows diverse responses across all SSPs, with a global increase from 2015 to 2100 ranging from 3.9% (SSP3) to 8.8% (SSP1). This further leads to an overall decrease in the total area with a change of land use types, with the largest decrease under SSP1 (−7.5%) and the smallest decrease under SSP3 (−0.7%) in 2100. Among land use types, considering forest management-induced change significantly reduces the expansion of managed forest and also reduces the loss of natural land in 2100 across SSPs. This suggests that ignoring forest management-induced forest productivity change underestimates the efficiency of wood production, overestimates the managed forest expansion required to meet the future demand, and consequently, potentially introduces uncertainties into relevant analyses, for example, carbon cycle and biodiversity. Thus, we advocate to better account for the impacts of forest management in future LULCC projections.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"12 8","pages":""},"PeriodicalIF":7.3,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF004878","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141980393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
G. Senger, B. Chtirkova, D. Folini, J. Wohland, M. Wild
Climatic extreme events are important because they can strongly impact humans, infrastructure, and biodiversity and will be affected by a changing climate. Surface Solar Radiation (SSR) is the primary energy source for solar photovoltaics (PV), which will be indispensable in future zero-emissions energy systems. Despite their pivotal role, extreme events in SSR remain under-documented. We provide a starting point in extreme SSR analysis by focusing on events caused by internal variability alone and therefore building a baseline for future extreme SSR research. We analyze extreme SSR events using daily-mean data from the pre-industrial control simulations (piControl) of the Coupled Model Intercomparison Project—Phase 6. We investigate their role in PV energy generation using the Global Solar Energy Estimator with the intent of strengthening the energy system's resilience. Our results show a pronounced asymmetry between consecutive days with extremely high and extremely low solar radiation over land, the former occurring more frequently than the latter. Moreover, our results call for detailed PV generation modeling that includes panel geometry. Simple models based on linear SSR representations prove insufficient due to pronounced seasonal variations and strong non-linear SSR dependency of high extremes. Our results demonstrate how climate model results can be leveraged to understand persistent radiation extremes that are relevant for future energy systems.
气候极端事件非常重要,因为它们会对人类、基础设施和生物多样性造成严重影响,并将受到气候变化的影响。地表太阳辐射(SSR)是太阳能光伏发电(PV)的主要能源,在未来的零排放能源系统中不可或缺。尽管其作用举足轻重,但地表太阳辐射极端事件的记录仍然不足。我们通过关注仅由内部变率引起的事件,为极端 SSR 分析提供了一个起点,从而为未来的极端 SSR 研究建立了一个基线。我们利用耦合模式相互比较项目第六阶段的工业化前控制模拟(piControl)中的日均值数据分析了极端 SSR 事件。我们利用全球太阳能估算器研究了它们在光伏发电中的作用,旨在加强能源系统的恢复能力。我们的研究结果表明,陆地上太阳辐射极高和极低的连续天数之间存在明显的不对称性,前者出现的频率高于后者。此外,我们的结果还要求建立详细的光伏发电模型,其中包括电池板的几何形状。基于线性 SSR 表示的简单模型被证明是不够的,因为存在明显的季节性变化和高极端太阳辐射的强烈非线性 SSR 依赖性。我们的研究结果展示了如何利用气候模型结果来了解与未来能源系统相关的持续极端辐射。
{"title":"Persistent Extreme Surface Solar Radiation and Its Implications on Solar Photovoltaics","authors":"G. Senger, B. Chtirkova, D. Folini, J. Wohland, M. Wild","doi":"10.1029/2023EF004266","DOIUrl":"https://doi.org/10.1029/2023EF004266","url":null,"abstract":"<p>Climatic extreme events are important because they can strongly impact humans, infrastructure, and biodiversity and will be affected by a changing climate. Surface Solar Radiation (SSR) is the primary energy source for solar photovoltaics (PV), which will be indispensable in future zero-emissions energy systems. Despite their pivotal role, extreme events in SSR remain under-documented. We provide a starting point in extreme SSR analysis by focusing on events caused by internal variability alone and therefore building a baseline for future extreme SSR research. We analyze extreme SSR events using daily-mean data from the pre-industrial control simulations (piControl) of the Coupled Model Intercomparison Project—Phase 6. We investigate their role in PV energy generation using the Global Solar Energy Estimator with the intent of strengthening the energy system's resilience. Our results show a pronounced asymmetry between consecutive days with extremely high and extremely low solar radiation over land, the former occurring more frequently than the latter. Moreover, our results call for detailed PV generation modeling that includes panel geometry. Simple models based on linear SSR representations prove insufficient due to pronounced seasonal variations and strong non-linear SSR dependency of high extremes. Our results demonstrate how climate model results can be leveraged to understand persistent radiation extremes that are relevant for future energy systems.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"12 8","pages":""},"PeriodicalIF":7.3,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2023EF004266","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141980488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The International Maritime Organization (IMO) introduced new regulations on the sulfur content of shipping emissions in 2020 (IMO2020). Estimates of the climatic impact of this global reduction in anthropogenic sulfate aerosols vary widely. Here, we contribute to narrowing this uncertainty with two sets of climate model simulations using UKESM1. Using fixed sea-surface temperature atmosphere-only simulations, we estimate an IMO2020 global effective radiative forcing of 0.139 ± 0.019 Wm−2 and show that most of this forcing is due to aerosol-induced changes to cloud properties. Using coupled ocean-atmosphere simulations, we note significant changes in cloud top droplet number concentration and size across regions with high shipping traffic density, and—in the North Atlantic and North Pacific—these microphysical changes translate to a decrease in cloud albedo. We show that IMO2020 increases global annual surface temperature on average by 0.046 ± 0.010°C across 2020–2029; approximately 2–3 years of global warming. Furthermore, our model simulations show that IMO2020 helps to explain the exceptional warming in 2023, but other factors are needed to fully account for it. The year 2023 also had an exceptionally large decrease in reflected shortwave radiation at the top-of-atmosphere. Our results show that IMO2020 made that more likely, yet the observations are within the variability of simulations without the reduction in shipping emissions. To better understand the climatic impacts of IMO2020, a model intercomparison project would be valuable whilst the community waits for a more complete observational record.
{"title":"IMO2020 Regulations Accelerate Global Warming by up to 3 Years in UKESM1","authors":"G. Jordan, M. Henry","doi":"10.1029/2024EF005011","DOIUrl":"https://doi.org/10.1029/2024EF005011","url":null,"abstract":"<p>The International Maritime Organization (IMO) introduced new regulations on the sulfur content of shipping emissions in 2020 (IMO2020). Estimates of the climatic impact of this global reduction in anthropogenic sulfate aerosols vary widely. Here, we contribute to narrowing this uncertainty with two sets of climate model simulations using UKESM1. Using fixed sea-surface temperature atmosphere-only simulations, we estimate an IMO2020 global effective radiative forcing of 0.139 ± 0.019 Wm<sup>−2</sup> and show that most of this forcing is due to aerosol-induced changes to cloud properties. Using coupled ocean-atmosphere simulations, we note significant changes in cloud top droplet number concentration and size across regions with high shipping traffic density, and—in the North Atlantic and North Pacific—these microphysical changes translate to a decrease in cloud albedo. We show that IMO2020 increases global annual surface temperature on average by 0.046 ± 0.010°C across 2020–2029; approximately 2–3 years of global warming. Furthermore, our model simulations show that IMO2020 helps to explain the exceptional warming in 2023, but other factors are needed to fully account for it. The year 2023 also had an exceptionally large decrease in reflected shortwave radiation at the top-of-atmosphere. Our results show that IMO2020 made that more likely, yet the observations are within the variability of simulations without the reduction in shipping emissions. To better understand the climatic impacts of IMO2020, a model intercomparison project would be valuable whilst the community waits for a more complete observational record.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"12 8","pages":""},"PeriodicalIF":7.3,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF005011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141980490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wake Smith, Madeline F. Bartels, Jasper G. Boers, Christian V. Rice
Tipping elements are features of the climate system that can display self-reinforcing and non-linear responses if pushed beyond a certain threshold (the “tipping point”). Models suggest that we may surpass several of these tipping points in the next few decades, irrespective of which emissions pathway humanity follows. Some tipping elements reside in the Arctic and Antarctic and could potentially be avoided or arrested via a stratospheric aerosol injection (SAI) program applied only at the poles. This paper considers the utility of proactively developing the capacity to respond to emergent tipping element threats at the poles as a matter of risk management. It then examines both the air and ground infrastructure that would be required to operationalize such capability by 2040 and finds that this would require a funded launch decision by a financially credible actor by roughly 2030.
{"title":"On Thin Ice: Solar Geoengineering to Manage Tipping Element Risks in the Cryosphere by 2040","authors":"Wake Smith, Madeline F. Bartels, Jasper G. Boers, Christian V. Rice","doi":"10.1029/2024EF004797","DOIUrl":"https://doi.org/10.1029/2024EF004797","url":null,"abstract":"<p>Tipping elements are features of the climate system that can display self-reinforcing and non-linear responses if pushed beyond a certain threshold (the “tipping point”). Models suggest that we may surpass several of these tipping points in the next few decades, irrespective of which emissions pathway humanity follows. Some tipping elements reside in the Arctic and Antarctic and could potentially be avoided or arrested via a stratospheric aerosol injection (SAI) program applied only at the poles. This paper considers the utility of proactively developing the capacity to respond to emergent tipping element threats at the poles as a matter of risk management. It then examines both the air and ground infrastructure that would be required to operationalize such capability by 2040 and finds that this would require a funded launch decision by a financially credible actor by roughly 2030.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"12 8","pages":""},"PeriodicalIF":7.3,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF004797","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141980457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}