Pub Date : 2024-07-24DOI: 10.1088/1748-9326/ad66e7
Ana Manero, Anna Normyle, M. Vardon, Quentin Grafton
No abstract for Perspectives
没有 "视角 "的摘要
{"title":"'Two sides of the same coin'? Bridging water accounting and valuation for better decision-making","authors":"Ana Manero, Anna Normyle, M. Vardon, Quentin Grafton","doi":"10.1088/1748-9326/ad66e7","DOIUrl":"https://doi.org/10.1088/1748-9326/ad66e7","url":null,"abstract":"\u0000 No abstract for Perspectives","PeriodicalId":507917,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141808711","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 : 2024-07-24DOI: 10.1088/1748-9326/ad66e8
Chuangwu Deng, Shifei Tu, Guoping Gao, Jianjun Xu
Storm surges caused by tropical cyclones (TCs) have long ranked first among all types of marine disasters in casualties and economic losses, and can lead to further regional exacerbation of consequences stemming from these losses along different coastlines. Understanding the spatial footprints of storm surges is thus highly important for developing effective risk management and protection plans. To this end, we designed an ideal storm surge model based on FVCOM to explore the relationship between TC intensity and the spatial footprint of storm surges, and its intrinsic mechanism. The spatial footprints of both positive and negative storm surges were positively correlated with TC intensity; however, the latter was more sensitive to the intensity when the TC intensity is weaker than CAT3 TC’s. The average positive storm surge footprint of CAT1 was 574 km, with CAT3 and CAT5 increasing by 6% and 25%, respectively, compared to CAT1. The average spatial footprint of the negative storm surge of CAT1 was 1,407 km, with CAT3 and CAT5 increasing by 18% and 29%, respectively, compared to CAT1. The decomposition and mechanism analysis of the storm surge show that the main contributing component of the total surge at the south end of the storm’s landfall and during the time of the forerunner was the Ekman surge, whereas the contribution of the normal surge component to the north and during the time of the main surge and resurgence was dominant. In addition, not all the spatial footprints of the storm surge components increased with the TC intensity, as the total surge did, similar to the Ekman surge. These quantitative analyses and intrinsic mechanisms provide a theoretical basis for predicting and evaluating storm surge risks.
{"title":"Effects of tropical cyclone intensity on spatial footprints of storm surges: an idealized numerical experiment","authors":"Chuangwu Deng, Shifei Tu, Guoping Gao, Jianjun Xu","doi":"10.1088/1748-9326/ad66e8","DOIUrl":"https://doi.org/10.1088/1748-9326/ad66e8","url":null,"abstract":"\u0000 Storm surges caused by tropical cyclones (TCs) have long ranked first among all types of marine disasters in casualties and economic losses, and can lead to further regional exacerbation of consequences stemming from these losses along different coastlines. Understanding the spatial footprints of storm surges is thus highly important for developing effective risk management and protection plans. To this end, we designed an ideal storm surge model based on FVCOM to explore the relationship between TC intensity and the spatial footprint of storm surges, and its intrinsic mechanism. The spatial footprints of both positive and negative storm surges were positively correlated with TC intensity; however, the latter was more sensitive to the intensity when the TC intensity is weaker than CAT3 TC’s. The average positive storm surge footprint of CAT1 was 574 km, with CAT3 and CAT5 increasing by 6% and 25%, respectively, compared to CAT1. The average spatial footprint of the negative storm surge of CAT1 was 1,407 km, with CAT3 and CAT5 increasing by 18% and 29%, respectively, compared to CAT1. The decomposition and mechanism analysis of the storm surge show that the main contributing component of the total surge at the south end of the storm’s landfall and during the time of the forerunner was the Ekman surge, whereas the contribution of the normal surge component to the north and during the time of the main surge and resurgence was dominant. In addition, not all the spatial footprints of the storm surge components increased with the TC intensity, as the total surge did, similar to the Ekman surge. These quantitative analyses and intrinsic mechanisms provide a theoretical basis for predicting and evaluating storm surge risks.","PeriodicalId":507917,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141806762","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 : 2024-07-24DOI: 10.1088/1748-9326/ad66e6
Bohan Huang, Zhuo Liu, Qingyun Duan, A. Rajib, Jina Yin
Climate change significantly impacts agricultural production, ecosystem stability, and socioeconomic development. Global Climate Models (GCMs) serve as the primary tool for simulating historical and future precipitation patterns. However, due to issues such as coarse resolution, boundary condition, and parameterization, model outputs require bias correction. With the evolution of deep learning techniques, supervised Convolutional Neural Network (CNN) frameworks have gained popularity in the area of climate model bias correction but face limitations in spatial correlation assumptions and data sparsity, particularly for extreme precipitation This study proposed an unsupervised learning approach using Cycle Generative Adversarial Network (CycleGAN) to correct the ensemble mean bias of models and compare its performance with CNN and Quantile Mapping methods. The results demonstrate that the proposed CycleGAN approach outperforms both CNN and Quantile Mapping in ensemble mean bias correction. It effectively learns the overall distribution of precipitation through an adversarial process and yields better extreme precipitation predictions.
{"title":"Unsupervised deep learning bias correction of CMIP6 global ensemble precipitation predictions with Cycle Generative Adversarial Network","authors":"Bohan Huang, Zhuo Liu, Qingyun Duan, A. Rajib, Jina Yin","doi":"10.1088/1748-9326/ad66e6","DOIUrl":"https://doi.org/10.1088/1748-9326/ad66e6","url":null,"abstract":"\u0000 Climate change significantly impacts agricultural production, ecosystem stability, and socioeconomic development. Global Climate Models (GCMs) serve as the primary tool for simulating historical and future precipitation patterns. However, due to issues such as coarse resolution, boundary condition, and parameterization, model outputs require bias correction. With the evolution of deep learning techniques, supervised Convolutional Neural Network (CNN) frameworks have gained popularity in the area of climate model bias correction but face limitations in spatial correlation assumptions and data sparsity, particularly for extreme precipitation This study proposed an unsupervised learning approach using Cycle Generative Adversarial Network (CycleGAN) to correct the ensemble mean bias of models and compare its performance with CNN and Quantile Mapping methods. The results demonstrate that the proposed CycleGAN approach outperforms both CNN and Quantile Mapping in ensemble mean bias correction. It effectively learns the overall distribution of precipitation through an adversarial process and yields better extreme precipitation predictions.","PeriodicalId":507917,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141807686","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 : 2024-07-23DOI: 10.1088/1748-9326/ad6677
Jianyu Wang, P. Zhai, Baiquan Zhou, Chao Li, Yang Chen
The rapid warming of the Tibetan Plateau (TP) in recent decades has led to severe consequences, including the melting of glaciers and snow cover, which further accelerates warming. Accurately projecting the magnitude of future warming is crucial for effective climate change adaptation. However, the projection of future temperature change is model dependent. In this study, we demonstrate a significant correlation between the historical intermodel warming trend and future temperature change, suggesting this relationship could be used to calibrate the best estimate of projections and reduce the uncertainty by observations. For a high emission scenario, the constraint helps to narrow down the uncertainty range of annual and summer temperature change on the western TP by up to 2 °C and 4 °C, respectively, in the end of this century. The most substantial calibrated increase of future change is in winter up to 2 °C, followed by autumn with an increase of up to about 1 °C. Discrepancies of historical warming trend among different observation datasets expose the largest impact on the constrained best estimate compared with emergent relationship derived from different climate models and historical periods.
{"title":"Constraining future surface air temperature change on the Tibetan Plateau","authors":"Jianyu Wang, P. Zhai, Baiquan Zhou, Chao Li, Yang Chen","doi":"10.1088/1748-9326/ad6677","DOIUrl":"https://doi.org/10.1088/1748-9326/ad6677","url":null,"abstract":"\u0000 The rapid warming of the Tibetan Plateau (TP) in recent decades has led to severe consequences, including the melting of glaciers and snow cover, which further accelerates warming. Accurately projecting the magnitude of future warming is crucial for effective climate change adaptation. However, the projection of future temperature change is model dependent. In this study, we demonstrate a significant correlation between the historical intermodel warming trend and future temperature change, suggesting this relationship could be used to calibrate the best estimate of projections and reduce the uncertainty by observations. For a high emission scenario, the constraint helps to narrow down the uncertainty range of annual and summer temperature change on the western TP by up to 2 °C and 4 °C, respectively, in the end of this century. The most substantial calibrated increase of future change is in winter up to 2 °C, followed by autumn with an increase of up to about 1 °C. Discrepancies of historical warming trend among different observation datasets expose the largest impact on the constrained best estimate compared with emergent relationship derived from different climate models and historical periods.","PeriodicalId":507917,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141812312","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 : 2024-07-23DOI: 10.1088/1748-9326/ad6679
Karimon Nesha, Martin Herold, Johannes Reiche, Robert N. Masolele, K. Hergoualc’h, E. Swails, Daniel Murdiyarso, C. Ewango
The largest tropical peatland complex in the Cuvette Centrale, is marked by persistent knowledge gaps. We assessed recent peat forest disturbances and their direct drivers from 2019 to 2021 in Cuvette Centrale, spanning the Republic of Congo (ROC) and the Democratic Republic of Congo (DRC). Utilizing peatland extent and Radar for Detecting Deforestation (RADD) alert data, we analyzed spatial and temporal patterns of disturbances. Further, we examined 2,267 randomly sampled peat forest disturbance events through visual interpretation of monthly Planet and Sentinel 2A data to identify direct drivers. Our findings revealed that between 2019 and 2021, about 91% of disturbances occurred in DRC, with hotspots concentrated in the northwest Sud-Ubangi district. Disturbances predominantly followed a sharp seasonal pattern, recurring during the first half of each year with temporal hotspots emerging between February and May, closely associated with smallholder agriculture activities. Smallholder agriculture accounted for over 88% of disturbances in Cuvette Centrale, representing a leading role both in ROC (~77%) and DRC (~89%). While, small-scale logging contributed 7% to disturbances in the region, it constituted an important driver (18 %) in the ROC. Other drivers included flood, roads and settlements. Approximately 77% of disturbances occurred outside managed forest concessions in Cuvette Centrale, with 40% extending into protected areas. About 90% of disturbances were concentrated within 1 km of peat forest edges and ~76% of the disturbances occurred within 5 km of road or river networks. The insights underscore the crucial need for effective peat forest conservation strategies in Cuvette Centrale and can inform national policies targeting peatland protection, aligning with commitments in the Brazzaville Declaration and Paris Agreement. Further, our findings on direct driver assessment could serve as a reference dataset for machine learning models to automate the visual interpretation and upscale the assessment across the entire region.
{"title":"An assessment of recent peat forest disturbances and their drivers in the Cuvette Centrale, Africa","authors":"Karimon Nesha, Martin Herold, Johannes Reiche, Robert N. Masolele, K. Hergoualc’h, E. Swails, Daniel Murdiyarso, C. Ewango","doi":"10.1088/1748-9326/ad6679","DOIUrl":"https://doi.org/10.1088/1748-9326/ad6679","url":null,"abstract":"\u0000 The largest tropical peatland complex in the Cuvette Centrale, is marked by persistent knowledge gaps. We assessed recent peat forest disturbances and their direct drivers from 2019 to 2021 in Cuvette Centrale, spanning the Republic of Congo (ROC) and the Democratic Republic of Congo (DRC). Utilizing peatland extent and Radar for Detecting Deforestation (RADD) alert data, we analyzed spatial and temporal patterns of disturbances. Further, we examined 2,267 randomly sampled peat forest disturbance events through visual interpretation of monthly Planet and Sentinel 2A data to identify direct drivers. Our findings revealed that between 2019 and 2021, about 91% of disturbances occurred in DRC, with hotspots concentrated in the northwest Sud-Ubangi district. Disturbances predominantly followed a sharp seasonal pattern, recurring during the first half of each year with temporal hotspots emerging between February and May, closely associated with smallholder agriculture activities. Smallholder agriculture accounted for over 88% of disturbances in Cuvette Centrale, representing a leading role both in ROC (~77%) and DRC (~89%). While, small-scale logging contributed 7% to disturbances in the region, it constituted an important driver (18 %) in the ROC. Other drivers included flood, roads and settlements. Approximately 77% of disturbances occurred outside managed forest concessions in Cuvette Centrale, with 40% extending into protected areas. About 90% of disturbances were concentrated within 1 km of peat forest edges and ~76% of the disturbances occurred within 5 km of road or river networks. The insights underscore the crucial need for effective peat forest conservation strategies in Cuvette Centrale and can inform national policies targeting peatland protection, aligning with commitments in the Brazzaville Declaration and Paris Agreement. Further, our findings on direct driver assessment could serve as a reference dataset for machine learning models to automate the visual interpretation and upscale the assessment across the entire region.","PeriodicalId":507917,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141811620","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 : 2024-07-23DOI: 10.1088/1748-9326/ad6678
Edward Layman Webb, J. Jamaludin
Cambodia is beset by high deforestation rates and fire frequencies. From 2001–2020, forest cover declined by 34%, and cropland and rubber expanded by 31,401 km2 and 4,530 km2, respectively; meanwhile nearly 8.7 million fires burned 41.6% of the land. Fires may be associated with deliberate land change, stable land management systems, and unplanned forest degradation. We integrated annual land cover and monthly burned area data from 2001–2020 to test three hypotheses. First, if fire is used during land conversion, there would be a detectable pulse in fire activity in the year immediately prior to, and the year of land cover change. Our temporal analysis found statistically elevated burn rates in five of 16 transition tests, however, they were typically <1% outside the predicted range, indicating no practical significance in the association of fire with land cover change. Second, fire prevalence would be lower in land managed for conservation or agricultural production than unclassified or unmanaged land. persistent forest and shrubland burned at significantly higher rates than expected, cropland burned significantly less, burning was almost absent from rubber plantations, and forests in protected areas (PAs) exhibited lower total burn percentages than unclassified land or industrial economic land concessions (ELCs), thus supporting the fire-land management hypothesis. However, total burned area in ELCs was greater than unclassified land for several persistent land cover classes, suggesting that local landowners may prevent fire in commercially valuable private agricultural land, but there may be no such prevention measures in industrial ELCs. Anti-fire policy enforcement in ELCs should be enhanced. Third, forests that converted into (degraded) shrublands would experience increasing fire frequency in the years leading up to transition, a hypothesis we found strong support for through our temporal analysis. Cambodia’s 2013 Law on Fire Prevention and Fire Fighting deputizes the public to enforce its provision, however given that the vast majority of fires occur in persistent forest in state-owned land, collective action problems are likely to hinder its effective implementation.
{"title":"Fire is associated with forest degradation and economic land concessions, but not land conversion in the rapidly transforming Cambodian landscape","authors":"Edward Layman Webb, J. Jamaludin","doi":"10.1088/1748-9326/ad6678","DOIUrl":"https://doi.org/10.1088/1748-9326/ad6678","url":null,"abstract":"\u0000 Cambodia is beset by high deforestation rates and fire frequencies. From 2001–2020, forest cover declined by 34%, and cropland and rubber expanded by 31,401 km2 and 4,530 km2, respectively; meanwhile nearly 8.7 million fires burned 41.6% of the land. Fires may be associated with deliberate land change, stable land management systems, and unplanned forest degradation. We integrated annual land cover and monthly burned area data from 2001–2020 to test three hypotheses. First, if fire is used during land conversion, there would be a detectable pulse in fire activity in the year immediately prior to, and the year of land cover change. Our temporal analysis found statistically elevated burn rates in five of 16 transition tests, however, they were typically <1% outside the predicted range, indicating no practical significance in the association of fire with land cover change. Second, fire prevalence would be lower in land managed for conservation or agricultural production than unclassified or unmanaged land. persistent forest and shrubland burned at significantly higher rates than expected, cropland burned significantly less, burning was almost absent from rubber plantations, and forests in protected areas (PAs) exhibited lower total burn percentages than unclassified land or industrial economic land concessions (ELCs), thus supporting the fire-land management hypothesis. However, total burned area in ELCs was greater than unclassified land for several persistent land cover classes, suggesting that local landowners may prevent fire in commercially valuable private agricultural land, but there may be no such prevention measures in industrial ELCs. Anti-fire policy enforcement in ELCs should be enhanced. Third, forests that converted into (degraded) shrublands would experience increasing fire frequency in the years leading up to transition, a hypothesis we found strong support for through our temporal analysis. Cambodia’s 2013 Law on Fire Prevention and Fire Fighting deputizes the public to enforce its provision, however given that the vast majority of fires occur in persistent forest in state-owned land, collective action problems are likely to hinder its effective implementation.","PeriodicalId":507917,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141812082","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 : 2024-07-23DOI: 10.1088/1748-9326/ad667a
Yun Liang, Ruixue Xia, Yan Du
The role of sea surface temperature (SST) variability in the boreal winter intraseasonal oscillation (ISO) over the tropical Indian Ocean (TIO) is investigated in this study using the Community Earth System Model Version 2 (CESM2). An atmospheric general coupled model (AGCM) run forced by daily SSTs derived from a parallel coupled circulation model (CGCM) run is compared with reanalysis and the original coupled simulation. The comparison of atmospheric-coupled GCMs reveals the frequency and spatial tendency of the SST effect on the atmospheric ISO. The lower-frequency component of the ISO over the TIO is significantly intensified in the AGCM run. The SST-to-atmosphere effect is most prominent over the southeastern TIO. In the AGCM run, low-level wind anomalies related to SST appear west of the ISO convection center, contrasting with the previous findings that the SST effect appears east of the convection center.
本研究利用共同体地球系统模式第 2 版（CESM2）研究了热带印度洋（TIO）上空北半球冬季季内振荡（ISO）中海面温度（SST）变率的作用。在平行耦合环流模式（CGCM）运行得出的日海温的强迫下，对大气一般耦合模式（AGCM）运行与再分析和原始耦合模拟进行了比较。大气耦合 GCM 的比较揭示了 SST 对大气 ISO 影响的频率和空间趋势。在 AGCM 运行中，TIO 上的 ISO 低频成分明显增强。海温对大气的影响在 TIO 东南部最为突出。在 AGCM 运行中，与 SST 有关的低层风异常出现在 ISO 对流中心以西，这与之前的发现形成了鲜明对比，即 SST 效应出现在对流中心以东。
{"title":"Ocean feedback on 50–80-day boreal winter intraseasonal oscillation in the Indian Ocean: Comparison of atmospheric and coupled CESM2 simulations","authors":"Yun Liang, Ruixue Xia, Yan Du","doi":"10.1088/1748-9326/ad667a","DOIUrl":"https://doi.org/10.1088/1748-9326/ad667a","url":null,"abstract":"\u0000 The role of sea surface temperature (SST) variability in the boreal winter intraseasonal oscillation (ISO) over the tropical Indian Ocean (TIO) is investigated in this study using the Community Earth System Model Version 2 (CESM2). An atmospheric general coupled model (AGCM) run forced by daily SSTs derived from a parallel coupled circulation model (CGCM) run is compared with reanalysis and the original coupled simulation. The comparison of atmospheric-coupled GCMs reveals the frequency and spatial tendency of the SST effect on the atmospheric ISO. The lower-frequency component of the ISO over the TIO is significantly intensified in the AGCM run. The SST-to-atmosphere effect is most prominent over the southeastern TIO. In the AGCM run, low-level wind anomalies related to SST appear west of the ISO convection center, contrasting with the previous findings that the SST effect appears east of the convection center.","PeriodicalId":507917,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141813576","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 : 2024-07-22DOI: 10.1088/1748-9326/ad661d
Jiquan Chen, Cheyenne Lei, Housen Chu, Xianglan Li, Margaret Susan Torn, Yingping Wang, P. Sciusco, G. P. Robertson
Radiative forcing (RF) resulting from changes in surface albedo is increasingly recognized as a significant driver of global climate change but has not been adequately estimated, including by IPCC assessment reports, compared with other warming agents. Here, we first present the physical foundation for modeling albedo-induced radiative forcing (RF¬) and the consequent global warming impact (GWI∆α). We then highlight the shortcomings of available current databases and methodologies for calculating GWI∆α at multiple temporal scales. There is a clear lack of comprehensive in situ measurements of albedo due to sparse geographic coverage of ground-based stations, whereas estimates from satellites suffer from biases due to the limited frequency of image collection, and estimates from Earth System Models suffer from very coarse spatial resolution land cover maps and associated albedo values in pre-determined lookup tables. Field measurements of albedo show large differences by ecosystem type and large diurnal and seasonal changes. As indicated from our findings in southwest Michigan, GWI∆α is substantial, exceeding the RF∆α values of IPCC reports. Inclusion of GWIΔα to landowners and carbon credit markets for specific management practices are needed in future policies. We further identify four pressing research priorities: developing a comprehensive albedo database, pinpointing accurate reference sites within managed landscapes, refining algorithms for remote sensing of albedo by integrating geostationary and other orbital satellites, and integrating the GWI∆α component into future Earth System Models.
{"title":"Overlooked cooling effects of albedo in terrestrial ecosystems","authors":"Jiquan Chen, Cheyenne Lei, Housen Chu, Xianglan Li, Margaret Susan Torn, Yingping Wang, P. Sciusco, G. P. Robertson","doi":"10.1088/1748-9326/ad661d","DOIUrl":"https://doi.org/10.1088/1748-9326/ad661d","url":null,"abstract":"\u0000 Radiative forcing (RF) resulting from changes in surface albedo is increasingly recognized as a significant driver of global climate change but has not been adequately estimated, including by IPCC assessment reports, compared with other warming agents. Here, we first present the physical foundation for modeling albedo-induced radiative forcing (RF¬) and the consequent global warming impact (GWI∆α). We then highlight the shortcomings of available current databases and methodologies for calculating GWI∆α at multiple temporal scales. There is a clear lack of comprehensive in situ measurements of albedo due to sparse geographic coverage of ground-based stations, whereas estimates from satellites suffer from biases due to the limited frequency of image collection, and estimates from Earth System Models suffer from very coarse spatial resolution land cover maps and associated albedo values in pre-determined lookup tables. Field measurements of albedo show large differences by ecosystem type and large diurnal and seasonal changes. As indicated from our findings in southwest Michigan, GWI∆α is substantial, exceeding the RF∆α values of IPCC reports. Inclusion of GWIΔα to landowners and carbon credit markets for specific management practices are needed in future policies. We further identify four pressing research priorities: developing a comprehensive albedo database, pinpointing accurate reference sites within managed landscapes, refining algorithms for remote sensing of albedo by integrating geostationary and other orbital satellites, and integrating the GWI∆α component into future Earth System Models.","PeriodicalId":507917,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141815358","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 : 2024-07-22DOI: 10.1088/1748-9326/ad6619
Elise Heffernan, Howard E. Epstein, T. D. McQuinn, David Lutz, Brendan M Rogers, Anna‐Maria Virkkala, Amanda H Armstrong
Modeling Arctic-Boreal vegetation is a challenging but important task, since this highly dynamic ecosystem is undergoing rapid and substantial environmental change. In this work, we synthesized information on 18 dynamic vegetation models that can be used to project vegetation structure, composition, and function in North American Arctic-Boreal ecosystems. We reviewed the ecosystem properties and scaling assumptions these models make, reviewed their applications from the scholarly literature, and conducted a survey of expert opinion to determine which processes are important but lacking in dynamic vegetation models. We then grouped the models into four categories (specific intention models, forest species models, cohort models, and carbon tracking models) using cluster analysis to highlight similarities among the models. Our application review identified 48 papers that addressed vegetation dynamics either directly (22) or indirectly (26). The expert survey results indicated a large desire for increased representation of active layer depth and permafrost in future model development. Ultimately, this paper serves as a summary of dynamic vegetation model development and application in Arctic-Boreal environments and can be used as a guide for potential model users, thereby prioritizing options for model development.
{"title":"Comparing assumptions and applications of dynamic vegetation models used in the Arctic-Boreal Zone of Alaska and Canada.","authors":"Elise Heffernan, Howard E. Epstein, T. D. McQuinn, David Lutz, Brendan M Rogers, Anna‐Maria Virkkala, Amanda H Armstrong","doi":"10.1088/1748-9326/ad6619","DOIUrl":"https://doi.org/10.1088/1748-9326/ad6619","url":null,"abstract":"\u0000 Modeling Arctic-Boreal vegetation is a challenging but important task, since this highly dynamic ecosystem is undergoing rapid and substantial environmental change. In this work, we synthesized information on 18 dynamic vegetation models that can be used to project vegetation structure, composition, and function in North American Arctic-Boreal ecosystems. We reviewed the ecosystem properties and scaling assumptions these models make, reviewed their applications from the scholarly literature, and conducted a survey of expert opinion to determine which processes are important but lacking in dynamic vegetation models. We then grouped the models into four categories (specific intention models, forest species models, cohort models, and carbon tracking models) using cluster analysis to highlight similarities among the models. Our application review identified 48 papers that addressed vegetation dynamics either directly (22) or indirectly (26). The expert survey results indicated a large desire for increased representation of active layer depth and permafrost in future model development. Ultimately, this paper serves as a summary of dynamic vegetation model development and application in Arctic-Boreal environments and can be used as a guide for potential model users, thereby prioritizing options for model development.","PeriodicalId":507917,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141816413","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 : 2024-07-22DOI: 10.1088/1748-9326/ad661c
Anne L. Bartlett, J. Alix-Garcia, Alejandro Abarca, Sarah Walker, Jamon Van Den Hoek, Paulo J. Murillo-Sandoval, Hannah K. Friedrich
Production bans are a common way for governments to address issues of social concern. However, when consumer demand for banned items is insensitive to price changes, cross-border trade may undermine these efforts. We examine the effects of Kenya's 2018 moratorium on the extraction of wood products, including logs and charcoal, from public and community forests. The data show an immediate 36% increase in the domestic charcoal price in Kenya, where over 80% of consumers use it as their primary energy source. Subsequently, we document an increase of 133% percent in charcoal imports from Uganda to Kenya during the first 6 months of the ban. Further, we estimate that avoided deforestation in Kenya was likely displaced to Uganda such that net carbon emissions increased. These findings demonstrate the ineffectiveness of the ban as a mechanism to decrease greenhouse gas emissions and biodiversity loss from deforestation.
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