Pub Date : 2024-07-22DOI: 10.1088/2752-5295/ad6632
Andrés Navarro, F. Tapiador
Climate Classification Systems (CCSs) were developed in the 19th century to explain the global distribution of plants and animals, but were given a new life in the Earth physics community in the 21st century as a means to validate Earth System Models (ESMs). The purpose of this paper is to critically review the evolution of this approach to validation and to discuss the current status. It is shown that CCSs can not only measure model performance, but also help identify and deconstruct systematic model biases. CCSs provide a rational and comprehensive zonation of the global environment using quantitative estimates of physical variables such as precipitation, temperature, and humidity. They offer several advantages over single variables due to the high sensitivity of the resulting classes to small changes in input variables and dimensionality reduction. CCSs encompass model behavior on both energy and water balances, allowing for a more comprehensive assessment of ESM performance.
{"title":"Climate classification systems for validating Earth system models","authors":"Andrés Navarro, F. Tapiador","doi":"10.1088/2752-5295/ad6632","DOIUrl":"https://doi.org/10.1088/2752-5295/ad6632","url":null,"abstract":"\u0000 Climate Classification Systems (CCSs) were developed in the 19th century to explain the global distribution of plants and animals, but were given a new life in the Earth physics community in the 21st century as a means to validate Earth System Models (ESMs). The purpose of this paper is to critically review the evolution of this approach to validation and to discuss the current status. It is shown that CCSs can not only measure model performance, but also help identify and deconstruct systematic model biases. CCSs provide a rational and comprehensive zonation of the global environment using quantitative estimates of physical variables such as precipitation, temperature, and humidity. They offer several advantages over single variables due to the high sensitivity of the resulting classes to small changes in input variables and dimensionality reduction. CCSs encompass model behavior on both energy and water balances, allowing for a more comprehensive assessment of ESM performance.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"3 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141816404","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: 10.1088/2752-5295/ad6631
K. Ng, G. Leckebusch, Kevin I. Hodges
While the improved performance of climate prediction systems has allowed better predictions of the East Asian Summer Monsoon rainfall to be made, the ability to predict extreme Mei-yu rainfall (MYR) remains a challenge. Given that large scale climate modes (LSCMs) tend to be better predicted by climate prediction systems than local extremes, one useful approach is to employ causality-guided statistical models (CGSMs), which link known LSCMs to improve MYR prediction. However, previous work suggests that CGSMs trained with data from 1979-2018 might struggle to model MYR in the pre-1978 period. One hypothesis is that this is due to potential changes in causal processes, which modulate MYR in different phases of the multidecadal variability, such as the Pacific Decadal Oscillation (PDO). In this study, we explore this hypothesis by constructing CGSMs for different PDO phases, which reflect the different phases of specific causal process, and examine the difference in quality as well as with respect to difference drivers and thus causal links between CGSMs of different PDO phases as well as the non-PDO phase specific CGSMs. Our results show that the set of predictors of CGSMs is PDO phase specific. Furthermore, the performance of PDO phase specific CGSMs are better than the non-PDO phase specific CGSMs. To demonstrate the added value of CGSMs, the PDO phase specific versions are applied to the latest UK Met Office decadal prediction system, DePreSys4, and it is shown that the root-mean squared errors of MYR prediction based on PDO phase specific CGSMs is consistently smaller than the MYR predicted based on the direct DePreSys4 extreme rainfall simulations. We conclude that the use of a causality approach improves the prediction of extreme precipitation based solely on known LSCMs because of the change in the main drivers of extreme rainfall during different PDO-phases.
{"title":"Improvement of decadal predictions of monthly extreme Mei-yu rainfall via a causality guided approach","authors":"K. Ng, G. Leckebusch, Kevin I. Hodges","doi":"10.1088/2752-5295/ad6631","DOIUrl":"https://doi.org/10.1088/2752-5295/ad6631","url":null,"abstract":"\u0000 While the improved performance of climate prediction systems has allowed better predictions of the East Asian Summer Monsoon rainfall to be made, the ability to predict extreme Mei-yu rainfall (MYR) remains a challenge. Given that large scale climate modes (LSCMs) tend to be better predicted by climate prediction systems than local extremes, one useful approach is to employ causality-guided statistical models (CGSMs), which link known LSCMs to improve MYR prediction. However, previous work suggests that CGSMs trained with data from 1979-2018 might struggle to model MYR in the pre-1978 period. One hypothesis is that this is due to potential changes in causal processes, which modulate MYR in different phases of the multidecadal variability, such as the Pacific Decadal Oscillation (PDO). In this study, we explore this hypothesis by constructing CGSMs for different PDO phases, which reflect the different phases of specific causal process, and examine the difference in quality as well as with respect to difference drivers and thus causal links between CGSMs of different PDO phases as well as the non-PDO phase specific CGSMs. Our results show that the set of predictors of CGSMs is PDO phase specific. Furthermore, the performance of PDO phase specific CGSMs are better than the non-PDO phase specific CGSMs. To demonstrate the added value of CGSMs, the PDO phase specific versions are applied to the latest UK Met Office decadal prediction system, DePreSys4, and it is shown that the root-mean squared errors of MYR prediction based on PDO phase specific CGSMs is consistently smaller than the MYR predicted based on the direct DePreSys4 extreme rainfall simulations. We conclude that the use of a causality approach improves the prediction of extreme precipitation based solely on known LSCMs because of the change in the main drivers of extreme rainfall during different PDO-phases.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"30 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141814180","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 : 2024-07-17DOI: 10.1088/2752-5295/ad6473
I. Cortés, J. Lorenzo‐Trueba, A. Rovai, R. Twilley, M. Chopping, T. Fatoyinbo
Although mangroves provide many beneficial ecosystem services, such as blue carbon storage and coastal protection, they are currently under threat due to changes in climate conditions, such as prolonged drought exposure. Under drought conditions, evaporation exceeds precipitation increasing porewater salinity causing mangroves stunted growth and die-back. To quantify this interplay, we developed a database for low-lying and uninhabited mangrove islands in the Caribbean under various evaporation and precipitation regimes. We extracted physical and biological information from each island using remote sensing techniques and coupled it with a process-based model. We used this database to develop a model that explains both the spatial variability in vegetated area across the Caribbean – as a function of rates of evaporation and precipitation – and porewater salinity concentration and dispersion from island edge towards the interior of mangrove islands. We then used this validated model to predict mangrove area loss associated with increases in evaporation to precipitation rates by 2100 for different Shared Socioeconomic Pathways (SSP). Less wealthy Caribbean regions such as Belize, Puerto Rico, and Venezuela are disproportionally affected, with mangrove area losses ranging from 3-7% for SSP 2.6 and 13-21% for SSP 7.0. Furthermore, foregone carbon sequestration in lost biomass under SSP 4.5 and 7.0 scenarios could compromise the ability of low-lying Caribbean mangrove islands to vertically adjust to sea level rise.
{"title":"Net evaporation-induced mangrove area loss across low-lying Caribbean islands","authors":"I. Cortés, J. Lorenzo‐Trueba, A. Rovai, R. Twilley, M. Chopping, T. Fatoyinbo","doi":"10.1088/2752-5295/ad6473","DOIUrl":"https://doi.org/10.1088/2752-5295/ad6473","url":null,"abstract":"\u0000 Although mangroves provide many beneficial ecosystem services, such as blue carbon storage and coastal protection, they are currently under threat due to changes in climate conditions, such as prolonged drought exposure. Under drought conditions, evaporation exceeds precipitation increasing porewater salinity causing mangroves stunted growth and die-back. To quantify this interplay, we developed a database for low-lying and uninhabited mangrove islands in the Caribbean under various evaporation and precipitation regimes. We extracted physical and biological information from each island using remote sensing techniques and coupled it with a process-based model. We used this database to develop a model that explains both the spatial variability in vegetated area across the Caribbean – as a function of rates of evaporation and precipitation – and porewater salinity concentration and dispersion from island edge towards the interior of mangrove islands. We then used this validated model to predict mangrove area loss associated with increases in evaporation to precipitation rates by 2100 for different Shared Socioeconomic Pathways (SSP). Less wealthy Caribbean regions such as Belize, Puerto Rico, and Venezuela are disproportionally affected, with mangrove area losses ranging from 3-7% for SSP 2.6 and 13-21% for SSP 7.0. Furthermore, foregone carbon sequestration in lost biomass under SSP 4.5 and 7.0 scenarios could compromise the ability of low-lying Caribbean mangrove islands to vertically adjust to sea level rise.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":" 14","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141831328","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 : 2024-06-13DOI: 10.1088/2752-5295/ad57e3
E. Yule, G. Hegerl, A. Schurer, A. Ballinger, Ed Hawkins
The intensity and frequency of extreme heat events is increasing due to climate change, resulting in a range of societal impacts. In this paper, we use temporal analogues to analyse how past UK heatwave events, such as during the summer of 1923, may change if they were to occur under different global warming scenarios. We find that the six most intense early heat events are caused by circulation patterns similar to that of 1923, which can cause intense heat over the UK and parts of NW Europe. Circulation analogues for the 1923 heatwave are also linked to intense heat events in the future, although not all analogues are anomalously hot. At 4 degrees of global warming, mean summer temperatures in England over the duration of the 1923 heatwave are between 4.9 and 6.4 degrees warmer than pre-industrial levels across the three models used. At that global mean warming level, future heat events with similar circulation as 1923 over England are estimated to be on average 6.9 to 10.7 degrees hotter than those at pre-industrial levels, with the most intense up 19.6 degrees higher. Exploring how the intensity of events similar to past events may change in the future could be an effective risk communication tool for adaptation decision making, particularly if past events are stored in society’s memory, for example, due to high impacts.
{"title":"Using analogues to predict changes in future UK heatwaves","authors":"E. Yule, G. Hegerl, A. Schurer, A. Ballinger, Ed Hawkins","doi":"10.1088/2752-5295/ad57e3","DOIUrl":"https://doi.org/10.1088/2752-5295/ad57e3","url":null,"abstract":"\u0000 The intensity and frequency of extreme heat events is increasing due to climate change, resulting in a range of societal impacts. In this paper, we use temporal analogues to analyse how past UK heatwave events, such as during the summer of 1923, may change if they were to occur under different global warming scenarios. We find that the six most intense early heat events are caused by circulation patterns similar to that of 1923, which can cause intense heat over the UK and parts of NW Europe. Circulation analogues for the 1923 heatwave are also linked to intense heat events in the future, although not all analogues are anomalously hot. At 4 degrees of global warming, mean summer temperatures in England over the duration of the 1923 heatwave are between 4.9 and 6.4 degrees warmer than pre-industrial levels across the three models used. At that global mean warming level, future heat events with similar circulation as 1923 over England are estimated to be on average 6.9 to 10.7 degrees hotter than those at pre-industrial levels, with the most intense up 19.6 degrees higher. Exploring how the intensity of events similar to past events may change in the future could be an effective risk communication tool for adaptation decision making, particularly if past events are stored in society’s memory, for example, due to high impacts.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"51 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141348880","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 : 2024-06-12DOI: 10.1088/2752-5295/ad574f
C. DaCamara, Virgílio A. Bento, Sílvia A. Nunes, Gil Lemos, P. M. Soares, Ricardo M. Trigo
Climate change poses a formidable strain on societies worldwide, demanding viable and timely adaptation measures to ensure future prosperity while avoiding the impact of more frequent and intense extreme events, like wildfires, that affect all continents and biomes, leaving authorities grappling to respond effectively. Here, we focus on mainland Portugal that is inserted in the Mediterranean climate change hotspot and investigate the impact of different adaptation strategies on wildfire risk. Relying on an ensemble of regional climate models from the EURO-CORDEX initiative, we project Fire Weather Index (FWI) and Fire Radiative Power (FRP) for various Representative Concentration Pathways (RCPs). Our findings reveal that very energetic fires, with energy release exceeding 1000 MW, may increase up to more than three-fold, depending on the RCP. Even under strong mitigation scenarios, the likelihood of having megafires increases by 1.5-fold. This underscores the need for proactive adaptation regardless of mitigation efforts. We present three different ignition avoidance strategies under different climate change scenarios. For all cases results indicate that a reduction between 20 and 60% is achievable for intense wildfires (above 1000 MW).
{"title":"Impacts of fire prevention strategies in a changing climate: an assessment for Portugal","authors":"C. DaCamara, Virgílio A. Bento, Sílvia A. Nunes, Gil Lemos, P. M. Soares, Ricardo M. Trigo","doi":"10.1088/2752-5295/ad574f","DOIUrl":"https://doi.org/10.1088/2752-5295/ad574f","url":null,"abstract":"\u0000 Climate change poses a formidable strain on societies worldwide, demanding viable and timely adaptation measures to ensure future prosperity while avoiding the impact of more frequent and intense extreme events, like wildfires, that affect all continents and biomes, leaving authorities grappling to respond effectively. Here, we focus on mainland Portugal that is inserted in the Mediterranean climate change hotspot and investigate the impact of different adaptation strategies on wildfire risk. Relying on an ensemble of regional climate models from the EURO-CORDEX initiative, we project Fire Weather Index (FWI) and Fire Radiative Power (FRP) for various Representative Concentration Pathways (RCPs). Our findings reveal that very energetic fires, with energy release exceeding 1000 MW, may increase up to more than three-fold, depending on the RCP. Even under strong mitigation scenarios, the likelihood of having megafires increases by 1.5-fold. This underscores the need for proactive adaptation regardless of mitigation efforts. We present three different ignition avoidance strategies under different climate change scenarios. For all cases results indicate that a reduction between 20 and 60% is achievable for intense wildfires (above 1000 MW).","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"45 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141353164","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 : 2024-06-12DOI: 10.1088/2752-5295/ad574e
Benedikt Becsi, Herbert Formayer
Global warming levels (GWLs) are increasingly becoming a central concept in climate change studies. In recent years, their integrative quality for climate change impact analysis has been demonstrated, and methodological advancements have helped to compensate for some inherent shortfalls of the concept. However, their applicability at the regional level is debatable, and no study to date has examined the possibility of linking local climate scenarios to GWLs. For the case of Austria, we have evaluated the relation between global and local warming patterns, and whether version changes of global climate models could be incorporated into local climate scenarios by means of the GWL concept, without updating the actual data. We applied the time sampling approach, where GWLs are determined as periods when global mean temperature anomalies cross a certain threshold. GWL periods were sampled both from the global models in the background of the local climate scenarios (CMIP5), and from an equivalent ensemble of newer-generation climate models (CMIP6). Uncertainties resulting from sampling GWLs from different global climate model ensembles were examined, and prospects for local climate change impact assessments were discussed. Accounting for updated global climate model versions might be useful when the changes at certain GWLs are related to fixed reference periods, but temperature increments between GWLs remained relatively constant across model versions, even on the local level. The study bridges a significant gap to link regional and local climate projections to GWLs. Climate change impacts assessments that build on those datasets can benefit from the integrative character of GWLs, making studies comparable across multiple disciplines and model versions, and thus fostering a way to communicate local climate change impacts more comprehensible.
{"title":"Linking local climate scenarios to global warming levels: applicability, prospects and uncertainties","authors":"Benedikt Becsi, Herbert Formayer","doi":"10.1088/2752-5295/ad574e","DOIUrl":"https://doi.org/10.1088/2752-5295/ad574e","url":null,"abstract":"\u0000 Global warming levels (GWLs) are increasingly becoming a central concept in climate change studies. In recent years, their integrative quality for climate change impact analysis has been demonstrated, and methodological advancements have helped to compensate for some inherent shortfalls of the concept. However, their applicability at the regional level is debatable, and no study to date has examined the possibility of linking local climate scenarios to GWLs. For the case of Austria, we have evaluated the relation between global and local warming patterns, and whether version changes of global climate models could be incorporated into local climate scenarios by means of the GWL concept, without updating the actual data. We applied the time sampling approach, where GWLs are determined as periods when global mean temperature anomalies cross a certain threshold. GWL periods were sampled both from the global models in the background of the local climate scenarios (CMIP5), and from an equivalent ensemble of newer-generation climate models (CMIP6). Uncertainties resulting from sampling GWLs from different global climate model ensembles were examined, and prospects for local climate change impact assessments were discussed. Accounting for updated global climate model versions might be useful when the changes at certain GWLs are related to fixed reference periods, but temperature increments between GWLs remained relatively constant across model versions, even on the local level. The study bridges a significant gap to link regional and local climate projections to GWLs. Climate change impacts assessments that build on those datasets can benefit from the integrative character of GWLs, making studies comparable across multiple disciplines and model versions, and thus fostering a way to communicate local climate change impacts more comprehensible.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"110 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141352139","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 : 2024-06-07DOI: 10.1088/2752-5295/ad557e
F. S. Riera, C. Hunecke, Alejandro Juan Gennari
Stakeholder adaptation is a critical strategy to overcome changing climate patterns worldwide. Still it relies on the speed and effectiveness of information flow to end-users. Research shows that the loss of information in several stages of its spread and learning from peers is more important than the knowledge circulated by extension services. Women’s participation and contribution are supportive and strategic, depending on the level of agreement and the interplay of trust variables within the network. In the arid Andes, agriculture is central and dependent on water management and macroeconomic conditions that shape market prospects, irrigation practices, and stakeholder behavior. Data were collected using the platform of a capacity-building program for organisations of water users in the Diamante and Atuel River basins in Mendoza, Argentina. Social Network Analysis (SNA) contributes to unveiling the cornerstones of information flow by identifying group structures, strong bonds, and bottlenecks in water management systems. In the first step, we evaluated the characteristics (density, centrality, average shortest path, and degree) of the pre-existing relationships and five sub-topic networks. Second, we compare networks containing pre-existing links only with those formed during the lecture. Emphasizing adaptation practices to cope with climate change impacts, the results provide valuable insights into the intricate interplay of gender dynamics, trust, expertise recognition, and discussion patterns within water and agricultural extension groups in Argentina. These insights highlight the ongoing need to promote gender equity, address biases in expertise recognition, and leverage trust for meaningful knowledge exchanges within evolving social contexts. It also reveals the alignment of Argentina's gender performance with similar production setups in Southern America or the Global North, highlighting the universality of challenges and opportunities in fostering inclusive and equitable participation. Our findings indicate that each group within the two river basins exhibits numerous pre-existing links and tends to be less accessible to newcomers, resulting in a shorter average path. Thus, information can spread faster. Trust is an underlying facilitator for sensible topics and a catalyzer for communication.
{"title":"Talking water: interplay of gender, trust and expertise in agricultural extension groups in Mendoza, Argentina","authors":"F. S. Riera, C. Hunecke, Alejandro Juan Gennari","doi":"10.1088/2752-5295/ad557e","DOIUrl":"https://doi.org/10.1088/2752-5295/ad557e","url":null,"abstract":"\u0000 Stakeholder adaptation is a critical strategy to overcome changing climate patterns worldwide. Still it relies on the speed and effectiveness of information flow to end-users. Research shows that the loss of information in several stages of its spread and learning from peers is more important than the knowledge circulated by extension services. Women’s participation and contribution are supportive and strategic, depending on the level of agreement and the interplay of trust variables within the network. In the arid Andes, agriculture is central and dependent on water management and macroeconomic conditions that shape market prospects, irrigation practices, and stakeholder behavior. Data were collected using the platform of a capacity-building program for organisations of water users in the Diamante and Atuel River basins in Mendoza, Argentina. Social Network Analysis (SNA) contributes to unveiling the cornerstones of information flow by identifying group structures, strong bonds, and bottlenecks in water management systems. In the first step, we evaluated the characteristics (density, centrality, average shortest path, and degree) of the pre-existing relationships and five sub-topic networks. Second, we compare networks containing pre-existing links only with those formed during the lecture. Emphasizing adaptation practices to cope with climate change impacts, the results provide valuable insights into the intricate interplay of gender dynamics, trust, expertise recognition, and discussion patterns within water and agricultural extension groups in Argentina. These insights highlight the ongoing need to promote gender equity, address biases in expertise recognition, and leverage trust for meaningful knowledge exchanges within evolving social contexts. It also reveals the alignment of Argentina's gender performance with similar production setups in Southern America or the Global North, highlighting the universality of challenges and opportunities in fostering inclusive and equitable participation. Our findings indicate that each group within the two river basins exhibits numerous pre-existing links and tends to be less accessible to newcomers, resulting in a shorter average path. Thus, information can spread faster. Trust is an underlying facilitator for sensible topics and a catalyzer for communication.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":" 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141373648","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}
The precipitation hotspot of the orographically locked convection highly depends on the interactions among physical processes governing local energetics and cloud dynamics. Accurately estimating the future change of these hotspots will require a model with sufficient spatial resolution as well as an appropriate representation of the critical physical processes. In this study, ensembles of TaiwanVVM large-eddy simulations (Δx=500 m) were designed to capture the summertime diurnal convection in Taiwan when local circulation dominates. The precipitation hotspots identified by long-term observations are well represented by the present-day ensemble simulations with appropriate environment variabilities. A pseudo global warming experiment is carried out to identify changes in convective structures, which results in local rainfall changes. Under the scenario of 3-K uniform warming with conserved relative humidity, the changes in the thermodynamic environment feature an overall higher convective available potential energy (CAPE) and a small decrease in convective inhibition (CIN), owing to the marked increase in low-level water vapor in the marine boundary layer. The results show that mean precipitation and the occurrence of extreme convective systems (ECSs) increase, with hotspots over mountains expanding toward the foothills and plains. The response in cloud dynamics leads to more short-duration, intense rainfall events. The tracking of extreme convective systems with maximum rainfall exceeding 100 mm hr-1 reveals more numerous short-lived ECSs (lifetime < 6 hr) and the enhancements in maximum updrafts by ~10 m s-1, in cloud top heights by ~1 km, and in the volume of cloud objects by ~1.5 folds. These sets of high-resolution simulations under the specific weather regime offer critical information for assessing the potential impacts of the future changes of extreme rainfall contributed by the orographically locked diurnal convection on natural disasters and water resources.
{"title":"The future extreme precipitation systems of orographically locked diurnal convection: the benefits of using large-eddy simulation ensembles","authors":"Wei‐Ting Chen, Yu-Hung Chang, Chien‐Ming Wu, Huai-Yi Huang","doi":"10.1088/2752-5295/ad557d","DOIUrl":"https://doi.org/10.1088/2752-5295/ad557d","url":null,"abstract":"\u0000 The precipitation hotspot of the orographically locked convection highly depends on the interactions among physical processes governing local energetics and cloud dynamics. Accurately estimating the future change of these hotspots will require a model with sufficient spatial resolution as well as an appropriate representation of the critical physical processes. In this study, ensembles of TaiwanVVM large-eddy simulations (Δx=500 m) were designed to capture the summertime diurnal convection in Taiwan when local circulation dominates. The precipitation hotspots identified by long-term observations are well represented by the present-day ensemble simulations with appropriate environment variabilities. A pseudo global warming experiment is carried out to identify changes in convective structures, which results in local rainfall changes. Under the scenario of 3-K uniform warming with conserved relative humidity, the changes in the thermodynamic environment feature an overall higher convective available potential energy (CAPE) and a small decrease in convective inhibition (CIN), owing to the marked increase in low-level water vapor in the marine boundary layer. The results show that mean precipitation and the occurrence of extreme convective systems (ECSs) increase, with hotspots over mountains expanding toward the foothills and plains. The response in cloud dynamics leads to more short-duration, intense rainfall events. The tracking of extreme convective systems with maximum rainfall exceeding 100 mm hr-1 reveals more numerous short-lived ECSs (lifetime < 6 hr) and the enhancements in maximum updrafts by ~10 m s-1, in cloud top heights by ~1 km, and in the volume of cloud objects by ~1.5 folds. These sets of high-resolution simulations under the specific weather regime offer critical information for assessing the potential impacts of the future changes of extreme rainfall contributed by the orographically locked diurnal convection on natural disasters and water resources.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":" 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141373596","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 : 2024-06-05DOI: 10.1088/2752-5295/ad5463
Markus Donat, Rashed Mahmood, Josep Cos, Pablo Ortega, F. Doblas-Reyes
Projections of near-term climate change in the next few decades are subject to substantial uncertainty from internal climate variability. Approaches to reduce this uncertainty by constraining the phasing of climate variability based on large ensembles of climate simulations have recently been developed. These approaches select those ensemble members that are in closer agreement with sea surface temperature patterns from either observations or initialized decadal predictions. Previous studies demonstrated the benefits of these constraints for projections up to 20 years into the future, but these studies applied the constraints to different ensembles of climate simulations, which prevents a consistent comparison of methods or identification of specific advantages of one method over another. Here we apply several methods to constrain internal variability phases, using either observations or decadal predictions as constraining reference, to an identical multi-model ensemble consisting of 311 simulations from 37 models from the Coupled Model Intercomparison Project phase 6 (CMIP6), and compare their forecast qualities. We show that constraining based on both observations and decadal predictions significantly enhances the skill of 10 and 20-year projections for near-surface temperatures in some regions, and that constraining based on decadal predictions leads to the largest added value in terms of probabilistic skill. We further explore the sensitivity to different implementations of the constraint that focus on the patterns of either internal variability alone or a combination of internal variability and long-term changes in response to forcing. Looking into the near-term future, all variations of the constraints suggest an accelerated warming of large parts of the Northern Hemisphere for the period 2020-2039, in comparison to the unconstrained CMIP6 ensemble.
{"title":"Improving the forecast quality of near-term climate projections by constraining internal variability based on decadal predictions and observations","authors":"Markus Donat, Rashed Mahmood, Josep Cos, Pablo Ortega, F. Doblas-Reyes","doi":"10.1088/2752-5295/ad5463","DOIUrl":"https://doi.org/10.1088/2752-5295/ad5463","url":null,"abstract":"\u0000 Projections of near-term climate change in the next few decades are subject to substantial uncertainty from internal climate variability. Approaches to reduce this uncertainty by constraining the phasing of climate variability based on large ensembles of climate simulations have recently been developed. These approaches select those ensemble members that are in closer agreement with sea surface temperature patterns from either observations or initialized decadal predictions. Previous studies demonstrated the benefits of these constraints for projections up to 20 years into the future, but these studies applied the constraints to different ensembles of climate simulations, which prevents a consistent comparison of methods or identification of specific advantages of one method over another. Here we apply several methods to constrain internal variability phases, using either observations or decadal predictions as constraining reference, to an identical multi-model ensemble consisting of 311 simulations from 37 models from the Coupled Model Intercomparison Project phase 6 (CMIP6), and compare their forecast qualities. We show that constraining based on both observations and decadal predictions significantly enhances the skill of 10 and 20-year projections for near-surface temperatures in some regions, and that constraining based on decadal predictions leads to the largest added value in terms of probabilistic skill. We further explore the sensitivity to different implementations of the constraint that focus on the patterns of either internal variability alone or a combination of internal variability and long-term changes in response to forcing. Looking into the near-term future, all variations of the constraints suggest an accelerated warming of large parts of the Northern Hemisphere for the period 2020-2039, in comparison to the unconstrained CMIP6 ensemble.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"34 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141382041","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 : 2024-06-04DOI: 10.1088/2752-5295/ad53f5
M. Grose, P. Hope, J. Risbey, Camille Mora, S. Perkins‐Kirkpatrick, A. King, L. Harrington, S. Rosier, R. Matear, Mitchell Black, Dáithí Stone, David J. Frame, R. McKay, Hamish Ramsay, Linjing Zhou, G. Tolhurst
Extreme event attribution (EEA) information is increasingly in demand from climate services. EEA messages can: raise awareness about the effect climate change has already imposed, inform climate change liability conversations, and be combined with climate projections to inform adaptation. However, due to limitations in observations, models and methods, there are barriers towards operationalising EEA in practice. Operational services will need EEA to be done transparently and using preset formats. Here we review recent experience and practice in EEA in Australia and New Zealand with a view to inform the design of an EEA component of climate services. We present a flow chart of the processes involved, noting particular care is needed on the trigger, event definition, and climate model evaluation, with effective stage gates. We also promote the use of tailored causal network diagrams as a standard tool to inform an EEA study and communicate results, with particular care needed for messages on events with lower confidence or complex sets of influences, including tropical cyclones and extratropical cyclones. We suggest that extending EEA to impact attribution is essential for making EEA messages salient but requires an uplift in forming interdisciplinary teams and in granular exposure and vulnerability datasets and is likely to raise new interdisciplinary methodological questions. Finally, we suggest communication of EEA messages can learn more from its origins in medical epidemiology.
{"title":"Processes and principles for producing credible climate change attribution messages: lessons from Australia and New Zealand","authors":"M. Grose, P. Hope, J. Risbey, Camille Mora, S. Perkins‐Kirkpatrick, A. King, L. Harrington, S. Rosier, R. Matear, Mitchell Black, Dáithí Stone, David J. Frame, R. McKay, Hamish Ramsay, Linjing Zhou, G. Tolhurst","doi":"10.1088/2752-5295/ad53f5","DOIUrl":"https://doi.org/10.1088/2752-5295/ad53f5","url":null,"abstract":"\u0000 Extreme event attribution (EEA) information is increasingly in demand from climate services. EEA messages can: raise awareness about the effect climate change has already imposed, inform climate change liability conversations, and be combined with climate projections to inform adaptation. However, due to limitations in observations, models and methods, there are barriers towards operationalising EEA in practice. Operational services will need EEA to be done transparently and using preset formats. Here we review recent experience and practice in EEA in Australia and New Zealand with a view to inform the design of an EEA component of climate services. We present a flow chart of the processes involved, noting particular care is needed on the trigger, event definition, and climate model evaluation, with effective stage gates. We also promote the use of tailored causal network diagrams as a standard tool to inform an EEA study and communicate results, with particular care needed for messages on events with lower confidence or complex sets of influences, including tropical cyclones and extratropical cyclones. We suggest that extending EEA to impact attribution is essential for making EEA messages salient but requires an uplift in forming interdisciplinary teams and in granular exposure and vulnerability datasets and is likely to raise new interdisciplinary methodological questions. Finally, we suggest communication of EEA messages can learn more from its origins in medical epidemiology.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141266493","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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