H. Meier, M. Reckermann, J. Langner, Ben Smith, I. Didenkulova
Abstract. Baltic Earth is an independent research network of scientists from all Baltic Sea countries that promotes regional Earth system research. Within the framework of this network, the Baltic Earth Assessment Reports (BEARs) were produced in the period 2019–2022. These are a collection of 10 review articles summarising current knowledge on the environmental and climatic state of the Earth system in the Baltic Sea region and its changes in the past (palaeoclimate), present (historical period with instrumental observations) and prospective future (until 2100) caused by natural variability, climate change and other human activities. The division of topics among articles follows the grand challenges and selected themes of the Baltic Earth Science Plan, such as the regional water, biogeochemical and carbon cycles; extremes and natural hazards; sea-level dynamics and coastal erosion; marine ecosystems; coupled Earth system models; scenario simulations for the regional atmosphere and the Baltic Sea; and climate change and impacts of human use. Each review article contains an introduction, the current state of knowledge, knowledge gaps, conclusions and key messages; the latter are the bases on which recommendations for future research are made. Based on the BEARs, Baltic Earth has published an information leaflet on climate change in the Baltic Sea as part of its outreach work, which has been published in two languages so far, and organised conferences and workshops for stakeholders, in collaboration with the Baltic Marine Environment Protection Commission (Helsinki Commission, HELCOM).
{"title":"Overview: The Baltic Earth Assessment Reports (BEAR)","authors":"H. Meier, M. Reckermann, J. Langner, Ben Smith, I. Didenkulova","doi":"10.5194/esd-14-519-2023","DOIUrl":"https://doi.org/10.5194/esd-14-519-2023","url":null,"abstract":"Abstract. Baltic Earth is an independent research network of scientists from\u0000all Baltic Sea countries that promotes regional Earth system research.\u0000Within the framework of this network, the Baltic Earth Assessment Reports\u0000(BEARs) were produced in the period 2019–2022. These are a collection of 10 review articles summarising current knowledge on the environmental and\u0000climatic state of the Earth system in the Baltic Sea region and its changes\u0000in the past (palaeoclimate), present (historical period with instrumental\u0000observations) and prospective future (until 2100) caused by natural\u0000variability, climate change and other human activities. The division of\u0000topics among articles follows the grand challenges and selected themes of\u0000the Baltic Earth Science Plan, such as the regional water, biogeochemical\u0000and carbon cycles; extremes and natural hazards; sea-level dynamics and\u0000coastal erosion; marine ecosystems; coupled Earth system models; scenario\u0000simulations for the regional atmosphere and the Baltic Sea; and climate\u0000change and impacts of human use. Each review article contains an\u0000introduction, the current state of knowledge, knowledge gaps, conclusions\u0000and key messages; the latter are the bases on which recommendations for future research are\u0000made. Based on the BEARs, Baltic Earth has published an information leaflet\u0000on climate change in the Baltic Sea as part of its outreach work, which has\u0000been published in two languages so far, and organised conferences and\u0000workshops for stakeholders, in collaboration with the Baltic Marine\u0000Environment Protection Commission (Helsinki Commission, HELCOM).\u0000","PeriodicalId":92775,"journal":{"name":"Earth system dynamics : ESD","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42969943","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}
Liying Qiu, Eun-Soon Im, S. Min, Yeon-Hee Kim, D. Cha, Seok-Woo Shin, Joong-Bae Ahn, Eun-Chul Chang, Young-Hwa Byun
Abstract. Statistical bias correction (BC) is a widely used tool to post-process climate model biases in heat-stress impact studies, which are often based on the indices calculated from multiple dependent variables. This study compares four BC methods (three univariate and one multivariate) with two correction strategies (direct and indirect) for adjusting two heat-stress indices with different dependencies on temperature and relative humidity using multiple regional climate model simulations over South Korea. It would be helpful for reducing the ambiguity involved in the practical application of BC for climate modeling and end-user communities. Our results demonstrate that the multivariate approach can improve the corrected inter-variable dependence, which benefits the indirect correction of heat-stress indices depending on the adjustment of individual components, especially those indices relying equally on multiple drivers. On the other hand, the direct correction of multivariate indices using the quantile delta mapping univariate approach can also produce a comparable performance in the corrected heat-stress indices. However, our results also indicate that attention should be paid to the non-stationarity of bias brought by climate sensitivity in the modeled data, which may affect the bias-corrected results unsystematically. Careful interpretation of the correction process is required for an accurate heat-stress impact assessment.
{"title":"Direct and indirect application of univariate and multivariate bias corrections on heat-stress indices based on multiple regional-climate-model simulations","authors":"Liying Qiu, Eun-Soon Im, S. Min, Yeon-Hee Kim, D. Cha, Seok-Woo Shin, Joong-Bae Ahn, Eun-Chul Chang, Young-Hwa Byun","doi":"10.5194/esd-14-507-2023","DOIUrl":"https://doi.org/10.5194/esd-14-507-2023","url":null,"abstract":"Abstract. Statistical bias correction (BC) is a widely used tool to\u0000post-process climate model biases in heat-stress impact studies, which are\u0000often based on the indices calculated from multiple dependent variables.\u0000This study compares four BC methods (three univariate and one multivariate)\u0000with two correction strategies (direct and indirect) for adjusting two\u0000heat-stress indices with different dependencies on temperature and relative\u0000humidity using multiple regional climate model simulations over South\u0000Korea. It would be helpful for reducing the ambiguity involved in the\u0000practical application of BC for climate modeling and end-user communities.\u0000Our results demonstrate that the multivariate approach can improve the\u0000corrected inter-variable dependence, which benefits the indirect correction\u0000of heat-stress indices depending on the adjustment of individual components,\u0000especially those indices relying equally on multiple drivers. On the other\u0000hand, the direct correction of multivariate indices using the quantile delta\u0000mapping univariate approach can also produce a comparable performance in the\u0000corrected heat-stress indices. However, our results also indicate that\u0000attention should be paid to the non-stationarity of bias brought by climate\u0000sensitivity in the modeled data, which may affect the bias-corrected results\u0000unsystematically. Careful interpretation of the correction process is\u0000required for an accurate heat-stress impact assessment.\u0000","PeriodicalId":92775,"journal":{"name":"Earth system dynamics : ESD","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44292671","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}
T. Palmer, C. McSweeney, B. Booth, Matthew D. K. Priestley, P. Davini, L. Brunner, L. Borchert, M. Menary
Abstract. We have created a performance-based assessment of CMIP6 models for Europe that can be used to inform the sub-selection of models for this region. Our assessment covers criteria indicative of the ability of individual models to capture a range of large-scale processes that are important for the representation of present-day European climate. We use this study to provide examples of how this performance-based assessment may be applied to a multi-model ensemble of CMIP6 models to (a) filter the ensemble for performance against these climatological and processed-based criteria and (b) create a smaller subset of models based on performance that also maintains model diversity and the filtered projection range as far as possible. Filtering by excluding the least-realistic models leads to higher-sensitivity models remaining in the ensemble as an emergent consequence of the assessment. This results in both the 25th percentile and the median of the projected temperature range being shifted towards greater warming for the filtered set of models. We also weight the unfiltered ensemble against global trends. In contrast, this shifts the distribution towards less warming. This highlights a tension for regional model selection in terms of selection based on regional climate processes versus the global mean warming trend.
{"title":"Performance-based sub-selection of CMIP6 models for impact assessments in Europe","authors":"T. Palmer, C. McSweeney, B. Booth, Matthew D. K. Priestley, P. Davini, L. Brunner, L. Borchert, M. Menary","doi":"10.5194/esd-14-457-2023","DOIUrl":"https://doi.org/10.5194/esd-14-457-2023","url":null,"abstract":"Abstract. We have created a performance-based assessment of CMIP6 models for Europe that can be used to inform the sub-selection of models for this region. Our assessment covers criteria indicative of the ability of individual models to capture a range of large-scale processes that are important for the representation of present-day European climate. We use this study to provide examples of how this performance-based assessment may be applied to a multi-model ensemble of CMIP6 models to (a) filter the ensemble for performance against these climatological and processed-based criteria and (b) create a smaller subset of models based on performance that also maintains model diversity and the filtered projection range as far as possible. Filtering by excluding the least-realistic models leads to higher-sensitivity models remaining in the ensemble as an emergent consequence of the assessment. This results in both the 25th percentile and the median of the projected temperature range being shifted towards greater warming for the filtered set of models. We also weight the unfiltered ensemble against global trends. In contrast, this shifts the distribution towards less warming. This highlights a tension for regional model selection in terms of selection based on regional climate processes versus the global mean warming trend.\u0000","PeriodicalId":92775,"journal":{"name":"Earth system dynamics : ESD","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45122384","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}
Abstract. The 18.6-year lunar nodal cycle arises from variations in the angle of the Moon's orbital plane. Previous work has linked the nodal cycle to climate but has been limited by either the length of observations analysed or geographical regions considered in model simulations of the pre-industrial period. Here we examine the global effect of the lunar nodal cycle in multi-centennial climate model simulations of the pre-industrial period. We find cyclic signals in global and regional surface air temperature (with amplitudes of around 0.1 K) and in ocean heat uptake and ocean heat content. The timing of anomalies of global surface air temperature and heat uptake is consistent with the so-called slowdown in global warming in the first decade of the 21st century. The lunar nodal cycle causes variations in mean sea level pressure exceeding 0.5 hPa in the Nordic Seas region, thus affecting the North Atlantic Oscillation during boreal winter. Our results suggest that the contribution of the lunar nodal cycle to global temperature should be negative in the mid-2020s before becoming positive again in the early 2030s, reducing the uncertainty in time at which projected global temperature reaches 1.5 ∘C above pre-industrial levels.
{"title":"The modelled climatic response to the 18.6-year lunar nodal cycle and its role in decadal temperature trends","authors":"M. Joshi, R. Hall, D. Stevens, E. Hawkins","doi":"10.5194/esd-14-443-2023","DOIUrl":"https://doi.org/10.5194/esd-14-443-2023","url":null,"abstract":"Abstract. The 18.6-year lunar nodal cycle arises from variations in the\u0000angle of the Moon's orbital plane. Previous work has linked the nodal cycle\u0000to climate but has been limited by either the length of observations\u0000analysed or geographical regions considered in model simulations of the\u0000pre-industrial period. Here we examine the global effect of the lunar nodal\u0000cycle in multi-centennial climate model simulations of the pre-industrial\u0000period. We find cyclic signals in global and regional surface air\u0000temperature (with amplitudes of around 0.1 K) and in ocean heat uptake and\u0000ocean heat content. The timing of anomalies of global surface air\u0000temperature and heat uptake is consistent with the so-called slowdown in\u0000global warming in the first decade of the 21st century. The lunar nodal\u0000cycle causes variations in mean sea level pressure exceeding 0.5 hPa in the\u0000Nordic Seas region, thus affecting the North Atlantic Oscillation during\u0000boreal winter. Our results suggest that the contribution of the lunar nodal\u0000cycle to global temperature should be negative in the mid-2020s before\u0000becoming positive again in the early 2030s, reducing the uncertainty in time\u0000at which projected global temperature reaches 1.5 ∘C above pre-industrial\u0000levels.\u0000","PeriodicalId":92775,"journal":{"name":"Earth system dynamics : ESD","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42965624","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}
C. Huntingford, P. Cox, M. Williamson, Joseph J. Clarke, P. Ritchie
Abstract. Planning for the impacts of climate change requires accurate projections by Earth system models (ESMs). ESMs, as developed by many research centres, estimate changes to weather and climate as atmospheric greenhouse gases (GHGs) rise, and they inform the influential Intergovernmental Panel on Climate Change (IPCC) reports. ESMs are advancing the understanding of key climate system attributes. However, there remain substantial inter-ESM differences in their estimates of future meteorological change, even for a common GHG trajectory, and such differences make adaptation planning difficult. Until recently, the primary approach to reducing projection uncertainty has been to place an emphasis on simulations that best describe the contemporary climate. Yet a model that performs well for present-day atmospheric GHG levels may not necessarily be accurate for higher GHG levels and vice versa. A relatively new approach of emergent constraints (ECs) is gaining much attention as a technique to remove uncertainty between climate models. This method involves searching for an inter-ESM link between a quantity that we can also measure now and a second quantity of major importance for describing future climate. Combining the contemporary measurement with this relationship refines the future projection. Identified ECs exist for thermal, hydrological and geochemical cycles of the climate system. As ECs grow in influence on climate policy, the method is under intense scrutiny, creating a requirement to understand them better. We hypothesise that as many Earth system components vary in both space and time, their behaviours often satisfy large-scale differential equations (DEs). Such DEs are valid at coarser scales than the equations coded in ESMs which capture finer high-resolution grid-box-scale effects. We suggest that many ECs link to such effective hidden DEs implicit in ESMs and that aggregate small-scale features. An EC may exist because its two quantities depend similarly on an ESM-specific internal bulk parameter in such a DE, with measurements constraining and revealing its (implicit) value. Alternatively, well-established process understanding coded at the ESM grid box scale, when aggregated, may generate a bulk parameter with a common “emergent” value across all ESMs. This single emerging parameter may link uncertainties in a contemporary climate driver to those of a climate-related property of interest. In these circumstances, the EC combined with a measurement of the driver that is uncertain constrains the estimate of the climate-related quantity. We offer simple illustrative examples of these concepts with generic DEs but with their solutions placed in a conceptual EC framework.
{"title":"Emergent constraints for the climate system as effective parameters of bulk differential equations","authors":"C. Huntingford, P. Cox, M. Williamson, Joseph J. Clarke, P. Ritchie","doi":"10.5194/esd-14-433-2023","DOIUrl":"https://doi.org/10.5194/esd-14-433-2023","url":null,"abstract":"Abstract. Planning for the impacts of climate change requires accurate projections by Earth system models (ESMs).\u0000ESMs, as developed by many research centres, estimate changes to weather and climate as atmospheric greenhouse gases (GHGs) rise,\u0000and they inform the influential Intergovernmental Panel on Climate Change (IPCC) reports.\u0000ESMs are advancing the understanding of key climate system attributes. However, there remain\u0000substantial inter-ESM differences in their estimates of future meteorological change, even for a common GHG trajectory, and\u0000such differences make adaptation planning difficult.\u0000Until recently, the primary approach to reducing projection uncertainty has been to place an emphasis\u0000on simulations that best describe the contemporary climate. Yet a model that performs well for present-day\u0000atmospheric GHG levels may not necessarily be accurate for higher GHG levels and vice versa. A relatively new approach of\u0000emergent constraints (ECs) is gaining much attention as a technique to remove uncertainty between climate models.\u0000This method involves searching for an inter-ESM link between a quantity that we can also measure now and a second quantity of major importance for\u0000describing future climate. Combining the contemporary\u0000measurement with this relationship refines the future projection. Identified ECs exist for thermal, hydrological and geochemical\u0000cycles of the climate system. As ECs grow in influence on climate policy, the method is under intense scrutiny, creating a requirement to understand them better.\u0000We hypothesise that as many Earth system components vary in both space and time, their behaviours often satisfy\u0000large-scale differential equations (DEs). Such DEs are valid at coarser scales than the equations\u0000coded in ESMs which capture finer high-resolution grid-box-scale effects. We suggest that many ECs link to such effective hidden\u0000DEs implicit in ESMs and that aggregate small-scale features. An EC may exist because its two quantities depend similarly on an ESM-specific\u0000internal bulk parameter in such a DE, with measurements constraining and revealing its (implicit) value.\u0000Alternatively, well-established process understanding coded at the ESM grid box scale,\u0000when aggregated, may generate a bulk parameter with a common “emergent” value across all ESMs. This\u0000single emerging parameter may link uncertainties in a contemporary climate driver to those of a climate-related property of interest. In these circumstances,\u0000the EC combined with a measurement of the driver that is uncertain constrains the estimate of the climate-related quantity.\u0000We offer simple illustrative examples of these concepts with generic DEs but with their solutions placed in a conceptual EC framework.\u0000","PeriodicalId":92775,"journal":{"name":"Earth system dynamics : ESD","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41447400","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}
S. Berthet, J. Jouanno, R. Séférian, M. Gehlen, W. Llovel
Abstract. The phytoplankton–light feedback (PLF) describes the interaction between phytoplankton biomass and the downwelling shortwave radiation entering the ocean. The PLF allows the simulation of differential heating across the ocean water column as a function of phytoplankton concentration. Only one third of the Earth system models contributing to the 6th phase of the Coupled Model Intercomparison Project (CMIP6) include a complete representation of the PLF. In other models, the PLF is either approximated by a prescribed climatology of chlorophyll or not represented at all. Consequences of an incomplete representation of the PLF on the modelled biogeochemical state have not yet been fully assessed and remain a source of multi-model uncertainty in future projection. Here, we evaluate within a coherent modelling framework how representations of the PLF of varying complexity impact ocean physics and ultimately marine production of nitrous oxide (N2O), a major greenhouse gas. We exploit global sensitivity simulations at 1∘ horizontal resolution over the last 2 decades (1999–2018), coupling ocean, sea ice and marine biogeochemistry. The representation of the PLF impacts ocean heat uptake and temperature of the first 300 m of the tropical ocean. Temperature anomalies due to an incomplete PLF representation drive perturbations of ocean stratification, dynamics and oxygen concentration. These perturbations translate into different projection pathways for N2O production depending on the choice of the PLF representation. The oxygen concentration in the North Pacific oxygen-minimum zone is overestimated in model runs with an incomplete representation of the PLF, which results in an underestimation of local N2O production. This leads to important regional differences of sea-to-air N2O fluxes: fluxes are enhanced by up to 24 % in the South Pacific and South Atlantic subtropical gyres but reduced by up to 12 % in oxygen-minimum zones of the Northern Hemisphere. Our results, based on a global ocean–biogeochemical model at CMIP6 state-of-the-art level, shed light on current uncertainties in modelled marine nitrous oxide budgets in climate models.
{"title":"How does the phytoplankton–light feedback affect the marine N2O inventory?","authors":"S. Berthet, J. Jouanno, R. Séférian, M. Gehlen, W. Llovel","doi":"10.5194/esd-14-399-2023","DOIUrl":"https://doi.org/10.5194/esd-14-399-2023","url":null,"abstract":"Abstract. The phytoplankton–light feedback (PLF) describes the interaction between\u0000phytoplankton biomass and the downwelling shortwave radiation entering the\u0000ocean. The PLF allows the simulation of differential heating across the ocean\u0000water column as a function of phytoplankton concentration. Only one third of\u0000the Earth system models contributing to the 6th phase of the Coupled\u0000Model Intercomparison Project (CMIP6) include a complete representation of\u0000the PLF. In other models, the PLF is either approximated by a prescribed\u0000climatology of chlorophyll or not represented at all. Consequences of an\u0000incomplete representation of the PLF on the modelled biogeochemical state\u0000have not yet been fully assessed and remain a source of multi-model\u0000uncertainty in future projection. Here, we evaluate within a coherent\u0000modelling framework how representations of the PLF of varying complexity\u0000impact ocean physics and ultimately marine production of nitrous oxide\u0000(N2O), a major greenhouse gas. We exploit global sensitivity\u0000simulations at 1∘ horizontal resolution over the last 2 decades\u0000(1999–2018), coupling ocean, sea ice and marine biogeochemistry. The\u0000representation of the PLF impacts ocean heat uptake and temperature of the\u0000first 300 m of the tropical ocean. Temperature anomalies due to an\u0000incomplete PLF representation drive perturbations of ocean stratification,\u0000dynamics and oxygen concentration. These perturbations translate into\u0000different projection pathways for N2O production depending on the\u0000choice of the PLF representation. The oxygen concentration in the North\u0000Pacific oxygen-minimum zone is overestimated in model runs with an\u0000incomplete representation of the PLF, which results in an underestimation of\u0000local N2O production. This leads to important regional differences of\u0000sea-to-air N2O fluxes: fluxes are enhanced by up to 24 % in the South\u0000Pacific and South Atlantic subtropical gyres but reduced by up to 12 % in\u0000oxygen-minimum zones of the Northern Hemisphere. Our results, based on a\u0000global ocean–biogeochemical model at CMIP6 state-of-the-art level, shed light on\u0000current uncertainties in modelled marine nitrous oxide budgets in climate\u0000models.\u0000","PeriodicalId":92775,"journal":{"name":"Earth system dynamics : ESD","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41864278","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}
Abstract. As a major sink for anthropogenic carbon, the oceans slow the increase in carbon dioxide in the atmosphere and regulate climate change. Future changes in the ocean carbon sink, and its uncertainty at a global and regional scale, are key to understanding the future evolution of the climate. Here we report on the changes and uncertainties in the historical and future ocean carbon sink using output from the Coupled Model Intercomparison Project Phase 6 (CMIP6) multi-model ensemble and compare to an observation-based product. We show that future changes in the ocean carbon sink are concentrated in highly active regions – 70 % of the total sink occurs in less than 40 % of the global ocean. High pattern correlations between the historical uptake and projected future changes in the carbon sink indicate that future uptake will largely continue to occur in historically important regions. We conduct a detailed breakdown of the sources of uncertainty in the future carbon sink by region. Consistent with CMIP5 models, scenario uncertainty dominates at the global scale, followed by model uncertainty and then internal variability. We demonstrate how the importance of internal variability increases moving to smaller spatial scales and go on to show how the breakdown between scenario, model, and internal variability changes between different ocean regions, governed by different processes. Using the CanESM5 large ensemble we show that internal variability changes with time based on the scenario, breaking the widely employed assumption of stationarity. As with the mean sink, we show that uncertainty in the future ocean carbon sink is also concentrated in the known regions of historical uptake. Patterns in the signal-to-noise ratio have implications for observational detectability and time of emergence, which we show to vary both in space and with scenario. We show that the largest variations in emergence time across scenarios occur in regions where the ocean sink is less sensitive to forcing – outside of the highly active regions. In agreement with CMIP5 studies, our results suggest that for a better chance of early detection of changes in the ocean carbon sink and to efficiently reduce uncertainty in future carbon uptake, highly active regions, including the northwestern Atlantic and the Southern Ocean, should receive additional focus for modeling and observational efforts.
{"title":"Time-varying changes and uncertainties in the CMIP6 ocean carbon sink from global to local scale","authors":"P. Gooya, N. Swart, R. Hamme","doi":"10.5194/esd-14-383-2023","DOIUrl":"https://doi.org/10.5194/esd-14-383-2023","url":null,"abstract":"Abstract. As a major sink for anthropogenic carbon, the oceans slow the\u0000increase in carbon dioxide in the atmosphere and regulate climate change.\u0000Future changes in the ocean carbon sink, and its uncertainty at a global and\u0000regional scale, are key to understanding the future evolution of the\u0000climate. Here we report on the changes and uncertainties in the historical\u0000and future ocean carbon sink using output from the Coupled Model\u0000Intercomparison Project Phase 6 (CMIP6) multi-model ensemble and compare to\u0000an observation-based product. We show that future changes in the ocean\u0000carbon sink are concentrated in highly active regions – 70 % of the\u0000total sink occurs in less than 40 % of the global ocean. High pattern\u0000correlations between the historical uptake and projected future changes in\u0000the carbon sink indicate that future uptake will largely continue to occur\u0000in historically important regions. We conduct a detailed breakdown of the\u0000sources of uncertainty in the future carbon sink by region. Consistent with\u0000CMIP5 models, scenario uncertainty dominates at the global scale, followed\u0000by model uncertainty and then internal variability. We demonstrate how the\u0000importance of internal variability increases moving to smaller spatial\u0000scales and go on to show how the breakdown between scenario, model, and\u0000internal variability changes between different ocean regions, governed by\u0000different processes. Using the CanESM5 large ensemble we show that internal\u0000variability changes with time based on the scenario, breaking the widely\u0000employed assumption of stationarity. As with the mean sink, we show that\u0000uncertainty in the future ocean carbon sink is also concentrated in the\u0000known regions of historical uptake. Patterns in the signal-to-noise ratio\u0000have implications for observational detectability and time of emergence,\u0000which we show to vary both in space and with scenario. We show that the\u0000largest variations in emergence time across scenarios occur in regions where\u0000the ocean sink is less sensitive to forcing – outside of the highly active\u0000regions. In agreement with CMIP5 studies, our results suggest that for a\u0000better chance of early detection of changes in the ocean carbon sink and to\u0000efficiently reduce uncertainty in future carbon uptake, highly active\u0000regions, including the northwestern Atlantic and the Southern Ocean, should\u0000receive additional focus for modeling and observational efforts.\u0000","PeriodicalId":92775,"journal":{"name":"Earth system dynamics : ESD","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41487373","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}
Susanne Baur, A. Nauels, Zebedee R. J. Nicholls, B. Sanderson, C. Schleussner
Abstract. A growing body of literature investigates the effects of solar radiation modification (SRM) on global and regional climates. Previous studies have focused on the potentials and the side effects of SRM, with little attention being given to possible deployment timescales and the levels of carbon dioxide removal required for a phase out. Here, we investigate the deployment timescales of SRM and how they are affected by different levels of mitigation, net-negative emissions (NNEs) and climate uncertainty. We generate a large dataset of 355 emission scenarios in which SRM is deployed to keep warming levels at 1.5 ∘C global mean temperature. Probabilistic climate projections from this ensemble result in a large range of plausible future warming and cooling rates that lead to various SRM deployment timescales. In all pathways consistent with extrapolated current ambition, SRM deployment would exceed 100 years even under the most optimistic assumptions regarding climate response. As soon as the temperature threshold is exceeded, neither mitigation nor NNEs or climate sensitivity alone can guarantee short deployment timescales. Since the evolution of mitigation under SRM, the availability of carbon removal technologies and the effects of climate reversibility will be mostly unknown at its initialisation time, it is impossible to predict how temporary SRM deployment would be. Any deployment of SRM therefore comes with the risk of multi-century legacies of deployment, implying multi-generational commitments of costs, risks and negative side effects of SRM and NNEs combined.
{"title":"The deployment length of solar radiation modification: an interplay of mitigation, net-negative emissions and climate uncertainty","authors":"Susanne Baur, A. Nauels, Zebedee R. J. Nicholls, B. Sanderson, C. Schleussner","doi":"10.5194/esd-14-367-2023","DOIUrl":"https://doi.org/10.5194/esd-14-367-2023","url":null,"abstract":"Abstract. A growing body of literature investigates the effects of solar\u0000radiation modification (SRM) on global and regional climates. Previous\u0000studies have focused on the potentials and the side effects of SRM, with little\u0000attention being given to possible deployment timescales and the levels of carbon\u0000dioxide removal required for a phase out. Here, we investigate the\u0000deployment timescales of SRM and how they are affected by different levels\u0000of mitigation, net-negative emissions (NNEs) and climate uncertainty. We\u0000generate a large dataset of 355 emission scenarios in which SRM is deployed\u0000to keep warming levels at 1.5 ∘C global mean temperature.\u0000Probabilistic climate projections from this ensemble result in a large range\u0000of plausible future warming and cooling rates that lead to various SRM\u0000deployment timescales. In all pathways consistent with extrapolated current\u0000ambition, SRM deployment would exceed 100 years even under the most\u0000optimistic assumptions regarding climate response. As soon as the temperature\u0000threshold is exceeded, neither mitigation nor NNEs or climate sensitivity\u0000alone can guarantee short deployment timescales. Since the evolution of\u0000mitigation under SRM, the availability of carbon removal technologies and\u0000the effects of climate reversibility will be mostly unknown at its\u0000initialisation time, it is impossible to predict how temporary SRM\u0000deployment would be. Any deployment of SRM therefore comes with the risk of\u0000multi-century legacies of deployment, implying multi-generational\u0000commitments of costs, risks and negative side effects of SRM and NNEs\u0000combined.\u0000","PeriodicalId":92775,"journal":{"name":"Earth system dynamics : ESD","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46478825","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}
Abstract. The Earth's albedo is observed to be symmetric between the hemispheres on the annual mean timescale, despite the clear-sky albedo being asymmetrically higher in the Northern Hemisphere due to more land area and aerosol sources; this is because the mean cloud distribution currently compensates for the clear-sky asymmetry almost exactly. We investigate the evolution of the hemispheric difference in albedo in the Coupled Model Intercomparison Project Phase 6 (CMIP6) coupled model simulations following an abrupt quadrupling of CO2 concentrations, to which all models respond with an initial decrease of albedo in the Northern Hemisphere (NH) due to loss of Arctic sea ice. Models disagree over whether the net effect of NH cloud responses is to reduce or amplify initial NH albedo reductions. After the initial response, the evolution of the hemispheric albedo difference diverges among models, with some models remaining stably at their new hemispheric albedo difference and others returning towards their pre-industrial difference primarily through a reduction in SH cloud cover. Whereas local increases in cloud cover contribute to negative shortwave cloud feedback, the cross-hemispheric communicating mechanism found to be primarily responsible for restoring hemispheric symmetry in the models studied implies positive shortwave cloud feedback.
{"title":"The implications of maintaining Earth's hemispheric albedo symmetry for shortwave radiative feedbacks","authors":"Aiden R. Jönsson, F. Bender","doi":"10.5194/esd-14-345-2023","DOIUrl":"https://doi.org/10.5194/esd-14-345-2023","url":null,"abstract":"Abstract. The Earth's albedo is observed to be symmetric between the hemispheres on the annual mean timescale, despite the clear-sky albedo being asymmetrically higher in the Northern Hemisphere due to more land area and aerosol sources; this is because the mean cloud distribution currently compensates for the clear-sky asymmetry almost exactly. We investigate the evolution of the hemispheric difference in albedo in the Coupled Model Intercomparison Project Phase 6 (CMIP6) coupled model simulations following an abrupt quadrupling of CO2 concentrations, to which all models respond with an initial decrease of albedo in the Northern Hemisphere (NH) due to loss of Arctic sea ice. Models disagree over whether the net effect of NH cloud responses is to reduce or amplify initial NH albedo reductions. After the initial response, the evolution of the hemispheric albedo difference diverges among models, with some models remaining stably at their new hemispheric albedo difference and others returning towards their pre-industrial difference primarily through a reduction in SH cloud cover. Whereas local increases in cloud cover contribute to negative shortwave cloud feedback, the cross-hemispheric communicating mechanism found to be primarily responsible for restoring hemispheric symmetry in the models studied implies positive shortwave cloud feedback.\u0000","PeriodicalId":92775,"journal":{"name":"Earth system dynamics : ESD","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42833139","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}
Soufiane Karmouche, E. Galytska, J. Runge, G. Meehl, A. Phillips, K. Weigel, V. Eyring
Abstract. The climate system and its spatio-temporal changes are strongly affected by modes of long-term internal variability, like the Pacific decadal variability (PDV) and the Atlantic multidecadal variability (AMV). As they alternate between warm and cold phases, the interplay between PDV and AMV varies over decadal to multidecadal timescales. Here, we use a causal discovery method to derive fingerprints in the Atlantic–Pacific interactions and to investigate their phase-dependent changes. Dependent on the phases of PDV and AMV, different regimes with characteristic causal fingerprints are identified in reanalyses in a first step. In a second step, a regime-oriented causal model evaluation is performed to evaluate the ability of models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) in representing the observed changing interactions between PDV, AMV and their extra-tropical teleconnections. The causal graphs obtained from reanalyses detect a direct opposite-sign response from AMV to PDV when analyzing the complete 1900–2014 period and during several defined regimes within that period, for example, when AMV is going through its negative (cold) phase. Reanalyses also demonstrate a same-sign response from PDV to AMV during the cold phase of PDV. Historical CMIP6 simulations exhibit varying skill in simulating the observed causal patterns. Generally, large-ensemble (LE) simulations showed better network similarity when PDV and AMV were out of phase compared to other regimes. Also, the two largest ensembles (in terms of number of members) were found to contain realizations with similar causal fingerprints to observations. For most regimes, these same models showed higher network similarity when compared to each other. This work shows how causal discovery on LEs complements the available diagnostics and statistical metrics of climate variability to provide a powerful tool for climate model evaluation.
{"title":"Regime-oriented causal model evaluation of Atlantic–Pacific teleconnections in CMIP6","authors":"Soufiane Karmouche, E. Galytska, J. Runge, G. Meehl, A. Phillips, K. Weigel, V. Eyring","doi":"10.5194/esd-14-309-2023","DOIUrl":"https://doi.org/10.5194/esd-14-309-2023","url":null,"abstract":"Abstract. The climate system and its spatio-temporal changes are strongly affected by modes of long-term internal variability, like the Pacific decadal variability (PDV) and the Atlantic multidecadal variability (AMV). As they alternate between warm and cold phases, the interplay between PDV and AMV varies over decadal to multidecadal timescales. Here, we use a causal discovery method to derive fingerprints in the Atlantic–Pacific interactions and to investigate their phase-dependent changes. Dependent on the phases of PDV and AMV, different regimes with characteristic causal fingerprints are identified in reanalyses in a first step. In a second step, a regime-oriented causal model evaluation is performed to evaluate the ability of models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) in representing the observed changing interactions between PDV, AMV and their extra-tropical teleconnections. The causal graphs obtained from reanalyses detect a direct opposite-sign response from AMV to PDV when analyzing the complete 1900–2014 period and during several defined regimes within that period, for example, when AMV is going through its negative (cold) phase. Reanalyses also demonstrate a same-sign response from PDV to AMV during the cold phase of PDV. Historical CMIP6 simulations exhibit varying skill in simulating the observed causal patterns. Generally, large-ensemble (LE) simulations showed better network similarity when PDV and AMV were out of phase compared to other regimes. Also, the two largest ensembles (in terms of number of members) were found to contain realizations with similar causal fingerprints to observations. For most regimes, these same models showed higher network similarity when compared to each other. This work shows how causal discovery on LEs complements the available diagnostics and statistical metrics of climate variability to provide a powerful tool for climate model evaluation.\u0000","PeriodicalId":92775,"journal":{"name":"Earth system dynamics : ESD","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49007081","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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