7 research outputs found

    Do Emergent Constraints on Carbon Cycle Feedbacks hold in CMIP6?

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    Emergent constraints on carbon cycle feedbacks in response to warming and increasing atmospheric CO2 concentration have previously been identified in Earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP) Phase 5. Here we examine whether two of these emergent constraints also hold for CMIP6. The spread of the sensitivity of tropical land carbon uptake to tropical warming in an idealized simulation with a 1% per year increase of atmospheric CO2 shows only a slight decrease in CMIP6 (-52 ± 35 GtC/K) compared to CMIP5 (-49 ± 40 GtC/K). For both model generations, the observed interannual variability in the growth rate of atmospheric CO2 yields a consistent emergent constraint on the sensitivity of tropical land carbon uptake with a constrained range of -37 ± 14 GtC/K for the combined ensemble (i.e., a reduction of ~30% in the best estimate and 60% in the uncertainty range relative to the multi-model mean of the combined ensemble). A further emergent constraint is based on a relationship between CO2 fertilization and the historical increase in the CO2 seasonal cycle amplitude in high latitudes. However, this emergent constraint is not evident in CMIP6. This is in part because the historical increase in the amplitude of the CO2 seasonal cycle is more accurately simulated in CMIP6, such that the models are all now close to the observational constraint

    Earth System Model Evaluation Tool (ESMValTool) v2.0 - diagnostics for emergent constraints and future projections from Earth system models in CMIP

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    The Earth System Model Evaluation Tool (ESMValTool), a community diagnostics and performance metrics tool for evaluation and analysis of Earth system models (ESMs) is designed to facilitate a more comprehensive and rapid comparison of single or multiple models participating in the Coupled Model Intercomparison Project (CMIP). The ESM results can be compared against observations or reanalysis data as well as against other models including predecessor versions of the same model. The updated and extended version 2.0 of the ESMValTool includes several new analysis scripts such as large-scale diagnostics for evaluation of ESMs as well as diagnostics for extreme events, regional model and impact evaluation. In this paper, the newly implemented climate metrics such as effective climate sensitivity (ECS) and transient climate response (TCR) as well as emergent constraints for various climate-relevant feedbacks and diagnostics for future projections from ESMs are described and illustrated with examples using results from the well-established model ensemble CMIP5. The emergent constraints implemented include constraints on ECS, snow-albedo effect, climate-carbon cycle feedback, hydrologic cycle intensification, future Indian summer monsoon precipitation, and year of disappearance of summer Arctic sea ice. The diagnostics included in ESMValTool v2.0 to analyze future climate projections from ESMs further include analysis scripts to reproduce selected figures of chapter 12 of the Intergovernmental Panel on Climate Change's (IPCC) Fifth Assessment report (AR5) and various multi-model statistics

    Do Emergent Constraints on Carbon Cycle Feedbacks Hold in CMIP6?

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    International audienceEmergent constraints on carbon cycle feedbacks in response to warming and increasing atmospheric CO2 concentration have previously been identified in Earth system models participating in the Coupled Model Intercomparison Project (CMIP) Phase 5. Here, we examine whether two of these emergent constraints also hold for CMIP6. The spread of the sensitivity of tropical land carbon uptake to tropical warming in an idealized simulation with a 1% per year increase of atmospheric CO2 shows only a slight decrease in CMIP6 (−52 ± 35 GtC/K) compared to CMIP5 (−49 ± 40 GtC/K). For both model generations, the observed interannual variability in the growth rate of atmospheric CO2 yields a consistent emergent constraint on the sensitivity of tropical land carbon uptake with a constrained range of −37 ± 14 GtC/K for the combined ensemble (i.e., a reduction of ∌30% in the best estimate and 60% in the uncertainty range relative to the multimodel mean of the combined ensemble). A further emergent constraint is based on a relationship between CO2 fertilization and the historical increase in the CO2 seasonal cycle amplitude in high latitudes. However, this emergent constraint is not evident in CMIP6. This is in part because the historical increase in the amplitude of the CO2 seasonal cycle is more accurately simulated in CMIP6, such that the models are all now close to the observational constraint

    Do Emergent Constraints on Carbon Cycle Feedbacks Hold in CMIP6?

    No full text
    International audienceEmergent constraints on carbon cycle feedbacks in response to warming and increasing atmospheric CO2 concentration have previously been identified in Earth system models participating in the Coupled Model Intercomparison Project (CMIP) Phase 5. Here, we examine whether two of these emergent constraints also hold for CMIP6. The spread of the sensitivity of tropical land carbon uptake to tropical warming in an idealized simulation with a 1% per year increase of atmospheric CO2 shows only a slight decrease in CMIP6 (−52 ± 35 GtC/K) compared to CMIP5 (−49 ± 40 GtC/K). For both model generations, the observed interannual variability in the growth rate of atmospheric CO2 yields a consistent emergent constraint on the sensitivity of tropical land carbon uptake with a constrained range of −37 ± 14 GtC/K for the combined ensemble (i.e., a reduction of ∌30% in the best estimate and 60% in the uncertainty range relative to the multimodel mean of the combined ensemble). A further emergent constraint is based on a relationship between CO2 fertilization and the historical increase in the CO2 seasonal cycle amplitude in high latitudes. However, this emergent constraint is not evident in CMIP6. This is in part because the historical increase in the amplitude of the CO2 seasonal cycle is more accurately simulated in CMIP6, such that the models are all now close to the observational constraint

    Do Emergent Constraints on Carbon Cycle Feedbacks Hold in CMIP6?

    No full text
    Emergent constraints on carbon cycle feedbacks in response to warming and increasing atmospheric CO2 concentration have previously been identified in Earth system models participating in the Coupled Model Intercomparison Project (CMIP) Phase 5. Here, we examine whether two of these emergent constraints also hold for CMIP6. The spread of the sensitivity of tropical land carbon uptake to tropical warming in an idealized simulation with a 1% per year increase of atmospheric CO2 shows only a slight decrease in CMIP6 (−52 ± 35 GtC/K) compared to CMIP5 (−49 ± 40 GtC/K). For both model generations, the observed interannual variability in the growth rate of atmospheric CO2 yields a consistent emergent constraint on the sensitivity of tropical land carbon uptake with a constrained range of −37 ± 14 GtC/K for the combined ensemble (i.e., a reduction of ∌30% in the best estimate and 60% in the uncertainty range relative to the multimodel mean of the combined ensemble). A further emergent constraint is based on a relationship between CO2 fertilization and the historical increase in the CO2 seasonal cycle amplitude in high latitudes. However, this emergent constraint is not evident in CMIP6. This is in part because the historical increase in the amplitude of the CO2 seasonal cycle is more accurately simulated in CMIP6, such that the models are all now close to the observational constraint.Plain Language Summary: The statistical model of so‐called emergent constraints help to better understand the sensitivity of Earth system processes in a changing climate. Here, we analyze the robustness of two previously found emergent constraints on carbon cycle feedbacks, using models from the Coupled Model Intercomparison Project (CMIP) of Phases 5 and 6. First the decrease of carbon storage in the tropics due to increasing near‐surface air temperatures, which is found to be robust on the choise of model ensemble. Giving a constraint estimate of −52 ± 35 GtC/K for CMIP6 models, being within the range of uncertainty for the previously estimated result for CMIP5. Second, the increase of carbon storage in high latitudes due to CO2 fertilization effect, which is found to be not evident among CMIP6 models. This is in part because the historical increase in the amplitude of the CO2 seasonal cycle is more accurately simulated in CMIP6, such that the models are all now close to the observational constraint.Key Points: An emergent constraint on the sensitivity of tropical land carbon to global warming, originally derived from Coupled Model Intercomparison Project Phase 5 (CMIP5), also holds for CMIP6. The combined CMIP5 + CMIP6 ensemble gives an emergent constraint on the sensitivity of tropical land carbon to global warming of −37 ± 14 GtC/K. An emergent constraint on the fertilization feedback due to rising CO2 levels, previously derived, is not evident in CMIP6.Horizon 2020 Framework Programme http://dx.doi.org/10.13039/100010661ERChttps://doi.org/10.5281/zenodo.6900341https://doi.org/10.5281/zenodo.3387139https://github.com/ESMValGrouphttps://docs.esmvaltool.org

    Earth System Model Evaluation Tool (ESMValTool) v2.0 – diagnostics for emergent constraints and future projections from Earth system models in CMIP

    No full text
    The Earth System Model Evaluation Tool (ESMValTool), a community diagnostics and performance metrics tool for evaluation and analysis of Earth system models (ESMs), is designed to facilitate a more comprehensive and rapid comparison of single or multiple models participating in the Coupled Model Intercomparison Project (CMIP). The ESM results can be compared against observations or reanalysis data as well as against other models including predecessor versions of the same model. The updated and extended version (v2.0) of the ESMValTool includes several new analysis scripts such as large-scale diagnostics for evaluation of ESMs as well as diagnostics for extreme events, regional model and impact evaluation. In this paper, the newly implemented climate metrics such as effective climate sensitivity (ECS) and transient climate response (TCR) as well as emergent constraints for various climate-relevant feedbacks and diagnostics for future projections from ESMs are described and illustrated with examples using results from the well-established model ensemble CMIP5. The emergent constraints implemented include constraints on ECS, snow-albedo effect, climate–carbon cycle feedback, hydrologic cycle intensification, future Indian summer monsoon precipitation and year of disappearance of summer Arctic sea ice. The diagnostics included in ESMValTool v2.0 to analyze future climate projections from ESMs further include analysis scripts to reproduce selected figures of chapter 12 of the Intergovernmental Panel on Climate Change's (IPCC) Fifth Assessment Report (AR5) and various multi-model statistics.ISSN:1991-9603ISSN:1991-959
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