Articles | Volume 11, issue 4
https://doi.org/10.5194/esd-11-995-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-11-995-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
13 Nov 2020
Research article | Highlight paper |
| 13 Nov 2020
| 13 Nov 2020
Reduced global warming from CMIP6 projections when weighting models by performance and independence
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Angeline G. Pendergrass
National Center for Atmospheric Research, Boulder, CO, USA
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
now at: Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, NY, USA
Flavio Lehner
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
now at: Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, NY, USA
Anna L. Merrifield
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Ruth Lorenz
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Reto Knutti
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
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Quantifying dynamical and thermodynamical components of regional precipitation change is a key challenge in climate science. We introduce a novel statistical model (Latent Linear Adjustment Autoencoder) that combines the flexibility of deep neural networks with the robustness advantages of linear regression. The method enables estimation of the contribution of a coarse-scale atmospheric circulation proxy to daily precipitation at high resolution and in a spatially coherent manner.
Claudia Tebaldi, Kevin Debeire, Veronika Eyring, Erich Fischer, John Fyfe, Pierre Friedlingstein, Reto Knutti, Jason Lowe, Brian O'Neill, Benjamin Sanderson, Detlef van Vuuren, Keywan Riahi, Malte Meinshausen, Zebedee Nicholls, Katarzyna B. Tokarska, George Hurtt, Elmar Kriegler, Jean-Francois Lamarque, Gerald Meehl, Richard Moss, Susanne E. Bauer, Olivier Boucher, Victor Brovkin, Young-Hwa Byun, Martin Dix, Silvio Gualdi, Huan Guo, Jasmin G. John, Slava Kharin, YoungHo Kim, Tsuyoshi Koshiro, Libin Ma, Dirk Olivié, Swapna Panickal, Fangli Qiao, Xinyao Rong, Nan Rosenbloom, Martin Schupfner, Roland Séférian, Alistair Sellar, Tido Semmler, Xiaoying Shi, Zhenya Song, Christian Steger, Ronald Stouffer, Neil Swart, Kaoru Tachiiri, Qi Tang, Hiroaki Tatebe, Aurore Voldoire, Evgeny Volodin, Klaus Wyser, Xiaoge Xin, Shuting Yang, Yongqiang Yu, and Tilo Ziehn
Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, https://doi.org/10.5194/esd-12-253-2021, 2021
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We present an overview of CMIP6 ScenarioMIP outcomes from up to 38 participating ESMs according to the new SSP-based scenarios. Average temperature and precipitation projections according to a wide range of forcings, spanning a wider range than the CMIP5 projections, are documented as global averages and geographic patterns. Times of crossing various warming levels are computed, together with benefits of mitigation for selected pairs of scenarios. Comparisons with CMIP5 are also discussed.
Anna Louise Merrifield, Lukas Brunner, Ruth Lorenz, Iselin Medhaug, and Reto Knutti
Earth Syst. Dynam., 11, 807–834, https://doi.org/10.5194/esd-11-807-2020, https://doi.org/10.5194/esd-11-807-2020, 2020
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Justifiable uncertainty estimates of future change in northern European winter and Mediterranean summer temperature can be obtained by weighting a multi-model ensemble comprised of projections from different climate models and multiple projections from the same climate model. Weights reduce the influence of model biases and handle dependence by identifying a projection's model of origin from historical characteristics; contributions from the same model are scaled by the number of members.
Axel Lauer, Veronika Eyring, Omar Bellprat, Lisa Bock, Bettina K. Gier, Alasdair Hunter, Ruth Lorenz, Núria Pérez-Zanón, Mattia Righi, Manuel Schlund, Daniel Senftleben, Katja Weigel, and Sabrina Zechlau
Geosci. Model Dev., 13, 4205–4228, https://doi.org/10.5194/gmd-13-4205-2020, https://doi.org/10.5194/gmd-13-4205-2020, 2020
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The Earth System Model Evaluation Tool is a community software tool designed for evaluation and analysis of climate models. New features of version 2.0 include analysis scripts for important large-scale features in climate models, diagnostics for extreme events, regional model and impact evaluation. In this paper, newly implemented climate metrics, emergent constraints for climate-relevant feedbacks and diagnostics for future model projections are described and illustrated with examples.
Flavio Lehner, Clara Deser, Nicola Maher, Jochem Marotzke, Erich M. Fischer, Lukas Brunner, Reto Knutti, and Ed Hawkins
Earth Syst. Dynam., 11, 491–508, https://doi.org/10.5194/esd-11-491-2020, https://doi.org/10.5194/esd-11-491-2020, 2020
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Projections of climate change are uncertain because climate models are imperfect, future greenhouse gases emissions are unknown and climate is to some extent chaotic. To partition and understand these sources of uncertainty and make the best use of climate projections, large ensembles with multiple climate models are needed. Such ensembles now exist in a public data archive. We provide several novel applications focused on global and regional temperature and precipitation projections.
Christoph Heinze, Veronika Eyring, Pierre Friedlingstein, Colin Jones, Yves Balkanski, William Collins, Thierry Fichefet, Shuang Gao, Alex Hall, Detelina Ivanova, Wolfgang Knorr, Reto Knutti, Alexander Löw, Michael Ponater, Martin G. Schultz, Michael Schulz, Pier Siebesma, Joao Teixeira, George Tselioudis, and Martin Vancoppenolle
Earth Syst. Dynam., 10, 379–452, https://doi.org/10.5194/esd-10-379-2019, https://doi.org/10.5194/esd-10-379-2019, 2019
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Earth system models for producing climate projections under given forcings include additional processes and feedbacks that traditional physical climate models do not consider. We present an overview of climate feedbacks for key Earth system components and discuss the evaluation of these feedbacks. The target group for this article includes generalists with a background in natural sciences and an interest in climate change as well as experts working in interdisciplinary climate research.
Gab Abramowitz, Nadja Herger, Ethan Gutmann, Dorit Hammerling, Reto Knutti, Martin Leduc, Ruth Lorenz, Robert Pincus, and Gavin A. Schmidt
Earth Syst. Dynam., 10, 91–105, https://doi.org/10.5194/esd-10-91-2019, https://doi.org/10.5194/esd-10-91-2019, 2019
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Best estimates of future climate projections typically rely on a range of climate models from different international research institutions. However, it is unclear how independent these different estimates are, and, for example, the degree to which their agreement implies robustness. This work presents a review of the varied and disparate attempts to quantify and address model dependence within multi-model climate projection ensembles.
Nadja Herger, Gab Abramowitz, Reto Knutti, Oliver Angélil, Karsten Lehmann, and Benjamin M. Sanderson
Earth Syst. Dynam., 9, 135–151, https://doi.org/10.5194/esd-9-135-2018, https://doi.org/10.5194/esd-9-135-2018, 2018
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Users presented with large multi-model ensembles commonly use the equally weighted model mean as a best estimate, ignoring the issue of near replication of some climate models. We present an efficient and flexible tool that finds a subset of models with improved mean performance compared to the multi-model mean while at the same time maintaining the spread and addressing the problem of model interdependence. Out-of-sample skill and reliability are demonstrated using model-as-truth experiments.
Angeline G. Pendergrass, Andrew Conley, and Francis M. Vitt
Earth Syst. Sci. Data, 10, 317–324, https://doi.org/10.5194/essd-10-317-2018, https://doi.org/10.5194/essd-10-317-2018, 2018
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We document and validate radiative kernels for the surface and top-of-atmosphere calculated with NCAR's CESM1 climate model. A radiative kernel is the change in radiation in response to a small change in a property of the atmosphere or surface, essentially a partial derivative. They are used to quantify temperature, water vapor, surface albedo, and cloud feedbacks. We made these kernels because few are available for the surface. We also validate the kernels against the expected model responses.
Lukas Brunner and Andrea K. Steiner
Atmos. Meas. Tech., 10, 4727–4745, https://doi.org/10.5194/amt-10-4727-2017, https://doi.org/10.5194/amt-10-4727-2017, 2017
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Atmospheric blocking is a weather pattern where a stable high pressure system blocks the westerly flow at mid-latitudes. We provide, for the first time, a global perspective on blocking and related impacts, based on satellite observations from GPS radio occultation for 2006–2016. We find strong direct and remote effects on the vertical atmospheric structure revealing significant temperature and humidity anomalies up to 15 km. The observations will help for a better insight into blocking impacts.
Benjamin M. Sanderson, Yangyang Xu, Claudia Tebaldi, Michael Wehner, Brian O'Neill, Alexandra Jahn, Angeline G. Pendergrass, Flavio Lehner, Warren G. Strand, Lei Lin, Reto Knutti, and Jean Francois Lamarque
Earth Syst. Dynam., 8, 827–847, https://doi.org/10.5194/esd-8-827-2017, https://doi.org/10.5194/esd-8-827-2017, 2017
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We present the results of a set of climate simulations designed to simulate futures in which the Earth's temperature is stabilized at the levels referred to in the 2015 Paris Agreement. We consider the necessary future emissions reductions and the aspects of extreme weather which differ significantly between the 2 and 1.5 °C climate in the simulations.
Hendrik Andersen, Jan Cermak, Julia Fuchs, Reto Knutti, and Ulrike Lohmann
Atmos. Chem. Phys., 17, 9535–9546, https://doi.org/10.5194/acp-17-9535-2017, https://doi.org/10.5194/acp-17-9535-2017, 2017
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Aerosol-cloud interactions continue to contribute large uncertainties to our climate system understanding. In this study, we use near-global satellite and reanalysis data sets to predict marine liquid-water clouds by means of artificial neural networks. We show that on the system scale, lower-tropospheric stability and boundary layer height are the main determinants of liquid-water clouds. Aerosols show the expected impact on clouds but are less relevant than some meteorological factors.
Benjamin M. Sanderson, Michael Wehner, and Reto Knutti
Geosci. Model Dev., 10, 2379–2395, https://doi.org/10.5194/gmd-10-2379-2017, https://doi.org/10.5194/gmd-10-2379-2017, 2017
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How should climate model simulations be combined to produce an overall assessment that reflects both their performance and their interdependencies? This paper presents a strategy for weighting climate model output such that models that are replicated or models that perform poorly in a chosen set of metrics are appropriately weighted. We perform sensitivity tests to show how the method results depend on variables and parameter values.
Nathan P. Gillett, Hideo Shiogama, Bernd Funke, Gabriele Hegerl, Reto Knutti, Katja Matthes, Benjamin D. Santer, Daithi Stone, and Claudia Tebaldi
Geosci. Model Dev., 9, 3685–3697, https://doi.org/10.5194/gmd-9-3685-2016, https://doi.org/10.5194/gmd-9-3685-2016, 2016
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Detection and attribution of climate change is the process of determining the causes of observed climate changes, which has underpinned key conclusions on the role of human influence on climate in the reports of the Intergovernmental Panel on Climate Change (IPCC). This paper describes a coordinated set of climate model experiments that will form part of the Sixth Coupled Model Intercomparison Project and will support improved attribution of climate change in the next IPCC report.
Brian C. O'Neill, Claudia Tebaldi, Detlef P. van Vuuren, Veronika Eyring, Pierre Friedlingstein, George Hurtt, Reto Knutti, Elmar Kriegler, Jean-Francois Lamarque, Jason Lowe, Gerald A. Meehl, Richard Moss, Keywan Riahi, and Benjamin M. Sanderson
Geosci. Model Dev., 9, 3461–3482, https://doi.org/10.5194/gmd-9-3461-2016, https://doi.org/10.5194/gmd-9-3461-2016, 2016
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The Scenario Model Intercomparison Project (ScenarioMIP) will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. The design consists of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions. Climate model projections will facilitate integrated studies of climate change as well as address targeted scientific questions.
Lukas Brunner, Andrea K. Steiner, Barbara Scherllin-Pirscher, and Martin W. Jury
Atmos. Chem. Phys., 16, 4593–4604, https://doi.org/10.5194/acp-16-4593-2016, https://doi.org/10.5194/acp-16-4593-2016, 2016
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Atmospheric blocking refers to persistent high-pressure systems which block the climatological flow at midlatitudes. We explore blocking with observations from GPS radio occultation (RO), a satellite-based remote-sensing system. Using two example cases, we find that RO data robustly capture blocking, highlighting the potential of RO observations to complement models and reanalysis as a basis for blocking research.
Andrew H. MacDougall and Reto Knutti
Biogeosciences, 13, 2123–2136, https://doi.org/10.5194/bg-13-2123-2016, https://doi.org/10.5194/bg-13-2123-2016, 2016
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The soils of the permafrost region are estimated to hold 1100 to 1500 billion tonnes of carbon. As climate change progresses much of this permafrost is expected to thaw and the carbon within it decay. Here we conduct numerical experiments with a climate model to estimate with formal uncertainty bounds the release of carbon from permafrost soils. Our simulations suggest that the permafrost carbon will make a significant but not cataclysmic contribution to climate change over the next centuries.
J. Kala, M. G. De Kauwe, A. J. Pitman, R. Lorenz, B. E. Medlyn, Y.-P Wang, Y.-S Lin, and G. Abramowitz
Geosci. Model Dev., 8, 3877–3889, https://doi.org/10.5194/gmd-8-3877-2015, https://doi.org/10.5194/gmd-8-3877-2015, 2015
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We implement a new stomatal conductance scheme within a land surface model coupled to a global climate model. The new model differs from the default in that it allows model parameters to vary by the different plant functional types, derived from global synthesis of observations. We show that the new scheme results in improvements in the model climatology and improves existing biases in warm temperature extremes by up to 10-20% over the boreal forests during summer.
D. E. Keller, A. M. Fischer, C. Frei, M. A. Liniger, C. Appenzeller, and R. Knutti
Hydrol. Earth Syst. Sci., 19, 2163–2177, https://doi.org/10.5194/hess-19-2163-2015, https://doi.org/10.5194/hess-19-2163-2015, 2015
R. Lorenz, A. J. Pitman, M. G. Donat, A. L. Hirsch, J. Kala, E. A. Kowalczyk, R. M. Law, and J. Srbinovsky
Geosci. Model Dev., 7, 545–567, https://doi.org/10.5194/gmd-7-545-2014, https://doi.org/10.5194/gmd-7-545-2014, 2014
N. Schaller, J. Cermak, M. Wild, and R. Knutti
Earth Syst. Dynam., 4, 253–266, https://doi.org/10.5194/esd-4-253-2013, https://doi.org/10.5194/esd-4-253-2013, 2013
Related subject area
Earth system change: climate prediction
Past and future response of the North Atlantic warming hole to anthropogenic forcing
Performance-based sub-selection of CMIP6 models for impact assessments in Europe
Emergent constraints for the climate system as effective parameters of bulk differential equations
Ensemble forecast of an index of the Madden–Julian Oscillation using a stochastic weather generator based on circulation analogs
Reconstructions and predictions of the global carbon budget with an emission-driven Earth system model
PInc-PanTher estimates of Arctic permafrost soil carbon under the GeoMIP G6solar and G6sulfur experiments
El Niño–Southern Oscillation (ENSO) predictability in equilibrated warmer climates
Investigation of the extreme wet–cold compound events changes between 2025–2049 and 1980–2004 using regional simulations in Greece
Constraining low-frequency variability in climate projections to predict climate on decadal to multi-decadal timescales – a poor man's initialized prediction system
Resilience of UK crop yields to compound climate change
Evaluating uncertainty in aerosol forcing of tropical precipitation shifts
A non-stationary extreme-value approach for climate projection ensembles: application to snow loads in the French Alps
Atmospheric regional climate projections for the Baltic Sea region until 2100
Balanced estimate and uncertainty assessment of European climate change using the large EURO-CORDEX regional climate model ensemble
Extreme metrics from large ensembles: investigating the effects of ensemble size on their estimates
Reduced-complexity model for the impact of anthropogenic CO2 emissions on future glacial cycles
Is time a variable like the others in multivariate statistical downscaling and bias correction?
Trivial improvements in predictive skill due to direct reconstruction of the global carbon cycle
Abrupt climate change as a rate-dependent cascading tipping point
Bayesian estimation of Earth's climate sensitivity and transient climate response from observational warming and heat content datasets
Comparison of CMIP6 historical climate simulations and future projected warming to an empirical model of global climate
Assessment of a full-field initialized decadal climate prediction system with the CMIP6 version of EC-Earth
A new view of heat wave dynamics and predictability over the eastern Mediterranean
Emergent constraints on equilibrium climate sensitivity in CMIP5: do they hold for CMIP6?
Dating hiatuses: a statistical model of the recent slowdown in global warming and the next one
Calibrating large-ensemble European climate projections using observational data
Emergent constraints on transient climate response (TCR) and equilibrium climate sensitivity (ECS) from historical warming in CMIP5 and CMIP6 models
Multivariate bias corrections of climate simulations: which benefits for which losses?
Historical and future anthropogenic warming effects on droughts, fires and fire emissions of CO2 and PM2.5 in equatorial Asia when 2015-like El Niño events occur
The impact of regional climate model formulation and resolution on simulated precipitation in Africa
Bayesian deconstruction of climate sensitivity estimates using simple models: implicit priors and the confusion of the inverse
Intensification of the hydrological cycle expected in West Africa over the 21st century
Winter hydrometeorological extreme events modulated by large-scale atmospheric circulation in southern Ontario
Investigating ENSO and its teleconnections under climate change in an ensemble view – a new perspective
Human influence on European winter wind storms such as those of January 2018
September Arctic sea ice minimum prediction – a skillful new statistical approach
ESD Reviews: Model dependence in multi-model climate ensembles: weighting, sub-selection and out-of-sample testing
Predicting near-term variability in ocean carbon uptake
A mathematical approach to understanding emergent constraints
Seasonal prediction skill of East Asian summer monsoon in CMIP5 models
Assessing the impact of a future volcanic eruption on decadal predictions
Projections of East Asian summer monsoon change at global warming of 1.5 and 2 °C
Changes in extremely hot days under stabilized 1.5 and 2.0 °C global warming scenarios as simulated by the HAPPI multi-model ensemble
Regional scaling of annual mean precipitation and water availability with global temperature change
Irreversible ocean thermal expansion under carbon dioxide removal
Changes in tropical cyclones under stabilized 1.5 and 2.0 °C global warming scenarios as simulated by the Community Atmospheric Model under the HAPPI protocols
Selecting a climate model subset to optimise key ensemble properties
Return levels of temperature extremes in southern Pakistan
On the meaning of independence in climate science
Minimal change of thermal continentality in Slovakia within the period 1961–2013
Saïd Qasmi
Earth Syst. Dynam., 14, 685–695, https://doi.org/10.5194/esd-14-685-2023, https://doi.org/10.5194/esd-14-685-2023, 2023
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A new statistical method combining climate models and observations confirms the anthropogenic role in the cooling of the North Atlantic warming hole. Aerosols increase sea surface temperature (SST), while greenhouse gases contribute to the cooling over the 1870–2020 period. The method is able to reduce model uncertainty in the SST projections by 65% in the short term and up to 50% in the long term, excluding previous unlikely temperature increase scenarios.
Tamzin E. Palmer, Carol F. McSweeney, Ben B. B. Booth, Matthew D. K. Priestley, Paolo Davini, Lukas Brunner, Leonard Borchert, and Matthew B. Menary
Earth Syst. Dynam., 14, 457–483, https://doi.org/10.5194/esd-14-457-2023, https://doi.org/10.5194/esd-14-457-2023, 2023
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We carry out an assessment of an ensemble of general climate models (CMIP6) based on the ability of the models to represent the key physical processes that are important for representing European climate. Filtering the models with the assessment leads to more models with less global warming being removed, and this shifts the lower part of the projected temperature range towards greater warming. This is in contrast to the affect of weighting the ensemble using global temperature trends.
Chris Huntingford, Peter M. Cox, Mark S. Williamson, Joseph J. Clarke, and Paul D. L. Ritchie
Earth Syst. Dynam., 14, 433–442, https://doi.org/10.5194/esd-14-433-2023, https://doi.org/10.5194/esd-14-433-2023, 2023
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Emergent constraints (ECs) reduce the spread of projections between climate models. ECs estimate changes to climate features impacting adaptation policy, and with this high profile, the method is under scrutiny. Asking
What is an EC?, we suggest they are often the discovery of parameters that characterise hidden large-scale equations that climate models solve implicitly. We present this conceptually via two examples. Our analysis implies possible new paths to link ECs and physical processes.
Meriem Krouma, Riccardo Silini, and Pascal Yiou
Earth Syst. Dynam., 14, 273–290, https://doi.org/10.5194/esd-14-273-2023, https://doi.org/10.5194/esd-14-273-2023, 2023
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We present a simple system to forecast the Madden–Julian Oscillation (MJO). We use atmospheric circulation as input to our system. We found a good-skill forecast of the MJO amplitude within 40 d using this methodology. Comparing our results with ECMWF and machine learning forecasts confirmed the good skill of our system.
Hongmei Li, Tatiana Ilyina, Tammas Loughran, Aaron Spring, and Julia Pongratz
Earth Syst. Dynam., 14, 101–119, https://doi.org/10.5194/esd-14-101-2023, https://doi.org/10.5194/esd-14-101-2023, 2023
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For the first time, our decadal prediction system based on Max Planck Institute Earth System Model enables prognostic atmospheric CO2 with an interactive carbon cycle. The evolution of CO2 fluxes and atmospheric CO2 growth is reconstructed well by assimilating data products; retrospective predictions show high confidence in predicting changes in the next year. The Earth system predictions provide valuable inputs for understanding the global carbon cycle and informing climate-relevant policy.
Aobo Liu, John C. Moore, and Yating Chen
Earth Syst. Dynam., 14, 39–53, https://doi.org/10.5194/esd-14-39-2023, https://doi.org/10.5194/esd-14-39-2023, 2023
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Permafrost thaws and releases carbon (C) as the Arctic warms. Most earth system models (ESMs) have poor estimates of C stored now, so their future C losses are much lower than using the permafrost C model with climate inputs from six ESMs. Bias-corrected soil temperatures and plant productivity plus geoengineering lowering global temperatures from a no-mitigation baseline scenario to a moderate emissions level keep C in the soil worth about USD 0–70 (mean 20) trillion in climate damages by 2100.
Yiyu Zheng, Maria Rugenstein, Patrick Pieper, Goratz Beobide-Arsuaga, and Johanna Baehr
Earth Syst. Dynam., 13, 1611–1623, https://doi.org/10.5194/esd-13-1611-2022, https://doi.org/10.5194/esd-13-1611-2022, 2022
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El Niño–Southern Oscillation (ENSO) is one of the dominant climatic phenomena in the equatorial Pacific. Understanding and predicting how ENSO might change in a warmer climate is both societally and scientifically important. We use 1000-year-long simulations from seven climate models to analyze ENSO in an idealized stable climate. We show that ENSO will be weaker and last shorter under the warming, while the skill of ENSO prediction will unlikely change.
Iason Markantonis, Diamando Vlachogiannis, Athanasios Sfetsos, and Ioannis Kioutsioukis
Earth Syst. Dynam., 13, 1491–1504, https://doi.org/10.5194/esd-13-1491-2022, https://doi.org/10.5194/esd-13-1491-2022, 2022
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This work focuses on the study of daily wet–cold compound events in Greece in the period November–April. We firstly study the historic period 1980–2004 in which we validate projection models with observations. Then we compare the model results with future period 2025–2049 RCP4.5 and RCP8.5 scenarios. The aim of the study is to calculate the probability of the events and to locate the areas where those are higher and how the probabilities will change at the future.
Rashed Mahmood, Markus G. Donat, Pablo Ortega, Francisco J. Doblas-Reyes, Carlos Delgado-Torres, Margarida Samsó, and Pierre-Antoine Bretonnière
Earth Syst. Dynam., 13, 1437–1450, https://doi.org/10.5194/esd-13-1437-2022, https://doi.org/10.5194/esd-13-1437-2022, 2022
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Near-term climate change projections are strongly affected by the uncertainty from internal climate variability. Here we present a novel approach to reduce such uncertainty by constraining decadal-scale variability in the projections using observations. The constrained ensembles show significant added value over the unconstrained ensemble in predicting global climate 2 decades ahead. We also show the applicability of regional constraints for attributing predictability to certain ocean regions.
Louise J. Slater, Chris Huntingford, Richard F. Pywell, John W. Redhead, and Elizabeth J. Kendon
Earth Syst. Dynam., 13, 1377–1396, https://doi.org/10.5194/esd-13-1377-2022, https://doi.org/10.5194/esd-13-1377-2022, 2022
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This work considers how wheat yields are affected by weather conditions during the three main wheat growth stages in the UK. Impacts are strongest in years with compound weather extremes across multiple growth stages. Future climate projections are beneficial for wheat yields, on average, but indicate a high risk of unseen weather conditions which farmers may struggle to adapt to and mitigate against.
Amy H. Peace, Ben B. B. Booth, Leighton A. Regayre, Ken S. Carslaw, David M. H. Sexton, Céline J. W. Bonfils, and John W. Rostron
Earth Syst. Dynam., 13, 1215–1232, https://doi.org/10.5194/esd-13-1215-2022, https://doi.org/10.5194/esd-13-1215-2022, 2022
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Anthropogenic aerosol emissions have been linked to driving climate responses such as shifts in the location of tropical rainfall. However, the interaction of aerosols with climate remains one of the most uncertain aspects of climate modelling and limits our ability to predict future climate change. We use an ensemble of climate model simulations to investigate what impact the large uncertainty in how aerosols interact with climate has on predicting future tropical rainfall shifts.
Erwan Le Roux, Guillaume Evin, Nicolas Eckert, Juliette Blanchet, and Samuel Morin
Earth Syst. Dynam., 13, 1059–1075, https://doi.org/10.5194/esd-13-1059-2022, https://doi.org/10.5194/esd-13-1059-2022, 2022
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Anticipating risks related to climate extremes is critical for societal adaptation to climate change. In this study, we propose a statistical method in order to estimate future climate extremes from past observations and an ensemble of climate change simulations. We apply this approach to snow load data available in the French Alps at 1500 m elevation and find that extreme snow load is projected to decrease by −2.9 kN m−2 (−50 %) between 1986–2005 and 2080–2099 for a high-emission scenario.
Ole Bøssing Christensen, Erik Kjellström, Christian Dieterich, Matthias Gröger, and Hans Eberhard Markus Meier
Earth Syst. Dynam., 13, 133–157, https://doi.org/10.5194/esd-13-133-2022, https://doi.org/10.5194/esd-13-133-2022, 2022
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The Baltic Sea Region is very sensitive to climate change, whose impacts could easily exacerbate biodiversity stress from society and eutrophication of the Baltic Sea. Therefore, there has been a focus on estimations of future climate change and its impacts in recent research. Models show a strong warming, in particular in the north in winter. Precipitation is projected to increase in the whole region apart from the south during summer. New results improve estimates of future climate change.
Guillaume Evin, Samuel Somot, and Benoit Hingray
Earth Syst. Dynam., 12, 1543–1569, https://doi.org/10.5194/esd-12-1543-2021, https://doi.org/10.5194/esd-12-1543-2021, 2021
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This research paper proposes an assessment of mean climate change responses and related uncertainties over Europe for mean seasonal temperature and total seasonal precipitation. An advanced statistical approach is applied to a large ensemble of 87 high-resolution EURO-CORDEX projections. For the first time, we provide a comprehensive estimation of the relative contribution of GCMs and RCMs, RCP scenarios, and internal variability to the total variance of a very large ensemble.
Claudia Tebaldi, Kalyn Dorheim, Michael Wehner, and Ruby Leung
Earth Syst. Dynam., 12, 1427–1501, https://doi.org/10.5194/esd-12-1427-2021, https://doi.org/10.5194/esd-12-1427-2021, 2021
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We address the question of how large an initial condition ensemble of climate model simulations should be if we are concerned with accurately projecting future changes in temperature and precipitation extremes. We find that for most cases (and both models considered), an ensemble of 20–25 members is sufficient for many extreme metrics, spatial scales and time horizons. This may leave computational resources to tackle other uncertainties in climate model simulations with our ensembles.
Stefanie Talento and Andrey Ganopolski
Earth Syst. Dynam., 12, 1275–1293, https://doi.org/10.5194/esd-12-1275-2021, https://doi.org/10.5194/esd-12-1275-2021, 2021
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We propose a model for glacial cycles and produce an assessment of possible trajectories for the next 1 million years. Under natural conditions, the next glacial inception would most likely occur ∼50 kyr after present. We show that fossil-fuel CO2 releases can have an extremely long-term effect. Potentially achievable CO2 anthropogenic emissions during the next centuries will most likely provoke ice-free conditions in the Northern Hemisphere landmasses throughout the next half a million years.
Yoann Robin and Mathieu Vrac
Earth Syst. Dynam., 12, 1253–1273, https://doi.org/10.5194/esd-12-1253-2021, https://doi.org/10.5194/esd-12-1253-2021, 2021
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We propose a new multivariate downscaling and bias correction approach called
time-shifted multivariate bias correction, which aims to correct temporal dependencies in addition to inter-variable and spatial ones. Our method is evaluated in a
perfect model experimentcontext where simulations are used as pseudo-observations. The results show a large reduction of the biases in the temporal properties, while inter-variable and spatial dependence structures are still correctly adjusted.
Aaron Spring, István Dunkl, Hongmei Li, Victor Brovkin, and Tatiana Ilyina
Earth Syst. Dynam., 12, 1139–1167, https://doi.org/10.5194/esd-12-1139-2021, https://doi.org/10.5194/esd-12-1139-2021, 2021
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Numerical carbon cycle prediction models usually do not start from observed carbon states due to sparse observations. Instead, only physical climate is reconstructed, assuming that the carbon cycle follows indirectly. Here, we test in an idealized framework how well this indirect and direct reconstruction with perfect observations works. We find that indirect reconstruction works quite well and that improvements from the direct method are limited, strengthening the current indirect use.
Johannes Lohmann, Daniele Castellana, Peter D. Ditlevsen, and Henk A. Dijkstra
Earth Syst. Dynam., 12, 819–835, https://doi.org/10.5194/esd-12-819-2021, https://doi.org/10.5194/esd-12-819-2021, 2021
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Tipping of one climate subsystem could trigger a cascade of subsequent tipping points and even global-scale climate tipping. Sequential shifts of atmosphere, sea ice and ocean have been recorded in proxy archives of past climate change. Based on this we propose a conceptual model for abrupt climate changes of the last glacial. Here, rate-induced tipping enables tipping cascades in systems with relatively weak coupling. An early warning signal is proposed that may detect such a tipping.
Philip Goodwin and B. B. Cael
Earth Syst. Dynam., 12, 709–723, https://doi.org/10.5194/esd-12-709-2021, https://doi.org/10.5194/esd-12-709-2021, 2021
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Climate sensitivityis a key measure of how sensitive Earth's climate is to human release of greenhouse gasses, such as from fossil fuels. However, there is still uncertainty as to the value of climate sensitivity, in part because different climate feedbacks operate over multiple timescales. This study assesses hundreds of millions of climate simulations against historical observations to reduce uncertainty in climate sensitivity and future climate warming.
Laura A. McBride, Austin P. Hope, Timothy P. Canty, Brian F. Bennett, Walter R. Tribett, and Ross J. Salawitch
Earth Syst. Dynam., 12, 545–579, https://doi.org/10.5194/esd-12-545-2021, https://doi.org/10.5194/esd-12-545-2021, 2021
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We use a reduced-complexity climate model trained by observations to show that at the current rate of human release of CO2, total cumulative emissions will pass the 66 % likelihood of limiting warming to 1.5° or 2°C in about 10 and 35 years, respectively. We also show that complex climate models often used to guide policy tend to warm faster than observed over the past few decades. To achieve the Paris Climate Agreement, CO2 and CH4 emissions must be severely curtailed in the next decade.
Roberto Bilbao, Simon Wild, Pablo Ortega, Juan Acosta-Navarro, Thomas Arsouze, Pierre-Antoine Bretonnière, Louis-Philippe Caron, Miguel Castrillo, Rubén Cruz-García, Ivana Cvijanovic, Francisco Javier Doblas-Reyes, Markus Donat, Emanuel Dutra, Pablo Echevarría, An-Chi Ho, Saskia Loosveldt-Tomas, Eduardo Moreno-Chamarro, Núria Pérez-Zanon, Arthur Ramos, Yohan Ruprich-Robert, Valentina Sicardi, Etienne Tourigny, and Javier Vegas-Regidor
Earth Syst. Dynam., 12, 173–196, https://doi.org/10.5194/esd-12-173-2021, https://doi.org/10.5194/esd-12-173-2021, 2021
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This paper presents and evaluates a set of retrospective decadal predictions with the EC-Earth3 climate model. These experiments successfully predict past changes in surface air temperature but show poor predictive capacity in the subpolar North Atlantic, a well-known source region of decadal climate variability. The poor predictive capacity is linked to an initial shock affecting the Atlantic Ocean circulation, ultimately due to a suboptimal representation of the Labrador Sea density.
Assaf Hochman, Sebastian Scher, Julian Quinting, Joaquim G. Pinto, and Gabriele Messori
Earth Syst. Dynam., 12, 133–149, https://doi.org/10.5194/esd-12-133-2021, https://doi.org/10.5194/esd-12-133-2021, 2021
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Skillful forecasts of extreme weather events have a major socioeconomic relevance. Here, we compare two approaches to diagnose the predictability of eastern Mediterranean heat waves: one based on recent developments in dynamical systems theory and one leveraging numerical ensemble weather forecasts. We conclude that the former can be a useful and cost-efficient complement to conventional numerical forecasts for understanding the dynamics of eastern Mediterranean heat waves.
Manuel Schlund, Axel Lauer, Pierre Gentine, Steven C. Sherwood, and Veronika Eyring
Earth Syst. Dynam., 11, 1233–1258, https://doi.org/10.5194/esd-11-1233-2020, https://doi.org/10.5194/esd-11-1233-2020, 2020
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As an important measure of climate change, the Equilibrium Climate Sensitivity (ECS) describes the change in surface temperature after a doubling of the atmospheric CO2 concentration. Climate models from the Coupled Model Intercomparison Project (CMIP) show a wide range in ECS. Emergent constraints are a technique to reduce uncertainties in ECS with observational data. Emergent constraints developed with data from CMIP phase 5 show reduced skill and higher ECS ranges when applied to CMIP6 data.
J. Isaac Miller and Kyungsik Nam
Earth Syst. Dynam., 11, 1123–1132, https://doi.org/10.5194/esd-11-1123-2020, https://doi.org/10.5194/esd-11-1123-2020, 2020
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We augment an energy balance model with a novel measure of the oceans' multidecadal temperatures cycles to assess the contributions of model forcings and natural variability to the so-called hiatus in global warming. The model partially explains the recent slowdown and explains nearly all of the subsequent warming. The natural cycle suggests the possibility of a much longer hiatus over roughly 2023–2061.
Christopher H. O'Reilly, Daniel J. Befort, and Antje Weisheimer
Earth Syst. Dynam., 11, 1033–1049, https://doi.org/10.5194/esd-11-1033-2020, https://doi.org/10.5194/esd-11-1033-2020, 2020
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This study examines how the output of large single-model ensembles can be calibrated using observational data to provide improved future projections over Europe. Using an out-of-sample
imperfect modeltest, in which calibration techniques are applied to individual climate model realisations, these techniques are shown to generally improve the reliability of European climate projections for the next 40 years, particularly for regional surface temperature.
Femke J. M. M. Nijsse, Peter M. Cox, and Mark S. Williamson
Earth Syst. Dynam., 11, 737–750, https://doi.org/10.5194/esd-11-737-2020, https://doi.org/10.5194/esd-11-737-2020, 2020
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One of the key questions in climate science is how much more heating we will get for a given rise in carbon dioxide in the atmosphere. A new generation of models showed that this might be more than previously expected. Comparing the new models to observed temperature rise since 1970, we show that there is no need to revise the estimate upwards. Air pollution, whose effect on climate warming is poorly understood, stopped rising, allowing us to better constrain the greenhouse gas signal.
Bastien François, Mathieu Vrac, Alex J. Cannon, Yoann Robin, and Denis Allard
Earth Syst. Dynam., 11, 537–562, https://doi.org/10.5194/esd-11-537-2020, https://doi.org/10.5194/esd-11-537-2020, 2020
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Recently, multivariate bias correction (MBC) methods designed to adjust climate simulations have been proposed. However, they use different approaches, leading potentially to different results. Therefore, this study intends to intercompare four existing MBC methods to provide end users with aid in choosing such methods for their applications. To do so, a wide range of evaluation criteria have been used to assess the ability of MBC methods to correct statistical properties of climate models.
Hideo Shiogama, Ryuichi Hirata, Tomoko Hasegawa, Shinichiro Fujimori, Noriko N. Ishizaki, Satoru Chatani, Masahiro Watanabe, Daniel Mitchell, and Y. T. Eunice Lo
Earth Syst. Dynam., 11, 435–445, https://doi.org/10.5194/esd-11-435-2020, https://doi.org/10.5194/esd-11-435-2020, 2020
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Based on climate simulations, we suggested that historical warming increased chances of drought exceeding the severe 2015 event in equatorial Asia due to El Niño. The fire and fire emissions of CO2/PM2.5 will largely increase at 1.5 and 2 °C warming. If global warming reaches 3 °C, as is expected from the current mitigation policies, chances of fire and CO2/PM2.5 emissions exceeding the 2015 event become approximately 100 %. Future climate policy has to consider these climate change effects.
Minchao Wu, Grigory Nikulin, Erik Kjellström, Danijel Belušić, Colin Jones, and David Lindstedt
Earth Syst. Dynam., 11, 377–394, https://doi.org/10.5194/esd-11-377-2020, https://doi.org/10.5194/esd-11-377-2020, 2020
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Regional Climate Models constitute a downscaling tool to provide high-resolution data for impact and adaptation studies. However, there is no unique definition of the added value of downscaling as it depends on many factors. We investigate the impact of spatial resolution and model formulation on downscaled rainfall in Africa. Our results show that improvements in downscaled rainfall compared to the driving reanalysis are often related to model formulation and not always to higher resolution.
James D. Annan and Julia C. Hargreaves
Earth Syst. Dynam., 11, 347–356, https://doi.org/10.5194/esd-11-347-2020, https://doi.org/10.5194/esd-11-347-2020, 2020
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We explore the implicit assumptions that underlie many published probabilistic estimates of the equilibrium climate sensitivity – that is, the amount the climate will warm under a doubling of the atmospheric CO2 concentration. We demonstrate that many such estimates have made assumptions that would be difficult to justify and show how the calculations can be repeated in a more defensible manner. Our results show some significant differences from previous calculations.
Stella Todzo, Adeline Bichet, and Arona Diedhiou
Earth Syst. Dynam., 11, 319–328, https://doi.org/10.5194/esd-11-319-2020, https://doi.org/10.5194/esd-11-319-2020, 2020
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This study uses climate projections over West Africa to investigate the future changes in different aspects of its hydrological cycle. Over the 21st century, temperatures are expected to increase at a faster rate (+0.5 °C per decade) than the global average (+0.3 °C per decade), leading to an intensification of the hydrological cycle on average of +11 % per °C over the Sahel (more intense precipitation and longer dry spells) and +3 % per °C over the Guinea Coast (more intense precipitation).
Olivier Champagne, Martin Leduc, Paulin Coulibaly, and M. Altaf Arain
Earth Syst. Dynam., 11, 301–318, https://doi.org/10.5194/esd-11-301-2020, https://doi.org/10.5194/esd-11-301-2020, 2020
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Southern Ontario has seen more high flows in winter recently due to earlier snowmelt. We show that 10 mm of daily rain and temperature higher than 5 °C are necessary conditions to generate winter high flows in the historical period. These conditions are associated with high pressure on the east coast bringing warm and wet conditions from the south. In the future, as snowfall decreases, warm events will generate less high flows, while rainfall will become a greater high-flow contributor.
Tímea Haszpra, Mátyás Herein, and Tamás Bódai
Earth Syst. Dynam., 11, 267–280, https://doi.org/10.5194/esd-11-267-2020, https://doi.org/10.5194/esd-11-267-2020, 2020
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We investigate the changes in the ENSO phenomenon and the alterations of its precipitation-related teleconnections in the CESM-LE. To avoid the disadvantages of the subjective choices of traditional temporal methods, we use an ensemble-based snapshot framework providing instantaneous quantities computed over the ensemble dimension of the simulation. We find that ENSO teleconnections undergo considerable changes, and the ENSO amplitude remarkably increases by 2100.
Robert Vautard, Geert Jan van Oldenborgh, Friederike E. L. Otto, Pascal Yiou, Hylke de Vries, Erik van Meijgaard, Andrew Stepek, Jean-Michel Soubeyroux, Sjoukje Philip, Sarah F. Kew, Cecilia Costella, Roop Singh, and Claudia Tebaldi
Earth Syst. Dynam., 10, 271–286, https://doi.org/10.5194/esd-10-271-2019, https://doi.org/10.5194/esd-10-271-2019, 2019
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The effect of human activities on the probability of winter wind storms like the ones that occurred in Western Europe in January 2018 is analysed using multiple model ensembles. Despite a significant probability decline in observations, we find no significant change in probabilities due to human influence on climate so far. However, such extreme events are likely to be slightly more frequent in the future. The observed decrease in storminess is likely to be due to increasing roughness.
Monica Ionita, Klaus Grosfeld, Patrick Scholz, Renate Treffeisen, and Gerrit Lohmann
Earth Syst. Dynam., 10, 189–203, https://doi.org/10.5194/esd-10-189-2019, https://doi.org/10.5194/esd-10-189-2019, 2019
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Based on a simple statistical model we show that the September sea ice extent has a high predictive skill, up to 4 months ahead, based on previous months' oceanic and atmospheric conditions. Our statistical model skillfully captures the interannual variability of the September sea ice extent and could provide a valuable tool for identifying relevant regions and oceanic and atmospheric parameters that are important for the sea ice development in the Arctic.
Gab Abramowitz, Nadja Herger, Ethan Gutmann, Dorit Hammerling, Reto Knutti, Martin Leduc, Ruth Lorenz, Robert Pincus, and Gavin A. Schmidt
Earth Syst. Dynam., 10, 91–105, https://doi.org/10.5194/esd-10-91-2019, https://doi.org/10.5194/esd-10-91-2019, 2019
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Best estimates of future climate projections typically rely on a range of climate models from different international research institutions. However, it is unclear how independent these different estimates are, and, for example, the degree to which their agreement implies robustness. This work presents a review of the varied and disparate attempts to quantify and address model dependence within multi-model climate projection ensembles.
Nicole S. Lovenduski, Stephen G. Yeager, Keith Lindsay, and Matthew C. Long
Earth Syst. Dynam., 10, 45–57, https://doi.org/10.5194/esd-10-45-2019, https://doi.org/10.5194/esd-10-45-2019, 2019
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This paper shows that the absorption of carbon dioxide by the ocean is predictable several years in advance. This is important because fossil-fuel-derived carbon dioxide is largely responsible for anthropogenic global warming and because carbon dioxide emission management and global carbon cycle budgeting exercises can benefit from foreknowledge of ocean carbon absorption. The promising results from this new forecast system justify the need for additional oceanic observations.
Femke J. M. M. Nijsse and Henk A. Dijkstra
Earth Syst. Dynam., 9, 999–1012, https://doi.org/10.5194/esd-9-999-2018, https://doi.org/10.5194/esd-9-999-2018, 2018
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State-of-the-art climate models sometimes differ in their prediction of key aspects of climate change. The technique of
emergent constraintsuses observations of current climate to improve those predictions, using relationships between different climate models. Our paper first classifies the different uses of the technique, and continues with proposing a mathematical justification for their use. We also highlight when the application of emergent constraints might give biased predictions.
Bo Huang, Ulrich Cubasch, and Christopher Kadow
Earth Syst. Dynam., 9, 985–997, https://doi.org/10.5194/esd-9-985-2018, https://doi.org/10.5194/esd-9-985-2018, 2018
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We find that CMIP5 models show more significant improvement in predicting zonal winds with initialisation than without initialisation based on the knowledge that zonal wind indices can be used as potential predictors for the EASM. Given the initial conditions, two models improve the seasonal prediction skill of the EASM, while one model decreases it. The models have different responses to initialisation due to their ability to depict the EASM–ESNO coupled mode.
Sebastian Illing, Christopher Kadow, Holger Pohlmann, and Claudia Timmreck
Earth Syst. Dynam., 9, 701–715, https://doi.org/10.5194/esd-9-701-2018, https://doi.org/10.5194/esd-9-701-2018, 2018
Jiawei Liu, Haiming Xu, and Jiechun Deng
Earth Syst. Dynam., 9, 427–439, https://doi.org/10.5194/esd-9-427-2018, https://doi.org/10.5194/esd-9-427-2018, 2018
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A novel method based on
present–futurerelationship in observed climate and model-simulated future climate is applied to give more reliable projections of East Asian summer monsoon intensity and associated precipitation changes at 1.5 and 2 °C warming levels. Projected future changes suggest decreased precipitation over the Meiyu belt and increased precipitation over the high latitudes of East Asia and central China, together with a considerable weakening of EASM intensity.
Michael Wehner, Dáithí Stone, Dann Mitchell, Hideo Shiogama, Erich Fischer, Lise S. Graff, Viatcheslav V. Kharin, Ludwig Lierhammer, Benjamin Sanderson, and Harinarayan Krishnan
Earth Syst. Dynam., 9, 299–311, https://doi.org/10.5194/esd-9-299-2018, https://doi.org/10.5194/esd-9-299-2018, 2018
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The United Nations Framework Convention on Climate Change challenged the scientific community to describe the impacts of stabilizing the global temperature at its 21st Conference of Parties. A specific target of 1.5 °C above preindustrial levels had not been seriously considered by the climate modeling community prior to the Paris Agreement. This paper analyzes heat waves in simulations designed for this target. We find there are reductions in extreme temperature compared to a 2 °C target.
Peter Greve, Lukas Gudmundsson, and Sonia I. Seneviratne
Earth Syst. Dynam., 9, 227–240, https://doi.org/10.5194/esd-9-227-2018, https://doi.org/10.5194/esd-9-227-2018, 2018
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Assessing projected hydroclimatological changes is crucial, but associated with large uncertainties. We statistically assess here the response of precipitation and water availability to global temperature change, enabling us to estimate the significance of drying/wetting tendencies under anthropogenic climate change. We further show that opting for a 1.5 K warming target just slightly influences the mean response but could substantially reduce the risk of experiencing extreme changes.
Dana Ehlert and Kirsten Zickfeld
Earth Syst. Dynam., 9, 197–210, https://doi.org/10.5194/esd-9-197-2018, https://doi.org/10.5194/esd-9-197-2018, 2018
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This study uses a global climate model to explore the extent to which sea level rise due to thermal expansion of the ocean is reversible if the atmospheric concentration of carbon dioxide (CO2) declines. It is found that sea level continues to rise for several decades after atmospheric CO2 starts to decline and does not return to the pre-industrial level for over thousand years after atmospheric CO2 is restored to the pre-industrial concentration.
Michael F. Wehner, Kevin A. Reed, Burlen Loring, Dáithí Stone, and Harinarayan Krishnan
Earth Syst. Dynam., 9, 187–195, https://doi.org/10.5194/esd-9-187-2018, https://doi.org/10.5194/esd-9-187-2018, 2018
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The United Nations Framework Convention on Climate Change invited the scientific community to explore the impacts of a world in which anthropogenic global warming is stabilized at only 1.5 °C above preindustrial average temperatures. We present a projection of future tropical cyclone statistics for both 1.5 and 2.0 °C stabilized warming scenarios using a high-resolution global climate model. We find more frequent and intense tropical cyclones, but a reduction in weaker storms.
Nadja Herger, Gab Abramowitz, Reto Knutti, Oliver Angélil, Karsten Lehmann, and Benjamin M. Sanderson
Earth Syst. Dynam., 9, 135–151, https://doi.org/10.5194/esd-9-135-2018, https://doi.org/10.5194/esd-9-135-2018, 2018
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Users presented with large multi-model ensembles commonly use the equally weighted model mean as a best estimate, ignoring the issue of near replication of some climate models. We present an efficient and flexible tool that finds a subset of models with improved mean performance compared to the multi-model mean while at the same time maintaining the spread and addressing the problem of model interdependence. Out-of-sample skill and reliability are demonstrated using model-as-truth experiments.
Maida Zahid, Richard Blender, Valerio Lucarini, and Maria Caterina Bramati
Earth Syst. Dynam., 8, 1263–1278, https://doi.org/10.5194/esd-8-1263-2017, https://doi.org/10.5194/esd-8-1263-2017, 2017
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The southern part of Pakistan (Sindh province) has been exposed to frequent and intense temperature extremes recently and is highly vulnerable to their impacts due to lack of information on recurrence of extremes. In this paper for the first time we estimated the return levels of daily maximum temperatures and daily maximum wet-bulb temperatures over the different return periods in Sindh, which would help the local administrations to prioritize the regions in terms of adaptations.
James D. Annan and Julia C. Hargreaves
Earth Syst. Dynam., 8, 211–224, https://doi.org/10.5194/esd-8-211-2017, https://doi.org/10.5194/esd-8-211-2017, 2017
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The concept of independence has been frequently raised in climate science, but has rarely been defined and discussed in a theoretically robust and quantifiable manner. Improved understanding of this topic is critical to better understanding of climate change. In this paper, we introduce a unifying approach based on the statistical definition of independence, and illustrate with simple examples how it can be applied to practical questions.
Jozef Vilček, Jaroslav Škvarenina, Jaroslav Vido, Paulína Nalevanková, Radoslav Kandrík, and Jana Škvareninová
Earth Syst. Dynam., 7, 735–744, https://doi.org/10.5194/esd-7-735-2016, https://doi.org/10.5194/esd-7-735-2016, 2016
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Thermal continentality plays an important role not only in the basic characterisation of the climate in particular regions but also in the phytogeographic distribution of plants and ecosystem formation. Due to ongoing climate change, questions surrounding the changes of thermal continentality are very relevant. Our results show that the continentality of Slovakia increased in the period 1961 to 2013; however, this trend is not significant.
Cited articles
Abramowitz, G. and Bishop, C. H.: Climate model dependence and the ensemble
dependence transformation of CMIP projections, J. Climate, 28, 2332–2348,
https://doi.org/10.1175/JCLI-D-14-00364.1, 2015. a
Abramowitz, G., Herger, N., Gutmann, E., Hammerling, D., Knutti, R., Leduc, M., Lorenz, R., Pincus, R., and Schmidt, G. A.: ESD Reviews: Model dependence in multi-model climate ensembles: weighting, sub-selection and out-of-sample
testing, Earth Syst. Dynam., 10, 91–105, https://doi.org/10.5194/esd-10-91-2019, 2019. a
Amos, M., Young, P. J., Hosking, J. S., Lamarque, J.-F., Abraham, N. L., Akiyoshi, H., Archibald, A. T., Bekki, S., Deushi, M., Jöckel, P., Kinnison, D., Kirner, O., Kunze, M., Marchand, M., Plummer, D. A., Saint-Martin, D., Sudo, K., Tilmes, S., and Yamashita, Y.: Projecting ozone hole recovery using an ensemble of chemistry–climate models weighted by model performance and independence, Atmos. Chem. Phys., 20, 9961–9977, https://doi.org/10.5194/acp-20-9961-2020, 2020. a
Andrews, T., Andrews, M. B., Bodas-Salcedo, A., Jones, G. S., Kuhlbrodt, T.,
Manners, J., Menary, M. B., Ridley, J., Ringer, M. A., Sellar, A. A., Senior,
C. A., and Tang, Y.: Forcings, Feedbacks, and Climate Sensitivity in HadGEM3-GC3.1 and UKESM1, J. Adv. Model. Earth Syst., 11, 4377–4394, https://doi.org/10.1029/2019MS001866, 2019. a
Annan, J. D. and Hargreaves, J. C.: On the meaning of independence in climate
science, Earth Syst. Dynam., 8, 211–224, https://doi.org/10.5194/esd-8-211-2017, 2017. a
Bishop, C. H. and Abramowitz, G.: Climate model dependence and the replicate
Earth paradigm, Clim. Dynam., 41, 885–900, https://doi.org/10.1007/s00382-012-1610-y, 2013. a, b
Boé, J.: Interdependency in Multimodel Climate Projections: Component
Replication and Result Similarity, Geophys. Res. Lett., 45, 2771–2779, https://doi.org/10.1002/2017GL076829, 2018. a, b, c
Boé, J. and Terray, L.: Can metric-based approaches really improve
multi-model climate projections? The case of summer temperature change in
France, Clim. Dynam., 45, 1913–1928, https://doi.org/10.1007/s00382-014-2445-5, 2015. a, b
Brunner, L., Hauser, M., Lorenz, R., and Beyerle, U.: The ETH Zurich CMIP6
next generation archive: technical documentation, Zenodo, https://doi.org/10.5281/zenodo.3734128, 2020a. a
Brunner, L., McSweeney, C., Ballinger, A. P., Hegerl, G. C., Befort, D. J.,
O'Reilly, C., Benassi, M., Booth, B., Harris, G., Lowe, J., Coppola, E.,
Nogherotto, R., Knutti, R., Lenderink, G., de Vries, H., Qasmi, S., Ribes,
A., Stocchi, P., and Undorf, S.: Comparing methods to constrain future European climate projections using a consistent framework, J. Climate, 33, 8671–8692, https://doi.org/10.1175/jcli-d-19-0953.1, 2020b. a, b
Brunner, L., Lorenz, R., Merrifield, A. L., and Sedlacek, J.: Climate model Weighting by Independence and Performance (ClimWIP): Code Freeze for Brunner et al. (2020) ESD, Zenodo, https://doi.org/10.5281/zenodo.4073039, 2020. a
Chen, X., Guo, Z., Zhou, T., Li, J., Rong, X., Xin, Y., Chen, H., and Su, J.:
Climate Sensitivity and Feedbacks of a New Coupled Model CAMS-CSM to
Idealized CO2 Forcing: A Comparison with CMIP5 Models, J. Meteorol. Res., 33, 31–45, https://doi.org/10.1007/s13351-019-8074-5, 2019. a
Cowtan, K.: The Climate Data Guide: Global surface temperatures: BEST:
Berkeley Earth Surface Temperatures, available at: https://climatedataguide.ucar.edu/climate-data/global-surface-,
last access: 9 September 2019. a
C3S: ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global
climate, https://doi.org/10.24381/cds.f17050d7, 2017. a
Deser, C., Phillips, A., Bourdette, V., and Teng, H.: Uncertainty in climate
change projections: the role of internal variability, Clim. Dynam., 38, 527–546, https://doi.org/10.1007/s00382-010-0977-x, 2012. a
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016. a
Eyring, V., Cox, P. M., Flato, G. M., Gleckler, P. J., Abramowitz, G.,
Caldwell, P., Collins, W. D., Gier, B. K., Hall, A. D., Hoffman, F. M., Hurtt, G. C., Jahn, A., Jones, C. D., Klein, S. A., Krasting, J. P.,
Kwiatkowski, L., Lorenz, R., Maloney, E., Meehl, G. A., Pendergrass, A. G.,
Pincus, R., Ruane, A. C., Russell, J. L., Sanderson, B. M., Santer, B. D.,
Sherwood, S. C., Simpson, I. R., Stouffer, R. J., and Williamson, M. S.:
Taking climate model evaluation to the next level, Nat. Clim. Change, 9, 102–110, https://doi.org/10.1038/s41558-018-0355-y, 2019. a
Flato, G., Marotzke, J., Abiodun, B., Braconnot, P., Chou, S., Collins, W.,
Cox, P., Driouech, F., Emori, S., Eyring, V., Forest, C., Gleckler, P.,
Guilyardi, E., Jakob, C., Kattsov, V., Reason, C., and Rummukainen, M.:
Evaluation of Climate Models, in: Climate Change 2013: The Physical Science
Basis, Contribution of Working Group I to the Fifth Assess- ment Report of
the Intergovernmental Panel on Climate Change, edited by: Stocker, T., Qin,
D., Plattner, G.-K., Tignor, M., Allen, S., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P., Cambridge University Press, Cambridge, UK and New York, NY, USA, 2013. a
Forster, P. M., Maycock, A. C., McKenna, C. M., and Smith, C. J.: Latest
climate models confirm need for urgent mitigation, Nat. Clim. Change, 10, 7–10, https://doi.org/10.1038/s41558-019-0660-0, 2020. a, b
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs, L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan, K.,
Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A.,
da Silva, A. M., Gu, W., Kim, G. K., Koster, R., Lucchesi, R., Merkova, D.,
Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert,
S. D., Sienkiewicz, M., and Zhao, B.: The modern-era retrospective analysis
for research and applications, version 2 (MERRA-2), J. Climate, 30, 5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017. a
Gettelman, A., Hannay, C., Bacmeister, J. T., Neale, R. B., Pendergrass, A. G., Danabasoglu, G., Lamarque, J., Fasullo, J. T., Bailey, D. A., Lawrence, D. M., and Mills, M. J.: High Climate Sensitivity in the Community Earth
System Model Version 2 (CESM2), Geophys. Res. Lett., 46, 8329–8337, https://doi.org/10.1029/2019GL083978, 2019. a
Giorgi, F. and Coppola, E.: Does the model regional bias affect the projected
regional climate change? An analysis of global model projections: A letter,
Climatic Change, 100, 787–795, https://doi.org/10.1007/s10584-010-9864-z, 2010. a
Giorgi, F. and Mearns, L. O.: Calculation of average, uncertainty range, and
reliability of regional climate changes from AOGCM simulations via the
“Reliability Ensemble Averaging” (REA) method, J. Climate, 15, 1141–1158, https://doi.org/10.1175/1520-0442(2002)015<1141:COAURA>2.0.CO;2, 2002. a, b
Gleckler, P. J., Taylor, K. E., and Doutriaux, C.: Performance metrics for
climate models, J. Geophys. Res. Atmos., 113, 1–20, https://doi.org/10.1029/2007JD008972, 2008. a
GMAO: MERRA-2 tavg1_2d_slv_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Single-Level Diagnostics V5.12.4, available at: https://disc.gsfc.nasa.gov/api/jobs/results/ 5e7b68e9ed720b5795af914a (last access: 25 March 2020), 2015a. a
GMAO: MERRA-2 statD_2d_slv_Nx: 2d,Daily,Aggregated
Statistics,Single-Level,Assimilation,Single-Level Diagnostics V5.12.4,
available at: https://disc.gsfc.nasa.gov/api/jobs/results/ 5e7b648f4900ab500326d17e (last access: 25 March 2020), 2015b. a
Golaz, J. C., Caldwell, P. M., Van Roekel, L. P., Petersen, M. R., Tang, Q.,
Wolfe, J. D., Abeshu, G., Anantharaj, V., Asay-Davis, X. S., Bader, D. C.,
Baldwin, S. A., Bisht, G., Bogenschutz, P. A., Branstetter, M., Brunke, M. A., Brus, S. R., Burrows, S. M., Cameron-Smith, P. J., Donahue, A. S., Deakin, M., Easter, R. C., Evans, K. J., Feng, Y., Flanner, M., Foucar, J. G., Fyke, J. G., Griffin, B. M., Hannay, C., Harrop, B. E., Hoffman, M. J., Hunke, E. C., Jacob, R. L., Jacobsen, D. W., Jeffery, N., Jones, P. W., Keen, N. D., Klein, S. A., Larson, V. E., Leung, L. R., Li, H. Y., Lin, W., Lipscomb, W. H., Ma, P. L., Mahajan, S., Maltrud, M. E., Mametjanov, A., McClean, J. L., McCoy, R. B., Neale, R. B., Price, S. F., Qian, Y., Rasch, P. J., Reeves Eyre, J. E., Riley, W. J., Ringler, T. D., Roberts, A. F., Roesler, E. L., Salinger, A. G., Shaheen, Z., Shi, X., Singh, B., Tang, J., Taylor, M. A., Thornton, P. E., Turner, A. K., Veneziani, M., Wan, H., Wang, H., Wang, S., Williams, D. N., Wolfram, P. J., Worley, P. H., Xie, S., Yang, Y., Yoon, J. H., Zelinka, M. D., Zender, C. S., Zeng, X., Zhang, C., Zhang, K., Zhang, Y., Zheng, X., Zhou, T., and Zhu, Q.: The DOE E3SM Coupled Model Version 1: Overview and Evaluation at Standard Resolution, J. Adv. Model. Earth Syst., 11, 2089–2129, https://doi.org/10.1029/2018MS001603, 2019. a
Gutjahr, O., Putrasahan, D., Lohmann, K., Jungclaus, J. H., Von Storch, J. S., Brüggemann, N., Haak, H., and Stössel, A.: Max Planck Institute
Earth System Model (MPI-ESM1.2) for the High-Resolution Model Intercomparison
Project (HighResMIP), Geosci. Model Dev., 12, 3241–3281,
https://doi.org/10.5194/gmd-12-3241-2019, 2019. a
Hajima, T., Watanabe, M., Yamamoto, A., Tatebe, H., Noguchi, M. A., Abe, M., Ohgaito, R., Ito, A., Yamazaki, D., Okajima, H., Ito, A., Takata, K., Ogochi, K., Watanabe, S., and Kawamiya, M.: Development of the MIROC-ES2L Earth system model and the evaluation of biogeochemical processes and feedbacks, Geosci. Model Dev., 13, 2197–2244, https://doi.org/10.5194/gmd-13-2197-2020, 2020. a
Hawkins, E. and Sutton, R.: The Potential to Narrow Uncertainty in Regional
Climate Predictions, B. Am. Meteorol. Soc., 90, 1095–1108, https://doi.org/10.1175/2009BAMS2607.1, 2009. a, b
Herger, N., Abramowitz, G., Knutti, R., Angélil, O., Lehmann, K., and
Sanderson, B. M.: Selecting a climate model subset to optimise key ensemble
properties, Earth Syst. Dynam., 9, 135–151, https://doi.org/10.5194/esd-9-135-2018,
2018a. a, b
Herger, N., Angélil, O., Abramowitz, G., Donat, M., Stone, D., and Lehmann, K.: Calibrating Climate Model Ensembles for Assessing Extremes in a
Changing Climate, J. Geophys. Res.-Atmos., 123, 5988–6004, https://doi.org/10.1029/2018JD028549, 2018b. a
Hersbach, H.: Decomposition of the Continuous Ranked Probability Score for
Ensemble Prediction Systems, Weather Forecast., 15, 559–570,
https://doi.org/10.1175/1520-0434(2000)015<0559:DOTCRP>2.0.CO;2, 2000. a
IPCC: Climate Change 2013: The Physical Science Basis, in: Contribution of
Working Group I to the Fifth Assessment Report of the Intergovern- mental
Panel on Climate Change, Cambridge University Press, Cambridge, 2013. a
Jiménez-de-la Cuesta, D. and Mauritsen, T.: Emergent constraints on
Earth's transient and equilibrium response to doubled CO2 from post-1970s global warming, Nat. Geosc., 12, 902–905, https://doi.org/10.1038/s41561-019-0463-y, 2019. a, b
Kay, J. E., Deser, C., Phillips, A., Mai, A., Hannay, C., Strand, G.,
Arblaster, J. M., Bates, S. C., Danabasoglu, G., Edwards, J., Holland, M.,
Kushner, P., Lamarque, J. F., Lawrence, D., Lindsay, K., Middleton, A.,
Munoz, E., Neale, R., Oleson, K., Polvani, L., and Vertenstein, M.: The community earth system model (CESM) large ensemble project: A community
resource for studying climate change in the presence of internal climate
variability, B. Am. Meteorol. Soc., 96, 1333–1349, https://doi.org/10.1175/BAMS-D-13-00255.1, 2015. a, b
Knutti, R.: The end of model democracy?, Climatic Change, 102, 395–404,
https://doi.org/10.1007/s10584-010-9800-2, 2010. a
Knutti, R., Furrer, R., Tebaldi, C., Cermak, J., and Meehl, G. A.: Challenges
in combining projections from multiple climate models, J. Climate, 23, 2739–2758, https://doi.org/10.1175/2009JCLI3361.1, 2010. a, b
Knutti, R., Rugenstein, M. A., and Hegerl, G. C.: Beyond equilibrium climate
sensitivity, Nat. Geosci., 10, 727–736, https://doi.org/10.1038/NGEO3017, 2017a. a
Leduc, M., Laprise, R., de Elía, R., and Šeparović, L.: Is
institutional democracy a good proxy for model independence?, J. Climate, 29,
8301–8316, https://doi.org/10.1175/JCLI-D-15-0761.1, 2016. a
Lehner, F., Deser, C., Maher, N., Marotzke, J., Fischer, E. M., Brunner, L., Knutti, R., and Hawkins, E.: Partitioning climate projection uncertainty with multiple large ensembles and CMIP5/6, Earth Syst. Dynam., 11, 491–508, https://doi.org/10.5194/esd-11-491-2020, 2020. a
Liang, Y., Gillett, N. P., and Monahan, A. H.: Climate Model Projections of
21st Century Global Warming Constrained Using the Observed Warming Trend,
Geophys. Res. Lett., 47, 1–10, https://doi.org/10.1029/2019GL086757, 2020. a, b
Maher, N., Milinski, S., Suarez-Gutierrez, L., Botzet, M., Dobrynin, M.,
Kornblueh, L., Kröer, J., Takano, Y., Ghosh, R., Hedemann, C., Li, C.,
Li, H., Manzini, E., Notz, D., Putrasahan, D., Boysen, L., Claussen, M.,
Ilyina, T., Olonscheck, D., Raddatz, T., Stevens, B., and Marotzke, J.: The
Max Planck Institute Grand Ensemble: Enabling the Exploration of Climate
System Variability, J. Adv. Model. Earth Syst., 11, 2050–2069, https://doi.org/10.1029/2019MS001639, 2019. a, b
Mauritsen, T., Bader, J., Becker, T., Behrens, J., Bittner, M., Brokopf, R.,
Brovkin, V., Claussen, M., Crueger, T., Esch, M., Fast, I., Fiedler, S.,
Fläschner, D., Gayler, V., Giorgetta, M., Goll, D. S., Haak, H., Hagemann, S., Hedemann, C., Hohenegger, C., Ilyina, T., Jahns, T.,
Jimenéz-de-la Cuesta, D., Jungclaus, J., Kleinen, T., Kloster, S.,
Kracher, D., Kinne, S., Kleberg, D., Lasslop, G., Kornblueh, L., Marotzke,
J., Matei, D., Meraner, K., Mikolajewicz, U., Modali, K., Möbis, B.,
Müller, W. A., Nabel, J. E., Nam, C. C., Notz, D., Nyawira, S. S., Paulsen, H., Peters, K., Pincus, R., Pohlmann, H., Pongratz, J., Popp, M.,
Raddatz, T. J., Rast, S., Redler, R., Reick, C. H., Rohrschneider, T.,
Schemann, V., Schmidt, H., Schnur, R., Schulzweida, U., Six, K. D., Stein, L., Stemmler, I., Stevens, B., von Storch, J. S., Tian, F., Voigt, A., Vrese,
P., Wieners, K. H., Wilkenskjeld, S., Winkler, A., and Roeckner, E.: Developments in the MPI-M Earth System Model version 1.2 (MPI-ESM1.2) and
Its Response to Increasing CO2, J. Adv. Model. Earth Syst., 11, 998–1038, https://doi.org/10.1029/2018MS001400, 2019. a
Müllner, D.: Modern hierarchical, agglomerative clustering algorithms,
1–29, arxiv preprint: http://arxiv.org/abs/1109.2378 (last access: 6 April 2020), 2011. a
Nijsse, F. J. M. M., Cox, P. M., and Williamson, M. S.: Emergent constraints on transient climate response (TCR) and equilibrium climate sensitivity (ECS) from historical warming in CMIP5 and CMIP6 models, Earth Syst. Dynam., 11, 737–750, https://doi.org/10.5194/esd-11-737-2020, 2020. a, b, c, d, e, f
O'Neill, B. C., Kriegler, E., Riahi, K., Ebi, K. L., Hallegatte, S., Carter,
T. R., Mathur, R., and van Vuuren, D. P.: A new scenario framework for
climate change research: the concept of shared socioeconomic pathways, Climatic Change, 122, 387–400, https://doi.org/10.1007/s10584-013-0905-2, 2014. a
Pennell, C. and Reichler, T.: On the Effective Number of Climate Models, J.
Climate, 24, 2358–2367, https://doi.org/10.1175/2010JCLI3814.1, 2011. a
Ribes, A., Zwiers, F. W., Azaïs, J. M., and Naveau, P.: A new statistical approach to climate change detection and attribution, Clim. Dynam., 48, 367–386, https://doi.org/10.1007/s00382-016-3079-6, 2017. a
Sanderson, B. and Wehner, M.: Appendix B. Model Weighting Strategy, Forth
Natl. Clim. Assess., 1, 436–442, https://doi.org/10.7930/J06T0JS3, 2017. a
Sanderson, B. M., Knutti, R., and Caldwell, P.: A representative democracy to
reduce interdependency in a multimodel ensemble, J. Climate, 28, 5171–5194, https://doi.org/10.1175/JCLI-D-14-00362.1, 2015a. a
Sanderson, B. M., Knutti, R., and Caldwell, P.: Addressing interdependency in
a multimodel ensemble by interpolation of model properties, J. Climate, 28, 5150–5170, https://doi.org/10.1175/JCLI-D-14-00361.1, 2015b. a
Sanderson, B. M., Wehner, M., and Knutti, R.: Skill and independence weighting for multi-model assessments, Geosci. Model Dev., 10, 2379–2395, https://doi.org/10.5194/gmd-10-2379-2017, 2017. a, b, c
Selten, F. M., Bintanja, R., Vautard, R., and van den Hurk, B. J.: Future
continental summer warming constrained by the present-day seasonal cycle of
surface hydrology, Scient. Rep., 10, 1–7, https://doi.org/10.1038/s41598-020-61721-9, 2020. a
Semmler, T., Danilov, S., Gierz, P., Goessling, H., Hegewald, J., Hinrichs, C., Koldunov, N. V., Khosravi, N., Mu, L., and Rackow, T.: Simulations for CMIP6 with the AWI climate model AWI-CM-1-1, Earth Space Science Open Archive,
p. 48, https://doi.org/10.1002/essoar.10501538.1, 2019.
a
Sherwood, S., Webb, M. J., Annan, J. D., Armour, K. C., Forster, P. M.,
Hargreaves, J. C., Hegerl, G., Klein, S. A., Marvel, K. D., Rohling, E. J.,
Watanabe, M., Andrews, T., Braconnot, P., Bretherton, C. S., Foster, G. L.,
Hausfather, Z., von der Heydt, A. S., Knutti, R., Mauritsen, T., Norris, J. R., Proistosescu, C., Rugenstein, M., Schmidt, G. A., Tokarska, K. B., and
Zelinka, M. D.: An assessment of Earth's climate sensitivity using multiple
lines of evidence, Rev. Geophys., 58, 4, https://doi.org/10.1029/2019rg000678, 2020. a, b
Swart, N. C., Cole, J. N., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett, N. P., Anstey, J., Arora, V., Christian, J. R., Hanna, S., Jiao, Y., Lee, W. G., Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Sigmond, M., Solheim, L., Von Salzen, K., Yang, D., and Winter, B.: The Canadian Earth System Model version 5 (CanESM5.0.3), Geosci. Model Dev., 12, 4823–4873, https://doi.org/10.5194/gmd-12-4823-2019, 2019. a
Tatebe, H., Ogura, T., Nitta, T., Komuro, Y., Ogochi, K., Takemura, T., Sudo,
K., Sekiguchi, M., Abe, M., Saito, F., Chikira, M., Watanabe, S., Mori, M.,
Hirota, N., Kawatani, Y., Mochizuki, T., Yoshimura, K., Takata, K., O'Ishi,
R., Yamazaki, D., Suzuki, T., Kurogi, M., Kataoka, T., Watanabe, M., and
Kimoto, M.: Description and basic evaluation of simulated mean state, internal variability, and climate sensitivity in MIROC6, Geosci. Model Dev., 12, 2727–2765, https://doi.org/10.5194/gmd-12-2727-2019, 2019. a
Tebaldi, C. and Knutti, R.: The use of the multi-model ensemble in
probabilistic climate projections, Philos. T. Roy. Soc. A, 365, 2053–2075,
https://doi.org/10.1098/rsta.2007.2076, 2007. a
Tegegne, G., Kim, Y.-O., and Lee, J.-K.: Spatiotemporal reliability ensemble
averaging of multi‐model simulations, Geophys. Res. Lett., 46, 12321–12330, https://doi.org/10.1029/2019GL083053, 2019. a
van Vuuren, D. P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard,
K., Hurtt, G. C., Kram, T., Krey, V., Lamarque, J. F., Masui, T., Meinshausen, M., Nakicenovic, N., Smith, S. J., and Rose, S. K.: The
representative concentration pathways: An overview, Climatic Change, 109,
5–31, https://doi.org/10.1007/s10584-011-0148-z, 2011. a
Voldoire, A., Saint‐Martin, D., Sénési, S., Decharme, B., Alias, A., Chevallier, M., Colin, J., Guérémy, J., Michou, M., Moine, M., Nabat, P., Roehrig, R., Salas y Mélia, D., Séférian, R., Valcke, S., Beau, I., Belamari, S., Berthet, S., Cassou, C., Cattiaux, J., Deshayes, J., Douville, H., Ethé, C., Franchistéguy, L., Geoffroy, O., Lévy, C., Madec, G., Meurdesoif, Y., Msadek, R., Ribes, A., Sanchez‐Gomez, E., Terray, L., and Waldman, R.: Evaluation of CMIP6 DECK Experiments With CNRM‐CM6‐1, J. Adv. Model. Earth Syst., 11, 2177–2213, https://doi.org/10.1029/2019MS001683, 2019. a
Yang, Y.-M., Wang, B., Cao, J., Ma, L., and Li, J.: Improved historical
simulation by enhancing moist physical parameterizations in the climate system model NESM3.0, Clim. Dynam., 54, 3819–3840,
https://doi.org/10.1007/s00382-020-05209-2, 2020.
a
Yukimoto, S., Kawai, H., Koshiro, T., Oshima, N., Yoshida, K., Urakawa, S.,
Tsujino, H., Deushi, M., Tanaka, T., Hosaka, M., Yabu, S., Yoshimura, H.,
Shindo, E., Mizuta, R., Obata, A., Adachi, Y., and Ishii, M.: The
meteorological research institute Earth system model version 2.0, MRI-ESM2.0:
Description and basic evaluation of the physical component, J. Meteorol. Soc. Jpn., 97, 931–965, https://doi.org/10.2151/jmsj.2019-051, 2019.
a
Zelinka, M. D., Myers, T. A., McCoy, D. T., Po‐Chedley, S., Caldwell, P. M.,
Ceppi, P., Klein, S. A., and Taylor, K. E.: Causes of Higher Climate
Sensitivity in CMIP6 Models, Geophys. Res. Lett., 47, 1–12,
https://doi.org/10.1029/2019GL085782, 2020. a, b
Short summary
In this study, we weight climate models by their performance with respect to simulating aspects of historical climate and their degree of interdependence. Our method is found to increase projection skill and to correct for structurally similar models. The weighted end-of-century mean warming (2081–2100 relative to 1995–2014) is 3.7 °C with a likely (66 %) range of 3.1 to 4.6 °C for the strong climate change scenario SSP5-8.5; this is a reduction of 0.4 °C compared with the unweighted mean.
In this study, we weight climate models by their performance with respect to simulating aspects...
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