Earth System Model Evaluation Tool (ESMValTool) v2.0 - An extended set of large-scale diagnostics for quasi-operational and comprehensive evaluation of Earth system models in CMIP
German Aerospace Center1, University of Bremen2, University of Turin3, Barcelona Supercomputing Center4, Max Planck Society5, Universidade Nova de Lisboa6, ENEA7, ETH Zurich8, Plymouth Marine Laboratory9, National Center for Atmospheric Research10, Swedish Meteorological and Hydrological Institute11, Met Office12, University of Arizona13, Free University of Berlin14, Alfred Wegener Institute for Polar and Marine Research15, University of Hamburg16, Central Maine Community College17, University of Reading18, Université catholique de Louvain19, Ludwig Maximilian University of Munich20, Polytechnic University of Turin21
TL;DR: Large-scale diagnostics of the second major release of the ESMValTool tool, a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of Earth system models participating in the Coupled Model Intercomparison Project (CMIP), are described.
Abstract: This research has been supported by Horizon 2020 (grant nos. 641816, 727862, 641727, and 824084), the Copernicus Climate Change Service (C3S) (Metrics and Access to Global Indices for Climate Projections, MAGIC), the Helmholtz Association (Advanced Earth System Model Evaluation for CMIP, EVal4CMIP), the Deutsche Forschungsgemeinschaft (grant no. 274762653), the Federal Ministry of Education and Research (BMBF) (grant no. CMIP6-DICAD), and the European Space Agency (ESA Climate Change Initiative Climate Model User Group, ESA CCI CMUG).
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01 Dec 2012
Abstract: We upscaled FLUXNET observations of carbon dioxide, water, and energy fluxes to the global scale using the machine learning technique, model tree ensembles (MTE). We trained MTE to predict site-level gross primary productivity (GPP), terrestrial ecosystem respiration (TER), net ecosystem exchange (NEE), latent energy (LE), and sensible heat (H) based on remote sensing indices, climate and meteorological data, and information on land use. We applied the trained MTEs to generate global flux fields at a 0.5 degrees x 0.5 degrees spatial resolution and a monthly temporal resolution from 1982 to 2008. Cross-validation analyses revealed good performance of MTE in predicting among-site flux variability with modeling efficiencies (MEf) between 0.64 and 0.84, except for NEE (MEf = 0.32). Performance was also good for predicting seasonal patterns (MEf between 0.84 and 0.89, except for NEE (0.64)). By comparison, predictions of monthly anomalies were not as strong (MEf between 0.29 and 0.52). Improved accounting of disturbance and lagged environmental effects, along with improved characterization of errors in the training data set, would contribute most to further reducing uncertainties. Our global estimates of LE (158 +/- 7 J x 10(18) yr(-1)), H (164 +/- 15 J x 10(18) yr(-1)), and GPP (119 +/- 6 Pg C yr(-1)) were similar to independent estimates. Our global TER estimate (96 +/- 6 Pg C yr(-1)) was likely underestimated by 5-10%. Hot spot regions of interannual variability in carbon fluxes occurred in semiarid to semihumid regions and were controlled by moisture supply. Overall, GPP was more important to interannual variability in NEE than TER. Our empirically derived fluxes may be used for calibration and evaluation of land surface process models and for exploratory and diagnostic assessments of the biosphere.
948 citations
National Center for Atmospheric Research1, University of Colorado Boulder2, Utrecht University3, Brown University4, Cooperative Institute for Research in Environmental Sciences5, University of Toronto6, University of Wisconsin–Milwaukee7, University of California, Irvine8, Columbia University9, Pacific Northwest National Laboratory10
TL;DR: The Community Earth System Model Version 2 (CESM2) as discussed by the authors is the most recent version of the Coupled Model Intercomparison Project (CMEI) coupled model.
Abstract: An overview of the Community Earth System Model Version 2 (CESM2) is provided, including a discussion of the challenges encountered during its development and how they were addressed. In addition, an evaluation of a pair of CESM2 long preindustrial control and historical ensemble simulations is presented. These simulations were performed using the nominal 1° horizontal resolution configuration of the coupled model with both the “low-top” (40 km, with limited chemistry) and “high-top” (130 km, with comprehensive chemistry) versions of the atmospheric component. CESM2 contains many substantial science and infrastructure improvements and new capabilities since its previous major release, CESM1, resulting in improved historical simulations in comparison to CESM1 and available observations. These include major reductions in low-latitude precipitation and shortwave cloud forcing biases; better representation of the Madden-Julian Oscillation; better El Nino-Southern Oscillation-related teleconnections; and a global land carbon accumulation trend that agrees well with observationally based estimates. Most tropospheric and surface features of the low- and high-top simulations are very similar to each other, so these improvements are present in both configurations. CESM2 has an equilibrium climate sensitivity of 5.1–5.3 °C, larger than in CESM1, primarily due to a combination of relatively small changes to cloud microphysics and boundary layer parameters. In contrast, CESM2's transient climate response of 1.9–2.0 °C is comparable to that of CESM1. The model outputs from these and many other simulations are available to the research community, and they represent CESM2's contributions to the Coupled Model Intercomparison Project Phase 6.
884 citations
01 Dec 2012
TL;DR: In this paper, the magnitude and evolution of parameters that characterize feedbacks in the coupled carbon-climate system are compared across nine Earth system models (ESMs), based on results from biogeochemically, radiatively, and fully coupled simulations in which CO2 increases at a rate of 1% yr−1.
Abstract: The magnitude and evolution of parameters that characterize feedbacks in the coupled carbon–climate system are compared across nine Earth system models (ESMs). The analysis is based on results from biogeochemically, radiatively, and fully coupled simulations in which CO2 increases at a rate of 1% yr−1. These simulations are part of phase 5 of the Coupled Model Intercomparison Project (CMIP5). The CO2 fluxes between the atmosphere and underlying land and ocean respond to changes in atmospheric CO2 concentration and to changes in temperature and other climate variables. The carbon–concentration and carbon–climate feedback parameters characterize the response of the CO2 flux between the atmosphere and the underlying surface to these changes. Feedback parameters are calculated using two different approaches. The two approaches are equivalent and either may be used to calculate the contribution of the feedback terms to diagnosed cumulative emissions. The contribution of carbon–concentration feedback to...
454 citations
TL;DR: Cloud feedbacks and cloud-aerosol interactions are the most likely contributors to the high values and increased range of ECS in CMIP6.
Abstract: For the current generation of earth system models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6), the range of equilibrium climate sensitivity (ECS, a hypothetical value of global warming at equilibrium for a doubling of CO2) is 18°C to 56°C, the largest of any generation of models dating to the 1990s Meanwhile, the range of transient climate response (TCR, the surface temperature warming around the time of CO2 doubling in a 1% per year CO2 increase simulation) for the CMIP6 models of 17°C (13°C to 30°C) is only slightly larger than for the CMIP3 and CMIP5 models Here we review and synthesize the latest developments in ECS and TCR values in CMIP, compile possible reasons for the current values as supplied by the modeling groups, and highlight future directions Cloud feedbacks and cloud-aerosol interactions are the most likely contributors to the high values and increased range of ECS in CMIP6
297 citations
Joint Global Change Research Institute1, German Aerospace Center2, University of Bremen3, ETH Zurich4, École Polytechnique5, University of Exeter6, University of Leeds7, Met Office8, University of Denver9, Centre national de la recherche scientifique10, Netherlands Environmental Assessment Agency11, International Institute for Applied Systems Analysis12, University of Melbourne13, University of Maryland, College Park14, Potsdam Institute for Climate Impact Research15, National Center for Atmospheric Research16, Goddard Institute for Space Studies17, University of Paris18, Max Planck Society19, University of Hamburg20, Korea Meteorological Administration21, Commonwealth Scientific and Industrial Research Organisation22, Central Maine Community College23, Geophysical Fluid Dynamics Laboratory24, Korean Ocean Research and Development Institute25, Pukyong National University26, Nanjing University of Information Science and Technology27, Norwegian Meteorological Institute28, Indian Institute of Tropical Meteorology29, Ontario Ministry of Natural Resources30, University of Toulouse31, Alfred Wegener Institute for Polar and Marine Research32, Oak Ridge National Laboratory33, Deutscher Wetterdienst34, University of Arizona35, Japan Agency for Marine-Earth Science and Technology36, Lawrence Livermore National Laboratory37, Swedish Meteorological and Hydrological Institute38, China Meteorological Administration39, Danish Meteorological Institute40, Chinese Academy of Sciences41
TL;DR: In this paper, the authors present a range of its outcomes by synthesizing results from the participating global coupled Earth system models for concentration driven simulations, focusing mainly on the analysis of strictly geophysical outcomes: mainly global averages and spatial patterns of change for surface air temperature and precipitation.
Abstract: . The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the primary future climate projections within the Coupled Model Intercomparison Project Phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models for concentration driven simulations. We limit our scope to the analysis of strictly geophysical outcomes: mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century encompassing the Tier 1 experiments (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by 1.15 °C) reached at the upper end of the 5–95 % envelope of the highest scenario, SSP5-8.5. This is due to both the wider range of radiative forcing that the new scenarios cover and to higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensembles' spread, according to a set of initial condition ensemble simulations available under SSP3-7.0. The same experiments suggest a tendency for internal variability to decrease along the course of the century, a new result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP, but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades in mid-century, as represented in SSP5-3.4OS, does not affect the end outcome in terms of temperature and precipitation changes by 2100, which return to the same level as those reached by the gradually increasing SSP4-3.4. Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level show all scenarios reaching 1.5 °C of warming compared to the 1850–1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering 20–28 years from present. 2 °C of warming is reached as early as the late '30s by the ensemble mean under SSP5-8.5, but as late as the late '50s under SSP1-2.6. The highest warming level considered, 5 °C, is reached only by the ensemble mean under SSP5-8.5, and not until the mid-90s.
190 citations
References
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TL;DR: The NCEP/NCAR 40-yr reanalysis uses a frozen state-of-the-art global data assimilation system and a database as complete as possible, except that the horizontal resolution is T62 (about 210 km) as discussed by the authors.
Abstract: The NCEP and NCAR are cooperating in a project (denoted “reanalysis”) to produce a 40-year record of global analyses of atmospheric fields in support of the needs of the research and climate monitoring communities. This effort involves the recovery of land surface, ship, rawinsonde, pibal, aircraft, satellite, and other data; quality controlling and assimilating these data with a data assimilation system that is kept unchanged over the reanalysis period 1957–96. This eliminates perceived climate jumps associated with changes in the data assimilation system. The NCEP/NCAR 40-yr reanalysis uses a frozen state-of-the-art global data assimilation system and a database as complete as possible. The data assimilation and the model used are identical to the global system implemented operationally at the NCEP on 11 January 1995, except that the horizontal resolution is T62 (about 210 km). The database has been enhanced with many sources of observations not available in real time for operations, provided b...
28,145 citations
TL;DR: ERA-Interim as discussed by the authors is the latest global atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF), which will extend back to the early part of the twentieth century.
Abstract: ERA-Interim is the latest global atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). The ERA-Interim project was conducted in part to prepare for a new atmospheric reanalysis to replace ERA-40, which will extend back to the early part of the twentieth century. This article describes the forecast model, data assimilation method, and input datasets used to produce ERA-Interim, and discusses the performance of the system. Special emphasis is placed on various difficulties encountered in the production of ERA-40, including the representation of the hydrological cycle, the quality of the stratospheric circulation, and the consistency in time of the reanalysed fields. We provide evidence for substantial improvements in each of these aspects. We also identify areas where further work is needed and describe opportunities and objectives for future reanalysis projects at ECMWF. Copyright © 2011 Royal Meteorological Society
22,055 citations
TL;DR: The fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the- art multimodel dataset designed to advance the authors' knowledge of climate variability and climate change.
Abstract: The fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the- art multimodel dataset designed to advance our knowledge of climate variability and climate change. Researchers worldwide are analyzing the model output and will produce results likely to underlie the forthcoming Fifth Assessment Report by the Intergovernmental Panel on Climate Change. Unprecedented in scale and attracting interest from all major climate modeling groups, CMIP5 includes “long term” simulations of twentieth-century climate and projections for the twenty-first century and beyond. Conventional atmosphere–ocean global climate models and Earth system models of intermediate complexity are for the first time being joined by more recently developed Earth system models under an experiment design that allows both types of models to be compared to observations on an equal footing. Besides the longterm experiments, CMIP5 calls for an entirely new suite of “near term” simulations focusing on recent decades...
12,384 citations
"Earth System Model Evaluation Tool ..." refers background or methods in this paper
...Standardization of model output in a common format (Juckes et al., 2020) and publication of the CMIP model output on the Earth System Grid Federation (ESGF) facilitates multi-model evaluation and analysis (Balaji et al., 2018; Eyring et al., 2016a; Taylor et al., 2012)....
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..., 2020) and publication of the CMIP model output on the Earth System Grid Federation (ESGF) facilitates multi-model evaluation and analysis (Balaji et al., 2018; Eyring et al., 2016a; Taylor et al., 2012)....
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...Simulations with climate and Earth system models (ESMs) performed by the major climate modelling centres around the world under common protocols have been coordinated as part of the World Climate Research Programme (WCRP) Coupled Model Intercomparison Project (CMIP) since the early 90s (Eyring et al., 2016a; Meehl et al., 2000, 2007; Taylor et al., 2012)....
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...…by the major climate modelling centres around the world under common protocols have been coordinated as part of the World Climate Research Programme (WCRP) Coupled Model Intercomparison Project (CMIP) since the early 90s (Eyring et al., 2016a; Meehl et al., 2000, 2007; Taylor et al., 2012)....
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TL;DR: HadISST1 as mentioned in this paper replaces the global sea ice and sea surface temperature (GISST) data sets and is a unique combination of monthly globally complete fields of SST and sea ice concentration on a 1° latitude-longitude grid from 1871.
Abstract: [1] We present the Met Office Hadley Centre's sea ice and sea surface temperature (SST) data set, HadISST1, and the nighttime marine air temperature (NMAT) data set, HadMAT1. HadISST1 replaces the global sea ice and sea surface temperature (GISST) data sets and is a unique combination of monthly globally complete fields of SST and sea ice concentration on a 1° latitude-longitude grid from 1871. The companion HadMAT1 runs monthly from 1856 on a 5° latitude-longitude grid and incorporates new corrections for the effect on NMAT of increasing deck (and hence measurement) heights. HadISST1 and HadMAT1 temperatures are reconstructed using a two-stage reduced-space optimal interpolation procedure, followed by superposition of quality-improved gridded observations onto the reconstructions to restore local detail. The sea ice fields are made more homogeneous by compensating satellite microwave-based sea ice concentrations for the impact of surface melt effects on retrievals in the Arctic and for algorithm deficiencies in the Antarctic and by making the historical in situ concentrations consistent with the satellite data. SSTs near sea ice are estimated using statistical relationships between SST and sea ice concentration. HadISST1 compares well with other published analyses, capturing trends in global, hemispheric, and regional SST well, containing SST fields with more uniform variance through time and better month-to-month persistence than those in GISST. HadMAT1 is more consistent with SST and with collocated land surface air temperatures than previous NMAT data sets.
8,958 citations
"Earth System Model Evaluation Tool ..." refers background in this paper
...Model Dev., 13, 3383–3438, 2020 to one standard observational dataset, namely the SST part of the Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) (Rayner et al., 2003) dataset....
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...…va ua hus tas psl hfds tauu tauv ERA-Interim (Tier 3; Dee et al., 2011) pr GPCP-SG (Tier 1; Adler et al., 2003) tos sic HadISST (Tier 2; Rayner et al., 2003) recipe_autoassess_ *.yml 3.1.2.4 Recipe for mix of top–down metrics evaluating key model output variables and bottom–up metrics.…...
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...…06_collect.ncl ipcc_ar5/ch09_ fig09_14.py tas ERA-Interim (Tier 3; Dee et al., 2011) HadCRUT4 (Tier 2; Morice et al., 2012) tos HadISST (Tier 2; Rayner et al., 2003) swcre lwcre netcre rlut CERES-EBAF (Tier 2; Loeb et al., 2018) pr GPCP-SG (Tier 1; Adler et al., 2003) recipe_…...
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...…the Arctic and Antarctic. seaice/SeaIce_ancyc.ncl seaice/SeaIce_tsline.ncl seaice/SeaIce_polcon.ncl seaice/SeaIce_polcon_diff.ncl sic HadISST (Tier 2; Rayner et al., 2003) Section 3.4: Detection of systematic biases in the physical climate: land recipe_landcover.yml 3.4.1 Recipe for plotting the…...
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...…2014) lai LAI3g (Tier 3; Zhu et al., 2013) fgco2 nbp JMA-TRANSCOM (Tier 2; Maki et al., 2017); GCP (Tier 2; Le Quéré et al., 2018) tos HadISST (Tier 2; Rayner et al., 2003) gpp MTE (Tier 2; Jung et al., 2011) cSoil HWSD (Tier 2; Wieder, 2014) cVeg NDP (Tier 2; Gibbs,…...
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TL;DR: In this article, the authors identify a robust, recurring pattern of ocean-atmosphere climate variability centered over the midlatitude North Pacific basin over the past century, the amplitude of this climate pattern has varied irregularly at interannual-to-interdecadal timescales.
Abstract: Evidence gleaned from the instrumental record of climate data identifies a robust, recurring pattern of ocean–atmosphere climate variability centered over the midlatitude North Pacific basin. Over the past century, the amplitude of this climate pattern has varied irregularly at interannual-to-interdecadal timescales. There is evidence of reversals in the prevailing polarity of the oscillation occurring around 1925, 1947, and 1977; the last two reversals correspond to dramatic shifts in salmon production regimes in the North Pacific Ocean. This climate pattern also affects coastal sea and continental surface air temperatures, as well as streamflow in major west coast river systems, from Alaska to California.
6,719 citations
"Earth System Model Evaluation Tool ..." refers background in this paper
...…evaluation of the major modes of climate variability, including ENSO (Deser et al., 2010), the Pacific Decadal Oscillation (PDO; Deser et al., 2010; Mantua et al., 1997), the Atlantic Multi-decadal Oscillation (AMO; Trenberth and Shea, 2006), the Atlantic Meridional Overturning Circulation (AMOC;…...
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