scholarly journals Simulations of the Mid-Pliocene Warm Period using the NASA/GISS ModelE2-R Earth System Model

2012 ◽  
Vol 5 (3) ◽  
pp. 2811-2842 ◽  
Author(s):  
M. A. Chandler ◽  
L. E. Sohl ◽  
J. A. Jonas ◽  
H. J. Dowsett
Keyword(s):  
North Atlantic ◽  
Climate Models ◽  
Climate Model ◽  
Geographic Region ◽  
Earth System Model ◽  
Warm Period ◽  
System Model ◽  
Earth System ◽  
Intergovernmental Panel ◽  
Future Global Warming

Abstract. Climate reconstructions of the mid-Pliocene Warm Period (mPWP) bear many similarities to aspects of future global warming as projected by the Intergovernmental Panel on Climate Change. In particular, marine and terrestrial paleoclimate data point to high latitude temperature amplification, with associated decreases in sea ice and land ice and altered vegetation distributions that show expansion of warmer climate biomes into higher latitudes. NASA GISS climate models have been used to study the Pliocene climate since the USGS PRISM project first identified that the mid-Pliocene North Atlantic sea surface temperatures were anomalously warm. Here we present the most recent simulations of the Pliocene using the AR5/CMIP5 version of the GISS Earth System Model known as ModelE2-R. These simulations constitute the NASA contribution to the Pliocene Model Intercomparison Project (PlioMIP) Experiment 2. Many findings presented here corroborate results from other PlioMIP multi-model ensemble papers, but we also emphasize features in the ModelE2-R simulations that are unlike the ensemble means. We provide discussion of features that show considerable improvement compared with simulations from previous versions of the NASA GISS models, improvement defined here as simulation results that more closely resemble the ocean core data as well as the PRISM3D reconstructions of the mid-Pliocene climate. In some regions even qualitative agreement between model results and paleodata are an improvement over past studies, but the dramatic warming in the North Atlantic and Greenland-Iceland-Norwegian Sea in these new simulations is by far the most accurate portrayal ever of this key geographic region by the GISS climate model. Our belief is that continued development of key physical routines in the atmospheric model, along with higher resolution and recent corrections to mixing parameterizations in the ocean model, have led to an Earth System Model that will produce more accurate projections of future climate.

scholarly journals Simulations of the mid-Pliocene Warm Period using two versions of the NASA/GISS ModelE2-R Coupled Model

2013 ◽  
Vol 6 (2) ◽  
pp. 517-531 ◽  
Author(s):  
M. A. Chandler ◽  
L. E. Sohl ◽  
J. A. Jonas ◽  
H. J. Dowsett ◽  
M. Kelley
Keyword(s):  
North Atlantic ◽  
Earth System Model ◽  
Warm Period ◽  
System Model ◽  
Earth System ◽  
Climate Control ◽  
Substantial Impact ◽  
The North ◽  
Future Global Warming ◽  
The North Atlantic

Abstract. The mid-Pliocene Warm Period (mPWP) bears many similarities to aspects of future global warming as projected by the Intergovernmental Panel on Climate Change (IPCC, 2007). Both marine and terrestrial data point to high-latitude temperature amplification, including large decreases in sea ice and land ice, as well as expansion of warmer climate biomes into higher latitudes. Here we present our most recent simulations of the mid-Pliocene climate using the CMIP5 version of the NASA/GISS Earth System Model (ModelE2-R). We describe the substantial impact associated with a recent correction made in the implementation of the Gent-McWilliams ocean mixing scheme (GM), which has a large effect on the simulation of ocean surface temperatures, particularly in the North Atlantic Ocean. The effect of this correction on the Pliocene climate results would not have been easily determined from examining its impact on the preindustrial runs alone, a useful demonstration of how the consequences of code improvements as seen in modern climate control runs do not necessarily portend the impacts in extreme climates. Both the GM-corrected and GM-uncorrected simulations were contributed to the Pliocene Model Intercomparison Project (PlioMIP) Experiment 2. Many findings presented here corroborate results from other PlioMIP multi-model ensemble papers, but we also emphasise features in the ModelE2-R simulations that are unlike the ensemble means. The corrected version yields results that more closely resemble the ocean core data as well as the PRISM3D reconstructions of the mid-Pliocene, especially the dramatic warming in the North Atlantic and Greenland-Iceland-Norwegian Sea, which in the new simulation appears to be far more realistic than previously found with older versions of the GISS model. Our belief is that continued development of key physical routines in the atmospheric model, along with higher resolution and recent corrections to mixing parameterisations in the ocean model, have led to an Earth System Model that will produce more accurate projections of future climate.

scholarly journals A comprehensive assessment of tropical stratospheric upwelling in the specified dynamics Community Earth System Model 1.2.2 – Whole Atmosphere Community Climate Model (CESM (WACCM))

2020 ◽  
Vol 13 (2) ◽  
pp. 717-734 ◽  
Author(s):  
Nicholas A. Davis ◽  
Sean M. Davis ◽  
Robert W. Portmann ◽  
Eric Ray ◽  
Karen H. Rosenlof ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Earth System Model ◽  
System Model ◽  
Trace Gas ◽  
Earth System ◽  
Mean Meridional Circulation ◽  
Community Earth System Model ◽  
The Mean ◽  
Wave Momentum

Abstract. Specified dynamics (SD) schemes relax the circulation in climate models toward a reference meteorology to simulate historical variability. These simulations are widely used to isolate the dynamical contributions to variability and trends in trace gas species. However, it is not clear if trends in the stratospheric overturning circulation are properly reproduced by SD schemes. This study assesses numerous SD schemes and modeling choices in the Community Earth System Model (CESM) Whole Atmosphere Chemistry Climate Model (WACCM) to determine a set of best practices for reproducing interannual variability and trends in tropical stratospheric upwelling estimated by reanalyses. Nudging toward the reanalysis meteorology as is typically done in SD simulations does not accurately reproduce lower-stratospheric upwelling trends present in the underlying reanalysis. In contrast, nudging to anomalies from the climatological winds or anomalies from the zonal-mean winds and temperatures better reproduces trends in lower-stratospheric upwelling, possibly because these schemes do not disrupt WACCM's climatology. None of the schemes substantially alter the structure of upwelling trends – instead, they make the trends more or less AMIP-like. An SD scheme's performance in simulating the acceleration of the shallow branch of the mean meridional circulation from 1980 to 2017 hinges on its ability to simulate the downward shift of subtropical lower-stratospheric wave momentum forcing. Key to this is not nudging the zonal-mean temperature field. Gravity wave momentum forcing, which drives a substantial fraction of the upwelling in WACCM, cannot be constrained by nudging and presents an upper limit on the performance of these schemes.

scholarly journals Setup of the PMIP3 paleoclimate experiments conducted using an Earth System Model, MIROC-ESM

2012 ◽  
Vol 5 (3) ◽  
pp. 2527-2569 ◽  
Author(s):  
T. Sueyoshi ◽  
R. Ohgaito ◽  
A. Yamamoto ◽  
M. O. Chikamoto ◽  
T. Hajima ◽  
...  
Keyword(s):  
Climate Model ◽  
Coupled Model ◽  
Earth System Model ◽  
Future Climate ◽  
System Model ◽  
Climate Feedback ◽  
Climate Projections ◽  
Earth System ◽  
Intergovernmental Panel ◽  
Intercomparison Project

Abstract. The importance of climate model evaluation using paleoclimate simulations for better future climate projections has been recognized by the Intergovernmental Panel on Climate Change. In recent years, Earth System Models (ESMs) were developed to investigate carbon-cycle climate feedback, as well as to project the future climate. Paleoclimate events, especially those associated with the variations in atmospheric CO2 level or land vegetation, provide suitable benchmarks to evaluate ESMs. Here we present implementations of the paleoclimate experiments proposed by the Coupled Model Intercomparison Project phase 5/Paleoclimate Modelling Intercomparison Project phase 3 (CMIP5/PMIP3) using an Earth System Model, MIROC-ESM. In this paper, experimental settings and procedures of the mid-Holocene, the Last Glacial Maximum, and the Last Millennium experiments are explained. The first two experiments are time slice experiments and the last one is a transient experiment. The complexity of the model requires various steps to correctly configure the experiments. Several basic outputs are also shown.

scholarly journals Coupling of a sediment diagenesis model (MEDUSA) and an Earth system model (CESM1.2): a contribution toward enhanced marine biogeochemical modelling and long-term climate simulations

2019 ◽  
Author(s):  
Takasumi Kurahashi-Nakamura ◽  
André Paul ◽  
Guy Munhoven ◽  
Ute Merkel ◽  
Michael Schulz
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Coupled Model ◽  
Earth System Model ◽  
System Model ◽  
Future Application ◽  
Coupling Scheme ◽  
Earth System ◽  
Climate Simulations

Abstract. We developed a coupling scheme for the Community Earth System Model version 1.2 (CESM1.2) and the Model of Early Diagenesis in the Upper Sediment of Adjustable complexity (MEDUSA), and explored the effects of the coupling on solid components in the upper sediment and on bottom seawater chemistry by comparing the coupled model's behaviour with that of the uncoupled CESM having a simplified treatment of sediment processes. CESM is a fully-coupled atmosphere-ocean-sea ice-land model and its ocean component (the Parallel Ocean Program version 2, POP2) includes a biogeochemical component (BEC). MEDUSA was coupled to POP2 in an off-line manner so that each of the models ran separately and sequentially with regular exchanges of necessary boundary condition fields. This development was done with the ambitious aim of a future application for long-term (spanning a full glacial cycle; i.e., ~ 105 years) climate simulations with a state-of-the-art comprehensive climate model including the carbon cycle, and was motivated by the fact that until now such simulations have been done only with less-complex climate models. We found that the sediment-model coupling already had non-negligible immediate advantages for ocean biogeochemistry in millennial-time-scale simulations. First, the MEDUSA-coupled CESM outperformed the uncoupled CESM in reproducing an observation-based global distribution of sediment properties, especially for organic carbon and opal. Thus, the coupled model is expected to act as a better bridge between climate dynamics and sedimentary data, which will provide another measure of model performance. Second, in our experiments, the MEDUSA-coupled model and the uncoupled model had a difference of 0.2‰ or larger in terms of δ13C of bottom water over large areas, which implied potential significant model biases for bottom seawater chemical composition due to a different way of sediment treatment. Such a model bias would be a fundamental issue for paleo model–data comparison often relying on data derived from benthic foraminifera.

Comparison of the surface mass and energy balance of CESM and MAR forced by CESM over Greenland: present and future

2020 ◽  
Author(s):  
Charlotte Lang ◽  
Charles Amory ◽  
Alison Delhasse ◽  
Stefan Hofer ◽  
Christoph Kittel ◽  
...  
Keyword(s):  
Energy Balance ◽  
Climate Models ◽  
Climate Model ◽  
Ice Sheet ◽  
Earth System Model ◽  
Global Climate Models ◽  
Added Value ◽  
System Model ◽  
Earth System ◽  
Surface Mass

<p>We have compared the surface mass (SMB) and energy balance of the Earth System model (ESM) CESM (Community Earth System Model) with those of the regional climate model (RCM) MAR (Modèle Atmosphérique Régional) forced by CESM over the present era (1981 — 2010) and the future (2011 — 2100 with SSP585 scenario).</p><p>Until now, global climate models (GCM) and ESMs forcing RCMs such as MAR didn’t include a module able to simulate snow and energy balance at the surface of a snow pack like the SISVAT module of MAR and were therefore not able to simulate the SMB of an ice sheet. Evaluating the added value of an RCM compared to a GCM could only be done by comparing atmospheric outputs (temperature, wind, precipitation …) in both models. CESM is the first ESM including a land model capable of simulating the surface of an ice sheet and thus to directly compare the SMB of an RCM and an ESM the first time.</p><p>Our results show that, if the SMB and is components are very similar in CESM and MAR over the present era, they quickly start to diverge in our future projection, the SMB of MAR decreasing more than that of CESM. This difference in SMB evolution is almost exclusively explained by a much larger increase of the melter runoff in MAR compared to CESM whereas the temporal evolution of snowfall, rainfall and sublimation is comparable in both runs.</p>

scholarly journals The EC-Earth3 Earth System Model for the Climate Model Intercomparison Project 6

2021 ◽  
Author(s):  
Ralf Döscher ◽  
Mario Acosta ◽  
Andrea Alessandri ◽  
Peter Anthoni ◽  
Almut Arneth ◽  
...  
Keyword(s):  
Physical Performance ◽  
Performance Metrics ◽  
Climate Model ◽  
Earth System Model ◽  
System Model ◽  
Historical Period ◽  
Earth System ◽  
Dynamic Features ◽  
The Earth ◽  
Intercomparison Project

Abstract. The Earth System Model EC-Earth3 for contributions to CMIP6 is documented here, with its flexible coupling framework, major model configurations, a methodology for ensuring the simulations are comparable across different HPC systems, and with the physical performance of base configurations over the historical period. The variety of possible configurations and sub-models reflects the broad interests in the EC-Earth community. EC-Earth3 key performance metrics demonstrate physical behaviour and biases well within the frame known from recent CMIP models. With improved physical and dynamic features, new ESM components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.

Recent developments on the Earth System Model Evaluation Tool

2021 ◽  
Author(s):  
Bouwe Andela ◽  
Fakhereh Alidoost ◽  
Lukas Brunner ◽  
Jaro Camphuijsen ◽  
Bas Crezee ◽  
...  
Keyword(s):  
Model Evaluation ◽  
Performance Metrics ◽  
Climate Model ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Evaluation Tool ◽  
Scientific Review ◽  
The Earth ◽  
User Friendly

<p>The Earth System Model Evaluation Tool (ESMValTool) is a free and open-source community diagnostic and performance metrics tool for the evaluation of Earth system models such as those participating in the Coupled Model Intercomparison Project (CMIP). Version 2 of the tool (Righi et al. 2020, www.esmvaltool.org) features a brand new design composed of a core that finds and processes data according to a ‘recipe’ and an extensive collection of ready-to-use recipes and associated diagnostic codes for reproducing results from published papers. Development and discussion of the tool (mostly) takes place in public on https://github.com/esmvalgroup and anyone with an interest in climate model evaluation is welcome to join there.</p><p> </p><p>Since the initial release of version 2 in the summer of 2020, many improvements have been made to the tool. It is now more user friendly with extensive documentation available on docs.esmvaltool.org and a step by step online tutorial. Regular releases, currently planned three times a year, ensure that recent contributions become available quickly while still ensuring a high level of quality control. The tool can be installed from conda, but portable docker and singularity containers are also available.</p><p> </p><p>Recent new features include a more user-friendly command-line interface, citation information per figure including CMIP6 data citation using ES-DOC, more and faster preprocessor functions that require less memory, automatic corrections for a larger number of CMIP6 datasets, support for more observational and reanalysis datasets, and more recipes and diagnostics.</p><p> </p><p>The tool is now also more reliable, with improved automated testing through more unit tests for the core, as well as a recipe testing service running at DKRZ for testing the scientific recipes and diagnostics that are bundled into the tool. The community maintaining and developing the tool is growing, making the project less dependent on individual contributors. There are now technical and scientific review teams that review new contributions for technical quality and scientific correctness and relevance respectively, two new principal investigators for generating a larger support base in the community, and a newly created user engagement team that is taking care of improving the overall user experience.</p>

scholarly journals Progress towards a probabilistic Earth system model: examining the impact of stochasticity in the atmosphere and land component of EC-Earth v3.2

2019 ◽  
Vol 12 (7) ◽  
pp. 3099-3118 ◽  
Author(s):  
Kristian Strommen ◽  
Hannah M. Christensen ◽  
Dave MacLeod ◽  
Stephan Juricke ◽  
Tim N. Palmer
Keyword(s):  
Climate Model ◽  
Weather Forecasting ◽  
Southern Oscillation ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Beneficial Impact ◽  
The Impact ◽  
Mean State

Abstract. We introduce and study the impact of three stochastic schemes in the EC-Earth climate model: two atmospheric schemes and one stochastic land scheme. These form the basis for a probabilistic Earth system model in atmosphere-only mode. Stochastic parametrization have become standard in several operational weather-forecasting models, in particular due to their beneficial impact on model spread. In recent years, stochastic schemes in the atmospheric component of a model have been shown to improve aspects important for the models long-term climate, such as El Niño–Southern Oscillation (ENSO), North Atlantic weather regimes, and the Indian monsoon. Stochasticity in the land component has been shown to improve the variability of soil processes and improve the representation of heatwaves over Europe. However, the raw impact of such schemes on the model mean is less well studied. It is shown that the inclusion of all three schemes notably changes the model mean state. While many of the impacts are beneficial, some are too large in amplitude, leading to significant changes in the model's energy budget and atmospheric circulation. This implies that in order to maintain the benefits of stochastic physics without shifting the mean state too far from observations, a full re-tuning of the model will typically be required.

Coupling the Earth system model INMCM with the biogeochemical flux model

2018 ◽  
Vol 33 (6) ◽  
pp. 325-331
Author(s):  
Ilya A. Chernov ◽  
Nikolay G. Iakovlev
Keyword(s):  
Climate Model ◽  
World Ocean ◽  
Coupled Model ◽  
Horizontal Resolution ◽  
Ocean Model ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Time Step ◽  
The Earth

Abstract In the present paper we consider the first results of modelling the World Ocean biogeochemistry system within the framework of the Earth system model: a global atmosphere-ocean-ice-land-biogeochemistry model. It is based on the INMCM climate model (version INMCM39) coupled with the pelagic ecosystem model BFM. The horizontal resolution was relatively low: 2∘ × 2.5∘ for the ‘longitude’ and ‘latitude’ in transformed coordinates with the North Pole moved to land, 33 non-equidistant σ-horizons, 1 hour time step. We have taken into account 54 main rivers worldwide with run–off supplied by the atmosphere submodel. The setup includes nine plankton groups, 60 tracers in total. Some components sink with variable speed. We discuss challenges of coupling the BFM with the σ-coordinate ocean model. The presented results prove that the model output is realistic in comparison with the observed data, the numerical efficiency is high enough, and the coupled model may serve as a basis for further simulations of the long-term climate change.

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