Advanced Earth System Modelling Capacity (ESM): Solving Grand Challenges by improving the representation of the components of the Earth system and their coupling

2020 ◽  
Author(s):  
Luisa Cristini ◽  
Keyword(s):  
Numerical Models ◽  
Earth System Model ◽  
Model Systems ◽  
System Model ◽  
System Modelling ◽  
Earth System ◽  
Grand Challenges ◽  
The Earth ◽  
Assimilation Capacity ◽  
Earth System Modelling

<p>With climate change and the conjoint challenges of food availability, clean water and geo-energy resources, our society is facing major challenges in the near future. These challenges are hard to address, because projections of Earth system change involve uncertainties that require quantification. Therefore, the Earth system science community tries to develop tools that provide decision-makers with the information required to effectively manage these issues.</p><p>The Advanced Earth System Modelling Capacity project (ESM) aims to enable such tools, investigating problems by looking at interactions between different Earth system components and improve their representation in numerical models. The project was funded by the German Helmholtz Association in April 2017 and involves eight research centers across Germany. The ultimate goal of the project is to represent the Earth system and how it changes with a world-leading modelling infrastructure that will support the process of developing solutions for the grand challenges we are facing.</p><p>The five different work packages of the project are working on topics such as enhancing the representation of Earth system model compartments, develop a flexible framework for coupling of Earth system model components, advance the Earth system data assimilation capacity, diagnose Earth system models, further develop cutting-edge frontier simulations, cross-scale modelling, and contribute to the shaping of a national strategy for Earth system modelling. The project also engages in training activities to educate and transfer knowledge to the next generation of scientists.</p><p>Since its initiation the project contributed with important results to several key model systems and platforms. In this presentation, we will highlight some current results and discuss advances in our Earth system modelling community and the way forward.</p>

scholarly journals 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

2020 ◽  
Vol 13 (7) ◽  
pp. 3383-3438 ◽  
Author(s):  
Veronika Eyring ◽  
Lisa Bock ◽  
Axel Lauer ◽  
Mattia Righi ◽  
Manuel Schlund ◽  
...  
Keyword(s):  
Model Evaluation ◽  
Large Scale ◽  
Performance Metrics ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Evaluation Tool ◽  
The Earth ◽  
And Performance ◽  
Earth System Models

Abstract. The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of Earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility. It consists of (1) an easy-to-install, well-documented Python package providing the core functionalities (ESMValCore) that performs common preprocessing operations and (2) a diagnostic part that includes tailored diagnostics and performance metrics for specific scientific applications. Here we describe large-scale diagnostics of the second major release of the tool that supports the evaluation of ESMs participating in CMIP Phase 6 (CMIP6). ESMValTool v2.0 includes a large collection of diagnostics and performance metrics for atmospheric, oceanic, and terrestrial variables for the mean state, trends, and variability. ESMValTool v2.0 also successfully reproduces figures from the evaluation and projections chapters of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) and incorporates updates from targeted analysis packages, such as the NCAR Climate Variability Diagnostics Package for the evaluation of modes of variability, the Thermodynamic Diagnostic Tool (TheDiaTo) to evaluate the energetics of the climate system, as well as parts of AutoAssess that contains a mix of top–down performance metrics. The tool has been fully integrated into the Earth System Grid Federation (ESGF) infrastructure at the Deutsches Klimarechenzentrum (DKRZ) to provide evaluation results from CMIP6 model simulations shortly after the output is published to the CMIP archive. A result browser has been implemented that enables advanced monitoring of the evaluation results by a broad user community at much faster timescales than what was possible in CMIP5.

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.

scholarly journals Erratum to: The earth system model of intermediate complexity CLIMBER-3α. Part I: description and performance for present-day conditions

2009 ◽  
Vol 34 (1) ◽  
pp. 151-151
Author(s):  
Marisa Montoya ◽  
Alexa Griesel ◽  
Anders Levermann ◽  
Juliette Mignot ◽  
Matthias Hofmann ◽  
...  
Keyword(s):  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Intermediate Complexity ◽  
The Earth ◽  
And Performance

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>

The Frontiers of Deep Learning for Earth System Modelling 

2021 ◽  
Author(s):  
David Hall
Keyword(s):  
Artificial Intelligence ◽  
Bias Correction ◽  
Neural Nets ◽  
Generative Adversarial Networks ◽  
System Modelling ◽  
Earth System ◽  
Adversarial Networks ◽  
The Earth ◽  
Medium Range ◽  
Earth System Modelling

<p>This talk gives an overview of cutting-edge artificial intelligence applications and techniques for the earth-system sciences. We survey the most important recent contributions in areas including extreme weather, physics emulation, nowcasting, medium-range forecasting, uncertainty quantification, bias-correction, generative adversarial networks, data in-painting, network-HPC coupling, physics-informed neural nets, and geoengineering, amongst others. Then, we describe recent AI breakthroughs that have the potential to be of greatest benefit to the geosciences. We also discuss major open challenges in AI for science and their potential solutions. This talk is a living document, in that it is updated frequently, in order to accurately relect this rapidly changing field.</p>

scholarly journals The compact Earth system model OSCAR v2.2: description and first results

2017 ◽  
Vol 10 (1) ◽  
pp. 271-319 ◽  
Author(s):  
Thomas Gasser ◽  
Philippe Ciais ◽  
Olivier Boucher ◽  
Yann Quilcaille ◽  
Maxime Tortora ◽  
...  
Keyword(s):  
Atmospheric Carbon Dioxide ◽  
Stratospheric Ozone ◽  
Earth System Model ◽  
Tropospheric Chemistry ◽  
System Model ◽  
Future Climate Change ◽  
Historical Period ◽  
Earth System ◽  
Atmospheric Concentration ◽  
The Earth

Abstract. This paper provides a comprehensive description of OSCAR v2.2, a simple Earth system model. The general philosophy of development is first explained, followed by a complete description of the model's drivers and various modules. All components of the Earth system necessary to simulate future climate change are represented in the model: the oceanic and terrestrial carbon cycles – including a book-keeping module to endogenously estimate land-use change emissions – so as to simulate the change in atmospheric carbon dioxide; the tropospheric chemistry and the natural wetlands, to simulate that of methane; the stratospheric chemistry, for nitrous oxide; 37 halogenated compounds; changing tropospheric and stratospheric ozone; the direct and indirect effects of aerosols; changes in surface albedo caused by black carbon deposition on snow and land-cover change; and the global and regional response of climate – in terms of temperature and precipitation – to all these climate forcers. Following the probabilistic framework of the model, an ensemble of simulations is made over the historical period (1750–2010). We show that the model performs well in reproducing observed past changes in the Earth system such as increased atmospheric concentration of greenhouse gases or increased global mean surface temperature.

A Multitask Learning View on the Earth System Model Ensemble

2015 ◽  
Vol 17 (6) ◽  
pp. 35-42
Author(s):  
Andre R. Goncalves ◽  
Fernando J. Von Zuben ◽  
Arindam Banerjee
Keyword(s):  
Multitask Learning ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Model Ensemble ◽  
The Earth

scholarly journals The compact Earth system model OSCAR v2.2: description and first results

2016 ◽  
Author(s):  
Thomas Gasser ◽  
Philippe Ciais ◽  
Olivier Boucher ◽  
Yann Quilcaille ◽  
Maxime Tortora ◽  
...  
Keyword(s):  
Atmospheric Carbon Dioxide ◽  
Stratospheric Ozone ◽  
Earth System Model ◽  
System Model ◽  
Future Climate Change ◽  
Historical Period ◽  
Earth System ◽  
Atmospheric Concentration ◽  
Carbon Cycles ◽  
The Earth

Abstract. This paper provides a comprehensive description of OSCAR v2.2, a simple Earth system model. The general philosophy of development is first explained, it is then followed by a complete description of the model's drivers and various modules. All components of the Earth system necessary to simulate future climate change are represented in the model: the oceanic and terrestrial carbon-cycles – including a book-keeping module to endogenously estimate land-use change emissions – so as to simulate the change in atmospheric carbon dioxide; the tropospheric OH chemistry and the natural wetlands, to simulate that of methane; the stratospheric chemistry, for nitrous oxide; thirty-seven halogenated compounds; changing tropospheric and stratospheric ozone; the direct and indirect effects of aerosols; changes in surface albedo caused by black carbon deposition on snow and land-cover change; and the global and regional response of climate – in terms of temperatures and precipitations – to all these climate forcers. Following the probabilistic framework of the model, an ensemble of simulations is made over the historical period (1750–2010). We show that the model performs well in reproducing observed past changes in the Earth system such as increased atmospheric concentration of greenhouse gases or increased global mean surface temperature.

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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