scholarly journals Inclusion of a suite of weathering tracers in the cGENIE Earth System Model – muffin release v.0.9.10

2020 ◽  
Author(s):  
Markus Adloff ◽  
Andy Ridgwell ◽  
Fanny M. Monteiro ◽  
Ian J. Parkinson ◽  
Alexander Dickson ◽  
...  
Keyword(s):  
Biogeochemical Cycles ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Weathering Rates ◽  
The Earth ◽  
Isotopic Shifts ◽  
Box Models ◽  
Geologic Record

Abstract. The metals strontium (Sr), lithium (Li), osmium (Os) and calcium (Ca) and their isotopes are important tracers in the study of changes in weathering rates and volcanism, two main processes which shape the long-term cycling of carbon and other biogeochemically important elements at the Earth's surface. Traditionally, isotopic shifts of these four elements in the geologic record are interpreted with isotope-mixing, tracer-specific box models because of their long residence times in the ocean. However, these models often lack mechanistic links between the cycling of the four metals and other geochemically relevant elements, particularly carbon. Here we develop and evaluate the implementation of Sr, Li, Os and Ca isotopes into the Earth system model cGENIE. The model has the potential to study these metal systems at equilibrium and under perturbations alongside other biogeochemical cycles. We provide examples of how to apply this new model to investigate Sr, Li, Os and Ca isotope dynamics and responses to environmental change.

scholarly journals Inclusion of a suite of weathering tracers in the cGENIE Earth system model – muffin release v.0.9.23

2021 ◽  
Vol 14 (7) ◽  
pp. 4187-4223
Author(s):  
Markus Adloff ◽  
Andy Ridgwell ◽  
Fanny M. Monteiro ◽  
Ian J. Parkinson ◽  
Alexander J. Dickson ◽  
...  
Keyword(s):  
Biogeochemical Cycles ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
The Earth ◽  
Isotopic Shifts ◽  
Box Models ◽  
Carbon Release ◽  
Geologic Record

Abstract. The metals strontium (Sr), lithium (Li), osmium (Os) and calcium (Ca), together with their isotopes, are important tracers of weathering and volcanism – primary processes which shape the long-term cycling of carbon and other biogeochemically important elements at the Earth's surface. Traditionally, because of their long residence times in the ocean, isotopic shifts in these four elements observed in the geologic record are almost exclusively interpreted with the aid of isotope-mixing, tracer-specific box models. However, such models may lack a mechanistic description of the links between the cycling of the four metals to other geochemically relevant elements, particularly carbon, or climate. Here we develop and evaluate an implementation of Sr, Li, Os and Ca isotope cycling in the Earth system model cGENIE. The model offers the possibility to study the dynamics of these metal systems alongside other more standard biogeochemical cycles, as well as their relationship with changing climate. We provide examples of how to apply this new model capability to investigate Sr, Li, Os and Ca isotope dynamics and responses to environmental change, for which we take the example of massive carbon release to the atmosphere.

scholarly journals Reciprocal bias compensation and ensuing uncertainties in model-based climate projections: pelagic biogeochemistry versus ocean mixing

2018 ◽  
Author(s):  
Ulrike Löptien ◽  
Heiner Dietze
Keyword(s):  
Ocean Circulation ◽  
Biogeochemical Cycles ◽  
Earth System Model ◽  
System Model ◽  
Model Parameters ◽  
Ocean Mixing ◽  
Earth System ◽  
Feedback Mechanisms ◽  
The Earth ◽  
Model Component

Abstract. Anthropogenic emissions of greenhouse gases such as CO2 and N2O impinge on the earth system which, in turn, modulates atmospheric greenhouse gas concentrations. The underlying feedback mechanisms are complex and, at times, counterintuitive. So-called Earth System Models have recently matured to standard tools tailored to assess these feedback mechanisms in a warming world. Respective model applications range from being targeted at basic process understanding to the assessment of geo-engineering options. A problem endemic to all these applications is the need to estimate poorly known model parameters, specifically for the biogeochemical component, based on observational data (e.g. nutrient fields). In the present study, we illustrate that by such an approach biases in the physical ocean-circulation model component of an Earth System Model can reciprocally compensate biases in the pelagic biogeochemical model component (and vice versa). We present two configurations of an Earth System Model that share a remarkably similar steady state (based on ad-hoc measures) when driven by historical boundary conditions, even though they feature substantially different configurations (sets) of ocean-mixing and biogeochemical cycling (model parameters). When projected into the future the similarity between the model responses breaks. Metrics like total oceanic carbon content and suboxic volume diverge in the model configurations as the Earth warms. Our results reiterate that advancing the understanding of oceanic mixing processes will reduce the uncertainty of future projections of the oceanic biogeochemical cycles. Vice versa, we suggest that an advanced understanding of oceanic biogeochemical cycles can be used for advancements in the ocean circulation modules.

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>

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.

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