scholarly journals Climate feedbacks in the Earth system and prospects for their evaluation

2018 ◽  
Author(s):  
Christoph Heinze ◽  
Veronika Eyring ◽  
Pierre Friedlingstein ◽  
Colin Jones ◽  
Yves Balkanski ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Projections ◽  
Earth System ◽  
Climate Feedbacks ◽  
Comprehensive Overview ◽  
The Earth ◽  
Cloud Dynamics ◽  
Spatial And Temporal Heterogeneity ◽  
Earth System Models

Abstract. Earth system models (ESMs) are key tools for providing climate projections under different scenarios of human-induced forcing. ESMs include a large number of additional processes and feedbacks such as biogeochemical cycles that traditional physical climate models do not consider. Yet, some processes such as cloud dynamics and ecosystem functional response still have fairly high uncertainties. In this article, we present an overview of climate feedbacks for Earth system components currently included in state-of-the-art ESMs and discuss the challenges to evaluate and quantify them. Uncertainties in feedback quantification arise from the interdependencies of biogeochemical matter fluxes and physical properties, the spatial and temporal heterogeneity of processes, and the lack of long-term continuous observational data to constrain them. We present an outlook for promising approaches that can help quantifying and constraining the large number of feedbacks in ESMs in the future. 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 (researchers, lecturers, and students). This study updates and significantly expands upon the last comprehensive overview of climate feedbacks in ESMs, which was produced 15 years ago (NRC, 2003).

scholarly journals ESD Reviews: Climate feedbacks in the Earth system and prospects for their evaluation

2019 ◽  
Vol 10 (3) ◽  
pp. 379-452 ◽  
Author(s):  
Christoph Heinze ◽  
Veronika Eyring ◽  
Pierre Friedlingstein ◽  
Colin Jones ◽  
Yves Balkanski ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Projections ◽  
Earth System ◽  
Climate Feedbacks ◽  
Comprehensive Overview ◽  
The Earth ◽  
Cloud Dynamics ◽  
Spatial And Temporal Heterogeneity ◽  
Earth System Models

Abstract. Earth system models (ESMs) are key tools for providing climate projections under different scenarios of human-induced forcing. ESMs include a large number of additional processes and feedbacks such as biogeochemical cycles that traditional physical climate models do not consider. Yet, some processes such as cloud dynamics and ecosystem functional response still have fairly high uncertainties. In this article, we present an overview of climate feedbacks for Earth system components currently included in state-of-the-art ESMs and discuss the challenges to evaluate and quantify them. Uncertainties in feedback quantification arise from the interdependencies of biogeochemical matter fluxes and physical properties, the spatial and temporal heterogeneity of processes, and the lack of long-term continuous observational data to constrain them. We present an outlook for promising approaches that can help to quantify and to constrain the large number of feedbacks in ESMs in the future. 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 (researchers, lecturers, and students). This study updates and significantly expands upon the last comprehensive overview of climate feedbacks in ESMs, which was produced 15 years ago (NRC, 2003).

scholarly journals Observing carbon cycle–climate feedbacks from space

2018 ◽  
Vol 115 (31) ◽  
pp. 7860-7868 ◽  
Author(s):  
Piers J. Sellers ◽  
David S. Schimel ◽  
Berrien Moore ◽  
Junjie Liu ◽  
Annmarie Eldering
Keyword(s):  
Carbon Dioxide ◽  
Earth System ◽  
Climate Feedbacks ◽  
System Models ◽  
Component Processes ◽  
The Impact ◽  
Atmospheric Concentrations ◽  
Earth System Models

The impact of human emissions of carbon dioxide and methane on climate is an accepted central concern for current society. It is increasingly evident that atmospheric concentrations of carbon dioxide and methane are not simply a function of emissions but that there are myriad feedbacks forced by changes in climate that affect atmospheric concentrations. If these feedbacks change with changing climate, which is likely, then the effect of the human enterprise on climate will change. Quantifying, understanding, and articulating the feedbacks within the carbon–climate system at the process level are crucial if we are to employ Earth system models to inform effective mitigation regimes that would lead to a stable climate. Recent advances using space-based, more highly resolved measurements of carbon exchange and its component processes—photosynthesis, respiration, and biomass burning—suggest that remote sensing can add key spatial and process resolution to the existing in situ systems needed to provide enhanced understanding and advancements in Earth system models. Information about emissions and feedbacks from a long-term carbon–climate observing system is essential to better stewardship of the planet.

scholarly journals Can we trust empirical marine DMS parameterisations within projections of future climate?

2010 ◽  
Vol 7 (5) ◽  
pp. 1645-1656 ◽  
Author(s):  
P. R. Halloran ◽  
T. G. Bell ◽  
I. J. Totterdell
Keyword(s):  
Climate Models ◽  
Global Climate Models ◽  
Future Climate ◽  
Climate Feedback ◽  
Climate Projections ◽  
Earth System ◽  
Aerosol Formation ◽  
System Models ◽  
Annual Variability ◽  
Earth System Models

Abstract. Dimethylsulphide (DMS) is a globally important aerosol precurser. In 1987 Charlson and others proposed that an increase in DMS production by certain phytoplankton species in response to a warming climate could stimulate increased aerosol formation, increasing the lower-atmosphere's albedo, and promoting cooling. Despite two decades of research, the global significance of this negative climate feedback remains contentious. It is therefore imperative that schemes are developed and tested, which allow for the realistic incorporation of phytoplankton DMS production into Earth System models. Using these models we can investigate the DMS-climate feedback and reduce uncertainty surrounding projections of future climate. Here we examine two empirical DMS parameterisations within the context of an Earth System model and find them to perform marginally better than the standard DMS climatology at predicting observations from an independent global dataset. We then question whether parameterisations based on our present understanding of DMS production by phytoplankton, and simple enough to incorporate into global climate models, can be shown to enhance the future predictive capacity of those models. This is an important question to ask now, as results from increasingly complex Earth System models lead us into the 5th assessment of climate science by the Intergovernmental Panel on Climate Change. Comparing observed and predicted inter-annual variability, we suggest that future climate projections may underestimate the magnitude of surface ocean DMS change. Unfortunately this conclusion relies on a relatively small dataset, in which observed inter-annual variability may be exaggerated by biases in sample collection. We therefore encourage the observational community to make repeat measurements of sea-surface DMS concentrations an important focus, and highlight areas of apparent high inter-annual variability where sampling might be carried out. Finally, we assess future projections from two similarly valid empirical DMS schemes, and demonstrate contrasting results. We therefore conclude that the use of empirical DMS parameterisations within simulations of future climate should be undertaken only with careful appreciation of the caveats discussed.

scholarly journals Ideas and perspectives: climate-relevant marine biologically driven mechanisms in Earth system models

2017 ◽  
Vol 14 (2) ◽  
pp. 403-413 ◽  
Author(s):  
Inga Hense ◽  
Irene Stemmler ◽  
Sebastian Sonntag
Keyword(s):  
Atmospheric Composition ◽  
Climate Projections ◽  
Marine Biota ◽  
Earth System ◽  
System Models ◽  
The Earth ◽  
Optical And Mechanical Properties ◽  
System 1 ◽  
Earth System Models

Abstract. The current generation of marine biogeochemical modules in Earth system models (ESMs) considers mainly the effect of marine biota on the carbon cycle. We propose to also implement other biologically driven mechanisms in ESMs so that more climate-relevant feedbacks are captured. We classify these mechanisms in three categories according to their functional role in the Earth system: (1) biogeochemical pumps, which affect the carbon cycling; (2) biological gas and particle shuttles, which affect the atmospheric composition; and (3) biogeophysical mechanisms, which affect the thermal, optical, and mechanical properties of the ocean. To resolve mechanisms from all three classes, we find it sufficient to include five functional groups: bulk phyto- and zooplankton, calcifiers, and coastal gas and surface mat producers. We strongly suggest to account for a larger mechanism diversity in ESMs in the future to improve the quality of climate projections.

scholarly journals Multi-objective optimization of GENIE Earth system models

2009 ◽  
Vol 367 (1898) ◽  
pp. 2623-2633 ◽  
Author(s):  
Andrew R. Price ◽  
Richard J. Myerscough ◽  
Ivan I. Voutchkov ◽  
Robert Marsh ◽  
Simon J. Cox
Keyword(s):  
High Performance ◽  
Climate Models ◽  
Earth System ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Surface Models ◽  
Iterative Evaluation ◽  
Performance Computing ◽  
Earth System Models

The tuning of parameters in climate models is essential to provide reliable long-term forecasts of Earth system behaviour. We apply a multi-objective optimization algorithm to the problem of parameter estimation in climate models. This optimization process involves the iterative evaluation of response surface models (RSMs), followed by the execution of multiple Earth system simulations. These computations require an infrastructure that provides high-performance computing for building and searching the RSMs and high-throughput computing for the concurrent evaluation of a large number of models. Grid computing technology is therefore essential to make this algorithm practical for members of the GENIE project.

scholarly journals Can we trust simple marine DMS parameterisations within complex climate models?

2010 ◽  
Vol 7 (1) ◽  
pp. 1295-1320 ◽  
Author(s):  
P. R. Halloran ◽  
T. G. Bell ◽  
I. J. Totterdell
Keyword(s):  
Interannual Variability ◽  
Climate Models ◽  
Global Climate Models ◽  
Future Climate ◽  
Climate Feedback ◽  
Climate Projections ◽  
Earth System ◽  
Aerosol Formation ◽  
System Models ◽  
Earth System Models

Abstract. Dimethylsulphide (DMS) is a globally important aerosol precurser. In 1987 Charlson and others proposed that an increase in DMS production by certain phytoplankton species in response to a warming climate could stimulate increased aerosol formation, increasing the lower-atmosphere's albedo, and promoting cooling. Despite two decades of research, the global significance of this negative climate feedback remains contentious. It is therefore imperative that schemes are developed and tested, which allow for the realistic incorporation of phytoplankton DMS production into Earth System models. Using these models we can investigate the DMS-climate feedback and reduce uncertainty surrounding projections of future climate. Here we examine two empirical DMS parameterisations within the context of an Earth System model and find them to perform marginally better than the standard DMS climatology at predicting observations from an independent global dataset. We then question whether parameterisations based on our present understanding of DMS production by phytoplankton, and simple enough to incorporate into global climate models, can be shown to enhance the future predictive capacity of those models. This is an important question to ask now, as results from increasingly complex Earth System models lead us into the 5th assessment of climate science by the Intergovernmental Panel on Climate Change. Comparing observed and predicted interannual variability, we suggest that future climate projections may underestimate the magnitude of surface ocean DMS change. Unfortunately this conclusion relies on a relatively small dataset, in which observed interannual variability may be exaggerated by biases in sample collection. We therefore encourage the observational community to make repeat measurements of sea-surface DMS concentrations an important focus, and highlight areas of apparent high interannual variability where sampling might be carried out. Finally, we assess future projections from two similarly valid empirical DMS schemes, and demonstrate contrasting results. We therefore conclude that the use of empirical DMS parameterisations within simulations of future climate should be undertaken only with careful appreciation of the caveats discussed.

scholarly journals Evaluating the Land and Ocean Components of the Global Carbon Cycle in the CMIP5 Earth System Models

2013 ◽  
Vol 26 (18) ◽  
pp. 6801-6843 ◽  
Author(s):  
A. Anav ◽  
P. Friedlingstein ◽  
M. Kidston ◽  
L. Bopp ◽  
P. Ciais ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Climate Models ◽  
Performance Metrics ◽  
Cycle Performance ◽  
Climate Projections ◽  
Seasonal Cycles ◽  
Earth System ◽  
Area Index ◽  
System Models ◽  
Earth System Models

Abstract The authors assess the ability of 18 Earth system models to simulate the land and ocean carbon cycle for the present climate. These models will be used in the next Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) for climate projections, and such evaluation allows identification of the strengths and weaknesses of individual coupled carbon–climate models as well as identification of systematic biases of the models. Results show that models correctly reproduce the main climatic variables controlling the spatial and temporal characteristics of the carbon cycle. The seasonal evolution of the variables under examination is well captured. However, weaknesses appear when reproducing specific fields: in particular, considering the land carbon cycle, a general overestimation of photosynthesis and leaf area index is found for most of the models, while the ocean evaluation shows that quite a few models underestimate the primary production.The authors also propose climate and carbon cycle performance metrics in order to assess whether there is a set of consistently better models for reproducing the carbon cycle. Averaged seasonal cycles and probability density functions (PDFs) calculated from model simulations are compared with the corresponding seasonal cycles and PDFs from different observed datasets. Although the metrics used in this study allow identification of some models as better or worse than the average, the ranking of this study is partially subjective because of the choice of the variables under examination and also can be sensitive to the choice of reference data. In addition, it was found that the model performances show significant regional variations.

scholarly journals The computational future for climate and Earth system models: on the path to petaflop and beyond

2008 ◽  
Vol 367 (1890) ◽  
pp. 833-846 ◽  
Author(s):  
Warren M Washington ◽  
Lawrence Buja ◽  
Anthony Craig
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Ecological Model ◽  
Earth System ◽  
System Models ◽  
Model Components ◽  
Supercomputer Systems ◽  
Physical And Chemical ◽  
Earth System Models

The development of the climate and Earth system models has had a long history, starting with the building of individual atmospheric, ocean, sea ice, land vegetation, biogeochemical, glacial and ecological model components. The early researchers were much aware of the long-term goal of building the Earth system models that would go beyond what is usually included in the climate models by adding interactive biogeochemical interactions. In the early days, the progress was limited by computer capability, as well as by our knowledge of the physical and chemical processes. Over the last few decades, there has been much improved knowledge, better observations for validation and more powerful supercomputer systems that are increasingly meeting the new challenges of comprehensive models. Some of the climate model history will be presented, along with some of the successes and difficulties encountered with present-day supercomputer systems.

scholarly journals Geosystemics and Earthquakes

2018 ◽  
Author(s):  
Angelo De Santis ◽  
Gianfranco Cianchini ◽  
Rita Di Giovambattista ◽  
Cristoforo Abbattista ◽  
Lucilla Alfonsi ◽  
...  
Keyword(s):  
Dynamical System ◽  
Solid Earth ◽  
Case Studies ◽  
Central Italy ◽  
Point Of View ◽  
Earth System ◽  
Complex Dynamical System ◽  
The Earth ◽  
Earth’S Interior

Abstract. Geosystemics (De Santis 2009, 2014) studies the Earth system as a whole focusing on the possible coupling among the Earth layers (the so called geo-layers), and using universal tools to integrate different methods that can be applied to multi-parameter data, often taken on different platforms. Its main objective is to understand the particular phenomenon of interest from a holistic point of view. In this paper we will deal with earthquakes, considered as a long term chain of processes involving, not only the interaction between different components of the Earth’s interior, but also the coupling of the solid earth with the above neutral and ionized atmosphere, and finally culminating with the main rupture along the fault of concern (De Santis et al., 2015a). Some case studies (particular emphasis is given to recent central Italy earthquakes) will be discussed in the frame of the geosystemic approach for better understanding the physics of the underlying complex dynamical system.

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.

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