On deeper human dimensions in Earth system analysis and modelling

Abstract. While humanity is altering planet Earth at unprecedented magnitude and speed, representation of the cultural driving factors and their dynamics in models of the Earth system is limited. In this review and perspectives paper, we argue that more or less distinct environmental value sets can be assigned to religion – a deeply embedded feature of human cultures, here defined as collectively shared belief in something sacred. This assertion renders religious theories, practices and actors suitable for studying cultural facets of anthropogenic Earth system change, especially regarding deeper, non-materialistic motivations that ask about humans' self-understanding in the Anthropocene epoch. We sketch a modelling landscape and outline some research primers, encompassing the following elements: (i) extensions of existing Earth system models by quantitative relationships between religious practices and biophysical processes, building on databases that allow for (mathematical) formalisation of such knowledge; (ii) design of new model types that specifically represent religious morals, actors and activities as part of co-evolutionary human–environment dynamics; and (iii) identification of research questions of humanitarian relevance that are underrepresented in purely economic–technocratic modelling and scenario paradigms. While this analysis is by necessity heuristic and semi-cohesive, we hope that it will act as a stimulus for further interdisciplinary and systematic research on the immaterial dimension of humanity's imprint on the Earth system, both qualitatively and quantitatively.

Download Full-text

On deeper human dimensions in Earth system analysis and modelling

10.5194/esd-2017-125 ◽

2018 ◽

Author(s):

Dieter Gerten ◽

Martin Schönfeld ◽

Bernhard Schauberger

Keyword(s):

System Analysis ◽

Human Dimensions ◽

Systematic Research ◽

Earth System ◽

Human Environment ◽

The Earth ◽

Biophysical Processes ◽

Research Questions ◽

Value Sets ◽

Earth System Models

Abstract. While humanity is altering planet Earth at unprecedented magnitude and speed, representation of the cultural driving factors and their dynamics in models of the Earth system is limited. In this review and perspectives paper, we argue that more or less distinct environmental value sets can be assigned to religion – a deeply embedded feature of human cultures, here defined as collectively shared belief in something sacred. This assertion renders religious theories, practices and actors suitable for studying cultural facets of anthropogenic Earth system change, especially regarding deeper, non-materialistic motivations that ask about humans' self-understanding in the Anthropocene epoch. We sketch a modelling landscape and outline some research primers, encompassing the following elements: (i) extensions of existing Earth system models by quantitative relationships between religious practices and biophysical processes, building on databases that allow for (mathematical) formalisation of such knowledge, (ii) design of new model types that specifically represent religious morals, actors and activities as part of coevolutionary human-environment dynamics, and (iii) identification of research questions of humanitarian relevance that are underrepresented in purely economic-technocratic modelling and scenario paradigms. While this analysis is by necessity heuristic and semi-cohesive, we hope that it will act as a stimulus for further, interdisciplinary and systematic research on the immaterial dimension of humanity's imprint on the Earth system, both qualitatively and quantitatively.

Download Full-text

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

Geoscientific Model Development ◽

10.5194/gmd-13-3383-2020 ◽

2020 ◽

Vol 13 (7) ◽

pp. 3383-3438 ◽

Cited By ~ 10

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.

Download Full-text

The Archaeology of Global Environment Change

Humans and the Environment ◽

10.1093/oso/9780199590292.003.0028 ◽

2013 ◽

Cited By ~ 1

Author(s):

Carole L. Crumley

Keyword(s):

Human Activity ◽

Global Environmental Change ◽

Earth System ◽

Human Environment ◽

The Past ◽

The Earth ◽

Global Environmental ◽

Urgent Task ◽

The Two Cultures ◽

Non Linear System

Recent, widely recognized changes in the Earth system are, in effect, changes in the coupled human–environment system. We have entered the Anthropocene, when human activity—along with solar forcing, volcanic activity, precession, and the like—must be considered a component (a ‘driver’) of global environmental change (Crutzen and Stoermer 2000; Levin 1998). The dynamic non-linear system in which we live is not in equilibrium and does not act in a predictable manner (see Fairhead, chapter 16 this volume for further discussion of non-equilibrium ecology). If humankind is to continue to thrive, it is of utmost importance that we identify the ideas and practices that nurture the planet as well as our species. Our best laboratory for this is the past, where long-, medium-, and short-term variables can be identified and their roles evaluated. Perhaps the past is our only laboratory: experimentation requires time we no longer have. Thus the integration of our understanding of human history with that of the Earth system is a timely and urgent task. Archaeologists bring two particularly useful sets of skills to this enterprise: how to collaborate, and how to learn from the past. Archaeology enjoys a long tradition of collaboration with colleagues in both the biophysical sciences and in the humanities to investigate human activity in all planetary environments. Archaeologists work alongside one another in the field, live together in difficult conditions, welcome collaboration with colleagues in other disciplines—and listen to them carefully—and tell compelling stories to an interested public. All are rare skills and precious opportunities. Until recently few practitioners of biophysical, social science, and humanities disciplines had experience in cross-disciplinary collaboration. Many scholars who should be deeply engaged in collaboration to avert disaster (for example, specialists in tropical medicine with their counterparts in land use change) still speak different professional ‘languages’ and have very different traditions of producing information. C. P. Snow, in The Two Cultures (1993 [1959]), was among the first to warn that the very structure of academia was leading to this serious, if unintended, outcome.

Download Full-text

Analytically tractable climate-carbon cycle feedbacks under 21st century anthropogenic forcing

10.5194/esd-2017-78 ◽

2017 ◽

Author(s):

Steven J. Lade ◽

Jonathan F. Donges ◽

Ingo Fetzer ◽

John M. Anderies ◽

Christian Beer ◽

...

Keyword(s):

Carbon Cycle ◽

Model Test ◽

Global Climate ◽

Earth System ◽

Planetary Boundaries ◽

Cycle Model ◽

Carbon Cycle Model ◽

The Earth ◽

Analytical Expressions ◽

Earth System Models

Abstract. Changes to climate-carbon cycle feedbacks may significantly affect the Earth System’s response to greenhouse gas emissions. These feedbacks are usually analysed from numerical output of complex and arguably opaque Earth System Models (ESMs). Here, we construct a stylized global climate-carbon cycle model, test its output against complex ESMs, and investigate the strengths of its climate-carbon cycle feedbacks analytically. The analytical expressions we obtain aid understanding of carbon-cycle feedbacks and the operation of the carbon cycle. We use our results to analytically study the relative strengths of different climate-carbon cycle feedbacks and how they may change in the future, as well as to compare different feedback formalisms. Simple models such as that developed here also provide workbenches for simple but mechanistically based explorations of Earth system processes, such as interactions and feedbacks between the Planetary Boundaries, that are currently too uncertain to be included in complex ESMs.

Download Full-text

Past climates inform our future

Science ◽

10.1126/science.aay3701 ◽

2020 ◽

Vol 370 (6517) ◽

pp. eaay3701

Author(s):

Jessica E. Tierney ◽

Christopher J. Poulsen ◽

Isabel P. Montañez ◽

Tripti Bhattacharya ◽

Ran Feng ◽

...

Keyword(s):

Climate Change ◽

Carbon Dioxide ◽

Model Evaluation ◽

Future Climate Change ◽

Earth System ◽

High Carbon ◽

The Earth ◽

The World ◽

Earth System Models ◽

High Carbon Dioxide

As the world warms, there is a profound need to improve projections of climate change. Although the latest Earth system models offer an unprecedented number of features, fundamental uncertainties continue to cloud our view of the future. Past climates provide the only opportunity to observe how the Earth system responds to high carbon dioxide, underlining a fundamental role for paleoclimatology in constraining future climate change. Here, we review the relevancy of paleoclimate information for climate prediction and discuss the prospects for emerging methodologies to further insights gained from past climates. Advances in proxy methods and interpretations pave the way for the use of past climates for model evaluation—a practice that we argue should be widely adopted.

Download Full-text

On inclusion of water resource management in Earth System models – Part 1: Problem definition and representation of water demand

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-11-8239-2014 ◽

2014 ◽

Vol 11 (7) ◽

pp. 8239-8298 ◽

Cited By ~ 2

Author(s):

A. Nazemi ◽

H. S. Wheater

Keyword(s):

Resource Management ◽

Water Resource ◽

Water Demand ◽

Water Resource Management ◽

Large Scale ◽

Earth System ◽

Water Demands ◽

The Earth ◽

Scale Models ◽

Earth System Models

Abstract. Human activities have caused various changes in the Earth System, and hence, the interconnections between humans and the Earth System should be recognized and reflected in models that simulate the Earth System processes. One key anthropogenic activity is water resource management that determines the dynamics of human–water interactions in time and space. There are various reasons to include water resource management in Earth System models. First, the extent of human water requirements is increasing rapidly at the global scale and it is crucial to analyze the possible imbalance between water demands and supply under various scenarios of climate change and across various temporal and spatial scales. Second, recent observations show that human–water interactions, manifested through water resource management, can substantially alter the terrestrial water cycle, affect land-atmospheric feedbacks and may further interact with climate and contribute to sea-level change. Here, we divide the water resource management into two interdependent elements, related to water demand as well as water supply and allocation. In this paper, we survey the current literature on how various water demands have been included in large-scale models, including Land Surface Schemes and Global Hydrological Models. The available algorithms are classified based on the type of demand, mode of simulation and underlying modeling assumptions. We discuss the pros and cons of available algorithms, address various sources of uncertainty and highlight limitations in current applications. We conclude that current capability of large-scale models in terms of representing human water demands is rather limited, particularly with respect to future projections and online simulations. We argue that current limitations in simulating various human demands and their impact on the Earth System are mainly due to the uncertainties in data support, demand algorithms and large-scale models. To fill these gaps, the available models, algorithms and data for representing various water demands should be systematically tested, intercompared and improved and human water demands should be considered in conjunction with water supply and allocation, particularly in the face of water scarcity and unknown future climate.

Download Full-text

Deep reinforcement learning in World-Earth system models to discover sustainable management strategies

10.5194/egusphere-egu2020-11263 ◽

2020 ◽

Author(s):

Felix Strnad ◽

Wolfram Barfuss ◽

Jonathan Donges ◽

Jobst Heitzig

Keyword(s):

Sustainable Development ◽

Reinforcement Learning ◽

Sustainable Management ◽

System Analysis ◽

Management Strategies ◽

Earth System ◽

Management Options ◽

System Models ◽

The World ◽

Earth System Models

The identification of pathways leading to robust mitigation of dangerous anthropogenic climate change is nowadays of particular interest&#160; not only to the scientific community but also to policy makers and the wider public.&#160;Increasingly complex, non-linear World-Earth system models are used for describing the dynamics of the biophysical Earth system and the socio-economic and socio-cultural World of human societies and their interactions. Identifying pathways towards a sustainable future in these models is a challenging and widely investigated task in the field of climate research and broader Earth system science. &#160;This problem is especially difficult when caring for both environmental limits and social foundations need to be taken into account.In this work, we propose to combine recently developed machine learning techniques, namely deep reinforcement learning (DRL), with classical analysis of trajectories in the World-Earth system as an approach to extend the field of Earth system analysis by a new method. Based on the concept of the agent-environment interface, we develop a method for using a DRL-agent that is able to act and learn in variable manageable environment models of the Earth system in order to discover management strategies for sustainable development.We demonstrate the potential of our framework by applying DRL algorithms to stylized World-Earth system models. The agent can apply management options to an environment, an Earth system model, and learn by rewards provided by the environment. We train our agent with a deep Q-neural network extended by current state-of-the-art algorithms. Conceptually, we thereby explore the feasibility of finding novel global governance policies leading into a safe and just operating space constrained by certain planetary and socio-economic boundaries. &#160;We find that the agent is able to learn novel, previously undiscovered policies that navigate the system into sustainable regions of the underlying conceptual models of the World-Earth system. In particular, the artificially intelligent agent learns that the timing of a specific mix of taxing carbon emissions and subsidies on renewables is of crucial relevance for finding World-Earth system trajectories that are sustainable in the long term. Overall, we show in this work how concepts and tools from artificial intelligence can help to address the current challenges on the way towards sustainable development.Underlying publication[1] Strnad, F. M.; Barfuss, W.; Donges, J. F. & Heitzig, J. Deep reinforcement learning in World-Earth system models to discover sustainable management strategies Chaos: An Interdisciplinary Journal of Nonlinear Science, AIP Publishing LLC, 2019, 29, 123122

Download Full-text

From Domination to a Caring Ecology: Healing Paradigms and Creative Practices for the Apprenticene

Interdisciplinary Journal of Partnership ◽

10.24926/ijps.v4i3.170 ◽

2017 ◽

Vol 4 (3) ◽

Author(s):

Jonee Kulman Brigham

Keyword(s):

Natural Environment ◽

Earth System ◽

Human Environment ◽

Creative Practice ◽

Earth Systems ◽

The Earth ◽

Ecological Principles

This article explores, in four main sections, the idea of designing and applying human-environment paradigms. First, Caring Ecology criteria for human-environment paradigms are proposed that combine the principles of caring in Partnership Studies, with compatible ecological conceptions of humans’ dependent and integrated relationship within Earth systems. Next, these criteria are used to evaluate the strengths and weaknesses of five environmental paradigms which sets the stage for the following section critiquing the current “Anthropocene” paradigm and proposing a counter-paradigm: the “Apprenticene.” Paradigms suggest roles and actions and “Apprenticene Practices” are proposed, calling for humans to see our dependence on Earth systems, heal our story as we accept past failures, and learn by apprenticing ourselves to the Earth system. Finally, these Apprenticene Practices are illustrated in an example of a creative practice called Earth Systems Journey that engages youth with an integrated experience of their human-natural environment. The paper concludes with reflections on how Partnership Studies and ecological principles can work together to support a thriving future for humans and the rest of nature.

Download Full-text

Next generation framework for aquatic modeling of the Earth System

Geoscientific Model Development Discussions ◽

10.5194/gmdd-2-279-2009 ◽

2009 ◽

Vol 2 (1) ◽

pp. 279-307 ◽

Cited By ~ 1

Author(s):

B. M. Fekete ◽

W. M. Wollheim ◽

D. Wisser ◽

C. J. Vörösmarty

Keyword(s):

Model Development ◽

Learning Curves ◽

Earth System ◽

Next Generation ◽

Model Calculations ◽

System Models ◽

The Earth ◽

Wide Range ◽

Spatial Domains ◽

Earth System Models

Abstract. Earth System model development is becoming an increasingly complex task. As scientists attempt to represent the physical and bio-geochemical processes and various feedback mechanisms in unprecedented detail, the models themselves are becoming increasingly complex. At the same time, the complexity of the surrounding IT infrastructure is growing as well. Earth System models must manage a vast amount of data in heterogeneous computing environments. Numerous development efforts are on the way to ease that burden and offer model development platforms that reduce IT challenges and allow scientists to focus on their science. While these new modeling frameworks (e.g. FMS, ESMF, CCA, OpenMI) do provide solutions to many IT challenges (performing input/output, managing space and time, establishing model coupling, etc.), they are still considerably complex and often have steep learning curves. The Next generation Framework for Aquatic Modeling of the Earth System (NextFrAMES, a revised version of FrAMES) have numerous similarities to those developed by other teams, but represents a novel model development paradigm. NextFrAMES is built around a modeling XML that lets modelers to express the overall model structure and provides an API for dynamically linked plugins to represent the processes. The model XML is executed by the NextFrAMES run-time engine that parses the model definition, loads the module plugins, performs the model I/O and executes the model calculations. NextFrAMES has a minimalistic view representing spatial domains and treats every domain (regardless of its layout such as grid, network tree, individual points, polygons, etc.) as vector of objects. NextFrAMES performs computations on multiple domains and interactions between different spatial domains are carried out through couplers. NextFrAMES allows processes to operate at different frequencies by providing rudimentary aggregation and disaggregation facilities. NextFrAMES was designed primarily for hydrological modeling purposes, but many of its functionality should be applicable for a wide range of land surface models. In its present capabilities NextFrAMES is probably inadequate to implement fully coupled Earth System models, but future versions with the guidance from Earth System developers might someday eliminate its limitations. Our intent with NextFrAMES is to initiate a dialog about new ways of expressing models that is less tied to the actual implementation and allow scientist to develop models at a more abstract level.

Download Full-text