Modeling Earth System and Human interactions 

 

Overview

Human activities are tightly integrated with the natural functioning of biogeochemical cycles, ecosystems, and the physical climate system. However, most analyses of these systems focus on only one direction of influence: human effects on natural systems, or vice versa. Coupled modeling has the potential to improve understanding of interactions and account for them in integrated analyses. Progress is being made toward a more integrated analysis of human-earth systems, but this progress is uneven, is motivated by a variety of research questions, and is scattered across different communities. The AIMES working group on Modeling Earth System and Human interactions (MESH) will facilitate the development of new methods and scenarios for coupling ESMs, IAMs and other human system models. This working group will bring together diverse communities engaged with integrated and Earth System modeling, foster advances in coupling methods, and stimulate improved use of coupled approaches in analyses. Specific topics include quantifying the magnitude of feedbacks between human and Earth systems, determining strategies for uncertainty and sensitivity analyses, improving consistency between climate representations in different classes of models, and assessing possible approaches to coupled modeling in global scenarios of human-Earth system interactions. Formalizing such feedbacks is a newly emerging field of research.

Objectives and Goals

The main three objectives of the working group on Modeling Human and Earth System interactions (MESH) are to:

  1. Evaluate and quantify bidirectional feedbacks between human and Earth systems.
    What level of complexity is required to evaluate particular human-Earth system feedbacks? Will incorporation of these feedbacks improve knowledge of carbon-climate feedbacks and improve prediction of carbon-climate systems?
  2. Assess methods of coupling human and Earth system models at a global scale.
    What are the pros and cons of human-Earth system model coupling? How can recent advances in decadal climate prediction in Earth system models be used to address socioeconomic and policy-related issues? What methods for linking the Earth system and human system modeling are necessary to accommodate unanticipated disruptions and surprises?
  3. Assess the role of coupled human and Earth system modeling within research and in future assessments of climate change. 
    Will the introduction of such feedbacks alter assessments of what future climate pathways might be plausible? Are all plausible futures conceptually represented in our current models and scenarios?

This working group is led by a group of co-chairs who are responsible for the intellectual leadership of the working group, and this leadership is further benefited by the engagement of a wide range of experts in the Earth system modeling, integrated assessment modeling, human systems modeling, and vulnerability, impacts and adaptation (VIA) communities. To create a cohesive community through which the sum is greater than the parts, the working group will support community building through the organization of meetings, workshops, and webinars. In these activities there will be balanced geographical, gender, career level, and scientific expertise. Products of the working group will be archived on the AIMES website. 

    Governance

    Co-chairs of this working group represent the intellectual leadership responsible for generating ideas; leading and contributing to proposals, papers, and other working group products; and leading and participating in working group events (e.g. online events, meetings, etc.). Additional membership of the working group will be included on an ad hoc basis to fill gaps in expertise in working group activities. In general, this effort is intended to build community and cohesiveness across disciplines that is balanced in terms of gender, career level, and scientific expertise. 

     

      Kate Calvin
      Pacific Northwest Laboratory, USA

      Brian O’Neill
      University of Denver, USA

      Julia Pongratz
      University of Munich; 
      MPI-MGermany

      Ben Sanderson
      CNRS, France

      Detlef van Vuuren
      University of Utrecht, Netherlands