Research in Integrated Assessment Inter-Model Comparison Development, Testing, and Diagnostics

award: DOE Grant DE-SC005171

active: 2010–2017

principal investigator: John Weyant (Stanford)

PCHES-IAMDDI was a community research project focused on Integrated Assessment Model (IAM) development, diagnostics, and inter-comparisons. PCHES-IAMDDI (previoiusly known as “PIAMDDI”) was the first major DOE-funded project of the PCHES research consoritium. The project’s research focused on the areas of:

  • science and technology
  • impacts and adaptation
  • regional integrated assessment modeling
  • key energy-related intersecting systems
  • uncertainty

PCHES-IAMDDI was dedicated to improving the science of integrated assessment by performing cutting-edge research in critical areas of IAM development. The program then further integrated that research with model inter-comparison and IAM scenario ensemble construction activities. The project has been very closely linked to other climate change research programs in the U.S. and abroad, which kept it responsive to the needs of the IAM community, highly transparent, accessible, and credible. Each research area, as well as the model comparison and ensemble construction work, was broken down to fundamental principals to help set focused priorities for the individual research efforts.

The first three years of work focused on:

  • advancing progress on selected major scientific challenges in the field of integrated assessment
  • advancing methods and capabilities for inter-model testing and diagnostics
  • enhancing capabilities for multi-model, “ensemble-like” analyses for improved insights in science studies and science-based analyses

Through this we identified three major focus areas for the last two years of the project:

  • integrated climate change impacts assessment
  • integrated assessment model component emulation
  • characterizing and representing uncertainty

The essence of PCHES-IAMDDI was in organizing and executing parallel efforts and research coordination which requires bringing researchers, research communities, and disciplines together in productive ways that aimed to improve the whole integrated assessment modeling community.