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  1. Home
  3. Iam-fire: A Climate Emulator-based Framework To Project Wildfire Impacts And Risks For Integrated Assessment Models.
  1. Home
  3. Iam-fire: A Climate Emulator-based Framework To Project Wildfire Impacts And Risks For Integrated Assessment Models.

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Published on: June 30, 2020

IAM-FIRE: A Climate Emulator-Based Framework to Project Wildfire Impacts and Risks for Integrated Assessment Models.

Théo Rouhette1,2, Dirk-Jan Van de Ven2, Kanishka Narayan3

  • 1Institute of Environmental Science and Technology (ICTA), Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain.

Global Change Biology
|June 19, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

Integrated Assessment Models often underestimate wildfire impacts, affecting carbon sink estimates. The new IAM-FIRE framework projects wildfire burned area and carbon emissions, revealing significant future variations based on socioeconomic and emissions scenarios.

Keywords:
burned areaclimate changeclimate emulatorsearth system modelsfire carbon emissionsintegrated assessment modelssocioeconomic developmentwildfires

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06:27

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12:44

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Published on: July 24, 2016

Area of Science:

  • Climate Science and Earth System Modeling
  • Environmental Science and Ecology
  • Carbon Cycle and Land-Use Change

Background:

  • Integrated Assessment Models (IAMs) frequently underestimate dynamic feedbacks from climate-driven disturbances like wildfires.
  • This underrepresentation can lead to an overestimation of the permanence of land-based carbon sinks.
  • Forest fires are projected to intensify, making their accurate representation in models increasingly critical.

Purpose of the Study:

  • To introduce IAM-FIRE (Integrated Assessment Model-Fire Impacts & Risks Emulator), a novel framework for projecting wildfire burned area (BA) and carbon emissions (CE).
  • To enable direct projection of wildfire impacts from IAM outputs under various socioeconomic and emissions scenarios.
  • To facilitate systematic exploration of fire-climate-land feedbacks and improve assessments of mitigation permanence and climate risks.

Main Methods:

  • IAM-FIRE integrates a spatial climate emulator, land-use downscaling, vegetation productivity modeling, and an empirical fire model.
  • The framework generates global annual wildfire impacts at 0.5° resolution for 2020-2100.
  • Model calibration was performed against GFEDv5 observations, using Global Change Analysis Model (GCAM) outputs for four Shared Socioeconomic Pathways (SSPs).

Main Results:

  • IAM-FIRE accurately reproduces historical global trends in total and forest burned area, including the recent observed decline.
  • Projected total burned area by 2100 varies significantly across scenarios, from 441 Mha/year (SSP1-2.6) to 794 Mha/year (SSP3-6.6).
  • Projected total carbon emissions by 2100 range from 1.8 PgC/year (SSP1-2.6) to 3.6 PgC/year (SSP5-7.6), showing substantial divergence.
  • Socioeconomic development primarily suppresses wildfire impacts, while climate change and CO2-driven vegetation growth amplify fire risk.

Conclusions:

  • IAM-FIRE demonstrates greater sensitivity to radiative forcing and a stronger role for human fire suppression compared to CMIP6 and FireMIP models.
  • The study highlights structural uncertainties in current wildfire projections.
  • The developed framework provides a crucial tool for understanding future fire dynamics and their implications for climate change mitigation and risk assessment.