FUND model

FUND model
Name	FUND model
Caption	Climate-economics integrated assessment model
Developer	National Center for Atmospheric Research; University of Sussex; others
Introduced	1990s
Latest release	multiple versions (e.g., 3.8)
Language	Fortran, R, Python interfaces
License	Academic

FUND model

The FUND model is an integrated assessment model for estimating socio-economic impacts of climate change and evaluating climate policy. It links geophysical projections from sources such as the IPCC with economic assessments used by institutions like the European Commission and the United Nations to produce damage estimates and social cost metrics. Widely cited in literature involving the Stern Review, the model interfaces with scenarios from the Representative Concentration Pathways and outputs used in analyses by the World Bank and OECD.

Overview

FUND (short for Climate Framework for Uncertainty, Negotiation and Distribution) was developed by researchers affiliated with University of Sussex, National Center for Atmospheric Research, and collaborators including those at Stanford University and Princeton University. It aims to represent heterogeneous impacts across regions such as United States, China, India, Brazil, and European Union members. FUND is one of several integrated assessment models alongside DICE model and PAGE model used in assessments by the Intergovernmental Panel on Climate Change and in policy briefs for bodies like the International Monetary Fund.

Model structure and components

The FUND architecture divides the world into multiple regions (e.g., Africa, Latin America, East Asia, Middle East) and represents modules for climate, impacts, and economic valuation. Core components include a climate module referencing radiative forcing pathways from CMIP ensembles, an impacts module covering sectors such as agriculture (studies from FAO), health (linking to WHO findings), and sea-level rise (drawing on work by NOAA), and an economic aggregation routine used in analyses by the World Trade Organization. FUND incorporates adaptation and mitigation pathways similar to scenario frameworks used by IEA and UNFCCC.

Calibration and input data

Calibration uses historical datasets and empirical studies from institutions like NASA, Met Office Hadley Centre, National Oceanic and Atmospheric Administration, Census Bureau and national statistical agencies. Damage functions are informed by meta-analyses published in journals and reports by Nature, Science, and the Journal of Climate. Socioeconomic input series draw from UN Department of Economic and Social Affairs population projections, World Bank GDP datasets, and scenario assumptions from Shared Socioeconomic Pathways. Calibration also responds to paleoclimate reconstructions and observational records compiled by groups such as the Paleoclimatology Program.

Applications and case studies

FUND has been applied to estimate the social cost of carbon in regulatory contexts used by US Environmental Protection Agency analyses and in policymaking at the European Commission. Case studies include regional impact assessments for Small Island Developing States affected by sea-level rise and storm surge, sectoral analyses for agricultural productivity in Sub-Saharan Africa and Southeast Asia, and health burden studies referencing World Health Organization disability-adjusted life year estimates. Researchers at Harvard University, University of Cambridge, and Columbia University have used FUND outputs in cross-model comparisons with Integrated Assessment Modeling Consortium datasets.

Limitations and critiques

Critiques focus on parametric uncertainty, regional aggregation, and sensitivity to discounting choices debated in contexts involving the Stern Review and work by William Nordhaus. Scholars from Massachusetts Institute of Technology and London School of Economics have highlighted concerns about nonlinear thresholds, tipping points described in research from Woods Hole Oceanographic Institution and Scripps Institution of Oceanography, and limited representation of socio-political feedbacks noted by studies at Princeton University and Yale University. Model structure has been criticized in debates at forums like the Royal Society and during IPCC review processes for oversimplifying migration, conflict, and endogenous technological change discussed in literature from RAND Corporation.

Mathematical formulation and equations

FUND operationalizes damages as regional functions D_r(t) = f(T(t), S_r(t), Y_r(t), P_r(t), A_r(t)), where T(t) denotes global mean temperature trajectory consistent with pathways used in CMIP outputs, S_r represents sea-level rise informed by NOAA projections, Y_r is regional income per capita data from World Bank, P_r population from UN, and A_r adaptation expenditure consistent with scenarios used by the IEA. The social cost of carbon (SCC) is computed from discounted net damages across regions: SCC = Σ_r ∫_t [∂D_r(t)/∂E(t)] · ω_r · exp(-ρ t) dt, where E(t) is emissions, ω_r are regional weights reflecting equity considerations debated in reports by UNFCCC and discount rate ρ follows normative debates involving Stern Review and Nordhaus. Damage sub-functions include empirical parametric forms estimated from econometric studies published in outlets such as American Economic Review and Ecological Economics, while uncertainty is propagated via Monte Carlo sampling techniques used in analyses by National Academy of Sciences.

Category:Integrated assessment models