Atmospheric Model Intercomparison Project

Atmospheric Model Intercomparison Project
Name	Atmospheric Model Intercomparison Project
Abbreviation	AMIP
Formation	1990
Type	Research project
Headquarters	Princeton University
Region served	Global
Parent organization	World Climate Research Programme

Atmospheric Model Intercomparison Project The Atmospheric Model Intercomparison Project is an international initiative coordinating evaluation of atmospheric general circulation models by prescribing sea surface temperatures and sea ice for standardized simulations. It supports assessment of model performance across time periods and forcings by facilitating comparisons among diverse centers such as National Center for Atmospheric Research, Met Office, NASA, European Centre for Medium-Range Weather Forecasts, and Max Planck Institute for Meteorology. The project underpins multi-model studies linked to intergovernmental assessments like the Intergovernmental Panel on Climate Change and collaborations with programs such as the World Climate Research Programme and the Coupled Model Intercomparison Project.

Overview

AMIP provides a coordinated framework for diagnosing atmospheric behavior in models developed at institutions including Columbia University, ETH Zurich, University of Washington, Scripps Institution of Oceanography, and Geophysical Fluid Dynamics Laboratory. The protocol prescribes observed boundary conditions from observational archives maintained by National Oceanic and Atmospheric Administration, Hadley Centre, and satellite missions operated by European Space Agency and National Aeronautics and Space Administration. By standardizing input datasets and diagnostics, AMIP enables systematic evaluation against reanalyses such as ERA-Interim, NCEP/NCAR Reanalysis, and MERRA and facilitates contributions to assessment reports by United Nations Environment Programme and policy-relevant assessments like IPCC Fifth Assessment Report.

History and Development

The project began in the early 1990s with leadership from researchers at WMO-affiliated programs and modeling groups at Princeton University and NCAR. Early workshops gathered participants from Met Office Hadley Centre, LSCE, GFDL, and CSIRO to define protocols and diagnostics. Subsequent development integrated lessons from experiments conducted at Lawrence Livermore National Laboratory and Los Alamos National Laboratory and drew on observational syntheses from Global Climate Observing System and paleo records used by PAGES. AMIP has evolved alongside initiatives like the Atmospheric Model Intercomparison Project Phase II and coordination with model intercomparison efforts led by IPSL and MPI-M.

Objectives and Design

Primary objectives include quantifying atmospheric model biases, diagnosing process representation, and informing model development at centers such as NOAA, JMA, CMA, KMA, and UK Met Office. The design prescribes observed sea surface temperatures and sea ice from datasets compiled by HadISST, ERSST, and OSTIA and prescribes radiative forcings informed by analyses from IPCC and satellite records from Aqua (satellite), Terra (satellite), and ERS. Standard output formats align with conventions used by CF Convention and data portals hosted by Earth System Grid Federation and ESGF nodes at PCMDI.

Model Experiments and Phases

AMIP experiments are organized into phases with standardized runs spanning historical periods and sensitivity experiments developed by groups at NCAR, GISS, CERFACS, and NOAA GFDL. Phases include control simulations, seasonal hindcasts, and perturbed-forcing experiments coordinated with the Coupled Model Intercomparison Project phases and regional downscaling exercises connected to CORDEX. Specific coordinated experiments have tested aerosol impacts following protocols influenced by AEROCOM and stratospheric chemistry interactions examined in studies involving SPARC.

Key Findings and Scientific Impact

AMIP has revealed robust intermodel differences in precipitation, circulation, and cloud feedbacks identified in multi-model comparisons contributed by IPSL, MIROC, CanESM, ACCESS, and ECMWF. Results have informed attribution studies used by IPCC chapters and influenced parameterization development at NCAR and Met Office. AMIP-based analyses clarified biases in tropical convection, midlatitude storm tracks, and stratosphere–troposphere coupling, informing improvements in representation pursued by Princeton University, Columbia University, and MPI-M teams. Cross-comparisons underpin emergent constraints featured in assessments by National Research Council and guidance for operational centers like JMA and ECMWF.

Participating Models and Institutions

Participants include a broad set of modeling centers and universities: National Center for Atmospheric Research, NASA Goddard Institute for Space Studies, Geophysical Fluid Dynamics Laboratory, Met Office Hadley Centre, Max Planck Institute for Meteorology, Institut Pierre-Simon Laplace, Canadian Centre for Climate Modelling and Analysis, Commonwealth Scientific and Industrial Research Organisation, Tokyo Metropolitan University, Potsdam Institute for Climate Impact Research, University of Reading, and others. Collaboration extends to data and infrastructure providers such as NOAA National Centers, ESGF, PCMDI, and observational archives from National Centers for Environmental Information and Hadley Centre.

Challenges and Future Directions

Challenges include reconciling prescribed boundary conditions with coupled feedbacks explored in CMIP6, reducing model spread in cloud and aerosol responses highlighted by AEROCOM, and integrating higher-resolution convection-permitting models from groups at NCAR and ECMWF. Future directions emphasize coordination with regional initiatives like CORDEX, incorporation of Earth system components represented by CESM and UKESM, and better leveraging of satellite constellations from NOAA, ESA, and private operators. Strengthening links with climate services used by agencies such as UNEP and enhancing data interoperability via ESGF remain priorities.

Category:Climate modeling