Decadal Climate Prediction Project

Decadal Climate Prediction Project
Name	Decadal Climate Prediction Project
Formation	2010s
Headquarters	Geneva
Parent organization	World Climate Research Programme

Decadal Climate Prediction Project is an international coordination initiative within the World Climate Research Programme that supports climate prediction on timescales of about one to thirty years. The project brings together Intergovernmental Panel on Climate Change, World Meteorological Organization, National Aeronautics and Space Administration, European Centre for Medium-Range Weather Forecasts, and multiple national National Oceanic and Atmospheric Administration centers to develop standards for initialized decadal forecasts and seamless climate projections. It interfaces with operational agencies such as Met Office, research institutions like Scripps Institution of Oceanography, and regional bodies such as the European Union climate services.

Overview

The initiative coordinates multinational efforts across United States, United Kingdom, France, Germany, Japan, China, Australia, Canada, India, and South Africa to produce coordinated decadal ensembles using coupled atmosphere–ocean–land–sea ice models such as ECMWF Integrated Forecasting System, Hadley Centre Global Environment Model, and Community Earth System Model. It aligns with international assessment activities including the IPCC Fifth Assessment Report, IPCC Sixth Assessment Report, and programs such as Coupled Model Intercomparison Project to standardize protocols for initialized prediction experiments. Partner organizations include the European Centre for Medium-Range Weather Forecasts, NOAA Geophysical Fluid Dynamics Laboratory, NASA Goddard Institute for Space Studies, National Institute of Water and Atmospheric Research, Max Planck Institute for Meteorology, and university groups at University of Oxford, Massachusetts Institute of Technology, and Potsdam Institute for Climate Impact Research.

Objectives and Scope

Primary objectives include improving forecast skill for multi-year climate variations linked to phenomena like the El Niño–Southern Oscillation, Atlantic Multidecadal Variability, Pacific Decadal Oscillation, and interactions with anthropogenic forcing assessed by the Intergovernmental Panel on Climate Change. The project seeks to develop common initialization strategies, ensemble design, and verification frameworks compatible with the Coupled Model Intercomparison Project Phase 6 and to produce coordinated datasets used by World Weather Watch services, regional European Commission adaptation programs, and national planning authorities including United States Congress advisory offices. Scope covers global to regional predictions, supporting sectors such as Food and Agriculture Organization, International Energy Agency, and World Health Organization for adaptation planning.

Methods and Models

Methods emphasize initialized coupled model hindcasts and forecasts using systems like the EC-Earth family, GFDL CM4, UK Met Office HadGEM3, and CESM2 with ensemble approaches inspired by Ensemble Kalman filter techniques and data assimilation frameworks such as those used at ECMWF and NOAA NCEP. Model development draws on advances from the Coupled Model Intercomparison Project, the Climate Model Intercomparison Project, and numerical schemes pioneered at institutions like Princeton University and Imperial College London. Experiment design follows protocols developed by panels including the WCRP Grand Challenge groups and is informed by paleoclimate constraints from archives curated at Smithsonian Institution and British Antarctic Survey.

Observational Data and Initialization

Initialization strategies use ocean reanalyses (e.g., ORA-S4, GECCO2), atmospheric reanalyses such as ERA5, MERRA-2, JRA-55, and observational syntheses from Argo (oceanography) floats, TOGA records, and satellite missions from European Space Agency, NASA, and Japan Aerospace Exploration Agency. Coupled initialization incorporates datasets maintained by National Centers for Environmental Information and Hadley Centre. Quality control and bias correction use methods aligned with standards from International Arctic Science Committee and data stewardship practices advocated by Global Climate Observing System. Teams from NOAA, CSIR, CNRS, and CSIRO contribute to observational evaluation.

Skill Assessment and Verification

Verification employs metrics from the World Meteorological Organization and approaches described in IPCC Assessment Reports, including anomaly correlation, mean square skill score, and probabilistic metrics used by European Centre for Medium-Range Weather Forecasts and National Oceanic and Atmospheric Administration. Skill attribution links predictable signals to modes like North Atlantic Oscillation, Indian Ocean Dipole, and Southern Annular Mode and is benchmarked against uninitialized simulations from CMIP6 ensembles. Independent validation datasets come from HadISST, Global Precipitation Climatology Project, and long-term instrumental records curated at National Oceanography Centre. Outcomes feed into decision-support tools used by United Nations Environment Programme and national climate services.

Applications and Policy Relevance

Forecast products inform adaptation planning by organizations such as the World Bank, Asian Development Bank, and national agencies including US Army Corps of Engineers and Ministry of Defence (United Kingdom). Sectors benefiting include agriculture programs run by Food and Agriculture Organization, water resource management by agencies like Bureau of Reclamation (United States), energy planners at International Renewable Energy Agency, and insurance firms coordinating with Geneva Association. The project supports policy processes under the United Nations Framework Convention on Climate Change and contributes evidence used in national climate assessments such as those produced by U.S. Global Change Research Program and UK Climate Change Committee.

Challenges and Future Directions

Key challenges include initialization shocks, model bias adjustment, limited observational coverage in regions managed by institutions like Antarctic Treaty Secretariat, and computational demands met by supercomputing centers such as Oak Ridge National Laboratory, NERSC, and PRACE infrastructure. Future directions emphasize improved ocean–atmosphere coupling, machine learning integration with efforts at Google DeepMind, enhanced regional downscaling for the Caribbean Community, and stronger links to impact modeling used by Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. Continued coordination with CMIP7 initiatives, expanded data sharing through GEOSS, and collaboration with private-sector weather services like The Weather Company are priorities.

Category:Climate research Category:Earth system science