NOAA's NCEP Climate Forecast System

NOAA's NCEP Climate Forecast System
Name	NOAA's NCEP Climate Forecast System
Agency	National Oceanic and Atmospheric Administration
Center	National Centers for Environmental Prediction
Country	United States
Established	2003
Type	Climate prediction system

Contents

NOAA's NCEP Climate Forecast System is a coupled climate model and operational forecasting system developed and run by National Oceanic and Atmospheric Administration's National Centers for Environmental Prediction for seasonal to interannual prediction. It integrates atmospheric, oceanic, land, and sea ice components to produce retrospective analyses, operational forecasts, and reanalyses used by agencies including the National Weather Service, International Research Institute for Climate and Society, and World Meteorological Organization. The system underpins national and international products supporting stakeholders such as the United Nations agencies, European Centre for Medium-Range Weather Forecasts, and regional centers across Africa, Asia, and South America.

Overview

The Climate Forecast System (CFS) couples models developed by organizations like the Geophysical Fluid Dynamics Laboratory, NOAA Geophysical Fluid Dynamics Laboratory, and collaborators at University of Maryland, University of Washington, and Columbia University to predict climate variability driven by phenomena such as El Niño–Southern Oscillation, North Atlantic Oscillation, and Pacific Decadal Oscillation. CFS outputs inform seasonal outlooks for temperature, precipitation, and extremes used by Federal Emergency Management Agency, Department of Defense (United States), and agricultural agencies including the United States Department of Agriculture. The framework interacts with observing networks such as Argo (oceanography), Global Precipitation Measurement, and satellite missions like NOAA-20, Suomi NPP, and Landsat.

CFS architecture couples an atmospheric general circulation model derived from the Global Forecast System, an ocean model based on the Modular Ocean Model, a land surface model related to NOAH Land Surface Model, and a sea-ice model influenced by schemes used at Hadley Centre and Canadian Meteorological Centre. Numerical cores leverage dynamical cores and parameterizations that trace lineage to models at NASA Goddard Institute for Space Studies, Jet Propulsion Laboratory, and Princeton University. Model components exchange fluxes and states on coupled interfaces employing schemes influenced by research at Scripps Institution of Oceanography, Woods Hole Oceanographic Institution, and Lamont–Doherty Earth Observatory. Resolution, ensemble generation, and initialization practices reflect best practices used at European Centre for Medium-Range Weather Forecasts and Met Office.

Initialization uses multivariate data assimilation methods integrating observations from Advanced Microwave Scanning Radiometer, Scatterometer, radiosonde networks such as Integrated Global Radiosonde Archive, and satellite radiances assimilated with techniques pioneered at National Aeronautics and Space Administration and European Space Agency. Ocean initialization employs Argo (oceanography) floats, TAO/Triton moorings, and historical ship-based hydrographic data from programs including World Ocean Database. Land and sea-ice states draw on products from National Snow and Ice Data Center, Global Soil Moisture Active Passive missions, and reanalyses like ERA-Interim and MERRA. Observational tie-ins enable coupling with platforms supported by National Geophysical Data Center and international initiatives such as Global Climate Observing System.

Operational outputs include ensemble seasonal forecasts of surface temperature, precipitation, soil moisture, and sea surface temperature used by National Centers for Environmental Prediction, Climate Prediction Center, Agricultural Research Service, and public health agencies like Centers for Disease Control and Prevention. Downscaled and bias-corrected derivatives support stakeholders in California, India, Brazil, and Australia for water-resource management, agriculture, and disaster preparedness coordinated with entities such as United Nations Development Programme and regional bodies like Association of Southeast Asian Nations. CFS products feed into multimodel frameworks, informing assessments by Intergovernmental Panel on Climate Change, World Bank, and insurance markets in London and New York City.

Verification against independent observations and reanalyses such as ERA5, JRA-55, and NCEP/NCAR Reanalysis indicates skill in predicting prominent modes like El Niño–Southern Oscillation and seasonal temperature anomalies but reduced skill for regional precipitation extremes and subseasonal variability. Performance metrics use standardized measures applied by World Meteorological Organization and research groups at National Center for Atmospheric Research, Princeton University, and Massachusetts Institute of Technology. Limitations derive from biases noted in studies by Scripps Institution of Oceanography and University of California, Los Angeles, including drift in coupled states, sensitivity to observational sparsity in regions like the Southern Ocean and Tropical Atlantic, and computational constraints faced by centers such as Los Alamos National Laboratory and Oak Ridge National Laboratory.

CFS evolution traces to operational initiatives at National Centers for Environmental Prediction and collaborative research funded by National Science Foundation, National Aeronautics and Space Administration, and international partners. Major upgrades produced generations like CFSv1 and CFSv2 with contributions from teams at Geophysical Fluid Dynamics Laboratory, NOAA Geophysical Fluid Dynamics Laboratory, University Corporation for Atmospheric Research, and Princeton University. Improvements incorporated advances in data assimilation from Joint Centre for Satellite Data Assimilation, higher-resolution modeling inspired by European Centre for Medium-Range Weather Forecasts research, and coupling strategies influenced by work at Centre National de Recherches Météorologiques and Canadian Centre for Climate Modelling and Analysis. Ongoing modernization aligns with initiatives by Office of Science and Technology Policy and interagency computational upgrades similar to procurements at Department of Energy facilities.

Category:Climate models