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Home » Development of ensemble-based sea ice analysis and forecasting in the Climate Forecast System

Development of ensemble-based sea ice analysis and forecasting in the Climate Forecast System

A unified global forecast system is planned for development at the Environmental Modeling Center (EMC) at NCEP. It will be a fully coupled global system representing the interaction between the Earth’s atmosphere, land, oceans, sea ice, waves, and chemistry. This proposal to the MAPP-CTB (MAPP Competition 1) will develop prototype ensemble Kalman Filter assimilation monitoring and prediction of sea ice properties within the Climate Forecast System (CFS). The proposal addresses the MAPP-CTB 2016 focus area (1b) call for testing of a community standard methodology to improve monitoring and prediction of sea ice conditions and testing of experimental prediction methodologies developed in the broader community.

Sea ice monitoring and forecasting is a crucial activity at the National Weather Service (NWS) because of its impact on seasonal weather and because of its role in environmental and commercial activity at high latitude. The NWS and many other operational centers have traditionally carried out sea ice monitoring and forecasting based on empirical relationships or simplified models combined with human expertise. At EMC this information has until now been used to constrain initial conditions for forecasts using CFS.

As data sets and models have improved many operational centers have begun to include sea ice monitoring and prediction as a component of their weather forecast systems (e.g. Buehner, et al., 2013). This project aims to introduce a sea ice data assimilation capability into the Climate Forecast System, building on the Local Ensemble Transform Kalman Filter (LETKF) assimilation previously applied to the ocean component by Co-I Penny. This proposed LETKF work will be coordinated with the Saha-Penny led efforts, outlined in a separate central data assimilation coupling proposal, to couple all components (aerosol, atmosphere, ocean, sea-ice, land, and waves) in the data assimilation system. The integrated approach is needed in order to generate a balanced state estimate with all other components during the assimilation step.

The primary outcome of this project will include: (a) real-time short-range sea ice analyses and forecasts. This enhancement can be transitioned into NCEP operation as a major NGAC upgrade. (b) A prototype global coupled system with sea ice modeling and data assimilation capabilities. This development is directly aligned with the NWS’s efforts to develop a fully- coupled global modeling and data assimilation system within Next Generation Global Prediction System (NGGPS) and Climate Forecast System version 3 (CFSv3).

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