Meeting
2016 SIPN Workshop
Presentation Type
plenary
Presentation Theme
Predictions and Dynamical Predictive Systems II
Abstract Authors

E. Joseph Metzger, Naval Research Laboratory, joe.metzger [at] nrlssc.navy.mil
Pamela Posey, Naval Research Laboratory, pam.posey [at] nrlssc.navy.mil
Alan Wallcraft, Naval Research Laboratory, alan.wallcraft [at] nrlssc.navy.mil
Michael Phelps, Jacobs Technology, michael.phelps.ctr [at] nrlssc.navy.mil

Abstract

For several years the Naval Research Laboratory has participated in the Sea Ice Outlook (SIO) to predict the Arctic September minimum sea ice extent. In earlier years these forecasts used the regional Arctic Cap Nowcast/Forecast System, but have more recently used the Global Ocean Forecast System (GOFS) 3.1, which is comprised of the two-way coupled Community Ice CodE (CICE) and the HYbrid Coordinate Ocean Model (HYCOM). The horizontal resolution is ~3.5 km near the North Pole and the system runs daily in pre-operational mode at the Naval Oceanographic Office assimilating satellite ice concentration data. Using ice and ocean initial conditions from this data-assimilative system at the appropriate start date, the ice/ocean models are integrated in forecast mode through October 1st. Atmospheric forcing is from the National Centers for Environmental Prediction Climate Forecast System Reanalysis (CFSR) for the years 2005-2014. This ensemble of 10 members gives an indication of how sea ice can respond to variable atmospheric conditions during summer and the projected sea ice extent for September is the average across all ensemble members. Each year’s forecast ice concentration bias is pre-determined by comparing a non-assimilative GOFS forecast with a data-assimilative GOFS hindcast. Monthly ice concentration error is translated into a monthly heat flux offset that is added to the net surface heat flux during the final SIO forecasts. This methodology has proven effective in reducing GOFS forecast ice concentration biases.

Time
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