Physically Consistent Eddy-resolving State Estimation and Prediction of the Coupled Pan-Arctic Climate System at Daily to Interannual Time Scales Using the Regional Arctic Climate Model (RACM)

• Main Authors: Maslowski, Wieslaw, Roberts, Andrew, Cassano, John, Hughes, Mimi
• Other Authors: NAVAL POSTGRADUATE SCHOOL MONTEREY CA DEPT OF OCEANOGRAPHY
• Format: Text
• Language: English
• Published: 2014
• Subjects: Meteorology; Snow; Ice and Permafrost; *CLIMATE; ARCTIC REGIONS; ATMOSPHERE MODELS; DAILY OCCURRENCE; ESTIMATES; PREDICTIONS; SEA ICE; SEASONAL VARIATIONS; Arctic; Ice; permafrost; Sea ice
• Online Access: http://www.dtic.mil/docs/citations/ADA616458; http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA616458

This project targets some of the key requirements in the Navy Arctic Roadmap 2014-2030 and in the 2014 Implementation Plan for the National Strategy for the Arctic Region, regarding the need for advanced modeling capabilities for operational forecasting and strategic climate predictions through 2030. The proposed research leverages ongoing developments of the state-of-the-art Regional Arctic System Model (RASM, previously called Regional Arctic Climate Model - RACM) through a multiinstitutional program supported by the Department of Energy Regional and Global Climate Modeling (DOE/RGCM) program and two ongoing complementary projects. This project is aimed at improved modeling of the atmosphere-ice-ocean interface to advance representation of the past and present state of the Arctic Climate System and prediction of its future states at time scales from daily (operational) through seasonal, interannual, and up to decadal (tactical). We use the Regional Arctic System Model (RASM) to extend the Navy sea ice predictive capability beyond the current forecasts of up to 7-day (provided by the Arctic Cap Nowcast/Forecast System (ACNFS) at NRL), to seasonal and up to decadal climate projections. Three main objectives are to (i) advance understanding and model representation of critical physical processes and feedbacks of importance to sea ice thickness and area distribution using a combination of forward modeling and state estimation techniques, (ii) investigate the relation between the upperocean heat content and sea ice volume change and its potential feedback in amplifying ice melt, (iii) upgrade RASM with the above improvements to advance both operational and tactical prediction of arctic climate using a single model.