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Participants: Wieslaw Maslowski (PI) - Naval Postgraduate School

Towards Advanced Understanding and Predictive Capability of Climate Change in the Arctic using a High-Resolution Regional Arctic Climate System Model (RAMC) – an overview. Participants: Wieslaw Maslowski (PI) - Naval Postgraduate School John Cassano (co-PI) - University of Colorado

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Participants: Wieslaw Maslowski (PI) - Naval Postgraduate School

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  1. Towards Advanced Understanding andPredictive Capability of Climate Changein the Arcticusing a High-ResolutionRegional Arctic Climate System Model (RAMC) – an overview Participants: Wieslaw Maslowski (PI) - Naval Postgraduate School John Cassano (co-PI) - University of Colorado William Gutowski (co-PI) - Iowa State University Dennis Lettenmeier (co-PI) - University of Washington Sponsor: DOE Climate Change Prediction Program (CCPP) Period of Performance: 09/01/2007 - 08/31/2011

  2. Rationale Changes in the Arctic sea ice cover have significant ramifications to the entire region and beyond, including: • Ocean thermohaline circulation • Heat / energy budget • Climate • Ecosystems • Native communities • Natural resource exploration • Commercial transportation

  3. Rationale - continued 1. Global climate models have errors in representing northward fluxes of heat and moisture, sea ice distribution, and export of freshwater into the North Atlantic. Those parameters control both regional Arctic and global climate variability and their realistic representation requires dedicated high-resolution modeling studies and it is critical to improved climate predictions 2. Existing regional Arctic models do not account for important sea-ice-atmosphere-land-hydrology feedbacks as they typically simulate either the atmospheric state using simplified lower boundary conditions for the ice/ocean or predict ice-ocean variability using prescribed atmospheric forcing. 3. A Regional high-resolution Arctic Climate system Model (RACM), can address these deficiencies and improve predictive skill of climate models. High resolution is defined as of order 10-km or less for ice/ocean and 50-km or less for atmosphere/land/hydrology components.

  4. Primary science objective To synthesize understanding of past and present states and thus improve decadal to centennial prediction of future Arctic climate and its influence on global climate.

  5. Specific objectives Determine and quantify the coupled Arctic climate system processes responsible for the recent observed and future projected changes in the ice pack, regional hydrological cycle, and freshwater export into the North Atlantic Assess decadal system scenarios of a seasonally / partially ice free Arctic Ocean, including their timing Address the general circulation model (GCM) limitations in predicting Arctic climate through the identification of physical and numerical requirements of future GCMs

  6. Implementation • Develop a state-of-the-art Regional Arctic Climate system Model (RACM) including high-resolution state-of-the-art atmosphere, ocean, sea ice, and land hydrology components and • Perform multi-decadal numerical experiments using high performance computers to minimize uncertainties and fundamentally improve current predictions of climate change in the northern polar regions

  7. Proposed climate modelcomponents and resolution • Atmosphere - Polar WRF (gridcell ≤50km) • Land Hydrology - VIC / CLM / Noah (≤50km) • Sea Ice - LANL/CICE (gridcell ≤10km) • Ocean - LANL/POP (gridcell ≤10km) • Flux Coupler(based on NCAR/CCSM global model coupler)

  8. (red box represents the domain of ocean and sea ice models) Proposed Arctic climate system model domain and elevations • Pan-Arctic region to include: • all sea ice covered ocean in the northern hemisphere • Arctic river drainage • critical inter-ocean exchange and transport • large-scale atmospheric weather patterns (AO, NAO, PDO)

  9. Proposed Work Proceed in three overlapping phases: • Climate system component studies via one-way coupling experiments (conducted under existing complementary funding) • Development of the Regional Arctic Climate System Model (RACM) • Physical feedback and future scenarios studies focusing on changes in Arctic sea ice using the fully coupled model

  10. Research Questions The primary research questions focus on the central role of the Arctic Ocean’s sea ice as a mediator in atmosphere-ocean interaction and as a sensitive indicator of Arctic climate-system change • What have been the main ocean / sea ice / atmosphere processes and Arctic system feedbacks that have led to the observed retreat of Arctic sea ice cover over the past 50 years? • What effect will the retreat of sea ice cover and warming of the upper ocean through 2007 have on atmospheric circulation and fluxes? How will these changes to the atmosphere feedback to further modify the ocean and sea ice state of the Arctic? • What is the relative control of the lower latitude variability (as defined along our regional model lateral boundaries) compared to the internal system interactions within the Arctic? • Can the retreat of the Arctic ice pack pass a tipping point that propels summer ice cover to complete collapse? • If so, how long will it take to arrive at a seasonally ice free Arctic Ocean and what physical processes will be responsible for moving the Arctic towards this new state? • If not, what changes are needed to reverse the present trend of sea ice retreat?

  11. Planned Coupled RACM Model Experiments • ERA40/ECMWF atmospheric initial/lateral boundary conditions and ocean/sea ice restarted from end of 48-year spin up with PHC lateral boundary conditions (1958-2007) with 1/12o ocean/ice and 50-km atmosphere/land models • Four future climate scenarios with ‘near-future’, ‘warm’, ‘cold’, and ‘neutral’ lateral boundary forcing data from GCM output (25-year simulation for each scenario restarted from end of 1 and configured the same as in 1)

  12. Computational resource requirements1. ARSC - FY08 allocation- Platform: Sun Cluster (Midnight)- FY08: 1 Mln proc-hrs2. DOE/INCITE proposal (pending)- Platform: Cray XT4 (Jaguar) at DOE/ORNL- Year 1: 3 Mln proc-hrs- Year 2: 4 Mln proc-hrs- Year 3: 4 Mln proc-hrs

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