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Toward Advanced Understanding and Prediction of Arctic Climate Change Wieslaw Maslowski Naval Postgraduate School

Toward Advanced Understanding and Prediction of Arctic Climate Change Wieslaw Maslowski Naval Postgraduate School. 34th Annual Climate Diagnostics and Prediction Workshop, Monterey, CA, 26-30 October, 2009. Outline. Model predictions of Arctic ice extent

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Toward Advanced Understanding and Prediction of Arctic Climate Change Wieslaw Maslowski Naval Postgraduate School

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  1. Toward Advanced Understanding and Prediction of Arctic Climate Change Wieslaw Maslowski Naval Postgraduate School 34th Annual Climate Diagnostics and Prediction Workshop, Monterey, CA, 26-30 October, 2009

  2. Outline • Model predictions of Arctic ice extent • Trends of melt rates based on Ice extent vice ice thickness and volume • Atmospheric vice Oceanic forcing of local sea ice melt • Future projections of ice melt • Regional Arctic Climate System Model

  3. Observed Rate of Loss Faster Than GCM Predicted SSM/I period Obs 79-00 Mean = 7.0 Mln km2 Adapted from Stroeve et al., 2007 • Wang & Overland, 2009: Ice-free summer Arctic Ocean by 2037 • "A linear increase in heat in the Arctic Ocean will result in a non-linear and accelerating loss of sea ice.“ - Norbert Untersteiner, Prof. Emeritus, Univ. of Washington, July 2006

  4. Observed Arctic sea ice extent (a,b) and modeled sea ice thickness (c,d) during September 1979 (a,c) and 2002 (b,c) 09/79 09/02 Significant decrease in observed sea ice extent (17-20%;top) and in modeled ice thickness (up to 1.5-2.0 m or ~35%;bottom) in the 2000s. Note that largest changes are downstream of Pacific / Atlantic water inflow into the Arctic Ocean. (Maslowski et al., 2007) SSM/I – 2D MODEL - 3D

  5. Observed MY Ice Fraction

  6. Forcing of Arctic sea ice melt • “Atmospheric circulation trends are weak over the record as a whole, suggesting that the long-term retreat of Arctic sea ice since 1979 in all seasons is due to factors other than wind-driven atmospheric thermal advection.” - Deser and Teng, J. Clim. 2008 • Oceanic Forcing can locally play critical role in melting sea ice via: • horizontal advection of warm Pacific / Atlantic water into/under the sea ice cover (e.g. Stroeve and Maslowski, 2007) • Locally induced (upwelling, topographically controlled flow, eddies) upward heat flux into the mixed layer (Maslowski and Clement Kinney, in review, 2009)

  7. 1979-2004 Mean Oceanic Heat Convergence: 0-120 m; Tref = Tfreezing • Modeling Challenges: • Inflow of Pacific / Atlantic • Water into the Arctic Ocean • Pacific Water entering via • narrow (~60mi) Bering Strait • outflow through Fram • Strait vs. Atlantic Water • inflow (FSBW) • Atlantic (BSBW) and Pacific • Water each losses majority • of heat to the atmosphere • before entering Arctic Basin • Arctic ocean-ice-atm feedbacks – not represented realistically in climate models Heat Loss Heat Loss BSBW FSBW Heat Loss Heat Loss High resolution is one of the top requirements for advanced modeling of Arctic climate (Maslowski and Clement Kinney, 2009; Maslowski et al., 2008, Clement et al., 2005)

  8. Modeled Oceanic heat flux exiting the Chukchi Shelf E W Sept. 1984 Heat Flux via Alaska Coastal Current accounts for ~67% of the Total Heat Flux across Chukchi Shelf Line Sept. 2002

  9. Modeled Upper Ocean Heat Content and Ice Thickness Anomalies (Mean Annual Cycle Removed) Heat content accumulated in the sub-surface ocean since mid-1990s explains at least 60% of total sea ice thickness change

  10. Intrusion of oceanic heat into the mixed layer due to anti-cyclonic eddies Temperature above freezing (oC) and velocity (cm/s) is shown in the top four panels. Potential density (σθ) and velocity (cm/s) profiles are shown in the lower four panels. The vertical section locations are shown by the black and red lines, which are across the Chukchi Rise and Eddy 2.

  11. 79-04 time series of Ice Volume, Area, Mean Thickness • Between 1997-2004: • annual mean sea ice • concentration has • decreased by ~17% • mean ice thickness has • decreased by ~0.9 m • or ~36% • ice volume decreased by • 40%, which is ~2.5x the • rate of ice area decrease • If this trend persists the Arctic Ocean will become ice-free by ~2013! Area (x107km2) Mean Thickness (m) Volume (x104km3)

  12. Need for Regional Arctic Climate System Model • There are large errors in global climate system model simulations of the Arctic climate system • Observed rapid changes in Arctic climate system • Sea ice decline • Greenland ice sheet • Temperature • Arctic change has global consequences • Sea ice change can alter the global energy balance and thermohaline circulation

  13. Regional Arctic Climate System Model (RAMC) Participants: Wieslaw Maslowski - Naval Postgraduate School John Cassano - University of Colorado William Gutowski - Iowa State University Dennis Lettenmeier - University of Washington Other collaborators: David Bromwich - OSU Greg Newby, Andrew Roberts, Juaxion He -UAF/IARC/ARSC 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. DOE Climate Change Prediction Program Funded Project

  14. Science Objectives • Perform multi-decadal simulations to: • Gain improved understanding of coupled Arctic climate system processes responsible for changes in • Arctic sea ice cover • hydrologic cycle • freshwater export • Improve predictions of Arctic climate change • Identify limitations and physical and numerical requirements of global climate system model simulations of Arctic

  15. RACM components and resolution • Atmosphere - Polar WRF (gridcell ≤50km) • Land Hydrology – VIC (same as WRF) • Ocean - LANL/POP (gridcell ≤10km) • Sea Ice - LANL/CICE (same as POP) • Flux Coupler – NCAR CPL7 Use NCAR CCSM4 framework for developing RACM Higher component resolutions to be evaluated subject to availability of computer resources

  16. RACM 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)

  17. Accomplishments to Date • 2nd year of 4 year DOE funded project • Coupled individual model components to CPL7 and full RACM testing • Model component evaluation studies • Polar WRF development and climatology • Polar WRF and fractional sea ice • Simulation of sea ice loss with POP/CICE • Oceanic heat transport

  18. Next Steps • Finalize component model / CPL7 coupling • Fully coupled simulations • Evaluation of fully coupled model • Multi-decadal retrospective and future climate simulations • Long-term goals • Regional simulations for next IPCC report • Additional climate system components • Ice sheets • Biogeochemistry

  19. Conclusions • Oceanic heat advection / storage has contributed significant forcing (>60%) to local sea ice melt during the last decade • Ice-edge & shelf/slope upwelling, eddies and other mesoscale circulation features in the Canada Basin provide a mechanism for horizontal heat distribution throughout the basin and up into the mixed layer • Oceanic heat accumulating in the western Arctic is potentially a critical initial factor in reducing ice concentration / thickness before & during the melt season • The rate of melt of sea ice volume possibly much greater than that of sea ice extent • A regional high-resolution Arctic Climate System Model can address these deficiencies and improve predictive skill of climate models

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