Regional Arctic Climate System Model (RACM) – Project Overview

Participants:Wieslaw Maslowski (PI) - Naval Postgraduate SchoolJohn Cassano (co-PI) - University of ColoradoWilliam Gutowski (co-PI) - Iowa State UniversityDennis Lettenmeier (co-PI) - University of Washington

Greg Newby, Andrew Roberts, - Arctic Region Supercomputing Juanxiang He, Anton Kulchitsky Center

Dave Bromwich and Keith Hines (OSU), Gabriele Jost (HPCMO),Tony Craig (NCAR), Jaromir Jakacki (IOPAN), Mark Seefeldt (CU), Chenmei Zhu (UW), Justin Glisan Brandon Fisel (ISU), Jaclyn Kinney

(NPS)

A 4-year (2007-2010) DOE / SciDAC-CCPP project

IARC / Arctic System Model Workshop, Boulder, CO, May 19-21, 2008IARC / Arctic System Model Workshop, Boulder, CO, May 19-21, 2008

Specific Goals• develop a state-of-the-art Regional Arctic Climate system

Model (RACM) including high-resolution atmosphere, ocean, sea ice, and land hydrology components

• perform multi-decadal numerical experiments using high performance computers to understand feedbacks, minimize uncertainties, and fundamentally improve predictions of climate change in the pan-Arctic region

• provide guidance to field observations and to GCMs on required improvements of future climate change simulations in the Arctic

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.

Main science objective

Regional Arctic climate modelcomponents and resolution

• Atmosphere - Polar WRF (gridcell ≤50km)

• Land Hydrology – VIC (gridcell ≤50km)

• Sea Ice – CICE/CSIM (gridcell ≤10km)

• Ocean - POP (gridcell ≤10km)

• Flux Coupler – CCSM/CPL7

RACM domain and elevations(red box represents the domain of ocean and sea ice models)

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)

Why develop a regional Arctic climate model?

1. Facilitate focused regional studies of the Arctic

2. Resolve critical details of land elevation, coastline and ocean bottom bathymetry

3. Improve representation of local physical processes and feedbacks (e.g. forcing and deformation of sea ice)

4. Minimize uncertainties and improve predictions of climate change in the pan-Arctic region

Arctic Sea Ice cover in September 2002

Comparison of sea ice conditions in September 2002

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NCAR/CCSM3 case (b30.040b) prediction of summer ice-free Arctic by 2050

CCSM3(b) simulates too much ice on the Greenland shelf (1), too much/little melt in the eastern(2) / western(3) Arctic.

Comparison of areal sea ice fluxes through Fram Strait

-CCSM3 sea ice export about twice as high as compared toKwok et al. (2003) and NPS/NAME fluxes

- Possibly too strong atmospheric forcing at Fram Strait- Consequences include

- too much ice production in the Arctic Ocean- overestimate of buoyancy flux into the North Atlantic

CCSM3(b) NPS/NAME

In Out Net In Out Net

Fram Strait

2.0/17 -6.9/ -23 -4.9/ -6 6.0/45 -8.4/ -36 -2.4/ +9

Barents Sea

Opening4.8/115 -0.3/ -5 4.5/110 5.0/107 -1.8/ -28 3.2/79

FJL-NZ 4.7/32 -0.35/ -1 4.35/31 3.4/2.9 -0.8/ -0.7 2.6/2.2

25-year mean ocean volume transport (Sv) / heat transport (TW)Note: 1Sv = 10 m6/sec; 1TW = 3.6 Petajoules/hour or 86.4 Petajoules/day or 2592 Petajoules/month

NPS/NAME TRANSPORTS (Maslowski et al., JGR, 2004)Fram Strait ‘in’ obs estimates: 7.0 Sv / 50 TW - Courtesy of A. Beszczynska-Möller, AWIFJL-NZ: near-zero heat transport (Gammelsrod et al., JMS submitted)

OCEAN BATHYMETRY/RESOLUTION IMPACTSOCEAN BATHYMETRY/RESOLUTION IMPACTSOCEAN BATHYMETRY/RESOLUTION IMPACTSOCEAN BATHYMETRY/RESOLUTION IMPACTS

• Barents Sea outflows (north of Novaya Zemlya and through Kara Gate) look similar but:Barents Sea outflows (north of Novaya Zemlya and through Kara Gate) look similar but:• Mean paths significantly different due to representation of bathymetry (I.e. resolution)Mean paths significantly different due to representation of bathymetry (I.e. resolution)• Velocity magnitudes differencesVelocity magnitudes differences• 9-km model circulation shown to match observed well 9-km model circulation shown to match observed well (Maslowski et al., 2004)(Maslowski et al., 2004)

• Implications for location of fronts, water mass transformations, heat and salt balancesImplications for location of fronts, water mass transformations, heat and salt balances(from Maslowski et al., 2008)(from Maslowski et al., 2008)

18-km Model18-km Model0-225 m (levels 1-7), every vector0-225 m (levels 1-7), every vector

9-km Model9-km Model0-223 m (levels 1-15), every 20-223 m (levels 1-15), every 2ndnd vector vector

• Increased horizontal resolution allows for improved representation of topography

• Topography impacts atmospheric circulation, precipitation, temperature, etc.

• ERA40 precipitation (above) is “smoothed” compared to higher resolution (50 km) Polar MM5 simulation (right)

• This will impact both atmosphere and land/ocean

ERA40 Annual Precipitation

Polar MM5 Annual Precipitation

ERA40 Annual Precipitation

LAND TOPOGRAPHY / RESOLUTION IMPACTSLAND TOPOGRAPHY / RESOLUTION IMPACTSLAND TOPOGRAPHY / RESOLUTION IMPACTSLAND TOPOGRAPHY / RESOLUTION IMPACTS

Cyclone Central Pressure and Size• Model resolution impacts the size and intensity of cyclones• Comparison of AMPS ( 20 km; based on Polar MM5 and

WRF) and three coarser reanalyses in the Southern Ocean• AMPS simulates lower pressure in and smaller cyclones

than all reanalyses• Similar results are expected in Arctic

Wetlands

Finer resolution captures dispersed features missed by coarse grids

Gutowski et al. (2007)

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500 hPa RMSD vs. Standard

WET10WET30LBCLLBCSICLICS

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Day

Unforced

“noise”

Wetlands cases

RMS Difference vs. Baseline (500 hPa Heights)

• Long-term streamflow changes (Peterson et al., 2002) are not captured by model in permafrost basins (particularly in discontinuous permafrost).

• Reasons include improper permanent ground ice initialization and lack of tracking.

Attribution of observed trends in Eurasian Arctic river runoff: Why don’t model reconstructed trends match observations?

(Visuals courtesy of Jennifer Adam, Washington State University)

High Quality GHCNPrecipitation Stations

High Quality GHCN Temperature Stations

• Improvements to the VIC frozen soils algorithm to handle permafrost are underway.

Sea Ice Divergence near SHEBA Tower (Stern &

Moritz, 2002)

Ice strain (reds/yellows)

(200km x 200 km)

1. Evaluate uncoupled model simulations for physical and numerical optimizations in RACM

2. Couple each climate model component to the coupler (CPL7)

3. Run and validate results as in #2

4. Couple all climate model components and run tests with RACM

RACM 2008-2009 OutlookRACM 2008-2009 Outlook

Movie of Daily Sea Ice Divergence