Ensemble simulations with a Regional Earth System Model of the Arctic CLIMARES WP 110 Ensemble simulations with a Regional Earth System Model of the Arctic Klaus Dethloff, Annette Rinke, Wolfgang Dorn Alfred Wegener Institute of Polar and Marine Research, Research Unit Potsdam, (AWI) Planing Meeting, 21. Oktober 2009, Bergen 1

Main objective: develop coupled Earth system models of the Arctic at the regional scale based on data: comprising regional atmospheric models with improved feedbacks and significantly increased resolution coupling to ocean, sea ice, land, soil, vegetation, chemistry, aerosols and ... These models need to be set-up: provided with adequate parameterizations validated in order to describe past, ongoing and future regional climate changes in spatial and temporal details needed for different scientific & managerial applications, Northern Sea routes Soil Vegetation Sea ice 2

Arctic Planetary Boundary Layer and Clouds Science Issues requiring special attention in Arctic regional and global models Arctic Planetary Boundary Layer and Clouds Snow and Land-Surface Processes Arctic Sea Ice Arctic Aerosols Arctic Ozone (Tropo-Stratosphere) Ocean dynamics and THC Carbon and Methane Cycles Horizontal and vertical resolution Arctic vegetation systems Glaciers

Polar 5 Measurements PAM-ARCMIP - ROUTE (30.03. - 28.04.2009) Pan Arctic Measurements and Arctic Regional Climate Model Intercom. Proj.

Polar 5 Measurements PAM-ARCMIP - ROUTE (30.03. - 28.04.2009)

Sea ice thickness with POLAR5, Courtesy of C. Haas, Flight to NP 36.

Flight to NP 36. Polar 5 on NP 36 11. April 2009

Structure of the shallow stable APBL

RESM results are sensitive to the choice of the integration domain, lateral and lower boundary conditions, horizontal and vertical resolution, parameterizations. Regionally coupled models of the climate system and improved data sets can contribute to the attribution of ongoing changes. Development of new ideas (e.g. sea ice albedo, organic soil layer) for improving global models in the Arctic. Two-way feedbacks has to be considered within a global model setup by regionally focused modelling of the area of interest.

Arctic components of the Earth system, © Dethloff 2009 Aerosols Clouds Momentum Heat Water CH4 CO2 H L Run-off Tracer Ozone O Sea ice Ocean currents 10

Synthesis of the regional model results will enable us to Objectives: Synthesis of the regional model results will enable us to to understand recent regional climate changes through simulation and validation, to distinguish variability arising from Arctic-internal processes and externally forced variability, to carry out ensemble modelling of future regional climate changes over the Arctic Ocean, to reduce uncertainties of climate projections for the Arctic Ocean. 11

Relative importance of internal versus external processes  Coupled Regional Atmosphere-Ocean-Sea Ice Model of the Arctic Sea ice is an integrator of oceanic and atmospheric changes Atmosphere model HIRHAM parallelized version 110×100 grid points horizontal resolution 0.5° 19 vertical levels Ocean–ice model NAOSIM based on MOM-2 Elastic-Viscous Plastic ice dynamics 242×169 grid points horizontal resolution 0.25° 30 vertical levels Boundary forcing ERA-40 or NCEP 12

Coupled regional Atmosphere-Ocean-Sea Ice Model

Standard deviation of sea ice concentration (%) Satellite observations Coupled model simulations Importance of internal (mainly atmospheric) variability in Arctic system Standard deviation of sea ice concentration (%) September 1988-2000, spin up time: 1980-1987, Dorn et al. 2007 14

(June-September) between “high-ice” minus “low-ice” years (1988-2000) Differences in September sea level pressure (hPa) and ice drift vectors (June-September) between “high-ice” minus “low-ice” years (1988-2000) High-ice years are 1996, 1988, 1992, and 1994 in the observation and 1989, 1996, 1988, and 1997 in simulation, Low-ice years are 1995, 1990, 1999, and 2000 in the observation and 1992, 1999, 1993, and 1991 in simulation. Influence of summertime atmospheric circulation on sea ice drift Cyclonic ice drift pattern during high-ice years Anticyclonic ice drift pattern during low-ice year Dorn et al. , Open Atmos. Sci. J. , 2, 2008

Sensitivity experiments over the Arctic Ocean Simulations from Dec Sensitivity experiments over the Arctic Ocean Simulations from Dec. 1997- Dec. 1998  Improved descriptions for sea ice growth, sea ice albedo parameterization and snow cover parameterization, Dorn, Dethloff, Rinke, Ocean Modelling 2009, 29, 103-114.

Arctic Sea-Ice Extent, Dec. 1997-1998, Sensitivity Exp. Already after one year there are model deviations in ice volume of up to 4500 km3 (one third of the total volume) as a result of altered sea ice- snow albedo parameterizations.

Sea-Ice Thickness (m), September 1998

Mean seasonal cycle of net surface heat flux (W/m2) over the Arctic Ocean north of 70 ° N June Summer surface heat fluxes depends on parameterization schemes for ice growth, sea ice albedo and snow cover Importance of regional A-O-I feedbacks during the summer months Changes in atmospheric static stability impact on baroclinic systems

Simulations with atmospheric and coupled A-O-I models for future scenarios over the Arctic Change in 2m air temperature [°C]. Colors show the changes "SCEN minus CTRL", isoline the present-day "CTRL". Change in seasonal mean. The difference is significant at the 95th significance level for all grid points. Change in seasonal standard deviation. The dotted areas represent the 95% significance., Rinke, Dethloff, 2008. 20

Milestones: Improved sea ice and related feedbacks in an Arctic coupled A-O-I model. Improved parameterizations of ice growth and onset of snow melt, of sea ice albedo, of snow cover and melt ponds Analysis of factors for reproducing observed recent sea ice variability in an Arctic coupled Earth system model. Ensemble of coupled RCM simulations to assess coupled feedbacks in the atmosphere-ice-ocean system. Ensemble of uncoupled and coupled RCM simulations for future climate scenarios, until 2030 and until 2010. 21

Work plan Realization of multi-decadal-long regional model simulations 1948-2009 with the pure atmospheric HIRHAM and the coupled model system HIRHAM-NAOSIM. Validation of regional model results in comparison with observations and identification of model deficiencies. Improvements of feedbacks within the coupled Arctic climate system with respect to sea-ice and snow. Ensemble simulations for future climate time slices with HIRHAM (Until 2030 and 2100) and HIRHAM-NAOSIM (until 2030 with different ocean-sea ice initial states). Quantification of the impact of Arctic processes on projections of the future climate and Arctic passages based on GESM ECHAM-OM1 simulations Estimation of the relative importance of regional processes inside the Arctic climate system and the large scale atmospheric circulation for the inter-annual climate variability of sea ice cover. 22

Deliverables of coupled Arctic RCMs: atmospheric component mean sea level pressure surface temperature / 2-m temperature surface fluxes (sensible and latent heat fluxes, short-wave and long-wave radiative fluxes) surface wind stress cloud cover precipitation

Deliverables of coupled Arctic RCMs: ocean ‒ ice component ice concentration ice thickness snow thickness (+ snow cover fraction) mixed layer temperature (+ salinity) ice drift velocity upper ocean current Manpower: 2 PhD student positions

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Improved parameterization schemes ICE GROWTH PARAMETERIZATION: Old scheme: Melting of ice did not occur until the snow layer has disappeared Snow disappeared too earlyleading to earlier ice melt since the albedo of a snow free sea-ice cover is higherdecreased energy input occured  and thus lower ice melt. New scheme: Possibility of ice melt even if snow layer is present  Improved onset of snow melting  More realistic representation of the two stage snow-albedo/ ice-albedo feedback  improved simulation of summer maximum in net short-wave radiative flux and the net surface heat flux

SEA ICE ALBEDO PARAMETERIZATION: In Reality: Albedo of sea ice depends on overlying snow cover, ice age, ice thickness, brine volume, melt ponds Albedo of snow depends on grain size, affected by snow age, contamination of snow by aerosol particles Albedo is affected by angle of incident solar radiation and clouds Old scheme: Model albedo a linear parameterization function of the ice/snow surface temperature New scheme: (Køltzow et al., 2007) 3 different surface types (snow covered ice, bare sea-ice, melt ponds and leads) Stronger surface temperature dependent linear scheme Reduced albedo for melting conditions, if snow already disappeared.

SNOW COVER PARAMETERIZATION: New scheme: This new snow cover scheme does not allow the formation of melt ponds as long as the snow cover is still thick New snow cover fraction on sea ice as a function of snow thickness described by a tanh approach  Validation against SHEBA measurements Important for the initiation of the snow melt period in summer The onset of ice decay and its strength depend on the time of disappearance of the snow layer If snow fraction is too low, melt ponds can form earlier with the result of amplified melting further reduction of snow cover and too early beginning of sea ice retreat If melt ponds are neglected albedo in summer is too high, leading to underestimated net surface heat fluxes and insufficient loss of ice during the melting period

Improved ice growth scheme

Improved ice albedo parameterization

Improved snow cover parameterization