CLIMARES WP 110 Climate model scenarios for the Arctic region for the next decades Current state: Klaus Dethloff, AWI WP Leader: Erich Roeckner, MPI Planing Meeting, 21. Oktober 2009, Bergen

Palmer et al. BAMS 2008 Climate feedbacks and chains, Palmer et al., BAMS, 2008

Main objective: GESM and RESM with special focus on improvements in the Arctic based on data:  comprising global and regional atmospheric models with improved feedbacks and significantly increased resolution  coupling to ocean, sea ice, land, soil, vegetation, chemistry, aerosols etc. 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 Sea ice Vegetation Soil

Measurements and process studies, RESM and GESM

Relative importance of sources of uncertainty (total, scenario, model physics, internal variability) in decadal mean surface temperature projections. Fractional uncertainty (the 90% confidence level divided by the mean prediction) for the British Isles mean, relative to the warming from the 1971–2000 mean.  The importance of model uncertainty is visible for all policy relevant timescales.  Internal variability grows in importance for the smaller region  Added value of RCM Sources of uncertainties in decadal surface temperature prediction Hawkins & Sutton, BAMS 2009

Momentum, Energy, H 2 O, CO 2 Land HD JSBACH Atmosphere ECHAM6 T63/L47 T159/L95 Solar variations Volcanic aerosol CO 2 emissions Natural forcing Anthropogenic forcing Land use change CH 4, N 2 O, CFC conc. Ocean MPIOM 1°/L40 0.4°/L80 HAMOCC MPI - IPCC AR5 Earth System Model

OCEAN (dynamics and physics) NEMO/ORCA2 (Barnier et al. 2006) SEA-ICE: LIM (Timmermann et al. 2005) ATMOSPHERE (dynamics, physics, prescribed gases and aerosols) ECHAM5 T159 - L31 Roeckner et al. (2006) T63-L95 (stratosphere resolving) (Manzini et al. 2006) COUPLER Oasis 3 Valcke et al. (2004) COUPLER Heat Flux Water Flux Momentum Flux Global Atmosphere Global Ocean & Sea-Ice SST Sea-ice The high resolution CMCC-MODEL High-resolution, short-term (decadal) prediction experiments

Aerosols Clouds Momentum Heat Water CH 4 CO 2 H L H H Run-off Tracer Ozone O OO Sea ice Ocean currents Arctic components of the Earth system, © Dethloff 2009

Regional climate model, Arctic integration area High horizontal resolution, improved simulation of hydrodynamical instabilities and baroclinic cyclones GCM (ERA40) RCM HIRHAM, 25 or 50 km Initial & boundary conditions for the RCM provided by ERA40 data (m)

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

WP 110: Topics and Contributors MPI : Global climate simulations and new sea ice model in ECHAM5-OM1, E. Roeckner CMCC : Short term climate change projections with a GESM, S. Gualdi AWI : Ensemble simulations with a regional ESM of the Arctic, K. Dethloff MGO : Ensemble simulation of regional climate in the Arctic, V. Meleshko AARI : Boundary layer over and under sea ice for improved parameterizations, ??? RIHMI- WDC : Meteorol. & oceanog. data sets for verification of climate models, N. Michailov MMBI : Bio-oceanological data bases, D. Moisseev GEUS : Use of paleoclimatic data for modelling future scenarios, N. Mikkelsen