POC: John Cassano and Annette Rinke

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Presentation transcript:

POC: John Cassano and Annette Rinke Arctic Cordex POC: John Cassano and Annette Rinke 13 Participating Institutes (alphabetically) which run circum-Arctic RCMs AWI Potsdam, Germany CCCma Victoria, Canada Colorado Uni. Boulder, USA DMI Copenhagen, Denmark EMUT Trier, Germany GERICS Hamburg, Germany ISU Iowa, USA Lund Uni. Lund, Sweden MGO St. Petersburg, Russia SMHI Norrköping, Sweden UNI Bergen, Norway Ulg Liège, Belgium UQAM Montreal, Canada Circum-Arctic domain horiz. resol. of 0.44° (ca. 50 km x 50 km)

Activities by 2015 SIMULATIONS Hindcast simulations for model evaluation (ERA-Interim-driven, 1979-2014) 12 atmospheric RCMs finished simulations 5 coupled atmosphere-ice-ocean RCMs finished simulations

ERA-Interim-driven simulations Atmosphere-only models ca. 50 km ca. 25 km ca. 15 km nudging period SMHI RCA4 x w/ and w/o 1980-2010 CCCma CanRCM5 w/ 1979-2014 AWI HIRHAM5 DMI w/o 1989-2011 ULg MAR3.6 MGO RRCM CU/ISU WRF UNI UQAM CRCM5 GERICS REMO (x) EMUT CCLM 2002-2014 (Nov-Apr) Uni Lund RCA4-GUESS 1979-2013 w/ with; w/o without Bold x means “simulation is finished or running”

ERA-Interim-driven simulations Atmosphere-Ocean Models resolution atm.-ocean (km) nudging period status SMHI RCAO 50-25 w/ and w/o 1979-2012 x Uni Lund RCAO-GUESS w/ 1989-2011 CU/ISU RASM 50-9 1989-2015 AWI HIRHAM-NAOSIM w/o 1979-2014 GERICS REMO-MPI-HAMOCC 50-20 DMI HIRHAM-HYCOM 30-20 UNI COAWST w/ with; w/o without Bold x means “simulation is finished or running”

Activities by 2015 SIMULATIONS Future projections (GCM-driven, RCP 8.5 and 4.5, 2006-2100) 6 atmospheric RCMs finished simulations 2 coupled atmosphere-ice-ocean RCMs finished simulations

w/ and w/o for MPI-ESM & EC-Earth; Scenario simulations (RCP8.5; 2006-2100) Atmosphere-only models RCM \GCM CanESM2 NorESM1-M EC-EARTH MPI-ESM-LR nudging SMHI RCA4 x w/ and w/o for MPI-ESM & EC-Earth; w/o for others Uni Lund RCA-GUESS w/o CCCma CanRCM4 w/ AWI HIRHAM5 (x) DMI ULg MAR MGO RRCM UQAM CRCM5 w/o ; (1) UNI WRF GERICS REMO The associated simulations are/will be done for the historical period 1950-2005 w/ with; w/o without Bold x means “simulation is finished or running” (1) w/ and w/o bias-corrected GCM SST and sea-ice

Scenario simulations (RCP8.5; 2006-2100) Atmosphere-Ocean Models RCM\GCM NorESM1-M EC-EARTH MPI-ESM-LR CCSM4 nudging SMHI RCAO x w/ and w/o CU/ISU RASM AWI HIRHAM-NAOSIM w/o GERICS REMO-HAMOCC (x) x (5 ens.) UNI COAWST DMI HIRHAM-HYCOM The associated simulations are/will be done for the historical period 1950-2005 w/ with; w/o without Bold x means “simulation is finished or running”

Analysis Activities Individual model results: nudging, added value, extremes, validation, climate change,… Multi-model analysis has been initiated and started: General skill & across-model scatter (temperature, precipitation, wind; Adakudlu et al.) Extremes (temperature, precipitation; Matthes et al., Königk et al., Diaconescu et al.) Precipitation and snowfall (Rinke et al.) Cyclone activity incl. polar lows (Akperov et al.) Gas exchange in the Arctic seas (Shkolnik et al.) Ocean (upper ocean T & S structure), sea-ice production & volume (Maslowski et al.) Atmosphere-sea ice interactions (Königk et al., Rinke et al.)

Planned activities in 2016 and beyond SIMULATIONS Future projections (CMIP5-GCM-driven, RCP 8.5, 2006-2100) 10 atmospheric RCMs: downscaling of 4 GCMs by 4 RCMs; 4 coupled RCMs simulation model developments & process understanding Higher resolution (circum-Arctic and/or subdomains?) – some (25, 12, 5 km) has been done CMIP6 downscaling ANALYSIS Continuation of multi-model analysis including also Extreme weather events (wind, waves, cyclones, temperature & hydrolog. extremes) Ocean structure (upper ocean heat content, surface mixed layer, eddies) & sea-ice processes (thickness distribution, deformation, export) Vegetation-biogeochemical feedbacks ….

Possible interactions with other projects CliC (SIMIP, Sea ice & Climate Model.Forum/Arctic Sea Ice Working Group) & FAMOS - support for our work on coupled Arctic RCMs - benefit from observational data for the evaluation/improvement of sea-ice simulation - learn from tuning sea-ice models Role of Arctic Cordex output for off-line models & IAV - Regional Arctic ocean model (Steiner et al.) - Ice sheet models; ISMIP (e.g. Greenland: DMI ,Ulg) - Hydrology (e.g. Siberia: Skolnik et al., Grenier et al.)