Tamas Kovacs, Rüdiger Gerdes

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Tamas Kovacs, Rüdiger Gerdes POLAR 2018 photo (C) Stephan Hendricks Wind stress forcing in the Arctic and North Atlantic oceans

Motivation LFWC = & - ' S )*+ S dz da./01 S )*+ S )*+ = 35 h = depth of 34 isohaline Arctic Ocean liquid freshwater content increase observed around 10,000 km 3 between 1992-2012 (Rabe et al. 2014) POLAR 2018 Davos, Switzerland 19-23 June 2018 1

Motivation LFWC = & - ' S )*+ S dz da./01 S )*+ S )*+ = 35 h = depth of 34 isohaline Arctic Ocean liquid freshwater content increase observed around 10,000 km 3 between 1992-2012 (Rabe et al. 2014) Anomalies in the Arctic Ocean, and the Subpolar North Atlantic and the Nordic Seas are significantly anti-correlated (95 % confidence). The similar size and the timing of anomalies suggest an oscillation (Horn et al. in review) POLAR 2018 Davos, Switzerland 19-23 June 2018 1

Methods Max Planck Institute Earth System Model Fully coupled MPI-ESM structure of model components (Giorgetta et al., 2013) Low resolution version MPIOM ocean component: - 1.5 horizontal resolution (15-185 km) - poles over Antarctica and Greenland - non eddy-resolving (Jungclaus et al. 2013) POLAR 2018 Davos, Switzerland 19-23 June 2018 2

Methods Modini Thoma et al. 2015 Observations Energy/Momentum MPI-ESM structure of model components (Giorgetta et al., 2013) Partial coupling technique (Thoma et al. 2015) MPIOM driven by prescribed wind stress anomalies Wind stress forcing from NCEPcfsr (Saha et al. 2010) POLAR 2018 Davos, Switzerland 19-23 June 2018 3

Experiment Design Fully coupled control runs with wind speed from coupling (with historical CMIP5 scenario + RCP4.5 from 2006) 1850 2016 POLAR 2018 Davos, Switzerland 19-23 June 2018 4

Experiment Design Fully coupled control runs with wind speed from coupling (with historical CMIP5 scenario + RCP4.5 from 2006) 1850 2016 CTRL x 10 Ensemble generation with lagged initialization POLAR 2018 Davos, Switzerland 19-23 June 2018 4

Experiment Design Fully coupled control runs with wind speed from coupling (with historical CMIP5 scenario + RCP4.5 from 2006) 1850 2016 CTRL x 10 Ensemble generation with lagged initialization Modini runs with external forcing from NCEPcfsr 1850 1979 2016 NCEP x 10 POLAR 2018 Davos, Switzerland 19-23 June 2018 4

Liquid Freshwater Content POLAR 2018 Davos, Switzerland 19-23 June 2018 5

Liquid Freshwater Content Observational data: from PHC3.0 (Steele et al. 2001) POLAR 2018 Davos, Switzerland 19-23 June 2018 5

Liquid Freshwater Content LFWC = & - ' S )*+ S dz da./01 S )*+ h = depth of 34 isohaline S )*+ = 35 h = 2000 m Observations are from Horn et al (in review) POLAR 2018 Davos, Switzerland 19-23 June 2018 6

Freshwater Content Signs of anti-correlation in fully coupled control runs. Large ensemble spread, no sign in recent decades. POLAR 2018 Davos, Switzerland 19-23 June 2018 7

Freshwater Content - Fluxes Most of the variability in the contents can be explained by lateral fluxes POLAR 2018 Davos, Switzerland 19-23 June 2018 8

Drivers of freshwater fluxes POLAR 2018 Davos, Switzerland 19-23 June 2018 9

Drivers of freshwater fluxes Atmospheric forcing plays a role in the variability of freshwater fluxes between the Arctic and the Nordic Seas and the North Atlantic POLAR 2018 Davos, Switzerland 19-23 June 2018 10

Runs with external wind forcing Somewhat reduced bias in Modini runs with NCEP wind forcing Observations are from Horn et al (in review) POLAR 2018 Davos, Switzerland 19-23 June 2018 11

Runs with external wind forcing Dominance of the lateral fluxes, smaller ensemble spread POLAR 2018 Davos, Switzerland 19-23 June 2018 12

Runs with external wind forcing POLAR 2018 Davos, Switzerland 19-23 June 2018 13

Runs with external wind forcing POLAR 2018 Davos, Switzerland 19-23 June 2018 13

Runs with external wind forcing POLAR 2018 Davos, Switzerland 19-23 June 2018 13

Summary Model experiments with the MPI-ESM: fully coupled control runs and partially coupled Modini-MPI-ESM runs with prescribed wind forcing Model resultsare closer to observationsin Modiniruns. Most of the variability can be explained by the lateral fluxes. Smaller ensemblespreadformodiniruns. Limited anti-correlation in fully coupled runs with large ensemble spread. No clear connection in recent decades. Modini runs with prescribed wind forcingshow significantanti-correlation forrecent decades.