Toward GELATO6 in EC-Earth3 V. Guemas, D. Salas-Mélia, M. Chevallier Picture from Matthieu Chevallier Toward GELATO6 in EC-Earth3 Melanie IC3 CFU S2d probabilistic forecasting using GCM ensemble approach FP7 projects – Environment, call for European s2d forecasts towards climate services. Climate services term from WMO GFCS. My role My background V. Guemas, D. Salas-Mélia, M. Chevallier virginie.guemas@ic3.cat, david.salas@meteo.fr, matthieu.chevallier@meteo.fr

A multi-category sea ice model since 1996 Number of categories to be selected in GELATO namelist Melting c, h c1 c3 c*2/3, h*2/3 GELATO LIM3 CICE h1 h3 Ocean grid cell Thin ice is more sensitive to thermodynamic forcing : thin ice melts faster and also grows faster, thermodynamic equations are solved for each thickness category, ice which grows or melts is transferred to another category, GELATO is a multi-category ice model since 1996 when its development started Melanie IC3 CFU S2d probabilistic forecasting using GCM ensemble approach FP7 projects – Environment, call for European s2d forecasts towards climate services. Climate services term from WMO GFCS. My role My background c c h/2 h Sea ice grid cell LIM2 c => concentration, h => thickness

GELATO in CNRM-CM since 1999 ARPEGE-climat atmosphere model Number of categories to be selected in GELATO namelist ARPEGE-climat atmosphere model Distribution within GELATO GELATO is used is coupled mode with multiple ice categories since 1999. Repartition of the heat fluxes sent by the atmosphere mode to the various ice categories within GELATO, number of sea ice categories to be selected in the namelist through a single parameter, a simulation with a new number of categories should be started from rest, the sea ice restarts produced contain the dynamic and thermodynamic information for each category. Melanie IC3 CFU S2d probabilistic forecasting using GCM ensemble approach FP7 projects – Environment, call for European s2d forecasts towards climate services. Climate services term from WMO GFCS. My role My background NEMO

History of GELATO development Old history: Development of Gelato (multi-category model) initiated in 1996 Dynamics + redistribution by rafting and ridging (1998) Coupling with OPA (1998) and ARPEGE-Climat (1999) Elastic-Viscous-Plastic = EVP rheology (2000) + incremental remapping (2002), Hunke & Dukowicz (1997) CMIP5 (2009-2010): many new developments Interactive prognostic salinity Salt uptake : follows Cox and Weeks (1988) Desalination processes adapted from Vancoppenolle et al., O. Mod. (2009) Enthalpy model H = H(T,S) and Cp=Cp(T,S) Vertical Heat Diffusion (VHD) Ice thermal conductivity k is a function of T,S (Pringle et al., 2007) Revised snow albedo (adapted from Curry et al. (2001)) New tracers can now easily be added : sea ice age COMBINE (2011-2012) Development of a surface melt pond scheme Multi-category model since 1996, run in coupled mode since 1999, EVP since 2000, each slab of ice is divided in 9 vertical layers to resolve the equations for thermodynamics and there is an additional layer for snow on top, explicit treatment of melt pond thermodynamics and dynamics since 2012 Melanie IC3 CFU S2d probabilistic forecasting using GCM ensemble approach FP7 projects – Environment, call for European s2d forecasts towards climate services. Climate services term from WMO GFCS. My role My background

GELATO surface scheme Melt ponds + snow + ice albedo Explicit resolution of melt ponds Melt ponds advected Snow Melt ponds are explicitly resolved which is not the case in CICE or LIM3: A volume V of melt ponds can be melt under thermodynamic forcings. The melt pond formed can be advected. From the volume V a parameterisation provides the depth, fraction and albedo. Melanie IC3 CFU S2d probabilistic forecasting using GCM ensemble approach FP7 projects – Environment, call for European s2d forecasts towards climate services. Climate services term from WMO GFCS. My role My background drainage Salinity profile NEMO

Use in forced mode embedded into NEMO Chevallier et al 2013 GELATO6 has already been tested in NEMO forced by DFS4.3, ERA-interim and CORE atmospheric forcings at ORCA1 configuration. Lindsay : mooring, upward looking sonar, Air-EM, ICESAT Melanie IC3 CFU S2d probabilistic forecasting using GCM ensemble approach FP7 projects – Environment, call for European s2d forecasts towards climate services. Climate services term from WMO GFCS. My role My background Validation sea ice thickness against Lindsay (2010) Bias : -0.14 to -0.46 m RMSE : 0.64 to 1m Correlation : 0.71 to 0.83 GELATO tested with DFS4.3, ERA-interim, CORE forcings

Use in coupled mode within CNRM-CM Performance : 4min/year with 4 nodes (48 procs) on BULL in ORCA1 CMIP5 : 9000 years of simulation within CNRM-CM5 (Voldoire et al 2013) performed at CNRM Decadal prediction activities: 3000 years of simulation performed at CERFACS (Germe et al 2014) Seasonal prediction : best skill scores (Chevallier and Salas y Mélia 2012, Chevallier et al 2013) Melanie IC3 CFU S2d probabilistic forecasting using GCM ensemble approach FP7 projects – Environment, call for European s2d forecasts towards climate services. Climate services term from WMO GFCS. My role My background Estimation of CPU for GELATO : several simulation calling GELATO at different frequencies Ensemble mean Correlation skill: CNRM-CM5 : 0.6 CFSv2 : 0.4 CanSIPS < 0.2 Observations Ensemble range

Toward an operational use for weather prediction SURFEX is a surface model used operationally in Numerical Weather Prediction by the HIRLAM European consortium Melanie IC3 CFU S2d probabilistic forecasting using GCM ensemble approach FP7 projects – Environment, call for European s2d forecasts towards climate services. Climate services term from WMO GFCS. My role My background GELATO has been included in the next release of SURFEX crucial for weather prediction in Northern Europe

The developers David Salas y Mélia : Matthieu Chevallier : Aurore Voldoire : Stéphane Sénési : Virginie Guemas : Initial developer and leader of the current development team Validation and inclusion of new processes 1D tests, technical aspects (portability on different platforms, parallelisation …) Inclusion in EC-Earth Melanie IC3 CFU S2d probabilistic forecasting using GCM ensemble approach FP7 projects – Environment, call for European s2d forecasts towards climate services. Climate services term from WMO GFCS. My role My background

In NEMO3.3.1-stand-alone from EC-Earth3.0.1 ORCA1 Melanie IC3 CFU S2d probabilistic forecasting using GCM ensemble approach FP7 projects – Environment, call for European s2d forecasts towards climate services. Climate services term from WMO GFCS. My role My background

Timeline Next month: Evaluating GELATO6.0.47 within NEMO3.3.1 from EC-Earth3.0.1 in the ORCA025 stand-alone configuration Testing GELATO6.0.47 within EC-Earth3.0.1 in coupled mode in configuration ORCA1 Melanie IC3 CFU S2d probabilistic forecasting using GCM ensemble approach FP7 projects – Environment, call for European s2d forecasts towards climate services. Climate services term from WMO GFCS. My role My background Later: Testing and evaluation GELATO6.0.47 within EC-Earth3.0.1 coupled mode in configuration ORCA025

Thanks a lot for you attention Any question to be directed to: virginie.guemas@ic3.cat, david.salas@meteo.fr, matthieu.chevallier@meteo.fr Melanie IC3 CFU S2d probabilistic forecasting using GCM ensemble approach FP7 projects – Environment, call for European s2d forecasts towards climate services. Climate services term from WMO GFCS. My role My background