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NEMO Modelling High Resolution Modelling of the Labrador Sea and Arctic Photo courtesy Department of Fisheries and Oceans Paul G. Myers, Xianmin Hu, Clark Pennelly, Yarisbel Garcia Quintana, Laura Castro de la Guardia, Laura Gillard, Nathan Grivault, Juliana Marson, Charlene Feucher, Natasha Ridenour, Ran Tao, Andrew Hamilton, Liam Buchart Department of Earth and Atmospheric Sciences University of Alberta Ongoing Activities • Use high to very high resolution NEMO modelling configurations to determine (and analyze) processes not included in climate models • 1/12th and 1/60th degree simulations • Role of resolution, representation of eddies • Water mass pathways Ongoing Activities • Use high to very high resolution NEMO modelling configurations to determine (and analyze) processes not included in climate models • 1/4th degree simulations • Air-sea flux products • Vertical resolution and representation of topography • Representation of tides • River runoff representation • Future climate representation Ongoing Activities • Use of the simplified BLING biogeochemical model • Evaluation with observations • Inter-comparison with other biogeochemical models • Comparison with climate models (e.g. CCCMA) • Questions of attribution ANHA: Arctic and Northern Hemisphere Atlantic ANHA12 & ANHA4 Resolution : 1/12 degree LS : ~ 5 km ¼ degree ~ 15 km Model : NEMO 3.4 Mesh : 1632 x 2400 LIM2 + EVP CAA : ~ 4 km 544 x 800 ~10 km 50 levels ANHA12 Initialization: 3D T, S, U and V (GLORYS2v3, Jan02) Sea Ice Atmospheric forcing: T2, Q2, U10, V10 CGRF Precipitation hourly Radiation (SW & LW) 33km Snow: Calculated from precipitation Runoff: Dai and Trenberth inter-annual Greenland Mass Loss (Bamber) + Iceberg Module OBC: U, V, T and S (GLORYS2v3) NO temperature & salinity restoring Jan 2002 – Dec 2019 CGRF: CMC GDPS reforecasts CMC: Canadian Meteorological Centre GDPS: Global Deterministic Prediction System GLORYS: GLobal Ocean ReanalYses and Simulations Horizontal mesh (km) 0 5 10 15 20 25 30 544 AGRIF: Adaptive Grid Refinement In Fortran 1/12° 1/4° Control Grid Box 1144 800 AGRIF Grid Boxes 766 1/12° 616 Simulation ANHA4 ANHA12 AGRIF AGRIF [CAA] [SPG] Horz. 1/4° 1/12° 1/12° 1/12° ° Resolution 1/12 Core years 0.7 37.8 5.3 3.7 709 ANHA4-SPG12-LAB60 “LAB60” NEMO 3.6 75 vertical levels 40s timestep H. Resolution 1/4° 2 way AGRIF nesting No-slip BC in 1/60 nest Atmospheric Forcing: Hourly 33km CGRF 1/12° Monthly runoff (including from Greenland) 1/60° 4 Passive Tracers: -Greenland Melt -Irminger Water -CAA outflow -Labrador Sea Water Pennelly and Myers, 2020 Iceberg module • Bigg et al. [1996, 1997] + modifications Marson et al., 2018 Biogeochemical with Light, Iron, Nutrient limitation and Gases Prognostic BLING v0 BLING Implicit variables BLING BLING tracers* DIC (selected) v0 DIC Fe x x Algae produc. x x PO4 x x Algae biomass x x DOP x x Chl-a x x O2 x x Bio. carbon export x x DIC x (POP) Alkalinity x DIC export x CaCO3 x *The small number of prognostic tracer in BLING allows to go higher in resolution at a relatively low computational cost 10 Mesoscale & Sub-mesoscale Features Weak stratification Pennelly and Myers, 2020 Mesoscale & Sub-mesoscale Features Pennelly and Myers, 2020 Eddy Resolving Power Pennelly and Myers, 2020 # Deformation radii per grid cell ANHA4 ANHA12 LAB60 Cape Farewell Region (Top 50 m) Cape Farewell Region (2005-2014) OSNAP West Section (2005-2014) OSNAP West Section - Variability Dec 2014 Jan 2005 Transports (2005-2014) Section OSNAP Cape OSNAP AR7W Cape East Farewell West Desolation VT (Sv) 0.60 0.45 0.56 0.53 0.42 FWT 34.4 25.8 29.7 28.0 22.2 (mSv) TT (TW) 5.7 4.3 6.6 7.4 6.0 Schematic Maximum Winter Mixed Layer Depth (2004-2009) Pennelly and Myers, 2021, in preparation Pennelly and Myers, 2020 Resulting Labrador Sea Properties Pennelly and Myers, 2020 Subduction Surface Buoyancy change Dataset N/m2s [10-5] DFS -2.1 ERA -1.8 CGRF -1.5 CORE-NCEP -1.5 JRA -2.1 Water volume which permanently passes below the mixed layer= LSW formation Solid bars = subduction via lateral advection Translucent bars = movement of the ML While DFS and JRA have the strongest heat /buoyancy loss, they do not correlate strongly to larger subduction rates. Instead, they correlate strongly with denser Labrador Sea Water Pennelly and Myers, 2020, submitted ANHA4 L50 vs L75 2012-2017 Average Gillard et al., 2020, submitted ANHA4 L50 vs L75 2012-2017 Average Gillard et al., 2020, submitted ANHA4 L75 – CGRF vs DFS5.2 2012-2017 Average Gillard et al., 2020, submitted Sensitivity to River Runoff Stadnyk et al., 2020, submitted Iceberg Discharge Products OLD = Bamber2012 NEW=Bamber2018 Gillard et al., 2021, in preparation The Flagler Bay polynya is a long-standing yet unknown phenomenon • It opens in April remaining ice-free longer than the regular open-water period • Archeological findings indicate the polynya has been a hunting site for thousands of years (Schledermann, 1978) Kane Basin The processes involved in the occurrence of this polynya are currently June 29, 2020 unknown. Three two-way nests were built to explore the Flagler Bay polynya occurrence NARES12 * Color scale represents horizontal resolution, KANE36 expressed in km POLY108 • Integration time: 2002 - 2020 • Initial conditions: GLORYS1V1 • Atmospheric forcing: ERA5 • Open Boundary Conditions: GLORYS1V1 • Vertical levels: 75 • Runoff • Greenland Melt (Bamber et al., 2018) • River runoff (Dai and Trenberth, 2010) Preliminary output: January 10th, 2002 Summary • StrongFeedbacks between Greenland melt, Canadian Arctic Archipelago fluxes and Baffin Bay heat content • Most of CAA freshwater export, plus that from Greenland that enters Baffin Bay exported in Labrador Current passes Labrador Sea convection site • Model does good job of estimating mixed layer depths, but over maybe a too broad region • Net subduction small even if much more water ventilated each year • Icebergs allow more Greenland freshwater to enter interior of the Labrador Sea • Warm Atlantic water penetrating Baffin Bay/CAA, using throughs to get near icesheets and glaciers.
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