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Understanding Variations of Volume & Freshwater Fluxes through CAA: Potential Application in Projecting Future Changes Youyu Lu, Simon Higginson, Shannon.

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Presentation on theme: "Understanding Variations of Volume & Freshwater Fluxes through CAA: Potential Application in Projecting Future Changes Youyu Lu, Simon Higginson, Shannon."— Presentation transcript:

1 Understanding Variations of Volume & Freshwater Fluxes through CAA: Potential Application in Projecting Future Changes Youyu Lu, Simon Higginson, Shannon Nudds Bedford Institute of Oceanography, DFO

2 Arctic-North Atlantic Interaction (from G Holloway) Focusing on NW Atlantic: Key for global “conveyor belt” Freshwater inputs important for deep convection Two routes: east or west of Greenland – which one is more important?

3 Monitoring at Key Locations (DFO Involved)

4 CAA Not Resolved by Climate Models (due to complicated small-scale geometry)

5 An Approach to Forecasting/Projecting Long-term Changes in CAA 1.High-resolution simulations – limited duration 2.Analysis to understand forcing mechanisms 3.Derive statistical relationship with large-scale forcing 4.Forecasting/projecting with outputs of large-scale forcing from climate models This combined dynamical + statistical approach can be applied to a wide range of problems

6 NEMO Configurations: BIO pan-Arctic Pan-Arctic 18 km grids; also include nested CAA 6 km grids; Pan-Arctic 6 km Grid spacing nearly uniform

7 Validation Example: Sea-ice Drift Model vs Ice Buoy June 1999 December 1999

8 Sea-ice Drift: Model vs Ice Buoy June 1999 December 1999

9 Volume Fluxes Through CAA High correlation between BIO 6 km Arctic model & GLORYS v2 global ocean reanalysis

10 Freshwater Fluxes Through CAA Less correlated than volume flux – due to difference in salinity field. Needs further validation/study.

11 Mean Fluxes during 1998-2007 LocationModelVolume Flux (Sv) FW Flux (mSv) FW Flux Ice (mSv) Nares StraitGlorys2v10.79 (0.27) 10.17 (3.90)3.34 (3.29) Arctic 6km1.14 (0.56)25.05 (12.57)5.48 (5.01) Lancaster SoundGlorys2v11.31 (0.23)61.40 (12.62)6.63 (3.85) Arctic 6km0.98 (0.32) 45.60 (11.79)7.30 (5.07) Barrow StraitGlorys2v11.42 (0.27)65.20 (17.31)7.45 (5.14) Arctic 6km1.15 (0.35)54.93 (15.00)9.33 (6.57) Davis StraitGlorys2v12.43 (0.55) 55.62 (16.27)13.53 (14.65) Arctic 6km2.07 (0.80) 71.28 (12.67)12.91 (14.25) Fram StraitGlorys2v11.73 (0.96)5.70 (4.50)69.57 (40.29) Arctic 6km1.62 (1.57)19.85 (10.36)22.23 (18.53) Indeed, FW transport from CAA is larger than that from east of Greenland.

12 What drives Fluxes Through CAA? Upstream influence – wind in Beaufort Sea (Peterson et al)

13 What drives Fluxes Through CAA? Downstream influence – Sea level in Baffin Bay (McGeehan & Maslowski 2012)

14 Analysis of 6 km Model: Seasonal Cycle in Barrow Strait Model agrees quite well with obs at southern side

15 Seasonal Cycle in Davis Strait Clear difference between western & eastern sides

16 Seasonal Cycle in Fram Strait Clear difference between western & eastern sides

17 Seasonal Cycles of Volume & FW Fluxes

18 Further Work Analyze correlation with forcing Determine how forcings operate: barotropic or baroclinic processes? Develop regression models: link flux variations to large-scale forcing

19 Summary Model results suggest that freshwater transport though CAA is larger than that from east of Greenland Two forcing mechanisms (up- & down-stream) have been proposed by previous studies. This analysis suggests that both mechanisms operate – depending on seasons & locations Understanding mechanisms may help to develop regression models: linking CAA transports to large- scale forcing This combined dynamical + statistical approach can help climate projection, and is useful for solving a lot of other problems


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