Jonathan Whitefield Peter Winsor Tom Weingartner USING IN SITU OBSERVATIONS TO VALIDATE THE PERFORMANCE OF ECCO IN THE ARCTIC SEAS

OUTLINE Model runs used

OUTLINE Model runs used Validation Bering Strait Overview Moorings Point to point comparisons

OUTLINE Model runs used Validation Bering Strait Overview Moorings Point to point comparisons Chukchi Sea Overview Moorings High frequency radar Gliders

OUTLINE Model runs used Validation Bering Strait Overview Moorings Point to point comparisons Chukchi Sea Overview Moorings High frequency radar Gliders Beaufort Sea PMEL wave glider

OUTLINE Model runs used Validation Bering Strait Overview Moorings Point to point comparisons Chukchi Sea Overview Moorings High frequency radar Gliders Beaufort Sea PMEL wave glider Conclusions

MODEL RUNS USED 18km monthly average for 1995 – 2007 (cube78) 18km 3 day average for 1992 – 2012 (cube92)

MODEL RUNS USED 18km monthly average for 1995 – 2007 (cube78) 18km 3 day average for 1992 – 2012 (cube92) 4km Arctic face, 3 day average for month of Aug 2011

MODEL RUNS USED 18km monthly average for 1995 – 2007 (cube78) 18km 3 day average for 1992 – 2012 (cube92) 4km Arctic face, 3 day average for month of Aug 2011

BERING STRAIT – OVERVIEW Bering Strait (BS) is the only gateway between the Pacific and the Arctic Ocean Mean northward transport of ~0.8Sv Estimates from moored instruments Does not capture all of the seasonally present ACC Moorings deployed almost continuously from 1990 to present, recording T, S, and velocity Siberia Alaska Bering Strait A2 mooring

BERING STRAIT Using ~18km spatial resolution model, point to point comparisons of model to instruments made with both monthly and 3 day averages.

BERING STRAIT High correlation between model and observations R > 0.8, p<0.05 for all moorings

BERING STRAIT As the model reproduces the BS throughflow well (V obs ≈ V model ), we can estimate long-term mean transport values including seasonally present ACC. 3 day average (cube92) calculations use different forcing fields to monthly (cube78) calculations. Modelled monthly mean transport increases are at the upper bounds of errors suggested by Woodgate et al (2005). Modelled 3 daily mean transport increases are at the lower bounds of errors suggested by Woodgate et al (2005). PublishedUpdatedIncrease Vol 0.8 Sv0.9 Sv – 1.1 Sv12 – 35% Heat 2.3 x J/yr3.18 – 4.2 x J/yr38 – 80% FW 1700 km 3 /yr2300 – 2700 km 3 /yr35 – 60%

BERING STRAIT Although model reproduces ACC, much of the small scale structure is not reproduced e.g. warmer layer to the west not discerned e.g. no stratification of eastern ACC boundary WE

CHUKCHI SEA – OVERVIEW Most water that flows through BS then crosses shelf in Chukchi Sea Water masses are modified during transit Existence of hydrocarbon lease area increased number of observations Barrow Wainwright Point Lay Beaufort Sea Chukchi Sea Hanna Shoal

CHUKCHI SEA Moorings recently deployed on Hanna Shoal ( ) and at Barrow Canyon head ( ), along with: MetOcean ( ) BOEM (Pickart; ) NSF (Pickart; ) NSF (Okkonen; ) JAMSTEC ( ) Regular CTD surveys in lease patches and along DBO line Barrow Wainwright Point Lay Beaufort Sea Chukchi Sea Hanna Shoal

CHUKCHI SEA UAF HF radar at three points along coast Continuous deployment since 1999 In 2012 operated 5 units along AK coast out of native villages. Doppler shift of scattered pulses yields surface current velocity

CHUKCHI SEA The coastal jet seems to be wind driven, and several modes are seen. Similaritites Off shore flow Minor differences Eddy formed, but in different location Major differences e.g. no reversal of jet Vertical resolution differences? Inaccuracies in forcing? Temporal averaging differences?

CHUKCHI SEA Point Lay Wainwright Barrow Chukchi Sea Hanna Shoal Beaufort Sea

CHUKCHI SEA 1 week subsample from glider and equivalent model grid points Large scale gradient reproduced well (∆T obs ≈ -2°C, ∆T model ≈ -1.75°C) Fine scale thermocline perturbations not seen in model Model shows very little stratification to south Too much vertical mixing/ diffusion (numerical/actual)? SN

BEAUFORT SEA Model severely underestimates depth integrated wave glider temperature by > 5°C at beginning of glider track May be due to seasonally warmer temperatures of Mackenzie River

BEAUFORT SEA River source in model forcing contains seasonal cycle of freshwater/volume input River source in model does NOT contain any variation in temperature

CONCLUSIONS Past observations in the Arctic have been rare, and poor in temporal and spatial resolution. More recent observations with high resolution (e.g. HFR – 6km spatial, 1hr temporal; Glider - <1m vertical, 250m horizontal) have generated data sets that can be used to more critically validate models. Over long periods, and at larger scale, model performs reasonably well when compared to observations.

CONCLUSIONS Model does not reproduce short term events, or small scale spatial variations. Smoothing of fine scale features (e.g. seen in UAF glider temperature, or HFR velocities) may have implications for wind driven mixing, stratification, and circulation.

CONCLUSIONS Key incomplete component is the interaction of large Arctic rivers and their influences on the Arctic shelf. Rivers supply a large fresh water component to the Arctic Ocean, so if forcing data sets do not have correct seasonal cycles, then model could mis- represent marginal ice zones, trapping of solar heating, and melting of sea ice from buoyant plumes. May have implications for modelled heat transport, stratification and ice melt.

ACKNOWLEDGEMENTS Observational/model assistance Dr Rebecca Woodgate (UW/APL) - Bering Strait mooring data Dr Kevin Wood (PMEL) - wave glider data Hank Statsewich (UAF) and Liz Dobbins (UAF) - UAF glider data Rachel Potter (UAF) - HF Radar data Dr Alan Condron (UMass), Dr Dimitris Menemenlis (NASA/JPL) and Dr An Nguyen (MIT) - model output fields. Funding sources BOEM NSF Bering Strait Arctic Observing Network NOAA RUSALCA program