Abstract
Free drift estimates of sea ice motion are necessary to produce a seamless observational record combining buoy and satellite-derived sea ice motion vectors. We develop a new parameterization for the free drift of sea ice based on wind forcing, wind turning angle, sea ice state variables (concentration and thickness) and ocean current (as a residual). Building on the fact that the spatially varying standard wind-ice transfer coefficient (considering only surface wind stress) has a structure as the spatial distribution of sea ice thickness, we introduce a wind-ice transfer coefficient that scales linearly with thickness. Results show a mean error of −0.5 cm/s (low-speed bias) and a root-mean-square error of 5.1 cm/s, considering daily buoy drift data as truth. This represents a 31 % reduction of the error on drift speed compared to the free drift estimates used in the Polar Pathfinder dataset. The thickness-dependent wind transfer coefficient provides an improved seasonality and long-term trend of the sea ice drift speed, with a minimum (maximum) drift speed in May (October), compared to July (January) for the constant wind transfer coefficient parameterizations which simply follow the peak in mean surface wind stresses. The trend in sea ice drift in this new model is +0.45 cm/s decade−1 compared with +0.39 cm/s decade−1 from the buoy observations, whereas there is essentially no trend in the standard free drift parameterization (−0.01 cm/s decade−1) or the Polar Pathfinder free drifts (−0.03 cm/s decade−1). The wind turning angle that minimize the cost function is equal of 25°, with a mean and root-mean square error of +2.6° and 51° on the direction of the drift, respectively. The residual from the minimization procedure (i.e. the ocean currents) resolves key large scale features such as the Beaufort Gyre and Transpolar Drift Stream, and is in good agreement with ocean state estimates from the ECCO, GLORYS and PIOMAS ice-ocean reanalyses, and geostrophic currents from dynamical ocean topography, with a root-mean-square difference of 2.4, 2.9, 2.6 and 3.8 cm/s, respectively. Finally, a repeat of the analysis on a two sub-section of the time series (pre- and post-2000) clearly shows the acceleration of the Beaufort Gyre (particularly along the Alaskan coastline) and an expansion of the gyre in the post-2000 concurrent with a thinning of the sea ice cover and observations acceleration of the ice drift speed and ocean current. This new dataset is publicly available for complementing merged observations-based sea ice drift datasets that includes satellite and buoy drift records.
Highlights
We develop a new parameterization for the free drift of sea ice based on wind forcing, wind turning angle, sea ice state variables and ocean current
To summarize this first step: we observe a reduction of the error and bias on the drift speed by 1.2 cm/s and 3 cm/sec by minimizing a cost function 275 for the wind-ice transfer coefficient and angle, and by using a higher spatial resolution atmospheric reanalysis (ERA5); and a further reduction of the error by 0.8 cm/s taking into account the ocean current as the residual of the linear fit between the surface wind stress and ice drift speed
Wind-driven ice motion estimates are an essential component of merged ice motion datasets (e.g.: Polar Pathfinder, Tschudi et al, 2019), providing information on sea ice drift when neither buoys nor satellite-derived drift vectors are available
Summary
Communities living in Arctic regions have had an implicit understanding of the drift of sea ice for well over hundreds of years, with the sea ice playing a major role in the way of life (Aporta, 2002; Krupnik et al, 2010). One useful simplification is to assume that the ice is free to 35 drift in response to the wind, i.e.: that there is no significat impact from the internal rheology. Such a free drift approximation is used in sea ice tracking models wherever the only data input is the wind field (Tschudi et al, 2019; Krumpen, 2018; Campbell et al, 2020) In this contribution, we propose a new parameterization for estimating the free drift sea ice motion, based on state variables such as thickness and concentration. Tracking sea ice motion in the Arctic can support a wide range of studies, including to: quantify changes in the dynamic
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