A determination of the initial mass function (IMF) of the current, incomplete census of the 10 Myrold TW Hya association (TWA) is presented. This census is built from a literature compilation supplemented with new spectra and 17 new radial velocities from on-going membership surveys, as well as a re-analysis of Hipparcos data that confirmed HR 4334 (A2 Vn) as a member. Though the dominant uncertainty in the IMF remains census incompleteness, a detailed statistical treatment is carried out to make the IMF determination independent of binning, while accounting for small number statistics. The currently known high-likelihood members are fitted by a log-normal distribution with a central mass of 0.21−0.06 M and a characteristic width of 0.8 +0.2 −0.1 dex in the 12 M Jup -2 M range, whereas a Salpeter power law with α = 2.2 +1.1 −0.5 best describes the IMF slope in the 0.1-2 M range. This characteristic width is higher than other young associations, which may be due to incompleteness in the current census of low-mass TWA stars. A tentative overpopulation of isolated planetary-mass members similar to 2MASS J11472421-2040204 and 2MASS J11193254-1137466 is identified: this indicates that there might be as many as 10 +13 −5 similar members of TWA with hot-start modeldependent masses estimated at ∼ 5-7 M Jup , most of which would be too faint to be detected in 2MASS . Our new radial velocity measurements corroborate the membership of 2MASS J11472421-2040204, and secure TWA 28 (M8.5 γ), TWA 29 (M9.5 γ) and TWA 33 (M4.5 e) as members. The discovery of 2MASS J09553336-0208403, a young L7-type interloper unrelated to TWA, is also presented.

Seasonal predictability of the minimum sea ice extent (SIE) in the Laptev Sea is investigated using winter coastal divergence as a predictor. From February to May, the new ice forming in wind-driven coastal polynyas grows to a thickness approximately equal to the climatological thickness loss due to summer thermodynamic processes. Estimating the area of sea ice that is preconditioned to melt enables seasonal predictability of the minimum SIE. Wintertime ice motion is quantified by seeding passive tracers along the coastlines and advecting them with the Lagrangian Ice Tracking System (LITS) forced with sea ice drifts from the Polar Pathfinder dataset for years 1992–2016. LITS-derived landfast ice estimates are comparable to those of the Russian Arctic and Antarctic Research Institute ice charts. Time series of the minimum SIE and coastal divergence show trends of −24.2% and +31.3% per decade, respectively. Statistically significant correlation ( r = −0.63) between anomalies of coastal divergence and the following September SIE occurs for coastal divergence integrated from February to the beginning of May. Using the coastal divergence anomaly to predict the minimum SIE departure from the trend improves the explained variance by 21% compared to hindcasts based on persistence of the linear trend. Coastal divergence anomalies correlate with the winter mean Arctic Oscillation index ( r = 0.69). LITS-derived areas of coastal divergence tend to underestimate the total area covered by thin ice in the CryoSat-2/SMOS (Soil Moisture and Ocean Salinity) thickness dataset, as suggested by a thermodynamic sea ice growth model.

The effects of climate change are leading to pronounced physical and ecological changes in the Arctic Marginal Ice Zone (MIZ). These are not only of concern for the research community but also for the tourism industry dependent on this unique marine ecosystem. Tourists increasingly become aware that the Arctic as we know it may disappear due to several environmental threats, and want to visit the region before it becomes irrevocably changed. However, 'last-chance tourism' in this region faces several challenges. The lack of infrastructure and appropriate search and rescue policies are examples of existing issues in such a remote location. Additionally, tourism itself may further amplify the physical and ecological changes in the Arctic region. In this article, we provide an interdisciplinary analysis of the links between the MIZ, climate change and the tourism industry. We also identify existing regulations and the need for new ones concerning operations in the MIZ and in the Arctic Ocean.

We use ocean observations and reanalyses to investigate the sub-seasonal predictability of summer and fall sea ice area (SIA) in the western Arctic Ocean associated with lateral ocean heat transport (OHT) through Bering Strait and vertical OHT along the Alaskan coastline from Ekman divergence and upwelling. Results show predictive skill of spring Bering Strait OHT anomalies in the Chukchi and eastern East Siberian seas for June and July SIA, followed by a sharp drop in predictive skill in August, September, and October and a resurgence of the correlation in November during freeze-up. Fall upwelling of Pacific Waters along the Alaskan coastline - a mechanism that was proposed as a preconditioner for lower sea ice concentration (SIC) in the Beaufort Sea the following summer shows - minimal predictive strength on both local and regional scales for any months of the melt season. A statistical hindcast based on May Bering Strait OHT anomalies explains 74% of July Chukchi Sea SIA variance. Using OHT as a predictor of SIA anomalies in the Chukchi Sea improves hindcasts from the simple linear trend by 32% and predictions from spring sea ice thickness anomalies by 22%. This work highlights the importance of ocean heat anomalies for melt season sea ice prediction and provides observational evidence of sub-seasonal changes in forecast skill observed in model based forecasts of the Chukchi Sea.

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 (thickness and concentration), and estimates of the ocean currents. Given the fact that the spatial distribution of the wind–ice–ocean transfer coefficient has a similar structure to that of the spatial distribution of sea ice thickness, we take the standard free-drift equation and introduce a wind–ice–ocean transfer coefficient that scales linearly with ice thickness. Results show a mean bias error of −0.5 cm s−1 (low-speed bias) and a root-mean-square error of 5.1 cm s−1, considering daily buoy drift data as truth. This represents a 35 % reduction of the error on drift speed compared to the free-drift estimates used in the Polar Pathfinder dataset (Tschudi et al., 2019b). The thickness-dependent 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 transfer coefficient parameterizations which simply follow the peak in mean surface wind stresses. Over the 1979–2019 period, the trend in sea ice drift in this new model is +0.45 cm s−1 per decade compared with +0.39 cm s−1 per decade from the buoy observations, whereas there is essentially no trend in a free-drift parameterization with a constant transfer coefficient (−0.09 cm s−1 per decade) or the Polar Pathfinder free-drift input data (−0.01 cm s−1 per decade). The optimal wind turning angle obtained from a least-squares fitting is 25∘, resulting in a mean error and a root-mean-square error of +3 and 42∘ on the direction of the drift, respectively. The ocean current estimates obtained from the minimization procedure resolve key large-scale features such as the Beaufort Gyre and Transpolar Drift Stream and are in good agreement with ocean state estimates from the ECCO, GLORYS, and PIOMAS ice–ocean reanalyses, as well as geostrophic currents from dynamical ocean topography, with a root-mean-square difference of 2.4, 2.9, 2.6, and 3.8 cm s−1, respectively. Finally, a repeat of the analysis on two sub-sections 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-2000s, concurrent with a thinning of the sea ice cover and the observed acceleration of the ice drift speed and ocean currents. This new dataset is publicly available for complementing merged observation-based sea ice drift datasets that include satellite and buoy drift records.