RESUMO
There is a growing need for operational oceanographic predictions in both the Arctic and Antarctic polar regions. In the former, this is driven by a declining ice cover accompanied by an increase in maritime traffic and exploitation of marine resources. Oceanographic predictions in the Antarctic are also important, both to support Antarctic operations and also to help elucidate processes governing sea ice and ice shelf stability. However, a significant gap exists in the ocean observing system in polar regions, compared to most areas of the global ocean, hindering the reliability of ocean and sea ice forecasts. This gap can also be seen from the spread in ocean and sea ice reanalyses for polar regions which provide an estimate of their uncertainty. The reduced reliability of polar predictions may affect the quality of various applications including search and rescue, coupling with numerical weather and seasonal predictions, historical reconstructions (reanalysis), aquaculture and environmental management including environmental emergency response. Here, we outline the status of existing near-real time ocean observational efforts in polar regions, discuss gaps, and explore perspectives for the future. Specific recommendations include a renewed call for open access to data, especially real-time data, as a critical capability for improved sea ice and weather forecasting and other environmental prediction needs. Dedicated efforts are also needed to make use of additional observations made as part of the Year of Polar Prediction (YOPP; 2017-2019) to inform optimal observing system design. To provide a polar extension to the Argo network, it is recommended that a network of ice-borne sea ice and upper-ocean observing buoys be deployed and supported operationally in ice-covered areas together with autonomous profiling floats and gliders (potentially with ice detection capability) in seasonally ice covered seas. Finally, additional efforts to better measure and parameterize surface exchanges in polar regions are much needed to improve coupled environmental prediction.
RESUMO
1541 Sentinel-1 SAR images, acquired over Fram Strait between 2014 and 2016, were considered for sea ice drift retrieval using an open-source feature tracking algorithm. Based on this SAR image data set, 2026 and 3120 image pairs in HH and HV polarisation were used to calculate monthly mean sea ice velocities at 79â¯N.
RESUMO
An ocean acoustic tomography system consisting of three moorings with low frequency, broadband transceivers and a moored receiver located approximately in the center of the triangle formed by the transceivers was installed in the central, deep-water part of Fram Strait during 2010-2012. Comparisons of the acoustic receptions with predictions based on hydrographic sections show that the oceanographic conditions in Fram Strait result in complex arrival patterns in which it is difficult to resolve and identify individual arrivals. In addition, the early arrivals are unstable, with the arrival structures changing significantly over time. The stability parameter α suggests that the instability is likely not due to small-scale variability, but rather points toward strong mesoscale variability in the presence of a relatively weak sound channel as being largely responsible. The estimator-correlator [Dzieciuch, J. Acoust. Soc. Am. 136, 2512-2522 (2014)] is shown to provide an objective formalism for generating travel-time series given the complex propagation conditions. Because travel times obtained from the estimator-correlator are not associated with resolved, identified ray arrivals, inverse methods are needed that do not use sampling kernels constructed from geometric ray paths. One possible approach would be to use travel-time sensitivity kernels constructed for the estimator-correlator outputs.
