© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Smith, G. C., Allard, R., Babin, M., Bertino, L., Chevallier, M., Corlett, G., Crout, J., Davidson, F., Delille, B., Gille, S. T., Hebert, D., Hyder, P., Intrieri, J., Lagunas, J., Larnicol, G., Kaminski, T., Kater, B., Kauker, F., Marec, C., Mazloff, M., Metzger, E. J., Mordy, C., O'Carroll, A., Olsen, S. M., Phelps, M., Posey, P., Prandi, P., Rehm, E., Reid, P., Rigor, I., Sandven, S., Shupe, M., Swart, S., Smedstad, O. M., Solomon, A., Storto, A., Thibaut, P., Toole, J., Wood, K., Xie, J., Yang, Q., & WWRP PPP Steering Grp. Polar ocean observations: A critical gap in the observing system and its effect on environmental predictions from hours to a season. Frontiers in Marine Science, 6, (2019): 429, doi:10.3389/fmars.2019.00429.
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.
The development of the new generation of floats (PRO-ICE) to be operated under ice was funded by the French project NAOS. Twelve PRO-ICE were funded by NAOS and nine by the Canadian Foundation for Innovation (FCI-30124). The GreenEdge project is funded by the following French and Canadian programs and agencies: ANR (Contract #111112), CNES (project #131425), IPEV (project #1164), CSA, Fondation Total, ArcticNet, LEFE and the French Arctic Initiative (GreenEdge project). The INTAROS project has received funding from the European Union’s Horizon 2020 Research and Innovation Program under grant agreement No. 727890. The setup of the ArcMBA system and the experiment described in section “Quantitative Network Design” were funded by the European Space Agency through its support to science element (contract #4000117710/16/I-NB). SSw was supported by a Wallenberg Academy Fellowship (WAF 2015.0186). The work at CLS (GL, PPr, and PT) has been funded by internal investment, in relation with on-going CNES and ESA funded studies making use of radar data over Polar regions. EMODNET (BK) is funded by the European Commission. NRL Funding (for RA, JC, DH, EM, PPo, OS) provided by NRL Research Option “Determining the Impact of Sea Ice Thickness on the Arctic’s Naturally Changing Environment (DISTANCE), ONR 6.2 Data Assimilation and under program element 0602435N (JC, RA, DH). JT’s Arctic research activities are supported by the U.S. National Science Foundation and ONR. SG was funded by NSF grants/awards PLR-1425989 and OCE 1658001. IR is funded by contributors to the US IABP (including CG, DOE, NASA, NIC, NOAA, NSF, ONR). CAFS is supported by the NOAA ESRL Physical Sciences Division (AS and JI). LB and JX are funded by CMEMS. The WWRP PPP Steering Group is funded by a WMO trust fund with support from AWI for the ICO. The publication fee is provided by ECCC.
ocean data assimilation
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