Arctic sea surface height (SSH) is poorly observed by radar altimeters due to the poor coverage of the polar oceans provided by conventional altimeter missions and because large areas are perpetually covered by sea ice, requiring specialized data processing. We utilize SSH estimates from both the icecovered and ice-free ocean to present monthly estimates of Arctic Dynamic Ocean Topography (DOT) from radar altimetry south of 81.58N and combine this with GRACE ocean mass to estimate steric height. Our SSH and steric height estimates show good agreement with tide gauge records and geopotential height derived from Ice-Tethered Profilers. The large seasonal cycle of Arctic SSH (amplitude 5 cm) is dominated by seasonal steric height variation associated with seasonal freshwater fluxes, and peaks in October-November. Overall, the annual mean steric height increased by 2.2 6 1.4 cm between 2003 and 2012 before falling to circa 2003 levels between 2012 and 2014 due to large reductions on the Siberian shelf seas. The total secular change in SSH between 2003 and 2014 is then dominated by a 2.1 6 0.7 cm increase in ocean mass. We estimate that by 2010, the Beaufort Gyre had accumulated 4600 km 3 of freshwater relative to the 2003-2006 mean. Doming of Arctic DOT in the Beaufort Sea is revealed by Empirical Orthogonal Function analysis to be concurrent with regional reductions in the Siberian Arctic. We estimate that the Siberian shelf seas lost 180 km 3 of freshwater between 2003 and 2014, associated with an increase in annual mean salinity of 0.15 psu yr 21 . Finally, ocean storage flux estimates from altimetry agree well with high-resolution model results, demonstrating the potential for altimetry to elucidate the Arctic hydrological cycle.
Abstract. Versions 6 and 7 of the UK Global Ocean configuration (known as GO6 and GO7) will form the ocean components of the Met Office GC3.1 coupled model and UKESM1 earth system model to be used in CMIP6 1 simulations. The label "GO6" refers to a traceable hierarchy of three model configurations at nominal 1, 1/4 and 1/12• resolutions. The GO6 configurations are described in detail with particular focus on aspects which have been updated since the previous version (GO5). Results of 30-year forced ocean-ice integrations with the 1/4 • model are presented, in which GO6 is coupled to the GSI8.1 sea ice configuration and forced with CORE2 2 fluxes. GO6-GSI8.1 shows an overall improved simulation compared to GO5-GSI5.0, especially in the Southern Ocean where there are more realistic summertime mixed layer depths, a reduced near-surface warm and saline biases, and an improved simulation of sea ice. The main drivers of the improvements in the Southern Ocean simulation are tuning of the vertical and isopycnal mixing parameters. Selected results from the full hierarchy of three resolutions are shown. Although the same forcing is applied, the three models show large-scale differences in the near-surface circulation and in the short-term adjustment of the overturning circulation. The GO7 configuration is identical to the GO6 1/4 • configuration except that the cavities
Abstract. Until recently, the Arctic Basin was generally considered to be a low productivity area and was afforded little attention in global-or even basin-scale ecosystem modelling studies. Due to anthropogenic climate change however, the sea ice cover of the Arctic Ocean is undergoing an unexpectedly fast retreat, exposing increasingly large areas of the basin to sunlight. As indicated by existing Arctic phenomena such as ice-edge blooms, this decline in sea-ice is liable to encourage pronounced growth of phytoplankton in summer and poses pressing questions concerning the future of Arctic ecosystems. It thus provides a strong impetus to modelling of this region.The Arctic Ocean is an area where plankton productivity is heavily influenced by physical factors. As these factors are strongly responding to climate change, we analyse here the results from simulations of the 1/4 • resolution global ocean NEMO (Nucleus for European Modelling of the Ocean) model coupled with the MEDUSA (Model for Ecosystem Dynamics, carbon Utilisation, Sequestration and Acidification) biogeochemical model, with a particular focus on the Arctic basin. Simulated productivity is consistent with the limited observations for the Arctic, with significant production occurring both under the sea-ice and at the thermocline, locations that are difficult to sample in the field.Results also indicate that a substantial fraction of the variability in Arctic primary production can be explained by two key physical factors: (i) the maximum penetration of winter mixing, which determines the amount of nutrients available for summer primary production, and (ii) short-wave radiation at the ocean surface, which controls the magnitude of phytoplankton blooms. A strong empirical correlation was Correspondence to: E. E. Popova (ekp@noc.soton.ac.uk) found in the model output between primary production and these two factors, highlighting the importance of physical processes in the Arctic Ocean.
International audienceAn established iceberg module, ICB, is used interactively with the Nucleus for European Modelling of the Ocean (NEMO) ocean model in a new implementation, NEMO–ICB (v1.0). A 30-year hindcast (1976–2005) simulation with an eddy-permitting (0.25°) global configuration of NEMO–ICB is undertaken to evaluate the influence of icebergs on sea ice, hydrography, mixed layer depths (MLDs), and ocean currents, through comparison with a control simulation in which the equivalent iceberg mass flux is applied as coastal runoff, a common forcing in ocean models. In the Southern Hemisphere (SH), drift and melting of icebergs are in balance after around 5 years, whereas the equilibration timescale for the Northern Hemisphere (NH) is 15–20 years. Iceberg drift patterns, and Southern Ocean iceberg mass, compare favourably with available observations. Freshwater forcing due to iceberg melting is most pronounced very locally, in the coastal zone around much of Antarctica, where it often exceeds in magnitude and opposes the negative freshwater fluxes associated with sea ice freezing. However, at most locations in the polar Southern Ocean, the annual-mean freshwater flux due to icebergs, if present, is typically an order of magnitude smaller than the contribution of sea ice melting and precipitation. A notable exception is the southwest Atlantic sector of the Southern Ocean, where iceberg melting reaches around 50% of net precipitation over a large area. Including icebergs in place of coastal runoff, sea ice concentration and thickness are notably decreased at most locations around Antarctica, by up to ~ 20% in the eastern Weddell Sea, with more limited increases, of up to ~ 10% in the Bellingshausen Sea. Antarctic sea ice mass decreases by 2.9%, overall. As a consequence of changes in net freshwater forcing and sea ice, salinity and temperature distributions are also substantially altered. Surface salinity increases by ~ 0.1 psu around much of Antarctica, due to suppressed coastal runoff, with extensive freshening at depth, extending to the greatest depths in the polar Southern Ocean where discernible effects on both salinity and temperature reach 2500 m in the Weddell Sea by the last pentad of the simulation. Substantial physical and dynamical responses to icebergs, throughout the global ocean, are explained by rapid propagation of density anomalies from high-to-low latitudes. Complementary to the baseline model used here, three prototype modifications to NEMO–ICB are also introduced and discussed
Abstract. Recent years have seen a rapid reduction in the summer Arctic sea ice extent. To both understand this trend and project the future evolution of the summer Arctic sea ice, a better understanding of the physical processes that drive the seasonal loss of sea ice is required. The marginal ice zone, here defined as regions with between 15 % and 80 % sea ice cover, is the region separating pack ice from the open ocean. Accurate modelling of this region is important to understand the dominant mechanisms involved in seasonal sea ice loss. Evolution of the marginal ice zone is determined by complex interactions between the atmosphere, sea ice, ocean, and ocean surface waves. Therefore, this region presents a significant modelling challenge. Sea ice floes span a range of sizes but sea ice models within climate models assume they adopt a constant size. Floe size influences the lateral melt rate of sea ice and momentum transfer between atmosphere, sea ice, and ocean, all important processes within the marginal ice zone. In this study, the floe size distribution is represented as a power law defined by an upper floe size cut-off, lower floe size cut-off, and power-law exponent. This distribution is also defined by a new tracer that varies in response to lateral melting, wave-induced break-up, freezing conditions, and advection. This distribution is implemented within a sea ice model coupled to a prognostic ocean mixed-layer model. We present results to show that the use of a power-law floe size distribution has a spatially and temporally dependent impact on the sea ice, in particular increasing the role of the marginal ice zone in seasonal sea ice loss. This feature is important in correcting existing biases within sea ice models. In addition, we show a much stronger model sensitivity to floe size distribution parameters than other parameters used to calculate lateral melt, justifying the focus on floe size distribution in model development. We also find that the attenuation rate of waves propagating under the sea ice cover modulates the impact of wave break-up on the floe size distribution. It is finally concluded that the model approach presented here is a flexible tool for assessing the importance of a floe size distribution in the evolution of sea ice and is a useful stepping stone for future development of floe size modelling.
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