The impact of sea ice dynamics on the Arctic climate system

Five paired global climate model experiments, one with an ice pack that only responds thermodynamically (TI) and one including sea-ice dynamics (DI), were used to investigate the sensitivity of Arctic climates to sea-ice motion. The sequence of experiments includes situations in which the Arctic was both considerably colder (Glacial Inception, ca 115,000 years ago) and considerably warmer (3 × CO2) than today. Sea-ice motion produces cooler anomalies year-round than simulations without ice dynamics, resulting in reduced Arctic warming in warm scenarios and increased Arctic cooling in cold scenarios. These changes reflect changes in atmospheric circulation patterns: the DI simulations favor outflow of Arctic air and sea ice into the North Atlantic by promoting cyclonic circulation centered over northern Eurasia, whereas the TI simulations favor southerly inflow of much warmer air from the North Atlantic by promoting cyclonic circulation centered over Greenland. The differences between the paired simulations are sufficiently large to produce different vegetation cover over >19% of the land area north of 55°N, resulting in changes in land-surface characteristics large enough to have an additional impact on climate. Comparison of the DI and TI experiments for the mid-Holocene (6000 years ago) with paleovegetation reconstructions suggests the incorporation of sea-ice dynamics yields a more realistic simulation of high-latitude climates. The spatial pattern of sea-ice anomalies in the warmer-than-modern DI experiments strongly resembles the observed Arctic Ocean sea-ice dipole structure in recent decades, consistent with the idea that greenhouse warming is already impacting the high-northern latitudes.

Sea surface temperature climate change initiative: alternative image classification algorithms for sea-ice affected oceans

We present a Bayesian image classification scheme for discriminating cloud, clear and sea-ice observations at high latitudes to improve identification of areas of clear-sky over ice-free ocean for SST retrieval. We validate the image classification against a manually classified dataset using Advanced Along Track Scanning Radiometer (AATSR) data. A three way classification scheme using a near-infrared textural feature improves classifier accuracy by 9.9 % over the nadir only version of the cloud clearing used in the ATSR Reprocessing for Climate (ARC) project in high latitude regions. The three way classification gives similar numbers of cloud and ice scenes misclassified as clear but significantly more clear-sky cases are correctly identified (89.9 % compared with 65 % for ARC). We also demonstrate the poetential of a Bayesian image classifier including information from the 0.6 micron channel to be used in sea-ice extent and ice surface temperature retrieval with 77.7 % of ice scenes correctly identified and an overall classifier accuracy of 96 %.

Dynamical and observational constraints on tropical Pacific sea surface temperatures at the last glacial maximum

Asynchronously coupled atmosphere and ocean general circulation model simulations are used to examine the consequences of changes in the west/east sea-surface temperature (SST) gradient across the equatorial Pacific at the last glacial maximum (LGM). Simulations forced by the CLIMAP SST for the LGM, where the west/east SST gradient across the Pacific is reduced compared to present, produce a reduction in the strength of the trade winds and a decrease in the west/east slope of the equatorial thermocline that is incompatible with thermocline depths newly inferred from foraminiferal assemblages. Stronger-than-present trade winds, and a more realistic simulation of the thermocline slope, are produced when eastern Pacific SSTs are 2°C cooler than western Pacific SSTs. Our study highlights the importance of spatial heterogeneity in tropical SSTs in determining key features of the glacial climate.

September Arctic sea-ice minimum predicted by spring melt-pond fraction

The area of Arctic September sea ice has diminished from about 7 million km2 in the 1990s to less than 5 million km2 in five of the past seven years, with a record minimum of 3.6 million km2 in 2012 (ref. 1). The strength of this decrease is greater than expected by the scientific community, the reasons for this are not fully understood, and its simulation is an on-going challenge for existing climate models2, 3. With growing Arctic marine activity there is an urgent demand for forecasting Arctic summer sea ice4. Previous attempts at seasonal forecasts of ice extent were of limited skill5, 6, 7, 8, 9. However, here we show that the Arctic sea-ice minimum can be accurately forecasted from melt-pond area in spring. We find a strong correlation between the spring pond fraction and September sea-ice extent. This is explained by a positive feedback mechanism: more ponds reduce the albedo; a lower albedo causes more melting; more melting increases pond fraction. Our results help explain the acceleration of Arctic sea-ice decrease during the past decade. The inclusion of our new melt-pond model10 promises to improve the skill of future forecast and climate models in Arctic regions and beyond.

Impact of variable atmospheric and oceanic form drag on simulations of Arctic sea ice

Over Arctic sea ice, pressure ridges and floe andmelt pond edges all introduce discrete obstructions to the flow of air or water past the ice and are a source of form drag. In current climate models form drag is only accounted for by tuning the air–ice and ice–ocean drag coefficients, that is, by effectively altering the roughness length in a surface drag parameterization. The existing approach of the skin drag parameter tuning is poorly constrained by observations and fails to describe correctly the physics associated with the air–ice and ocean–ice drag. Here, the authors combine recent theoretical developments to deduce the total neutral form drag coefficients from properties of the ice cover such as ice concentration, vertical extent and area of the ridges, freeboard and floe draft, and the size of floes and melt ponds. The drag coefficients are incorporated into the Los Alamos Sea Ice Model (CICE) and show the influence of the new drag parameterization on the motion and state of the ice cover, with the most noticeable being a depletion of sea ice over the west boundary of the Arctic Ocean and over the Beaufort Sea. The new parameterization allows the drag coefficients to be coupled to the sea ice state and therefore to evolve spatially and temporally. It is found that the range of values predicted for the drag coefficients agree with the range of values measured in several regions of the Arctic. Finally, the implications of the new form drag formulation for the spinup or spindown of the Arctic Ocean are discussed.

A case study of sea breeze blocking regulated by sea surface temperature along the English south coast

The sensitivity of sea breeze structure to sea surface temperature (SST) and coastal orography is investigated in convection-permitting Met Office Unified Model simulations of a case study along the south coast of England. Changes in SST of 1 K are shown to significantly modify the structure of the sea breeze immediately offshore. On the day of the case study, the sea breeze was partially blocked by coastal orography, particularly within Lyme Bay. The extent to which the flow is blocked depends strongly on the static stability of the marine boundary layer. In experiments with colder SST, the marine boundary layer is more stable, and the degree of blocking is more pronounced. Although a colder SST would also imply a larger land–sea temperature contrast and hence a stronger onshore wind – an effect which alone would discourage blocking – the increased static stability exerts a dominant control over whether blocking takes place. The implications of prescribing fixed SST from climatology in numerical weather prediction model forecasts of the sea breeze are discussed.

A review on Arctic sea ice predictability and prediction on seasonal-to-decadal timescales

Sea ice plays a crucial role in the earth's energy and water budget and substantially impacts local and remote atmospheric and oceanic circulations. Predictions of Arctic sea ice conditions a few months to a few years in advance could be of interest for stakeholders. This article presents a review of the potential sources of Arctic sea ice predictability on these timescales. Predictability mainly originates from persistence or advection of sea ice anomalies, interactions with the ocean and atmosphere and changes in radiative forcing. After estimating the inherent potential predictability limit with state-of-the-art models, current sea ice forecast systems are described, together with their performance. Finally, some challenges and issues in sea ice forecasting are presented, along with suggestions for future research priorities.

Pan-Arctic and regional sea ice predictability: initialization month dependence

Seasonal-to-interannual predictions of Arctic sea ice may be important for Arctic communities and industries alike. Previous studies have suggested that Arctic sea ice is potentially predictable but that the skill of predictions of the September extent minimum, initialized in early summer, may be low. The authors demonstrate that a melt season “predictability barrier” and two predictability reemergence mechanisms, suggested by a previous study, are robust features of five global climate models. Analysis of idealized predictions with one of these models [Hadley Centre Global Environment Model, version 1.2 (HadGEM1.2)], initialized in January, May and July, demonstrates that this predictability barrier exists in initialized forecasts as well. As a result, the skill of sea ice extent and volume forecasts are strongly start date dependent and those that are initialized in May lose skill much faster than those initialized in January or July. Thus, in an operational setting, initializing predictions of extent and volume in July has strong advantages for the prediction of the September minimum when compared to predictions initialized in May. Furthermore, a regional analysis of sea ice predictability indicates that extent is predictable for longer in the seasonal ice zones of the North Atlantic and North Pacific than in the regions dominated by perennial ice in the central Arctic and marginal seas. In a number of the Eurasian shelf seas, which are important for Arctic shipping, only the forecasts initialized in July have continuous skill during the first summer. In contrast, predictability of ice volume persists for over 2 yr in the central Arctic but less in other regions.

The drivers of projected North Atlantic sea level change

Sea level change predicted by the CMIP5 atmosphere–ocean general circulation models (AOGCMs) is not spatially homogeneous. In particular, the sea level change in the North Atlantic is usually characterised by a meridional dipole pattern with higher sea level rise north of 40°N and lower to the south. The spread among models is also high in that region. Here we evaluate the role of surface buoyancy fluxes by carrying out simulations with the FAMOUS low-resolution AOGCM forced by surface freshwater and heat flux changes from CO2-forced climate change experiments with CMIP5 AOGCMs, and by a standard idealised surface freshwater flux applied in the North Atlantic. Both kinds of buoyancy flux change lead to the formation of the sea level dipole pattern, although the effect of the heat flux has a greater magnitude, and is the main cause of the spread of results among the CMIP5 models. By using passive tracers in FAMOUS to distinguish between additional and redistributed buoyancy, we show that the enhanced sea level rise north of 40°N is mainly due to the direct steric effect (the reduction of sea water density) caused by adding heat or freshwater locally. The surface buoyancy forcing also causes a weakening of the Atlantic meridional overturning circulation, and the consequent reduction of the northward ocean heat transport imposes a negative tendency on sea level rise, producing the reduced rise south of 40°N. However, unlike previous authors, we find that this indirect effect of buoyancy forcing is generally less important than the direct one, except in a narrow band along the east coast of the US, where it plays a major role and leads to sea level rise, as found by previous authors.

Attribution of the spatial pattern of CO2-forced sea level change to ocean surface flux changes

Climate models taking part in the coupled model intercomparison project phase 5 (CMIP5) all predict a global mean sea level rise for the 21st century. Yet the sea level change is not spatially uniform and differs among models. Here we evaluate the role of air–sea fluxes of heat, water and momentum (windstress) to find the spatial pattern associated to each of them as well as the spread they can account for. Using one AOGCM to which we apply the surface flux changes from other AOGCMs, we show that the heat flux and windstress changes dominate both the pattern and the spread, but taking the freshwater flux into account as well yields a sea level change pattern in better agreement with the CMIP5 ensemble mean. Differences among the CMIP5 control ocean temperature fields have a smaller impact on the sea level change pattern.

Sea ice–ocean coupling using a rescaled vertical coordinate z*

Realistic representation of sea ice in ocean models involves the use of a non-linear free-surface, a real freshwater flux and observance of requisite conservation laws. We show here that these properties can be achieved in practice through use of a rescaled vertical coordinate ‘‘z*” in z-coordinate models that allows one to follow undulations in the free-surface under sea ice loading. In particular, the adoption of "z*" avoids the difficult issue of vanishing levels under thick ice. Details of the implementation within MITgcm are provided. A high resolution global ocean sea ice simulation illustrates the robustness of the z* formulation and reveals a source of oceanic variability associated with sea ice dynamics and ice-loading effects. The use of the z* coordinate allows one to achieve perfect conservation of fresh water, heat and salt, as shown in extended integration of coupled ocean sea ice atmospheric model.

Mixed layer lateral eddy fluxes mediated by air-sea interaction

The modulation of air–sea heat fluxes by geostrophic eddies due to the stirring of temperature at the sea surface is discussed and quantified. It is argued that the damping of eddy temperature variance by such air–sea fluxes enhances the dissipation of surface temperature fields. Depending on the time scale of damping relative to that of the eddying motions, surface eddy diffusivities can be significantly enhanced over interior values. The issues are explored and quantified in a controlled setting by driving a tracer field, a proxy for sea surface temperature, with surface altimetric observations in the Antarctic Circumpolar Current (ACC) of the Southern Ocean. A new, tracer-based diagnostic of eddy diffusivity is introduced, which is related to the Nakamura effective diffusivity. Using this, the mixed layer lateral eddy diffusivities associated with (i) eddy stirring and small-scale mixing and (ii) surface damping by air–sea interaction is quantified. In the ACC, a diffusivity associated with surface damping of a comparable magnitude to that associated with eddy stirring (;500 m2 s21) is found. In frontal regions prevalent in the ACC, an augmentation of surface lateral eddy diffusivities of this magnitude is equivalent to an air–sea flux of 100 W m22 acting over a mixed layer depth of 100 m, a very significant effect. Finally, the implications for other tracer fields such as salinity, dissolved gases, and chlorophyll are discussed. Different tracers are found to have surface eddy diffusivities that differ significantly in magnitude.

Sea surface temperature datasets for climate applications from Phase 1 of the European Space Agency Climate Change Initiative (SST CCI)

Sea surface temperature (SST) datasets have been generated from satellite observations for the period 1991–2010, intended for use in climate science applications. Attributes of the datasets specifically relevant to climate applications are: first, independence from in situ observations; second, effort to ensure homogeneity and stability through the time-series; third, context-specific uncertainty estimates attached to each SST value; and, fourth, provision of estimates of both skin SST (the fundamental measure- ment, relevant to air-sea fluxes) and SST at standard depth and local time (partly model mediated, enabling comparison with his- torical in situ datasets). These attributes in part reflect requirements solicited from climate data users prior to and during the project. Datasets consisting of SSTs on satellite swaths are derived from the Along-Track Scanning Radiometers (ATSRs) and Advanced Very High Resolution Radiometers (AVHRRs). These are then used as sole SST inputs to a daily, spatially complete, analysis SST product, with a latitude-longitude resolution of 0.05°C and good discrimination of ocean surface thermal features. A product user guide is available, linking to reports describing the datasets’ algorithmic basis, validation results, format, uncer- tainty information and experimental use in trial climate applications. Future versions of the datasets will span at least 1982–2015, better addressing the need in many climate applications for stable records of global SST that are at least 30 years in length.

North Sea archaeologies

North Sea Archaeologies traces the way people engaged with the North Sea from the end of the last ice age, around 10,000 BC, to the close of the Middle Ages, about AD 1500, drawing upon archaeological research from many countries, including the UK, Netherlands, Germany, Denmark, Sweden, Norway, Belgium, and France. It addresses topics which include the first interactions of people with the emerging North Sea, the origin and development of fishing, the creation of coastal landscapes, the importance of islands and archipelagos, the development of seafaring ships and their use by early seafarers and pirates, and the treatment of boats and ships at the end of their useful lives. The study offers a ‘maritime turn’ in Archaeology through the investigation of aspects of human behaviour that have been, to various extents, disregarded, overlooked, or ignored in archaeological studies of the land. The study concludes that the relationship between humans and the sea challenges the frequently invoked dichotomy between pre-modernity and modernity, since many ancient beliefs, superstitions, and practices linked to seafaring and engagement with the sea are still widespread in the modern era.