Polar Oceans Research Articles

Floes, the marginal ice zone and coupled wave-sea-ice feedbacks.

Marginal ice zones (MIZs) are qualitatively distinct sea-ice-covered areas that play a critical role in the interaction between the polar oceans and the broader Earth system. MIZ regions have high spatial and temporal variability in oceanic, atmospheric and ecological conditions. The salient qualitative feature of MIZs is their composition as a mosaic of individual floes that range in horizontal extent from centimetres to tens of kilometres. Thus the floe size distribution (FSD) can be used to quantitatively identify and describe them. Here, the history of FSD observations and theory, and the processes (particularly the impact of ocean waves) that determine floe sizes and size distribution, are reviewed. Coupled wave-FSD feedbacks are explored using a stochastic model for thermodynamic wave-sea-ice interactions in the MIZ, and some of the key open questions in this rapidly growing field are discussed.This article is part of the theme issue ‘Theory, modelling and observations of marginal ice zone dynamics: multidisciplinary perspectives and outlooks’.

The influence of tides on the marine carbonate chemistry of a coastal polynya in the south-eastern Weddell Sea

Abstract. Tides significantly affect polar coastlines by modulating ice shelf melt and modifying shelf water properties through transport and mixing. However, the effect of tides on the marine carbonate chemistry in such regions, especially around Antarctica, remains largely unexplored. We address this topic with two case studies in a coastal polynya in the south-eastern Weddell Sea, neighbouring the Ekström Ice Shelf. The case studies were conducted in January 2015 (PS89) and January 2019 (PS117), capturing semi-diurnal oscillations in the water column. These are pronounced in both physical and biogeochemical variables for PS89. During rising tide, advection of sea ice meltwater from the north-east created a fresher, warmer, and more deeply mixed water column with lower dissolved inorganic carbon (DIC) and total alkalinity (TA) content. During ebbing tide, water from underneath the ice shelf decreased the polynya's temperature, increased the DIC and TA content, and created a more stratified water column. The variability during the PS117 case study was much smaller, as it had less sea ice meltwater input during rising tide and was better mixed with sub-ice shelf water. The contrasts in the variability between the two case studies could be wind and sea ice driven, and they underline the complexity and highly dynamic nature of the system. The variability in the polynya induced by the tides results in an air–sea CO2 flux that can range between a strong sink (−24 mmol m−2 d−1) and a small source (3 mmol m−2 d−1) on a semi-diurnal timescale. If the variability induced by tides is not taken into account, there is a potential risk of overestimating the polynya's CO2 uptake by 67 % or underestimating it by 73 %, compared to the average flux determined over several days. Depending on the timing of limited sampling, the polynya may appear to be a source or a sink of CO2. Given the disproportionate influence of polynyas on heat and carbon exchange in polar oceans, we recommend future studies around the Antarctic and Arctic coastlines to consider the timing of tidal currents in their sampling strategies and analyses. This will help constrain variability in oceanographic measurements and avoid potential biases in our understanding of these highly complex systems.

Analytical and Numerical Analyses on Vertical Site Responses of Submarine Permafrost in Polar Ocean

Submarine permafrost is widely distributed in polar ocean, which has an important impact on polar engineering and subsea energy exploitation. According to the frozen porous medium theory, an analytical solution of the one-dimensional vertically dynamic response of the submarine permafrost is derived by using the Laplace transform and the separation variable method. Using the general forms of partial differential equations and the pressure acoustics module in COMSOL software, a finite element model of submarine permafrost overlying a seawater layer is established. The results show that the degraded solution agrees well with the existing results of the vertically dynamic response of the saturated soil layer in the seabed, and the analytical and numerical solutions are in good agreement. The water depth, saturation and temperature have important effects on the dynamic responses of submarine permafrost. When the soil layer is fully saturated, the water depth has a weak effect on resonance frequency. However, if not fully saturated, even a small amount of air bubbles will have a significant impact on the resonance frequency of the soil layer, and this effect increases with the increase of water depth. The effect of temperature on the nearly saturated permafrost layer is also significantly higher than that on the saturated permafrost layer.

Thermohaline-turbulence instability and thermohaline staircase formation in the polar oceans

The thermohaline staircase structure, which is characterized by a series of remarkably homogeneous layers of temperature and salinity separated by sharp interfaces, widely exists in the Arctic Ocean's main thermocline. In our most recent work (Ma and Peltier (2022), JFM), we have proposed a stratified turbulence-based theory to describe the formation mechanism of the staircase structure. In this work, we test the effectiveness of such theory using a series of body-forced direct numerical simulations. We show that the staircase structure spontaneously forms in our simulations in a way that is consistent with our theoretical predictions.

Climate Change Impacts on the Marine Cycling of Biogenic Sulfur: A Review.

A key component of the marine sulfur cycle is the climate-active gas dimethylsulfide (DMS), which is synthesized by a range of organisms from phytoplankton to corals, and accounts for up to 80% of global biogenic sulfur emissions. The DMS cycle starts with the intracellular synthesis of the non-gaseous precursor dimethylsulfoniopropionate (DMSP), which is released to the water column by various food web processes such as zooplankton grazing. This dissolved DMSP pool is rapidly turned over by microbially mediated conversion using two known pathways: demethylation (releasing methanethiol) and cleavage (producing DMS). Some of the formed DMS is ventilated to the atmosphere, where it undergoes rapid oxidation and contributes to the formation of sulfate aerosols, with the potential to affect cloud microphysics, and thus the regional climate. The marine phase cycling of DMS is complex, however, as heterotrophs also contribute to the consumption of the newly formed dissolved DMS. Interestingly, due to microbial consumption and other water column sinks such as photolysis, the amount of DMS that enters the atmosphere is currently thought to be a relatively minor fraction of the total amount cycled through the marine food web—less than 10%. These microbial processes are mediated by water column temperature, but the response of marine microbial assemblages to ocean warming is poorly characterized, although bacterial degradation appears to increase with an increase in temperature. This review will focus on the potential impact of climate change on the key microbially mediated processes in the marine cycling of DMS. It is likely that the impact will vary across different biogeographical regions from polar to tropical. For example, in the rapidly warming polar oceans, microbial communities associated with the DMS cycle will likely change dramatically during the 21st century with the decline in sea ice. At lower latitudes, where corals form an important source of DMS (P), shifts in the microbiome composition have been observed during thermal stress with the potential to alter the DMS cycle.

A full year of turbulence measurements from a drift campaign in the Arctic Ocean 2019–2020

Ocean turbulent mixing is a key process in the global climate system, regulating ocean circulation and the uptake and redistribution of heat, carbon, nutrients, oxygen and other tracers. In polar oceans, turbulent heat transport additionally affects the sea ice mass balance. Due to the inaccessibility of polar regions, direct observations of turbulent mixing are sparse in the Arctic Ocean. During the year-long drift expedition “Multidisciplinary drifting Observatory for the Study of Arctic Climate” (MOSAiC) from September 2019 to September 2020, we obtained an unprecedented data set of vertical profiles of turbulent dissipation rate and water column properties, including oxygen concentration and fluorescence. Nearly 1,700 profiles, covering the upper ocean down to approximately 400 m, were collected in sets of 3 or more consecutive profiles every day, and complemented with several intensive sampling periods. This data set allows for the systematic assessment of upper ocean mixing in the Arctic, and the quantification of turbulent heat and nutrient fluxes, and can help to better constrain turbulence parameterizations in ocean circulation models.

Third revision of the global surface seawater dimethyl sulfide climatology (DMS-Rev3)

Abstract. This paper presents an updated estimation of the bottom-up global surface seawater dimethyl sulfide (DMS) climatology. This update, called DMS-Rev3, is the third of its kind and includes five significant changes from the last climatology, L11 (Lana et al., 2011), that was released about a decade ago. The first change is the inclusion of new observations that have become available over the last decade, creating a database of 873 539 observations leading to an ∼ 18-fold increase in raw data as compared to the last estimation. The second is significant improvements in data handling, processing, and filtering, to avoid biases due to different observation frequencies which result from different measurement techniques. Thirdly, we incorporate the dynamic seasonal changes observed in the geographic boundaries of the ocean biogeochemical provinces. The fourth change involves the refinement of the interpolation algorithm used to fill in the missing data. Lastly, an upgraded smoothing algorithm based on observed DMS variability length scales (VLS) helps to reproduce a more realistic distribution of the DMS concentration data. The results show that DMS-Rev3 estimates the global annual mean DMS concentration to be ∼ 2.26 nM (2.39 nM without a sea-ice mask), i.e., about 4 % lower than the previous bottom-up L11 climatology. However, significant regional differences of more than 100 % as compared to L11 are observed. The global sea-to-air flux of DMS is estimated at ∼ 27.1 TgS yr−1, which is about 4 % lower than L11, although, like the DMS distribution, large regional differences were observed. The largest changes are observed in high concentration regions such as the polar oceans, although oceanic regions that were under-sampled in the past also show large differences between revisions of the climatology. Finally, DMS-Rev3 reduces the previously observed patchiness in high productivity regions. The new climatology, along with the algorithm, can be found in the online repository: https://doi.org/10.17632/hyn62spny2.1 (Mahajan, 2021).

The role of zinc in the adaptive evolution of polar phytoplankton

Zinc is an essential trace metal for oceanic primary producers with the highest concentrations in polar oceans. However, its role in the biological functioning and adaptive evolution of polar phytoplankton remains enigmatic. Here, we have applied a combination of evolutionary genomics, quantitative proteomics, co-expression analyses and cellular physiology to suggest that model polar phytoplankton species have a higher demand for zinc because of elevated cellular levels of zinc-binding proteins. We propose that adaptive expansion of regulatory zinc-finger protein families, co-expanded and co-expressed zinc-binding proteins families involved in photosynthesis and growth in these microalgal species and their natural communities were identified to be responsible for the higher zinc demand. The expression of their encoding genes in eukaryotic phytoplankton metatranscriptomes from pole-to-pole was identified to correlate not only with dissolved zinc concentrations in the upper ocean but also with temperature, suggesting that environmental conditions of polar oceans are responsible for an increased demand of zinc. These results suggest that zinc plays an important role in supporting photosynthetic growth in eukaryotic polar phytoplankton and that this has been critical for algal colonization of low-temperature polar oceans.

Synergistic Use of Far‐ and Mid‐Infrared Spectral Radiances for Satellite‐Based Detection of Polar Ice Clouds Over Ocean

AbstractCloud phase is an important factor affecting cloud contributions to the polar energy budget. Brightness temperature differences (BTDs) between two mid‐infrared (mid‐IR) spectral channels are commonly used in satellite remote sensing to determine the cloud phase, but the mid‐IR has limitations for cloud phase determination in polar regions. This study explores the synergy between the far‐ and mid‐IR for ice cloud phase determinations over polar oceans. A far‐IR BTD test (BTD449‐521) is developed based on the spectral variations of both ice cloud scattering and absorption properties in the far‐IR “dirty window” region (400–600 cm−1 or 16.7–25 μm). Synthetic IR radiances at 1 cm−1 spectral resolution are generated using ERA5 reanalysis data for both polar regions. A subset of these spectra is used to compare the ice phase determination skill of the far‐IR test with an “AIRS‐Like” mid‐IR BTD test (BTD1231‐960) for combinations of effective ice particle diameter (Deff_ice), cloud optical depth (COD), and cloud top pressure (CTP). The far‐IR test is performing better for ice clouds with the smallest Deff_ice that we have studied (20 μm) due to the sensitivity of far‐IR scattering to ice particle size. The mid‐IR test was either comparable to or more successful than the far‐IR test for ice clouds with large particle sizes. For all Deff_ice, increasing COD leads to enhanced far‐IR BTD signals due to stronger multiple scattering in the far‐IR than in the mid‐IR. Overall, the variations in far‐IR and mid‐IR BTD test performance are strongly sensitive to Deff_ice, followed by COD and CTP.

A Prototype for Remote Monitoring of Ocean Heat Content Anomalies

Abstract To overcome challenges with observing ocean heat content (OHC) over the entire ocean, we propose a novel approach that exploits the abundance of satellite data, including data from modern satellite geomagnetic surveys such as Swarm. The method considers a novel combination of conventional in situ (temperature and pressure) as well as satellite (altimetry and gravimetry) data with estimates of ocean electrical conductance (depth-integrated conductivity), which can potentially be obtained from magnetic observations (by satellite, land, seafloor, ocean, and airborne magnetometers). To demonstrate the potential benefit of the proposed method, we sample model output of an ocean state estimate to reflect existing observations and train a machine learning algorithm [Generalized Additive Model (GAM)] on these samples. We then calculate OHC everywhere using information potentially derivable from various global satellite coverage—including magnetic observations—to gauge the GAM’s goodness of fit on a global scale. Inclusion of in situ observations of OHC in the upper 2000 m from Argo-like floats and conductance data each reduce the root-mean-square error by an order of magnitude. Retraining the GAM with recent ship-based hydrographic data attains a smaller RMSE in polar oceans than training the GAM only once on all available historical ship-based hydrographic data; the opposite is true elsewhere. The GAM more accurately calculates OHC anomalies throughout the water column than below 2000 m and can detect global OHC anomalies over multiyear time scales, even when considering hypothetical measurement errors. Our method could complement existing methods and its accuracy could be improved through careful ship-based campaign planning. Significance Statement The purpose of this manuscript is to demonstrate the potential for practical implementation of a remote monitoring method for ocean heat content (OHC) anomalies. To do this, we sample data from a reanalysis product primarily because of the dearth of observations below 2000 m depth that can be used for validation and the fact that full-depth-integrated electrical seawater conductivity data products derived from satellite magnetometry are not yet available. We evaluate multiple factors related to the accuracy of OHC anomaly estimation and find that, even with hypothetical measurement errors, our method can be used to monitor OHC anomalies on multiyear time scales.

Physical Drivers of Ocean Wave Attenuation in the Marginal Ice Zone

Abstract Despite a recent resurgence of observational studies attempting to quantify the ice-induced attenuation of ocean waves in polar oceans, the physical processes governing this phenomenon are still poorly understood. Most analyses have attempted to relate the spatial rate of wave attenuation to wave frequency, but have not considered how this relationship depends on ice, wave, and atmospheric conditions. An in-depth analysis of the wave-buoy data collected during the 2017 Polynyas, Ice Production, and Seasonal Evolution in the Ross Sea (PIPERS) program in the Ross Sea is conducted. Standard techniques are used to estimate the spatial rate of wave attenuation α, and the influence of a number of potential physical drivers on its dependence on wave period T is investigated. A power law is shown to consistently describe the α(T) relationship, in line with other recent analyses. The two parameters describing this relationship are found to depend significantly on sea ice concentration, mean wave period, and wind direction, however. Looking at cross correlations between these physical drivers, three regimes of ice-induced wave attenuation are identified, which characterize different ice, wave, and wind conditions, and very possibly different processes causing this observed attenuation. This analysis suggests that parameterizations of ice-induced wave decay in spectral wave models should be piecewise, so as to include their dependence on local ice, wave, and wind conditions. Significance Statement This work attempts to quantify how ice, wave, and wind conditions in polar oceans affect the way that ocean waves decay as a result of their interactions with sea ice. In situ wave data collected in the Ross Sea are analyzed along with several freely available ice, wave, and wind datasets. A simple relationship is shown to describe how wave attenuation due to sea ice depends on the wave period consistently across all data analyzed. However, the parameters of this relationship are significantly affected by sea ice concentration, mean wave period, and wind direction. This finding suggests that large-scale wave models need to account for this dependence on ice, wave, and wind conditions to improve wave forecast in ice-covered oceans.

ВКЛАД Ф. В-Я. НАНСЕНА В ФИЗИЧЕСКУЮ ОКЕАНОГРАФИЮ

The article lists the main results of Nansen’s work in the field of physical oceanography. It tells about the results and ideas of Nansen in the field of arctic drifting measuring platforms, a bathometer, a hydrometer, a bottom current meter and unique sleds. The merits of Nansen in the field of regional oceanography are described: debunking the theory of the “open polar ocean”, measuring the depths of the Arctic Basin, estimating the trajectory and velocity of the transarctic drift, the dependence of the drift velocity and direction on the wind, factors determining the speed ice accretion, discovery and description of surface and warm (Atlantic) intermediate water masses in the Arctic. We are also talking about the processes in the ocean, which Nansen first measured, and then, together with Ekman, described them with mathematical formulas.

Diatoms and Their Microbiomes in Complex and Changing Polar Oceans.

Diatoms, a key group of polar marine microbes, support highly productive ocean ecosystems. Like all life on earth, diatoms do not live in isolation, and they are therefore under constant biotic and abiotic pressures which directly influence their evolution through natural selection. Despite their importance in polar ecosystems, polar diatoms are understudied compared to temperate species. The observed rapid change in the polar climate, especially warming, has created increased research interest to discover the underlying causes and potential consequences on single species to entire ecosystems. Next-Generation Sequencing (NGS) technologies have greatly expanded our knowledge by revealing the molecular underpinnings of physiological adaptations to polar environmental conditions. Their genomes, transcriptomes, and proteomes together with the first eukaryotic meta-omics data of surface ocean polar microbiomes reflect the environmental pressures through adaptive responses such as the expansion of protein families over time as a consequence of selection. Polar regions and their microbiomes are inherently connected to climate cycles and their feedback loops. An integrated understanding built on “omics” resources centered around diatoms as key primary producers will enable us to reveal unifying concepts of microbial co-evolution and adaptation in polar oceans. This knowledge, which aims to relate past environmental changes to specific adaptations, will be required to improve climate prediction models for polar ecosystems because it provides a unifying framework of how interacting and co-evolving biological communities might respond to future environmental change.

Vertical occurrence of copepod carcasses in the Cosmonaut Sea during austral summer

Zooplankton carcasses and their contribution to carbon export are increasingly garnering attention in food web studies of polar oceans. We investigated the occurrence of carcasses of dominant copepod species at four depths (100–200 m, 200–500 m, 500–1000 m, 1000–1500 m) and their potential contribution to particulate organic carbon (POC) concentrations in the Cosmonaut Sea, Antarctica, during summer, 2019/2020. The abundance of small copepods (< 2 mm), either live or dead individuals, was 1-3 orders of magnitude higher than the four dominant large copepod species Calanoides acutus, Calanus propinquus, Metridia gerlachei and Rhincalanus gigas at each depth. Most carcasses were observed at the surface (100–200 m), while the proportions of dead individuals increased with depth, from 22% in the 100–200 m layer to 70% of the 500–1500 m layer. The total number of passive sinkers (carcasses and moults) was dominated by carcasses of small copepods in each depth layer, while the carbon biomass of passive sinkers was dominated by carcasses of large copepods. Both abundance and carbon biomass of passive sinkers decreased with depth. The average contribution of passive sinkers to the POC concentration decreased from 0.27% in the 100–200 m depth stratum to 0.10% in the 500–1500 m layer. This study provides the first report of occurrence and contribution of carcasses from the surface to the mesopelagic layer of the Southern Ocean. This information can improve understanding of the role zooplankton play in downward carbon flux within the ocean’s twilight zone.

HBIs and Sterols in Surface Sediments Across the East Siberian Sea: Implications for Palaeo Sea‐Ice Reconstructions

AbstractHighly branched isoprenoids (HBIs) in marine sediments have emerged as promising semi‐quantitative proxies to reconstruct seasonal sea ice in polar oceans. In this work, we examine the distribution of sympagic HBIs (IP25 and HBI‐II), pelagic phytoplankton biomarkers (brassicasterol, dinosterol and HBI‐III) as well as terrestrial sterols (campesterol and β‐sitosterol) in the surface sediments of the East Siberian Sea (ESS) to test their reliability as sea‐ice proxies under continental run‐off influence. Our data suggest that dinosterol performs better than brassicasterol to assess sea ice across the ESS shelf, yet the correlation between PDIP25 and spring sea ice is relatively weak but improves when removing sites with salinity &lt;25. Strongest relationship is found between PIIIIP25 and summer sea ice in regions remote from riverine influence. Overall, our results show that semi‐quantitative estimates of sea ice based on biomarkers can be problematic in Arctic Ocean margins because of biases induced by continental run‐off on biological productivity and sea‐ice production.

Quantifying Energy Balance Regimes in the Modern Climate, Their Link to Lapse Rate Regimes, and Their Response to Warming

Abstract Energy balance and lapse rate regimes qualitatively characterize the low, middle, and high latitudes of Earth’s modern climate. Currently we do not have a complete quantitative understanding of the spatiotemporal structure of energy balance regimes [e.g., radiative convective equilibrium (RCE) and radiative advective equilibrium (RAE)] and their connection to lapse rate regimes (moist adiabat and surface inversion). Here we use the vertically integrated moist static energy budget to define a nondimensional number that quantifies where and when RCE and RAE are approximately satisfied in Earth’s modern climate. We find RCE exists year-round in the tropics and in the northern midlatitudes during summertime. RAE exists year-round over Antarctica and in the Arctic with the exception of early summer. We show that lapse rates in RCE and RAE are consistent with moist adiabatic and surface inversion lapse rates, respectively. We use idealized models (energy balance and aquaplanet) to test the following hypotheses: 1) RCE occurs during midlatitude summer for land-like (small heat capacity) surface conditions, and 2) sea ice is necessary for the existence of annual-mean RAE over a polar ocean, such as the Arctic. Consistent with point 1, an aquaplanet configured with a shallow mixed layer transitions to RCE in the midlatitudes during summertime whereas it does not for a deep mixed layer. Furthermore, we confirm point 2 using mechanism-denial aquaplanet experiments with and without thermodynamic sea ice. Finally, we show energy balance regimes of the modern climate provide a useful guide to the vertical structure of the warming response in the annual mean, and seasonally over the tropics and the southern high latitudes.

Sea-Ice Mapping of RADARSAT-2 Imagery by Integrating Spatial Contexture With Textural Features

Mapping different types of sea ice that form, grow, and melt in polar oceans is essential for shipping navigation, climate change modeling, and local community safety. Currently, ice charts are manually generated by analysts at the Canadian Ice Service (CIS) based on dual-polarized RADARSAT-2/RADARSAT Constellation Mission (RCM) imagery on a daily basis. Inspired by the demand for a computer-based mapping system, we have developed an automatic sea ice classification method that integrates spatial contexture (unsupervised segmentation) with textural features (supervised pixel-level labeling). First, the full-scene image is oversegmented, and the segments are merged into homogeneous regions across the entire scene. Second, pixel-based classifiers (support vector machine, random forest) are compared for their ability to label the generated homogeneous regions. Finally, the segmentation and labeling are combined using a proposed energy function. The proposed method was tested on 18 dual-polarization RADARSAT-2 scenes acquired over the Beaufort Sea. This dataset contains water, young ice, first-year ice, and multi-year ice covering melt, summer, and freeze-up seasons. The proposed method obtains an average classification accuracy of 86.33% based on the leave-one-out validation. The experimental results show that the proposed method achieves promising classification results in both quantity and quality measurements compared to benchmark methods. The robustness against incidence angle variance indicates that the proposed method is well-qualified for operational sea ice mapping.

Artificial Neural Network Model for Estimating Ocean Heat Content in the Sea Ice-Covered Arctic Regions Using Satellite Data

Ocean heat content (OHC) is an essential parameter to assess Earth’s energy imbalance, global warming, and climate change over the historical record. An accurate estimate of the OHC in the Arctic sea ice regions is challenging due to the lack of in-situ data and satellite-based algorithms. In this study, an artificial neural network-based (ANN) novel approach is presented for estimating OHC changes at various standard depth extents (by World Ocean Atlas) in the Arctic sea ice regions based on the relationships of the sea ice thermodynamic parameters from the satellite measurements and in-situ OHC estimates. Because of the potential uncertainty that arises from the inaccessible near-surface oceanic layer in the in-situ OHC estimates, a preliminary ANN model was developed with a set of approximations to account for the in-situ OHC stored in the respective depths within the inaccessible near-surface oceanic layer. The ANN model architecture was optimized for a depth extent of 700 m and adopted for the remaining depths of 20 m, 30 m, 40 m, 50 m, 100 m, 150 m, 200 m, 250 m, 300 m, 350 m, 400 m, 450 m, 500 m, 550 m, 600 m, and 650 m. The new model was robust in capturing the spatial, temporal, and depth variabilities of OHC in the sea ice-covered Arctic regions with greater accuracy (mean bias error 0.022 GJ m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> , mean bias percentage error 0.015%, mean absolute error 0.182 GJ m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> , mean absolute percentage error 0.148%, root mean square error 0.24 GJ m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> , R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> 0.94, slope 0.93, and intercept 25.05 GJ m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> ). This model is capable of estimating OHC and its temporal trends from satellite data which will have implications for understanding the global climate change and its impacts in the Polar Oceans.

Biogeography of culturable marine bacteria from both poles reveals that ‘everything is not everywhere’ at the genomic level

Based on 16S rRNA gene analyses, the same bacterial operational taxonomic units (OTUs) are common to both the Arctic and Antarctic oceans, supporting the concept 'everything is everywhere'. However, whether the same OTUs from both poles have identical genomes, i.e. whether 'everything is still everywhere' at the genomic level has not yet been examined systematically. Here, we isolated, sequenced and compared the genomes of 45 culturable marine bacteria belonging to three genera of Salinibacterium, Psychrobacter and Pseudoalteromonas from both polar oceans. The bacterial strains with identical 16S rRNA genes were common to both poles in every genus, and four identical genomes were detected in the genus Salinibacterium from the Arctic region. However, no identical genomes were observed from opposite poles in this study. Our data, therefore, suggest that 'everything is not everywhere' at the genomic level. The divergence time between bacteria is hypothesized to exert a strong impact on the bacterial biogeography at the genomic level. The geographical isolation between poles was observed for recently diverged, highly similar genomes, but not for moderately similar genomes. This study thus improves our understanding of the factors affecting the genomic-level biogeography of marine microorganisms isolated from distant locations.

Bimodality in ensemble forecasts of 2 m temperature: identification

Abstract. Bimodality and other types of non-Gaussianity arise in ensemble forecasts of the atmosphere as a result of nonlinear spread across ensemble members. In this paper, bimodality in 50-member ECMWF ENS-extended ensemble forecasts is identified and characterized. Forecasts of 2 m temperature are found to exhibit widespread bimodality well over a derived false-positive rate. In some regions bimodality occurs in excess of 30 % of forecasts, with the largest rates occurring during lead times of 2 to 3 weeks. Bimodality occurs more frequently in the winter hemisphere with indications of baroclinicity being a factor to its development. Additionally, bimodality is more common over the ocean, especially the polar oceans, which may indicate development caused by boundary conditions (such as sea ice). Near the equatorial region, bimodality remains common during either season and follows similar patterns to the Intertropical Convergence Zone (ITCZ), suggesting convection as a possible source for its development. Over some continental regions the modes of the forecasts are separated by up to 15 ∘C. The probability density for the modes can be up to 4 times greater than at the minimum between the modes, which lies near the ensemble mean. The widespread presence of such bimodality has potentially important implications for decision makers acting on these forecasts. Bimodality also has implications for assessing forecast skill and for statistical postprocessing: several commonly used skill-scoring methods and ensemble dressing methods are found to perform poorly in the presence of bimodality, suggesting the need for improvements in how non-Gaussian ensemble forecasts are evaluated.