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Involving air traffic controllers and pilots into the bird strike prevention process is considered an essential step to increase aviation and avian safety. Prior to implementing operational measures such as real-time warning systems, it is vital to evaluate their feasibility. This paper studies the efficacy of a bird strike advisory system for air traffic control. In addition to the potential safety benefit, the possible impact on airport operations is analyzed. To this end, a previously developed collision avoidance algorithm underlying the system was tested in fast-time Monte Carlo simulations involving various air traffic and bird densities to obtain representative conclusions for different operational conditions. The results demonstrate the strong safety potential of operational bird strike prevention in case of precise bird movement prediction. Unless airports operate close to their capacity limits while bird abundance is high, the induced delays remain tolerable. Prioritization of hazardous strikes involving large individuals as well as flocks of birds are expected to support operational feasibility in all conditions, Control & Simulation, Control & Operations

The concept of wake steering on wind farms for power maximization has gained significant popularity over the last decade. Recent field trials described in the literature not only demonstrate the real potential of wake steering on commercial wind farms but also show that wake steering does not yet consistently lead to an increase in energy production for all inflow conditions. Moreover, a recent survey among experts shows that validation of the concept currently remains the largest barrier to adoption. In response, this article presents the results of a field experiment investigating wake steering in three-turbine arrays at an onshore wind farm in Italy. This experiment was performed as part of the European CL-Windcon project. While important, this experiment excludes an analysis of the structural loads and focuses solely on the effects of wake steering on power production. The measurements show increases in power production of up to 35 % for two-turbine interactions and up to 16 % for three-turbine interactions. However, losses in power production are seen for various regions of wind directions too. In addition to the gains achieved through wake steering at downstream turbines, more interesting to note is that a significant share in gains is from the upstream turbines, showing an increased power production of the yawed turbine itself compared to baseline operation for some wind directions. Furthermore, the surrogate model, while capturing the general trends of wake interaction, lacks the details necessary to accurately represent the measurements. This article supports the notion that further research is necessary, notably on the topics of wind farm modeling and experiment design, before wake steering will lead to consistent energy gains on commercial wind farms., Team Jan-Willem van Wingerden

Involving air traffic controllers and pilots into the bird strike prevention process is considered an essential step to increase aviation and avian safety. Prior to implementing operational measures such as real-time warning systems, it is vital to evaluate their feasibility. This paper studies the efficacy of a bird strike advisory system for air traffic control. In addition to the potential safety benefit, the possible impact on airport operations is analyzed. To this end, a previously developed collision avoidance algorithm underlying the system was tested in fast-time Monte Carlo simulations involving various air traffic and bird densities to obtain representative conclusions for different operational conditions. The results demonstrate the strong safety potential of operational bird strike prevention in case of precise bird movement prediction. Unless airports operate close to their capacity limits while bird abundance is high, the induced delays remain tolerable. Prioritization of hazardous strikes involving large individuals as well as flocks of birds are expected to support operational feasibility in all conditions, Control & Simulation, Control & Operations

The concept of wake steering on wind farms for power maximization has gained significant popularity over the last decade. Recent field trials described in the literature not only demonstrate the real potential of wake steering on commercial wind farms but also show that wake steering does not yet consistently lead to an increase in energy production for all inflow conditions. Moreover, a recent survey among experts shows that validation of the concept currently remains the largest barrier to adoption. In response, this article presents the results of a field experiment investigating wake steering in three-turbine arrays at an onshore wind farm in Italy. This experiment was performed as part of the European CL-Windcon project. While important, this experiment excludes an analysis of the structural loads and focuses solely on the effects of wake steering on power production. The measurements show increases in power production of up to 35 % for two-turbine interactions and up to 16 % for three-turbine interactions. However, losses in power production are seen for various regions of wind directions too. In addition to the gains achieved through wake steering at downstream turbines, more interesting to note is that a significant share in gains is from the upstream turbines, showing an increased power production of the yawed turbine itself compared to baseline operation for some wind directions. Furthermore, the surrogate model, while capturing the general trends of wake interaction, lacks the details necessary to accurately represent the measurements. This article supports the notion that further research is necessary, notably on the topics of wind farm modeling and experiment design, before wake steering will lead to consistent energy gains on commercial wind farms., Team Jan-Willem van Wingerden

Owing to differing and complex snow geophysical properties, radar waves of different wavelengths undergo variable penetration through snow-covered sea ice. However, the mechanisms influencing radar altimeter backscatter from snow-covered sea ice, especially at Ka-and Ku-band frequencies, and the impact on the Ka-and Ku-band radar scattering horizon or the "track point"(i.e. the scattering layer depth detected by the radar re-tracker) are not well understood. In this study, we evaluate the Ka-and Ku-band radar scattering horizon with respect to radar penetration and ice floe buoyancy using a first-order scattering model and the Archimedes principle. The scattering model is forced with snow depth data from the European Space Agency (ESA) climate change initiative (CCI) round-robin data package, in which NASA's Operation IceBridge (OIB) data and climatology are included, and detailed snow geophysical property profiles from the Canadian Arctic. Our simulations demonstrate that the Ka-and Ku-band track point difference is a function of snow depth; however, the simulated track point difference is much smaller than what is reported in the literature from the Ku-band CryoSat-2 and Ka-band SARAL/AltiKa satellite radar altimeter observations. We argue that this discrepancy in the Ka-and Ku-band track point differences is sensitive to ice type and snow depth and its associated geophysical properties. Snow salinity is first increasing the Ka-and Ku-band track point difference when the snow is thin and then decreasing the difference when the snow is thick (> 0:1 m). A relationship between the Ku-band radar scattering horizon and snow depth is found. This relationship has implications for (1) the use of snow climatology in the conversion of radar freeboard into sea ice thickness and (2) the impact of variability in measured snow depth on the derived ice thickness. For both (1) and (2), the impact of using a snow climatology versus the actual snow depth is relatively small o

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Newman, L., Heil, P., Trebilco, R., Katsumata, K., Constable, A., van Wijk, E., Assmann, K., Beja, J., Bricher, P., Colemans, R., Costa, D., Diggs, S., Farneti, R., Fawcett, S., Gille, S. T., Hendry, K. R., Henley, S., Hofmann, E., Maksym, T., MazIoff, M., Meijers, A., Meredith, M. M., Moreau, S., Ozsor, B., Robertson, R., Schloss, I., Schofield, O., Shi, J., Sikes, E., Smith, I. J., Swart, S., Wahlin, A., Williams, G., Williams, M. J. M., Herraiz-Borreguero, L., Kern, S., Liesers, J., Massom, R. A., Melbourne-Thomas, J., Miloslavich, P., & Spreen, G. Delivering sustained, coordinated, and integrated observations of the Southern Ocean for global impact. Frontiers in Marine Science, 6, (2019): 433, doi:10.3389/fmars.2019.00433., The Southern Ocean is disproportionately important in its effect on the Earth system, impacting climatic, biogeochemical, and ecological systems, which makes recent observed changes to this system cause for global concern. The enhanced understanding and improvements in predictive skill needed for understanding and projecting future states of the Southern Ocean require sustained observations. Over the last decade, the Southern Ocean Observing System (SOOS) has established networks for enhancing regional coordination and research community groups to advance development of observing system capabilities. These networks support delivery of the SOOS 20-year vision, which is to develop a circumpolar system that ensures time series of key variables, and delivers the greatest impact from data to all key end-users. Although the Southern Ocean remains one of the least-observed ocean regions, enhanced international coordination and advances in autonomous platforms have resulted in progress toward sustained observations of this region. Since 2009, the Southern Ocean community has deployed over 5700 observational platforms south of 40°S. Large-scale, multi-year or sustained, multidisciplinary efforts have been supported and are now delivering observations of essential variables at space and time scales that enable assessment of changes being observed in Southern Ocean systems. The improved observational coverage, however, is predominantly for the open ocean, encompasses the summer, consists of primarily physical oceanographic variables, and covers surface to 2000 m. Significant gaps remain in observations of the ice-impacted ocean, the sea ice, depths >2000 m, the air-ocean-ice interface, biogeochemical and biological variables, and for seasons other than summer. Addressing these data gaps in a sustained way requires parallel advances in coordination networks, cyberinfrastructure and data management tools, observational platform and sensor technology, two-way platform interrogati, PH was supported by the Australian Government’s Cooperative Research Centers Program through the Antarctica Climate and Ecosystems Cooperative Research Centre, and the International Space Science Institute’s team grant #406. This work contributes to the Australian Antarctica Science projects 4301 and 4390.

The Southern Ocean is disproportionately important in its effect on the Earth system, impacting climatic, biogeochemical and ecological systems, which makes recent observed changes to this system cause for global concern. The enhanced understanding and improvements in predictive skill needed for understanding and projecting future states of the Southern Ocean require sustained observations. Over the last decade, the Southern Ocean Observing System (SOOS) has established networks for enhancing regional coordination and research community groups to advance development of observing system capabilities. These networks support delivery of the SOOS 20-year vision, which is to develop a circumpolar system that ensures time series of key variables, and deliver the greatest impact from data to all key end-users. Although the Southern Ocean remains one of the least-observed ocean regions, enhanced international coordination and advances in autonomous platforms have resulted in progress towards addressing the need for sustained observations of this region. Since 2009, the Southern Ocean community has deployed over 5700 observational platforms south of 40°S. Large-scale, multi-year or sustained, multidisciplinary efforts have been supported and are now delivering observations of essential variables at space and time scales that enable assessment of changes being observed in Southern Ocean systems. The improved observational coverage, however, is predominantly for the open ocean, encompasses the summer, consists of primarily physical oceanographic variables and covers surface to 2000 m. Significant gaps remain in observations of the ice-impacted ocean, the sea ice, depths more than 2000 m, the air-sea-ice interface, biogeochemical and biological variables, and for seasons other than summer. Addressing these data gaps in a sustained way requires parallel advances in coordination networks, cyberinfrastructure and data management tools, observational platform and sensor technology

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Newman, L., Heil, P., Trebilco, R., Katsumata, K., Constable, A., van Wijk, E., Assmann, K., Beja, J., Bricher, P., Colemans, R., Costa, D., Diggs, S., Farneti, R., Fawcett, S., Gille, S. T., Hendry, K. R., Henley, S., Hofmann, E., Maksym, T., MazIoff, M., Meijers, A., Meredith, M. M., Moreau, S., Ozsor, B., Robertson, R., Schloss, I., Schofield, O., Shi, J., Sikes, E., Smith, I. J., Swart, S., Wahlin, A., Williams, G., Williams, M. J. M., Herraiz-Borreguero, L., Kern, S., Liesers, J., Massom, R. A., Melbourne-Thomas, J., Miloslavich, P., & Spreen, G. Delivering sustained, coordinated, and integrated observations of the Southern Ocean for global impact. Frontiers in Marine Science, 6, (2019): 433, doi:10.3389/fmars.2019.00433., The Southern Ocean is disproportionately important in its effect on the Earth system, impacting climatic, biogeochemical, and ecological systems, which makes recent observed changes to this system cause for global concern. The enhanced understanding and improvements in predictive skill needed for understanding and projecting future states of the Southern Ocean require sustained observations. Over the last decade, the Southern Ocean Observing System (SOOS) has established networks for enhancing regional coordination and research community groups to advance development of observing system capabilities. These networks support delivery of the SOOS 20-year vision, which is to develop a circumpolar system that ensures time series of key variables, and delivers the greatest impact from data to all key end-users. Although the Southern Ocean remains one of the least-observed ocean regions, enhanced international coordination and advances in autonomous platforms have resulted in progress toward sustained observations of this region. Since 2009, the Southern Ocean community has deployed over 5700 observational platforms south of 40°S. Large-scale, multi-year or sustained, multidisciplinary efforts have been supported and are now delivering observations of essential variables at space and time scales that enable assessment of changes being observed in Southern Ocean systems. The improved observational coverage, however, is predominantly for the open ocean, encompasses the summer, consists of primarily physical oceanographic variables, and covers surface to 2000 m. Significant gaps remain in observations of the ice-impacted ocean, the sea ice, depths >2000 m, the air-ocean-ice interface, biogeochemical and biological variables, and for seasons other than summer. Addressing these data gaps in a sustained way requires parallel advances in coordination networks, cyberinfrastructure and data management tools, observational platform and sensor technology, two-way platform interrogati, PH was supported by the Australian Government’s Cooperative Research Centers Program through the Antarctica Climate and Ecosystems Cooperative Research Centre, and the International Space Science Institute’s team grant #406. This work contributes to the Australian Antarctica Science projects 4301 and 4390.

The Southern Ocean is disproportionately important in its effect on the Earth system, impacting climatic, biogeochemical and ecological systems, which makes recent observed changes to this system cause for global concern. The enhanced understanding and improvements in predictive skill needed for understanding and projecting future states of the Southern Ocean require sustained observations. Over the last decade, the Southern Ocean Observing System (SOOS) has established networks for enhancing regional coordination and research community groups to advance development of observing system capabilities. These networks support delivery of the SOOS 20-year vision, which is to develop a circumpolar system that ensures time series of key variables, and deliver the greatest impact from data to all key end-users. Although the Southern Ocean remains one of the least-observed ocean regions, enhanced international coordination and advances in autonomous platforms have resulted in progress towards addressing the need for sustained observations of this region. Since 2009, the Southern Ocean community has deployed over 5700 observational platforms south of 40°S. Large-scale, multi-year or sustained, multidisciplinary efforts have been supported and are now delivering observations of essential variables at space and time scales that enable assessment of changes being observed in Southern Ocean systems. The improved observational coverage, however, is predominantly for the open ocean, encompasses the summer, consists of primarily physical oceanographic variables and covers surface to 2000 m. Significant gaps remain in observations of the ice-impacted ocean, the sea ice, depths more than 2000 m, the air-sea-ice interface, biogeochemical and biological variables, and for seasons other than summer. Addressing these data gaps in a sustained way requires parallel advances in coordination networks, cyberinfrastructure and data management tools, observational platform and sensor technology

We report on results of a systematic inter-comparison of 10 global sea-ice concentration (SIC) data products at 12.5 to 50.0 km grid resolution for both the Arctic and the Antarctic. The products are compared with each other with respect to differences in SIC, sea-ice area (SIA), and sea-ice extent (SIE), and they are compared against a global wintertime near-100 % reference SIC data set for closed pack ice conditions and against global year-round ship-based visual observations of the sea-ice cover. We can group the products based on the concept of their SIC retrieval algorithms. Group I consists of data sets using the self-optimizing EUMETSAT OSI SAF and ESA CCI algorithms. Group II includes data using the Comiso bootstrap algorithm and the NOAA NSIDC sea-ice concentration climate data record (CDR). The standard NASA Team and the ARTIST Sea Ice (ASI) algorithms are put into group III, and NASA Team 2 is the only element of group IV. The three CDRs of group I (SICCI-25km, SICCI-50km, and OSI-450) are biased low compared to a 100 % reference SIC data set with biases of −0.4 % to −1.0 % (Arctic) and −0.3 % to −1.1 % (Antarctic). Products of group II appear to be mostly biased high in the Arctic by between +1.0 % and +3.5 %, while their biases in the Antarctic range from −0.2 % to +0.9 %. Group III product biases are different for the Arctic, +0.9 % (NASA Team) and −3.7 % (ASI), but similar for the Antarctic, −5.4 % and −5.6 %, respectively. The standard deviation is smaller in the Arctic for the quoted group I products (1.9 % to 2.9 %) and Antarctic (2.5 % to 3.1 %) than for group II and III products: 3.6 % to 5.0 % for the Arctic and 4.0 % to 6.5 % for the Antarctic. We refer to the paper to understand why we could not give values for group IV here. We discuss the impact of truncating the SIC distribution, as naturally retrieved by the algorithms around the 100 % sea-ice concentration end. We show that evaluation studies of such truncated SIC products can result in m

We introduce the OSI-450, the SICCI-25km and the SICCI-50km climate datarecords of gridded global sea-ice concentration. These three records arederived from passive microwave satellite data and offer three distinct advantages compared to existing records: first, all three records provide quantitative information on uncertainty and possibly applied filtering at every grid point and every time step. Second, they are based on dynamic tiepoints, which capture the time evolution of surface characteristics of the ice cover and accommodate potential calibration differences between satellite missions. Third, they are produced in the context of sustained services offering committed extension, documentation, traceability, and user support.The three records differ in the underlying satellite data (SMMR & SSM/I& SSMIS or AMSR-E & AMSR2), in the imaging frequency channels (37 GHzand either 6 or 19 GHz), in their horizontal resolution (25 or 50 km), and in the time period they cover. We introduce the underlying algorithms and provide an evaluation. We find that all three records compare well within dependent estimates of sea-ice concentration both in regions with very highsea-ice concentration and in regions with very low sea-ice concentration. We hence trust that these records will prove helpful for a better understanding of the evolution of the Earth's sea-ice cover.

Wind energy is one of the fastest growing energy sources, leading to important research efforts targeting costs reduction, improved reliability and grid integration of the wind farms. The development of wind farm simulation tools is thus particularly important, as numerical approaches offer a convenient framework for elaborating control strategies aimed at responding to a grid demand or at mitigating the negative effects related to the rotor wakes. Indeed, in a wind farm configuration, the wake phenomena are responsible for a decrease in power production and a shortening of the lifetime of the turbines, and have a direct impact on the Levelized Cost of Energy. Numerical tools thus have to accurately capture the physics of the rotors and wakes and the unsteady nature of a wind farm production, at a reasonable computational cost. This work aims at achieving this by using Large Eddy Simulation on coarse meshes, combined with an Actuator Disk (AD) method for the wind turbine model. This last approach implies an averaged effect of the blade forces on the surface swept by the rotor. A major effort is made in order to have the most accurate response of the AD, in spite of the underlying approximation and of its coarse resolution: we here consider a rotating disk, for which the loads are estimated from local disk velocities, and a new methodology is implemented to enable the use of a tip-loss correction in wind farm flows. This correction aims at improving the AD behavior by accounting for the differences between a disk method and a discrete blade type approach. This implemented AD is first verified in terms of aerodynamics, loads and wake statistics for a single wind turbine, and results are compared to a higher fidelity approach at a finer resolution, here a Vortex Particle-Mesh method coupled to immersed lifting lines. In a second part, the AD is equipped with realistic control schemes and used in wind farm simulations. These aim at several purposes: (i) to evaluate the, (FSA - Sciences de l'ingénieur) -- UCL, 2018

In order to derive long-term changes in sea-ice volume, a multi-decadal sea-ice thickness record is required. CryoSat-2 has showcased the potential of radar altimetry for sea-ice mass-balance estimation over the recent years. However, precursor altimetry missions such as Environmental Satellite (Envisat) have not been exploited to the same extent so far. Combining both missions to acquire a decadal sea-ice volume data set requires a method to overcome the discrepancies due to different footprint sizes from either pulse-limited or beam-sharpened radar echoes. In this study, we implemented an inter-mission-consistent surface-type classification scheme for both hemispheres, based on the waveform pulse peakiness, leading-edge width, and surface backscatter. In order to achieve a consistent retracking procedure, we adapted the threshold first-maximum retracker algorithm, previously used only for CryoSat-2, to develop an adaptive retracker threshold that depends on waveform characteristics. With our method, we produce a global and consistent freeboard data set for CryoSat-2 and Envisat. This novel data set features a maximum monthly difference in the mission-overlap period of 2.2cm (2.7cm) for the Arctic (Antarctic) based on all gridded values with spatial resolution of 25 km × 25 km and 50 km × 50 km for the Arctic and Antarctic, respectively.

In order to derive long-term changes in sea-ice volume, a multi-decadal sea-ice thickness record is required. CryoSat-2 has showcased the potential of radar altimetry for sea-ice mass-balance estimation over the recent years. However, precursor altimetry missions such as Environmental Satellite (Envisat) have not been exploited to the same extent so far. Combining both missions to acquire a decadal sea-ice volume data set requires a method to overcome the discrepancies due to different footprint sizes from either pulse-limited or beam-sharpened radar echoes. In this study, we implemented an inter-mission-consistent surface-type classification scheme for both hemispheres, based on the waveform pulse peakiness, leading-edge width, and surface backscatter. In order to achieve a consistent retracking procedure, we adapted the threshold first-maximum retracker algorithm, previously used only for CryoSat-2, to develop an adaptive retracker threshold that depends on waveform characteristics. With our method, we produce a global and consistent freeboard data set for CryoSat-2 and Envisat. This novel data set features a maximum monthly difference in the mission-overlap period of 2.2cm (2.7cm) for the Arctic (Antarctic) based on all gridded values with spatial resolution of 25 km × 25 km and 50 km × 50 km for the Arctic and Antarctic, respectively.

Global warming has led to a strong deterioration of the Arctic sea ice cover. Ice thickness, age and coverage have been strongly declining in recent years. Brine channels that form in sea ice when seawater freezes represent a unique habitat for bacteria, algae, proto- and small metazoans. We hypothesized that the loss of multi-year ice and the more prevalent formation of first-year ice even in central regions of the Arctic will lead to changes in the Arctic sea ice meiofauna community composition. We therefore analysed the sea ice meiofauna community composition of three different ice types sampled in summer and autumn 2007. Young, thin ice of few cm thickness was typified by taxa of pelagic origin or with good swimming abilities (ciliates, pelagic foraminifera, rotifers and platyhelminthes). Harpacticoid copepods and nematodes with poor swimming abilities were prevalent in older, thicker (>0.5 m) first- and multi-year ice. Brash ice—which was likely a mix of older broken ice, slush and pancake ice—was characterized by a high abundance of platyhelminthes and rotifers. An experimental analysis of colonization efficiencies of artificial thin ice also revealed that species with poor swimming ability are less successful to colonize newly forming thin ice. We conclude that observed and predicted changes in the ice formation regime will likely result in changes in the composition of Arctic sea ice communities. We predict negative effects particularly for species with low dispersal capacities like harpacticoid copepods and endemic nematodes, as these are less successful in colonizing newly forming thin ice.

Global warming has led to a strong deterioration of the Arctic sea ice cover. Ice thickness, age and coverage have been strongly declining in recent years. Brine channels that form in sea ice when seawater freezes represent a unique habitat for bacteria, algae, proto- and small metazoans. We hypothesized that the loss of multi-year ice and the more prevalent formation of first-year ice even in central regions of the Arctic will lead to changes in the Arctic sea ice meiofauna community composition. We therefore analysed the sea ice meiofauna community composition of three different ice types sampled in summer and autumn 2007. Young, thin ice of few cm thickness was typified by taxa of pelagic origin or with good swimming abilities (ciliates, pelagic foraminifera, rotifers and platyhelminthes). Harpacticoid copepods and nematodes with poor swimming abilities were prevalent in older, thicker (>0.5 m) first- and multi-year ice. Brash ice—which was likely a mix of older broken ice, slush and pancake ice—was characterized by a high abundance of platyhelminthes and rotifers. An experimental analysis of colonization efficiencies of artificial thin ice also revealed that species with poor swimming ability are less successful to colonize newly forming thin ice. We conclude that observed and predicted changes in the ice formation regime will likely result in changes in the composition of Arctic sea ice communities. We predict negative effects particularly for species with low dispersal capacities like harpacticoid copepods and endemic nematodes, as these are less successful in colonizing newly forming thin ice.

Recent salinity changes in the Southern Ocean are among the most prominent signals of climate change in the global ocean, yet their underlying causes have not been firmly established. Here we propose that trends in the northward transport of Antarctic sea ice are a major contributor to these changes. Using satellite observations supplemented by sea-ice reconstructions, we estimate that wind-driven northward freshwater transport by sea ice increased by 20 ± 10 per cent between 1982 and 2008. The strongest and most robust increase occurred in the Pacific sector, coinciding with the largest observed salinity changes. We estimate that the additional freshwater for the entire northern sea-ice edge entails a freshening rate of −0.02 ± 0.01 grams per kilogram per decade in the surface and intermediate waters of the open ocean, similar to the observed freshening. The enhanced rejection of salt near the coast of Antarctica associated with stronger sea-ice export counteracts the freshening of both continental shelf and newly formed bottom waters due to increases in glacial meltwater. Although the data sources underlying our results have substantial uncertainties, regional analyses13 and independent data from an atmospheric reanalysis support our conclusions. Our finding that northward sea-ice freshwater transport is also a key determinant of the mean salinity distribution in the Southern Ocean further underpins the importance of the sea-ice-induced freshwater flux. Through its influence on the density structure of the ocean, this process has critical consequences for the global climate by affecting the exchange of heat, carbon and nutrients between the deep ocean and surface waters

Recent salinity changes in the Southern Ocean are among the most prominent signals of climate change in the global ocean, yet their underlying causes have not been firmly established. Here we propose that trends in the northward transport of Antarctic sea ice are a major contributor to these changes. Using satellite observations supplemented by sea-ice reconstructions, we estimate that wind-driven northward freshwater transport by sea ice increased by 20 ± 10 per cent between 1982 and 2008. The strongest and most robust increase occurred in the Pacific sector, coinciding with the largest observed salinity changes. We estimate that the additional freshwater for the entire northern sea-ice edge entails a freshening rate of −0.02 ± 0.01 grams per kilogram per decade in the surface and intermediate waters of the open ocean, similar to the observed freshening. The enhanced rejection of salt near the coast of Antarctica associated with stronger sea-ice export counteracts the freshening of both continental shelf and newly formed bottom waters due to increases in glacial meltwater. Although the data sources underlying our results have substantial uncertainties, regional analyses13 and independent data from an atmospheric reanalysis support our conclusions. Our finding that northward sea-ice freshwater transport is also a key determinant of the mean salinity distribution in the Southern Ocean further underpins the importance of the sea-ice-induced freshwater flux. Through its influence on the density structure of the ocean, this process has critical consequences for the global climate by affecting the exchange of heat, carbon and nutrients between the deep ocean and surface waters

Sea-ice concentrations derived from satellite microwave brightness temperatures are less accurate during summer. In the Arctic Ocean the lack of accuracy is primarily caused by melt ponds, but also by changes in the properties of snow and the sea-ice surface itself. We investigate the sensitivity of eight sea-ice concentration retrieval algorithms to melt ponds by comparing sea-ice concentration with the melt-pond fraction. We derive gridded daily sea-ice concentrations from microwave brightness temperatures of summer 2009. We derive the daily fraction of melt ponds, open water between ice floes, and the ice-surface fraction from contemporary Moderate Resolution Spectroradiometer (MODIS) reflectance data. We only use grid cells where the MODIS sea ice concentration, which is the melt-pond fraction plus the ice-surface fraction, exceeds 90 %. For one group of algorithms, e.g., Bristol and Comiso bootstrap frequency mode (Bootstrap_f), sea-ice concentrations are linearly related to the MODIS melt-pond fraction quite clearly after June. For other algorithms, e.g., Near9OGHz and Comiso bootstrap polarization mode (Bootstrap_p), this relationship is weaker and develops later in summer. We attribute the variation of the sensitivity to the melt-pond fraction across the algorithms to a different sensitivity of the brightness temperatures to snow-property variations. We find an underestimation of the sea-ice concentration by between 14 % (Bootstrap_f) and 26 % (Bootstrap_p) for 100 % sea ice with a melt-pond fraction of 40 %. The underestimation reduces to 0 % for a melt pond fraction of 20 %. In presence of real open water between ice floes, the sea-ice concentration is overestimated by between 26 % (Bootstrap_f) and 14 % (Bootstrap_p) at 60 % sea-ice concentration and by 20 % across all algorithms at 80 % sea-ice concentration. None of the algorithms investigated performs best based on our investigation of data from summer 2009. We suggest that those algorithms which are m

We present the coupling of a vortex particle-mesh method with immersed lifting lines for the Large Eddy Simulation of wind turbine wakes. The method relies on the Lagrangian discretization of the Navier–Stokes equations in vorticity-velocity formulation. Advection is handled by the particles while the mesh allows the evaluation of the differential operators and the use of fast Poisson solvers. We use a Fourier-based fast Poisson solver which simultaneously allows unbounded directions and inlet/outlet boundaries. The method also allows the feeding of a turbulent incoming flow. We apply this methodology to the study of large scale aerodynamics and wake behavior of tandem wind turbines. We analyze the generators performance, unsteady power, loads and aerodynamics they are subjected to. The average flow field of the wakes is also computed and turbulence statistics are extracted. In particular, we investigate the influence of the type of turbulent inflow used—precomputed or synthetic—, and study wake meandering.

We present the coupling of a vortex particle-mesh method with immersed lifting lines. The method relies on the Lagrangian discretization of the Navier-Stokes equations in vorticity- velocity formulation. Advection is handled by the particles while the mesh allows the evaluation of the differential operators and the use of fast Poisson solvers. We use a Fourier-based fast Poisson solver which simultaneously allows unbounded directions and inlet/outlet boundaries. A lifting line approach models the vorticity sources in the flow. Its immersed treatment efficiently captures the development of vorticity from thin sheets into a three-dimensional field. We apply this approach to the simulation of a wind turbine wake at very high Reynolds number. The combined use of particles and multiscale subgrid models allows the capture of wake dynamics with minimal spurious diffusion and dispersion, while being computationally efficient.

Advanced Microwave Scanning Radiometer (AMSR-E) snow-depth data for Antarctic sea ice are compared with ship-based visual observations of snow depth, ice type and ridged-ice fraction, and with satellite C-band and Ku-band radar backscatter observations for two ship cruises into the Weddell Sea (ISPOL 2004–05, WWOS 2006) and one cruise into the Bellingshausen Sea (SIMBA 2007) during late winter/spring. Most (>75%) AMSR-E and ship-based snow-depth observations agree within 0.2 m during WWOS and SIMBA. Remaining observations indicate substantial underestimations of snow depths by AMSR-E data. These underestimations tend to increase with the ridged-ice fraction for WWOS and SIMBA. In areas with large snow depths, a combination of relatively stable low C-band radar backscatter and variable Ku-band radar backscatter is associated with undeformed first-year ice and may indicate snow metamorphism at this time of year during SIMBA. In areas with small snow depths, a combination of relatively stable low Ku-band radar backscatter, high C-band radar backscatter and low C-band radar backscatter standard deviations is associated with rough first-year ice during SIMBA. This information can help to better understand causes of the observed AMSR-E snow-depth bias during late-winter/spring conditions with decreasing average snow depth and to delineate areas where this bias occurs.

Advanced Microwave Scanning Radiometer (AMSR-E) snow-depth data for Antarctic sea ice are compared with ship-based visual observations of snow depth, ice type and ridged-ice fraction, and with satellite C-band and Ku-band radar backscatter observations for two ship cruises into the Weddell Sea (ISPOL 2004–05, WWOS 2006) and one cruise into the Bellingshausen Sea (SIMBA 2007) during late winter/spring. Most (>75%) AMSR-E and ship-based snow-depth observations agree within 0.2 m during WWOS and SIMBA. Remaining observations indicate substantial underestimations of snow depths by AMSR-E data. These underestimations tend to increase with the ridged-ice fraction for WWOS and SIMBA. In areas with large snow depths, a combination of relatively stable low C-band radar backscatter and variable Ku-band radar backscatter is associated with undeformed first-year ice and may indicate snow metamorphism at this time of year during SIMBA. In areas with small snow depths, a combination of relatively stable low Ku-band radar backscatter, high C-band radar backscatter and low C-band radar backscatter standard deviations is associated with rough first-year ice during SIMBA. This information can help to better understand causes of the observed AMSR-E snow-depth bias during late-winter/spring conditions with decreasing average snow depth and to delineate areas where this bias occurs.

We investigate schemes to accelerate the decay of aircraft trailing vortices. These structures are susceptible to several instabilities that lead to their eventual destruction. We employ an Evolution Strategy to design a lift distribution and a lift perturbation scheme that minimize the wake hazard as proposed by Crouch et al. (2001). The performance of a scheme is measured as the reduction of the mean rolling moment that would be induced on a following aircraft; it is computed by means of a Direct Numerical Simulation using a parallel vortex particle code. We find a configuration and a perturbation scheme characterized by an intermediate wavelength $lambda sim 4.64$, necessary to trigger medium wavelength instabilities between tail and flap vortices and subsequently amplify long wavelength modes.

The direct numerical simulation (DNS) of the channel flow with an anisotropic compliant surface is performed in order to investigate its drag reduction effect in a fully developed turbulent flow. The surface is passievely driven by the pressure and wall-shear stress fluctuations, and the surface velocity provides a boundary condition for the fluid velocity field. A stochastic optimization method (CMA-ES)is used to optimize the parameters of the anisotropic compliant surface. The optimization identifies several sets of parameters that resuslt in a reduction of the friction drag with a maximum reduction rate of 8%. The primary mechanism for drag reduction is attributed to the decrease of the Reynolds Shear Stress (RSS) near the wall induced by the anisotropic structure and kinematics of the surface. The resultant wall motion is a uniform wave traveling downstream.

The direct numerical simulation (DNS) of the channel flow with an anisotropic compliant surface is performed in order to investigate its drag reduction effect in a fully developed turbulent flow. The surface is passively driven by the pressure and wall-shear stress fluctuations, and the surface velocity provides a boundary condition for the fluid velocity field. A stochastic optimization method (CMA-ES) is used to optimize the parameters of the anisotropic compliant surface. The optimization identifies several sets of parameters that result in a reduction of the friction drag with a maximum reduction rate of 8%. The primary mechanism for drag reduction is attributed to the decrease of the Reynolds Shear Stress (RSS) near the wall induced by the anisotropic structure and kinematics of the surface. The resultant wall motion is a uniform wave traveling downstream.

[no abstract]

Sea ice is a very important component of the climate system. While the Arctic sea ice extent has retreated during the past 20 years, it has remained constant in the Antarctic. In order to better understand the role of sea ice in the climate system in the context of global warming currently used coupled Atmosphere-Ocean Global Circulation Models have to be improved. This requires to know the sea ice concentration C for a long period for both hemispheres and at the best possible spatial resolution. Currently used methods to obtain C like the NASA Team (NT) algorithm are based on data acquired by the Special Sensor Microwave/Imager (SSM/I) at 19 and 37GHz. The SEA LION (SL) algorithm presented here allows to infer C from the polarization P at 85GHz taking advantage of the higher spatial resolution at this frequency. However, the decrease of P caused by the weather influence leads to an overestimation of C. Therefore, P is corrected using a radiative transfer model and atmospheric data taken from Numerical Weather Prediction models and/or derived from SSM/I measurements. The various sea ice and snow properties are considered calculating monthly sea ice tie points. The average standard deviation of C derived with the SL algorithm is 12% for C < 50% and below 5% for C > 90%. The SL ice edge agrees within 10km with the one evident in VIS/IR images. The SL ice concentration gradient across the marginal ice zone (MIZ) agrees much better with the one evident in SAR images compared to results of the NT algorithm. Using the higher spatial resolution at 85GHz the SL algorithm allows to detect smaller open water areas than known algorithms. A major limitation of the SL algorithm arises from the quality of atmospheric data needed for the weather correction. A spatial resolution of these data lower than the 85GHz SSM/I channels and/or a time lag larger than half an hour between both data sets can cause relative errors above 100%, particulary in the cloud-covered parts of the MIZ.

Sea ice is a very important component of the climate system. While the Arctic sea ice extent has retreated during the past 20 years, it has remained constant in the Antarctic. In order to better understand the role of sea ice in the climate system in the context of global warming currently used coupled Atmosphere-Ocean Global Circulation Models have to be improved. This requires to know the sea ice concentration C for a long period for both hemispheres and at the best possible spatial resolution. Currently used methods to obtain C like the NASA Team (NT) algorithm are based on data acquired by the Special Sensor Microwave/Imager (SSM/I) at 19 and 37GHz. The SEA LION (SL) algorithm presented here allows to infer C from the polarization P at 85GHz taking advantage of the higher spatial resolution at this frequency. However, the decrease of P caused by the weather influence leads to an overestimation of C. Therefore, P is corrected using a radiative transfer model and atmospheric data taken from Numerical Weather Prediction models and/or derived from SSM/I measurements. The various sea ice and snow properties are considered calculating monthly sea ice tie points. The average standard deviation of C derived with the SL algorithm is 12% for C < 50% and below 5% for C > 90%. The SL ice edge agrees within 10km with the one evident in VIS/IR images. The SL ice concentration gradient across the marginal ice zone (MIZ) agrees much better with the one evident in SAR images compared to results of the NT algorithm. Using the higher spatial resolution at 85GHz the SL algorithm allows to detect smaller open water areas than known algorithms. A major limitation of the SL algorithm arises from the quality of atmospheric data needed for the weather correction. A spatial resolution of these data lower than the 85GHz SSM/I channels and/or a time lag larger than half an hour between both data sets can cause relative errors above 100%, particulary in the cloud-covered parts of the MIZ.

Sea ice is a very important component of the climate system. While the Arctic sea ice extent has retreated during the past 20 years, it has remained constant in the Antarctic. In order to better understand the role of sea ice in the climate system in the context of global warming currently used coupled Atmosphere-Ocean Global Circulation Models have to be improved. This requires to know the sea ice concentration C for a long period for both hemispheres and at the best possible spatial resolution. Currently used methods to obtain C like the NASA Team (NT) algorithm are based on data acquired by the Special Sensor Microwave/Imager (SSM/I) at 19 and 37GHz. The SEA LION (SL) algorithm presented here allows to infer C from the polarization P at 85GHz taking advantage of the higher spatial resolution at this frequency. However, the decrease of P caused by the weather influence leads to an overestimation of C. Therefore, P is corrected using a radiative transfer model and atmospheric data taken from Numerical Weather Prediction models and/or derived from SSM/I measurements. The various sea ice and snow properties are considered calculating monthly sea ice tie points. The average standard deviation of C derived with the SL algorithm is 12% for C < 50% and below 5% for C > 90%. The SL ice edge agrees within 10km with the one evident in VIS/IR images. The SL ice concentration gradient across the marginal ice zone (MIZ) agrees much better with the one evident in SAR images compared to results of the NT algorithm. Using the higher spatial resolution at 85GHz the SL algorithm allows to detect smaller open water areas than known algorithms. A major limitation of the SL algorithm arises from the quality of atmospheric data needed for the weather correction. A spatial resolution of these data lower than the 85GHz SSM/I channels and/or a time lag larger than half an hour between both data sets can cause relative errors above 100%, particulary in the cloud-covered parts of the MIZ.