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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

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

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.