Wind Components Research Articles

Near-infrared Integral-field Spectroscopy of the Wind Forming Region of CW Leo

Abstract The circumstellar envelope of the carbon star CW Leo exhibited various unexpected changes in recent optical imaging observations. We have performed a follow-up observation using the Near-infrared Integral-Field Spectrograph (NIFS) equipped on the Gemini-North telescope. We report the near-infrared counterparts of a local brightness peak in the optical at the stellar position of CW Leo. On the other hand, a second peak detected at short wavelengths in the J band coincides with the brightest, bluest position in the optical images. The absorption features in the K band are minimized at a radius of 0 . ′ ′ 2 from the predicted stellar position. The reduction of the absorption depths likely indicates dilution of the absorption features by thermal emission of dust grains newly formed at such a radius and heated by radiation from the central star. The broad absorption feature at 1.53 μm is significantly deeper than in template carbon stars, consistent with the presence of a substantial amount of circumstellar material around CW Leo. Its northeastern quadrant lacks circumstellar absorption features and scattered light in the near-infrared regime, which are possibly manifestations of its conical cavity in both gas and dust. In addition, a cross correlation of CO overtone bands indicates that the average expansion velocity of dust grains is smaller to the northern direction, likewise the velocity of transverse wind components derived using the differential proper motion of a circumstellar whirled pattern. The gradual brightening of CW Leo and the changes in its innermost circumstellar envelope need further continuous monitoring observations to properly understand its transitional phase toward the post-asymptotic-giant-branch stage.

The Future of China‐Gulf Solar and Wind Supply Chains

ABSTRACTThis paper examines the medium‐term trajectory of China‐Gulf renewable energy supply chains amid growing global trade restrictions on China. The research explores how the Arab Gulf states, key collaborators in China's renewable energy sector, navigate these challenges, focusing on the dominance of China in global supply chains for solar and wind components. Using a demand‐pull, supply‐push framework, qualitative analysis assesses two potential scenarios: ‘Blue Sky’, where China‐Gulf supply chains grow stronger through ambitious renewable energy targets and expanded foreign direct investment, and ‘Sand Storm’, where geopolitical tensions and export restrictions could weaken these ties. The findings indicate that while supply chain engagement with China has risks, on balance China‐Gulf supply solar and wind technology supply chains are currently robust and projected to remain so in the future. The study concludes with policy recommendations for strengthening China's engagement with the broader Global South, highlighting opportunities for countries as they scale up domestic renewable energy deployment.

Exploring, sampling, and interpreting lunar volatiles in polar cold traps

Numerous missions to the Moon have identified and documented volatile deposits associated with permanently shadowed regions. A series of science goals for the Artemis Program is to explore these volatile deposits and return samples to Earth. Volatiles in these reservoirs may consist of a variety of species whose stable isotope characteristics could elucidate both their sources and the processes instrumental in their formation. For example, the δD of potential contributors to the deposits can be used to identify a uniquely light solar wind component. Because of the exceptionally low temperatures of these volatile deposits, examining and interpreting their stable isotope systems to fulfill Artemis science goals through sampling, preserving, curating, and analyzing these samples are far more difficult than for other sample return missions. Collecting and preserving the samples at cryogenic temperatures dramatically increases science yield but is technologically demanding and poses increased risk during transport.

Optimization of a direct-detection UV wind lidar architecture for 3D wind reconstruction at high altitude

Abstract. An architecture for a UV wind lidar dedicated to measuring vertical and lateral wind in front of an aircraft for gust load alleviation is presented. To optimize performance and robustness, it includes a fiber laser architecture and a Quadri Mach–Zehnder (QMZ) interferometer with a robust design to spectrally analyze the backscattered light. Different lidar parameters have been selected to minimize the standard deviation of wind speed measurement projected onto the laser axis, calculated through end-to-end simulations of the instrument. The optimization involves selecting an emission–reception telescope to maximize the number of collected photons backscattered between 100 and 300 m, a background filter to reduce noise from the scene, and photomultiplier tubes (PMTs) to minimize detection noise. Simulations were performed to evaluate lidar performance as a function of laser parameters. This study led to the selection of three laser architectures, a commercial solid-state laser, a design of a fiber laser, and a hybrid fiber laser, resulting in standard deviations of projected wind speed of 0.17, 0.16, and 0.09 m s−1, respectively, at 10 km altitude. To reconstruct the vertical and lateral wind on the flight path, the lidar is directed along four different directions to measure four different projections of the wind. We analytically calculate (and validate through simulations) the directed angle with respect to the flight direction that minimizes the root mean square error (RMSE) between the reconstructed vertical and lateral wind components and the actual ones, assuming turbulence that follows the von Kármán turbulence model. We found that the optimum angle for an estimation at 100 m is about 50°, resulting in an improvement of about 50 % compared to an angle of 15–30° typically used in current studies.

Transport pathway identification and meteorological driving force spatial-temporal analysis of an extreme dust storm event on South Mongolian Plateau

ABSTRACT Dust storms are destructive extreme weather events that are difficult to detect because of their large spatial distributions and temporal movement characteristics. The Mongolian Plateau is one of the most important dust sources and poses a serious threat to dust storm disasters in north-east Asia. Understanding the transboundary transport pathways and meteorological driving forces of dust is crucial for dust storm prevention and control. We selected one extreme dust storm event that occurred from 19th to 24th March 2023, in the southern Mongolian Plateau, identified its spatial-temporal transport pathways, and analyzed the impact of multiple meteorological components on dust storm occurrences. The daily distribution of dust storms was recognized firstly by using a normalized difference dust index supported by MOD09GA data. ERA-5 hourly data were used to analyze the spatiotemporal variations of meteorological components. By integrating data on the daily distribution of dust storms with the time-series trends of meteorological components, this study identified dewpoint temperature, air temperature, wind components, surface pressure, and precipitation as the key variables influencing the formation and propagation of dust storms. The results showed that dust storm occurrence is associated with a reduction in dewpoint temperature and increase in air dryness. Low-pressure systems are important precursors of dust storm formation, and strong winds drive their propagation and spread. The reversal of these meteorological trends reduces their intensity and extent, while increased precipitation at the end of a dust storm event helps settle dust. These findings provide crucial insights into the meteorological driving forces and predictability of dust storms on the Mongolian Plateau, and can be utilized in other geographical areas prone to dust storm.

Study on Energy‐Saving and Emission Reduction Solutions for the Bearing Heating System of Offshore Wind Turbines: A Case Study of General Electric's Offshore Wind Power Assembly Base

ABSTRACTIn the context of the global transition to renewable energy sources, the offshore wind power sector is confronted with operational inefficiencies during the thermal processing and assembly of wind turbine spindles and components. The research, centered on General Electric's offshore wind turbine assembly facility, addresses the deficiencies in the thermal management of bearing heating systems, the prevalence of rework due to substandard thermal treatments, and the inefficiencies in energy utilization. The paper proposes a targeted strategy comprising three key interventions: (1) The synchronization of bearing heating procedures with the off‐peak electricity tariff regime to mitigate peak demand and associated energy expenditures and carbon footprints. (2) The deployment of a thermoelectric generator (TEG) system to harness and convert waste heat into electrical energy, with meticulous modeling of its thermal dynamics. (3) The engineering of a thermally insulated housing for bearings to curtail thermal losses. The projected outcomes of these interventions are a reduction in electricity costs by 127.83 yuan, a decrease in carbon emissions by 90.41 kg, and a substantial reduction in heat loss. The findings of this research underscore the efficacy of thermal process optimization, waste heat recuperation, and thermal insulation in enhancing the energy efficiency of bearing heating systems, thereby contributing to the broader objectives of energy conservation and emission reduction in the renewable energy sector, which is imperative in the contemporary era of climate change mitigation and sustainable development.

Analysis of the measurement uncertainty for a 3D wind lidar

Abstract. High-resolution three-dimensional (3D) wind velocity measurements are of major importance for the characterization of atmospheric turbulence. The use of a multi-beam wind lidar focusing on a measurement volume from different directions is a promising approach for obtaining such wind data. This paper provides a detailed study of the propagation of measurement uncertainty of a three-beam wind lidar designed for mounting on airborne platforms with geometrical constraints that lead to increased measurement uncertainties of the wind components transverse to the main axis of the system. The uncertainty analysis is based on synthetic wind data generated by an Ornstein–Uhlenbeck process as well as on experimental wind data from airborne and ground-based 3D ultrasonic anemometers. For typical atmospheric conditions, we show that the measurement uncertainty of the transverse components can be reduced by about 30 %–50 % by applying an appropriate post-processing algorithm. Optimized post-processing parameters can be determined in an actual experiment by characterizing measured data in terms of variance and correlation time of wind fluctuations, allowing for the optimized design of a multi-beam wind lidar with strong geometrical limitations.

The Unique Role of the Intraseasonal Zonal Wind in March Over the Equatorial Western Pacific Contributes to Shaping the Subsequent ENSO Development

AbstractThe predictability of the El Niño‐Southern Oscillation (ENSO) is significantly limited by the spring predictability barrier (SPB). Our observational analysis suggests that considering high‐frequency wind components during the spring season may mitigate the SPB impact on ENSO predictability. The intraseasonal zonal wind in March over the equatorial western Pacific initially perturbs the sea surface temperature (SST). It contributes nearly 40% of the east‐west SST gradient after 2–3 months, ranking first among other calendar months. This significant contribution causes March to become the earliest month to effectively indicate the following ENSO direction due to the active eastward‐propagating Madden‐Julian oscillation (MJO) activity. Through the obvious variation of the eastward‐propagating MJO speed, it also shows the possible close relationship between the mean SST state and the interdecadal variability in intraseasonal zonal wind. Additionally, the current strong variability of intraseasonal zonal wind suggests the important role of atmospheric information in recent ENSO development.

Dynamic Analysis of Slender Buildings under Wind Loading

This dissertation project aims to understand and compare methods that simulate the dynamic characteristics of atmospheric wind loads acting on slender structures, with a focus on NBR 6123 and the Synthetic Wind Method. The amount of research conducted on this topic since the 1960s has led to significant advancements in understanding the dynamic behavior of wind. This progress has facilitated the development of methodologies for quantifying its impact on buildings and the continuous refinement of these methodologies up to the present day. In this context, it is possible to encounter two key approaches: NBR 6123 (2023), developed by the Brazilian Association of Technical Standards, and the Synthetic Wind Method, initially proposed by Franco (1993). The Brazilian standard provides two methods to determine maximum values of variables such as acceleration, displacement, and forces for structures subjected to wind, without describing how these values vary over time. Despite advances in wind engineering studies and methodologies, the procedure described in the 1988 version of the standard remained unchanged in its 2023 update. On the other hand, the Synthetic Wind Method, first published in 1993 and subsequently refined until 2014, works by decomposing the fluctuating component of wind into harmonic functions. This approach not only allows to obtain absolute maximum values but also provides the structural response over time. To address this, a comparative study is planned between NBR 6123 (2023) and the most updated version of the Synthetic Wind Method. Additional relevant methods may also be included in the analysis to identify the limitations, advantages, and disadvantages of each approach.

Data imbalance causes underestimation of high ozone pollution in machine learning models: A weighted support vector regression solution

Machine learning (ML) models have been widely utilized for the prediction of ground-level ozone (O3), one of the most concerning air pollutants in China. However, many of the ML models tend to underestimate high O3 levels, likely due to the class imbalance issue within the input training data. In this study, we combined data from ground monitoring stations (CO, NO2, SO2, PM10, PM2.5, MDA8 O3, longitude, and latitude), satellite observations (HCHO column concentration) and meteorological variables (2m temperature, solar radiation, relative humidity, wind components, surface pressure, precipitation, evaporation, boundary layer height, and cloud cover) to assess the impact of data imbalance on prediction performance. Results demonstrated that ML models without considering data imbalance issue severely underestimate high O3 levels. We proposed a sample weighting-based support vector regression model (SVR-W) that fully considered the data imbalance. Based on data from 2026 monitoring stations across 31 provinces in China, the SVR-W model achieved an average bin-slope value between observed and predicted O3 of 0.74 ± 0.12 (s.d.), which is significantly better than commonly used ML models (0.64 ± 0.11). The average bin-RMSE of the SVR-W model was 26.7μg/m3, outperforming other models. The average recall of high O3 levels was 11–31% higher than commonly used ML models. The SVR-W model demonstrated improved prediction performance for both regular and extreme pollutant O3 levels based on the three metrics. Our findings suggest that addressing data imbalance is crucial when applying ML models to environmental data.

Arkenstone - II. A model for unresolved cool clouds entrained in galactic winds in cosmological simulations

Abstract Arkenstone is a new scheme that allows multiphase, stellar feedback-driven winds to be included in coarse resolution cosmological simulations. The evolution of galactic winds and their subsequent impact on the circumgalactic medium are altered by exchanges of mass, energy, momentum, and metals between their component phases. These exchanges are governed by complex, small-scale physical processes that cannot be resolved in cosmological simulations. In this second presentation paper, we describe Arkenstone’s novel cloud particle approach for modelling unresolvable cool clouds entrained in hot, fast winds. This general framework allows models of the cloud–wind interaction, derived from state-of-the-art high-resolution simulations, to be applied in a large-scale context. In this work, we adopt a cloud evolution model that captures simultaneous cloud mass loss to and gain from the ambient hot phase via turbulent mixing and radiative cooling, respectively. We demonstrate the scheme using non-cosmological idealized simulations of a galaxy with a realistic circumgalactic medium component, using the Arepo code. We show that the ability of a high-specific energy wind component to perform preventative feedback may be limited by heavy loading of cool clouds coupled into it. We demonstrate that the diverging evolution of clouds of initially differing masses leads to a complex velocity field for the cool phase and a cloud mass function that varies both spatially and temporally in a non-trivial manner. These latter two phenomena can manifest in the simulation because of our choice of a Lagrangian discretisation of the cloud population, in contrast to other proposed schemes.

Spatiotemporal wind speed forecasting using conditional local convolution and multidimensional meteorology features

Wind speed prediction is crucial for precisely wind power forecasting and reduced maintenance costs. Highland regions, which possess a considerable wind potential, present complex meteorological conditions, making wind speed prediction challenging. Traditional weather forecasting relies on complex statistical methods and extensive prior knowledge. While recent deep learning models have improved prediction accuracy, they often assume uniform influence weight structure, limiting model effectiveness. This study introduces an enhanced Conditional Local Convolution Recurrent Network (CLCRN) model to improve spatiotemporal wind speed forecasting using multidimensional meteorological inputs such as temperature, pressure, and dew point, alongside wind components. This model addresses uniform influence model weight issue by redesigning convolution kernels to better capture local meteorological features and integrating multiple influencing factors. Our model consistently achieves lower Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) values across various prediction intervals (3, 6, 9, and 12 h) compared to other models, supported by the meteorological station data from 2019 to 2021. Furthermore, the spatial distribution of the local convolution weights aligns with local wind velocity patterns in Inner Mongolia, enhancing model interpretability. These results demonstrate potential for practical applications in renewable energy planning and wind dynamics simulation.

Characterisation of the stellar wind in Cyg X-1 via modelling of colour-colour diagrams

Context. Cygnus X-1 (Cyg X-1) is a high-mass X-ray binary where accretion onto the black hole (BH) is mediated by the stellar wind from the blue supergiant companion star HDE 226868. Due to its inclination, the system is a perfect laboratory to study the not yet well-understood stellar wind structure. In fact, depending on the position of the BH along the orbit, X-ray observations can probe different layers of the stellar wind. Deeper wind layers can be investigated at superior conjunction (i.e. null orbital phases). Aims. We aim to characterise the stellar wind in the Cyg X-1/HDE 226868 system, analysing one passage at superior conjunction covered by XMM-Newton during the ‘Cyg X-1 Hard state Observations of a Complete Binary Orbit in X-rays’ (CHOCBOX) campaign. Methods. To analyse the properties of the stellar wind, we computed colour-colour diagrams. Since X-ray absorption is energy-dependent, colour indices provide information on the parameters of the stellar wind, such as the column density, NH, w, and the covering factor, fc. We fitted colour-colour diagrams with models that include both a continuum and a stellar wind component. We used the kernel density estimation method to infer the unknown probability distribution of the data points in the colour-colour diagram, and selected the model corresponding to the highest likelihood. In order to study the temporal evolution of the wind around superior conjunction, we extracted and fitted time-resolved colour-colour diagrams. Results. We found that the model that best describes the shape of the colour-colour diagram of Cyg X-1 at superior conjunction requires the wind to be partially ionised. The shape of the colour-colour diagram strongly varies during the analysed observation, due to concurrent changes of the mean NH, w and the fc of the wind. Our results suggest the existence of a linear scaling between the rapid variability amplitude of NH, w (on timescales between 10 s and 11 ks) and its long-term variations (on timescales > 11 ks). Using the inferred best-fit values, we estimated the stellar mass loss rate to be ∼7 × 10−6 M⊙ yr−1 and the clumps to have a characteristic mass of ∼1017 g.

ДИНАМІЧНІ УМОВИ ФОРМУВАННЯ ПРОСТОРОВИХ ЕКСТРЕМУМІВ ОЗОНОВОГО ШАРУ НАД ТЕРИТОРІЄЮ УКРАЇНИ

The paper examines the conditions for the formation of spatial extremes in total ozone content (TOC) over the territory of Ukraine caused by dynamic factors. The study used satellite observations of TOC and meteorological parameters (u,v components of wind and geopotential height) from the ERA5 reanalysis in the Northern Hemisphere. We describe the processes of air advection with significant TOC deviations and implement its classification into the main types. Seventy cases of spatial extremes were identified, 86% of which were observed under air advection with a western component. The intense westerly flow in the lower stratosphere is responsible for both the advection of air with high TOC (total ozone content) and its local formation. Under a well-developed polar vortex, most ozone extremes are transported by the main flow and reach the territory of Ukraine from the west and northwest, forming significant positive deviations. In this case, the polar vortex itself must be displaced into the Eastern Hemisphere for Ukraine to be closer to its outer boundary. When the integrity of the polar vortex is disrupted, it takes on a wavelike structure, leading to greater variability in the processes forming ozone extremes over Ukraine, including TOC advection from the north and local formation. With the breakdown of the polar vortex and the onset of a rapid TOC decrease in late March to April, the likelihood of positive ozone deviations from the north increases, though their recurrence does not exceed 7% of the total number of extremes. Significant negative TOC deviations spread over Ukraine during the period of seasonal minima under two conditions: advection from the northwest when the stratospheric polar vortex is absent (until November), and advection from the west in the early stages of vortex formation (in December). The established and described dynamic conditions for the formation of ozone layer extremes are important for extending the lead time in forecasting ozone anomalies over Ukraine.

Aspect sensitivity measurement of backscattering radar echoes from 205 MHz Stratosphere–Troposphere radar at a tropical coastal station

Aspect sensitivity in VHF radar refers to the extent to which the power and spectrum width of echoes vary with changes in the zenith angle, which is related to the backscattering process. The scattering of clear air signals is primarily caused by Fresnel reflection, anisotropic scattering, and isotropic scattering. The aspect sensitivity and accuracy of moment and wind estimation in clear air radars are influenced by the beam width, beam pointing angle from zenith, and atmospheric conditions. This study proposes a method to determine the sensitivity of the recently developed Stratosphere–Troposphere (ST) wind profile Radar in Cochin, India (10.04°N, 76.33°E). The radar operates at a distinct frequency of 205 MHz in the far VHF band. The experiment is conducted at an altitude of 5 to 20 km above the ground by adjusting the beam’s orientation with a resolution of 2°in both the east–west and north-south directions. The estimation of wind components is subject to uncertainty due to the varying aspect angles caused by the distinct dispersion properties in this height range. The study found that power variance is lowest between 6 and 12 km in both north-south and east–west directions, while daily fluctuations in aspect-sensitive echoes complicate wind component estimation. Correlation length (ζ) ranges from 0.5 to 15 m, indicating various air scattering processes. Notably, θs is smaller near the zenith and increases with tilt angles, exceeding 20°up to 14 km before declining at higher altitudes, indicating significant anisotropy at elevated levels. The wide range of R factor values (0.1 to 0.9) across different heights causes significant ambiguity in wind estimation. In this study, the impact of various aspect sensitivity parameters on wind estimation on days with clear air has been analyzed.

Experimental and computational study of aerodynamic loads on the NATO Generic Destroyer

This paper describes a detailed study into the aerodynamic loading of a 150 m long conceptual combat ship known as the NATO Generic Destroyer. Results are presented from a wind tunnel experiment in which the drag and side forces, and the roll and yaw moments, were measured around the 360° azimuth using a 0.75 m long model of the ship. Surface pressures were also measured between 0° and 180°, using 252 pressure taps distributed over the surface of the ship. The measured loads and surface pressures are shown to agree reasonably well, for most wind directions, with those predicted by a steady RANS CFD method. An unexpected result was found in the drag measurements, whereby the force was found to be towards the stern for wind directions up to 120°, i.e., with a wind component towards the bow. The reason for this apparent anomaly was explained by considering the flow field and the surface pressures acting on the ship for wind angles between 90° and 135°. The primary purpose of the paper is to make available a set of high-quality aerodynamic load measurements for a well-defined ship geometry, which is freely accessible, thereby providing a test case for CFD validation.

Chlorophyll-a and suspended matter variability in a data-scarce coastal-estuarine ecosystem

Analyzing the variability of chlorophyll-a (Chl-a) and total suspended matter (TSM) in estuarine and coastal environments is crucial for understanding ecosystem health, guiding environmental management decisions, and evaluating climate change impacts. Satellite remote sensing offers a powerful tool for this analysis due to its extensive spatial and temporal coverage. Although several algorithms exist for complex coastal and estuarine waters, long-term datasets such as GlobColor's Ocean Color (OC5) and neural network (NN) algorithms are frequently used for robust variability analysis. This study uses the GlobColor NN algorithm to investigate the seasonal and inter-annual variability of Chl-a and TSM in a data-scare region, namely the Meghna estuary in Bangladesh and its adjacent coastal fringe. The other algorithm (i.e. OC5), while offers the longest time series, cannot be used in this region due to the high number of invalid pixels. Therefore, this study examines different environmental factors (i.e. sea surface temperature (SST), photosynthetically active radiation (PAR), rainfall, zonal (ZWC) and meridional (MWC) wind components, and ocean currents) and climatic indices (i.e., El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD)) to understand their influence on the seasonal and inter-annual variability of Chl-a and TSM derived from the GlobColor NN algorithm. Empirical orthogonal function analysis identifies the seasonal signal as dominant in the study region. The seasonal cycle of Chl-a is influenced by factors including MWC, TSM, SST, and rainfall. In contrast, TSM seasonal variations are primarily driven by rainfall and MWC. Post-monsoon Chl-a inter-annual fluctuations are mainly linked to TSM inter-annual variability, with secondary influences from monsoon rainfall and the winter ENSO index. Inter-annual changes in TSM are primarily associated with the winter ENSO index and monsoon rainfall. This research elucidates the primary mechanisms influencing Chl-a and TSM variability in the Meghna estuary and its adjacent coast, thus advancing the understanding of the dynamics in the study region. The information obtained through this study is valuable for scientists, policymakers, and stakeholders involved in the sustainable management of the Meghna estuary and its coastal resources, particularly in the context of climate change.

Role of thermospheric winds on the generation of F-region irregularities over Indonesian sector during the solar minimum year 2020

Analysis of ionosonde observations over Chumpon (10.7°N, 99.4°E, 3.3° Mag. Lat.) and Kototabang (0.2° S, 100.3° E, 10° S Mag. Lat.) during the low solar activity year 2020 reveals that the occurrence of post-sunset spread-F maximises during winter (November-February), whereas that of post-midnight spread-F maximises during summer (May-August). The thermospheric winds observed by the Michelson Interferometer for Global High-Resolution Thermospheric Imaging (MIGHTI) on board the Ionospheric Connection Explorer (ICON) satellite over the Indonesian longitudes (95°E-115°E) are investigated to determine their impact on the generation of spread-F. The thermospheric winds at equatorial and low latitudes (10°N) are strongly eastward (> 50 m/s) around post-sunset hours (∼19:00 LST) in winter and equinox. The strong eastward wind is present only around midnight hours (after 22:00 LST) in summer. However, the present study reveals that the zonal wind does not contribute to the generation of plasma bubbles. Besides, the ICON-MIGHTI meridional wind at low latitude (10°N) is observed to be equatorward throughout the day during summer. Compared to the post-sunset hours, the intensity of trans-equatorial wind is stronger on the windward side (60–70 m/s) than on the leeward side (10–20 m/s) during midnight hours. The component of the equatorward meridional wind along the magnetic field lines can lift the F-layer to higher heights leading to a net decrease in the field line-integrated Pedersen conductivity thereby increasing the growth rate of the Rayleigh Taylor instability that can result in the generation of post-midnight spread F.

Jets from the Upper Scorpius Variable Young Star System 2MASS J16075796-2040087 via KECK/HIRES Spectro-astrometry

2MASS J16075796-2040087 is an ∼5 Myr young star in Upper Sco with evidence for accretion bursts on a timescale of about 15 days and, uncommonly for its age, outflows traced by multicomponent forbidden emission lines (FELs). The accretion bursts may be triggered by a companion at ∼4.6 au. We analyze HIRES spectra optimised for spectro-astrometry to better understand the origin of the several FEL velocity components and determine whether a magnetohydrodynamic (MHD) disk wind is present. The FEL high-velocity component (HVC) traces an asymmetric, bipolar jet ∼700 au long. The jet’s position angle ∼ 277° is not perpendicular to the disk. The lower-velocity emission, classified previously as a disk wind low-velocity component, is found to have more in common with the HVC and overall it is not possible to identify an MHD disk wind component. The spectro-astrometric signal of the low-velocity emission resembles those of jets and its density and ionisation fraction fall into the range of HVCs. We suggest a scenario where the accretion bursts due to the close companion power the jets past the age where such activity ends around most stars. The low-velocity emission here could come from a slow jet launched near the close companion and this emission would be blended with emission from the MHD wind.

Assimilation of ground-based GNSS data using a local ensemble Kalman filter

Tropical cyclones become increasingly nonlinear and dynamically unstable in high-resolution models. The initial conditions are typically sub-optimal, leaving scope to improve the accuracy of forecasts with improved data assimilation. Simultaneously, the lack of real ground-based GNSS observations over the ocean poses significant challenges when evaluating the assimilation results in oceanic regions. In this study, an Observation System Simulation Experiment is carried out based on a tropical cyclone case. Assimilation experiments using the WRF-PDAF framework are conducted. Conventional and GNSS observation operators are implemented. A diverse array of synthetic observations, encompassing temperature (T), wind components (U and V), precipitable water (PW), and zenith total delay (ZTD), are assimilated utilizing the Local Error-Subspace Transform Kalman filter (LESTKF). The findings highlight the improvement in forecast accuracy achieved through the assimilation process over the ocean. Multiple observation types further improve the forecast accuracy. The study underscores the crucial role of GNSS data assimilation techniques. The assimilation of GNSS data presents potential for advancing weather forecasting capabilities. Thus, the construction of ground-based GNSS observation stations over the ocean is promising.