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At least 307 records · Page 17

Solar Spicules: A Review of Recent Models and Targets for Future Observations

Since their discovery over 100 years ago, there have been many suggestions for the origin and development of solar spicules. Because the velocities of spicules are comparable to the sound and Alfven speeds of the low chromosphere, linear theory cannot fully describe them. Consequently, detailed tests of theoretical ideas had to await the development of computing power that only became available during the 1970s. This work reviews theories for spicules and spicule-like features over approximately the past 25 years, with an emphasis an the models based on nonlinear numerical simulations. These models have given us physical insight into wave propagation in the solar atmosphere and have helped elucidate how such waves, and associated shock waves, may be capable of creating motions and structures on magnetic flux tubes in the lower solar atmosphere. So far, however, it has been difficult to reproduce the most commonly quoted parameters for spicules with these models, using what appears to be the most suitable input parameters. A key impediment to developing satisfactory models has been the lack of reliable observational information, which is a consequence of the small angular size and transient lifetime of spicules. I close with a list of key observational questions to be addressed with space-based satellites, such as the currently operating Transition Region and Coronal Explorer (TRACE) satellite, and especially the upcoming Solar-B mission. Answers to these questions will help determine which, if any, of the current models correctly explains spicules.

Sterling, Alphonse C.↗

Machine-learning identification of the variability of mean velocity and turbulence intensity for wakes generated by onshore wind turbines: Cluster analysis of wind LiDAR measurements

Light detection and ranging (LiDAR) measurements of isolated wakes generated by wind turbines installed at an onshore wind farm are leveraged to characterize the variability of the wake mean velocity and turbulence intensity during typical operations, which encompass a breadth of atmospheric stability regimes and rotor thrust coefficients. The LiDAR measurements are clustered through the k-means algorithm, which enables identifying the most representative realizations of wind turbine wakes while avoiding the imposition of thresholds for the various wind and turbine parameters. Considering the large number of LiDAR samples collected to probe the wake velocity field, the dimensionality of the experimental dataset is reduced by projecting the LiDAR data on an intelligently truncated basis obtained with the proper orthogonal decomposition (POD). The coefficients of only five physics-informed POD modes are then injected in the k-means algorithm for clustering the LiDAR dataset. The analysis of the clustered LiDAR data and the associated supervisory control and data acquisition and meteorological data enables the study of the variability of the wake velocity deficit, wake extent, and wake-added turbulence intensity for different thrust coefficients of the turbine rotor and regimes of atmospheric stability. Furthermore, the cluster analysis of the LiDAR data allows for the identification of systematic off-design operations with a certain yaw misalignment of the turbine rotor with the mean wind direction.

17 WIND ENERGY↗

Synthetic properties of starburst galaxies

We present the results of an extensive grid of evolutionary synthesis models for populations of massive stars. The parameter space has been chosen to correspond to conditions typically found in objects like giant H II regions, H II galaxies, blue compact dwarf galaxies, nuclear starbursts, and infrared luminous starburst galaxies. The models are based on the most up-to-date input physics for the theory of stellar atmospheres, stellar winds, and stellar evolution. A population of massive stars is not only important in terms of its output of radiation but also via its deposition of mechanical energy. The output of radiative and mechanical luminosity is compared at various starburst epochs. In a supernova dominated instantaneous starburst, the mechanical luminosity can be as large as almost 10% of the total radiative luminosity. This occurs when most massive O stars have disappeared, and the synthetic spectrum in the optical and near-ultraviolet is dominated by B and A stars. During this epoch, the output of ionizing radiation below 912 A becomes very small, as indicated by a very large Lyman discontinuity and a very small ratio of ionizing over mechanical luminosity. We discuss the relevance of these results for the interpretation of starburst galaxies, active galactic nuclei, and the energetics of the interstellar medium.

Leitherer, Claus↗

Achieving Realistic Runoff in the Western United States with a Land Surface Model Forced by Dynamically Downscaled Meteorology

Abstract In this study, we calibrate a regional climate model’s (RCM) underlying land surface model (LSM). In addition to providing a realistic representation of runoff across the hydroclimatically diverse western United States, this is done to take advantage of the RCM’s ability to physically resolve meteorological forcing data in ungauged regions, and to prepare the calibrated hydrologic model for tight coupling, or the ability to represent land surface–atmosphere interactions, with the RCM. Specifically, we use a 9-km resolution meteorological forcing dataset across the western United States, from the fifth generation ECMWF Reanalysis (ERA5) downscaled by the Weather Research Forecasting (WRF) regional climate model, as an offline forcing for Noah-Multiparameterization (Noah-MP). We detail the steps involved in producing an LSM capable of accurately representing runoff, including physical parameterization selection, parameter calibration, and regionalization to ungauged basins. Based on our model evaluation from 1954 to 2021 for 586 basins with daily natural streamflow, the streamflow bias is reduced from 24.2% to 4.4%, and the median daily Nash–Sutcliffe efficiency (NSE) is improved from 0.12 to 0.36. When validating against basins with monthly natural streamflow data, we obtain a similar reduction in bias and a median monthly NSE improvement from 0.18 to 0.56. In this study, we also discover the optimal setup when using a donor-basin method to regionalize parameters to ungauged basins, which can vary by 0.06 NSE for unique designs of this regionalization method. Significance Statement This study provides useful guidance for improving a land surface model to accurately represent runoff across a spatially extensive and hydroclimatically diverse region (the western United States). The land surface model is updated to represent runoff more accurately at gauged basins, and then additionally updated for basins without observational data using a mathematical approach called the donor-basin method. We make use of a regional climate model’s reanalysis-derived meteorological data and its underlying land surface model to achieve realistic runoff. The calibrated land surface model can thus be tightly coupled in subsequent studies in a manner that should more accurately reflect runoff conditions. Findings from this study will serve as a useful reference for the atmospheric (and hydrologic) modeling communities and their ability to represent large-scale hydrology accurately.

Meteorology & Atmospheric Sciences↗

Trajectory reconstruction and aerodynamic results from the first Discovery flight, STS-14(41-D)

Trajectory reconstruction results for the first Discovery flight are presented. Spacecraft dynamic measurements from IMU2 were utilized in conjunction with the ground based tracking data from two S-band stations, eight C-band, and five cameras at Edwards Air Force Base to determine the spacecraft trajectory from epoch through roll-out on Runway 17. Specifics as to the trajectory reconstruction are discussed in Section 1. The final inertial profile is BT14NO2/UN=169750N. Merging of this file with the final LAIRS atmosphere is discussed in Section 2. The final Extended BET is ST14BET/UN=274885C. Section 3 presents plots of relevant parameters from the AEROBET as well as aerodynamic performance comparison results. High frequency files for maneuver extraction were also generated as discussed in Section 4. Appendices are attached which contain: (1) spacecraft and physical parameters utilized, (2) final residuals obtained from the data fitting process, (3) listing of trajectory parameters, and (4) archival information.

Kelly, G. M.↗

Light scattering by randomly oriented crystals

The scattering phase function and the degree of linear polarization for small crystals oriented randomly in space have been computed using the geometric ray tracing theory and assuming that the crystals are homogeneous and isotropic. Calculations have been carried out for the main crystal geometries. Detection of halos from crystals other than hexagonal water ice is briefly discussed. The crystal size and shape parameters have also been averaged over some simple distributions in order to examine general light scattering properties of sharp-edged particles. A scalar physical optics correction has been developed for the geometric optics phase functions. Results can be applied to light scattering from regoliths and planetary rings, and possibly also to atmospheric halos. Retroreflecting crystals in the regolith would cause an opposition spike, a phenomenon observed for many bright satellites.

Muinonen, Karri↗

Incoherent scatter radar observations of the ionosphere

Incoherent scatter radar (ISR) has become the most powerful means of studying the ionosphere from the ground. Many of the ideas and methods underlying the troposphere and stratosphere (ST) radars have been taken over from ISR. Whereas the theory of refractive index fluctuations in the lower atmosphere, depending as it does on turbulence, is poorly understood, the theory of the refractivity fluctuations in the ionosphere, which depend on thermal fluctuations, is known in great detail. The underlying theory is one of the most successful theories in plasma physics, and allows for many detailed investigations of a number of parameters such as electron density, electron temperature, ion temperature, electron mean velocity, and ion mean velocity as well as parameters pertaining to composition, neutral density and others. Here, the author reviews the fundamental processes involved in the scattering from a plasma undergoing thermal or near thermal fluctuations in density. The fundamental scattering properties of the plasma to the physical parameters characterizing them from first principles. He does not discuss the observation process itself, as the observational principles are quite similar whether they are applied to a neutral gas or a fluctuating plasma.

Hagfors, Tor↗

The Earth and Ocean Physics Applications Program (EOPAP). Ocean dynamics program

SEASAT-A is a research oriented program consisting of a spacecraft, precision ground tracking systems, and data processing and modelling capabilities that address both scientific and application programs problems in ocean surface dynamics for the EOPAP program. An array of active radar and passive microwave and infrared instruments allows for quantitative measurements of oceanic, atmospheric, and geodetic parameters under stormy wind and wave conditions, as well as over regions lying under a cloud cover.

Apel, J. R.↗

Data-driven wind turbine wake modeling via probabilistic machine learning

Wind farm design primarily depends on the variability of the wind turbine wake flows to the atmospheric wind conditions and the interaction between wakes. Physics-based models that capture the wake flow field with high-fidelity are computationally very expensive to perform layout optimization of wind farms, and, thus, data-driven reduced-order models can represent an efficient alternative for simulating wind farms. In this work, we use real-world light detection and ranging (LiDAR) measurements of wind-turbine wakes to construct predictive surrogate models using machine learning. Specifically, we first demonstrate the use of deep autoencoders to find a low-dimensional latent space that gives a computationally tractable approximation of the wake LiDAR measurements. Then, we learn the mapping between the parameter space and the (latent space) wake flow fields using a deep neural network. Additionally, we also demonstrate the use of a probabilistic machine learning technique, namely, Gaussian process modeling, to learn the parameter-space-latent-space mapping in addition to the epistemic and aleatoric uncertainty in the data. Finally, to cope with training large datasets, we demonstrate the use of variational Gaussian process models that provide a tractable alternative to the conventional Gaussian process models for large datasets. Furthermore, we introduce the use of active learning to adaptively build and improve a conventional Gaussian process model predictive capability. Overall, we find that our approach provides accurate approximations of the wind-turbine wake flow field that can be queried at an orders-of-magnitude cheaper cost than those generated with high-fidelity physics-based simulations.

Deep neural networks↗

Predictability of time averages. I - Dynamical predictability of monthly means. II - The influence of the boundary forcings

The physical basis for the dynamic prediction of monthly means in weather parameters is examined in two papers. In the first paper, an attempt is made to determine the theoretical upper limit of dynamical predictability of monthly means for prescribed nonfluctuating external forcings. In the second paper, the physical mechanisms through which changes in the boundary forcings of SST, soil moisture, albedo, and snow influence atmospheric circulation are discussed. On the basis of both studies, the essential requirements for establishing the physical basis for dynamical prediction of monthly means are to show that: (1) fluctuations of monthly means are larger than can be expected due to sampling of day-to-day weather changes; (2) there are low frequency planetary scale components of circulation which remain predictable beyond the limits of synoptic scale predictability; and (3) the influences of the slowly varying boundary conditions of SST, soil moisture, snow, sea ice are large enough to produce significant and detectable changes in the monthly mean circulations. Observational and numerical evidence which support these requirements are presented.

Shukla, J.↗

The Joint Aerosol-Monsoon Experiment: A New Challenge to Monsoon Climate Research

Aerosol and monsoon related droughts and floods are two of the most serious environmental hazards confronting more than 60% of the population of the world living in the Asian monsoon countries. In recent years, thanks to improved satellite and in-situ observations, and better models, great strides have been made in aerosol, and monsoon research respectively. There is now a growing body of evidence suggesting that interaction of aerosol forcing with water cycle dynamics in monsoon regions may substantially alter the redistribution of energy at the earth surface and in the atmosphere, and therefore significantly impact monsoon rainfall variability and long term trends. In this talk, I will describe issues related to societal needs, scientific background, and challenges in studies of aerosol-water cycle interaction in Asian monsoon regions. As a first step towards addressing these issues, the authors call for an integrated observation and modeling research approach aimed at the interactions between aerosol chemistry and radiative effects and monsoon dynamics of the coupled ocean-atmosphere-land system. A Joint Aerosol-Monsoon Experiment (JAMEX) is proposed for 2007-2011, with an enhanced observation period during 2008-09, encompassing diverse arrays of observations from surface, aircraft, unmanned aerial vehicles, and satellites of physical and chemical properties of aerosols, long range aerosol transport as well as meteorological and oceanographic parameters in the Indo-Pacific Asian monsoon region. JAMEX will leverage on coordination among many ongoing and planned national programs on aerosols and monsoon research in China, India, Japan, Nepal, Italy, US, as well as international research programs of the World Climate Research Program (WCRP) and the World Meteorological Organization (WMO).

Lau, William K. M.↗

From Multi-Sensors Observations Towards Cross-Disciplinary Study of Pre-Earthquake Signals. What have We Learned from the Tohoku Earthquake?

The lessons we have learned from the Great Tohoku EQ (Japan, 2011) how this knowledge will affect our future observation and analysis is the main focus of this presentation.We present multi-sensors observations and multidisciplinary research in our investigation of phenomena preceding major earthquakes. These observations revealed the existence of atmospheric and ionospheric phenomena occurring prior to theM9.0 Tohoku earthquake of March 11, 2011, which indicates s new evidence of a distinct coupling between the lithosphere and atmosphere/ionosphere, as related to underlying tectonic activity. Similar results have been reported before the catastrophic events in Chile (M8.8, 2010), Italy (M6.3, 2009) and Sumatra (M9.3, 2004). For the Tohoku earthquake, our analysis shows a synergy between several independent observations characterizing the state of the lithosphere /atmosphere coupling several days before the onset of the earthquakes, namely: (i) Foreshock sequence change (rate, space and time); (ii) Outgoing Long wave Radiation (OLR) measured at the top of the atmosphere; and (iii) Anomalous variations of ionospheric parameters revealed by multi-sensors observations. We are presenting a cross-disciplinary analysis of the observed pre-earthquake anomalies and will discuss current research in the detection of these signals in Japan. We expect that our analysis will shed light on the underlying physics of pre-earthquake signals associated with some of the largest earthquake events

Ouzounov, D.↗

Precision Neutrino Oscillation Physics with the Daya Bay and DUNE Experiments

The team supported by this grant made significant contributions to the final results of the Daya Bay Reactor Antineutrino Experiment. This experiment utilized eight identically designed antineutrino detectors positioned at varying distances from six 2.9 GW th nuclear reactors to precisely measure the oscillation parameters that govern antineutrino disappearance at short (<2 km) baselines. Our group played a leading role in the calibration and data quality efforts, both of which have been crucial for all final results. Additionally, we co-led the development of an independent measurement of the neutrino mixing angle θ 13 and the atmospheric mass splitting using a sample of antineutrinos identified via neutron capture on hydrogen. Lastly, we laid the groundwork for a search for seasonal modulation in Daya Bay’s measured muon flux using the final dataset, a result expected to be published soon. Simultaneously, our team ramped up its participation in the Deep Underground Neutrino Experiment (DUNE). This experiment will employ a powerful neutrino beam from Fermilab in Illinois directed to the Homestake mine in South Dakota to address some of the most pressing questions in neutrino physics, including the ordering of neutrino masses and whether neutrinos violate the CP symmetry. Our work focused on the development of the pixelated and modularized Liquid Argon Time-Projection Chamber technology that is being prepared for DUNE’s Near Detector. Our group took responsibility for the development, testing, and maintenance of the firmware for the control boards of the detector’s charge readout system and played an active role in analyzing data produced by the very first fully integrated prototypes.

2x2 Demonstrator↗

Semi-automated Design of Artificial Intelligence Earth Systems Models

Prediction and observation of water cycles at various scales involve not only patterns isolated in space and time, but also modeling of complex spatio-temporal relationships across multiple domains. For instance, evapotranspiration (ET) and leaf area indexes (LAI) are two parameters that are needed to accurately model and understand land-atmosphere processes. Accurate assessments of ET and LAI are critical for understanding hydrological processes, deforestation, crop yield, and irrigation impacts. However, ET estimates for global simulations are available at very coarse spatial resolution. They are usually derived from satellite data based on broad plant functional types (PFTs), which fail to capture fine-scale variations because of changes in vegetation type across the globe. Similarly LAI estimates have typically been derived from vegetation indices at global scales or estimated locally using physical models, both of which suffer from a range of uncertainties that impact model sensitivity. The new era of AI model development for Earth systems (ES) calls for data-driven methods that provide domain scientists with uncertainty-aware estimations of biophysical parameters such as ET and LAI in a generalizable, interpretable, and discoverable manner.

54 ENVIRONMENTAL SCIENCES↗

Mechanical and chemical properties of PVD and cold spray Cr-coatings on Zircaloy-4

In this paper, accident-tolerant fuel (ATF) cladding materials aim to improve fuel reliability and safety during accident scenarios in water-cooled reactors. These ATF cladding should also perform comparable or better than the current zirconium alloy cladding under reactor normal operating conditions. Surface-modified Zircaloy-4 was produced by depositing a protective coating of chromium by two different coating techniques, Physical Vapor Deposition (PVD) and Cold Spray (CS). The coating thickness, structure, composition, and mechanical properties of the coated Zircaloy were assessed with advanced materials characterization techniques. Results showed a strengthening effect of the Cr-coating, along with ~83% higher hardness compared to that of the Zircaloy-4 substrate. Surface topography and surface chemistry of the Cr-coated Zircaloy-4 were assessed with contact profilometry, atomic force microscopy, contact angle goniometry, and X-ray photoelectron spectroscopy. Deposited Cr-coating significantly improved surface wettability compared to the substrate Zircaloy-4. The formation of surface oxides on the coatings by prolonged exposure to ambient air showed a further increase in the hydrophobic behavior. Surface parameters and surface chemistry after flow boiling critical heat flux tests, conducted at atmospheric pressure, evidenced a slight increase in surface roughness with notable changes in wettability associated with the formation of surface oxides.

36 MATERIALS SCIENCE↗

A regression technique for evaluation and quantification for water quality parameters from remote sensing data

The paper attempts to define optical physics and/or environmental conditions under which the linear multiple-regression should be applicable. It is reported that investigation of the signal response shows that the exact solution for a number of optical physics conditions is of the same form as a linearized multiple-regression equation, even if nonlinear contributions from surface reflections, atmospheric constituents, or other water pollutants are included. Limitations on achieving this type of solution are defined. Laboratory data are used to demonstrate that the technique is applicable to water mixtures which contain constituents with both linear and nonlinear radiance gradients. Finally, it is concluded that instrument noise, ground-truth placement, and time lapse between remote sensor overpass and water sample operations are serious barriers to successful use of the technique.

Whitlock, C. H.↗

Lidar Remote Sensing

The laser radar, or lidar (for light detection and ranging) is an important tool for atmospheric studies. Lidar provides a unique and powerful method for unobtrusively profiling aerosols, wind, water vapor, temperature, and other atmospheric parameters. This brief overview of lidar remote sensing is focused on atmospheric applications involving pulsed lasers. The level of technical detail is aimed at the educated non-lidar expert and references are provided for further investigation of specific topics. The article is divided into three main sections. The first describes atmospheric scattering processes and the physics behind laser-atmosphere interactions. The second section highlights some of the primary lidar applications, with brief descriptions of each measurement capability. The third section describes the practical aspects of lidar operation, including the governing equation and operational considerations.

McGill, Matthew J.↗

Post-conjunction detection of β Pictoris b with VLT/SPHERE

Context. With an orbital distance comparable to that of Saturn in the solar system, β Pictoris b is the closest (semi-major axis ≃9 au) exoplanet that has been imaged to orbit a star. Thus it offers unique opportunities for detailed studies of its orbital, physical, and atmospheric properties, and of disk-planet interactions. With the exception of the discovery observations in 2003 with NaCo at the Very Large Telescope (VLT), all following astrometric measurements relative to β Pictoris have been obtained in the southwestern part of the orbit, which severely limits the determination of the planet’s orbital parameters. Aims. We aimed at further constraining β Pictoris b orbital properties using more data, and, in particular, data taken in the northeastern part of the orbit. Methods. We used SPHERE at the VLT to precisely monitor the orbital motion of beta β Pictoris b since first light of the instrument in 2014. Results. We were able to monitor the planet until November 2016, when its angular separation became too small (125 mas, i.e., 1.6 au) and prevented further detection. We redetected β Pictoris b on the northeast side of the disk at a separation of 139 mas and a PA of 30° in September 2018. The planetary orbit is now well constrained. With a semi-major axis (sma) of a = 9.0 ± 0.5 au (1σ), it definitely excludes previously reported possible long orbital periods, and excludes β Pictoris b as the origin of photometric variations that took place in 1981. We also refine the eccentricity and inclination of the planet. From an instrumental point of view, these data demonstrate that it is possible to detect, if they exist, young massive Jupiters that orbit at less than 2 au from a star that is 20 pc away.

A.-M. Lagrange↗