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Multigrid properties of upwind-biased data reconstructions

The multigrid properties of two data reconstruction methods used for achieving second-order spatial accuracy when solving the two-dimensional Euler equations are examined. The data reconstruction methods are used with an implicit upwind algorithm which uses linearized backward-Euler time-differencing. The solution of the resulting linear system is performed by an iterative procedure. In the present study only regular quadrilateral grids are considered, so a red-black Gauss-Seidel iteration is used. Although the Jacobian is approximated by first-order upwind extrapolation, two alternative data reconstruction techniques for the flux integral that yield higher-order spatial accuracy at steady state are examined. The first method, probably most popular for structured quadrilateral grids, is based on estimating the cell gradients using one-dimensional reconstruction along curvilinear coordinates. The second method is based on Green's theorem. Analysis and numerical results for the two dimensional Euler equations show that data reconstruction based on Green's theorem has superior multigrid properties as compared to the one-dimensional data reconstruction method.

Warren, Gary P.↗

Advanced Observation Operators for GPS Radio Occultation: Validation of the 2D Ray Tracing Approach with CHAMP and SAC-C bending angle and refractivity data - Part 1

Global Positioning System (GPS) Radio Occultations (RO) bending angles and refractivity data characterize mostly the vertical structure of the Earth's atmosphere. We answer the question whether proper simulation of GPS RO data for data assimilation can be obtained with one-dimensional vertical operators, or if accounting also for horizontal atmospheric structures via ray-tracing makes a positive difference when compared with real data. We present a detailed implementation of a geometrical optics multi-plane two-dimensional (2D) ray-tracing as an observation operator to simulate GPS RO bending angles and refractivities within the Finite Volume Data Assimilation System (FVDAS). Comparisons of the outputs of that 2D observation operator with those of simpler ID observation operators are used to generate estimates of errors induced by neglecting tangent point drift (TPD) and horizontal gradients (HG). These error estimates are then confronted with errors estimates derived using 6335 real CHAMP and SAC-C occultations. The agreement for TPD-induced (HG-induced) errors is remarkably positive at altitudes 10-30 km (below 10 km). Comparisons in bending angles O - B STD of the outputs of the multi-plane 2D ray-tracer with those of a vertical Abel transform show reductions of about 8% of the usual O - B bending angle STD due to TPD in the stratosphere (3% due to HG, in the troposphere only). In terms of refractivity, the O - B STD reductions are about 1520% for TPD and 3-5% for HG in the same regions. These reductions are obtained using either 6-hour forecasts or analyses as backgrounds, and using Geometrical Optics (GO) or Canonical Transform (CT) data.

Poli, P.↗

Kurtosis Approach Nonlinear Blind Source Separation

In this paper, we introduce a new algorithm for blind source signal separation for post-nonlinear mixtures. The mixtures are assumed to be linearly mixed from unknown sources first and then distorted by memoryless nonlinear functions. The nonlinear functions are assumed to be smooth and can be approximated by polynomials. Both the coefficients of the unknown mixing matrix and the coefficients of the approximated polynomials are estimated by the gradient descent method conditional on the higher order statistical requirements. The results of simulation experiments presented in this paper demonstrate the validity and usefulness of our approach for nonlinear blind source signal separation Keywords: Independent Component Analysis, Kurtosis, Higher order statistics.

Duong, Vu A.↗

Kurtosis Approach for Nonlinear Blind Source Separation

In this paper, we introduce a new algorithm for blind source signal separation for post-nonlinear mixtures. The mixtures are assumed to be linearly mixed from unknown sources first and then distorted by memoryless nonlinear functions. The nonlinear functions are assumed to be smooth and can be approximated by polynomials. Both the coefficients of the unknown mixing matrix and the coefficients of the approximated polynomials are estimated by the gradient descent method conditional on the higher order statistical requirements. The results of simulation experiments presented in this paper demonstrate the validity and usefulness of our approach for nonlinear blind source signal separation.

kurtosis↗

Influence of Exercise Modality on Cerebral-Ocular Hemodynamics and Pressures

Background: Moderate and high intensity aerobic or resistance exercise has clearly identified benefits for cardiac, muscle, and bone health. However, the impact of such exercise - either as a mitigating or an exacerbating factor - on the development of the visual impairment and intracranial pressure syndrome (VIIP) is unknown. Accordingly, our aim was to characterize the effect of an acute bout of resistance (RE), moderate-intensity continuous (CE), and high-intensity interval exercise (IE) during a cephalad fluid shift on cerebral-ocular hemodynamics and pressures. Methods: 10 male subjects (36 plus or minus 9 years) completed 4 testing days in a 15 degree head-down tilt (HDT): (1) assessment of maximum volume of O (sub 2), (2) RE session (4 sets of 12 repetition maximum leg press exercise), (3) CE session (30 minutes of cycling at 60 percent maximum volume of O (sub 2)), and (4) IE session (4 by 4-minute intervals of exercise at 85 percent maximum volume of O (sub 2) with 3-minute active rest periods). During each session, blood flow (Vivid-e, GE Healthcare) in extracranial arteries (common carotid artery, CCA; internal carotid artery, ICA; external carotid artery, ECA and vertebral artery, VA), and mean blood flow velocity in middle cerebral artery (MCA), internal jugular pressure (IJP; VeinPress), and intraocular pressure (IOP; Icare PRO) were measured at rest, at the end of each resistance or interval set, and every 5 minutes during continuous exercise. Translaminar pressure gradient (TLPG) was estimated by subtracting IJP from IOP. Results: There were no differences across days in pre-exercise resting blood flows or pressures. IOP decreased slightly from HDT rest (20.2 plus or minus 2.3 millimeters of mercury) to exercise (RE: 19.2 plus or minus 2.8 millimeters of mercury; CE: 18.9 plus or minus 3.2 millimeters of mercury; IE: 20.1 plus or minus 2.8 millimeters of mercury), while IJP decreased during CE (31.6 plus or minus 9.5 millimeters of mercury) and RE (32.0 plus or minus 8.1 millimeters of mercury), and increased during IE (35.1 plus or minus 9.5 millimeters of mercury) from HDT rest (33.3 plus or minus 6.5 millimeters of mercury). Estimated TLPG was increased during IE only. Compared to RE and CE, IE resulted in the greatest increase in MCA blood flow velocity and extracranial artery blood flow. Conclusions: These preliminary results suggest that high-intensity IE acutely increases cerebral blood flow, IJP, and TLPG. Alterations in TLPG is one mechanism that may contribute to optic nerve sheath edema in astronauts. Accordingly, acutely raising IOP and/or orbital pressure during exercise could optimize cerebral-ocular pressures during spaceflight.

Scott, J.↗

Scientific and Technical Assistance for the Deployment of a Flexible Airborne Spectrometer System During C-MAPExp and COMEX: COMEX Version - 1.9T

The COMEX (CO2 and MEthane eXperiment) campaign supports the mission definition of CarbonSat and HyspIRI (Hyperspectral Infrared Imager) by providing representative airborne remote sensing data ‐ MAMAP (Methane Airborne MAPper) for CarbonSat; the Airborne Visual InfraRed Imaging Spectrometer (Classic & Next Generation) AVIRIS‐C/AVIRIS‐NG for HyspIRI ‐ as well as ground-based and airborne in‐situ data. The objectives of the COMEX campaign activities are (see Campaign Implementation Plan (RD‐4)): 1. Investigate spatial/spectral resolution trade‐offs for CH4 anomaly detection and flux inversion by comparison of MAMAP‐derived emission estimates with AVIRIS/AVIRIS‐NG derived data. 2. Evaluate sun‐glint observation geometry on CH4 retrievals for marine sources. 3. Characterize the effect of Surface Spectral Reflectance (SSR) heterogeneity on trace gas retrievals of CO2 and CH4 for medium and low‐resolution spectrometry. 4. Identify benefits from joint SWIR/TIR (ShortWave InfraRed/Thermal InfraRed ) data for trace gas detection and retrieval by comparison of MAMAP and AVIRIS/AVIRIS‐NG NIR/SWIR data with MAKO (Aerospace Corp.)TIR data. The ability to derive emission source strength for a range of strong emitting targets by remote sensing will be evaluated from combined AVIRIS‐NG and MAMAP data, adding significant value to the HyspIRI campaign AVIRIS‐NG dataset. The data will be used to quantify anomalies in atmospheric CO2 and CH4 from strong local greenhouse gas sources e.g. localized industrial complexes, landfills, etc. and to derive CO2 and CH4 emissions estimates from atmospheric gradient measurements. The original campaign concept was developed by University of Bremen and BRI. The COMEX campaign is funded bilaterally by NASA and ESA (European Space Agency). Whereas NASA funds the US part of the project via a contract with Dr. Ira Leifer, BRI (Bubbleology Research International), the contribution of MAMAP to the COMEX campaign is funded by ESA within the COMEX‐E project and NASA with respect to a 50 percent contribution to the flight-related costs of flying MAMAP on a US aircraft. The Data Acquisition Report (RD‐9) describes the instrumentation used, the measurements made by the team during the COMEX campaign in May/June 2014 and August/September 2014 in California, and an initial assessment of the data quality.

Point Sources↗

GIGA-Lens: Fast Bayesian Inference for Strong Gravitational Lens Modeling

We present GIGA-Lens: a gradient-informed, GPU-accelerated Bayesian framework for modeling strong gravitational lensing systems, implemented in TensorFlow and JAX. The three components, optimization using multistart gradient descent, posterior covariance estimation with variational inference, and sampling via Hamiltonian Monte Carlo, all take advantage of gradient information through automatic differentiation and massive parallelization on graphics processing units (GPUs). We test our pipeline on a large set of simulated systems and demonstrate in detail its high level of performance. The average time to model a single system on four Nvidia A100 GPUs is 105 s. The robustness, speed, and scalability offered by this framework make it possible to model the large number of strong lenses found in current surveys and present a very promising prospect for the modeling of ${ \mathcal O }({10}^{5})$ lensing systems expected to be discovered in the era of the Vera C. Rubin Observatory, Euclid, and the Nancy Grace Roman Space Telescope.

79 ASTRONOMY AND ASTROPHYSICS↗

Motion-Contrast Sensitivity: Visibility of Motion Gradients of Various Spatial Frequencies

The purpose of our experiments was to estimate basic sensitivity to motion gradients and to evaluate the evidence for second-order integration and differentiation of motion signals. We measured sensitivity to spatially sinusoidal contrast modulation between two oppositely moving bandpass-filtered noise images. The motion-contrast sensitivity function, defined as the inverse of threshold modulation amplitude as a function of modulation spatial frequency, was bandpass in shape with declines at both highest and lowest frequencies. The functions for three noise spatial frequencies had approximately the same shape when modulation frequency was expressed as a fraction of noise frequency. We compared the data with a model in which linear motion filters, whose outputs are squared or rectified, are followed by a second stage of excitatory or inhibitory pooling. The data are consistent with a model in which (1) all excitatory pooling occurs at the linear stage and (2) the second stage contains a large inhibitory pooling area, with a radius approximately eight times that of the linear receptive field.

Watson, Andrew B.↗

Simulation studies of wide and medium field of view earth radiation data analysis

A parameter estimation technique is presented to estimate the radiative flux distribution over the earth from radiometer measurements at satellite altitude. The technique analyzes measurements from a wide field of view (WFOV), horizon to horizon, nadir pointing sensor with a mathematical technique to derive the radiative flux estimates at the top of the atmosphere for resolution elements smaller than the sensor field of view. A computer simulation of the data analysis technique is presented for both earth-emitted and reflected radiation. Zonal resolutions are considered as well as the global integration of plane flux. An estimate of the equator-to-pole gradient is obtained from the zonal estimates. Sensitivity studies of the derived flux distribution to directional model errors are also presented. In addition to the WFOV results, medium field of view results are presented.

Green, R. N.↗

An Empirical Quantile Estimation Approach for Chance-Constrained Nonlinear Optimization Problems

We investigate an empirical quantile estimation approach to solve chance-constrained nonlinear optimization problems. Our approach is based on the reformulation of the chance constraint as an equivalent quantile constraint to provide stronger signals on the gradient. In this approach, the value of the quantile function is estimated empirically from samples drawn from the random parameters, and the gradient of the quantile function is estimated via a finite-difference approximation on top of the quantile-function-value estimation. We establish a convergence theory of this approach within the framework of an augmented Lagrangian method for solving general nonlinear constrained optimization problems. The foundation of the convergence analysis is a concentration property of the empirical quantile process, and the analysis is divided based on whether or not the quantile function is differentiable. In contrast to the sampling-and-smoothing approach used in the literature, the method developed in this paper does not involve any smoothing function and hence the quantile-function gradient approximation is easier to implement and there are less accuracy-control parameters to tune. Furthermore, we demonstrate the effectiveness of this approach and compare it with a smoothing method for the quantile-gradient estimation. Numerical investigation shows that the two approaches are competitive for certain problem instances.

Applied Probability↗

Remote Radiation Sensing Using Aerial and Ground Platforms

Remote sensing of ionizing radiation has a significant role in waste management, nuclear material management and nonproliferation, and radiation safety. Robotic platforms can surpass the number of tasks that are achieved by humans. With this technique, the operator's radiation exposure can be decreased. Remote sensing allows for the evaluation and monitoring of radiological contamination. Gamma-ray and neutron sensors were integrated onto the robotic platforms. This approach allows for the radiation sensor data to be dynamically tracked and mapped thus enabling further analysis of the radiation flux in temporal and spatial domains. The goal is to complete scheduled tasks while the robot is being irradiated. To achieve this, electronic components must be shielded and radiation hardened. CZT Detector: Cadmium Zinc Telluride (CZT) detector technology has been a promising solution for gamma-ray and x-ray measurements. Detector data is transferred to the Odroid minicomputer that controls and powers the module via the USB. Robot Operating System (ROS) was utilized for data acquisition and data fusion. The Mariscotti method was employed for the spectrum analysis. A function was programmed in ROS for the automatic identification of photopeaks. CLYC Detector: A Cs{sub 2}LiYCl{sub 6}:Ce{sup 3+} (CLYC) detector was used for simultaneous medium-resolution gamma-ray measurements and neutron counting. A 2.54 cm diameter photomultiplier tube (PMT) was equipped with a high voltage supply and a miniature digitizer. Gamma-ray excitation: fast core-to-valence luminescence (CVL) with 1 ns decay constant, and prompt Ce{sup 3+} emission with 50 ns decay constant. Neutron excitation: slow cerium self-trapped excitation (Ce{sup 3+} STE), 1000 ns decay constant. Radiation Source Localization: Maximum Likelihood Estimation (MLE) and gradient-based methods were used to locate the position of a radiation source based on measured radiation intensities. Multi-Particle Transport Code FLUKA: Estimation of radiation damage of the electronic components is important in order to optimize the robot's operational time while it is irradiated. Displacement per atom (DPA) represents the radiation damage in materials exposed to the ionizing radiation. Various shielding layers of different thickness t were analyzed (< 5% statistical error). The model of the controller of the UAS was designed in FLUKA. Conclusion: CZT and CLYC detectors were integrated onto the robotic platforms. Radiation source localization and contour mapping using robotic platforms were studied. Functions for data analysis and fusion were developed in ROS. FLUKA code was utilized to analyze DPA values. Layers of low-density and high-density materials were used to shield the UAS electronics.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Error-mitigated data-driven circuit learning on noisy quantum hardware

Application-level benchmarks measure how well a quantum device performs meaningful calculations. In the case of parameterized circuit training, the computational task is the preparation of a target quantum state via optimization over a loss landscape. This is complicated by various sources of noise, fixed hardware connectivity, and generative modeling, the choice of target distribution. Gradient-based training has become a useful benchmarking task for noisy intermediate-scale quantum computers because of the additional requirement that the optimization step uses the quantum device to estimate the loss function gradient. In this work, we use gradient-based data-driven circuit learning to qualitatively evaluate the performance of several superconducting platform devices and present results that show how error mitigation can improve the training of quantum circuit Born machines with 28 tunable parameters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Exploiting the Temperature Dependence of Magnetic Susceptibility to Control Convection in Fundamental Studies of Solidification Phenomena

It is well known that convection is a dominant mass transport mechanism when materials are solidified on Earth's surface. This convection is caused by gradients in density (and therefore gravitational force) that are brought about by gradients in temperature, composition or both. Diffusion of solute is therefore dwarfed by convection and the study of fundamental parameters, such as dendrite tip shape and growth velocity in the absence of convection is nearly impossible. Significant experimental work has therefore been carried out in orbiting laboratories with the intent of minimizing convection by minimizing gravity. One of the best known experiments of this kind is the Isothermal Dendritic Growth Experiment (IDGE), supported by NASA. Naturally such experiments are costly and one objective of the present investigation is to develop an experimental method whereby convection can be- halted, in solidification and other experiments, on the surface. A second objective is to use the method to minimize convection resulting from the residual accelerations suffered by experiments in microgravity. The method to be used to minimize convection relies on the dependence of the magnetic susceptibility of a fluid on temperature or composition (whichever is driving convection). All materials experience a force when placed in a magnetic field gradient. The direction and magnitude of that force depend on the magnetic susceptibility of the material. Consequently the force will vary if the susceptibility varies with temperature or composition. With a magnetic field gradient in the right direction (typically upward) and of the right magnitude, this variation in the magnetic force can be made to exactly cancel the variation in the gravitational force. Expressed another way, normal buoyancy is exactly countered by a "magnetic buoyancy". To demonstrate the principle, a solution of MnC12 in water has been used. First the variation of the susceptibility of this paramagnetic solution with temperature and concentration was measured. Then a "cell", containing this solution and 50mm long by 15mm high by 155mm wide, was placed in a superconducting magnet at Marshall Space Flight Center. The magnetic field was measured at various positions within the bore of the magnet using a Hall effect probe. In this way, a position was found where the magnetic field gradient was predominantly upward; the magnitude of the gradient could then be adjusted by adjusting the current of the magnet. The ends of the cell consisted of machined copper blocks maintained at controlled temperatures by circulating water from constant temperature baths. The walls of the cell were of rectangular section glass tubing so that the cell contents could be seen. Velocities arising from thermal gradients within the cell were measured by particle image velocimetry (PIV). Particles used for this purpose were silver-coated hollow glass spheres of micrometers diameter and nearly the same density as the solution. A central vertical plane of the cell was illuminated by a laser beam passing through a cylindrical lens. Digital images of the particles were captured on a CCD camera and fed to a computer so that frame-to-frame movements of particles traveling with the fluid were captured. These images were employed to compute velocity maps using commercial PIV software. In a typical experiment the cold end of the cell was maintained at 10C and the warm end at 30 C. With no current in the magnet, i.e.- with natural -convection allowed to occur, the fluid was observed to circulate with an average speed of approximately 0.3 millimeters per second. It was visually apparent that this circulation was diminished as the current was increased. At currents of approximately 20A the flow was halted, to within the precision of the PIV measurements. At yet higher currents the convection was reversed with the hotter solution sinking and the cooler solution rising. At 40A this reversed convection had speeds averaging 0.43 millimeters per second. The measurements of susceptibility and density allow an estimate of the field gradient necessary to halt convection in the experiment. That estimate was 7.8T (squared) per meter and the convection was observed to halt in the magnet at a current giving 7.21T (squared) per meter from the magnetic field measurements. Calculations of the flow have been carried out using the computational fluid dynamics software FLUENT and show good agreement with the measurements.

Seybert, C. D.↗

Wave steepening and shock formation in ultracold neutral plasmas

We present observations of wave steepening and signatures of shock formation during expansion of ultracold neutral plasmas formed with an initial density distribution that is centrally peaked and decays exponentially with distance. The plasma acceleration and velocity decrease at large distance from the plasma center, leading to central ions overtaking ions in the outer regions and the development of a steepening front that is narrow compared to the size of the plasma. The density and velocity change dramatically across the front, and significant heating of the ions is observed in the region of steepest gradients. For a reasonable estimate of electron temperature, the relative velocity of ions on either side of the front modestly exceeds the local sound speed (Mach number M≳1). This indicates that by sculpting steep density gradients, it is possible to create the conditions for shock formation, or very close to it, opening a new avenue of research for ultracold neutral plasmas.

Computational fluid dynamics↗

Estimating SHmax azimuth with P sources and vertical geophones: Use P-P reflection amplitudes or use SV-P reflection times?

We compared two methods for extracting the azimuth of maximum horizontal stress (SHmax) from 3D land-based seismic data generated by a P source and recorded with vertical geophones. In the first method, we used the direct-SV mode that is produced by all land-based P sources. P sources generate SV illumination that radiates in all azimuth directions from a source station and creates SV-P reflections that are recorded by vertical geophones. Unless stratigraphy has steep dip, SV-P raypaths recorded by vertical geophones are the reverse of P-SV raypaths recorded by horizontal geophones. Thus, SV-P data provide the same S-wave sensitivity to stress fields as popular P-SV data do. In the second method, we retrieved P-P reflections and then performed an amplitude-variation-with-azimuth (AVA) analysis of the amplitude-gradient behavior of P-P reflection wavelets. We did this analysis in narrow azimuth corridors to determine the gradient of reflection-wavelet amplitudes as a function of azimuth. This P-P AVA amplitude-gradient method has been of great interest in the reflection seismology community since it was introduced in the late 1990s. Each of these methods, AVA analysis of the gradient of P-P reflection amplitudes and azimuth-dependent arrival times of SV-P reflections, can be used to determine the azimuth of SHmax stress. We compare the results of the two methods with ground truth measurements of SHmax azimuth at a CO 2 sequestration site in the Michigan Basin. SHmax azimuths were determined from P-P and SV-P data at three major boundaries at depths of approximately 3500 ft (1067 m), 5500 ft (1676 m), and 7500 ft (2286 m). Two estimates of SHmax azimuth (one using SV-P data and one using P-P data) were made at each stacking bin inside a 24 mi 2 (62 km 2 ) image space. The result was approximately 98,000 estimates of SHmax azimuth across each of these three boundaries for each of these two prediction strategies. Histogram displays of PP AVA gradient estimates had peaks at correct azimuths of SHmax at all three depths, but the spread of the distributions widened with depth and split into two peaks at the deepest boundary. In contrast, each histogram of SHmax azimuth predicted by azimuth-dependent SV-P traveltimes had a single, definitive peak that was positioned at the correct SHmax azimuth at all three boundary depths.

Geochemistry & Geophysics↗

Baltimore Social-Environmental Collaborative (BSEC) Doppler Lidar & Derived Products

This repository contains all processed Doppler‐lidar outputs from the PSU lidar deployed for the Baltimore Social‐Environmental Collaborative (BSEC) project. Vertical Stare Scans (fixed‐beam, vertical profiling): 1 Hz backscatter intensity (m⁻¹ sr⁻¹), signal‐to‐noise ratio (unitless), and Doppler vertical‐velocity (m s⁻¹) on ~30 m range gates, stored as CF-compliant NetCDF. Wind Profiles (horizontal‐wind retrieval): daily NetCDF outputs of retrieved horizontal wind speed (m s⁻¹) and direction (degrees), computed from the angled‐scan returns. Profile Statistics (summary statistics on the vertical velocity): 15 min windows (default) of mean, variance, skewness, kurtosis, high-frequency variance, etc., as a function of height; saved as CF-compliant NetCDF files. Boundary Layer Height (BLH) (fuzzy-logic output): 15 min BLH estimates (m), with lower/upper fuzzy bounds (m) and a quality flag (0–4) indicating data status (e.g., no data, good, below range, ran out of signal, cloud-topped). Cloud Base Height (Haar-gradient detection): 15 min estimates of cloud-base height (m) with a cloud-detection quality flag (0–3: none, low, moderate, high). All five product streams are organized by year and date under their own top-level folders (01_Vertical_Stare_Scans/ through 05_Cloud_Height/). Each folder contains a data_ /YYYY/ subdirectory with daily CF-compliant NetCDF outputs (96 windows per day at 15 min intervals). Global attributes in each file include creation history, version (2.0.0), institution, and source. Instrument & MeasurementsThe PSU Doppler Lidar samples aerosol backscatter (m⁻¹ sr⁻¹), signal-to-noise ratio, and radial velocity at ~1 Hz. Vertical stare scans point the beam straight up; after collecting angled scans through multiple elevation angles, the "Wind Profiles" product contains the fully retrieved horizontal wind speed and direction. Data were collected continuously at ~30 m range resolution, with a typical height ceiling of ~12 km. How to Use Open any NetCDF with Python's xarray, MATLAB, or similar CF-compliant tools. Stare scans and angled-scan retrievals (Wind Profiles) are CF-compliant daily NetCDF files. Profile-Statistics, BLH, and Cloud Height files are daily 15 min summaries (96 time steps per file). Inspect the included variables (e.g., vertical_velocity_variance, wind_speed, BLH, cloud_base_height) for your analyses. Use the quality flags (BLH_flag, cloud_flag) to filter out poor-quality retrievals. For more information or questions about processing methods, please contact:Nicholas E. Prince ⟨nec5299@psu.edu⟩Penn State Department of Meteorology & Atmospheric Science

Air Quality↗

Baltimore Social-Environmental Collaborative (BSEC) Doppler Lidar & Derived Products

This repository contains all processed Doppler‐lidar outputs from the PSU lidar deployed for the Baltimore Social‐Environmental Collaborative (BSEC) project. Vertical Stare Scans (fixed‐beam, vertical profiling): 1 Hz backscatter intensity (m⁻¹ sr⁻¹), signal‐to‐noise ratio (unitless), and Doppler vertical‐velocity (m s⁻¹) on 30 m range gates (and 3 m range gates), stored as CF-compliant NetCDF. Wind Profiles (horizontal‐wind retrieval): daily NetCDF outputs of retrieved horizontal wind speed (m s⁻¹) and direction (degrees), computed from the angled‐scan returns. Profile Statistics (summary statistics on the vertical velocity): 15 min windows (default) of mean, variance, skewness, kurtosis, high-frequency variance, etc., as a function of height; saved as CF-compliant NetCDF files. Boundary Layer Height (BLH) (fuzzy-logic output): 15 min BLH estimates (m), with lower/upper fuzzy bounds (m) and a quality flag (0–4) indicating data status (e.g., no data, good, ran out of signal, below range, cloud-topped). Cloud Base Height (Haar-gradient detection): 10 min estimates of cloud-base height (m). All five product streams are organized by year and date under their own top-level folders (01_Vertical_Stare_Scans/ through 05_Cloud_Height/). Each folder contains a data_ /YYYY/ subdirectory with daily CF-compliant NetCDF outputs (96 windows per day at 15 min intervals). Global attributes in each file include creation history, version (3.0.0), institution, and source. Instrument & MeasurementsThe PSU Doppler Lidar samples aerosol backscatter (m⁻¹ sr⁻¹), signal-to-noise ratio, and radial velocity at ~1 Hz. Vertical stare scans point the beam straight up; after collecting angled scans through multiple elevation angles, the "Wind Profiles" product contains the fully retrieved horizontal wind speed and direction. Data were collected continuously at ~30 m range resolution (and 3 m for the year of 2025), with a typical height ceiling of ~12 km. How to Use Open any NetCDF with Python's xarray, MATLAB, or similar CF-compliant tools. Stare scans and angled-scan retrievals (Wind Profiles) are CF-compliant daily NetCDF files. Profile-Statistics, BLH, and Cloud Height files are daily 15 min (10 min for Cloud Heights) summaries (96 time steps per file). Inspect the included variables (e.g., vertical_velocity_variance, wind_speed, BLH, cloud_base_height) for your analyses. Use the quality flags (BLH_flag, cloud_flag) to filter out poor-quality retrievals. For more information or questions about processing methods, please contact:Nicholas E. Prince ⟨nec5299@psu.edu⟩Penn State Department of Meteorology & Atmospheric Science

Air Quality↗