Oceanography and Atmospheric Sciences and Meteorology Commons^™

Effective Visibility In The Infrared Bands, Peter L. Dean-Erlander, Steven T. Fiorino, Ronald G. Driggers

Faculty Publications

Visibility is an atmospheric metric for the comparison of terrestrial imaging conditions and locations. A limitation of visibility is that it is defined for the visible spectrum only, and there is no simple infrared equivalent. This study compares three reflective infrared wavebands: near-IR (NIR), shortwave IR (SWIR), and extended shortwave IR (eSWIR), to the visible band across a global set of cities to develop three rule-of-thumb functions for IR effective visibility. To accomplish this, a radiometric sensor model is combined with the Laser Environmental Effects Definition and Reference (LEEDR) software package to calculate the visibility of a black-and-white contrast target …

An Atmospheric Optical Turbulence Structure Parameter Measurements System Based On Direct Ri Sensing Using High-Resolution Fiber-Optic Sensors, Matej Njegovec, Simon Pevec, Vedran Budinski, Boris Macuh, Melissa K. Beason, Denis Onlagic

Faculty Publications

The paper presents a method to characterize the refractive index structure parameter (C_n²) associated with optical turbulence directly. The characterization system is based on miniature, high‑resolution, all‑fiber refractive index (RI) sensors. The refractive index sensors employ open‑path, low‑finesse Fabry–Perot interferometers that are approximately 8 mm long and 200 μm in diameter. The active part of the interferometers is made of ultra‑low‑expansion glass, which eliminates the influence of thermal expansion on the refractive index measurements. The proposed refractive index sensor, operating in a differential configuration, achieved a resolution of 2×10^-9 RIU using a custom‑designed spectral interrogation system …

Modeling Formation Of Turbulent Sporadic-E Clouds Using Realistic Wind Data, Aaron M. Schinder, Kenneth S. Obenberger, Jorge L. Chau, Juan M. Urco, Matthias Clahsen, Benjamin F. Akers, Daniel J. Emmons

Faculty Publications

A high resolution two-dimensional multi-fluid model of sporadic-E layers was developed and driven with physically realistic mesosphere, lower thermosphere (MLT) winds measured over Albuquerque, New Mexico. The realistic E-region winds are produced by the HYdrodynamic Point-wise Environment Reconstructor (HYPER) model that ingests meteor derived wind observations from a Spread-spectrum Interferometric Multistatic meteor radar Observing Network (SIMONe) system combined with the Navier-Stokes equations to provide high resolution three-dimensional wind fields over time. Sporadic-E dynamics are simulated using both realistic winds from HYPER as well as idealized hyperbolic tangent windshears to compare and contrast. Overall, the model shows greater inhomogeneity and irregularity …

Characterizing Atmospheric Turbulence With The Lunar Step Response Method, Patrick D. Carattini, Caleb J. Stilp, Katelyn M. Atkinson, Stephen C. Cain

Faculty Publications

Most methods that astronomers use to characterize the strength of atmospheric turbulence in and around their observatories use differential image motion monitors observing a star to provide the necessary data for the measurement. With the Moon becoming a greater national priority, the need to characterize atmospheric paths between observatories on Earth and the Moon is potentially going to grow in the future. To this end, the differential image motion monitor is not an ideal instrument for characterizing turbulence along paths between observatories and the Moon as the bright Moon makes it difficult to detect and locate stars in its vicinity. …

A Comparison Of Modeled Daytime E Regions From E-Probed And Pyiri With Ionosonde Observations, Daniel J. Emmons, Cornelius C. J. H. Salinas, Dong L. Wu, Nimalan Swarnalingam, Eugene V. Dao, Jorge L. Chau, Yosuke Yamazaki, Kyle E. Fitch, Victoriya V. Forsythe

Faculty Publications

While the F region is the primary focus of many ionospheric models because it contains the peak electron density, the E region is an important region for ionospheric conductivities and high-frequency radio propagation. This study analyzes modeled E regions from the newly developed PyIRI and E-PROBED models. A long-term comparison of E region predictions from E-PROBED and PyIRI with ionosonde observations is performed for three sites spanning low- (Fortaleza, Brazil), mid- (El Arenosillo, Spain), and high-latitudes (Gakona, Alaska). Modeled foE and hmE trends are compared against a combination of manually-scaled and automatically-scaled ionograms using ARTIST-5 for the period 2009–2024 for …

Validation And Proposed Expansion Of The Data-Driven D Region Model, Kevin M. Watson

Theses and Dissertations

Predicting ionosphere effects on radio wave propagation is critical for communications and over-the-horizon radar systems. The D region is challenging to model for several reasons, one of which is chemical complexity. Ion density changes during sunrise/sunset introduce substantial uncertainty in electron density profiles (EDPs). The Data Driven D Region (D3R) model solves electron densities through an ion chemistry model and assimilates relevant space weather inputs. This study evaluates D3R against the Faraday International Reference Ionosphere (FIRI) and measurements using Very Low Frequency (VLF) propagation paths. Space weather event impacts on D3R EDPs are evaluated during the disturbed period from 8-12 …

Global Sporadic-E Prediction And Climatology Using Deep Learning, J. A. Ellis, Daniel J. Emmons, M. B. Cohen

Faculty Publications

Sporadic-E (E_s) is an ionospheric phenomenon defined by strong layers of plasma which may interfere with radio wave propagation. In this work, we develop deep learning models to improve the understanding of E_s, including the presence, intensity and height of the layers. We developed three separate models. The first, building off earlier work in (J. A. Ellis et al., 2024, link in AFIT Scholar, 10.1029/2023sw003669), includes only the main features from radio occultation (RO) measurements. The second adds to that time, date, location, geomagnetic and solar indices, solar winds, x-ray flux, weather and lightning. A …

Simultaneous Observations Of Irregular Sporadic E Structures Using The Lwa And A Dps4d, Kenneth S. Obenberger, C. A. Taylor, Jonah J. Colman, Eugene Dao, J. Dowell, J. D. Eccles, Daniel J. Emmons, C. T. Fallen, J. M. Holmes, G. B. Taylor

Faculty Publications

Multi-instrument studies have recently shed new light on the morphology of sporadic E, especially intense sporadic E. Here we present simultaneous observations of dense sporadic E (E_s) structures using the Long Wavelength Array (LWA) radio telescopes and a Digisonde Portable Sounder 4D (DPS4D). Our coordinated observations show that the LWA radio telescopes in central New Mexico can reliably locate regions of dense Es structures as they pass over a Digisonde located over 500 km away in Texas. The LWA appears to be most sensitive to the densest E_s structures, which also appear to contain irregularities with vertical …

Global Ionospheric F Region Parameters From Gnss-Pod Limb Measurements: Evaluations And Comparisons With Two Empirical Models - Iri-2020 And Nequick-2, Nimalan Swarnalingam, Dong L. Wu, Dieter Bilitza, Daniel J. Emmons, Cornelius Csar Jude H. Salinas, Artem Smirnov, Yenca Migoya-Oru

Faculty Publications

An optimal estimation (OE) technique has recently been developed for F region electron density (Ne) using Global Navigation Satellite System (GNSS) limb sounding on low Earth orbit (LEO) satellites (COSMIC-2, Spire, and FengYun-3). This method provides unprecedented spatiotemporal sampling for global monthly Ne climatology within 100–500 km in 2 hr intervals. The global dataset, collected during mid to moderately high solar activity, is compared with leading models: IRI-2020 and NeQuick-2. Diurnal variations in summer, winter, and equinoctial months are examined for the F2-layer peak, as well as the topside and bottomside of the F region. The observed and modeled NmF2 …

The Effects Of Snow Cover On The Dynamic Pressure Of Nuclear Detonation Blast Waves, Adam Card, Andrew W. Decker

Faculty Publications

Blast pressure is the primary military targeting metric for nuclear weapons. Any local conditions that affect blast pressure have the potential for altering nuclear plans, both from defensive and offensive standpoints. Understanding the impact of snow to the blast wave, therefore, provides a benefit both to military planners and to warfighters on the ground, for any operation occurring in arctic environments. No existing data provides a quantitative description of how snow on the ground affects a nuclear detonation blast wave passing over it. Similar blast waves passing over dust have experimentally proven to enhance blast pressure in a localized region.1 …

Analyzing Lf/Vlf Lightning Waveforms To Estimate D-Region Electron Density Profiles: Process, Application, And Comparison, William R. Smith

Theses and Dissertations

Lightning waveforms in the low frequency (LF; 30-300 kHz) and the very low frequency (VLF; 3-30 kHz) can be exploited to produce data-driven ionospheric Dregion electron density profile (EDP) estimates with significantly higher spatial and temporal coverage than previously available. The lightning waveforms used in this paper are signals detected in the LF/VLF of negative cloud-to-ground lightning by the Earth Networks Total Lightning Detection Network. Each waveform contains a ground wave and a time-delayed ionospheric reflection. The time delay between the ground wave and ionospheric reflection has previously been used to estimate a single specular reflection altitude, where LF/VLF emissions …

Spatiotemporal Prediction Of Atmospheric Events Through Recurrent Deep Learning Model, Brian W. F. Popick

Theses and Dissertations

The main contributions of this research is to add to the growing library of literature on the use of deep learning algorithms for the spatiotemporal prediction of dangerous atmospheric and hydrologic phenomena. Specifically, we develop novel attention-based and non-attention-based recurrent neural network frameworks to produce short-range sequential forecasts for lightning and tornado occurrences. Additionally, we introduce methods that account for and include error in the model tuning process to generate more reliable models. Furthermore, we have created a lightweight spatiotemporal tornadic prediction dataset that we plan to make publicly available. The first component of this research develops three novel spatiotemporal …

Evaluating Weather Effects On Sortie Generation Using Discrete Event Simulation, Markus Case

Theses and Dissertations

United States Air Force (USAF) operations rely on sortie generation, a complex system involving aircraft maintenance, operational planning, munitions, security forces, and aircrew. Failures in any of these areas can jeopardize a mission, and extreme weather events such as lightning, high winds, and snow further complicate operations. This thesis examines the impact of extreme weather on sortie generation, focusing on developing a data-driven discrete-event simulation (DES) to predict generation timelines and identify high-risk areas. The model allows users to adjust key inputs, including the month, number of aircraft, processing times, and personnel/equipment availability. By simulating real-world conditions, the model helps …

Global Empirical Model Of Sporadic-E Occurrence Rates, Eli V. Parsch, Anthony L. Franz, Eugene V. Dao, Dong L. Wu, Nimalan Swarnalingam, Cornelius C. J. H. Salinas, Daniel J. Emmons

Faculty Publications

Intense ionization enhancements in the Earth’s ionosphere, known as sporadic-E (E_s), can degrade and severely disrupt the propagation of radio signals. Although many previous studies have analyzed the characteristics and morphologies of sporadic-E, few efforts have attempted to model global E_s occurrence rates (ORs) at high time resolutions. This study develops a global empirical model of blanketing sporadic-E occurrence rates using a Karhunen–Loéve Expansion (KLE) of a global OR climatology built with Global Navigation Satellite System radio occultation (GNSS-RO) and ionosonde observations. Using an fbE ≥ threshold of 3 MHz, the model outputs a blanketing sporadic-E …

Predictability Limit Of The 2021 Pacific Northwest Heatwave From Deep‐Learning Sensitivity Analysis, P. Trent Vonich, Gregory J. Hakim

Faculty Publications

The traditional method for estimating weather forecast sensitivity to initial conditions uses adjoint models, which are limited to short lead times due to linearization around a control forecast. The advent of deep‐learning frameworks enables a new approach using backpropagation and gradient descent to iteratively optimize initial conditions, minimizing forecast errors. We apply this approach to the June 2021 Pacific Northwest heatwave using the GraphCast model, yielding over 90% reduction in 10‐day forecast errors over the Pacific Northwest. Similar improvements are found for Pangu‐Weather model forecasts initialized with the GraphCast‐derived optimal, suggesting that model error is an unimportant part of the …

Open-Loop Wavefront Sensing In The Presence Of Speckle And Weak Scintillation, Derek J. Burrell, Mark F. Spencer, Ronald G. Driggers

Faculty Publications

In this paper, we show that speckle averaging helps to reduce the measurement error associated with a Shack–Hartmann wavefront sensor (SHWFS); however, this reduction is rendered ineffective with increasing beacon anisoplanatism. We do so operating in a weak-scintillation regime, where the SHWFS offers robust performance, and using in-plane translation of the illuminated rough surface to accomplish frame-to-frame speckle diversity. Understanding these trade-space limitations is critical when performing wavefront sensing with noncooperative, extended-source beacons.

Remote Profiling Of Atmospheric Turbulence: Enhanced Resolution With Stacked Rayleigh Beacons In Tardis, Benjamin C. Wilson

Theses and Dissertations

A stacked beacon turbulence profiling methodology has been introduced and applied to have increased profiling on the Turbulence and Aerosol Research and Investigation System (TARDIS). The model was derived and demonstrated the applicability through discussion on data processing and inversion processes. The methodology was applied for two different nighttime experiments, one in Summer and one in Fall. C 2 n profiles were derived into the 1300 m altitude ranges for both nights and the summer experiment was compared to a co-located DELTA Sky measurements and LEEDR generated Climatological profiles. The comparison implied promise in the methodology with additional work needed …

Phase Error Scaling Law In Two-Wavelength Adaptive Optics, Milo W. Hyde Iv, Matthew Kalensky, Michael J. Spencer

Faculty Publications

We derive a simple, physical, closed-form expression for the optical-path difference (OPD) of a two-wavelength adaptive-optics (AO) system. Starting from Hogge and Butts’ classic OPD variance integral expression, we apply Mellin transform techniques to obtain series and asymptotic solutions to the integral. For realistic two-wavelength AO systems, the former converges slowly and has limited utility. The latter, on the other hand, is a simple formula in terms of the separation between the AO sensing (i.e., the beacon) and compensation (or observation) wavelengths. We validate this formula by comparing it to the OPD variances obtained from the aforementioned series and direct …

Quantification Of Surface Layer Turbulence Using Sensible Heat Values From Energy Balance Versus Aerodynamic Methods, Steven T. Fiorino, Yogendra Raut, Jaclyn Schmidt, Laura Slabaugh, Blaine Fourman, Jack E. Mccrae, Benjamin C. Wilson, Santasri R. Bose-Pillai

Faculty Publications

Surface layer optical turbulence values in the form of the refractive index structure function C_n^2 are often calculated from surface layer temperature, moisture, and wind characteristics and compared to measurements from sonic anemometers, differential temperature sensors, and imaging systems. A key derived component needed in the surface layer turbulence calculations is the sensible heat value. Typically, the sensible heat is calculated using the bulk aerodynamic method that assumes a certain surface roughness and a friction velocity that approximates the turbulence drag on temperature and moisture mixing from the change in the average surface layer vertical wind velocity. These assumptions/approximations generally …

Deterministic Global 3d Fractal Cloud Model For Synthetic Scene Generation, Aaron M. Schinder, Shannon R. Young, Bryan J. Steward, Michael L. Dexter, Andrew Kondrath, Stephen Hinton, Ricardo Davila

Faculty Publications

This paper describes the creation of a fast, deterministic, 3D fractal cloud renderer for the AFIT Sensor and Scene Emulation Tool (ASSET). The renderer generates 3D clouds by ray marching through a volume and sampling the level-set of a fractal function. The fractal function is distorted by a displacement map, which is generated using horizontal wind data from a Global Forecast System (GFS) weather file. The vertical windspeed and relative humidity are used to mask the creation of clouds to match realistic large-scale weather patterns over the Earth. Small-scale detail is provided by the fractal functions which are tuned to …

Investigating Turbulence Distribution In The Lower Atmosphere Using Time-Lapse Imagery From A Camera Bank, Benjamin C. Wilson, Santasri R. Bose-Pillai, Jack E. Mccrae, Steven T. Fiorino, Robert P. Freeman, Laura R. Slabaugh

Faculty Publications

The atmosphere’s surface layer (first 50–100 m above the ground) is extremely dynamic and is influenced by surface radiative properties, roughness, and atmospheric stability. Understanding the distribution of turbulence in the surface layer is critical to many applications, such as directed energy and free space optical communications. Several measurement campaigns in the past have relied on weather balloons or sonic detection and ranging (SODAR) to measure turbulence up to the atmospheric boundary layer. However, these campaigns had limited measurements near the surface. We have developed a time-lapse imaging technique to profile atmospheric turbulence from turbulence-induced differential motion or tilts between …

Assessing The Relationship Between The Quasi-Biennial Oscillation And D-Region Electron Density, Natalie R. Wirth

Theses and Dissertations

High frequency (HF) communication is a vital aspect of military communication and is highly reliant upon ionospheric conditions. The variation in electron density within the lowest echelon of the ionosphere, the D-region, can significantly impact HF signals, making communication inconsistent and unreliable for these wavelengths. Despite the D-region’s important, research in this area mainly focuses on understanding the impact of space weather anomalies on the upper ionosphere, particularly its higher layers, with relatively little exploration of the D-region. This region, situated closest to the troposphere and stratosphere, has been definitively linked to solar weather events like solar flares and geomagnetic …

Global Empirical Model Of Sporadic-E Occurrence Rates, Eli V. Parsch

Theses and Dissertations

Encompassing the Earth, the ionosphere presents unique challenges to modern communication, navigation, and surveillance technologies. Intense ionization enhancements known as sporadic-E (Es), can degrade and disrupt signals in unpredictable ways. Much work has been done to understand this phenomenon and more recent efforts have attempted to model its behavior and impacts. However, there have been limited efforts at modeling global Es occurrence rates (OR) at high time resolutions. This study develops a global empirical model of blanketing sporadic-E (fbEs) occurrence rates using a Karhunen-Lo´eve Expansion (KLE) of global fbEs OR climatologies built with Global Positioning System radio occultations (GPS-RO) and …

Investigation Of High-Latitude Gnss Radio Occulation Sporadic-E And Auroral-E Measurements, Kyle D. Roberts

Theses and Dissertations

Abnormal sporadic-E (E_s) occurrences were found in the high latitude regions during a recent climatology study by (Hodos, 2022), that calculated sporadic-E occurrence rates derived from a data set of GPS radio occultation (GPS-RO) and ionosondes. In this study, sporadic-E GNSS-RO techniques are shown to falsely attribute sporadic-E events to auroral-E (E_a) events. A comparative study is conducted on GPS-RO measurement techniques to find false occurrence rates for various RO techniques using a single ionosonde site in Gakona, Alaska. Phase-based RO techniques were found to be more likely to falsely attribute sporadic-E as auroral-E, while amplitude …

Modeling Lightning Flashes In Dissimilar Non-Homogeneous Clouds, Scott R. Wolff

Theses and Dissertations

A new methodology for near-infrared lightning radiative transfer through clouds is presented. High-resolution weather modeling is used to generate realistic three-dimensional non-homogeneous clouds, which are then used as environments for a Monte Carlo simulation of photon multiple scattering from approximations of lightning flashes. Resultant emissions from the cloud tops are in line with previous studies and satellite observations.

Center Fixing Tropical Depressions And Tropical Storms Using Machine Learning-Nighttime Visible Imagery, Nathan K. Stanford

Theses and Dissertations

The first step in most TC-retrieval algorithms is determining the storm’s central position. In mature TCs, the center is highlighted by a distinct eye and curved band pattern; however, in intensifying and decaying storms, the center is often obscured by thick clouds or overlying cirrus. This study assesses the benefits of incorporating machine learning-derived nighttime visual imagery to improve analysis of center fix in intensifying and decaying TD- and TS-strength TCs during periods of darkness and when polar orbiting satellites are unavailable. The study is divided into two parts: the first, an objective analysis using the ARCHER-2 algorithm, and the …

Seasonal Variability And Predictability Of Monsoon Precipitation In Southern Africa, Matthew F. Horan, Fred Kucharski, Moetasim Ashfaq

Faculty Publications

Rainfed agriculture is the mainstay of economies across Southern Africa (SA), where most precipitation is received during the austral summer monsoon. This study aims to further our understanding of monsoon precipitation predictability over SA. We use three natural climate forcings, El Niño–Southern Oscillation, Indian Ocean Dipole (IOD), and the Indian Ocean Precipitation Dipole (IOPD)—the dominant precipitation variability mode—to construct an empirical model that exhibits significant skill over SA during monsoon in explaining precipitation variability and in forecasting it with a five-month lead. While most explained precipitation variance (50%–75%) comes from contemporaneous IOD and IOPD, preconditioning all three forcings is key …

Editorial: Observations And Simulations Of Layering Phenomena In The Middle/Upper Atmosphere And Ionosphere, Bingkun Yu, Xuguang Cai, Daniel J. Emmons Ii, Chong Wang, Jainfei Wu

Faculty Publications

The middle/upper atmosphere and ionosphere are the transition between neutral and ionized components of the Earth’s atmosphere, including stratosphere, mesosphere, thermosphere, ionospheric E region and ionospheric F region (Laštovička et al., 2006; Xu, et al., 2007; Smith, 2012). The atmospheric thermal structure and composition are significantly affected by dynamical processes through coupling. The layering phenomena such as mesospheric metal layers, sporadic E layers, and noctilucent clouds are important tracers to study mechanisms of the vertical coupling from the lower to the upper atmosphere (Dou et al., 2010; Plane, 2012; Xue et al., 2013).

Detection And Classification Of Sporadic E Using Convolutional Neural Networks, J. A. Ellis, Daniel J. Emmons, M. B. Cohen

Faculty Publications

In this work, convolutional neural networks (CNN) are developed to detect and characterize sporadic E (E_s), demonstrating an improvement over current methods. This includes a binary classification model to determine if Es is present, followed by a regression model to estimate the Es ordinary mode critical frequency (foEs), a proxy for the intensity, along with the height at which the Es layer occurs (hEs). Signal-to-noise ratio (SNR) and excess phase profiles from six Global Navigation Satellite System (GNSS) radio occultation (RO) missions during the years 2008–2022 are used as the inputs of the model. Intensity (foEs) and the …

Lightning Forecast From Chaotic And Incomplete Time Series Using Wavelet De-Noising And Spatiotemporal Kriging, Jared K. Nystrom, Raymond Hill, Andrew J. Geyer, Joseph J. Pignatiello Jr., Eric Chicken

Faculty Publications

Purpose: Present a method to impute missing data from a chaotic time series, in this case lightning prediction data, and then use that completed dataset to create lightning prediction forecasts.

Design/Methodology/Approach: Using the technique of spatiotemporal kriging to estimate data that is autocorrelated but in space and time. Using the estimated data in an imputation methodology completes a dataset used in lighting prediction.

Findings: The techniques provided prove robust to the chaotic nature of the data, and the resulting time series displays evidence of smoothing while also preserving the signal of interest for lightning prediction.

Abstract © Emerald Publishing …