Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Oklahoma”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Examining the Ice-Nucleating Particles from the North Slope of Alaska (ExINP-NSA) (Final Campaign Report)

The Examining the Ice-Nucleating Particles from the North Slope of Alaska (ExINP-NSA) campaign was conducted at the National Oceanic and Atmospheric Administration’s (NOAA) Barrow Atmospheric Baseline Observatory (71.3230° N, 156.6114° W, “BRW” hereafter), next to the Atmospheric Radiation Measurement (ARM) user facility NSA site and ~ 6 km northeast of the town of Utqiaġvik. The location of the NSA site is shown in Figure 1. Our observing period began in October 2021 and continued until May 2024. This campaign was funded by the U.S. Department of Energy (DOE) Office of Science Early Career Research Program through grant number DE-SC001879. This grant contains funding for three ARM field campaigns. The previous field campaigns were performed at ARM’s Southern Great Plains atmospheric observatory in Oklahoma (SGP; 36.6073° N, 97.4876° W) and the ARM’s Eastern North Atlantic atmospheric observatory on Graciosa Island, Azores (ENA; 39.0916° N, 28.0257° W). The ExINP-NSA campaign aims included: • Determining the number concentration of ice-nucleating particles (n INPs ) active at temperatures spanning the range of heterogeneous freezing processes (from ≈−30 °C to 0 °C) using a combination of online and offline measurements, • Determining whether local meteorological conditions and/or synoptic scale air mass transport impact INP abundance and/or ice nucleation efficiency, • Examining if the physicochemical properties of INPs relate to aerosol chemistry, and • Assessing if there is a similarity in INP properties across three ARM sites Multi-seasonal datasets of INP abundance in the NSA region were delivered from this campaign. This campaign also allowed researchers to perform a comprehensive analysis of atmospheric INPs based on long- term ground-based measurements in the Alaskan Arctic. Our data and results from the ExINP-NSA campaign will help refine current earth system models. One of the stated goals of ARM is to advance aerosol-cloud ice interaction, which will be a direct result of this campaign. Current earth system models poorly represent INPs, and the 15-minute time resolution data over several seasons generated during this campaign will provide an invaluable resource, especially combined with the datasets generated during two previous ARM ExINP campaigns. These datasets will allow for a greater understanding of ice nucleation processes as they may (or may not) relate to local meteorological processes and aerosol chemistry and will eventually help further the understanding of the Earth’s atmospheric processes and energy balance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

CarbonSAFE Phase II: Optimizing Alabama’s CO 2 Storage in Shelby County, Alabama (Project OASIS), Milestone M3 - Site Specific Drilling Report

The Phase II Storage Complex Feasibility project, entitled "Optimizing Alabama's CO 2 Storage in Shelby County, Alabama (Project OASIS)," is a part of the DOE/NETL's CarbonSAFE initiative. The Project is managed by the Southern States Energy Board (SSEB), and includes participation from Advanced Resources International, Inc. (ARI), Crescent Resource Innovation, Southern Company, Alabama A&M University, Auburn University, and Oklahoma State University. Project OASIS is working to establish the foundation for a commercial-scale geologic storage complex for CO 2 captured from Plant Gaston (home of the National Carbon Capture Center) and surrounding industrial sources of CO 2 located in Shelby County, Alabama. The Project objectives are: • Demonstrate that the subsurface saline formations at the storage complex can store commercial volumes of CO 2 safely and permanently. • Develop a comprehensive Community Benefits Plan. • Develop the infrastructure framework for a CO 2 storage hub. • Develop a rigorous risk registry and to conduct a comprehensive risk assessment. • Develop a monitoring plan. • Develop a comprehensive site characterization plan to support an Underground Injection Control Class VI Permit in a future Phase III program. • Evaluate the commercial viability of the project. Project OASIS is about 30 miles southeast of Birmingham, Alabama within a geologic province called the Valley and Ridge (Figure 1.1). The Valley and Ridge Province comprises a sequence of Paleozoic carbonate and clastic rocks that underwent structural deformation during the Alleghanian Orogeny. Storage prospects occur in relatively flat lying structural panels located between thrust faults. Available geologic studies related to hydrocarbon exploration suggest that Cambro-Ordovician carbonates and Cambrian clastic units offer multiple potential storage intervals, and that regional confining systems are present, such as the tectonically thickened Floyd-Parkwood Shale. The surface property is owned by a timber and land stewardship company, The Westervelt Company, Inc., who worked with the Project Team to select and prepare adequate sites for geologic assessment. The purpose of drilling the Westover Stratigraphic Test Well #2 was to collect geologic data to model the feasibility of commercial scale CO 2 injection and storage. This includes geological and geophysical evaluations, reservoir engineering analyses, and risk assessments.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Optimizing Alabama’s CO 2 Storage in Shelby County (Project OASIS) - Deliverable Task 7: Risk Assessment

The “Optimizing Alabama’s CO 2 Storage in Shelby County: Project OASIS” CarbonSAFE Phase II Project seeks to build on regional data sets that demonstrate that the subsurface within Shelby County, Alabama has the potential to store commercial volumes of CO 2 safely, permanently, and economically. The primary target CO 2 Storage Complex is the deep Ketona Dolomite located within a 140 square mile area of the Valley and Ridge Region of Alabama. This deep saline reservoir is beneath a confining system encompassing at least 6,500 ft of shales and other low permeability sediments. Project OASIS drilled a deep stratigraphic test well to confirm the geological properties of the confining system and storage reservoir(s) within the Storage Complex. The geological data was incorporated into numerical models to establish the areal extent of the CO 2 plume and help design the storage site and its monitoring system. The project is managed by the Southern States Energy Board (SSEB), an interstate compact organization consisting of governors and state legislative leaders from sixteen southern states, Puerto Rico, and the U.S. Virgin Islands, as well as an appointee by the President of the United States. The organizational compact provides it with access to state government organizations and legislatures. The Board also maintains an Associate Members program comprised of energy resource companies, utilities, trade groups, academic R&D science and technology experts and energy consultants. Further, the SSEB staff is experienced in managing and coordinating complex energy and environmental programs, from research programs to full-scale design and demonstrations of new and innovative technologies. Project OASIS is a public-private partnership of six entities with multiple principal investigators (PIs). SSEB’s Lead PI and Co-PI are responsible for all aspects of project performance in accordance with the DOE-NETL Cooperative Agreement. SSEB has issued subgrants to Advanced Resources International, Inc., Alabama A&M University, Auburn University, Crescent Resource Innovation, and Oklahoma State University. Advanced Resources International, Inc., issued subgrants to Baker Hughes and Loudon Technical Services for field services

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Southeast Regional CO 2 Utilization and Storage Acceleration Partnership (SECARB-USA): Risk Inventory for Commercial Storage Projects

The “Southeast Regional CO2 Utilization and Storage Acceleration Partnership” (SECARB USA) project supports the U.S. Department of Energy (DOE) Odice of Fossil Energy's (FE) mission to help the United States meet its need for secure, adordable, and environmentally sound fossil energy supplies by utilizing the advancements made since 2003 by the Regional Carbon Sequestration Partnership (RCSP) Initiative to continue to identify and address knowledge gaps. The SECARB-USA regional initiative encompasses the states of Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, North Carolina, South Carolina, Tennessee, Virginia, and portions of Kentucky, Missouri, Oklahoma, Texas, and West Virginia as noted in Figure 1. The primary objective of the project is to identify and address regional onshore storage and transport challenges facing commercial deployment of carbon dioxide (CO2) capture, utilization, and storage (CCUS) technologies.

42 ENGINEERING↗
DOE OSTI2020

Southeast Regional CO 2 Utilization and Storage Acceleration Partnership (SECARB-USA): A Sub-Basin Framework for Future CO 2 Infrastructure Development (Task 4.1.a)

The “Southeast Regional CO 2 Utilization and Storage Acceleration Partnership” (SECARB-USA) project supports the U.S. Department of Energy (DOE) Office of Fossil Energy's (FE) mission to help the United States meet its need for secure, affordable, and environmentally sound fossil energy supplies by utilizing the advancements made since 2003 by the Regional Carbon Sequestration Partnership (RCSP) Initiative to continue to identify and address knowledge gaps. The SECARB-USA regional initiative encompasses the states of Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, North Carolina, South Carolina, Tennessee, Virginia, and portions of Kentucky, Missouri, Oklahoma, Texas, and West Virginia as noted in Figure 1.1. The primary objective of the project is to identify and address regional onshore storage and transport challenges facing commercial deployment of carbon dioxide (CO 2 ) capture, utilization, and storage (CCUS) technologies.

42 ENGINEERING↗
DOE OSTI2020

Southeast Regional CO 2 Utilization and Storage Acceleration Partnership (SECARB-USA): Initial Inventory of Non-Technical Challenges to CCUS Deployment

The “Southeast Regional CO 2 Utilization and Storage Acceleration Partnership” (SECARBUSA) project supports the U.S. Department of Energy (DOE) Office of Fossil Energy's (FE) mission to help the United States meet its need for secure, affordable, and environmentally sound fossil energy supplies by utilizing the advancements made by the current Regional Carbon Sequestration Partnership (RCSP) Initiative to continue to identify and address knowledge gaps. The primary project objective is to identify and address regional onshore storage and transport challenges facing commercial deployment of carbon dioxide (CO 2 ) capture, utilization, and storage (CCUS) technologies. The Research Partners and a selected industry network of experienced CCUS project developers and operators will coordinate their capabilities to accelerate CCUS deployment by achieving four primary research objectives: 1) address key technical challenges; 2) facilitate data collection, sharing and analysis; 3) assess transportation and distribution infrastructure; and 4) promote regional technology transfer and dissemination of knowledge. The SECARB-USA Region includes the states of Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, North Carolina, South Carolina, Tennessee, and Virginia and portions of Kentucky, Missouri, Oklahoma, Texas, and West Virginia. Under subtask 5.2: Non-Technical Challenges to CCUS Deployment, the Southern States Energy Board (SSEB) will define and identify An Inventory of Non-Technical Challenges to CCUS Deployment. As an initial step, SSEB organized an Industry and Non-Governmental Organization (NGO) Working Group comprised of knowledgeable market participants to assist in the development of an initial list of non-technical challenges to CCUS development.

42 ENGINEERING↗
DOE OSTI2025

ArcticShark Uncrewed Aerial System

Some studies of atmospheric processes benefit from specialized instrumented observation platforms, including towers, crewed aircraft, tethered balloon systems, and uncrewed aerial systems (UAS). The ArcticShark UAS, managed by the U.S. Department of Energy’s (DOE’s) Atmospheric Radiation Measurement (ARM) User Facility, has emerged as a vital scientific platform, providing comprehensive measurements to expand the horizons of atmospheric research and ARM data. The ArcticShark focuses on small-scale, accurate, and repetitive flight patterns over areas of scientific interest, including ARM’s ground observatories in Alabama and Oklahoma. When used in concert with data from ground-based instruments and other aerial platforms, UAS observations help deliver a complete picture of atmospheric processes, helping scientists evaluate and improve the accuracy of earth system models needed to inform energy infrastructure planning.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Beryllium Isotopes in Rainfall for Stratospheric-Tropospheric Exchange Dynamics Experiment (BIRDIE) (Field Campaign Report)

The Beryllium Isotopes in Rainfall for Stratospheric-Tropospheric Exchange Dynamics Experiment or BIRDIE was a precipitation collection campaign designed to measure cosmogenic isotopes of beryllium in rainfall and other forms of precipitation across the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Southern Great Plains (SGP) atmospheric observatory. Precipitation samples were collected over three weeks (May 21-June 10, 2022) at 11 SGP sites across a 120-km 2 domain in northern and central Oklahoma. The field campaign targeted summertime convection rain events. We aimed to capture any spatial and/or temporal variability in the concentrations of beryllium-10 (10Be) and beryllium-7 (7Be) across the ARM SGP site during these rainfall events. The ratio of 10Be to 7Be (10/7Be) has been shown to be a powerful tracer for transport processes in the stratosphere-troposphere exchange (STE) system (e.g., Koch and Rind 1998). Any observed variability is analyzed to see if it could be linked to STE processes, including overshooting of deep convection clouds that penetrate the lower stratosphere. Six wet weather system events were collected within our three-week span. Five out of six of these rainfall events are classified as moderately to strongly convective. Those events are studied in more detail. The five systems also follow each other over a short period of 11 days. In our rainfall samples we observed spatial and event variability in the concentrations of beryllium-10 and -7 that resulted in variability of 10/7Be ratios. Each weather event appeared to exhibit a unique 10/7Be pattern across the domain that was not directly linked to storm total precipitation amount. To better understand the causes for this spatial variability, cloud characteristics in the domain were looked at to assess cloud type, cloud height, and depth information. We also ran Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model back trajectories to identify possible air mass and moisture origins across our events. Detailed analysis is ongoing. The purpose of this technical report is to provide background on using cosmogenic isotopes as atmospheric tracers, describe the experimental design, and present the beryllium concentration and ratio data. Lastly, we note that BIRDIE coincided with two other deep convection field campaigns in the area: The National Aeronautics and Space Administration (NASA)’s Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) experiment (https://dcotss.org/) centered in Salina, Kansas, and the Targeted Observation by Radars and (uncrewed aerial systems) UAS of Supercells (TORUS) experiment (https://catalog.eol.ucar.edu/torus_2022) across the U.S. Central Plains. Additionally, a Lawrence Livermore National Laboratory ( LLNL) team at DCOTSS attempted to measure 10Be/7Be ratios on aerosols collected in situ in the lower and mid-stratosphere over Kansas using high-altitude balloons. Precipitation samples were also collected on the ground in Salina, Kansas.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

AWAKEN Dual-Doppler Lidar (ADDLidar) Field Campaign Report

The AWAKEN Dual-Doppler Lidar (ADDLidar) experiment was conducted as part of the larger AWAKEN field campaign (https://www.nrel.gov/wind/awaken.html). The American Wake Experiment (AWAKEN) is an international, multi-institutional wind energy field campaign that was conducted from May 2022 to 2024, in the vicinity of the King Plains wind farm in north central Oklahoma. The goal of AWAKEN was to provide observations to better understand interactions between wind turbines in a wind farm and the interactions between the wind farm as a whole and the atmosphere. The focus of the ADDLidar campaign was to provide height-resolved measurements of wind speed and direction at key locations upwind of the wind farm to characterize the inflow and possible blockage effects upwind of the farm. Specifically, dual-Doppler scanning methods were employed to create a number of so-called virtual towers (Calhoun et al 2006, Debnath et al. 2017, Fernando et al. 2019, Hill et al. 2010, Newman et al. 2016, Newsom et al. 2008, 2015) upwind of the farm. The ADDLidar campaign involved the deployment of two U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility scanning Doppler lidars (S/N 236 and 237) to AWAKEN sites A4 (36.361894°, -97.356352°) and A7 (36.347259°, -97.389968°). Both sites are located approximately 29 km south of the ARM Southern Great Plains (SGP) observatory C1 site, as shown in Figure 1. These sites were chosen for their close proximity to the most southerly row of turbines in the King Plains wind farm.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Dataset for "Enrichment of phosphates, lead, and mixed soil-organic particles in INPs at the Southern Great Plains site"

Ice nucleating particles (INPs) are rare particles that initiate primary ice formation, a critical step required for subsequent important cloud microphysical processes that ultimately govern cloud phase and cloud radiative properties. Laboratory studies have found that organic-rich dusts, such as those found in soils, are more efficient INPs compared to mineral dust. However, the atmospheric relevance of these organic-rich dusts are not well understood, particularly in regions with significant agricultural activity. The Agricultural Ice nuclei at the Southern Great Plains field campaign (AGINSGP) was conducted in rural Oklahoma to investigate how soil dusts contribute to INP populations in the Great Plains. We present chemical characterization of ambient and ice crystal residual particles from a single day of sampling using single particle mass spectrometry (SPMS) and scanning microscopy. Ambient particle concentrations were primarily carbonaceous or secondary aerosol, while dust particles were enhanced in the residual particles. Dust particles measured during residual sampling contained elevated signals for phosphate ($^{63}$PO$_2^-$ and $^{79}$PO$_3^-$) and lead ($^{208}$Pb$_2^+$). Nitrate was slightly depleted relative to ambient dust, and strong sulfate signals were not seen in the residual particles measured by the miniSPLAT. The residual and ambient particles measured by the miniSPLAT were approximately the same size, though this may be a reflection of the SPMS size-dependent transmission efficiency and not that of physical truth. This study shows that organic-rich soils may be important contributors to the ambient INP population in agricultural regions.

Cornwell, Gavin C↗
DOE OSTI2023

Machine Learning Downscaling of SoilMERGE in the United States Southern Great Plains

SoilMERGE (SMERGE) is a root-zone soil moisture (RZSM) product that covers the entire continental United States and spans 1978 to 2019. Machine learning techniques, Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Gradient Boost (GBoost) downscaled SMERGE to spatial resolutions straddling the field scale domain (100 to 3000 m). Study area was northern Oklahoma and southern Kansas. The coarse resolution of SMERGE (0.125 degree) limits this product’s utility. To validate downscaled results in situ data from four sources were used that included: United States Department of Energy Atmospheric Radiation Measurement (ARM) observatory, United States Climate Reference Network (USCRN), Soil Climate Analysis Network (SCAN), and Soil moisture Sensing Controller and oPtimal Estimator (SoilSCAPE). In addition, RZSM retrievals from NASA’s Airborne Microwave Observatory of Subcanopy and Surface (AirMOSS) campaign provided a nearly spatially continuous comparison. Three periods were examined: era 1 (2016 to 2019), era 2 (2012 to 2015), and era 3 (2003 to 2007). During eras 1 and 2, RF outperformed XGBoost and GBoost, whereas during era 3 no model dominated. Performance was better during eras 1 and 2 as opposed to the pre-L band era 3. Improvements across all eras, regions, and models realized from downscaling included an increase in correlation from 0.03 to 0.42 and a decrease in ub RMSE from -0.0005 to -0.0118 m 3 /m 3 . This study demonstrates the feasibility of SMERGE downscaling opening the prospect for the development of a long-term RZSM dataset at a more desirable field-scale resolution with the potential to support diverse hydrometeorological and agricultural applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Aerosol characteristics at the Southern Great Plains site during the HI-SCALE campaign

Abstract. Large uncertainties exist in global climate model predictions of radiative forcing due to insufficient understanding and simplified numerical representation of cloud formation and cloud–aerosol interactions. The Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) campaign was conducted near the DOE's Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in north-central Oklahoma to provide a better understanding of land–atmosphere interactions, aerosol and cloud properties, and the influence of aerosol and land–atmosphere interactions on cloud formation. The HI-SCALE campaign consisted of two intensive observational periods (IOPs) (April–May and August–September, 2016), during which coincident measurements were conducted both on the G-1 aircraft platform and at the SGP ground site. In this study we focus on the observations at the SGP ground site. An Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) and an Ionicon proton-transfer-reaction mass spectrometer (PTR-MS) were deployed, characterizing chemistry of non-refractory aerosol and trace gases, respectively. Contributions from various aerosol sources, including biogenic and biomass burning emissions, were retrieved using factor analysis of the AMS data. In general, the organic aerosols at the SGP site was highly oxidized, with oxygenated organic aerosol (OOA) identified as the dominant factor for both the spring and summer IOP though more aged in spring. Cases of isoprene-epoxydiol-derived secondary organic aerosol (IEPOX SOA) and biomass burning events were further investigated to understand additional sources of organic aerosol. Unlike other regions largely impacted by IEPOX chemistry, the IEPOX SOA at SGP was more highly oxygenated, likely due to the relatively weak local emissions of isoprene. Biogenic emissions appear to largely control the formation of organic aerosol (OA) during the HI-SCALE campaign. Potential HOM (highly oxygenated molecule) chemistry likely contributes to the highly oxygenated feature of aerosols at the SGP site, with impacts on new particle formation and global climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The Portable Ice Nucleation Experiment (PINE): a new online instrument for laboratory studies and automated long-term field observations of ice-nucleating particles

Atmospheric ice-nucleating particles (INPs) play an important role in determining the phase of clouds, which affects their albedo and lifetime. A lack of data on the spatial and temporal variation of INPs around the globe limits our predictive capacity and understanding of clouds containing ice. Automated instrumentation that can robustly measure INP concentrations across the full range of tropospheric temperatures is needed in order to address this knowledge gap. In this study, we demonstrate the functionality and capacity of the new Portable Ice Nucleation Experiment (PINE) to study ice nucleation processes and to measure INP concentrations under conditions pertinent for mixed-phase clouds, with temperatures from about -10 to about -40°C. PINE is a cloud expansion chamber which avoids frost formation on the cold walls and thereby omits frost fragmentation and related background ice signals during the operation. The development, working principle and treatment of data for the PINE instrument is discussed in detail. We present laboratory-based tests where PINE measurements were compared with those from the established AIDA (Aerosol Interaction and Dynamics in the Atmosphere) cloud chamber. Within experimental uncertainties, PINE agreed with AIDA for homogeneous freezing of pure water droplets and the immersion freezing activity of mineral aerosols. Results from a first field campaign conducted at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory in Oklahoma, USA, from 1 October to 14 November 2019 with the latest PINE design (a commercially available PINE chamber) are also shown, demonstrating PINE's ability to make automated field measurements of INP concentrations at a time resolution of about 8 min with continuous temperature scans for INP measurements between -10 and -30°C. During this field campaign, PINE was continuously operated for 45 d in a fully automated and semi-autonomous way, demonstrating the capability of this new instrument to also be used for longer-term field measurements and INP monitoring activities in observatories.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Identifying insects, clouds, and precipitation using vertically pointing polarimetric radar Doppler velocity spectra

Abstract. This study presents a method to identify and distinguish insects, clouds, and precipitation in 35 GHz (Ka-band) vertically pointing polarimetric radar Doppler velocity power spectra and then produce masks indicating the occurrence of hydrometeors (i.e., clouds or precipitation) and insects at each range gate. The polarimetric radar used in this study transmits a linear polarized wave and receives signals in collinear (CoPol) and cross-linear (XPol) polarized channels. The measured CoPol and XPol Doppler velocity spectra are used to calculate linear depolarization ratio (LDR) spectra. The insect–hydrometeor discrimination method uses CoPol and XPol spectral information in two separate algorithms with their spectral results merged and then filtered into single value products at each range gate. The first algorithm discriminates between insects and clouds in the CoPol Doppler velocity power spectra based on the spectra texture, or spectra roughness, which varies due to the scattering characteristics of insects vs. cloud particles. The second algorithm distinguishes insects from raindrops and ice particles by exploiting the larger Doppler velocity spectra LDR produced by asymmetric insects. Since XPol power return is always less than CoPol power return for the same target (i.e., insect or hydrometeor), fewer insects and hydrometeors are detected in the LDR algorithm than the CoPol algorithm, which drives the need for a CoPol based algorithm. After performing both CoPol and LDR detection algorithms, regions of insect and hydrometeor scattering from both algorithms are combined in the Doppler velocity spectra domain and then filtered to produce a binary hydrometeor mask indicating the occurrence of cloud, raindrops, or ice particles at each range gate. Forty-seven summertime days were processed with the insect–hydrometeor discrimination method using US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Ka-band zenith pointing radar observations in northern Oklahoma, USA. For these 47 d, over 70 % of the hydrometeor mask column bottoms were within ±100 m of simultaneous ceilometer cloud base heights. All datasets and images are available to the public on the DOE ARM repository.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Revisiting matrix-based inversion of scanning mobility particle sizer (SMPS) and humidified tandem differential mobility analyzer (HTDMA) data

Abstract. Tikhonov regularization is a tool for reducing noise amplification during data inversion. This work introduces RegularizationTools.jl, a general-purpose software package for applying Tikhonov regularization to data. The package implements well-established numerical algorithms and is suitable for systems of up to ∼ 1000 equations. Included is an abstraction to systematically categorize specific inversion configurations and their associated hyperparameters. A generic interface translates arbitrary linear forward models defined by a computer function into the corresponding design matrix. This obviates the need to explicitly write out and discretize the Fredholm integral equation, thus facilitating fast prototyping of new regularization schemes associated with measurement techniques. Example applications include the inversion involving data from scanning mobility particle sizers (SMPSs) and humidified tandem differential mobility analyzers (HTDMAs). Inversion of SMPS size distributions reported in this work builds upon the freely available software DifferentialMobilityAnalyzers.jl. The speed of inversion is improved by a factor of ∼ 200, now requiring between 2 and 5 ms per SMPS scan when using 120 size bins. Previously reported occasional failure to converge to a valid solution is reduced by switching from the L-curve method to generalized cross-validation as the metric to search for the optimal regularization parameter. Higher-order inversions resulting in smooth, denoised reconstructions of size distributions are now included in DifferentialMobilityAnalyzers.jl. This work also demonstrates that an SMPS-style matrix-based inversion can be applied to find the growth factor frequency distribution from raw HTDMA data while also accounting for multiply charged particles. The outcome of the aerosol-related inversion methods is showcased by inverting multi-week SMPS and HTDMA datasets from ground-based observations, including SMPS data obtained at Bodega Marine Laboratory during the CalWater 2/ACAPEX campaign and co-located SMPS and HTDMA data collected at the US Department of Energy observatory located at the Southern Great Plains site in Oklahoma, USA. Results show that the proposed approaches are suitable for unsupervised, nonparametric inversion of large-scale datasets as well as inversion in real time during data acquisition on low-cost reduced-instruction-set architectures used in single-board computers. The included software implementation of Tikhonov regularization is freely available, general, and domain-independent and thus can be applied to many other inverse problems arising in atmospheric measurement techniques and beyond.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Moderate spectral resolution solar irradiance measurements, aerosol optical depth, and solar transmission, from 360 to 1070 nm, using the refurbished rotating shadow band spectroradiometer (RSS)

Abstract. This paper reports on a third-generation rotating shadow band spectroradiometer (RSS) used to measure global and diffuse horizontal plus direct normal irradiances and transmissions at 1002 wavelengths between 360 and 1070 nm. The prism-dispersed spectral data are from the Atmospheric Radiation Measurement (ARM) Southern Great Plains site in north-central Oklahoma (36.605∘ N, 97.486∘ W) and cover dates between August 2009 and February 2014. The refurbished RSS isolates the detector in a vacuum chamber with pressures near 10−7 torr. This prevents the deposition of outgassed vapors from the interior of the spectrometer shell on the cooled detector that affected the operation of the first commercial RSS. Methods for (1) ensuring the correct wavelength registration of the data and (2) deriving extraterrestrial responses over the entire spectrum, including throughout strong water vapor and oxygen bands, are described. The resulting data produced are archived as ARM data records and include cloud-screened aerosol optical depths, spectral irradiances and direct normal solar transmission, as well as normalized diffuse and global irradiances.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Correcting for filter-based aerosol light absorption biases at the Atmospheric Radiation Measurement program's Southern Great Plains site using photoacoustic measurements and machine learning

Abstract. Measurement of light absorption of solar radiation by aerosols is vital for assessing direct aerosol radiative forcing, which affects local and global climate. Low-cost and easy-to-operate filter-based instruments, such as the Particle Soot Absorption Photometer (PSAP), that collect aerosols on a filter and measure light attenuation through the filter are widely used to infer aerosol light absorption. However, filter-based absorption measurements are subject to artifacts that are difficult to quantify. These artifacts are associated with the presence of the filter medium and the complex interactions between the filter fibers and accumulated aerosols. Various correction algorithms have been introduced to correct for the filter-based absorption coefficient measurements toward predicting the particle-phase absorption coefficient (Babs). However, the inability of these algorithms to incorporate into their formulations the complex matrix of influencing parameters such as particle asymmetry parameter, particle size, and particle penetration depth results in prediction of particle-phase absorption coefficients with relatively low accuracy. The analytical forms of corrections also suffer from a lack of universal applicability: different corrections are required for rural and urban sites across the world. In this study, we analyzed and compared 3 months of high-time-resolution ambient aerosol absorption data collected synchronously using a three-wavelength photoacoustic absorption spectrometer (PASS) and PSAP. Both instruments were operated on the same sampling inlet at the Department of Energy's Atmospheric Radiation Measurement program's Southern Great Plains (SGP) user facility in Oklahoma. We implemented the two most commonly used analytical correction algorithms, namely, Virkkula (2010) and the average of Virkkula (2010) and Ogren (2010)–Bond et al. (1999) as well as a random forest regression (RFR) machine learning algorithm to predict Babs values from the PSAP's filter-based measurements. The predicted Babs was compared against the reference Babs measured by the PASS. The RFR algorithm performed the best by yielding the lowest root mean square error of prediction. The algorithm was trained using input datasets from the PSAP (transmission and uncorrected absorption coefficient), a co-located nephelometer (scattering coefficients), and the Aerosol Chemical Speciation Monitor (mass concentration of non-refractory aerosol particles). A revised form of the Virkkula (2010) algorithm suitable for the SGP site has been proposed; however, its performance yields approximately 2-fold errors when compared to the RFR algorithm. To generalize the accuracy and applicability of our proposed RFR algorithm, we trained and tested it on a dataset of laboratory measurements of combustion aerosols. Input variables to the algorithm included the aerosol number size distribution from the Scanning Mobility Particle Sizer, absorption coefficients from the filter-based Tricolor Absorption Photometer, and scattering coefficients from a multiwavelength nephelometer. The RFR algorithm predicted Babs values within 5 % of the reference Babs measured by the multiwavelength PASS during the laboratory experiments. Thus, we show that machine learning approaches offer a promising path to correct for biases in long-term filter-based absorption datasets and accurately quantify their variability and trends needed for robust radiative forcing determination.

54 ENVIRONMENTAL SCIENCES↗