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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.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

ComStock Measure Documentation: Heat Pump Rooftop Units with Standard Performance

This documentation focuses on a single end-use savings shape measure - heat pump rooftop units (HP-RTUs) with standard efficiencies that are prevalent in the current market. Today, these products are claimed as standard efficiency by the manufacturers and are most commonly installed. This document will primarily discuss the additional changes of performance and configuration of the standard efficiency HP-RTUs while a comprehensive overview of the fundamental modeling methodology and background of the HP-RTU measure, including applicability, sizing scheme, and other key assumptions can be found in the original documentation: Heat Pump RTU. The definition of "standard efficiency" can be a bit vague when considering detailed specifics other than efficiency metrics of a heat pump. Thus, we have focused on reflecting products where manufacturers claim as standard efficiency and products that are not top-of-the-line in their model lineup. Based on gathering information from eight products from four major manufacturers, there are some common (or relatively prevalent) characteristics and we have defined standard efficiency product as follows: direct drive outdoor unit fan, two stages of heat pump cooling, single stage heat pump heating (i.e., all compressors running at the same time), heat pump minimum lockout temperature of 0°F (-17.8°C), backup electric resistance heating, backup heating runs at the same time as heat pump heating , heat pump heating locking out below minimum operating temperature, IEER in between 11-13, and HSPF in between 8-8.9. There are cases where some of these products have other variations: a variable frequency drive fan, dual fuel (i.e., gas backup heating) option, three or more cooling stages, two stages of heat pump heating, no backup heating as default , etc. However, this work tried to reflect the most common and prevalent options for a standard efficiency product.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Resonant anomaly detection with multiple reference datasets

An important class of techniques for resonant anomaly detection in high energy physics builds models that can distinguish between reference and target datasets, where only the latter has appreciable signal. Such techniques, including Classification Without Labels (CWoLa) and Simulation Assisted Likelihood-free Anomaly Detection (SALAD) rely on a single reference dataset. They cannot take advantage of commonly available multiple datasets and thus cannot fully exploit available information. In this work, we propose generalizations of CWoLa and SALAD for settings where multiple reference datasets are available, building on weak supervision techniques. We demonstrate improved performance in a number of settings with realistic and synthetic data. As an added benefit, our generalizations enable us to provide finite-sample guarantees, improving on existing asymptotic analyses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Emerging investigator series: influence of marine emissions and atmospheric processing on individual particle composition of summertime Arctic aerosol over the Bering Strait and Chukchi Sea

The Arctic is rapidly transforming due to sea ice loss, increasing shipping activity, and oil and gas development. Associated marine and combustion emissions influence atmospheric aerosol composition, impacting complex aerosol–cloud–climate feedbacks. To improve understanding of the sources and processes determining Arctic aerosol composition, atmospheric particles were collected aboard the Korean icebreaker R/V Araon cruising within the Bering Strait and Chukchi Sea during August 2016. Offline analyses of individual particles by microspectroscopic techniques, including scanning electron microscopy with energy dispersive X-ray spectroscopy and atomic force microscopy with infrared spectroscopy, provided information on particle size, morphology, and chemical composition. The most commonly observed particle types were sea spray aerosol (SSA), comprising ~60–90%, by number, of supermicron particles, and organic aerosol (OA), comprising ~50–90%, by number, of submicron particles. Sulfate and nitrate were internally mixed within both SSA and OA particles, consistent with particle multiphase reactions during atmospheric transport. Within the Bering Strait, SSA and OA particles were more aged, with greater number fractions of particles containing sulfate and/or nitrate, compared to particles collected over the Chukchi Sea. This is indicative of greater pollution influence within the Bering Strait from coastal and inland sources, while the Chukchi Sea is primarily influenced by marine sources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Theoretical priors in scalar-tensor cosmologies: Thawing quintessence

The late time acceleration of the Universe can be characterized in terms of an extra, time-dependent, component of the Universe - dark energy. The simplest proposal for dark energy is a scalar-tensor theory - quintessence - which consists of a scalar field, φ, whose dynamics is solely dictated by its potential, V(φ). Such a theory can be uniquely characterized by the equation of state of the scalar field energy momentum-tensor. We find the time dependence of the equation of state for a broad family of potentials and, using this information, we propose an analytic prior distribution for the most commonly used parametrization. Here, we show that this analytic prior can be used to accurately predict the distribution of observables for the next generation of cosmological surveys. Including the theoretical priors in the comparison with observations considerably improves the constraints on the equation of state.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

A Learning-based Power Management Method for Networked Microgrids Under Incomplete Information

In this paper, we present a model-free reinforcement learning (RL)-based technique to solve the power management problem of networked microgrids (MGs), when the utility has only limited or no detailed knowledge of the MG asset models.The proposed method consists of two levels: at the first level, using an approximate RL strategy and aggregated data, a utility agent determines the locational price signals to maximize its profit under incomplete information on the MGs’ private data behind their points of common coupling (PCC). The proposed RL strategy enables the utility to adapt to changing system conditions and learn from previous experiences, while respecting the data ownership of the MGs. At the second level, the MGs receive the price signals to dispatch their generation/storage assets individually over look-ahead decision time window, while considering power flow constraints. The performance of the proposed RL technique has been verified under realistic operational scenarios.

Zhang, Qianzhi↗
DOE OSTI2020

Epidemiological surveillance of common respiratory viruses in patients with suspected COVID-19 in Southwest China

Abstract Background The outbreak of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently the peak season of common respiratory viral infections. However, the clinical symptoms of most SARS-CoV-2 infected patients are not significantly different from those of common respiratory viral infections. Therefore, knowing the epidemiological patterns of common respiratory viruses may be valuable to improve the diagnostic and therapeutic efficacy of patients with suspected COVID-19, especially in Southwest China (a mild epidemic area). Methods A total of 2188 patients with clinically suspected of COVID-19 in Southwest China were recruited from January 21 to February 29, 2020. Nasopharyngeal swabs, throat swabs and sputum specimens were collected to detect SARS-CoV-2 by using real-time reverse transcription-polymerase chain reaction (RT-PCR) and other 12 viruses via PCR fragment analysis combined with capillary electrophoresis. Clinical characteristics and laboratory test findings were acquired from electronic medical records. All data were analyzed to unravel the epidemiological patterns. Results Only 1.1% (24/2188) patients with suspected COVID-19 were eventually confirmed to have SARS-CoV-2 infection, and the most frequently observed symptoms were fever (75.0%, 18/24) and cough (20.8%, 5/24). The overall detection rate of other respiratory pathogens was 10.3% (226/2188). Among them, human rhinovirus (3.2%, 71/2188), human parainfluenza viruses (1.6%, 35/2188), influenza B virus (1.2%, 26/2188) and mycoplasma pneumonia (1.2%, 26/2188) were the predominantly detected pathogens in this study. Moreover, the co-infection was observed in 22 specimens. Notably, one COVID-19 case had a coexisting infection with human parainfluenza virus (4.2%, 1/24) and bocavirus was the most common virus tending to occur in co-infection with other respiratory pathogens. Conclusions This study reveals the epidemiological features of common respiratory viruses and their clinical impact during the ongoing outbreak of COVID-19 in a mild epidemic area. The findings highlight the importance of understanding the transmission patterns of the common respiratory virus in COVID-19 regions, which can provide information support for the development of appropriate treatment plans and health policies, while eliminating unnecessary fear and tension.

Si, Yanjun↗
DOE OSTI2026

Grid Architecture Mapping to Understand Transformation (GAMUT): Methods and Framework Architecture

Grid architecture (GA) is a concept that was developed to address the need for a comprehensive view of power grid challenges. GA can be viewed as a relatively consistent and fixed high-level approach; however, for any instantiation of grid structures, a combinatorial explosion results from each lower-layer expansion. This constitutes the main challenge with GA—it is a grid architect’s view of the system, which might not be very informative at the implementation level. Grid Architecture Mapping to Understand Transformation (GAMUT project) seeks to bridge that gap by integrating subject matter expertise across GA structures, providing users who lack expertise in GA approaches with valuable insights and informational materials. GAMUT seeks to answer feasibility questions for the approach. System-level expectations are that a GA baseline needs to be established in order for GA to be the common framework to which any lower layer approach is tied. This report explores a potential information ingestion and documentation framework to support GAMUT. The main concepts that enable the solution domain of GAMUT are discussed, and examples are provided. The solution domain leverages already-existing technology and concepts related to GA, knowledge management, and other relevant areas. To assess GAMUT building blocks and the overall approach, a feasibility assessment is proposed, rooted in systems engineering and GA architecture evaluation concepts.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Statin Drug‐Drug Interactions: Pharmacokinetic Basis of FDA Labeling Recommendations and Comparison Across Common Tertiary Clinical Resources

Abstract Statins are widely prescribed and highly susceptible to pharmacokinetic (PK)‐based drug–drug interactions (DDIs). To date, there has not been a comprehensive analysis of the basis upon which statin DDI recommendations in US Food and Drug Administration (FDA) prescribing information (PI) are derived. We have conducted such an analysis. We also assessed the degree of concordance of statin DDI recommendations in FDA PI and those provided in common tertiary clinical resources. We catalogued statin DDI information, including PK data and management recommendations, for statin precipitant drugs approved from 2010 to 2021, available from FDA PI and tertiary clinical resource databases. Recommendations were categorized and mapped with associated PK data to assess consistency in the PK basis for labeling recommendations. From the 80 precipitant drugs evaluated, 180 statin DDIs were identified in FDA PI. Dedicated clinical DDI studies were conducted for 54% (n = 97) of these DDIs and 34% (n = 61) of DDI recommendations were extrapolated from clinical data with other statins. Overall, we found that PK‐based statin recommendations were consistent across PI. These findings highlight regulatory precedence for translating information across statins without conducting dedicated clinical DDI studies, which may support future efforts toward streamlining the approach to investigation and labeling of statin DDIs. In addition, with the exception of some notable discrepancies, general concordance was observed between FDA and tertiary resources regarding “Dose Adjustment” and “Avoid Coadministration” recommendations. However, further analyses are warranted across other DDI pairs to determine whether discordance can routinely lead to different clinical recommendations depending on the drug information resource.

Mease, James↗
DOE OSTI2025

Detecting flash drought events to inform adaptive water management

Abstract: Flash droughts are characterized by a rapid onset of drought conditions, a common feature among various indicators of these events. The lack of a standardized definition and indicator makes flash droughts particularly challenging to predict and manage. We test six state-of-the-art flash drought indicators using 41 years of daily data across all Hydrological Unit Code 4 (HUC4) regions in the contiguous United States. Our results show substantial disagreements among indicators, suggesting that the detection of a flash drought event strongly depends on the choice of indicator. From the perspective of informing management and operations, an open challenge remains: which flash drought indicator should be used to trigger operational adaptations? To this end, we propose a methodological framework that informs adaptive actions by regionally assessing the level of agreement between different indicators. The regional differences in hydroclimatic conditions are expected to be reflected in the level of agreement between indicators. To better inform adaptive actions, the framework will also consider the impacted sectoral water uses and their varying response times. The insights gained from this study improve the understanding of how these different flash drought indicators capture the different aspects of regional differences and impacted sectors. Furthermore, this information can support more targeted adaptive actions to mitigate adverse impacts through improved preparedness and response strategies.

climate resilience↗
DOE OSTI2024

MISIP: a data standard for the reuse and reproducibility of any stable isotope probing-derived nucleic acid sequence and experiment

DNA/RNA-stable isotope probing (SIP) is a powerful tool to link in situ microbial activity to sequencing data. Every SIP dataset captures distinct information about microbial community metabolism, process rates, and population dynamics, offering valuable insights for a wide range of research questions. Data reuse maximizes the information derived from the labor and resource-intensive SIP approaches. Yet, a review of publicly available SIP sequencing metadata showed that critical information necessary for reproducibility and reuse was often missing. Here, we outline the Minimum Information for any Stable Isotope Probing Sequence (MISIP) according to the Minimum Information for any (x) Sequence (MIxS) framework and include examples of MISIP reporting for common SIP experiments. Our objectives are to expand the capacity of MIxS to accommodate SIP-specific metadata and guide SIP users in metadata collection when planning and reporting an experiment. The MISIP standard requires 5 metadata fields—isotope, isotopolog, isotopolog label, labeling approach, and gradient position—and recommends several fields that represent best practices in acquiring and reporting SIP sequencing data (e.g., gradient density and nucleic acid amount). The standard is intended to be used in concert with other MIxS checklists to comprehensively describe the origin of sequence data, such as for marker genes (MISIP-MIMARKS) or metagenomes (MISIP-MIMS), in combination with metadata required by an environmental extension (e.g., soil). The adoption of the proposed data standard will improve the reuse of any sequence derived from a SIP experiment and, by extension, deepen understanding of in situ biogeochemical processes and microbial ecology.

Simpson, Abigayle↗
DOE OSTI2023

Rock Valley Direct Comparison Relocation Working Group Location Results and Recommendations

Work accomplished: Collected and compared historic data for the 1993 Rock Valley earthquake sequence; Compared preliminary and prior location work from different location algorithms, phase pick sets, station constellations, and velocity models; Selected a common set of stations that could be used across all location methods for consistency; Reviewed 8 different sets of phase picks and converged on a single, reviewed set of picks for all common stations; Evaluated four pre-existing regional velocity models and incorporated new and preliminary results for five new velocity models that provide information on the very shallow (< 2km) structure near station RTPP; Compared location results from different methods while using the common sets of picks, stations, and velocity models

58 GEOSCIENCES↗
DOE OSTI2025

Automation of Vulnerability and Patch Management: Information Extraction, Association, and Optimization

Vulnerability and patch management is an integral part of a robust cybersecurity program, yet it grows increasingly complex due to the sheer amount of data that must be analyzed. Particularly in Operational Technology (OT) environments, analysis must be done manually because of the lack of automated solutions. Additionally, there are many steps in this process, from the initial discovery of the vulnerability to the implementation of its remediation, and each step in the process requires different data in order to be performed effectively. In this work, we provide approaches and strategies to assist operators in industrial or OT environments throughout the vulnerability management cycle. Security advisories provide key information about mitigation strategies, or actions that can be taken when a patch is unavailable or cannot be installed. Details of these strategies are not shared in public vulnerability databases and must be found manually. We approach this problem by designing a solution to automatically identify that information within vendor security advisories and retrieve it for operator use. We start with an approach that requires domain-specific knowledge of certain frequently-seen reference websites. Next, an approach that can work on an arbitrary website but relies on certain keywords. Finally, an approach that uses Natural Language Processing (NLP) methods and does not require specific knowledge or keywords. Each of these approaches is more general than its predecessor; we demonstrate high accuracy for all approaches Advisories also often contain details of affected products in non-standard or natural language formats. While this information can be easily understood when read by an operator, the non-standard format acts as a barrier to effective automation. We provide an approach for the first step in this process: identifying vendors in security advisories and mapping them to a standard framework for representing digital assets and software products. We evaluate five established string similarity algorithms, plus one of our own design that combines string similarity and information theory, on the task of mapping vendors to their corresponding entries in the Common Platform Enumeration (CPE) repository. Our results show that our proposed metric outperforms all others. Due to the constraints on time, finances, and personnel for organizations, Large Language Models (LLMs) may seem like attractive opportunities for security operators to speed up information gathering; however, it is still not clear whether LLMs can handle vulnerability management tasks well. To answer this question, we perform an empirical study of LLMs’ ability to provide consistent, accurate information about vulnerabilities in order to guide organizations in their adoption of LLMs. We observe poor performance for all models tested, suggesting that these models are not well-suited to the consistent retrieval of accurate vulnerability information. Finally, once vulnerabilities have been identified and any additional information has been obtained, operators must decide which remediation actions to implement based on their available resources. This already-complex problem becomes even more so when we consider that a vulnerability may have multiple avenues for remediation. We formulate this scenario as two knapsack problems and provide solutions, which we then compare against several existing strategies for vulnerability prioritization seen in real operational environments.

McClanahan, Kylie↗
DOE OSTI2020

Survey of Current State of the Art Entity-Relation Extraction Tools

In the area of information extraction from text data, there exists a number of tools with the capability of extracting entities, topics, and their relationships with one another from both structured and unstructured text sources. Such information has endless uses in a number of domains, however, the solutions to getting this information are still in early stages and has room for improvement. The topic has been explored from a research perspective by academic institutions, as well as formal tool creation from corporations but has not made much advancement since the early 2000's. Overall, entity extraction, and the related topic of entity linking, is common among these tools, though with varying degrees of accuracy, while relationship extraction is more difficult to find and seems limited to same sentence analysis. In this report, we take a look at the top state of the art tools currently available and identify their capabilities, strengths, and weaknesses. We explore the common algorithms in the successful approaches to entity extraction and their ability to efficiently handle both structured and unstructured text data. Finally, we highlight some of the common issues among these tools and summarize the current ability to extract relationship information.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Information content of and the ability to reconstruct dichroic X-ray tomography and laminography

Dichroic tomography is a 3D imaging technique in which the polarization of the incident beam is used to induce contrast due to the magnetization or orientation of a sample. The aim is to reconstruct not only the optical density but the dichroism of the sample. The theory of dichroic tomographic and laminographic imaging in the parallel-beam case is discussed as well as the problem of reconstruction of the sample’s optical properties. The set of projections resulting from a single tomographic/laminographic measurement is not sufficient to reconstruct the magnetic moment for magnetic circular dichroism unless additional constraints are applied or data are taken at two or more tilt angles. For linear dichroism, three polarizations at a common tilt angle are insufficient for unconstrained reconstruction. However, if one of the measurements is done at a different tilt angle than the other, or the measurements are done at a common polarization but at three distinct tilt angles, then there is enough information to reconstruct without constraints. Possible means of applying constraints are discussed. Furthermore, it is shown that for linear dichroism, the basic assumption that the absorption through a ray path is the integral of the absorption coefficient, defined on the volume of the sample, along the ray path, is not correct when dichroism or birefringence is strong. This assumption is fundamental to tomographic methods. An iterative algorithm for reconstruction of linear dichroism is demonstrated on simulated data.

Marcus, Matthew A. (ORCID:0000000325277586)↗
DOE OSTI2025

$H_0$ Without the Sound Horizon (or Supernovae): A 2% Measurement in DESI DR1

The sound horizon scale $r_s$ is a key source of information for early-time $H_0$ measurements, and is therefore a common target of new physics proposed to solve the Hubble tension. We present a sub-2% measurement of the Hubble constant that is independent of this scale, using data from the first data release of the Dark Energy Spectroscopic Instrument (DESI DR1). Building on previous work, we remove dependency on the sound horizon size using a heuristic rescaling procedure at the power spectrum level. A key innovation is the inclusion of \emph{uncalibrated} (agnostic to $r_s$) post-reconstruction BAO measurements from DESI DR1, as well as using the CMB acoustic scale $θ_*$ as a high-redshift anchor. Uncalibrated type-Ia supernovae are often included as an independent source of $Ω_m$ information; here we demonstrate the robustness of our results by additionally considering two supernova-independent alternative datasets. We find somewhat higher values of $H_0$ relative to our previous work: $69.2^{+1.3}_{-1.4}$, $70.3^{+1.4}_{-1.2}$, and $69.6^{+1.3}_{-1.8}\,{\rm km\,s^{-1}\,Mpc^{-1}}$ respectively when including measurements from i) Planck/ACT CMB lensing $\times$ unWISE galaxies, ii) the DES Year 3 6$\times$2pt analysis, and iii) Planck/ACT CMB lensing + the DES Year 5 supernova analysis. These remarkably consistent constraints achieve better than 2% precision; they are among the most stringent sound horizon-independent measurements from LSS to date, and provide a powerful avenue for probing the origin of the Hubble tension.

Cosmology and Nongalactic Astrophysics (astro-ph.C↗
DOE OSTI2020

Proteogenomic Characterization of Endometrial Carcinoma

We undertook a comprehensive proteogenomic characterization of 95 endometrial carcinomas, of which 83 were endometrioid tumors and 12 were serous tumors. This analysis revealed new consequences of perturbations to the p53 and Wnt/ß-catenin pathways, identified a potential role for circRNAs in the epithelial-mesenchymal transition, and provided new insights into proteomic markers of clinical and genomic tumor subgroups, some of which are in known druggable pathways. We performed a broad genome-wide acetylation survey, one of the first of its kind, yielding insights into regulatory mechanisms of histone acetylation. We also characterized the tumor immune landscape, including immunogenic alterations, neoantigens, common cancer/testis antigens, and the immune microenvironment, all of which can inform immunotherapy decisions. Collectively, our multi-omic analyses provide a valuable resource for researchers and clinicians, further our understanding of the molecular mechanisms underlying endometrial carcinoma, and identify new avenues for investigating potential therapeutic targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Microextraction-Single Particle-Inductively Coupled Plasma-Mass Spectrometry for the Direct Analysis of Nanoparticles on Surfaces

A novel employment of single particle-inductively coupled plasma-mass spectrometry (SP-ICP-MS) was developed, where a microextraction (ME) probe is used to sample nanoparticles from a surface and analyze them in a single analytical step. The effects of several parameters on the performance of ME-SP-ICP-MS were investigated, including the flow rate, choice of carrier solution, particle size, and the design of the microextraction probe head itself. The optimized ME-SP-ICP-MS technique was used to compare the extraction efficiency (EE, defined as the ratio of particles measured to particles deposited on the surface) of the commercial probe head to a newly designed SP polyether ether ketone (PEEK) probe head. The SP PEEK probe head was found to have increased EE compared to the commercial probe head (8.5 ± 3% vs 3.9 ± 3%, respectively). Increasing the carrier solution flow rate was found to decrease the total analysis time at the cost of decreasing EE. Extraction efficiencies for ME-SP-ICP-MS were typically 4–10%, which is similar to transport efficiencies (1–10%) for conventional SP-ICP-MS. Lastly, ME-SP-ICP-MS was employed for the analysis of nano- and microparticles. The sizes of gold nanoparticles, 30 ± 3 and 51 ± 1.9 nm (certified sizes), and iron-based microparticles, 1000 ± 50 nm (certified size), were accurately determined to be 32.2 ± 2.5, 50.8 ± 3.4, and 1030 ± 57 nm, respectively, by ME-SP-ICP-MS. Further, this work demonstrates the potential of ME-SP-ICP-MS for the direct analysis of particles on common collection surfaces (GSR tabs, carbon planchettes, etc.) while retaining spatial information on particle distribution across the surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Macro-physical Properties of Shallow Cumulus from Integrated ARM Observations (Final Report)

Fair-weather shallow cumuli (ShCu) play an important role in many climate-related processes. Irregular geometry of ShCu and their strong temporal and spatial variability make it challenging to observe ShCu holistically and to represent them correctly in climate models. To improve ShCu parameterizations, information on both vertically and horizontally resolved cloud properties is required. Commonly, the vertically resolved cloud properties are provided by zenith pointing lidar-radar observations with a very narrow field of view (FOV). Thus, these “pencil-beam” properties may not be representative of a larger surrounding area. Limited number of areal-averaged cloud properties, such as fractional sky cover (FSC), are offered typically by wide-FOV observations. The main goal of our project was to integrate advantages of the narrow-FOV (vertical structure of clouds) and wide-FOV (spatial arrangement of clouds) observations for an improved characterization of single-layer ShCu observed at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site for an 18-yr period (2000-2017). There are four major accomplishments of our project, First, an updated operational cloud classification for days with ShCu has been suggested and evaluated through a detailed comparison with the manually curated records. Our classification extends successfully the latest ARM cloud type Value Added Product (VAP) based on the Active Remote Sensing of Clouds (ARSCL) cloud product by incorporating both cloud fraction (CF) provided by narrow-FOV ceilometer data and FSC from wide-FOV images offered by a Total Sky Imager (TSI). Moreover, our classification allows one to identify impact of instrumentation changes at the SGP site, namely the transition to KAZRARSCL with the updated cloud radar, on the identification of periods with single-layer ShCu. Second, a new approach that resolves cloud area distributions for a given region (up to 4x4 km 2 ) has been suggested and cloud equivalent diameters (CEDs) have been estimated for the first time. These estimations have been performed over a wide range of cloud sizes (about 0.01–3.5 km) with high temporal resolution (30s) using wide-FOV TSI images and cloud base height (CBH) provided by complementary narrow-FOV lidar measurements. Our simple and computationally inexpensive approach offers a previously unavailable dataset for process studies in the convective boundary layer and evaluation of ShCu parameterizations in cloud-resolving models. Third, a long-term integrated record of ShCu macrophysical properties has been developed. The developed record represents the longest available compilation of events with ShCu and includes (i) a novel visualization of the spatial variability in cloud cover both along- and across-wind directions, (ii) updated estimates of narrow-FOV CF and wide-FOV FSC, (iii) updated narrow-FOV CBH, and (iv) complementary data, such as wind speed and direction from the 915-MHz Radar Wind Profiler (RWP) data. The developed record has been used successfully to assess conventional observational estimates of cloud cover and their sensitivity to the following two factors: (i) instrument-dependent cloud detection and data merging criteria and (ii) FOV configuration. Fourth, co-variability of the ShCu macrophysical properties and environmental parameters has been analyzed for a 3-yr period (2016-2018). Our initial analysis includes diurnal changes of FSCs obtained for clouds with small, moderate and large CEDs and several environmental parameters, such as lifted condensation level (LCL) and mixed layer height (zi). Preliminary results of our analysis suggest that the horizontal extent of ShCu is controlled substantially by the sign and magnitude of difference between these two parameters (zi-LCL): the CED tends to grow with increase of this difference (zi exceeds LCL). We have initiated relationships between the ShCu and key atmospheric parameters that control both the development and evolution of ShCu using our new data product, which combines effectively the advantages of narrow-FOV data offered by zenith pointing cloud radars and lidars and wide-FOV TSI images. While the latest instrumentation at the ARM sites may address these challenging relationships in the future, we believe that the historical ARM data at the SGP site has not yet been fully utilized. Overall, our data product can be used by researchers working on a wide range of climate-related projects. These projects may include (i) a comprehensive evaluation of outputs from the Large-Eddy Simulation (LES) and single-column models for their future improvement, (ii) the representativeness of “short-period” results obtained from the previous model and observational studies and (iii) the planning of future field campaigns with focus on improved understanding of the diurnal cycle of cumulus convection.

54 ENVIRONMENTAL SCIENCES↗