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DOE OSTI2025

Identifying Adversarial Cyber-Activity in Operational Technology Environments Using Bayesian Networks

Critical infrastructure and other operational technology (OT) environments face increasing cybersecurity risks from adversarial behavior. This paper describes the development of a risk model using a Bayesian network to enhance the comprehension of observable cyber events caused by malicious activity in OT environments. The core of the Bayesian network is a process model that describes the stages of adversary behavior. The remainder of the model is based on the MITRE ATT&CK® for Industrial Control Systems (ICS) taxonomy, which includes tactics and techniques that may be used by the adversary. The observables provide evidence for adversary behavior through the intermediary technique and tactic nodes. One challenge in constructing this model is a lack of open-source data from cyber-attacks on OT systems. This paper discusses learning from limited data, the elicitation of expert opinion to construct the conditional probability tables when data is scarce, and the refinement of the most difficult conditional probabilities tables using several forms of sensitivity analyses. Finally, the Bayesian network is demonstrated using two historical case studies: the DarkSide ransomware attack on the Colonial Pipeline and the destructive cyberattack targeting the ThyssenKrupp blast furnace. Index Terms—Cybersecurity, industrial control systems, operational technology

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Modeling Autonomous Vehicle-Targeted Aggressive Merging Behaviors in Mixed Traffic Environment

Promising advances in Autonomous Vehicle (AV) technology have fueled industry and research fields to dedicate significant effort to the study of the integration of AVs into the traffic network. This study focuses on the transition phase between all Human Driven Vehicles (HDVs) in the network to all AVs, where these different vehicle types coexist in a mixed traffic environment. This paper investigates the potential impacts of aggressive merging behaviors by human drivers on traffic performance in a mixed environment. For this, three vehicle types – AVs, HDVs, and Aggressive HDVs (AHDVs) – are modeled in an open-source microscopic traffic simulation model, SUMO. In the developed simulation, the AHDVs are modeled to emulate aggressive merging behaviors in front of AVs at a merge section of a freeway exit ramp. Several experiments are used to study the impact of such behavior. Results show travel time gains by AHDVs at the expense of AVs and HDVs.

Bae, JongIn↗

DOE OSTI2025

Arctic shrub expansion generates regional variation in litter decomposition by altering litter quality and the decomposition environment

Abstract The expansion of deciduous shrubs into the graminoid‐dominated arctic tundra is expected to alter litter decomposition by changing litter quality and local abiotic and biotic conditions. However, it remains unclear how shrub expansion will affect litter decomposition at regional scales, where macroclimate is expected to be the dominant regulator of decomposition. To determine the relative influence of macroclimate and local controls on regional patterns of litter mass loss and nitrogen release, we conducted two hierarchical litter decomposition experiments across spatial scales. We decomposed leaf and root litter from a prominent graminoid ( Eriophorum vaginatum ) and three genera of deciduous shrubs ( Betula , Alnus and Salix ) for 1 year within replicated plots at five sites spanning a 160 km latitudinal gradient in northern Alaska. Using Eriophorum litter as a substrate, we found that macroclimate was the primary regulator of mass loss but had opposing effects on leaf and root litter. As summer temperature increased along the latitudinal gradient (11.9 to 13.9°C), leaf litter mass loss increased by 20% whereas root litter mass loss decreased by 33%. Leaf nitrogen release also increased with summer temperature. Conversely, root nitrogen release was controlled by the vegetation type of the decomposition environment. Using different shrub litters as substrates, we found that litter quality and its interaction with soil microclimate and macroclimate controlled decomposition. Overall, shrub root litters decomposed faster than Eriophorum root litter, losing 53% more mass and 190% more nitrogen across all sites and decomposition environments. For leaf litter, however, patterns varied by litter genus, with Salix losing more mass and Betula and Alnus losing less mass than Eriophorum . Our findings demonstrate that shrub expansion in the Arctic can regulate leaf and root litter decomposition at the regional scale through its effects on local controls, primarily litter quality. Ongoing increases in shrub cover are likely to accelerate the turnover of root litter carbon and nitrogen pools in tundra ecosystems. Therefore, including shrub‐related processes in Earth system models will improve our ability to predict regional‐scale litter decomposition and its effects on carbon and nutrient cycling in a warming Arctic. Read the free Plain Language Summary for this article on the Journal blog.

Vozzo, Justin T. [Department of Natural Resources ↗

DOE OSTI2021

Distributed electric field sensing using fibre optics in borehole environments

In the past decade, rapid advances in distributed optical fibre sensing technologies have made it possible to record various geophysical data (e.g. strain, temperature and pressure) continuously in both time and space along the fibre, providing an unprecedented quantity and spatial density of data compared to traditional geophysical measurements as well as reducing data acquisition cost. To date, no distributed fibre-based electromagnetic field sensing system has been implemented although electromagnetic sensing could have a broad range of applications to geophysical imaging and monitoring in borehole environments. The goal of this paper is to provide a theoretical feasibility study regarding the design and use of an electromagnetic sensing optical fibre for geophysical applications. First, we present the sensitivity analysis of a ‘hypothetical’ optical fibre coated with polyvinylidene fluoride, a polymer that provides relatively high piezoelectric properties, yet unlike ceramics, is flexible. Next, using a two-dimensional electromagnetic modelling algorithm, we simulate the earth electric-field-to-fibre-strain transfer function and estimate the theoretical sensitivity of the optical fibre to electric fields. Given the state-of-the-art distributed acoustic sensing strain sensitivities in the picometres strain range, our numerical modelling analysis suggests that a perfectly coupled polyvinylidene fluoride–coated optical fibre can measure electric field values in the mV/m to V/m amplitude range. We then apply a cylindrically symmetric modelling algorithm to simulate numerical models demonstrating the applicability of such a fibre in an oilfield environment. Scenarios investigated employ an electric field source and suggest that the measurements can be used to distinguish the oil versus water ratio with a fibre mounted inside a producing steel cased oil well as well as distinguishing between brine and hydrocarbon filled reservoir zones with a fibre located outside of the casing.

58 GEOSCIENCES↗

DOE OSTI2021

A Statistical Evaluation of Combining Human Productivity Metrics in the Indoor Environment

The potential of improving human productivity by providing healthy indoor environments has been a consistent interest in the building field for decades. This research field's long-standing challenge is to measure human productivity given the complex nature of office work. Previous studies have diversified productivity metrics, allowing greater flexibility in collecting human data; however, this diversity complicates the ability to combine productivity metrics from disparate studies within a meta-analysis. This study aims to categorize existing productivity metrics and statistically assess which categories show similar behavior when used to measure the impacts of indoor environmental quality. The 106 productivity metrics compiled were grouped into six productivity metric categories: neurobehavioral speed, accuracy, neurobehavioral response time, call handling time, self-reported productivity, and performance score. Then, this study set neurobehavioral speed as the baseline category given its fitness to the efficiency-based definition of productivity (i.e., output versus input) and conducted three statistical analyses with the other categories to evaluate their similarity. As results, the categories of neurobehavioral response time, self-reported productivity, and call handling time were found to have statistical similarity with neurobehavioral speed. This study contributes to creating a constructive research environment for future meta-analyses to understand which human productivity metrics can be combined with each other.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

An Experimental Investigation of Supercritical Methane Injection Characteristics in a CO2 Environment

Abstract Clean energy generation is gaining significant attention from industries, academia, and governments across the globe. The Allam cycle is one such technology that has been under focus due to its efficiency, environmental friendliness, and economics. This is a direct-fired cycle operating at supercritical conditions using carbon dioxide as a working fluid. Fuel or oxidizer jet mixing with CO2 is a vital phenomenon that governs combustion efficiency, and it is not well understood for the Allam cycle conditions. This paper experimentally investigated the jet characteristics of a methane jet injected into a subcritical to supercritical carbon dioxide environment. A wide range of injection pressures and temperatures were targeted between subcritical to supercritical conditions. Unlike previous studies, the current work focused on injecting lower-density (methane) jets into higher-density (carbon dioxide) environments. Schlieren imaging and methane absorption measurements were simultaneously performed with a CMOS high-speed camera and a 3.39 μm infrared laser. Specifically, we looked at the classical injection parameter of jet spreading angle, which was classically established to be mainly a density ratio function. Here, the jet cone angle was obtained from the postprocessed schlieren imaging. The jet cone angle is a critical characteristic parameter that describes the entrainment rate in a jet; thus, it is a crucial parameter in understanding the nature of the jet. The laser measurements were only used as an additional check to confirm the entry time of methane into the chamber filled with carbon dioxide. Notably, this paper makes a detailed comparison between the jet cone angles of jets with a density ratio. The result showed that the classical correlations, such as Abramovich's theory applied to submerged turbulent gas jets developed for low-density ratio jets, were unsuitable for higher-density ratio jets. It was also observed that the divergence angles were dependent not only on density ratio but also on other parameters such as pressure ratios and reduced pressures.

Engineering↗

DOE OSTI2024

Selective Deposition and Fusion of AISI 316L: An Additive Manufacturing Process for Space Environments via Direct Ink Writing and Laser Processing

Unlocking the potential of additive manufacturing (AM) for space exploration hinges on overcoming key challenges, notably the ability to manufacture or repair parts on-site during exploration missions with consideration of quality, feedstock utilization, and challenges involved in microgravity environments. While there are multiple efforts to investigate the use of existing metal AM processes such as powder bed fusion (PBF), directed energy deposition (DED), and filament-based material extrusion, each process comes with a different set of challenges in space environments. Here, in this work, we introduce a new AM method that integrates the benefits of direct ink writing (DIW) to selectively deposit metallic pastes with laser-based processing to locally debind and subsequently melt and fuse metal powder, layer by layer, enabling the manufacturing of AISI 316L samples with densities exceeding 99.0%. The impact of process parameters on single-track dimensions, surface morphology, and porosity was characterized. The efficacy of laser debinding was assessed via secondary-ion mass spectrometry, permitting the carbon content to be estimated at 0.0152%, which is safely below the acceptable limit (0.03 wt%) for AISI 316L.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Evaluation of Common Thermoplastic Polymers in High-Pressure Cycling Hydrogen Under Ambient and Cold Environments as Applicable to the Hydrogen Infrastructure

Thermoplastic polymers are required to perform unfailingly under stringent conditions of changing pressures (35 MPa to 70 MPa) and temperatures (-40°C to +85°C) in storage and fueling operations. Although diffusivity in glassy polymers appear to be an order of magnitude lower than elastomers, polymer microstructural attributes such as degree of crystallinity and presence of polar and non-polar groups on the main chain with and without branching can play a substantial role in influencing their behaviors in hydrogen environments. In the work described here, the effect of high-pressure hydrogen cycling on PEEK, PTFE, PA11, HDPE, POM (and different commercial grades of these polymers) under ambient and cold (-40°C) conditions is addressed. Ex-situ characterization for polymer changes included density measurements for impact of hydrogen retention, hardness changes using nanoindentation, storage modulus and glass transition changes using dynamic mechanical and thermal analysis (DMTA), degree of crystallization with Differential Scanning Calorimetry (DSC) and tensile testing following ASTM D412. In other evaluations, solid-state nuclear magnetic resonance (NMR), attenuated total reflectance Fourier transform infra-red spectroscopy (ATRFTIR), X-ray diffraction (XRD), and X-ray CT results are presented. The overall impact of these evaluations is to establish a technical basis for the behaviors of common thermoplastics in cycling hydrogen environments under ambient and cold temperatures while establishing the relationship between polymer structure-based properties and hydrogen transport effects.

Menon, Nalini C.↗

DOE OSTI2020

Etching of Si 3 N 4 induced by electron beam plasma from hollow cathode plasma in a downstream reactive environment

An etching system based on the interaction of electrons extracted from a direct current (DC) hollow-cathode (HC) Ar plasma and injected towards a Si3N4 covered silicon substrate located in the downstream reactive environment created by an additional remote CF 4 /O 2 plasma source was developed and evaluated. By controlling the properties of the injected beam electrons, this approach allows to deliver energy to a surface functionalized by exposure to reactive species, and initiate surface etching. The energy of the primary beam electrons is controlled by the acceleration voltage relative to the HC discharge. Ar atoms flow from the high-pressure HC discharge into the low pressure downstream reactive environment in the process chamber. For an acceleration voltage greater than the ionization potential of Ar and/or process gas species, the energetic primary beam electrons produce a secondary plasma in the process chamber, and can also cause additional dissociation. We have characterized the properties of the secondary plasma and also surface etching of Si 3 N 4 as a function of process parameters, including acceleration voltage (0-80 V), discharge current of the HC discharge (1-2 A), pressure (3.5-20 mTorr), source to substrate distance (1.5 to 5 cm), and feed gas composition (20% and 80% O2 in CF 4 /O 2 ). The electron energy probability function (EEPF) measured with a Langmuir probe about 2.5 cm below the extraction ring suggests several major groups of electrons for this situation, including high energy primary beam electrons with an energy that varies as the acceleration voltage is changed and low energy electrons produced by beam electron-induced ionization of the Ar gas in the process chamber. When a remote CF 4 /O 2 plasma is additionally coupled to the process chamber, Si 3 N 4 surfaces can be functionalized, and by varying the energy of the beam electrons, Si 3 N 4 etching can be induced by electron-neutral synergy effect with plasma-surface interaction. For conditions without beam electron injection, the remote plasma etching rate (ER) of Si 3 N 4 depends strongly on the O 2 concentration in the CF 4 /O 2 processing gas mixture and can be suppressed for O 2 -rich process conditions by the formation of a SiONF passivation layer on the Si 3 N 4 surface. The combination of the HC electron beam source with the remote plasma source (HCEB-RP) makes it possible to induce Si 3 N 4 etching for O 2 -rich remote plasma conditions where remote plasma by itself produces negligible Si 3 N 4 etching. The electron enhanced etching of Si 3 N 4 depends strongly on O 2 /CF 4 mixing ratio reflecting changing arrival rates of O and F species at the surface. Optical emission spectroscopy was used to estimate the ratio of gas phase F and O densities and found to be controlled by the gas mixing ratio and independent of HC EB operating conditions. At this time the detailed sequence of events operative in the etching mechanism is unclear. While the increase of the electron energy is ultimately responsible for initiating surface etching, at present we cannot rule out a role of ions from the simultaneously produced secondary plasma in plasma surface interaction mechanisms.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

The dynamic atmospheric and aeolian environment of Jezero crater, Mars

Despite the importance of sand and dust to Mars geomorphology, weather, and exploration, the processes that move sand and that raise dust to maintain Mars’ ubiquitous dust haze and to produce dust storms have not been well quantified in situ, with missions lacking either the necessary sensors or a sufficiently active aeolian environment. Perseverance rover’s novel environmental sensors and Jezero crater’s dusty environment remedy this. In Perseverance’s first 216 sols, four convective vortices raised dust locally, while, on average, four passed the rover daily, over 25% of which were significantly dusty (“dust devils”). More rarely, dust lifting by nonvortex wind gusts was produced by daytime convection cells advected over the crater by strong regional daytime upslope winds, which also control aeolian surface features. One such event covered 10 times more area than the largest dust devil, suggesting that dust devils and wind gusts could raise equal amounts of dust under nonstorm conditions.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Single rhenium atoms on nanomagnetite: Probing the recharge process that controls the fate of rhenium in the environment

Understanding the redox transitions that control rhenium geochemistry is central to paleoredox and geochronology studies, as well as predicting the fate of chemically similar hazardous oxyanions in the environment such as pertechnetate. However, detailed mechanistic information regarding rhenium redox transitions in anoxic systems is scarce. Here, we performed a comprehensive laboratory study of rhenium redox transitions on variably oxidized magnetite nanoparticle surfaces. Through high-end spectroscopic and microscopic tools, we propose an abiotic transition pathway in which aqueous iron(II) ions in the presence of pure or preoxidized magnetite serve as an electron source to reduce rhenium(VII) to individual rhenium(IV) atoms or small polynuclear species on nanoparticle surfaces. Notably, iron(II) ions recharged preoxidized magnetite nanoparticles exhibit a maghemite core and a magnetite shell, challenging the traditional core-shell magnetite-maghemite model. This study provides a fundamental understanding of redox processes governing rhenium fate and transport in the environment and enables an improved basis for predicting its speciation in geochemical systems.

Science & Technology - Other Topics↗

DOE OSTI2024

Formation of a constructed microbial community in a nutrient-rich environment indicates bacterial interspecific competition

ABSTRACT Understanding the organizational principles of microbial communities is essential for interpreting ecosystem stability. Previous studies have investigated the formation of bacterial communities under nutrient-poor conditions or obligate relationships to observe cooperative interactions among different species. How microorganisms form stabilized communities in nutrient-rich environments, without obligate metabolic interdependency for growth, is still not fully disclosed. In this study, three bacterial strains isolated from the Populus deltoides rhizosphere were co-cultured in complex medium, and their growth behavior was tracked. These strains co-exist in mixed culture over serial transfer for multiple growth-dilution cycles. Competition is proposed as an emergent interaction relationship among the three bacteria based on their significantly decreased growth levels. The effects of different initial inoculum ratios, up to three orders of magnitude, on community structure were investigated, and the final compositions of the mixed communities with various starting composition indicate that community structure is not dependent on the initial inoculum ratio. Furthermore, the competitive relationships within the community were not altered by different initial inoculum ratios. The community structure was simulated by generalized Lotka-Volterra and dynamic flux balance analysis to provide mechanistic predictions into emergence of community structure under a nutrient-rich environment. Metaproteomic analyses provide support for the metabolite exchanges predicted by computational modeling and for highly altered physiologies when microbes are grown in co-culture. These findings broaden our understanding of bacterial community dynamics and metabolic diversity in higher-order interactions and could be significant in the management of rhizospheric bacterial communities. IMPORTANCE Bacteria naturally co-exist in multispecies consortia, and the ability to engineer such systems can be useful in biotechnology. Despite this, few studies have been performed to understand how bacteria form a stable community and interact with each other under nutrient-rich conditions. In this study, we investigated the effects of initial inoculum ratios on bacterial community structure using a complex medium and found that the initial inoculum ratio has no significant impact on resultant community structure or on interaction patterns between community members. The microbial population profiles were simulated using computational tools in order to understand intermicrobial relationships and to identify potential metabolic exchanges that occur during stabilization of the bacterial community. Studying microbial community assembly processes is essential for understanding fundamental ecological principles in microbial ecosystems and can be critical in predicting microbial community structure and function.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Towards a High Fidelity Training Environment for Autonomous Cyber Defense Agents

Cyber defenders are overwhelmed by the frequency and scale of attacks against their networks. This problem will only be exacerbated as attackers leverage AI to automate their workflows. Autonomous cyber defense capabilities could aid defenders by automating operations and adapting dynamically to novel threats. However, existing training environments fall short in areas such as generalization, explainability, scalability, and transferability, making it intractable to train agents that will be effective in real networks. In this paper we take an important step towards creating autonomous cyber defense agents — we present a high fidelity training environment called Cyberwheel that includes both simulation and emulation capabilities. Cyberwheel simplifies customization of the training network and easily allows redefining the agent’s reward function, observation space, and action space to support rapid experimentation of novel approaches to agent design. It also provides visibility into agent behaviors necessary for agent evaluation and sufficient documentation / examples to lower the barrier to entry. As an example use case of Cyberwheel, we present initial results training an autonomous agent to deploy cyber deception strategies in simulation.

Oesch, T↗

DOE OSTI2025

CGSim: A Simulation Framework for Large Scale Distributed Computing Environment

Large-scale distributed computing infrastructures such as the Worldwide LHC Computing Grid (WLCG) require comprehensive simulation tools for evaluating performance, testing new algorithms, and optimizing resource allocation strategies. However, existing simulators suffer from limited scalability, hardwired algorithms, lack of real-time monitoring, and inability to generate datasets suitable for modern machine learning approaches. We present CGSim, a simulation framework for large-scale distributed computing environments that addresses these limitations. Built upon the validated SimGrid simulation framework, CGSim provides high-level abstractions for modeling heterogeneous grid environments while maintaining accuracy and scalability. Key features include a modular plugin mechanism for testing custom workflow scheduling and data movement policies, interactive real-time visualization dashboards, and automatic generation of event-level datasets suitable for AI-assisted performance modeling. We demonstrate CGSim’s capabilities through a comprehensive evaluation using production ATLAS PanDA workloads, showing significant calibration accuracy improvements across WLCG computing sites. Scalability experiments show near-linear scaling for multi-site simulations, with distributed workloads achieving 6 × better performance compared to single-site execution. The framework enables researchers to simulate WLCG-scale infrastructures with hundreds of sites and thousands of concurrent jobs within practical time budget constraints on commodity hardware.

Vatsavai, Sairam Sri [Brookhaven National Laborato↗

DOE OSTI2022

LANL Contributions to pyiron: An integrated development environment for computational materials science

To support and accelerate the development of simulation protocols in atomistic modelling, we introduce an integrated development environment (IDE) for computational materials science called pyiron (http://pyiron.org). The pyiron IDE combines a web based source code editor, a job management system for build automation, and a hierarchical data management solution. The core components of the pyiron IDE are pyiron objects based on an abstract class, which links application structures such as atomistic structures, projects, jobs, simulation protocols and computing resources with persistent storage and an interactive user environment. The simulation protocols within the pyiron IDE are constructed using the Python programming language. To highlight key concepts of this tool as well as to demonstrate its ability to simplify the implementation and testing of simulation protocols we discuss two applications. In these examples we show how pyiron supports the whole life cycle of a typical simulation, seamlessly combines ab initio with empirical potential calculations, and how complex feedback loops can be implemented. While originally developed with focus on ab initio thermodynamics simulations, the concepts and implementation of pyiron are general thus allowing to employ it for a wide range of simulation topics.

Janssen, Jan↗

DOE OSTI2025

Software-Defined Data Center Network Architecture using VXLAN-based BGP EVPN for Dynamic Workflows in a Supercomputing Environment (VXLAN-based BGP EVPN Fabric for HPC) v1

This software repository automates the deployment of a multi-vendor VXLAN-based BGP EVPN architecture, leveraging Containerlab to instantiate a stretched CLOS topology. It integrates Linux, Nokia SR Linux, and Arista cEOS, using BGP for underlay, overlay, and topology extension. The software enables rapid prototyping and testing of advanced network configurations. Its key advantage lies in providing a dynamic, programmable environment for research and development of critical technologies supporting dynamic workflows within supercomputing environments, surpassing the limitations of static, vendor-locked alternatives by fostering interoperability and agility.

Kumar, Ronal [Lawrence Berkeley National Laborator↗

DOE OSTI2022

Going mobile to address emerging climate equity needs in the heterogeneous urban environment

We report the Brookhaven National Laboratory Center for Multiscale Applied Sensing (CMAS) aims to address environmental equity needs in the context of a changing climate. As a first step towards this goal, the center developed a one-of-a-kind observatory tailored to the study of highly heterogeneous urban environments. This article describes the features of the mobile observatory that enable its rapid deployment either on or off the power grid, as well as its instrument payload. Beyond its unique design, the observatory optimizes data collection within the obstacle-laden urban environment using a new smart sampling paradigm. This setup facilitated the collection of previously poorly documented environmental properties including wind profiles throughout the atmospheric column. The mobile observatory captured unique observations during its first few intensive observation periods (IOPs).. Vertical air motion and infrared temperature measurements collected along the faces of the supertall One Vanderbilt skyscraper in Manhattan, NY reveal how solar and anthropogenic heating affect wind flow and thus the venting of heat, pollution, and contaminants in urban street canyons. Also, air temperature measurements collected during travel along a 150-km transect between Upton and Manhattan, NY offer a high-resolution view of the urban heat island and reveal that temperature disparities also exist within the city across different neighborhoods. Ultimately, the datasets collected by CMAS are poised to help guide equitable urban planning by highlighting existing disparities and characterizing the impact of urban features on the urban microclimate with the goal of improving human comfort.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Low-Level Liquid-Bearing Clouds Contribute to Seasonal Lower Atmosphere Stability and Surface Energy Forcing over a High-Mountain Watershed Environment

Measurements of atmospheric structure and surface energy budgets distributed along a high-altitude moun tain watershed environment near Crested Butte, Colorado, from two separate, but coordinated, field campaigns, Surface Atmosphere Integrated field Laboratory (SAIL) and Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH), are analyzed. This study identifies similarities and differences in how clouds influence the radiative budget over one snow-free summer season (2022) and two snow-covered seasons (2021/22; 2022/23) for this alpine location. A relationship between lower-tropospheric stability stratification and longwave radiative flux from the presence or absence of clouds is identified. When low clouds persisted, often with signatures of supercooled liquid in win ter, the lower troposphere experienced weaker stability, while radiatively clear skies that are less likely to be influenced by liquid droplets were associated with appreciably stronger lower-tropospheric stratification. Corresponding surface turbu lent heat fluxes partitioned differently based upon the cloud–stability stratification regime derived from early morning radiosounding profiles. Combined with the differences in the radiative budget largely resulting from dramatic seasonal dif ferences in surface albedo, the lower atmosphere stratification, surface energy budget, and near-surface thermodynamics are shown to be modified by the effective longwave radiative forcing of clouds. The diurnal evolution of thermodynamics and surface energy components varied depending on the early morning stratification state. Thus, the importance of quies cent versus synoptically active large-scale meteorology is hypothesized as a critical forcing for cloud properties and associ ated surface energy budget variations. The physical relationships between clouds, radiation, and stratification can provide a useful suite of metrics for process understanding and to evaluate numerical models in such an undersampled, highly com plex terrain environment.

54 ENVIRONMENTAL SCIENCES↗