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At least 181 records · Page 10

The field of human building interaction for convergent research and innovation for intelligent built environments

Human-Building Interaction (HBI) is a convergent field that represents the growing complexities of the dynamic interplay between human experience and intelligence within built environments. This paper provides core definitions, research dimensions, and an overall vision for the future of HBI as developed through consensus among 25 interdisciplinary experts in a series of facilitated workshops. Three primary areas contribute to and require attention in HBI research: humans (human experiences, performance, and well-being), buildings (building design and operations), and technologies (sensing, inference, and awareness). Three critical interdisciplinary research domains intersect these areas: control systems and decision making, trust and collaboration, and modeling and simulation. Finally, at the core, it is vital for HBI research to center on and support equity, privacy, and sustainability. Compelling research questions are posed for each primary area, research domain, and core principle. State-of-the-art methods used in HBI studies are discussed, and examples of original research are offered to illustrate opportunities for the advancement of HBI research.

42 ENGINEERING↗

Ship-based Observations and Climate Model Simulations of Cloud Phase over the Southern Ocean

The Southern Ocean (SO) clouds exert a significant influence on the Earth’s radiation budget. Here we analyzed ship-based remote sensing observations of SO clouds over a five-month long DOE ARM Measurements of Aerosols, Radiation and Clouds over the Southern Oceans (MARCUS) field campaign to better understand cloud phase variability. We developed a method to classify eight categories of hydrometeors (ice, liquid, mixed phase, rain, drizzle, snow, aerosols, and clear sky) based on measurements of lidar, radar and radiosondes. Cloud thermodynamic phases (liquid, ice and mixed phase) at coarser scales were further derived to compare with the DOE Energy Exascale Earth System Model version 1 (E3SMv1) simulation and the Earth Model Column Collaboratory (EMC 2 ) instrument simulator. For a scale-aware comparison with climate model simulations, we found that spatially averaging the raw remote sensing data (e.g., backscatter, reflectivity) results in increased cloud cover and cloud liquid, whereas, directly averaging cloud phase from higher to lower resolution maintains clear air regions and is thus recommended for in-cloud frequency comparisons. For cloud thermodynamic phases in stratiform clouds, the E3SM underestimates cloud ice and overestimates cloud liquid at temperatures between -40 and 0°C. When latitudes increase, both observations and simulations show a transition of dominant phase from liquid to ice for cloud tops as well as for the entire cloud columns, but the model underestimation of ice phase is more severe at higher latitudes. Such model bias is unlikely caused by spatial scale differences or lack of heterogeneity in cloud vertical structure in the simulation.

54 ENVIRONMENTAL SCIENCES↗

Advancing Tassel Detection and Counting: Annotation and Algorithms

Tassel counts provide valuable information related to flowering and yield prediction in maize, but are expensive and time-consuming to acquire via traditional manual approaches. High-resolution RGB imagery acquired by unmanned aerial vehicles (UAVs), coupled with advanced machine learning approaches, including deep learning (DL), provides a new capability for monitoring flowering. In this article, three state-of-the-art DL techniques, CenterNet based on point annotation, task-aware spatial disentanglement (TSD), and detecting objects with recursive feature pyramids and switchable atrous convolution (DetectoRS) based on bounding box annotation, are modified to improve their performance for this application and evaluated for tassel detection relative to Tasselnetv2+. The dataset for the experiments is comprised of RGB images of maize tassels from plant breeding experiments, which vary in size, complexity, and overlap. Results show that the point annotations are more accurate and simpler to acquire than the bounding boxes, and bounding box-based approaches are more sensitive to the size of the bounding boxes and background than point-based approaches. Overall, CenterNet has high accuracy in comparison to the other techniques, but DetectoRS can better detect early-stage tassels. The results for these experiments were more robust than Tasselnetv2+, which is sensitive to the number of tassels in the image.

54 ENVIRONMENTAL SCIENCES↗

Integrated Methane Monitoring Platform Extension, Volume I: Final Technical Report

The IMMPE project, DE-FE0032284, was to enhance methane monitoring technologies and their applications across various natural gas asset classes. The scope included deploying advanced methane detection and monitoring technologies to identify and mitigate fugitive methane emissions, measuring emission rates, and assessing impacts. The findings included the successful mitigation of identified emissions and quantification of emission rates. A key outcome was the development of a comprehensive template and summary of recommendations for methane emissions monitoring, which is replicable for both upstream and downstream applications. Furthermore, the project emphasized the importance of education by providing training opportunities for technicians and regulators, thereby fostering awareness and promoting the adoption of cost-effective methane emissions monitoring and management techniques.

02 PETROLEUM↗

SCCOUT: Surveying for Categorization and Control of Organism in Unwelcome Territory

Advancements in the fields of science, technology, and medicine have contributed largely to the growth of society over the last century. Thanks to these discoveries, all corners of the planet are connected both digitally and physically. Progress in the field of medicine has led to people living longer, fuller lives and a general increase in global population. Awareness of our world’s changing climate and the effects that has on local and global ecosystems has spurred great efforts to protect the environment. These discoveries along with many others have helped our world grow in a myriad of ways; however, certain efforts in agriculture, natural resource management, and ecosystem management have not scaled to accommodate this growth. Increasing prevalence and ease of dissemination of invasive plants and animals, diseases, and changing ecological conditions pose significant challenges to biodiversity, ecosystem health, and agricultural productivity. Moreover, as the world population grows, there are more people to feed and less viable farmland to produce food for them. Despite the increasing prevalence of these issues, methods for addressing and tracking them have stayed relatively the same for at least the last several decades.

54 ENVIRONMENTAL SCIENCES↗

Quantifying the Resolution Sensitivity of the Kain–Fritsch Scheme Across the Gray Zone by Isolating Interactions: A TWP‐ICE Case Study

The resolution sensitivity of the Kain–Fritsch (KF) convection scheme and the role of interactions between the physics and dynamics within the gray zone (<10 km) were investigated using the Separate Physics and Dynamics Experiment (SPADE) framework. Two groups of experiments were conducted using the Weather Research and Forecasting (WRF) model via traditional (Tradition) runs and SPADE runs with resolutions of 1, 2, 4, and 8 km during the wet period of the Tropical Warm Pool–International Cloud Experiment (TWP‐ICE). Results show that the KF scheme simulates the weakened convective processes well as the resolution increases in both groups, and the changes in the convective variables with resolution in SPADE are smaller than in the Tradition group. This indicates the important effects of interactions between model components on convection parameterizations as the resolution changes. Additionally, the microphysics variables remain nearly unchanged with resolution in SPADE and weaken slightly in Tradition as the resolution decreases, suggesting the relatively weaker influences of model interactions for the resolved‐cloud parameterization. Therefore, the scale‐aware behavior of KF scheme is further strengthened in Tradition runs, primarily through inhibiting the strength of stratiform processes through physics–dynamics interactions and physical components.

54 ENVIRONMENTAL SCIENCES↗

“Which Projections Do I Use?” Strategies for Climate Model Ensemble Subset Selection Based on Regional Stakeholder Needs

Climate model (or earth system model) projections are increasingly used for climate adaptation planning and impact assessments. As part of this process, many end‐users evaluate a subset of downscaled climate projections without being aware of the implications of downscaling methodology for statistics or event outcomes. Approaches for determining a subset of global climate models to use often focus on values from the raw models, rather than from their downscaled counterparts, in other words assuming that the statistical distribution of the multi‐model ensemble does not change post downscaling. This study demonstrates that a downscaled ensemble will typically retain the change distribution as a raw ensemble, but individual models can differ dramatically post‐downscaling. We recommend that subset‐selection methods account for this possibility and that decision‐relevant downscaled climate projections provide proper descriptions of fitness‐for‐purpose and essential caveats, so that non‐specialists can interpret the results with an appropriate level of confidence.

54 ENVIRONMENTAL SCIENCES↗

Primary and secondary ice production: interactions and their relative importance

A discrepancy of up to 5 orders of magnitude between ice crystal and ice nucleating particle (INP) number concentrations was found in the measurements, indicating the potentially important role of secondary ice production (SIP) in the clouds. However, the interactions between primary and SIP processes and their relative importance remain unexplored. In this study, we implemented five different ice nucleation schemes as well as physical representations of SIP processes (i.e., droplet shattering during rain freezing, ice-ice collisional break-up, and rime splintering) in the Community Earth System Model version 2 (CESM2). We ran CESM2 in the single column mode for model comparisons with the DOE Atmospheric Radiation Measurement (ARM) Mixed-Phase Arctic Cloud Experiment (M-PACE) observations. We found that the model experiments with aerosol-aware ice nucleation schemes and SIP processes yield the best simulation results for the M-PACE single-layer mixed-phase clouds. We further investigated the relative importance of ice nucleation and SIP to ice number and cloud phase as well as interactions between ice nucleation and SIP in the M-PACE single-layer mixed-phase clouds. Our results show that SIP contributes 80 % to the total ice formation and transforms ~30 % of pure liquid-phase clouds simulated in the model experiments without considering SIP into mixed-phase clouds. The SIP is not only a result of ice crystals produced from ice nucleation, but also competes with the ice nucleation by reducing the number concentrations of cloud droplets and cloud-borne dust INPs. Conversely, strong ice nucleation also suppresses SIP by glaciating mixed-phase clouds and thereby reducing the amount of precipitation particles (rain and graupel).

54 ENVIRONMENTAL SCIENCES↗

From legacy contamination to watershed systems science: a review of scientific insights and technologies developed through DOE-supported research in water and energy security

Abstract Water resources, including groundwater and prominent rivers worldwide, are under duress because of excessive contaminant and nutrient loads. To help mitigate this problem, the United States Department of Energy (DOE) has supported research since the late 1980s to improve our fundamental knowledge of processes that could be used to help clean up challenging subsurface problems. Problems of interest have included subsurface radioactive waste, heavy metals, and metalloids (e.g. uranium, mercury, arsenic). Research efforts have provided insights into detailed groundwater biogeochemical process coupling and the resulting geochemical exports of metals and nutrients to surrounding environments. Recently, an increased focus has been placed on constraining the exchanges and fates of carbon and nitrogen within and across bedrock to canopy compartments of a watershed and in river–floodplain settings, because of their important role in driving biogeochemical interactions with contaminants and the potential of increased fluxes under changing precipitation regimes, including extreme events. While reviewing the extensive research that has been conducted at DOE’s representative sites and testbeds (such as the Oyster Site in Virginia, Savannah River Site in South Carolina, Oak Ridge Reservation in Tennessee, Hanford in Washington, Nevada National Security Site in Nevada, Riverton in Wyoming, and Rifle and East River in Colorado), this review paper explores the nature and distribution of contaminants in the surface and shallow subsurface (i.e. the critical zone) and their interactions with carbon and nitrogen dynamics. We also describe state-of-the-art, scale-aware characterization approaches and models developed to predict contaminant fate and transport. The models take advantage of DOE leadership-class high-performance computers and are beginning to incorporate artificial intelligence approaches to tackle the extreme diversity of hydro-biogeochemical processes and measurements. Recognizing that the insights and capability developments are potentially transferable to many other sites, we also explore the scientific implications of these advances and recommend future research directions.

54 ENVIRONMENTAL SCIENCES↗

IDAES-PSE 2.1.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost, most environmentally sustainable solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.1.0 Release Highlights New IDAES Examples Repository Starting with this release, the IDAES examples are developed in the new IDAES/examples repository. Along with many content and usability improvements, the most significant changes are: To install the examples, after installing IDAES, run pip install idaes-examples The idaes get-examples command, previously used for this, has been removed The HTML version is now available at https://idaes-examples.readthedocs.io The previous URL, https://idaes.github.io/examples-pse, will not be updated and may be removed at some point in the future For more details, refer to the resources available at IDAES/examples. Removal of Non-Functional Apps A review of the code in the idaes/apps and idaes/models_extra folders was undertaken, and a number of tools were identified as being outdated or non-functional and no longer supported by their development teams. Due to this, the following tools have been removed: idaes/apps/alamopy_depr (note that the new ALAMOpy interface remains avaialble in idaes/core/surrogates) idaes/apps/helmet idaes/apps/ripe idaes/apps/roundingRegression idaes/models_extra/carbon_capture Pyomo 6.6 This version of IDAES is the first requiring Pyomo 6.6. This version of Pyomo contains multiple internal improvements and refactorings. While for the majority of cases this should have positive or no impact on solvability of IDAES models, we are aware of a small number of models that have been affected as a result of these changes. For more information, refer to the Pyomo 6.6.1 release notes. Other highlights Model Initialization A prototype API for a new approach to initializing IDAES models is now available which makes available some new techniques for initializing models. This is documented in the Initializing Models Reference Guide Modular Properties Framework Support for some transport properties Helmholtz Equation of State properties Better error checking for case where unit models are set to include phase equilibrium but the property package is set to support only a single phase Multi-Stream Contactor model: a new base model for systems involving contacting of two or more streams with mass transfer. This model is intended to be used as the foundation for models such as membrane separators, solvent extraction and other similar processes. This is documented in the Multi-Stream Contactor Reference Guide idaes/models_extra/power_generation report() methods for unit models using Helmholtz equation of state General Code Maintenance Streamlining of dependencies and creation of new optional dependency groupings to support non-core tools General linting of codebase to ensure compliance with most pylint checks Spell checking of all code and doc strings Removal of backward compatibility code for Python 2

IDAES↗

Multi-scale impacts of climate change on hydropower for long-term water-energy planning in the contiguous United States

Climate change impacts on watersheds can potentially exacerbate water scarcity issues where water serves multiple purposes including hydropower. The long-term management of water and energy resources is still mostly approached in a siloed manner at different basins or watersheds, failing to consider the potential impacts that may concurrently affect many regions at once. There is a need for a large-scale hydropower modeling framework that can examine climate impacts across adjoining river basins and balancing authorities (BAs) and provide a periodic assessment at regional to national scales. Expanding from our prior assessment only for the United States (US) federal hydropower plants, we enhance and extend two regional hydropower models to cover over 85% of the total hydropower nameplate capacity and present the first contiguous US-wide assessment of future hydropower production under Coupled Model Intercomparison Project phase 6’s high-end Shared Socioeconomic Pathway 5-8.5 emission scenario using an uncertainty-aware multi-model ensemble approach. We present regional hydropower projections, using both BA regions and US Hydrologic Subregions (HUC4s), to consistently inform the energy and water communities for two future periods—the near-term (2020–2039) and the mid-term (2040–2059) relative to a historical baseline period (1980–2019). We find that the median projected changes in annual hydropower generation are typically positive—approximately 5% in the near-term, and 10% in the mid-term. However, since the risk of regional droughts is also projected to increase, future planning cannot overly rely on the ensemble median, as the potential of severe hydropower reductions could be overlooked. The assessment offers an ensemble of future hydropower generation projections, providing regional utilities and power system operators with consistent data to develop drought scenarios, design long duration storage and evaluate energy infrastructure reliability under intensified inter-annual and seasonal variability.

13 HYDRO ENERGY↗

Broadband and filter radiometers at Ross Island, Antarctica: detection of cloud ice phase versus liquid water influences on shortwave and longwave radiation

Abstract. Surface radiometer data from Ross Island, Antarctica, collected during the austral summer 2015–2016 by the US Department of Energy Atmospheric Radiation Measurement (ARM) program West Antarctic Radiation Experiment (AWARE), are used to evaluate how shortwave and longwave irradiance respond to changing cloud properties as governed by contrasting meteorological regimes. Shortwave atmospheric transmittance is derived from pyranometer measurements, and cloud conservative-scattering optical depth is derived from filter radiometer measurements at 870 nm. With onshore flow associated with marine air masses, clouds contain mostly liquid water. With southerly flow over the Transantarctic Mountains, orographic forcing induces substantial cloud ice water content. These ice and mixed-phase clouds attenuate more surface shortwave irradiance than the maritime-influenced clouds and also emit less longwave irradiance due to colder cloud base temperature. These detected irradiance changes are in a range that can mean onset or inhibition of surface melt over ice shelves. This study demonstrates how basic and relatively low-cost broadband and filter radiometers can be used to detect subtle climatological influences of contrasting cloud microphysical properties at very remote locations.

54 ENVIRONMENTAL SCIENCES↗

When energy doesn’t add up: use of an energyshed framework in assessing progress towards renewable energy transitions

Global progress in energy transitions to support climate mitigation goals has been slower than anticipated; this has prompted shifts away from traditional paradigms of regulated energy ownership towards a model of energy democratization by local communities and individuals. For example, in the United States, local communities in over 250 cities, counties, and states have made pledges to reach 100% renewable electrification by target dates ranging from 2020 to 2050. However, the availability of infrastructure and the competition for renewable energy resources, as well as lack of awareness of these limitations, present significant barriers to overcome. In this study, we explored a subset of 31 of these cities to assess their current electricity generation and how much further they have to go to meet their goals. Through an energyshed framework, we estimated powerplant electricity allocation to each city assuming competition for power from various renewable and non-renewable resource types, as well as look at the ‘best case scenario’ assuming 100% allocation of renewable-sourced electricity for a handful of cities in order to understand the existing and planned energy mixes for 2021 and the following 20 years. It is likely most cities will meet 10% of their energy demand with renewable energy, with best cases scenarios reaching between 35% and 65% renewable penetration, within the next 20–30 years. This highlights the need for infrastructural development in the energy sector, as well as intentional planning efforts in order to make these energy goals a reality.

54 ENVIRONMENTAL SCIENCES↗

Climate-Relevant Gas Absorption Properties from AWARE and Other ARM Spectral Measurements (Final Report)

The objective of this project has been to use measurements from the Atmospheric Emitted Radiance Interferometer (AERI) deployed at ARM sites to improve our knowledge of uncertain infrared spectroscopic parameters of importance to climate, remote sensing, and data assimilation. A primary focus has been the water vapor continuum in the infrared atmospheric window. Radiation codes used to predict climate and weather base their representation of the water vapor continuum in this window on the MT_CKD model, but in this spectral region the MT_CKD water vapor continuum absorption coefficients were derived almost two decades ago by an analysis of AERI measurements for conditions with a limited range of precipitable water vapor (PWV) and temperature values, leading to uncertainty in the derived coefficients. This project has included a new, comprehensive analysis of all aspects of the water vapor continuum in the atmospheric window -- the self continuum, the foreign continuum, and the self continuum temperature dependence, all resolved spectrally. Having a wide range of PWV amounts and temperatures from deployments of the ARM Mobile Facility for GoAmazon as well as the more than a decade of AERI measurements at SGP has provided an appropriate foundation for such a comprehensive analysis.

54 ENVIRONMENTAL SCIENCES↗

Real-time kinematic (RTK) Drone-collected Data and Processed Models of Port Arthur Coastal Neighborhood and Pleasure Island Golf Course, June 2024

The Southeast Texas Urban Integrated field lab’s Co-design team captured aerial photos in the Port Arthur Coastal Neighborhood Community and the Golf Course on Pleasure Island, Texas, in June 2024. Aerial photos taken were through autonomous flight, and models were processed through the DroneDeploy engine. All aerial photos are in .JPG format and contained in zipped files for each area. The processed data package includes 3D models, geospatial data, mappings, and point clouds. Please be aware that DTM, Elevation toolbox, Point Cloud, and Orthomosaic use EPSG: 6588. And 3D Model uses EPSG: 3857.For using these data:- The Adobe Suite gives you great software to open .Tif files.- You can use LASUtility (Windows), ESRI ArcGIS Pro (Windows), or Blaze3D (Windows, Linux) to open a LAS file and view the data it contains.- Open an .OBJ file with a large number of free and commercial applications. Some examples include Microsoft 3D Builder, Apple Preview, Blender, and Autodesk.- You may use ArcGIS, Merkaartor, Blender (with the Google Earth Importer plug-in), Global Mapper, and Marble to open .KML files.- The .tfw world file is a text file used to georeference the GeoTIFF raster images, like the orthomosaic and the DSM. You need suitable software like ArcView to open a .TFW file.This dataset provides researchers with sufficient geometric data and the status quo of the land surface at the locations mentioned above. This dataset will support researchers' decision-making processes under uncertainties.

2D mapping↗

Aerial Data and Processed Models of Port Arthur Coastal Neighborhood and Pleasure Island Golf Course, June 2024

Our Co-design team is from the University of Texas, working on a Department of Energy-funded project focused on the Beaumont-Port Arthur area. As part of this project, we will be developing climate-resilient design solutions for areas of the region. More on www.caee.utexas.edu.We captured aerial photos in the Port Arthur Coastal Neighborhood Community and the Golf Course on Pleasure Island, Texas, in June 2024.Aerial photos taken were through DroneDeploy autonomous flight, and models were processed through the DroneDeploy engine as well. All aerial photos are in .JPG format and contained in zipped files for each area.The processed data package includes 3D models, geospatial data, mappings, and point clouds. Please be aware that DTM, Elevation toolbox, Point cloud, and Orthomosaic use EPSG: 6588. And 3D Model uses EPSG: 3857.For using these data:- The Adobe Suite gives you great software to open .Tif files.- You can use LASUtility (Windows), ESRI ArcGIS Pro (Windows), or Blaze3D (Windows, Linux) to open a LAS file and view the data it contains.- Open an .OBJ file with a large number of free and commercial applications. Some examples include Microsoft 3D Builder, Apple Preview, Blender, and Autodesk.- You may use ArcGIS, Merkaartor, Blender (with the Google Earth Importer plug-in), Global Mapper, and Marble to open .KML files.- The .tfw world file is a text file used to georeference the GeoTIFF raster images, like the orthomosaic and the DSM. You need suitable software like ArcView to open a .TFW file.This dataset provides researchers with sufficient geometric data and the status quo of the land surface at the locations mentioned above. This dataset could streamline researchers' decision-making processes and enhance the design as well.

2D mapping↗

Joint Analysis of the Epidemic Evolution and Human Mobility During the First Wave of COVID-19 in Spain: Retrospective Study

Background The initial wave of the COVID-19 pandemic placed a tremendous strain on health care systems worldwide. To mitigate the spread of the virus, many countries implemented stringent nonpharmaceutical interventions (NPIs), which significantly altered human behavior both before and after their enactment. Despite these efforts, a precise assessment of the impact and efficacy of these NPIs, as well as the extent of human behavioral changes, remained elusive. Objective In this study, we conducted a retrospective analysis of the initial wave of COVID-19 in Spain to better comprehend the influence of NPIs and their interaction with human behavior. Such investigations are vital for devising future mitigation strategies to combat COVID-19 and enhance epidemic preparedness more broadly. Methods We used a combination of national and regional retrospective analyses of pandemic incidence alongside large-scale mobility data to assess the impact and timing of government-implemented NPIs in combating COVID-19. Additionally, we compared these findings with a model-based inference of hospitalizations and fatalities. This model-based approach enabled us to construct counterfactual scenarios that gauged the consequences of delayed initiation of epidemic response measures. Results Our analysis demonstrated that the pre–national lockdown epidemic response, encompassing regional measures and heightened individual awareness, significantly contributed to reducing the disease burden in Spain. The mobility data indicated that people adjusted their behavior in response to the regional epidemiological situation before the nationwide lockdown was implemented. Counterfactual scenarios suggested that without this early epidemic response, there would have been an estimated 45,400 (95% CI 37,400-58,000) fatalities and 182,600 (95% CI 150,400-233,800) hospitalizations compared to the reported figures of 27,800 fatalities and 107,600 hospitalizations, respectively. Conclusions Our findings underscore the significance of self-implemented prevention measures by the population and regional NPIs before the national lockdown in Spain. The study also emphasizes the necessity for prompt and precise data quantification prior to enacting enforced measures. This highlights the critical interplay between NPIs, epidemic progression, and human behavior. This interdependence presents a challenge in predicting the impact of NPIs before they are implemented.

Public, Environmental & Occupational Health↗

Assessing Physical Relationships Between Atmospheric State, Fluxes, and Boundary Layer Stability at McMurdo Station, Antarctica

Observations at McMurdo Station, Antarctica from 24 November 2015 through 3 January 2017 were used to characterize the physical relationships between boundary layer stability and atmospheric state and fluxes. The basis of this analysis was self-organizing maps (SOMs), a neural network algorithm, used to identify the range of potential temperature profiles present in the twice-daily radiosonde data during the ARM (Atmospheric Radiation Measurement) West Antarctic Radiation Experiment (AWARE) campaign. The SOM identified profiles ranging from strongly stable to weakly stable regimes over the lowest 500 m of the atmosphere. It was found that in the winter (MJJA), moderate and strongly stable regimes occur most frequently (61%), while weakly stable regimes dominate in the summer (DJ, 83.4%). The mechanisms responsible for the dominance of different stability regimes in each season were analyzed to determine why these regimes occur with varying frequency throughout the year. This analysis found that wind speed variations and radiative cooling are responsible for the stability observed in the winter, radiative warming, as well as weaker wind speeds, are responsible for summer weak stability, and stability variations in the transition seasons (FMA, SON) are characterized by a change in sign of net radiation with increasing stability, as wind speed changes little across stability regimes. Low-level jets were observed to occur about 50% of the time below areas of enhanced stability aloft and were observed most frequently in the transition seasons. The boundary layer depth, as determined by the Bulk Richardson number, was found to decrease with increasing stability.

54 ENVIRONMENTAL SCIENCES↗