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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Preserving Tracer Correlations in Moment-Based Atmospheric Transport Models

A linear non-diffusive algorithm for advective transport is developed that greatly improves the detail at which aerosols and clouds can be represented in atmospheric models. Linear advection schemes preserve tracer correlations but the most basic linear scheme is rarely used by atmospheric modelers on account of its excessive numerical diffusion. Higher-order schemes are in widespread use, but these present new problems as nonlinear adjustments are required to avoid occurrences of negative concentrations, spurious oscillations, and other non-physical effects. Generally successful at reducing numerical diffusion during the advection of individual tracers, for example, particle number or mass, the higher-order schemes fail to preserve even the simplest of correlations between interrelated tracers. As a result, important attributes of aerosol and cloud populations including radial moments of particle size distributions, molecular precursors related through chemical equilibria, aerosol mixing state, and distribution of cloud phase are poorly represented. We introduce a new transport scheme, minVAR, that is both non-diffusive and preservative of tracer correlations, thereby combining the best features of the basic and higher-order schemes while enabling new features such as the tracking of sub-grid information at arbitrarily fine scales with high computational efficiency.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Tropical Cyclone Wind Shear-Relative Asymmetry in Reanalyses

Abstract While tropical cyclones (TCs) are axisymmetric vortices to the first order, they often exhibit noteworthy structural asymmetries. These often result from environmental vertical wind shear, which tilts the vortex and induces a wavenumber 1 pattern in the circulation and precipitation fields. Reanalyses and climate models have improved in representing the TC structure and climatology, but their relatively coarse resolution and dependence on parameterized physics cast doubt on their ability to capture the asymmetric TC structure. We perform the most comprehensive process-oriented assessment of TC asymmetry to date in reanalyses. Specifically, we analyze the composite shear-relative TC structure in ERA5 and Climate Forecast System Reanalysis (CFSR), which vary in their resolutions, physical parameterization suites, and data assimilation techniques. These structures are compared with aircraft reconnaissance radar observations. In agreement with the observations, the strongest tangential winds are usually found left-of-shear, while inner core rainfall, ascent, vortex tilt, and low-level inflow are favored directly downshear or in the downshear-left quadrant. Outer rainband convection generally peaks in the downshear-right quadrant. Thermodynamic asymmetries are also apparent, with anomalous low-level moisture right-of-shear, midlevel warmth in the upshear-right quadrant (uptilt), and cloud properties suggestive of a realistic precipitation life cycle from growth to fallout. We also decompose rainfall contributions from the convective parameterization and large-scale cloud schemes and highlight the roles of vorticity advection, buoyancy advection, and diabatic processes in driving asymmetric vertical motions in the inner core and outer rainband regions. Our results suggest that process-level studies of TC asymmetry and TC–wind shear interaction under future warming are viable using climate models. Significance Statement Asymmetries are common in tropical cyclones (TCs), influencing their intensity, track, and hazards. Vertical wind shear often plays a leading-order role in causing these asymmetries. It is uncertain how well asymmetric structures and processes are captured in reanalyses and global climate models (GCMs) with grid spacings of 0.25° and coarser. In this study, we first evaluate TC asymmetry in reanalyses, which have the benefit of being forced by observations. This helps to assess whether the resolutions associated with GCMs sufficiently capture asymmetric structures and processes and motivates upcoming work with free-running GCMs to study how TC asymmetry may change in a warming climate.

Carstens, Jacob D.↗
DOE OSTI2023

A Process Model for ITCZ Narrowing under Warming Highlights Clear-Sky Water Vapor Feedbacks and Gross Moist Stability Changes in AMIP Models

Tropical areas with mean upward motion—and as such the zonal-mean intertropical convergence zone (ITCZ)—are projected to contract under global warming. To understand this process, a simple model based on dry static energy and moisture equations is introduced for zonally symmetric overturning driven by sea surface temperature (SST). Processes governing ascent area fraction and zonal mean precipitation are examined for insight into Atmospheric Model Intercomparison Project (AMIP) simulations. Bulk parameters governing radiative feedbacks and moist static energy transport in the simple model are estimated from the AMIP ensemble. Uniform warming in the simple model produces ascent area contraction and precipitation intensification—similar to observations and climate models. Contributing effects include stronger water vapor radiative feedbacks, weaker cloud-radiative feedbacks, stronger convection-circulation feedbacks, and greater poleward moisture export. The simple model identifies parameters consequential for the inter-AMIP-model spread; an ensemble generated by perturbing parameters governing shortwave water vapor feedbacks and gross moist stability changes under warming tracks inter-AMIP-model variations with a correlation coefficient ~0.46. Here, the simple model also predicts the multimodel mean changes in tropical ascent area and precipitation with reasonable accuracy. Furthermore, the simple model reproduces relationships among ascent area precipitation, ascent strength, and ascent area fraction observed in AMIP models. A substantial portion of the inter-AMIP-model spread is traced to the spread in how moist static energy and vertical velocity profiles change under warming, which in turn impact the gross moist stability in deep convective regions—highlighting the need for observational constraints on these quantities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Exploring ship track spreading rates with a physics-informed Langevin particle parameterization

Abstract. The rate at which aerosols spread from a point source injection, such as from a ship or other stationary pollution source, is critical for accurately representing subgrid plume spreading in a climate model. Such climate model results will guide future decisions regarding the feasibility and application of large-scale intentional marine cloud brightening (MCB). Prior modeling studies have shown that the rate at which ship plumes spread may be strongly dependent on meteorological conditions, such as precipitating versus non-precipitating boundary layers and shear. In this study, we apply a Lagrangian particle model (PM-ABL v1.0), governed by a Langevin stochastic differential equation, to create a simplified framework for predicting the rate of spreading from a ship-injected aerosol plume in sheared, precipitating, and non-precipitating boundary layers. The velocity and position of each stochastic particle is predicted with the acceleration of each particle being driven by the turbulent kinetic energy, dissipation rate, momentum variance, and mean wind. These inputs to the stochastic particle velocity equation are derived from high-fidelity large-eddy simulations (LES) equipped with a prognostic aerosol–cloud microphysics scheme (UW-SAM) to simulate an aerosol injection from a ship into a cloud-topped marine boundary layer. The resulting spreading rate from the reduced-order stochastic model is then compared to the spreading rate in the LES. The stochastic particle velocity representation is shown to reasonably reproduce spreading rates in sheared, precipitating, and non-precipitating cases using domain-averaged turbulent statistics from the LES.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Can ERA5 Be Used to Study Mesoscale Convective System Climatological Characteristics?

Mesoscale convective systems (MCSs) produce more than half of tropical rainfall and are central to the global hydrologic cycle. As the climate warms, environments favorable for MCSs may become more common; however, limited observational records hamper understanding of how MCSs respond to variations and changes in their environments. Here, we evaluate how well MCSs are represented in ERA5, a widely used global high‐resolution reanalysis product. Using PyFLEXTRKR, which jointly tracks top‐of‐atmosphere infrared brightness temperature and surface precipitation, we identified MCSs in ERA5 and compared them with those identified in satellite observations using the same detection algorithm. This comparison analysis spans 2007–2020 using hourly data at 0.25° horizontal resolution focusing over the tropics. ERA5 reproduces observed brightness‐temperature statistics and captures the geographic distribution and seasonal and diurnal cycles of MCS cold cloud shields. However, ERA5 precipitation exhibits an intensity bias—too much light rain and too little heavy rain—which shifts the rain‐rate distribution and reduces the frequency of MCSs relative to observations. Within MCSs, ERA5 precipitation exhibits the same pattern of bias, yielding a systematic underestimation of MCS precipitation intensity. Consistent with these biases, ERA5 underestimates the contribution of MCS to tropical rainfall by 25%–34% in key regions. Overall, ERA5 is suitable for studying MCS cold cloud‐shield climatology and evolution, but precipitation‐based MCS characteristics (including event‐level precipitation features and the geospatial distribution of MCS precipitation) should be interpreted with caution. These findings clarify which aspects of MCS behavior are robustly represented in ERA5 for climatological applications.

mesoscale convection↗
DOE OSTI2024

Characterizing Wet Season Precipitation in the Central Amazon Using a Mesoscale Convective System Tracking Algorithm

To comprehensively characterize convective precipitation in the central Amazon region, we utilize the Python FLEXible object TRacKeR (PyFLEXTRKR) to track mesoscale convective systems (MCSs) observed through satellite measurements and simulated by the Weather Research and Forecasting model at a convection-permitting resolution. This study spans a 2-month period during the wet seasons of 2014 and 2015. We observe a strong correlation between the MCS track density and accumulated precipitation in the Amazon basin. Key factors contributing to precipitation, such as MCS properties (number, size, rainfall intensity, and movement), are thoroughly examined. Our analysis reveals that while the overall model produces fewer MCSs with smaller mean sizes compared to observations, it tends to overpredict total precipitation due to excessive rainfall intensity for heavy rainfall events (≥10 mm hr –1 ). These biases in simulated MCS properties could vary with the constraints on the convective background environment. Moreover, while the wet bias from heavy (convective) rainfall outweighs the dry bias in light (stratiform) rainfall, the latter can be crucial, particularly when MCS cloud cover is significantly underestimated. A case study for 1 April 2014 highlights the influence of environmental conditions on the MCS lifecycle and identifies an unrealistic model representation in both stratiform and convective precipitation features.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Comparative Study of Straight-Strip and Zigzag-Interleaved Anode Patterns for MPGD Readouts

Due to their simplicity and versatility of design, straight strip or rectangular pad anode structures are frequently employed with micro-pattern gas detectors to reconstruct high precision space points for various tracking applications. The particle impact point is typically determined by interpolating the charge collected by several neighboring strips. However, to effectively extract the inherent positional information, the lateral spacing of the straight strips must be comparable to or preferably smaller than the full extent of the incident charge cloud. In contrast, highly interleaved anode patterns, such as zigzags, can adequately sample the incident charge with a pitch appreciably larger than the charge cloud.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

TRACER-Coastal Urban Boundary-Layer Interactions with Convection (TRACER-CUBIC) Field Campaign Report

To better understand the complicated web of processes governing convective cloud life cycle and aerosol-convection interactions, the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) user facility supported deployment of a variety of advanced atmospheric measurement systems to the greater Houston, Texas, area from 1 October 2021 to 30 September 2022 as part of the Tracking Aerosol Convection Interactions Experiment (TRACER). Houston was selected as a study area because isolated convection and a variety of aerosol conditions are common in this region. This one-year ARM Mobile Facility (AMF) deployment featured a four-month intensive operational period (IOP) during summer 2022 (1 June–30 September). The ARM instrumentation was deployed at three sites along an east-west transect from La Porte, Texas to an ancillary site in a less-polluted rural region southwest of downtown Houston (Figure 1). At the La Porte Site, which is located near the Houston ship channel in an area that experiences significant pollution, the first ARM Mobile Facility (AMF1) was deployed. During the IOP, the ARM tethered balloon system (TBS) operated at the ancillary site. The second-generation C-Band Scanning ARM Precipitation Radar (CSAPR) operated near Pearland, Texas, roughly halfway between the Laporte and ancillary sites. As part of the TRACER- Coastal Urban Boundary-Layer Interactions with Convection (CUBIC) project, three boundary-layer profiling systems) were deployed along a north-south transect spanning from the University of Houston Coastal Center to the Aldine site north of downtown Houston (also blue dot in Figure 1) during the TRACER IOP. These systems included the National Oceanic and Atmospheric Administration (NOAA) National Severe Storms Laboratory CLAMPS2 (C2), which was deployed at the UHCC, the University of Wisconsin SPARC, which was deployed at the ARM CSAPR site near Pearland (orange diamond in middle of map in Figure 1), and the University of Oklahoma CLAMPS1 (C1), which was deployed at Aldine. These three systems have been successfully operated in various field campaigns, providing data sets that collectively offer new insights into atmospheric-boundary-layer (ABL) processes, sea-breeze (SB) circulations, and convection initiation (CI). For the TRACER IOP window, these systems ran continuously between 1 June and 26 September, 2022. Due to commitments to NOAA projects, the Doppler lidar at the UHCC site was not available until 24 June 2022. The CLAMPS and SPARC profiling systems are self-contained platforms that have benefited from several years of development and deployment. Instruments and data processing were maintained remotely, which made the 4-month deployment for the TRACER-CUBIC IOP period possible. The same basic instrument configuration comprises each system: a scanning Doppler wind lidar for flow characterization and passive profiler(s) for characterizing planetary-boundary-layer (PBL) thermodynamic properties. Each platform includes a Halo Streamline Doppler wind lidar, an Atmospheric Emitted Radiance Interferometer (AERI), and a surface meteorology station. CLAMPS1 and CLAMPS2 each also include a microwave radiometer (MWR, Figure 1d). The TRACER-CUBIC hypotheses included (i) Interactions of SB and urban circulations and how they affect the PBL structure in the Houston environment, causing spatially (horizontally and vertically) and temporally highly variable flow patterns, (ii) heat, moisture, and aerosol transport and mixing depend on these flow dynamics, and (iii) an improved understanding of the flow patterns and PBL structure are critical for investigating the processes leading to CI. To test these hypotheses, the project aimed at (i) characterizing SB circulations and their impacts on the diurnal evolution of the structure of the ABL, (ii) studying the evolution of Houston’s complex urban boundary layer, and (iii) identifying effects of urban-induced circulations on pre-convective environments. TRACER-CUBIC observations generally provide good coverage during the summer IOP. Initial screening of the data indicates a good number of cases with bay-breeze (BB) and/or SB signatures, local CI, and interesting boundary-layer features such as strong nocturnal low-level jets (LLJs, Table 1). The numbers listed in rows 3-5 in this table will be further updated as part of ongoing in-depth analyses and systematic identification of local circulations and CI events. More detailed information about the data availability and quality for each instrument is provided in the “readme” files that were submitted to the ARM Data Center along with each archived data sets. These “readme” files also provide instrument descriptions, information about the data collection and processing procedures, data formats, and any additional information relevant for further data analysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Refining Processing Engines from SAPHIRE: Initialization of Fault Tree/Event Tree Solver

SAPHIRE has been extensively employed for over 35 years to model risk-important systems and quantify risk models. As a well-established and thoroughly documented Probabilistic Risk Assessment (PRA) tool, SAPHIRE has continuously tracked computational trends and received regular updates. Despite its ongoing evolution, there remains a need for further enhancements, particularly in dealing with the quantification of exceptionally large models. These improvements could take the form of algorithmic advancements, harnessing the power of parallel computing, and exploring the potential benefits of cloud computing solutions. Considering these aspirations, the notion of a remote solve option was introduced and subsequently evolved into a dedicated project within the SAPHIRE development team. A significant outcome of this initiative is SAPHSOLVE, an engine extracted from the SageRisk API designed specifically for remote solving capabilities. The ongoing project is nearing its culmination, marked by a series of discoveries that have brought undocumented aspects to light. Among these revelations is the intricacy of the input and output format for the SAPHSOLVE engine. This document serves the crucial purpose of meticulously delineating the precise formats for both input and output, as they form an indispensable foundation. The importance of documenting these formats cannot be overstated, as it is a pivotal step in facilitating rigorous testing and comparison. Whether it involves scrutinizing SAPHSOLVE results against those of the internal integrated solver or other external solvers, the ability to construct models or transform existing ones into a compatible SAPHSOLVE format is imperative. Chapter 1 offers a succinct introduction to both SAPHIRE and SAPHSOLVE, followed by Chapter 2 which outlines the roadmap for enhancing SAPHSOLVE. The core of this report is Chapter 3, which intricately elucidates the intricacies of the input and output file formats. To provide a tangible illustration of these formats, a rudimentary example has been compiled and is available in Appendix. SAPHSOLVE represents a novel external solving mechanism developed by the SAPHIRE team, although it has not yet reached the full spectrum of capabilities possessed by SAPHIRE's internal solver. However, the SAPHIRE team has set a comprehensive course for incorporating the functionalities of SAPHSOLVE. A comprehensive outlook on the future of SAPHSOLVE is expounded upon in Chapter 4.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Measurements of TRACER pre-convective conditions and mesoscale circulations using small unmanned aircraft systems (sUAS)

Improved comprehension of the physical processes governing convective cloud formation and lifecycle are of critical importance for understanding and predicting future climate states. The influence of these clouds on the planetary energy budget, including on precipitation, is significant. Things are particularly complex in coastal regimes, where gradients in aerosol particle properties, localized circulations such as sea breezes, and large population centers are found. To date, numerical models struggle to accurately represent these critical clouds and are therefore challenged to provide a realistic view on the planetary energy budget. Through the proposed research, we deployed two uncrewed aircraft systems (UAS) equipped with a variety of instruments alongside sensors deployed by the US Department of Energy Atmospheric Radiation Measurement (ARM) program for the TRACER (Tracking Aerosol Convection Interactions Experiment) field campaign. The two small UAS platforms consisted of a CU RAAVEN fixed-wing airplane and an OU CopterSonde system, with the copter collecting frequent vertical profiles of thermodynamic and kinematic variables such as temperature, pressure, wind and humidity. At the same time, the fixed-wing captured horizontal gradients of these quantities and aerosol size distribution. These systems were deployed south of the Houston metro area, in an area that is impacted by the Gulf of Mexico sea breeze on a daily basis. These observations offer enhanced and complementary perspectives to those provided by the DOE ARM Mobile Facility (AMF) which is was deployed in southeast Houston, and an ancillary site in a more rural location west of the urban Houston area. Quality-controlled versions of the UAS data were collected and posted on the DOE ARM data archive after the conclusion of the campaign where they are accessible by the research community and general public. The UAS perspective offers revolutionary insight into key spatial and temporal effects that have not been evaluated previously.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

DELVE-ing into the Jet: A Thin Stellar Stream on a Retrograde Orbit at 30 kpc

We perform a detailed photometric and astrometric analysis of stars in the Jet stream using data from the first data release of the DECam Local Volume Exploration Survey DR1 and Gaia EDR3. We discover that the stream extends over ∼ 29° on the sky (increasing the known length by 18°), which is comparable to the kinematically cold Phoenix, ATLAS, and GD-1 streams. Using blue horizontal branch stars, we resolve a distance gradient along the Jet stream of 0.2 kpc deg$^{−1}$, with distances ranging from D $_{⊙}$ ∼ 27–34 kpc. We use natural splines to simultaneously fit the stream track, width, and intensity to quantitatively characterize density variations in the Jet stream, including a large gap, and identify substructure off the main track of the stream. Furthermore, we report the first measurement of the proper motion of the Jet stream and find that it is well aligned with the stream track, suggesting the stream has likely not been significantly perturbed perpendicular to the line of sight. Finally, we fit the stream with a dynamical model and find that it is on a retrograde orbit, and is well fit by a gravitational potential including the Milky Way and Large Magellanic Cloud. These results indicate the Jet stream is an excellent candidate for future studies with deeper photometry, astrometry, and spectroscopy to study the potential of the Milky Way and probe perturbations from baryonic and dark matter substructure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Cumulonimbus Clouds Convert a Smaller Fraction of CAPE into Kinetic Energy in a Warmer Atmosphere

Abstract This study investigates how entrainment’s diluting effect on cumulonimbus updraft buoyancy is affected by the temperature of the troposphere, which is expected to increase by the end of the century. A parcel model framework is constructed that allows for independent variations in the temperature ( T ), the entrainment rate ε , the free-tropospheric relative humidity (RH), and the convective available potential energy (CAPE). Using this framework, dilution of buoyancy is evaluated with T and RH independently varied and with CAPE either held constant or increased with temperature. When CAPE is held constant, buoyancy decreases as T increases, with parcels in warmer environments realizing substantially smaller fractions of their CAPE as kinetic energy (KE). This occurs because the increased moisture difference between an updraft and its surroundings at warmer temperatures drives greater updraft dilution. Similar results are found in midlatitude and tropical conditions when CAPE is increased with temperature. With the expected 6%–7% increase in CAPE per kelvin of warming, KE only increases at 2%–4% K −1 in narrow updrafts but tracks more closely with CAPE at 4%–6% in wider updrafts. Interestingly, the rate of increase in the KE with T becomes larger than that of CAPE when the later quantity increases at more than 10% K −1 . These findings emphasize the importance of considering entrainment in studies of moist convection’s response to climate change, as the entrainment-driven dilution of buoyancy may partially counteract the influence of increases in CAPE on updraft intensity. Significance Statement Cumulonimbus clouds mix air with their surrounding environment through a process called entrainment, which controls how efficiently environmental energy is converted into upward speed in thunderstorm updrafts. Our research shows that warmer temperatures will exacerbate the moisture difference between cumulonimbus updrafts and their surroundings, leading to greater mixing and less efficient conversion of environmental energy into updraft speeds. This effect should be considered in future research that investigates how climate change will affect cumulonimbus clouds.

Peters, John M.↗
DOE OSTI2022

A Cybersecurity Threat Profile for a Connected Lighting System

In anticipation of improved energy performance and cost savings, cities and building owners are increasingly considering “smart lighting initiatives” that aim to convert their collection of simple luminaires (i.e., lighting fixtures) into an intelligent connected lighting system (CLS) capable of remotely monitoring energy consumption and fault conditions, and possibly implementing adaptive lighting schemes. The U.S. Department of Energy (DOE) has set an national goal of tripling the energy efficiency and demand flexibility of the buildings sector by 2030, relative to 2020 levels 1. It is forecast that connected lighting systems can contribute to that goal by delivering 125 TWh of annual energy savings by 2035 2, equivalent to the annual output of 50 typical (500 MW) power plants. However, these energy savings and the DOE goal are put at significant risk if connected technologies are not adopted due to real or perceived cybersecurity concerns. Connected IoT devices such as these have historically been rife with vulnerabilities which sometimes put security considerations secondary to functionality and operability. What are the cybersecurity threats that will impact these systems, as formerly banal luminaires transition into intelligent connected devices that collect information about themselves, their surrounding environment, and possibly us? In this paper we analyze a threat profile performed on a fault-detection use case for streetlights. A threat profile establishes security requirements, justifies security measures, yields actionable controls, and effectively communicates risk to stakeholders. This effort provides critical information for making threat-based decisions to increase security at a reasonable cost, and can effectively be used by development teams, software architects, and managers to make cybersecurity a part of their ongoing culture of awareness, training, and prevention. This leads to more secure systems and better-understood security. On-premise, cloud, and hybrid architectures with different authentication mechanisms were modeled and later categorized using the Microsoft STRIDE framework. An analysis of the recommended controls for each threat was performed to determine which controls could and should be put in place by manufacturers or third-party suppliers, and which controls need to be left up the end-user to implement. Fifty-seven threats were identified. Among our key findings: (1) 65% (37/57) of the threats did not involve the luminaires, but rather the other components needed to communicate with and manage them; (2) 63% (36/57) of the threats could have been mitigated through manufacturer-implemented defensive techniques or “controls”; and (3) 23% (13/57) of the threats were dependent on the network configuration. Recommendations based on the results of this work are made to key stakeholder groups. Notably, lighting technology developers are advised to address all threats that can be reasonably controlled with baked-in technology solutions (e.g., encryption or authentication controls), and employ some form of secure supply chain management and tracking where other parts (e.g., sensors, microprocessors) of a luminaire must also be built and manufactured with the proper security controls in place. Developers should also review threats involving assets not developed in-house to understand how connectivity with other devices will affect their product during system operation and determine if a compensating control for a defense-in-depth strategy will be needed. Finally, those interested in deploying CLS should compare the differences between cloud and on-premise models to determine which is more suitable for their needs and the abilities of their security team.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

TRACER Radar b1 Data Processing: Corrections, Calibrations, and Processing Report

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility deployed the first ARM Mobile Facility (AMF1) to Houston, Texas for the Tracking Aerosol Convection Interactions Experiment (TRACER) field campaign. The TRACER campaign was conducted from October 1, 2021 to September 30, 2022, with an intensive operational period (IOP) from June 1 to September 30, 2022. To investigate the life cycles of convective cells in the polluted and humid urban environment of Houston, ARM deployed cloud and precipitation radars, including the C-band Scanning ARM Precipitation Radar (CSAPR2), the X/Ka-band Scanning ARM Cloud Radar (SACR), and the Ka-band ARM Zenith cloud Radar (KAZR), as shown in Figure 1. This report presents an analysis of radar data quality, hardware calibrations, and radar data corrections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evaluating Mesoscale Convective Systems Over the US in Conventional and Multiscale Modeling Framework Configurations of E3SMv1

Organized mesoscale convective systems (MCSs) contribute a significant amount of precipitation in the Central and Eastern US during spring and summer, which impacts the availability of freshwater and flooding events. However, current global Earth system models cannot capture MCSs well and misrepresent the statistics of precipitation in the region. In this study, we investigate the representation of MCSs in three configurations of the Energy Exascale Earth System Model (E3SMv1) by tracking individual storms based on outgoing longwave radiation using a new application of TempestExtremes. Our results indicate that conventional parameterizations of convection, implemented in both low (LR; ~150 km) and high (HR; ~25 km) resolution configurations, fail to capture almost all MCS-like events, in-part because they underestimate high-level cloud ice associated with deep convection. On the other hand, the multiscale modeling framework (MMF; cloud-resolving models embedded in each grid-column of ~150 km resolution E3SMv1) configuration represents MCSs and their annual cycle better. Nevertheless, relative to observations, the E3SMv1-MMF spatial distribution of MCSs and associated precipitation is shifted eastward, and the diurnal timing is lagged. A comparison between the large-scale environment in E3SMv1-MMF and ERA5 reanalysis suggests that the biases during the summer in E3SMv1-MMF are associated with biases in low-level humidity and meridional moisture transport within the low-level jet. The fact that conventional parameterizations of convection, even with high-resolution, cannot capture MCSs over the US suggests that methods with explicit representation of kilometer-scale convective organization, such as the MMF, may be necessary for improving the simulation of these convective systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Collaborative Proposal: Improving understanding of the internal structure and dynamics of deep convection using ARM observations and large eddy simulations

Recent observational and large eddy simulation (LES) modeling studies have nearly unanimously supported the view of deep cumulus convection being composed of a series of quasi-spherical bubbles of buoyant air, known as moist thermals. Despite the prevalence of moist thermals in deep convection, a comprehensive theory for the dynamics of these structures is lacking. Most current conceptual models for cumulus convection are based on canonical scaling theories for dry thermals or plumes; however, there is considerable evidence that the behavior of moist thermals differs markedly from these theories. Furthermore, the theoretical basis for most cumulus parameterizations originates from the plume conceptual model, and therefore these parameterizations are inconsistent with the real structure of moist convection. Motivated by the aforementioned knowledge gaps, this “end-to-end” research effort use theory, observations, numerical simulations, and direct improvements to the Zhang-McFarlane (ZM) convection scheme in the global climate Community Atmosphere Model (CAM) to address the following research questions: What key environmental parameters determine whether or not shallow convection will transition into deep convection, in the context of thermal-like updrafts? What factors regulate the size of thermals within cumulus updrafts? How does vertical wind shear influence thermal behavior, and as a consequence, vertical velocity and mass flux profiles and the shallow-to-deep convective transition? What are the critical processes that determine updraft vertical velocities and their connection to the vertical mass flux profile for thermal-like updrafts? Idealized LES modeling will be used in conjunction with theoretical models for the core properties of thermal-like updrafts to better understand key processes that regulate thermal ascent rates and entrainment properties. Thermal-tracking procedures will be used to characterize the behavior of thermals within the LES, and recently developed direct measures of entrainment and detrainment will be used to quantify entrainment/detrainment rates. Building from these results, we will analyze the structure of moist thermals from hemispheric range-height indicator scans taken during the Atmospheric Radiation Measurement Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign, and from “real case” LES of CACTI events. This combined modeling and observational analysis will provide essential validation for the existing body of research on moist thermal dynamics, which is based primarily on modeling studies. With the insight gained from the aforementioned activities, we will modify the Zhang-McFarlane convection scheme to improve its representation of updraft vertical velocity and entrainment rate profiles. These process-level changes will be tested in the Community Atmosphere Model to assess the impact on global climate simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Simulating Hurricane Katrina in the Simple Cloud‐Resolving E3SM Atmosphere Model v1

Climate models are important tools for advancing understanding and prediction of tropical cyclones (TCs). Traditional global climate models, however, do not have the ability to properly simulate TC intensity due to their coarse horizontal resolution. Regional models can be run at convection‐permitting resolutions, but these models are often strongly influenced by the data used in the lateral boundary forcing, and domain choice can have a large impact on the simulation. Cloud‐resolving global climate models have demonstrated great potential for realism in TC simulations, and in this study we focus specifically on the Simple Cloud‐Resolving Energy Exascale Earth System Model (E3SM) Atmosphere Model (SCREAM) v1 configuration. We evaluate SCREAMv1 against the observational record and the Weather Research and Forecasting (WRF) model run at a convection‐permitting resolution with Hurricane Katrina as our case study. We found that both models produced realistic simulations of Hurricane Katrina. SCREAMv1 demonstrated skill in simulating TC track, size, and intensity, while the model produced an excessive amount of precipitation. In comparison, WRF more accurately simulated TC precipitation and intensity, although the TC wind extent was smaller than the observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Quantifying the Solar Energy Resource for Puerto Rico

After Hurricane Maria, multiple U.S. Department of Energy laboratories studied the state of the electric grid in Puerto Rico and analyzed grid resilience and grid integration of renewable energy. As part of the work done at the National Renewable Energy Laboratory, researchers created new solar resource data, conducted a technical potential and supply curve analysis, and studied the interannual variability of the solar resource. A new methodology was developed to downscale solar resource data from the National Solar Radiation Data Base (NSRDB) from a 4-km x 4-km spatial and 30-minute temporal resolution to a 2 km x 2 km and 5-minute resolution. This methodology primarily used simple physical principles to develop high-resolution cloud properties which were then used to compute solar radiation. The high-resolution datasets were validated against ground measurements and the error metrics were found to be similar to the original lower resolution dataset. Using 20 years of downscaled data from the NSRDB multi-year capacity factors for photovoltaics (PV) were developed for both single-axis tracking and fixed latitude-tilt configurations. Use of the multi-year data provides the ability to understand variability in capacity factors due to variability in weather over a long period of time. For Puerto Rico the coastal regions were found to have significant higher capacity factors than inland. Using land-use and terrain information a technical potential analysis was conducted for Puerto Rico. This analysis restricted single PV plant development to a maximum of 100 MW nameplate capacity. The nameplate capacity for each municipality were then determined. Based on our assumptions, 56 of the 78 total municipalities of Puerto Rico contain some level of solar capacity. Most of the interior municipalities did not have any capacity because of the geographic exclusions used in this study. The lowest capacity for a PV plant observed in a municipality was 10 MW. The maximum capacity within a county was 2,000 MW. Further a supply curve analysis was conducted by taking the results of the technical potential and quantifying system and transmission costs. The levelized cost of energy (LCOE) was calculated for each theoretical PV plant site, and the levelized cost of transmission was added to the LCOE to produce a total cost estimate for each site. The results of the supply curve analysis allow for a relative comparison of the cost for integrating new PV capacity into the grid. This analysis indicates that cheaper total LCOE sites tend to be larger in capacity. The total capacity in this study was found to be far beyond the maximum peak load for the island. However, this study does not consider the economic and market potential for development. The cumulative capacity presented in this study assumes that the best locations are developed first and ignores the complex decision paths for new power plant development. Therefore, this analysis can only be treated as illustrative. Finally this study investigates the impact of inter-annual variability of resource using a variety of metrices including probability of exceedance and variation in capacity factor and LCOE. This study demonstrates that the capacity factor or LCOE could vary by over 10% year to year. This clearly indicates the risks involved in using any particular year of data and clearly points to the use of multi-year data to reduce some of the risks related to variability in weather.

14 SOLAR ENERGY↗