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DOE OSTI2025

Simulations of the fault current limiting operation of a long-length REBCO CORC ® superconducting cable cooled by helium gas

Conductor-on-round-core (CORC®) cables composed of rare-earth-barium-copper-oxide high-temperature superconducting (HTS) tapes are of great interest for power transmission applications due to their many advantages such as high power density, light weight, and low loss. Closed circulation loops of cryogenic helium gas can be used to cool HTS cables down to low temperatures to significantly improve their current-carrying capacity. Coupled circuit-electromagnetic-thermal finite element simulations implemented in the COMSOL Multiphysics package were developed, validated, and then used for simulating the fault current limiting (FCL) performance and the cooling processes of an 8-layer CORC® cable cooled with a flow of cryogenic helium gas. In the simulations, the temperature dependence of the electrical and thermal properties of all component materials is implemented for improved accuracy. To overcome computational challenges caused by the considerable difference in geometrical scales (i.e. few-µm-thick HTS layers versus 10 m-long HTS cable), the model is divided into two separate simulations. The first simulation is performed on the transverse cross-section of the cable to calculate the electric field, heating power and temperature rise in each component of a CORC® cable during FCL operation. The heating power calculated in the first simulation is transferred to the second model to simulate the cooling of a 10 m-long cable after the fault is cleared. The effect of the helium gas flow rate on the cooling process is also investigated to develop strategic approaches for optimizing cooling systems for HTS cables with FCL capability. The simulations indicated that a 40 ms fault with a voltage drop of 20 V m −1 along the cable can result in a temperature increase from 60 K to about 165 K inside the cable, and it takes about 500 s to cool the cable back to nearly 60 K with a flow of cold helium gas at a rate of 5 g s −1 .

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Numerical modeling of pedestal stability and broadband turbulence of wide-pedestal QH-mode plasmas on DIII-D

The wide-pedestal quiescent high confinement mode discovered on DIII-D in recent years is a stationary and quiescent H-mode (QH-mode) with the pedestal width exceeding EPED prediction by at least 25%. Its characteristics, such as low rotation, high energy confinement and edge localized mode-free operation, make it an attractive operation mode for future reactors. Linear and nonlinear simulations using BOUT++ reduced two fluid MHD models and awere carried out to investigate the bursty broadband turbulence often observed in the edge of wide-pedestal QH-mode plasmas. Two kinds of MHD-scale instabilities in different spatial locations within the pedestal were found in the simulations: one mild peeling–ballooning (PB) mode γ PB < 0.04ω A ) located near the minimum in E r</:sub> well propagating in ion diamagnetic drift direction; and one drift-Alfvén wave locates at smaller radius compared to E r</:sub> well propagating in the electron diamagnetic drift direction and unstable only when the parallel electron dynamics is included in the simulation. The coupling between drift wave and shear Alfvén wave provides a possible cause of the experimentally observed local profile flattening in the upper-pedestal. The rotation direction, mode location, as well as the wavenumber of these two modes from BOUT++ simulations agree reasonably well with the experimental measurements, while the lack of quantitative agreement is likely due to the lack of trapped electron physics in current fluid model. This work presents improved physics understanding of the pedestal stability and turbulence dynamics for wide-pedestal QH-mode.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Watch and learn—a generalized approach for transferrable learning in deep neural networks via physical principles

Transfer learning refers to the use of knowledge gained while solving a machine learning task and applying it to the solution of a closely related problem. Such an approach has enabled scientific breakthroughs in computer vision and natural language processing where the weights learned in state-of-the-art models can be used to initialize models for other tasks which dramatically improve their performance and save computational time. Here we demonstrate an unsupervised learning approach augmented with basic physical principles that achieves fully transferrable learning for problems in statistical physics across different physical regimes. By coupling a sequence model based on a recurrent neural network to an extensive deep neural network, we are able to learn the equilibrium probability distributions and inter-particle interaction models of classical statistical mechanical systems. Our approach, distribution-consistent learning, DCL, is a general strategy that works for a variety of canonical statistical mechanical models (Ising and Potts) as well as disordered interaction potentials. Using data collected from a single set of observation conditions, DCL successfully extrapolates across all temperatures, thermodynamic phases, and can be applied to different length-scales. This constitutes a fully transferrable physics-based learning in a generalizable approach.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Torrefaction of almond shell as a renewable reinforcing agent for plastics: techno-economic analyses and comparison to bioethanol process

Abstract In 2016, the US state of California alone produced nearly 3.5 billion kilograms of almonds, accounting for approximately 84% of the world’s almond production. This generated about 2.58 million metric tons (MTs) of almond residues. Almond shells are currently either burned to generate power or disposed of in landfill. Valorizing almond shells and hulls provides an opportunity to replace petroleum-derived products and divert organic material from landfill. Here we demonstrate a detailed techno-economic analysis (TEA) of an almond shell torrefaction process capable of utilizing the 520 000 MTs of almond shells produced annually in California. Our process also includes preprocessing the torrefied biomass to exploit it as a reinforcing agent for plastics. We further compared the revenue generated from the torrefied biomass and bioethanol derived from the same quantity of almond shells. We considered three different torrefaction facility scales to evaluate trade-offs between economies of scale at the facility and trucking costs to deliver almond shells. A facility that takes in 200 000 MT yr –1 of almond shells results in lower per-unit-output basis capital and operating cost relative to other smaller-scale torrefaction facilities, including 10 000 MT yr –1 and 50 000 MT yr –1 , considered for analysis in this study. The large-sale facility results in a minimum selling price (MSP) of the torrefied biomass of $311.4 MT –1 . An analogous TEA on converting almond residues into bioethanol is also investigated. The MSP of almond shell derived ethanol ($1.71 kg −1 ) is higher than that of corn ($0.48 kg −1 ) or cellulosic biomass ($0.88 kg −1 ) derived ethanol. Compared with the bioethanol route, the torrefied almond shells result in three times more revenue if utilized as a reinforcing agent for plastics.

Liu, Dupeng (ORCID:0000000269514064)↗

DOE OSTI2023

Planting a Lyman alpha forest on ABACUSSUMMIT

The full-shape correlations of the Lyman alpha (Ly$α$) forest contain a wealth of cosmological information through the Alcock Paczynski effect. However, these measurements are challenging to model without robustly testing and verifying the theoretical framework used for analyzing them. Here, we leverage the accuracy and volume of the $N$-body simulation suite ABACUSSUMMIT to generate high-resolution Ly$α$ skewers and quasi-stellar object (QSO) catalogs. One of the main goals of our mocks is to aid in the full-shape Ly$α$ analysis planned by the Dark Energy Spectroscopic Instrument (DESI) team. We provide optical depth skewers for six of the fiducial cosmology base-resolution simulations ($L$ box = 2 $h$ -1 Gpc, $N$ = 6912 3 ) at $z$ = 2.5. We adopt a simple recipe based on the Fluctuating Gunn-Peterson Approximation (FGPA) for constructing these skewers from the matter density in an $N$-body simulation and calibrate it against the 1D and 3D Ly$α$ power spectra extracted from the hydrodynamical simulation IllustrisTNG (TNG; $L$ box = 205 $h$ -1 Mpc, $N$ = 2500 3 ). As an important application, we study the non-linear broadening of the baryon acoustic oscillation (BAO) peak and show the cross-correlation between DESI-like QSOs and our Ly$α$ forest skewers. We find differences on small scales between the Kaiser approximation prediction and our mock measurements of the Ly$α$×QSO cross-correlation, which would be important to account for in upcoming analyses. The ABACUSSUMMIT Ly$α$ forest mocks open up the possibility for improved modelling of cross correlations between Ly$α$ and cosmic microwave background (CMB) lensing and Ly$α$ and QSOs, and for forecasts of the 3-point Ly$α$ correlation function. Furthermore, our catalogues and skewers are publicly available on Globus via the National Energy Research Scientific Computing Center (NERSC) (full link under Data Availability).

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Ageing and quenching through the Ageing Diagram – II. Physical characterization of galaxies

The connection between quenching mechanisms, which rapidly turn star-forming systems into quiescent, and the properties of the galaxy population remains difficult to discern. In this work we investigate the physical properties of MaNGA and SAMI galaxies at different stages of their star formation history. Specifically, we compare galaxies with signatures of recent quenching (Quenched) – Hα in absorption and low D n (4000) – with the rest of the low star-forming and active population (Retired and Ageing, respectively). The analysis is performed in terms of characteristics such as the total stellar mass, half-light radius, velocity-to-dispersion ratio, metallicity, and environment. We find that the Ageing population comprises a heterogeneous mixture of galaxies, preferentially late-type systems, with diverse physical properties. Retired galaxies, formerly Ageing or Quenched systems, are dominated by early-type high-mass galaxies found both at low and dense environments. Most importantly, we find that recently quenched galaxies are consistent with a population of compact low-mass satellite systems, with higher metallicities than their Ageing analogues. We argue that this is compatible with being quenched after undergoing a star-burst phase induced by environmental processes (e.g. ram pressure). However, we also detect a non-negligible fraction of field central galaxies likely quenched by internal processes. This study highlights that, in order to constrain the mechanisms driving galaxy evolution, it is crucial to distinguish between old (Retired) and recently quenched galaxies, thus requiring at least two estimates of the specific star formation rate over different time-scales.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Agora : Multicomponent simulation for cross-survey science

ABSTRACT Next-generation cosmological surveys will observe large portions of the sky, with significant overlap between them. Multi-wavelength observations will enable us to analyse the same large-scale structure from different angles using a variety of tracers and astrophysical effects. The complex interplay between these observables calls for a model that can accurately and coherently describe their collective behaviour, posing a challenge that can only be met through the use of simulations. In this work, a suite of simulated extragalactic skies is presented, including maps and/or catalogues of cosmic microwave background (CMB) lensing, thermal and kinetic Sunyaev–Zel’dovich (tSZ/kSZ) effects, cosmic infrared background (CIB), radio sources, galaxy overdensity and galaxy weak lensing. Each of these probes is implemented in the lightcone using halo catalogues and/or particles from the Multidark-Planck2 ($\small {MDPL2}$) N-body simulation, and the modelling is calibrated using hydrodynamic simulations and publicly available data. The auto and cross-spectra of the individual probes, as well as the cross-spectra between the observables, are shown to be consistent with theoretical models and measurements from data. The simulation is shown to have a wide range of applications, including forecasting, pipeline testing, and evaluating astrophysical biases in cross-correlation measurements. It is further demonstrated that the simulation products produced in this work have sufficient accuracy to recover the input cosmology when subjected to a full cosmological analysis and are ready for application in real-world analyses for ongoing and future surveys. The simulation products presented in this work can be accessed at: https://yomori.github.io/agora/index.html.

Astronomy & Astrophysics↗

DOE OSTI2024

Dark energy survey year 3 results: cosmology from galaxy clustering and galaxy–galaxy lensing in harmonic space

We present the joint tomographic analysis of galaxy-galaxy lensing and galaxy clustering in harmonic space (HS), using galaxy catalogues from the first three years of observations by the Dark Energy Survey (DES Y3). We utilize the redMaGiC and MagLim catalogues as lens galaxies and the metacalibration catalogue as source galaxies. The measurements of angular power spectra are performed using the pseudo-$C_\ell$ method, and our theoretical modelling follows the fiducial analyses performed by DES Y3 in configuration space, accounting for galaxy bias, intrinsic alignments, magnification bias, shear magnification bias and photometric redshift uncertainties. We explore different approaches for scale cuts based on non-linear galaxy bias and baryonic effects contamination. Our fiducial covariance matrix is computed analytically, accounting for mask geometry in the Gaussian term, and including non-Gaussian contributions and super-sample covariance terms. To validate our HS pipelines and covariance matrix, we used a suite of 1800 log-normal simulations. We also perform a series of stress tests to gauge the robustness of our HS analysis. In the $\Lambda$CDM model, the clustering amplitude $S_8 =\sigma _8(\Omega _m/0.3)^{0.5}$ is constrained to $S_8 = 0.704\pm 0.029$ and $S_8 = 0.753\pm 0.024$ (68 per cent C.L.) for the redMaGiC and MagLim catalogues, respectively. For the wCDM, the dark energy equation of state is constrained to $w = -1.28 \pm 0.29$ and $w = -1.26^{+0.34}_{-0.27}$, for redMaGiC and MagLim catalogues, respectively. These results are compatible with the corresponding DES Y3 results in configuration space and pave the way for HS analyses using the DES Y6 data.

(cosmology:) cosmological parameters↗

DOE OSTI2026

Measurement of 𝐷 0 Meson Photoproduction in Ultraperipheral Heavy Ion Collisions

This Letter reports the first measurement of photonuclear 𝐷 0 meson production in ultraperipheral heavy ion collisions. The study is performed using lead-lead collision data, with an integrated luminosity of 1.34 nb −1 , collected by the CMS experiment at a nucleon-nucleon center-of-mass energy of 5.36 TeV. Photonuclear events, where one of the colliding nuclei breaks up and the other remains intact, are selected based on breakup neutron emissions and by requiring no particle activity in a large rapidity interval in the direction of the photon-emitting nucleus. The 𝐷 0 mesons are reconstructed via the 𝐷 0 → 𝐾 −⁢ 𝜋 + decay channel, with the cross section measured as a function of 𝐷 0 meson transverse momentum and rapidity. The results are compared with next-to-leading-order perturbative QCD calculations that employ recent parametrizations of the lead nuclear parton distribution functions, as well as with predictions based on the color glass condensate framework. This measurement is the first photonuclear collision study characterizing parton distribution functions of lead nuclei for parton fractional momenta 𝑥 (relative to the nucleon) ranging approximately from a few 10 −4 to 10 −2 for different hard energy scale 𝑄 2 selections.

charm quark↗

DOE OSTI2023

Entropy and Seebeck signals meet on the edges

Here, we explore the electronic entropy per particle s and Seebeck coefficient S in zigzag graphene ribbons. Pristine and edge-doped ribbons are considered using tight-binding models to inspect the role of edge states in the observed thermal transport properties. As a band gap opens when the ribbons are doped at one or both edges, due to asymmetric edge potentials, we find that s and S signals are closely related to each other: both develop sharp dip-peak line shapes as the chemical potential lies in the gap, while the ratio s/S exhibits a near-constant value equal to the elementary charge e at low temperatures. This constant ratio suggests that S can be seen as the transport differential entropy per charge, as suggested by some authors. Our calculations also indicate that measurement of s and S may be useful as a spectroscopic probe of different electronic energy scales involved in such quantities in gapped materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Bipartite mutual information in classical many-body dynamics

Information theoretic measures have helped to sharpen our understanding of many-body quantum states. As perhaps the most well-known example, the entanglement entropy (or more generally, the bipartite mutual information) has become a powerful tool for characterizing the dynamical growth of quantum correlations. By contrast, although computable, the bipartite mutual information (MI) is almost never explored in classical many particle systems; this owes in part to the fact that computing the MI requires keeping track of the evolution of the full probability distribution, a feat which is rarely done (or thought to be needed) in classical many-body simulations. Here, we utilize the MI to analyze the spreading of information in 1D elementary cellular automata (CA). Broadly speaking, we find that the behavior of the MI in these dynamical systems exhibits a few different types of scaling that roughly correspond to known CA universality classes. Of particular note is that we observe a set of automata for which the MI converges parametrically slowly to its thermodynamic value. We develop a microscopic understanding of this behavior by analyzing a two-species model of annihilating particles moving in opposite directions. Furthermore, our work suggests the possibility that information theoretic tools such as the MI might enable a more fine-grained characterization of classical many-body states and dynamics.

Cellular automata↗

DOE OSTI2022

Mapping the Universe in hydrogen deuteride

Hydrogen deuteride (HD) is prevalent in a wide variety of astrophysical environments, and measuring its large-scale distribution at different epochs can, in principle, provide information about the properties of these environments. In this paper we explore the prospects for accessing this distribution using line-intensity mapping of emission from the lowest rotational transition in HD, focusing on observations of the epoch of reionization (z~6–10) and earlier. We find the signal from the epoch of reionization to be most promising, through cross correlations within existing [CII] intensity mapping surveys. While the signal we predict is out of reach for current-generation projects, planned future improvements should be able to detect reionization-era HD without any additional observations, and would help to constrain the properties of the star-forming galaxies thought to play a key role in reionization. We also investigate several avenues for measuring HD during “cosmic dawn” (z~10–30), a period in which HD could provide one of the only complementary observables to 21 cm intensity maps. We conclude that existing and planned facilities are poorly matched to the specifications desirable for a significant detection, though such a measurement may be achievable with sustained future effort. Finally, we explain why HD intensity mapping of the intergalactic medium during the cosmic dark ages (z≳30) appears to be out of reach of any conceivable experiment.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Reconstructing the spatial structure of quantum correlations in materials

Quantum correlations are a fundamental property of quantum many-body states. Yet they remain experimentally elusive, hindering certification of genuine quantum behavior, especially in quantum materials. Here we show that the momentum-dependent dynamical susceptibility measured via inelastic neutron scattering enables the systematic reconstruction of a general family of quantum correlation functions, which express the degree of quantum coherence in the fluctuations of two spins at an arbitrary mutual distance. Using neutron scattering data for the compound KCuF 3 —a system of weakly coupled S = 1 / 2 Heisenberg chains—and numerically exact quantum Monte Carlo data, we show that quantum correlations possess a radically different spatial structure with respect to conventional correlations. Indeed, they exhibit a different emergent length scale—the quantum coherence length—which is finite at any finite temperature (including when long-range magnetic order develops). Moreover, we show theoretically that coupled Heisenberg spin chains exhibit a form of quantum monogamy, with a trade-off between quantum correlations along and transverse to the spin chains. These results highlight real-space quantum correlators as an informative, model-independent means of probing the underlying quantum state of real quantum materials. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗

DOE OSTI2026

Feasibility of Correlation-Aware Inference and Universal Precision Scaling in Bonse–Hart Ultra-Small-Angle Neutron Scattering

Bonse–Hart ultra-small-angle neutron scattering (USANS) provides access to micrometre-scale structure, but useful measurements often require long counting times. In this work, we test whether the expected smoothness of the scattering profile can be exploited to improve data quality at lower counting statistics. We apply a Gaussian-process-based method to Bonse–Hart USANS data and evaluate its performance on pseudo-measurements generated from high-statistics experiments under Poisson statistics. This provides a stringent test of how well the underlying I(Q) profile can be reconstructed when the available counts are substantially reduced. We further show that, in the counting-limited regime, the reconstruction error follows a universal scaling behaviour that differs from the usual independent-counting expectation. At higher counts, the improvement crosses over to a resolution-limited regime set by analyser-angle discretization and rocking-curve width. These results clarify when correlation-aware inference is useful in USANS and provide a practical basis for improving measurement efficiency and beam-time usage.

Tung, Chi-Huan [ORNL] (ORCID:0000000221972074)↗

DOE OSTI2024

Coherency-Aware Learning Control of Inverter-Dominated Grids: A Distributed Risk-Constrained Approach

Here, this letter investigates the importance of integrating the coherency knowledge for designing controllers to dampen sustained oscillations in wide-area power networks with significant penetration of inverter-interfaced resources. Coherency is a fundamental property of power systems, where time-scale separation in frequency dynamics leads to clustered behavior among generators of different groups. Large-scale penetration of inverter-driven low inertia resources replacing conventional synchronous generators (SGs) can lead to perturbation in the coherent partitioning; hence, integrating such information is of utmost importance for oscillation control designs. We present the coherency-aware design of a distributed output feedback-based reinforcement learning method that additionally incorporates risk constraints to capture the uncertainties related to net-load fluctuations. The use of domain-aware coherency information has produced improved training and oscillation performance than the coherency-agnostic control design, hence proving to be effective in controller design. Finally, we validated the proposed method with numerical experiments on the benchmark IEEE 68-bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Filling gaps in our understanding of belowground plant traits across the world: an introduction to a Virtual Issue

The belowground world is one of the final frontiers in terrestrial ecology. The tangling of plant roots with the surrounding soil below is a lifeline for the humble forbs and towering trees above, and roots play a key role in shaping ecosystem carbon, water and nutrient cycling (Bardgett et al., 2014). Ecologists have long sought to better understand the ecosystem-scale consequences of differing plant strategies, above- and belowground, by relating plant characteristics, or traits, to plant function (Grime, 1977; Pregitzer, 2002). While developing trait–function linkages is arguably more difficult for plant traits that are hidden belowground, root and rhizosphere ecologists continue to fan out across grasslands and forests with their shovels, isotopes, and specialized cameras, seeking a better understanding of the secret lives of roots. Over the years, New Phytologist has served as a virtual town square for scientists to discuss their hard-won observations on the interplay among belowground plant traits, microbial activity, and edaphic and environmental conditions from biomes around the world (Norby & Jackson, 2000; Pregitzer, 2002; Matamala & Stover, 2013; Norby & Iversen, 2017). In this Editorial we highlight the newest papers that update and add to our understanding of the role of root and rhizosphere traits in broader ecosystem processes. We focused on papers published in New Phytologist between 1 January 2019 and 31 December 2020 and extended this window to papers still in ‘early view’ up to the time of writing. Because of the overwhelming number of papers, we did not include those with a decidedly genomic focus or that served primarily as data syntheses, reviews, insights or commentaries.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Lagrangian and Eulerian Supersaturation Statistics in Turbulent Cloudy Rayleigh–Bénard Convection: Applications for LES Subgrid Modeling

Abstract Turbulent fluctuations of scalar and velocity fields are critical for cloud microphysical processes, e.g., droplet activation and size distribution evolution, and can therefore influence cloud radiative forcing and precipitation formation. Lagrangian and Eulerian water vapor, temperature, and supersaturation statistics are investigated in direct numerical simulations (DNS) of turbulent Rayleigh–Bénard convection in the Pi Convection Cloud Chamber to provide a foundation for parameterizing subgrid-scale fluctuations in atmospheric models. A subgrid model for water vapor and temperature variances and covariance and supersaturation variance is proposed, valid for both clear and cloudy conditions. Evaluation of phase change contributions through an a priori test using DNS data shows good performance of the model. Supersaturation is a nonlinear function of temperature and water vapor, and relative external fluxes of water vapor and heat (e.g., during entrainment-mixing and phase change) influence turbulent supersaturation fluctuations. Although supersaturation has autocorrelation and structure functions similar to the independent scalars (temperature and water vapor), the autocorrelation time scale of supersaturation differs. Relative scalar fluxes in DNS without cloud make supersaturation PDFs less skewed than the adiabatic case, where they are highly negatively skewed. However, droplet condensation changes the PDF shape response: it becomes positively skewed for the adiabatic case and negatively skewed when the sidewall relative fluxes are large. Condensation also increases correlations between water vapor and temperature in the presence of relative scalar fluxes but decreases correlations for the adiabatic case. These changes in correlation suppress supersaturation variability for the nonadiabatic cases and increase it for the adiabatic case. Implications of this work for subgrid microphysics modeling using a Lagrangian stochastic scheme are also discussed.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Assimilation of a Coordinated Fleet of Uncrewed Aircraft System Observations in Complex Terrain: Observing System Experiments

Uncrewed aircraft system (UAS) observations from the Lower Atmospheric Profiling Studies at Elevation–A Remotely-Piloted Aircraft Team Experiment (LAPSE-RATE) field campaign were assimilated into a high-resolution configuration of the Weather Research and Forecasting (WRF) Model. The impact of assimilating targeted UAS observations in addition to surface observations was compared to that obtained when assimilating surface observations alone using observing system experiments (OSEs) for a terrain-driven flow case and a convection initiation (CI) case observed within Colorado’s San Luis Valley (SLV). The assimilation of UAS observations in addition to surface observations results in a clear increase in skill for both flow regimes over that obtained when assimilating surface observations alone. For the terrain-driven flow case, the UAS observations improved the representation of thermal stratification across the northern SLV, which produced stronger upvalley flow over the eastern half of the SLV that better matched the observations. For the CI case, the UAS observations improved the representation of the pre-convective environment by reducing dry biases across the SLV and over the surrounding terrain. This led to earlier CI and more organized convection over the foothills that spilled outflows into the SLV, ultimately helping to increase low-level convergence and CI there. In addition, the importance of UAS capturing an outflow that originated over the Sangre de Cristo Mountains and triggered CI is discussed. These outflows and subsequent CI were not well captured in the simulation that assimilated surface observations alone. We report that observations obtained with a fleet of UAS are shown to notably improve high-resolution analyses and short-term predictions of two very different mesogamma-scale weather events.

54 ENVIRONMENTAL SCIENCES↗