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At least 829 records · Page 46

CO2ROpt (Feedstock Allocation Optimization Model) [SWR-22-13]

Reducing greenhouse gas emissions remains a critical challenge for the transportation and chemical sectors. The electrochemical reduction of carbon dioxide is a potential pathway for production of fuels and chemicals that uses atmospheric carbon dioxide as a feedstock. Here we present an analysis of the potential for carbon dioxide captured from point sources and via direct air capture to be utilized in electrochemical reduction under different market scenarios. Using a numerical optimization framework and national data sets, scenarios for nationwide production of ethylene, formate, and carbon monoxide are evaluated at scales comparable to current production of these molecules in the United States. We show that developing a network for production of these products at scale requires capture and utilization of significant portions of the carbon dioxide that is currently emitted from large stationary point sources. Because carbon dioxide point sources are spatially and compositionally variable, their use for carbon dioxide reduction depends on electricity prices, capture cost, and location. If the power sector in the United States is decarbonized, carbon dioxide supply decreases significantly, increasing the importance of utilizing other carbon dioxide streams, and increasing the likelihood that direct air capture plays a role in supplying carbon dioxide feedstocks. These findings provide a first insight into the feedstock and energy constraints for carbon dioxide reduction.

Badgett, Alex↗

LTAU-FF: Loss Trajectory Analysis for Uncertainty in atomistic Force Fields

LTAU (Loss Trajectory Analysis for Uncertainty) is a technique for estimating the uncertainty in a model's predictions for any regression task by approximating the cumulative distribution function (CDF) of the model's errors over the course of training. The approximated CDF, combined with a similarity search algorithm in the model's descriptor space, can then be used to estimate the likelihood that the model's predictions on any given test point will fall below a chosen threshold. LTAU-FF (LTAU in atomistic Force Fields) is the application of LTAU specifically for use with atomistic force fields.

Vita, JoshuaA↗

Simulation-Based Inference for Neutrino Interaction Model Tuning

This project demonstrates, for the first time, the application of simulation-based inference (SBI) techniques to tune neutrino–nucleus interaction models. Using a mock dataset based on the MicroBooNE tuning of the GENIE event generator, our approach employs a Neural Posterior Estimator (NPE) with Masked Autoregressive Flows (MAF) to infer the posterior distributions of key GENIE parameters directly from simulated histograms. The workflow provides a scalable and amortized framework for performing likelihood-free inference in high-dimensional parameter spaces, offering a pathway to more efficient and uncertainty-aware model tuning for next-generation neutrino experiments such as DUNE and SBND.

Tame-Narvaez, KarlaMaria [Fermi National Accelerat↗

MTRE

Multi-Token Reliability Estimation (MTRE) is a lightweight, white-box hallucination detector for vision-language models. Instead of using only the first output token, MTRE aggregates logits from the first ~10 tokens and feeds them to a small attention-based reliability head; per-token scores are combined via a sequential log-likelihood-ratio test with early-stopping, and an MTRE-t variant calibrates thresholds via cross-fitting. MTRE reports average gains of +9.4% Accuracy and +14.8% AUROC over common baselines across MAD-Bench, MM-SafetyBench, MathVista, and arithmetic/counting tasks, while adding ~4.3M params and ~1% inference overhead (~26 MB VRAM, ~0.94 ms per detection). Key limitation: requires access to early token logits and is evaluated on a handful of open-source 7B VLMs.

Bhattarai, Manish [Los Alamos National Labs]↗

Molecular phylogenetic analysis of the Paguristes tortugae Schmitt, 1933 complex and selected other Paguroidea (Crustacea: Decapoda: Anomura)

Morphological characters, as presently applied to describe members of the Paguristes tortugae Schmitt, 1933 species complex, appear to be of limited value in inferring phylogenetic relationships within the genus, and may have similarly misinformed understanding of relationships between members of this complex and those presently assigned to the related genera Areopaguristes Rahayu & McLaughlin, 2010 and Pseudopaguristes McLaughlin, 2002. Previously undocumented observations of similarities and differences in color patterns among populations additionally suggest genetic divergences within some species, or alternatively seem to support phylogenetic groupings of some species. In the present study, a Maximum Likelihood (ML) phylogenetic analysis was undertaken based on the H3, 12S mtDNA, and 16S mtDNA sequences of 148 individuals, primarily representatives of paguroid species from the western Atlantic. This molecular analysis supported a polyphyletic Diogenidae Ortmann, 1892, although incomplete taxonomic sampling among the genera of Diogenidae limits the utility of this finding for resolving family level relationships. Several hypotheses regarding the evolutionary relationships among hermit crab genera were refuted by the Kishino-Hasegawa (KH). ShimodairaHasegawa (SH) and Approximately Unbiased (AU) tree topology tests, among them the hypothesis that Areopaguristes is monophyletic. A lack of support for the monophyly of Areopaguristes calls into question the phylogenetic validity of gill number for the differentiation of Paguristes, Areopaguristes, and Pseudopaguristes. The study was inconclusive with regard to the relationships among these three genera, but previously unknown diversity within both Paguristes and Areopaguristes was demonstrated. Existence of an undescribed species confounded under the name Paguristes tortugae Schmitt, 1933 was supported by genetics, morphology, and coloration. A second undescribed species with remarkable similarity to Areopaguristes hummi Wass, 1955 was discovered based on genetics and coloration.

12S↗

Variability in Wind Energy Generation across the Contiguous United States

ERA5 provides high-resolution, high-quality hourly wind speeds at 100 m and is a unique resource for quantifying temporal variability in likely wind-derived power production across the United States. Gross capacity factors (CF) in seven independent system operators (ISOs) are estimated using the location and rated power of each wind turbine, a simplified power curve, and ERA5 output from 1979 to 2018. Excluding the California ISO, the marginal probability of a calm (zero power production) is less than 0.1 in any ERA5 grid cell. When a calm occurs, the mean co-occurrence across wind-turbine-containing grid cells ranges from 0.38 to 0.39 for ISOs in the Midwest and central plains [Midcontinent (or Midwest) ISO (MISO), Southwest Power Pool (SPP), and the Electric Reliability Council of Texas (ERCOT) region], increasing to 0.54–0.58 for ISOs in the eastern United States [Pennsylvania–New Jersey–Maryland interconnection (PJM), New York ISO (NYISO), and New England ISO (NEISO)]. Periods with low gross CF have a median duration of ≤6 h, except in California, and are most likely during summer. Additionally, gross CF exhibit highest variance at periods of 1 day in ERCOT and SPP; on synoptic scales in MISO, NEISO, and NYISO; and on interannual time scales in PJM. This implies differences in optimal strategies for ensuring resilience of supply. Theoretical scenarios show adding wind energy capacity near existing wind farms is advantageous even in areas with high existing installed capacity (IC), while expanding into areas with lower IC is more beneficial to reducing ramps and the probability of gross CF falling below 20%. These results emphasize the benefits of large balancing areas and aggregation in reducing wind power variability and the likelihood of wind droughts.

17 WIND ENERGY↗

The Response of the Polar Vortex to Tropospheric Temperature Eddies in an Idealized General Circulation Model

Abstract A dry-core idealized general circulation model with a stratospheric polar vortex in the Northern Hemisphere is run with a combination of simplified topography and imposed tropospheric temperature perturbations, each located in the Northern Hemisphere with a zonal wavenumber of 1. The phase difference between the imposed temperature wave and the topography is varied to understand what effect this has on the occurrence of polar vortex displacements. Geometric moments are used to identify the centroid of the polar vortex for the purposes of classifying whether or not the polar vortex is displaced. Displacements of the polar vortex are a response to increased tropospheric wave activity. Compared to a model run with only topography, the likelihood of the polar vortex being displaced increases when the warm region is located west of the topography peak, and decreases when the cold region is west of the topography peak. This response from the polar vortex is due to the modulation of vertically propagating wave activity by the temperature forcing. When the southerly winds on the western side of the topographically forced anticyclone are collocated with warm- or cold-temperature forcing, the vertical wave activity flux in the troposphere becomes more positive or negative, respectively. This is in line with recent reanalysis studies that showed that anomalous warming west of the surface pressure high, in the climatological standing wave, precedes polar vortex disturbances.

54 ENVIRONMENTAL SCIENCES↗

The Influence of Shallow Cloud Populations on Transitions to Deep Convection in the Amazon

Abstract In this study, a pair of convection-permitting (2-km grid spacing), month-long, wet-season Weather Research and Forecasting (WRF) Model simulations with and without the eddy-diffusivity mass-flux (EDMF) scheme are performed for a portion of the Green Ocean Amazon (GoAmazon) 2014/15 field campaign period. EDMF produces an ensemble of subgrid-scale convective plumes that evolve in response to the boundary layer meteorological conditions and can develop into shallow clouds. The objective of this study is to determine how different treatments of shallow cumulus clouds (i.e., with and without EDMF) impact the total cloud population and precipitation across the Amazonian rain forest, with emphasis on impacts on the likelihood of shallow-to-deep convection transitions. Results indicate that the large-scale synoptic conditions in the EDMF and control simulations are nearly identical; however, on the local scale their rainfall patterns diverge drastically and the biases decrease in EDMF. The EDMF scheme significantly increases the frequency of shallow clouds, but the frequencies of deep clouds are similar between the simulations. Deep convective clouds are tracked using a cloud-tracking algorithm to examine the impact of shallow cumulus on the surrounding ambient environment where deep convective clouds initiate. Results suggest that a rapid increase of low-level cloudiness acts to cool and moisten the low to midtroposphere during the day, favoring the transition to deep convection.

54 ENVIRONMENTAL SCIENCES↗

Environmental Conditions Affecting Global Mesoscale Convective System Occurrence

Abstract The ERA5 environments of mesoscale convective systems (MCSs), tracked from satellite observations, are assessed over a 20-yr period. The use of a large set of MCS tracks allows us to robustly test the sensitivity of the results to factors such as region, latitude, and diurnal cycle. We aim to provide novel information on environments of observed MCSs for assessments of global atmospheric models and to improve their ability to simulate MCSs. Statistical analysis of all tracked MCSs is performed in two complementary ways. First, we investigate the environments when an MCS has occurred at different spatial scales before and after MCS formation. Several environmental variables are found to show marked changes before MCS initiation, particularly over land. The vertically integrated moisture flux convergence shows a robust signal across different regions and when considering MCS initiation diurnal cycle. We also found spatial scale dependence of the environments between 200 and 500 km, providing new evidence of a natural length scale for use with MCS parameterization. In the second analysis, the likelihood of MCS occurrence for given environmental conditions is evaluated, by considering all environments and determining the probability of being in an MCS core or shield region. These are compared to analogous non-MCS environments, allowing discrimination between conditions suitable for MCS and non-MCS occurrence. Three environmental variables are found to be useful predictors of MCS occurrence: total column water vapor, midlevel relative humidity, and total column moisture flux convergence. Such relations could be used as trigger conditions for the parameterization of MCSs, thereby strengthening the dependence of the MCS scheme on the environment. Significance Statement Large storm systems called mesoscale convective systems form across Earth. These are collections of thunderstorms, with associated high-level clouds that produce substantial, lighter rainfall and modulate Earth’s energy balance. They produce hazardous weather conditions, such as floods and high winds, and are responsible for a high percentage of rainfall in many regions globally. We investigate the environmental conditions under which they form, so that we can understand the spatial extent of the environment which is important for their formation, and also where and when the effects of these storms might be felt. The novel information generated here should help improve the representation of these storms in weather and climate models, improving the prediction of rainfall, thunderclouds, and high-level clouds.

54 ENVIRONMENTAL SCIENCES↗

The Role of Subcloud Mesoscale Convergence in Sculpting Convective Updraft Width and Depth

The initiation of deep moist convection is governed in part by the horizontal width of updrafts near cloud base, which limits the deleterious effects of entrainment-driven dilution on buoyant thermals ascending through the free troposphere. However, the factors controlling cloud-base updraft width, which in turn dictates cloud depth, are not well understood. We track the evolving three-dimensional structure of the mesoscale subcloud forcing for vertical motion and near-cloud thermodynamic ingredients within a high-resolution ensemble of simulations of seven realistic daytime orographic convection initiation events to determine their relative roles in controlling cloud width and depth. Statistical analysis of approximately 5000 cloudy updraft samples indicates that the most important contributors to the width of cloudy updrafts across the ensemble are the depth and magnitude of the subcloud mesoscale ascent. However, the depth achieved by clouds is more consistently predicted by the near-cloud ambient relative humidity within the lower to middle free troposphere and convective available potential energy. Therefore, although the width of cloudy updrafts may be partly set at low levels by the mesoscale vertical mass and moisture flux, the likelihood of deep moist convection is governed by the generation of positive buoyancy within cumulus thermals and entrainment-driven dilution that reduces it. The persistence of the low-level mesoscale vertical forcing locally consolidates and vertically transports boundary layer moisture, helping to reduce updraft dilution. However, these factors vary in relative impacts on cloudy updrafts across individual cases, indicating multiple pathways for deep convection initiation.

Convective storms↗

A Bayesian Approach to Regional Decadal Predictability: Sparse Parameter Estimation in High-Dimensional Linear Inverse Models of High-Latitude Sea Surface Temperature Variability

Stochastic reduced models are an important tool in climate systems whose many spatial and temporal scales cannot be fully discretized or underlying physics may not be fully accounted for. One form of reduced model, the linear inverse model (LIM), has been widely used for regional climate predictability studies—typically focusing more on tropical or midlatitude studies. However, most LIM fitting techniques rely on point estimation techniques deriving from fluctuation–dissipation theory. In this methodological study we explore the use of Bayesian inference techniques for LIM parameter estimation of sea surface temperature (SST), to quantify the skillful decadal predictability of Bayesian LIM models at high latitudes. We show that Bayesian methods, when compared to traditional point estimation methods for LIM-type models, provide better calibrated probabilistic skill, while simultaneously providing better point estimates due to the regularization effect of the prior distribution in high-dimensional problems. We compare the effect of several priors, as well as maximum likelihood estimates, on 1) estimating parameter values on a perfect model experiment and 2) producing calibrated 1-yr SST anomaly forecast distributions using a preindustrial control run of the Community Earth System Model (CESM). Finally, we employ a host of probabilistic skill metrics to determine the extent to which an LIM can forecast SST anomalies at high latitudes. We find that the choice of prior distribution has an appreciable impact on estimation outcomes, and priors that emphasize physically relevant properties enhance the model’s ability to capture variability of SST anomalies.

54 ENVIRONMENTAL SCIENCES↗

Influence of Background Divergent Moisture Flux on the Frequency of North Pacific Atmospheric Rivers

The frequency of North Pacific atmospheric rivers (ARs) affects water supply and flood risk over western North America. Thus, understanding factors that affect the variability of landfalling AR frequency is of scientific and societal importance. This study aims at identifying the sources of the moisture for North Pacific ARs and assessing how different modes of variability modulate these sources. To this end, the sources and variability of the background divergent component of the integrated moisture flux (DIVT) in ARs are identified using MERRA reanalysis. It is shown that in the boreal winter, this background DIVT in ARs is related to the outflow from the subsidence over the subtropics which transports moisture northward, while in summer it is related to the Asian monsoon and it transports moisture northwestward. This leads to a seasonal northwest/southeast movement of the AR frequency climatology. At the intra-seasonal scale, propagation of the Madden-Julian Oscillation introduces an anti-clockwise rotation of the background DIVT, with northward transport in phases 1 and 2, westward in 3 and 4, southward in 5 and 6 and eastward in 7 and 8, making landfall over the west coast of North America most likely during the last two phases. Similarly, El Niño Southern Oscillation variability also affects the frequency of ARs through modulation of the westerly background DIVT, favoring landfall over the US west coast during strong El Niño phases. It is shown that in general the likelihood of AR landfall over the western US is correlated with the zonal background DIVT over northeastern Pacific.

54 ENVIRONMENTAL SCIENCES↗

Warming Pattern over the Northern Hemisphere Midlatitudes in Boreal Summer 1979–2020

Abstract Significant surface air temperature warming during summer 1979–2020 is not uniformly distributed in the northern midlatitudes over land but rather is confined to several longitudinal sectors including Europe, central Siberia and Mongolia, and both coasts of North America. These hot spots are accompanied by a chain of high pressure ridges from an anomalous, circumglobal Rossby wave train in the upper troposphere. From reanalysis data and several baseline experiments from phase 6 of the Coupled Model Intercomparison Project (CMIP6), we find that the circulation trend pattern is associated with fluctuations of the Atlantic multidecadal variability (AMV) and the interdecadal Pacific oscillation. The phase shift of AMV in the 1990s is particularly noteworthy for accelerating warming averaged over the northern midlatitude land. The amplitude of the observed trend in both surface air temperature and the upper-level geopotential height generally falls beyond the range of multidecadal trends simulated by the CMIP6 preindustrial control runs, supporting the likelihood that anthropogenic forcing played a critical role in the observed trend. On the other hand, the fidelity of the simulated low-frequency modes of variability and their teleconnections, especially on multidecadal time scales, is difficult to assess because of the relatively short observational records. Our mechanistic modeling results indicate that synoptic eddy–mean flow interaction is a key to the formation of the anomalous wave train but how the multidecadal modes can modulate the synoptic eddies through atmosphere–ocean and atmosphere–land interactions remains poorly understood. This gap in our knowledge makes it challenging to quantify the roles of the low-frequency modes and external forcings in causing the observed multidecadal trends.

54 ENVIRONMENTAL SCIENCES↗

An Evaluation of Tropical Cyclone Rainfall Structures in the HighResMIP Simulations against Satellite Observations

This study evaluates tropical cyclone (TC) rainfall structures in the CMIP6 HighResMIP global climate model (GCM) simulations against satellite rainfall retrievals. Here, we specifically focus on TCs within the deep tropics (25°S–25°N). Analysis of TC rain rate composites indicates that in comparison to the satellite observations at the same intensity, many HighResMIP simulations tend to overproduce rain rates around TCs, in terms of both maximum rain rate magnitude and area-averaged rain rates. In addition, as model horizontal resolution increases, the magnitude of the peak rain rate appears to increase. However, the area-averaged rain rates decrease with increasing horizontal resolution, partly due to the TC eyewall being located closer to the TC center, thus occupying a smaller area and contributing less to the area-averaged rain rates. The effect of ocean coupling is to lower the TC rain rates, bringing them closer to the satellite observations, due to reduced horizontal moisture flux convergence and surface latent heat flux beneath TCs. Examination of horizontal rain rate distributions indicates that vertical wind shear–induced rainfall asymmetries in HighResMIP-simulated TCs are qualitatively consistent with the observations. In addition, a positive relationship is observed between the area-averaged inner-core rainfall and TC intensification likelihoods across the HighResMIP simulations, as GCM simulations producing stronger TCs more frequently have the greater rainfall close to the center, in agreement with previous theoretical and GCM simulation results.

54 ENVIRONMENTAL SCIENCES↗

Floods due to Atmospheric Rivers along the U.S. West Coast: The Role of Antecedent Soil Moisture in a Warming Climate

Precipitation extremes are projected to become more frequent along the U.S. West Coast due to increased atmospheric river (AR) activity, but the frequency of less intense precipitation events may decrease. Antecedent soil moisture (ASM) conditions can have a large impact on flood responses, especially if prestorm precipitation decreases. Taken together with increased antecedent evaporative demand due to warming, this would result in reduced soil moisture at the onset of extreme precipitation events. In this work, we examine the impact of ASM on AR-related floods in a warming climate in three basins that form a transect along the U.S. Pacific Coast: the Chehalis River basin in Washington, the Russian River basin in Northern California, and the Santa Margarita River basin in Southern California. Additionally, we ran the Distributed Hydrology Soil Vegetation Model (DHSVM) over the three river basins using forcings downscaled from 10 global climate models (GCMs). We examined the dynamic role of ASM by comparing the changes in the largest 50, 100, and 150 extreme events in two periods, 1951–2000 and 2050–99. In the Chehalis basin, the projected fraction of AR-related extreme discharge events slightly decreases. In the Russian basin, this fraction increases, however, and more substantially so in the Santa Margarita basin. This is due to increases in AR-related extreme precipitation events, as well as the fact that the relationship of extreme precipitation to extreme discharge is strengthened by projected increases in year-to-year volatility of annual precipitation in California, which increases the likelihood of concurrent occurrence of large storms and wet ASM conditions.

54 ENVIRONMENTAL SCIENCES↗

Multisensor Agile Adaptive Sampling (MAAS): A Methodology to Collect Radar Observations of Convective Cell Life Cycle

Abstract Multisensor Agile Adaptive Sampling (MAAS), a smart sensing framework, was adapted to increase the likelihood of observing the vertical structure (with little to no gaps), spatial variability (at subkilometer scale), and temporal evolution (at ∼2-min resolution) of convective cells. This adaptation of MAAS guided two mechanically scanning C-band radars (CSAPR2 and CHIVO) by automatically analyzing the latest NEXRAD data to identify, characterize, track, and nowcast the location of all convective cells forming in the Houston domain. MAAS used either a list of predetermined rules or real-time user input to select a convective cell to be tracked and sampled by the C-band radars. The CSAPR2 tracking radar was first tasked to collect three sector plan position indicator (PPI) scans toward the selected cell. Edge computer processing of the PPI scans was used to identify additional targets within the selected cell. In less than 2 min, both the CSAPR2 and CHIVO radars were able to collect bundles of three to six range–height indicator (RHI) scans toward different targets of interest within the selected cell. Bundles were successively collected along the path of cell advection for as long as the cell met a predetermined set of criteria. Between 1 June and 30 September 2022 over 315 000 vertical cross-section observations were collected by the C-band radars through ∼1300 unique isolated convective cells, most of which were observed for over 15 min of their life cycle. To the best of our knowledge, this dataset, collected primarily through automatic means, constitutes the largest dataset of its kind.

54 ENVIRONMENTAL SCIENCES↗

A Climatology and Extreme Value Analysis of Large Hail in China

In this paper, hail size records are analyzed at 2254 stations in China and a hail size climatology is developed based on gridded hail observations for the period 1960–2015. It is found that the annual percentiles of hail size records changed sharply and national-wide after 1980, therefore two periods, 1960–79 and 1980–2015, are studied. There are some similarities between the two periods in terms of the characteristics of hail size such as the spatial distribution patterns of mean annual maximum hail size and occurrence week of annual maximum hail size. The 1980–2015 period had higher observation density than the 1960–79 period, but showed smaller mean annual maximum hail size, especially in northern China. In the majority of grid boxes, the annual maximum hail size experienced a decreasing trend during the 1980–2015 period. A Gumbel extreme value model is fitted to each grid box to estimate the return periods of maximum hail size. The scale and location parameter of the fitted Gumbel distributions are higher in eastern China than in western China, thereby reflecting a greater likelihood of large hail in eastern China. In southern China, the maximum hail size exceeds 127 mm for a 10-yr return period, whereas in northern China maximum hail size exceeds this threshold for a 50-yr return period. Furthermore, the Gumbel model is found to potentially underestimate the maximum hail size for certain return periods, but provides a more informed picture of the spatial distribution of extreme hail size and the regional differences.

54 ENVIRONMENTAL SCIENCES↗