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At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Ice-shelf freshwater triggers for the Filchner–Ronne Ice Shelf melt tipping point in a global ocean–sea-ice model

Some ocean modeling studies have identified a potential tipping point from a low to a high basal melt regime beneath the Filchner–Ronne Ice Shelf (FRIS), Antarctica, with significant implications for subsequent Antarctic ice sheet mass loss. To date, investigation of the climate drivers and impacts of this possible event have been limited because ice-shelf cavities and ice-shelf melting are only now starting to be included in global climate models. Using a global ocean–sea-ice configuration of the Energy Exascale Earth System Model (E3SM) that represents both ocean circulations and melting within ice-shelf cavities, we explore freshwater triggers (iceberg melt and ice-shelf basal melt) of a transition to a high-melt regime at FRIS in a low-resolution (30 km in the Southern Ocean) global ocean–sea-ice model. We find that a realistic spatial distribution of iceberg melt fluxes is necessary to prevent the FRIS melt regime change from unrealistically occurring under historical-reanalysis-based atmospheric forcing. Further, improvement of the default parameterization for mesoscale eddy mixing significantly reduces a large regional fresh bias and weak Antarctic Slope Front structure, both of which precondition the model to melt regime change. Using two different stable model con figurations, we explore the sensitivity of FRIS melt regime change to regional ice-sheet freshwater fluxes. Through a series of sensitivity experiments prescribing incrementally increasing melt rates from the smaller, neighboring ice shelves in the eastern Weddell Sea, we demonstrate the potential for an ice-shelf melt “domino effect” should the upstream ice shelves experience increased melt rates. The experiments also reveal that modest ice-shelf melt biases in a model, especially at coarse ocean resolution where narrow continental shelf dynamics are not well resolved, can lead to an unrealistic melt regime change at downstream ice shelves. Thus, we find that remote connections between melt fluxes at different ice shelves are sensitive to baseline model conditions. Our results highlight both the potential and the peril of simulating prognostic Antarctic ice-shelf melt rates in a low-resolution global model.

58 GEOSCIENCES↗
DOE OSTI2023

DECOVALEX-2023: Task F Specification (Revision 10)

This report is the revised (Revision 10) Task F specification for DECOVALEX-2023. Task F is a comparison of the models and methods used in deep geologic repository performance assessment. The task proposes to develop a reference case for a mined repository in a fractured crystalline host rock (Task F1) and a reference case for a mined repository in a salt formation (Task F2). Teams may choose to participate in the comparison for either or both reference cases. For each reference case, a common set of conceptual models and parameters describing features, events, and processes that impact performance will be given, and teams will be responsible for determining how best to implement and couple the models. The comparison will be conducted in stages, beginning with a comparison of key outputs of individual process models, followed by a comparison of a single deterministic simulation of the full reference case, and moving on to uncertainty propagation and uncertainty and sensitivity analysis. This report provides background information, a summary of the proposed reference cases, and a staged plan for the analysis.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Cerberus and the Zeus Suite of Critical Experiment Benchmarks [Slides]

This presentation finds that as it was designed, Cerberus is extremely sensitive to copper nuclear data. Just changing copper nuclear data to another library can swing simulated keff by >1000 pcm. ENDF/B-VIII.1 and JENDL-5.0 both show large downward trends in keff as copper interstitial thickness is increased

ENDF/B-VIII.1↗
DOE OSTI2023

Bridging Time-series Image Phenotyping and Functional–Structural Plant Modeling to Predict Adventitious Root System Architecture

Root system architecture (RSA) is an important measure of how plants navigate and interact with the soil environment. However, current methods in studying RSA must make tradeoffs between precision of data and proximity to natural conditions, with root growth in germination papers providing accessibility and high data resolution. Functional–structural plant models (FSPMs) can overcome this tradeoff, though parameterization and evaluation of FSPMs are traditionally based in manual measurements and visual comparison. Here, we applied a germination paper system to study the adventitious RSA and root phenology of Populus trichocarpa stem cuttings using time-series image-based phenotyping augmented by FSPM. We found a significant correlation between timing of root initiation and thermal time at cutting collection (P value = 0.0061, R 2 = 0.875), but little correlation with RSA. We also present a use of RhizoVision [1] for automatically extracting FSPM parameters from time series images and evaluating FSPM simulations. A high accuracy of the parameterization was achieved in predicting 2D growth with a sensitivity rate of 83.5%. This accuracy was lost when predicting 3D growth with sensitivity rates of 38.5% to 48.7%, while overall accuracy varied with phenotyping methods. Despite this loss in accuracy, the new method is amenable to high throughput FSPM parameterization and bridges the gap between advances in time-series phenotyping and FSPMs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Integrating Light Curve and Atmospheric Modeling of Transiting Exoplanets

Spectral retrieval techniques are currently our best tool to interpret the observed exoplanet atmospheric data. Said techniques retrieve the optimal atmospheric components and parameters by identifying the best fit to an observed transmission/emission spectrum. Over the past decade, our understanding of remote worlds in our galaxy has flourished thanks to the use of increasingly sophisticated spectral retrieval techniques and the collective effort of the community working on exoplanet atmospheric models. A new generation of instruments in space and from the ground is expected to deliver higher quality data in the next decade; it is therefore paramount to upgrade current models and improve their reliability, their completeness, and the numerical speed with which they can be run. In this paper, we address the issue of reliability of the results provided by retrieval models in the presence of systematics of unknown origin. More specifically, we demonstrate that if we fit directly individual light curves at different wavelengths (L-retrieval), instead of fitting transit or eclipse depths, as it is currently done (S-retrieval), the said methodology is more sensitive against astrophysical and instrumental noise. This new approach is tested, in particular, when discrepant simulated observations from Hubble Space Telescope/Wide Field Camera 3 and Spitzer/IRAC are combined. We find that while S-retrievals converge to an incorrect solution without any warning, L-retrievals are able to flag potential discrepancies between the data sets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The Signatures of Self-interacting Dark Matter and Subhalo Disruption on Cluster Substructure

The abundance, distribution, and inner structure of satellites of galaxy clusters can be sensitive probes of the properties of dark matter. We run 30 cosmological zoom-in simulations with self-interacting dark matter (SIDM), with a velocity-dependent cross section, to study the properties of subhalos within cluster-mass hosts. We find that the abundance of subhalos that survive in the SIDM simulations are suppressed relative to their cold dark matter (CDM) counterparts. Once the population of disrupted subhalos—which may host orphan galaxies—is taken into account, satellite galaxy populations in CDM and SIDM models can be reconciled. However, even in this case, the inner structures of subhalos are significantly different in the two dark matter models. We study the feasibility of using the weak-lensing signal from the subhalo density profiles to distinguish between the cold and self-interacting dark matter while accounting for the potential contribution of orphan galaxies. We find that the effects of self-interactions on the density profile of subhalos can appear degenerate with subhalo disruption in CDM, when orphans are accounted for. With current error bars from the Subaru Hyper Suprime-Cam Strategic Program, we find that subhalos in the outskirts of clusters (where disruption is less prevalent) can be used to constrain dark matter physics. In the future, the Vera C. Rubin Observatory Legacy Survey of Space and Time will give precise measurements of the weak-lensing profile and can be used to constrain σ $_{T}$/m at the ∼1 cm$^{2}$ g$^{−1}$ level at v ∼ 2000 km s$^{−1}$.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Earth-system-model evaluation of cloud and precipitation occurrence for supercooled and warm clouds over the Southern Ocean's Macquarie Island

Abstract. Over the remote Southern Ocean (SO), cloud feedbacks contribute substantially to Earth system model (ESM) radiative biases. The evolution of low Southern Ocean clouds (cloud-top heights < ∼ 3 km) is strongly modulated by precipitation and/or evaporation, which act as the primary sink of cloud condensate. Constraining precipitation processes in ESMs requires robust observations suitable for process-level evaluations. A year-long subset (April 2016–March 2017) of ground-based profiling instrumentation deployed during the Macquarie Island Cloud and Radiation Experiment (MICRE) field campaign (54.5∘ S, 158.9∘ E) combines a 95 GHz (W-band) Doppler cloud radar, two lidar ceilometers, and balloon-borne soundings to quantify the occurrence frequency of precipitation from the liquid-phase cloud base. Liquid-based clouds at Macquarie Island precipitate ∼ 70 % of the time, with deeper and colder clouds precipitating more frequently and at a higher intensity compared to thinner and warmer clouds. Supercooled cloud layers precipitate more readily than layers with cloud-top temperatures > 0 ∘C, regardless of the geometric thickness of the layer, and also evaporate more frequently. We further demonstrate an approach to employ these observational constraints for evaluation of a 9-year GISS-ModelE3 ESM simulation. Model output is processed through the Earth Model Column Collaboratory (EMC2) radar and lidar instrument simulator with the same instrument specifications as those deployed during MICRE, therefore accounting for instrument sensitivities and ensuring a coherent comparison. Relative to MICRE observations, the ESM produces a smaller cloud occurrence frequency, smaller precipitation occurrence frequency, and greater sub-cloud evaporation. The lower precipitation occurrence frequency by the ESM relative to MICRE contrasts with numerous studies that suggest a ubiquitous bias by ESMs to precipitate too frequently over the SO when compared with satellite-based observations, likely owing to sensitivity limitations of spaceborne instrumentation and different sampling methodologies for ground- versus space-based observations. Despite these deficiencies, the ESM reproduces the observed tendency for deeper and colder clouds to precipitate more frequently and at a higher intensity. The ESM also reproduces specific cloud regimes, including near-surface clouds that account for ∼ 25 % of liquid-based clouds during MICRE and optically thin, non-precipitating clouds that account for ∼ 27 % of clouds with bases higher than 250 m. We suggest that the demonstrated framework, which merges observations with appropriately constrained model output, is a valuable approach to evaluate processes responsible for cloud radiative feedbacks in ESMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Ice-shelf freshwater triggers for the Filchner–Ronne Ice Shelf melt tipping point in a global ocean–sea-ice model

Abstract. Some ocean modeling studies have identified a potential tipping point from a low to a high basal melt regime beneath the Filchner–Ronne Ice Shelf (FRIS), Antarctica, with significant implications for subsequent Antarctic ice sheet mass loss. To date, investigation of the climate drivers and impacts of this possible event have been limited because ice-shelf cavities and ice-shelf melting are only now starting to be included in global climate models. Using a global ocean–sea-ice configuration of the Energy Exascale Earth System Model (E3SM) that represents both ocean circulations and melting within ice-shelf cavities, we explore freshwater triggers (iceberg melt and ice-shelf basal melt) of a transition to a high-melt regime at FRIS in a low-resolution (30 km in the Southern Ocean) global ocean–sea-ice model. We find that a realistic spatial distribution of iceberg melt fluxes is necessary to prevent the FRIS melt regime change from unrealistically occurring under historical-reanalysis-based atmospheric forcing. Further, improvement of the default parameterization for mesoscale eddy mixing significantly reduces a large regional fresh bias and weak Antarctic Slope Front structure, both of which precondition the model to melt regime change. Using two different stable model configurations, we explore the sensitivity of FRIS melt regime change to regional ice-sheet freshwater fluxes. Through a series of sensitivity experiments prescribing incrementally increasing melt rates from the smaller, neighboring ice shelves in the eastern Weddell Sea, we demonstrate the potential for an ice-shelf melt “domino effect” should the upstream ice shelves experience increased melt rates. The experiments also reveal that modest ice-shelf melt biases in a model, especially at coarse ocean resolution where narrow continental shelf dynamics are not well resolved, can lead to an unrealistic melt regime change at downstream ice shelves. Thus, we find that remote connections between melt fluxes at different ice shelves are sensitive to baseline model conditions. Our results highlight both the potential and the peril of simulating prognostic Antarctic ice-shelf melt rates in a low-resolution global model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Summary of Geometric Parameters and Their Effects on Performance of U-10Mo Fuel Plates

A monolithic plate-type fuel system has been under development to convert high-performance test reactors from highly enriched uranium to low-enrichment uranium fuels and is now moving into the qualification phase, a predecessor to the timely conversion of the target reactors. To qualify this fuel system, the plates must meet safety standards and perform well in a reactor. The plates must maintain mechanical integrity, exhibit geometric stability, and have stable and predictable in-reactor behavior. The requirement to maintain mechanical integrity under normal operating conditions is primarily demonstrated by successful testing. However, each high-performance reactor employs a distinct design, resulting in distinct plate geometries, with unique features, attributes, irregularities, and tolerances. Due to the abundance of such distinct geometric varieties, a single “generic” plate geometry capturing all extremes is not achievable. It is also impractical to test each of these proposed designs in a reactor. This limitation necessitates cautious evaluations since the thermomechanical response of a plate with a certain geometry may not be representative for a plate with a significantly different geometry. To address concerns related to in-reactor plate performance, large set of sensitivity studies were performed. These parametric studies aimed to better understand irradiation performance, while evaluating the sensitivity of results to various modeling inputs, including geometric, operational, and material parameters. This work studied selected geometric parameters based on provided fuel specifications and performed a series of parametric simulations. The resulting temperature, displacement, and stress strains were comparatively evaluated to determine the effects of various geometric parameters. This draft provides a “high-level summary” of our parametric sensitivity studies and summarizes the key findings.

42 ENGINEERING↗
DOE OSTI2025

Muon momentum reconstruction in ICARUS-T600 LArTPC via Multiple Scattering

The SBN program at Fermilab investigates the possible existence of eV-scale sterile neutrinos. This work focuses on reconstructing muon momentum in $\nu$-Ar interactions within the ICARUS-T600 LArTPC detector using Multiple Coulomb Scattering (MCS), the only viable method for non-contained muons. Two algorithms are evaluated: the Gran Sasso algorithm (2D, Collection view) and the MicroBooNE algorithm (3D angles), applied to 2391 simulated and 2255 real stopping muon tracks (0.4-1 GeV/c). Performance is assessed via bias and resolution, using range-based momentum as a reference. Two enhanced versions of the Gran Sasso algorithm are also developed: one combining all three wire plane views, and one using 3D angles. Results show that the MicroBooNE algorithm performs slightly better, with resolution down to 14\% in simulation and 16\% in real data. These improvements significantly boost $\nu_\mu$ CC statistics, enhancing sensitivity to $\nu_\mu$ disappearance and 3+1 oscillation signals.

Chiello, Giovanni [Pisa U.] (ORCID:000900064571071↗
DOE OSTI2026

Integration of Silica in G4CMP for Phonon Simulations: Framework and Tools for Material Integration

Superconducting detectors with sub-eV energy resolution have demonstrated success setting limits on Beyond the Standard Model (BSM) physics due to their unique sensitivity to low-energy events. G4CMP, a Geant4-based extension for condensed matter physics, provides a comprehensive toolkit for modeling phonon and charge dynamics in cryogenic materials. This paper introduces a technical formalism to support the superconducting qubit and low-threshold detector community in implementing phonon simulations in custom materials into the G4CMP. As a case study, we present the results of a detailed analysis of silica phonon transport properties relevant for simulating substrate backgrounds in Beryllium Electron capture in Superconducting Tunnel junctions (BeEST)-style experiments using G4CMP. Additionally, Python-based tools were developed to aid users in implementing their own materials and are available on the G4CMP repository.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Modeling land surface processes over a mountainous rainforest in Costa Rica using CLM4.5 and CLM5

This study compares the performance of the Community Land Models (CLM4.5 and CLM5) against tower and ground measurements from a tropical montane rainforest in Costa Rica. The study site receives over 4000 mm of mean annual precipitation and has high daily levels of relative humidity. The measurement tower is equipped with eddy-covariance and vertical profile systems able to measure various micrometeorological variables, particularly in wet and complex terrain. In this work, results from point-scale simulations for both CLM4.5 and its updated version (CLM5) are compared to observed canopy flux and micrometeorological data. Both models failed to capture the effects of frequent rainfall events and mountainous topography on the variables of interest (temperatures, leaf wetness, and fluxes). Overall, CLM5 alleviates some errors in CLM4.5, but CLM5 still cannot precisely simulate a number of canopy processes for this forest. Soil, air, and canopy temperatures, as well as leaf wetness, remain too sensitive to incoming solar radiation rates despite updates to the model. As a result, daytime vapor flux and carbon flux are overestimated, and modeled temperature differences between day and night are higher than those observed. Slope effects appear in the measured average diurnal variations of surface albedo and carbon flux, but CLM5 cannot simulate these features. This study suggests that both CLMs still require further improvements concerning energy partitioning processes, such as leaf wetness process, photosynthesis model, and aerodynamic resistance model for wet and mountainous regions.

58 GEOSCIENCES↗
DOE OSTI2025

Constraining Black Carbon Aging in Global Models to Reflect Timescales for Internal Mixing

The radiative effects of black carbon depend critically on its atmospheric lifetime, which is controlled by the rate at which freshly emitted combustion particles become internally mixed with other aerosol components. Global aerosol models strive to represent this process, but the timescale for aerosol mixing is not easily constrained using observations. In this study, we apply a timescale parameterization derived from particle‐resolved simulations to quantify, in a global aerosol model, the timescale for internal mixing. We show that, while highly variable, the average timescale for internal mixing is approximately 3 hr, which is much shorter than the 24‐hr aging timescale traditionally applied in bulk aerosol models. We then use the mixing timescale to constrain the aging criterion in the Modal Aerosol Module. Our analysis reveals that, to best reflect timescales for internal mixing, modal models should assume that particles transition from the hydrophobic (fresh) to the hydrophilic (aged) class once they accumulate a coating thickness equal to four monolayers of sulfuric acid, as opposed to the model's current aging criterion of eight monolayers. We show that, in remote regions like the Arctic and Antarctic, predictions of black carbon loading and its seasonal variation are particularly sensitive to the model representation of aging. By constraining aging in global models to reflect mixing timescales simulated by the particle‐resolved model, we eliminate one of the free parameters governing black carbon's long‐range transport and spatiotemporal distribution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Reweighting Underlying Event and Colour Reconnection parameter variations in Sherpa

We propose and validate a new method to trace the impact of parameter variations in the simulation of multi-parton interactions and colour reconnections in the Sherpa event generator. They are reflected, at an event-by-event basis, through relative weights with respect to the central production parameters that give rise to the generated events and distributions. Our method facilitates the tuning of the Monte Carlo event generator at a dramatically reduced computational cost, alleviates parameter sensitivity studies, and enables robust quantification of parametric uncertainties on-the-fly, one of the missing ingredients for future simulations of high-energy particle collisions. The method can easily be adapted to and implemented in other event generators. To illustrate its potential, we here consider combined tunes of the multi-parton-interaction and colour-reconnection models in Sherpa using LHC proton-proton collision data at $\sqrt{s}=7\,\text{TeV}$. We furthermore calibrate the energy-scaling behaviour of dimensionful model parameters based on $\sqrt{s}=13\,\text{TeV}$ LHC data and Tevatron data taken at $\sqrt{s}=1.96\,\text{TeV}$.

Pabst, Moritz [Gottingen U.]↗
DOE OSTI2023

Status of HEU-Pb in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook

The Department of Energy invests tens of millions of dollars each year to develop the next generation of nuclear engineering modeling & simulation (M&S) tools. These tools are used to analyze advanced reactor designs and the safety of current nuclear operations. As computers become more powerful, we are able to enhance resolution in our calculations. This improved resolution is taking us to a point where the limitations of simulation capability are in the quality of data, including our ability to quantify the uncertainty and sensitivity of the data. In order to model systems of interest with increasing accuracy, the industry must improve key nuclear data measurements. Thus, M&S tools need evaluated and quality-assured experimental data for validation purposes. The International Criticality Safety Benchmark Evaluation Project (ICSBEP) compiles and evaluates experiment data in a handbook that can be used by criticality safety engineers and others to validate computer codes and cross-section libraries at nuclear facilities. Both critical and subcritical experiments are included in the handbook. Figure 1 organizes all the benchmark evaluations that have been performed by the isotope of interest, in this case Pb, and the average neutron energy the system. Compared to other isotopes of interest for nuclear applications, there are few benchmark evaluations for Pb systems. The lack of integral measurements to determine errors in Pb cross-section data has caused the latest nuclear cross-section libraries to over/underestimate k eff compared to experimental results. Therefore, this evaluation fills an important knowledge gap in benchmark evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Fast-Spectrum Critical Assemblies with a Pb-HEU Core Surrounded by a Copper Reflector

The Department of Energy invests tens of millions of dollars each year to develop the next generation of nuclear engineering modeling & simulation (M&S) tools. These M&S tools are used to analyze advanced reactor designs and the safety of current nuclear operations. As computers become more powerful, we are able to enhance resolution in our calculations. This improved resolution is taking us to a point where the limitations of simulation capability are in the quality of data, including our ability to quantify the uncertainty and sensitivity of the data. In order to accurately model systems of interest, the industry must improve key nuclear data measurements and our confidence of how well we understand the data. Thus, M&S tools need evaluated and quality-assured experimental data for validation purposes. The International Criticality Safety Benchmark Evaluation Project (ICSBEP) compiles benchmark experiment data in a handbook that can be used by criticality safety engineers to validate computer codes and cross-section libraries at nuclear facilities. Both critical and subcritical experiments are included in the handbook. Figure 1 organizes all the benchmark evaluations that have been performed by the isotope of interest, in this case Pb, and the neutron energy within the system. Compared to other isotopes of interest for nuclear applications, there are few benchmark evaluations for Pb systems. This has caused the latest nuclear cross-section libraries to over/underestimate changes in the neutron population compared to experimental results. Therefore, this evaluation fills an important knowledge gap in benchmark evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

A Faster-Than-Real-Time Framework for Reliability-Oriented Simulation of PV Inverters

Physics-of-Failure (PoF) based reliability assessment for photovoltaic (PV) inverters requires long-duration electrical and electrothermal stress histories, yet generating such stress histories with high-fidelity switching models over year long mission profiles is computationally prohibitive. Conventional methods either sacrifice modeling fidelity for speed or require runtimes that are impractical for design iteration and uncertainty studies. To address this bottleneck, this paper presents a High-Performance Computing (HPC) based simulation frame work for faster-than-real-time reliability-oriented simulation. The proposed framework integrates the Average-to-Switching (A2S) method with parallel computing techniques to accelerate switching-level waveform reconstruction. We further introduce optimization strategies, including cluster merging and sensitivity based mission profile screening, to reduce the computational burden. Evaluated using real-world mission profile inputs and a MATLAB/Simulink switching-model reference, the framework reduces the simulation time for a one-year mission from an intractable multi-year duration to approximately 7.3 minutes while maintaining low waveform error. This acceleration provides a practical reliability-oriented simulation engine that can be coupled with component-specific aging models for subsequent PV inverter PoF assessment.

High-performance Computing↗
DOE OSTI2020

Description of the LASSO Data Bundles Product

The U. S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility began a pilot project in May 2015 to design a routine, high-resolution modeling capability to complement ARM’s extensive suite of measurements. This modeling capability has evolved into the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) datastream. The datastream, broadly termed data bundles, contains high-resolution model output, input files, observations for evaluation, and skill scores for the simulations. The initial focus of LASSO is on shallow convection at the ARM Southern Great Plains (SGP) atmospheric observatory. The availability of LES simulations with concurrent observations serves many purposes. LES helps bridge the scale gap between DOE ARM observations and models, and the use of routine LES adds value to observations. It provides a self-consistent representation of the atmosphere and a dynamical context for the observations. Further, it elucidates unobservable processes and properties. LASSO generates a simulation library for researchers that enables statistical approaches beyond a single-case mentality. It also provides tools necessary for modelers to reproduce the LES and conduct their own sensitivity experiments. The LASSO library of data bundles is designed to facilitate a wide range of research. For an observationalist, LASSO can help inform instrument remote-sensing retrievals, conduct observation system simulation experiments (OSSEs), and test implications of radar scan strategies or flight paths. For a theoretician, LASSO can help calculate estimates of fluxes and co-variability of values, and test relationships without having to run the model personally. For a modeler, LASSO can help one know ahead of time which days have good forcing, have co-registered observations at high-resolution scales, and have simulation inputs and corresponding outputs to test parameterizations. Further details on the overall LASSO project are available at https://www.arm.gov/capabilities/modeling/lasso.

54 ENVIRONMENTAL SCIENCES↗