Description of the LASSO-ENA Activity: A LASSO Scenario for Shallow Maritime Clouds (web based)
LASSO-ENA documentation
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Results for “LASSO”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Assessing Cloud and Precipitation Properties on Temporal and Spatial Scales Using LASSO Simulations over ENA
Low clouds and precipitation representation remain a major source of uncertainty in Earth System Models (ESMs), particularly due to challenges in representing their sub-grid variability and scale-dependent sampling. This study evaluates the performance of preliminary simulations from the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) project over the Eastern North Atlantic (ENA), with a focus on liquid water path (LWP), ice water path (IWP), cloud fraction (CF), and surface precipitation simulated across closed-cell, open-cell, and transitional cloud regimes. Using LES (100 m horizontal grid spacing) driven by ERA5 and MERRA-2 reanalyses, we assess the representativeness of ground-based point observations by analyzing their correspondence to model-resolved spatial and temporal means. Results suggest that observational sampling of at least 6 hours is required to achieve consistency with domain-scale averages, in particular for observations that exhibit pronounced sub-grid heterogeneity, such as precipitation. ERA5-forced simulations exhibit improved spatial coherence and agreement with domain-averaged quantities when compared to MERRA-2 runs, with performance discrepancies largest for convective cloud conditions due to differences in forcing fidelity and temporal resolution. These findings highlight the importance of regime-aware model evaluation strategies and potentially demonstrate how LES can inform observation-model comparison practices and the development of cloud and precipitation parameterizations in ESMs.
Liang, Jiakun [University of Hawai'i at Manoa] (OR↗
LASSO experiment: Intercalibrations of the LASSO ranging stations
Presented are equations for time synchronization of laser ranging stations. The system consists of a satellite fitted with laser retroreflectors associated to a light detector and an event timer and two laser ranging stations with their own event timers. Methods of determining the Lasso intercalibration constant are given.
Gaignebet, J.↗
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↗
The Large-Eddy Simulation (LES) Atmospheric Radiation Measurement (ARM) Symbiotic Simulation and Observation (LASSO) Activity for Continental Shallow Convection
The U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) user facility recently initiated the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) activity focused on shallow convection at ARM’s Southern Great Plains (SGP) atmospheric observatory in Oklahoma. LASSO is designed to overcome an oft-shared difficulty of bridging the gap from point-based measurements to scales relevant for model parameterization development, and it provides an approach to add value to observations through modeling. LASSO is envisioned to be useful to modelers, theoreticians, and observationalists needing information relevant to cloud processes. LASSO does so by combining a suite of observations, LES inputs and outputs, diagnostics, and skill scores into data bundles that are freely available, and by simplifying user access to the data to speed scientific inquiry. The combination of relevant observations with observationally constrained LES output provides detail that gives context to the observations by showing physically consistent connections between processes based on the simulated state. A unique approach for LASSO is the generation of a library of cases for days with shallow convection combined with an ensemble of LES for each case. The library enables researchers to move beyond the single-case-study approach typical of LES research. The ensemble members are produced using a selection of different large-scale forcing sources and spatial scales. Since large-scale forcing is one of the most uncertain aspects of generating the LES, the ensemble informs users about potential uncertainty for each date and increases the probability of having an accurate forcing for each case.
54 ENVIRONMENTAL SCIENCES↗
Utilization of lasso peptides for biodegradation of polycyclic aromatic hydrocarbons
Abstract Many microbial genes involved in degrading recalcitrant environmental contaminants such as polycyclic aromatic hydrocarbons (PAHs) have been identified and characterized. However, all molecular mechanisms required for PAH utilization have not yet been elucidated. In this work, we demonstrate the proposed involvement of lasso peptides in the utilization of the PAH phenanthrene in Sphingomonas BPH. Transpositional mutagenesis of Sphingomonas BPH with the miniTn5 transposon yielded 3 phenanthrene utilization deficient mutants, #257, #1778, and #1782. In mutant #1782, Tn5 had inserted into the large subunit of the naph/bph dioxygenase gene. In mutant #1778, Tn5 had inserted into the B2 protease gene of a lasso peptide cluster. This finding is the first report on the role of lasso peptides in PAH utilization. Our studies also demonstrate that interruption of the lasso peptide cluster resulted in a significant increase in the amount of biosurfactant produced in the presence of glucose when compared to the wild‐type strain. Collectively, these results suggest that the mechanisms Sphingomonas BPH utilizes to degrade phenanthrene are far more complex than previously understood and that the #1778 mutant may be a good candidate for bioremediation when glucose is applied as an amendment due to its higher biosurfactant production.
59 BASIC BIOLOGICAL SCIENCES↗
Proposal and application of ROM-Lasso method for sensitivity coefficient evaluation
We propose a novel method for evaluating sensitivity coefficients of neutronics parameters to cross sections, so-called the reduced-order modeling technique ROM-Lasso. In this method, cross sections of interest are randomly sampled, and corresponding perturbed core analyses are performed. Then, the sensitivity coefficient vector of the higher-level model is expanded via the active subspace bases obtained with the lower-level model whose dimensional complexity is smaller than that of the higher-level model, and the expansion coefficients are estimated by the Lasso regression. A unique feature of the ROM-Lasso method allows the use of different bases optimized for each neutronics parameter. We conducted a verification calculation for an accelerator-driven system and demonstrated that the ROM-Lasso method can reproduce the sensitivity coefficients with a much smaller number of forward calculations than the direct method. The proposed method can be used to practically evaluate sensitivity coefficients. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
WRF Simulation Data for LASSO-CACTI Overview Paper
A portion of the LASSO-CACTI simulation output was used in writing the LASSO-CACTI overview paper, which has been submitted to Geoscientific Model Development as of November 2025 by Gustafson et al. This product contains YAML files to be used in conjunction with the LASSO-CACTI Bundle Browser to download the specific WRF data used with each figure in the paper. This reduces the overall data downloaded so that the entire 2 PB data set is not needed.
{WRF,LASSO-CACTI}↗
Final DOE-ASR Report for the Project “Using LASSO to bridge the gap between model and observations and to learn about atmospheric convection”
Atmospheric convection spans a wide range of spatial and temporal scales and involves complex interactions with the surrounding dynamic and thermodynamic environment, particularly over tropical continental regions. These processes remain a major source of uncertainty in weather and climate models, including persistent biases in the diurnal cycle of convective precipitation that directly affect estimates of climate sensitivity. Addressing these challenges requires the combined use of high-resolution observations and cloud-resolving modeling frameworks. In this context, the DOE Atmospheric Radiation Measurement (ARM) program’s Large-Eddy Simulation ARM Symbiotic Simulation and Observation (LASSO) activity provides a powerful platform that pairs comprehensive observations with numerical simulations to enable process-level understanding of atmospheric convection. Within this context, this Research and Development Partnership Pilot (RDPP) project was designed to initiate and expand DOE ARM/ASR research capacity at minority-serving institutions, while advancing scientific understanding of convective processes over the Amazon rainforest. Consistent with the RDPP mission, the project emphasized partnership development, training, and workforce capacity building alongside exploratory research activities. On the scientific side, the project produced two peer-reviewed journal articles, and one manuscript currently under review (see list in section 3.1). Together, these studies combine long-term ARM observations and cloud-resolving and convection-permitting modeling to investigate the environmental controls on the shallow-to-deep convective transition during the Amazon wet season. The results demonstrate the central role of early-day moisture preconditioning and large-scale dynamical forcing in regulating isolated deep convection, provide mechanistic insight into convective evolution, and establish physically informed modeling frameworks for future sensitivity experiments. These scientific outcomes are described in sections 2.1 to 2.3 and were disseminated in 8 conference presentations (see section 3.2) and 5 invited talks (see section 3.3), reflecting broad engagement with our community. Equally important, the project achieved its RDPP capacity-building objectives (see section 2.4). A sustained research partnership was established among the University of Maryland, Baltimore County (UMBC), Morgan State University (MSU), and Howard University (HU), and extended to include collaboration with Pacific Northwest National Laboratory (PNNL). The project organized multiple multi-day training events focused on ARM data, LASSO simulations, and quantitative analysis methods, directly engaging students, postdoctoral researchers, and faculty across institutions. These activities broadened participation in ASR research and led to independent adoption of LASSO workflows by students beyond the immediate project team. Finally, the project successfully positioned the participating institutions to pursue future DOE research. Preliminary scientific results, coupled with strengthened partnerships and technical capacity, enabled the submission of follow-on proposals to DOE ASR funding opportunities. In this way, the project fulfilled the RDPP goal of seeding durable research capacity and laying the foundation for larger-scale, sustained engagement with DOE ARM and ASR programs.
54 ENVIRONMENTAL SCIENCES↗
LASSO, two-way, and GPS time comparisons: A (very) preliminary status report
The first results are presented on the time transfer experiments between TUG (Graz, Austria) and OCA (Grasse, France) using common view Global Positioning System (GPS) and two-way stations at both sites. The present data, providing arms of the clock offsets of 2 to 3 nanoseconds for a three month period, have to be further analyzed before any conclusions on the respective precision and accuracy of these techniques can be drawn. Two years after its start, the Laser Synchronization from Stationary Orbit (LASSO) experiment is finally giving its first results at TUG and OCA. The first analysis of three common sessions permitted researchers to conclude that the LASSO package on board Meteosat P2 is working satisfactorily, and that time transfer using this method should provide clock offsets at better than 1 nanosecond precision, and clock rates at better than 10(exp -12) s/s in a 5 to 10 minutes session. A new method for extracting this information from the raw data sent by LASSO should enhance the performances of this experiment, exploiting the stability of the on-board oscillator.
Veillet, Christian J. L.↗
LASSO observations at McDonald and OCA/CERGA: A preliminary analysis
The Laser Synchronization from Synchronous Orbit (LASSO) observations between USA and Europe were made possible with the move of Meteosat 3/P2 toward 50 deg W. Two Lunar Laser Ranging stations participated into the observations: the MLRS at McDonald Observatory (Texas, USA) and OCA/CERGA (Grasse, France). Common sessions were performed since 30 Apr. 1992, and will be continued up to the next Meteosat 3/P2 move further West (planned for January 1993). The preliminary analysis made with the data already collected by the end of Nov. 1992 shows that the precision which can be obtained from LASSO is better than 100 ps, the accuracy depending on how well the stations maintain their time metrology, as well as on the quality of the calibration (still to be made.) For extracting such a precision from the data, the processing has been drastically changed compared to the initial LASSO data analysis. It takes into account all the measurements made, timings on board, and echoes at each station. This complete use of the data increased dramatically the confidence into the synchronization results.
Veillet, CH.↗
Comparison of LASSO and GPS time transfers
The LASSO is a technique which should allow the comparison of remote atomic clocks with sub-nanosecond precision and accuracy. The first successful time transfer using LASSO has been carried out between the Observatoire de la Cote d'Azur in France and the McDonald Observatory in Texas, United States. This paper presents a preliminary comparison of LASSO time transfer with GPS common-view time transfer.
Lewandowski, W.↗
A LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATOR (LASSO) FOR NONLINEAR SYSTEM IDENTIFICATION
Identification of parametric nonlinear models involves estimating unknown parameters and detecting its underlying structure. Structure computation is concerned with selecting a subset of parameters to give a parsimonious description of the system which may afford greater insight into the functionality of the system or a simpler controller design. In this study, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of nonlinear systems. The LASSO minimises the residual sum of squares by the addition of a 1 penalty term on the parameter vector of the traditional 2 minimisation problem. Its use for structure detection is a natural extension of this constrained minimisation approach to pseudolinear regression problems which produces some model parameters that are exactly zero and, therefore, yields a parsimonious system description. The performance of this LASSO structure detection method was evaluated by using it to estimate the structure of a nonlinear polynomial model. Applicability of the method to more complex systems such as those encountered in aerospace applications was shown by identifying a parsimonious system description of the F/A-18 Active Aeroelastic Wing using flight test data.
Kukreja, Sunil L.↗
Input files and WRF run directory for a LASSO-CACTI simulation
Tar file containing files necessary for reproducing a given Weather Research and Forecasting (WRF) simulation from the Large-Eddy Simulation (LES) Atmospheric Radiation Measurement (ARM) Symbiotic Simulation and Observation (LASSO) deep-convection scenario for the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. The LASSO-CACTI simulations span grid spacings from 7.5 km to 100 m for convection near the Sierras de Córdoba mountain range, roughly centered on the ARM Mobile Facility. More information can be found at https://www.arm.gov/capabilities/modeling/lasso. Types of files in this tar include the initial and boundary conditions, WRF namelist, and other files present in a WRF run directory.
54 ENVIRONMENTAL SCIENCES↗
Raw WRF model output files from a LASSO-CACTI simulation
The raw model output from a Weather Research and Forecasting (WRF) simulation from the Large-Eddy Simulation (LES) Atmospheric Radiation Measurement (ARM) Symbiotic Simulation and Observation (LASSO) deep-convection scenario for the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. The LASSO-CACTI simulations span grid spacings from 7.5 km to 100 m through the use of four nested domains, labeled d1 through d4. The simulations are of convection near the Sierras de Córdoba mountain range, roughly centered on the ARM Mobile Facility. More information can be found at https://www.arm.gov/capabilities/modeling/lasso. The raw model output is in netCDF format as output by the WRF model, i.e., the “wrfout” files, with the files renamed for archival purposes.
54 ENVIRONMENTAL SCIENCES↗
WRF restart files for a LASSO-CACTI simulation
The restart files from a Weather Research and Forecasting (WRF) simulation from the Large-Eddy Simulation (LES) Atmospheric Radiation Measurement (ARM) Symbiotic Simulation and Observation (LASSO) deep-convection scenario for the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. The LASSO-CACTI simulations span grid spacings from 7.5 km to 100 m through the use of four nested domains, labeled d1 through d4. Restarts are available for the LES domains, i.e., d3 and d4. The simulations are of convection near the Sierras de Córdoba mountain range, roughly centered on the ARM Mobile Facility. More information can be found at https://www.arm.gov/capabilities/modeling/lasso. The restart files are output every 30 minutes in netCDF format as output by the WRF model, i.e., the “wrfrst” files, with the files renamed for archival purposes.
54 ENVIRONMENTAL SCIENCES↗
Subsetted model output for aerosol-related variables from a LASSO-CACTI WRF simulation
Aerosol-related model output from a Weather Research and Forecasting (WRF) simulation from the Large-Eddy Simulation (LES) Atmospheric Radiation Measurement (ARM) Symbiotic Simulation and Observation (LASSO) deep-convection scenario for the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. The LASSO-CACTI simulations span grid spacings from 7.5 km to 100 m through the use of four nested domains, labeled d1 through d4. The simulations are of convection near the Sierras de Córdoba mountain range, roughly centered on the ARM Mobile Facility. More information can be found at https://www.arm.gov/capabilities/modeling/lasso. This version of the output is a collection of variables subsetted from the raw WRF output to reduce the file overhead for users not needing the full raw dataset. The subset files are in netCDF format with the height-based variables on the raw, model eta levels. The aerosol properties are consistent with the Thompson aerosol-aware cloud microphysics scheme where the simulated aerosol are proxies for representative “water friendly” and “ice friendly” aerosol.
54 ENVIRONMENTAL SCIENCES↗
Subsetted model output for cloud-related variables from a LASSO-CACTI WRF simulation
Cloud-related model output from a Weather Research and Forecasting (WRF) simulation from the Large-Eddy Simulation (LES) Atmospheric Radiation Measurement (ARM) Symbiotic Simulation and Observation (LASSO) deep-convection scenario for the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. The LASSO-CACTI simulations span grid spacings from 7.5 km to 100 m through the use of four nested domains, labeled d1 through d4. The simulations are of convection near the Sierras de Córdoba mountain range, roughly centered on the ARM Mobile Facility. More information can be found at https://www.arm.gov/capabilities/modeling/lasso. This version of the output is a collection of variables subsetted from the raw WRF output to reduce the file overhead for users not needing the full raw dataset. The subset files are in netCDF format with the height-based variables on the raw, model eta levels.
54 ENVIRONMENTAL SCIENCES↗