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Site C1a - NREL ASSIST (SN12) Thermodynamic Retrievals TROPoe / Derived Data

This dataset contains daily files with thermodynamic profiles retrieved with the optimal estimation physical retrieval TROPoe v0.12 (Turner and Löhnert 2014; Turner and Blumberg 2019; Turner and Löhnert 2021). The profiles are retrieved every 10 minutes from instantaneous observations from the NREL ASSIST-II (SN 12) infrared spectrometer. Observations are noise-filtered but not averaged in time to minimize errors due to non-uniform clouds. Additional input data in TROPoe are cloud base height (CBH), which is a combined data product that uses data from ceilometers at sites A1 and H and scanning lidars from ARM sites C1 and E37. The CBH is weighted inversely proportionally to the distance to the respective site to take into account the spatial variability of clouds (see https://github.com/StefanoWind/ASSIST_analysis/blob/main/awaken_processing/combine_cbh.py). The full pipeline for running the retrieval is available at https://github.com/StefanoWind/TROPoe_processor. Met data was not ingested. In addition to these temporally resolved input data, TROPoe requires an a priori dataset (prior) that provides mean climatological estimates of thermodynamic profiles and specifies how temperature and humidity covary with height as an input (for details see, e.g., Djalalova et al. 2022). The prior is a key component of the retrieval and provides a constraint on the ill-posed inversion problem. A monthly prior was computed from operational radiosonde launches at ARM SGP, OK.

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Rhode Island Site - NREL ASSIST Thermodynamic Retrievals TROPoe v0.19 / Derived Data

This dataset contains daily files with thermodynamic profiles retrieved with the optimal estimation physical retrieval TROPoe v0.19 (Turner and Löhnert, 2014; Turner and Blumberg, 2019; Turner and Löhnert, 2021). The profiles are retrieved every 10 minutes from instantaneous observations from the NREL ASSIST-II (SN 12) infrared spectrometer. Observations are noise-filtered but not averaged in time to minimize errors due to non-uniform clouds. Additional input data in TROPoe are cloud base height from the collocated NREL upgraded Galion lidar (Newsom et al., 2019), and surface temperature, relative humidity, and pressure from the collocated PNNL met tower. The full pipeline to run the retrieval is available at https://github.com/StefanoWind/TROPoe_processor. In addition to these temporally resolved input data, TROPoe requires an a priori dataset (prior) that provides mean climatological estimates of thermodynamic profiles and specifies how temperature and humidity covary with height as an input (for details see, e.g., Djalalova et al., 2022). The prior is a key component of the retrieval and provides a constraint on the ill-posed inversion problem. A monthly prior was computed from operational radiosonde launches at Upton, NY.

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BLOC Site - ASSIST Thermodynamic Retrievals TROPoe v0.18 / Derived Data

This dataset contains daily files with thermodynamic profiles retrieved with the optimal estimation physical retrieval TROPoe (Turner and Löhnert 2014; Turner and Blumberg 2019; Turner and Löhnert 2021). This is a post-processed dataset and recommended for use. The profiles are retrieved every 10 minutes from instantaneous radiances observed with an Atmospheric Sounder Spectrometer by Infrared Spectral Technology (ASSIST, Michaud-Belleau et al. 2025) operated by NOAA Physical Sciences Laboratory (PSL) on Block Island for WFIP3. The spectral bands used in the retrieval are in the wavenumber range from 612 - 905.4 cm-1 and are specified in Turner and Löhnert (2021). Additional input data in TROPoe are cloud base height from a collocated ceilometer operated by NOAA GML and temperature, water vapor mixing ratio, and pressure from a collocated surface tower operated by NOAA PSL. In addition to these temporally resolved input data, TROPoe requires an a priori dataset (prior) that provides mean climatological estimates of thermodynamic profiles and specifies how temperature and humidity covary with height as an input (for details see, e.g., Djalalova et al. 2022). The prior is a key component of the retrieval and provides a constraint on the ill-posed inversion problem. A monthly prior was computed from operational radiosonde launches at Upton, NY. The TROPoe docker container (version 0.18) is available from Docker Hub at https://hub.docker.com/r/davidturner53/tropoe/tags, and the source code code is available in the GitHub repository https://github.com/OAR-atmospheric-observations/TROPoe.

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NANT Site - ASSIST Thermodynamic Retrievals TROPoe v0.18 / Derived Data

This dataset contains daily files with thermodynamic profiles retrieved with the optimal estimation physical retrieval TROPoe (Turner and Löhnert 2014; Turner and Blumberg 2019; Turner and Löhnert 2021). This is a post-processed dataset and recommended for use. The profiles are retrieved every 10 minutes from instantaneous radiances observed with an Atmospheric Sounder Spectrometer by Infrared Spectral Technology (ASSIST, Michaud-Belleau et al. 2025) operated by NOAA Physical Sciences Laboratory (PSL) on Nantucket Island for WFIP3. The spectral bands used in the retrieval are in the wavenumber range from 612 - 905.4 cm-1 and are specified in Turner and Löhnert (2021). Additional input data in TROPoe are cloud base height from a collocated ceilometer operated by NOAA GML and temperature, water vapor mixing ratio, and pressure from a collocated surface tower operated by NOAA PSL. In addition to these temporally resolved input data, TROPoe requires an a priori dataset (prior) that provides mean climatological estimates of thermodynamic profiles and specifies how temperature and humidity covary with height as an input (for details see, e.g., Djalalova et al. 2022). The prior is a key component of the retrieval and provides a constraint on the ill-posed inversion problem. A monthly prior was computed from operational radiosonde launches at Upton, NY. The TROPoe docker container (version 0.18) is available from Docker Hub at https://hub.docker.com/r/davidturner53/tropoe/tags, and the source code code is available in the GitHub repository https://github.com/OAR-atmospheric-observations/TROPoe.

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FC Site 4.0 - NLR Thermodynamic profiler (ASSIST II-11) Thermodynamic Retrievals TROPoe

This dataset contains daily files with thermodynamic profiles retrieved with the optimal estimation physical retrieval TROPoe v0.19 (Turner and Löhnert 2014; Turner and Blumberg 2019; Turner and Löhnert 2021). The profiles are retrieved every 10 minutes from instantaneous observations from the NLR ASSIST II infrared spectrometer. Observations are noise-filtered but not averaged in time to minimize errors due to non-uniform clouds. Additional input data in TROPoe are cloud base height (CBH) from co-located scanning lidar. The full pipeline for running the retrieval is available at https://github.com/StefanoWind/TROPoe_processor. Met data was not ingested. In addition to these temporally resolved input data, TROPoe requires an a priori dataset (prior) that provides mean climatological estimates of thermodynamic profiles and specifies how temperature and humidity covary with height as an input (for details see, e.g., Djalalova et al. 2022). The prior is a key component of the retrieval and provides a constraint on the ill-posed inversion problem. A monthly prior was computed from operational radiosonde launches in Denver, CO.

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Microwave Radiometer

This dataset contains daily files with thermodynamic profiles retrieved with the optimal estimation physical retrieval TROPoe (Turner and Löhnert 2014; Turner and Blumberg 2019; Turner and Löhnert 2021). The profiles are retrieved every 10 minutes from instantaneous brightness temperature measurements at 35 channels observed with a microwave radiometer MP3000A operated by UND on the Barge for WFIP3. Additional input data in TROPoe are cloud base height from a collocated ceilometer operated by NOAA GML and temperature, water vapor mixing ratio, and pressure from a sensor attached to the MWR housing. In addition to these temporally resolved input data, TROPoe requires an a priori dataset (prior) that provides mean climatological estimates of thermodynamic profiles and specifies how temperature and humidity covary with height as an input (for details see, e.g., Djalalova et al. 2022). The prior is a key component of the retrieval and provides a constraint on the ill-posed inversion problem. A monthly prior was computed from operational radiosonde launches at Upton, NY.

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NREL ASSIST Rhode Island / Thermodynamic retrievals TROPoe

This dataset contains daily files with thermodynamic profiles retrieved with the optimal estimation physical retrieval TROPoe (Turner and Löhnert 2014; Turner and Blumberg 2019; Turner and Löhnert 2021). The profiles are retrieved every 10 minutes from instantaneous observations from the NREL ASSIST-II (SN 11) infrared spectrometer. Observations are noise-filtered but not averaged in time to minimize errors due to non-uniform clouds. Additional input data in TROPoe are cloud base height from a collocated NREL Upgraded Galion lidar #1212-60 and temperature, RH, and pressure from collocated PNNL met station. The lidar beta is used to estimate the cloud base height through a modified algorithm by Newsom et al., 2019 used at ARM SGP. The full pipeline for running the retrieval is available at https://github.com/StefanoWind/TROPoe_processor. In addition to these temporally resolved input data, TROPoe requires an a priori dataset (prior) which provides mean climatological estimates of thermodynamic profiles and specifies how temperature and humidity covary with height as an input (for details see e.g. Djalalova et al. 2022). The prior is a key component of the retrieval and provides a constraint on the ill-posed inversion problem. A monthly prior was computed from operational radiosonde launches at Upton, NY.

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The Psyche Gamma-Ray and Neutron Spectrometer

A Gamma-Ray and Neutron Spectrometer (GRNS) instrument has been developed as part of the science payload for NASA’s Discovery Program Psyche mission to the M-class asteroid (16) Psyche. The GRNS instrument is designed to measure the elemental composition of Psyche with the goal to understand the origin of this mysterious, potentially metal-rich planetary body. The GRNS will measure the near-surface abundances for the elements Ni, Fe, Si, K, S, Al, and Ca, as well as the spatial distribution of Psyche’s metal-to-silicate fraction (or metal fraction). These measurements address three of the five Psyche mission science objectives: determine if Psyche is a core; determine whether small metal bodies incorporate light elements into the metal phase; and determine whether Psyche was formed under reducing conditions. The Gamma-Ray Spectrometer (GRS) uses a cryocooled, high-purity Ge (HPGe) sensor to detect cosmic-ray generated gamma rays in the 60 to 9000-keV energy range. The HPGe sensor is surrounded by a borated plastic anticoincidence shield that provides three functions: active background rejection from charged particle interactions in the HPGe sensor; fast neutron measurements; and direct measurements of the incident galactic cosmic ray flux. The Neutron Spectrometer (NS) uses three 3 He gas proportional sensors, each with different material wraps to measure thermal (<0.4 eV), low-energy epithermal (0.4 eV to 1 keV), and high-energy epithermal (up to 100 keV) neutrons. This paper provides an overview of the Psyche GRNS, including: its science and measurement objectives; the design of the instrument hardware, software, and operation; pre-launch performance measurements and its initial performance in space; and an overview of its data products and expected operation for different Psyche mission phases.

Engineering - Instrumentation related to nuclear s↗

Developing Sample Management Tools for the Irradiation Test Area (ITA)

The ITA Data Manager (IDM) has been ported from CERN’s Proton Irradiation Facility (IRRAD), where it was used previously as the IRRAD Data Manager (IDM), in order to meet the data management and sample tracking needs of the Irradiation Test Area (ITA), a newly developed facility at Fermilab (launching Fall 2020) operating under the Fermilab Test Beam Facility.

43 PARTICLE ACCELERATORS↗

Flexible Pilot Jobs Framework for Distributed High Throughput Computing

Experimental particle physics has been at the forefront of analyzing the world’s largest datasets for decades. The high-energy physics (HEP) community was among the first to develop suitable software and computing tools for this purpose. GlideinWMS is a Glidein-based workload management system whose purpose is to provide experiments like CMS at CERN, DUNE at Fermilab, and others, a way to access and efficiently use vast amounts of computing resources. This system wants to provide a simple way to submit jobs to a set of computing resources, that will be provided to users behind the scenes. Glideins are the pilot jobs executed on the worker nodes at the grid sites, performing operations such as hardware detection, environment setup, and error handling. After all these operations, they will launch the actual user job. Many grid sites are supported, such as shared clusters, Google CE, and AWS. My internship aimed to design and code a flexible pilot jobs framework that will replace the one used by GlideinWMS, developing a modular and flexible skeleton of the Glidein and adding further functionalities. My project also focused on the application of machine learning techniques as support to this management system.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Initial in-orbit operation of the soft X-ray spectrometer Resolve onboard the X-ray imaging and spectroscopy mission satellite

The X-Ray Imaging and Spectroscopy Mission satellite was launched on September 6, 2023 (UT). Its Resolve instrument is a high-resolution X-ray spectrometer enabled by a microcalorimeter array thermally anchored to a 50-mK heat sink. Many sensitive, critical sub-systems comprise Resolve, including a multistage cryogenic cooling system, thin-film aperture filters, low-noise electronics, on-board signal processing, and several sources of X-rays for calibration. We summarize the initial on-orbit power-on and checkout of Resolve that commenced immediately after launch. Soon after launch, the cryocoolers were activated, and their operation was successfully established. On October 9, 2023, the first cycle of the adiabatic demagnetization refrigerator was carried out, bringing the sensors to their steady-state operational temperatures. Following this, the energy resolution at 5.9 keV was successfully measured. The energy scale of the system is highly sensitive to the thermal environment surrounding both the sensors and their analog electronics. Gain correction was performed using reference X-ray lines from onboard calibration sources. To optimize cooler frequency settings, noise spectra were collected across a range of frequencies, and the most suitable frequency pair was selected based on the in-orbit environment. During the final phase of the checkout, an attempt was made to open the gate valve, which is designed to protect the Dewar’s interior from external pressure during ground operations and launch. Unfortunately, this attempt was unsuccessful. As a result, the checkout process was temporarily paused, and a stable operational strategy was subsequently developed to enable Resolve to function effectively with the gate valve remaining closed.

X-ray micro-calorimeter↗

Sandia National Laboratories Annual Site Environmental Report, 2019: Tonopah Test Range, Nevada and Kaua'i Test Facility, Hawai'i

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the United States Department of Energy (DOE) National Nuclear Security Administration. The National Nuclear Security Administration’s Sandia Field Office administers the contract and oversees contractor operations at Sandia National Laboratories, Tonopah Test Range (SNL/TTR) in Nevada and Sandia National Laboratories, Kaua‘i Test Facility (SNL/KTF) in Hawai‘i. Activities at SNL/TTR are conducted in support of DOE weapons programs and have operated at the site since 1957. SNL/KTF has operated as a rocket preparation launching and tracking facility since 1962. DOE and its management and operating contractor are committed to safeguarding the environment, assessing sustainability practices, and ensuring the validity and accuracy of the monitoring data presented in this Annual Site Environmental Report. This report summarizes the environmental protection, restoration, and monitoring programs in place at SNL/TTR and SNL/KTF during calendar year 2019. Environmental topics include air quality, ecology, environmental restoration, oil storage, site sustainability, terrestrial surveillance, waste management, water quality, and implementation of the National Environmental Policy Act. This report is prepared in accordance with and as required by DOE O 231.1B, Admin Change 1, Environment, Safety, and Health Reporting, and has been approved for public distribution.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

2020 Annual Site Environmental Report for Sandia National Laboratories, Tonopah Test Range, Nevada, and Kaua'i Test Facility, Hawai'i

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration. The National Nuclear Security Administration’s Sandia Field Office administers the contract and oversees contractor operations at Sandia National Laboratories, Tonopah Test Range (SNL/TTR) in Nevada and Sandia National Laboratories, Kaua‘i Test Facility (SNL/KTF) in Hawai‘i. Activities at SNL/TTR are conducted in support of U.S. Department of Energy weapons programs and have operated at the site since 1957. SNL/KTF has operated as a rocket preparation launching and tracking facility since 1962. The U.S. Department of Energy and its management and operating contractor are committed to safeguarding the environment, assessing sustainability practices, and ensuring the validity and accuracy of the monitoring data presented in this Annual Site Environmental Report. This report summarizes the environmental protection, restoration, and monitoring programs in place at SNL/TTR and SNL/KTF during calendar year 2020. Environmental topics include air quality, ecology, environmental restoration, oil storage, site sustainability, terrestrial surveillance, waste management, water quality, and implementation of the National Environmental Policy Act. This report is prepared in accordance with and as required by DOE O 231.1B, Admin Change 1, Environment, Safety and Health Reporting , and has been approved for public distribution.

54 ENVIRONMENTAL SCIENCES↗

2022 Annual Site Environmental Report for Sandia National Laboratories, Kaua'i Test Facility, Hawai'i

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the. U.S. Department of Energy’s National Nuclear Security Administration. The National Nuclear Security Administration’s Sandia Field Office administers the contract and oversees contractor operations at the Sandia National Laboratories Kaua'i Test Facility in Hawai'i. Activities at the site are conducted in support of U.S. Department of Energy weapons programs., and the site has operated as a rocket preparation launching and tracking facility since 1962. The U.S. Department of Energy and its management and operating contractor are committed to safeguarding the environment, assessing sustainability practices, and ensuring the validity and accuracy of the monitoring data presented in this annual site environmental report. This report summarizes the environmental protection, restoration, and monitoring programs in place at Sandia National Laboratories, Kaua'i Test Facility, during calendar year 2022. Environmental topics include cultural resource management, chemical management, air quality, meteorology, ecology, oil storage, site sustainability, terrestrial surveillance, waste management, water quality, wastewater discharge, and implementation of the National Environmental Policy Act. This report is prepared in accordance with and as required by DOE O 231.1B, Admin Change 1, Environment, Safety and Health Reporting and has been approved for public distribution.

54 ENVIRONMENTAL SCIENCES↗

2023 Annual Site Environmental Report for Sandia National Laboratories, Kaua‘i Test Facility, Hawai‘i

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration. The National Nuclear Security Administration’s Sandia Field Office administers the contract and oversees contractor operations at the Sandia National Laboratories Kaua‘i Test Facility in Hawai‘i. Activities at the site are conducted in support of U.S. Department of Energy weapons programs, and the site has operated as a rocket preparation launching and tracking facility since 1962. The U.S. Department of Energy and its management and operating contractor are committed to safeguarding the environment, assessing sustainability practices, and ensuring the validity and accuracy of the monitoring data presented in this annual site environmental report. This report summarizes the environmental protection, restoration, and monitoring programs in place at Sandia National Laboratories, Kaua‘i Test Facility, during calendar year 2023. Environmental topics include cultural resource management, chemical management, air quality, meteorology, ecology, oil storage, site sustainability, terrestrial surveillance, waste management, water quality, wastewater discharge, and implementation of the National Environmental Policy Act. This report is prepared in accordance with and as required by DOE O 231.1B, Admin Change 1, Environment, Safety and Health Reporting, and has been approved for public distribution.

54 ENVIRONMENTAL SCIENCES↗

SuperCam Calibration Targets: Design and Development

Abstract SuperCam is a highly integrated remote-sensing instrumental suite for NASA’s Mars 2020 mission. It consists of a co-aligned combination of Laser-Induced Breakdown Spectroscopy (LIBS), Time-Resolved Raman and Luminescence (TRR/L), Visible and Infrared Spectroscopy (VISIR), together with sound recording (MIC) and high-magnification imaging techniques (RMI). They provide information on the mineralogy, geochemistry and mineral context around the Perseverance Rover. The calibration of this complex suite is a major challenge. Not only does each technique require its own standards or references, their combination also introduces new requirements to obtain optimal scientific output. Elemental composition, molecular vibrational features, fluorescence, morphology and texture provide a full picture of the sample with spectral information that needs to be co-aligned, correlated, and individually calibrated. The resulting hardware includes different kinds of targets, each one covering different needs of the instrument. Standards for imaging calibration, geological samples for mineral identification and chemometric calculations or spectral references to calibrate and evaluate the health of the instrument, are all included in the SuperCam Calibration Target (SCCT). The system also includes a specifically designed assembly in which the samples are mounted. This hardware allows the targets to survive the harsh environmental conditions of the launch, cruise, landing and operation on Mars during the whole mission. Here we summarize the design, development, integration, verification and functional testing of the SCCT. This work includes some key results obtained to verify the scientific outcome of the SuperCam system.

Manrique, J. A. (ORCID:0000000220532819)↗

Effect of controlled magnetic island bifurcation on electron diffusion

Magnetic islands strongly influence cross-field electron transport in magnetized plasmas. In particular, bifurcations of the island topology modify the number and location of O-points, X-points, and separatrix boundaries, thereby altering diffusion pathways. In recent DIII-D experiments, external magnetic perturbations were used to rotate and periodically bifurcate the island on the q = 2 surface, causing a switchback between a q = 2/1-dominated structure and a narrower q = 4/2-dominated structure. To investigate how this topological change affects electron transport, we employ the field line tracing code TRIP3D with an implemented collisional operator. Thermal, tracer electrons launched from O-points, X-points, and outside separatrix boundaries reveal distinct diffusion regimes, including classical, subdiffusive, and superdiffusive behavior, depending on both the dominant island mode and launch location. These results suggest that island bifurcation can alter electron diffusion across rational surfaces, with direct implications for particle confinement. While the present work emphasizes diffusion as a general framework, the findings provide insight into the conditions under which electron trapping into an island or stochastization of the island's separatrix can enable additional mechanisms, such as the generation of energetic electrons.

DIII-D↗

Toward Understanding the Differences between Mesoscale and Large-Eddy Simulations of Tropical Cyclones

In this work, we investigate the ability of mesoscale and large-eddy simulation (LES) model configurations to predict the mean wind speed profile within the boundary layer of tropical cyclones (TCs). To this end, we perform idealized simulations of five hypothetical intense storms ranging from categories 1 to 5 on the Saffir–Simpson scale and extract time-averaged quantities near the eyewall region. We compare the model-generated data against mean wind speed profiles compiled from dropsondes launched from reconnaissance aircraft operating in the North Atlantic basin. Our analysis shows that mesoscale- and LES-generated mean wind fields display important differences in the boundary layer, including the magnitude of shear as well as the height where their low-level wind speed maxima are located. In addition, a comparison between the two model configurations with the dropsonde data shows that both modeling approaches are unable to capture the typical structure of mean winds in the lower part of the TC boundary layer (10–500 m), calling into question the use of simulations of near-axisymmetric storms for investigating the wind structure of past events. To better understand these differences, we conduct a momentum-budget analysis and show that modeled turbulent fluxes are underestimated in the mesoscale boundary layer parameterization compared to the LES model. Based on the analysis of the horizontal turbulent fluxes and their potential impact on mean flow quantities, a TC-specific boundary layer parameterization may be needed.

17 WIND ENERGY↗