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At least 1,153 records · Page 64

Inventory and Probabilistic Function of Natural Hazards in the United States: July 19, 2018 - September 18, 2018

The U.S. Department of Energy's National Renewable Energy Laboratory (NREL) developed a standardized risk assessment process that considers the location-specific vulnerabilities and threats (climate-related as well as human-caused) at a site to generate a ranked list of organizational risks and associated mitigation options for reducing those risks. To support this effort, the Southern Climate Impacts Planning Program (SCIPP), a National Oceanic and Atmospheric (NOAA) Regional Integrated Sciences and Assessments (RISA) team, was selected to provide climate science expertise to develop a comprehensive inventory and probabilistic function of natural hazards (e.g., hurricanes, tornadoes, flooding, and sea level rise) for the entire United States by region. The inventory of climate-related hazards and the associated likelihood scores are incorporated into a companion risk assessment tool enabling standardized comparisons of risk at sites across the country.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Comprehensive Chemical Fingerprinting by Multidimensional GC and Supervised Machine Learning

This project leverages advances in machine learning based data analysis techniques and untargeted omic analytical methods to progress nuclear nonproliferation technologies beyond current capabilities. The developed approaches can be used to identify and detect complex chemical fingerprints of facilities of interest. These techniques have been developed for fields such as metabolomics and genomics but have not been applied to nuclear nonproliferation applications. Adaptation of these techniques for volatile organic compound analysis has far reaching application within the scientific community including environmental chemistry, atmospheric physics, and climate sciences.

97 MATHEMATICS AND COMPUTING↗

Lawrence Livermore National Laboratory Site Annual Environmental Report 2020

Lawrence Livermore National Laboratory (LLNL) is a premier research laboratory that is part of the National Nuclear Security Administration (NNSA) within the U.S. Department of Energy (DOE). As a national security laboratory, LLNL is responsible for ensuring that the nation’s nuclear weapons remain safe, secure, and reliable. The Laboratory also meets other pressing national security needs, including countering the proliferation of weapons of mass destruction and strengthening homeland security, and conducting major research in atmospheric, earth, and energy sciences, bioscience and biotechnology, and engineering, basic science, and advanced technology. The Laboratory is managed and operated by Lawrence Livermore National Security, LLC (LLNS), and serves as a scientific resource to the U.S. government and a partner to industry and academia.

54 ENVIRONMENTAL SCIENCES↗

Comprehensive Chemical Fingerprinting by Multidimensional GC and Supervised Machine Learning

This project leveraged advances in machine learning based data analysis techniques and untargeted analytical methods for organic analysis to progress nuclear nonproliferation technologies beyond current capabilities. The developed approaches can be used to detect and identify complex chemical fingerprints of facilities of interest. These techniques have been developed for fields such as metabolomics and genomics but have not been applied to nuclear nonproliferation applications. Adaptation of these techniques for volatile organic compound analysis has far reaching application within the scientific community including environmental chemistry, atmospheric physics, and climate sciences.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Lawrence Livermore National Laboratory (2022 Annual Site Environment Report (ASER))

Lawrence Livermore National Laboratory (LLNL) is a premier research laboratory that is part of the National Nuclear Security Administration (NNSA) within the U.S. Department of Energy (DOE). As a national security laboratory, LLNL is responsible for ensuring that the nation’s nuclear weapons remain safe, secure, and reliable. The Laboratory also meets other pressing national security needs including countering the proliferation of weapons of mass destruction, strengthening homeland security, and conducting major research in atmospheric, earth, and energy sciences, bioscience and biotechnology, and engineering, basic science, and advanced technology. The Laboratory is managed and operated by Lawrence Livermore National Security, LLC (LLNS) and serves as a scientific resource to the U.S. government and a partner to industry and academia.

54 ENVIRONMENTAL SCIENCES↗

Lidar - ESRL WindCube 200s, Wasco Airport - Reviewed Data

The available "Readme" file introduces the basics of the Doppler lidar data and offers a detailed description of the variables present in the data files. For those with any further questions about the data and its interpretation, contact either Alan Brewer ( ) or Sunil Baidar ( ). It is highly recommended to discuss any planned use of the data with National Oceanic and Atmospheric Administration-Chemical Sciences Division (NOAA-CSD) scientists. For more information, refer to the Readme file: "noaa-esrl-wascolidar-readme-1.pdf."

17 WIND ENERGY↗

Lidar - ESRL WindCube 200s, Arlington Airport - Reviewed Data

The available "readme" file introduces the basics of the Doppler lidar data and offers a detailed description of the variables present in the data files. For those with any further questions about the data and its interpretation, contact either Alan Brewer ( ) or Sunil Baidar ( ). It is highly recommended to discuss any planned use of the data with National Oceanic and Atmospheric Administration-Chemical Sciences Division (NOAA-CSD) scientists. For more information, refer to the Readme file: "noaa-esrl-arlingtonlidar-readme-1.pdf."

17 WIND ENERGY↗

Lidar - ESRL WindCube 200s, Wasco Airport - Processed Data

The available "Readme" file introduces the basics of the Doppler lidar data and offers a detailed description of the variables present in the data files. For those with any further questions about the data and its interpretation, contact either Alan Brewer ( ) or Sunil Baidar ( ). It is highly recommended to discuss any planned use of the data with National Oceanic and Atmospheric Administration-Chemical Sciences Division (NOAA-CSD) scientists. For more information, refer to the Readme file: "noaa-esrl-wascolidar-readme.docx."

17 WIND ENERGY↗

Exosphere Modeling of Proxima b: A Case Study of Photochemical Escape with a Venus-like Atmosphere

Exoplanets orbiting M dwarfs within habitable zones are exposed to stellar environments more extreme than that terrestrial planets experience in our solar system, which can significantly impact the atmospheres of the exoplanets and affect their habitability and sustainability. This study provides the first prediction of hot oxygen corona structure and the associated photochemical loss from a 1 bar CO 2 -dominated atmosphere of a Venus-like rocky exoplanet, where dissociative recombination of O 2 + ions is assumed to be the major source reaction for the escape of neutral O atoms and formation of the hot O corona (or exospheres) as on Mars and Venus. We employ a 3D Monte Carlo code to simulate the exosphere of Proxima Centauri b (PCb) based on the ionosphere simulated by a 3D magnetohydrodynamic model. Our simulation results show that variability of the stellar wind dynamic pressure over one orbital period of PCb does not affect the overall spatial structure of the hot O corona but contributes to the change in the global hot O escape rate that varies by an order of magnitude. The escape increases dramatically when the planet possesses its intrinsic magnetic fields as the ionosphere becomes more extended with the presence of a global magnetic field. Furthermore, the extended hot O corona may lead to a more extended H exosphere through collisions between thermal H and hot O, which exemplifies the importance of considering nonthermal populations in exospheres to interpret future observations.

79 ASTRONOMY AND ASTROPHYSICS↗

DTS data from SGP TBS

Distributed temperature-sensing data collected using a Silixa-XT DTS and 50/125 MM fiber. Data are calibrated using two water baths at the surface and an iMet aloft at the end of the fiber and tether. The data are then assigned an altitude for the TBS flight. Data collected prior to Febuary 11, 2020 were collected at the SGP Central Facility (CF). Data from 2/11/20 were collected with a Sensornet Oryx DTS at the E9 site, not at the CF. Data from May 2021 were collected with a Sensornet Oryx at the CF, and with a Silixa XT at the CF. Data from July 2021 were collected at the SGP CF, EF9, and EF36 with a Silixa XT. Data from October 2021 were collected at the SGP EF36 with a Silixa XT. Data from February 2022 were collected at the CF with a Silixa XT.

54 ENVIRONMENTAL SCIENCES↗