Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “REMOTE AREAS”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

CEBAF Accelerator Tunnel Robot Project

Advancements in the field of robotics allow for the use of remotely controlled robots to perform tasks that have typically required human intervention. Jefferson Lab has explored the possibilities of robots placed in the accelerator tunnel to perform remote inspections that would otherwise require powering down equipment and completing lengthy radiological surveys that impact beam operations. A robotic solution ? driven by a human operator ? could not only reduce accelerator down time but also support the Lab's radiation exposure policy (known as "ALARA" - As Low As Reasonably Acceptable) by handling routine tunnel and beamline investigations in place of a human being. However, operating a remote device in a radioactive, high electronic-noise area is not a trivial task and drop-in solutions are rarely as simple as they seem. We will present the past prototypes that were tested as well follow-on technology developed from the project. We will also briefly survey current applications of robots at accelerator facilities with an eye toward future applications.

McGuckin, Theodore↗
DOE OSTI2019

A Gamma Assay System for Characterizing Excavated Soil with High {sup 137}Cs and {sup 90}Sr Contamination - 19460

We report on the recent development of a remote gamma-assay system for the measurement and characterization of high-activity soil excavated as part of an ongoing remediation project. The soil below a hot cell in our customer's facility has been contaminated with high concentrations of radionuclides {sup 137}Cs and {sup 90}Sr over the past several decades. The contaminated soil is to be remotely excavated from beneath the hot cell floor, to a depth of several feet, and placed in steel-walled waste bins for assay and disposition. The project requires measuring the {sup 137}Cs activity to a minimum detectable concentration (MDC) of 1 micro curie per gram. The high dose-rate of the material and the expectation of high Bremsstrahlung background, due to an unknown ratio of {sup 90}Sr admixture with the {sup 137}Cs, present unique measurement challenges. A novel assay system was designed to make measurements through a small access port in a 4-foot thick concrete wall isolating operators from the high-dose excavation area. Waste bins filled with soil are placed by a remotely operated crane onto an automated turntable, and initial dose measurements are taken for all bins. When excavation has proceeded to the point that dose rates below 20 Rad/hr on contact are reached, gamma spectroscopy will be used to characterize the {sup 137}Cs content. Gamma assay is performed with a 1 cm{sup 3} CZT detector in a collimated tungsten shield, which is extended through the access port toward the side of the bin by means of a seven foot long aluminum pipe. Each of the four sides of the bin is assayed in a discrete measurement, and the individual segments and summed result are reported. Canberra's NDA2000 software is used to collect and analyze the spectroscopic data and to control the turntable movement during the assay. The system is expected to meet the required MDC limits within a forty minute assay time under the most adverse conditions anticipated, with total measurement uncertainty of less than 25%. We describe in this paper the design and construction of the assay system, its calibration using the ISOCS software, and the evaluation of performance estimates. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Studying drought-induced forest mortality using high spatiotemporal resolution evapotranspiration data from thermal satellite imaging

Drought can have pervasive and wide-spread impacts to forest health, as evidenced in several severe events occurring over the recent decades. Extensive forest die-off due to drought can impair the ecological functioning of forests, impacting habitat, water yield and quality from forested lands, and altering forest fire dynamics and intensity. Satellite remote sensing provides an effective means for detecting and monitoring spatial patterns of forest mortality over large areas, exploiting free and open long-term image archives available at a range in spatial and temporal resolutions. While remotely sensed surface reflectances and vegetation indices have been widely used to study optical response of forest canopies to drought events, retrievals of evapotranspiration (ET) derived from thermal satellite imagery – particularly at resolutions approaching crown scale - can provide insights into cumulative tree stresses that can incite disease and trigger mortality. In this study, we applied a multi-sensor satellite data fusion approach to estimate daily 30-m resolution ET and an associated Evaporative Stress Index (ESI) to study drought-induced mortality in a temperate forest at the Missouri Ozark AmeriFlux (MOFLUX) site, located in the central United States. The study covered the period from 2010 to 2014, including an exceptional drought year of 2012. Modeled ET agreed well with eddy flux measurements from the MOFLUX tower, with average monthly relative errors of 15%. Plot-scale ESI, describing temporal anomalies in the ratio of actual-to-reference ET, was used as an index of relative forest health to investigate relationships between forest mortality and drought severity. ESI showed good agreement with observed predawn leaf water potential, especially during the drought year. Furthermore, plot-scale ESI was also correlated with the subsequent year's tree mortality, suggesting the importance of considering the forest health condition prior to drought when studying drought-induced forest impacts. This study demonstrates the utility of multi-year ET remote sensing data at the stand or plot scale as an indicator of forest health and as a predictor of future mortality due to drought.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Housedon-Hill - A ChemCam/RMI mega mosaic to investigate distant features

The ChemCam Remote Microscopic Imager (RMI) onboard Curiosity was originally designed to document the tiny areas analyzed by ChemCam’s laser-induced breakdown spectroscopy (LIBS) technique on rocks at few meters distance around the rover. The RMI produces 1024 x 1024 pixel black and white images directly from ChemCam’s telescope focal plane. Early in the mission, it was recognized that, thanks to its powerful optics, RMI could also play a role as a long-distance reconnaissance tool, complementing other cameras on the remote sensing mast, and taking advantage of its very long 700 mm focal length. Imaging areas several kilometers from the rover provides pictures that are very complementary to orbital observations and gives a more human-like, ground-based perspective. Between sols 2878 and 2921, Curiosity stayed parked at the same place to perform various rock sampling analyses. This opportunity was used to target very distant areas of interest, daily building an RMI mosaic of 216 overlapping images covering an area ranging from the bottom layers of Mount Sharp to the edge of Vera Rubin Ridge. This product is so far the largest RMI mosaic acquired during the entire mission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Integration of energy storage with diesel generation in remote communities

Highlights Battery energy storage may improve energy efficiency and reliability of hybrid energy systems composed by diesel and solar photovoltaic power generators serving isolated communities. In projects aiming update of power plants serving electrically isolated communities with redundant diesel generation, battery energy storage can improve overall economic performance of power supply system by reducing fuel usage, decreasing capital costs by replacing redundant diesel generation units, and increasing generator system life by shortening yearly runtime. Fast-acting battery energy storage systems with grid-forming inverters might have potential for improving drastically the reliability indices of isolated communities currently supplied by diesel generation. Abstract This paper will highlight unique challenges and opportunities with regard to energy storage utilization in remote, self-sustaining communities. The energy management of such areas has unique concerns. Diesel generation is often the go-to power source in these scenarios, but these systems are not devoid of issues. Without dedicated maintenance crews as in large, interconnected network areas, minor interruptions can be frequent and invasive not only for those who lose power, but also for those in the community that must then correct any faults. Although the immediate financial benefits are perhaps not readily apparent, energy storage could be used to address concerns related to reliability, automation, fuel supply concerns, generator degradation, solar utilization, and, yes, fuel costs to name a few. These ideas are shown through a case study of the Levelock Village of Alaska. Currently, the community is faced with high diesel prices and a difficult supply chain, which makes temporary loss of power very common and reductions in fuel consumption very impactful. This study will investigate the benefits that an energy storage system could bring to the overall system life, fuel costs, and reliability of the power supply. The variable efficiency of the generators, impact of startup/shutdown process, and low-load operation concerns are considered. The technological benefits of the combined system will be explored for various scenarios of future diesel prices and technology maintenance/replacement costs as well as for the avoidance of power interruptions that are so common in the community currently. Graphic abstract Discussion In several cases, energy storage can provide a means to promote energy equity by improving remote communities’ power supply reliability to levels closer to what the average urban consumer experiences at a reduced cost compared to transmission buildout. Furthermore, energy equity represents a hard-to-quantify benefit achieved by the integration of energy storage to isolated power systems of under-served communities, which suggests that the financial aspects of such projects should be questioned as the main performance criterion. To improve battery energy storage system valuation for diesel-based power systems, integration analysis must be holistic and go beyond fuel savings to capture every value stream possible.

25 ENERGY STORAGE↗
DOE OSTI2023

Evaluation of E3SM land model snow simulations over the western United States

Abstract. Seasonal snow has crucial impacts on climate, ecosystems, and humans, but it is vulnerable to global warming. The land component (ELM) of the Energy Exascale Earth System Model (E3SM) mechanistically simulates snow processes from accumulation, canopy interception, compaction, and snow aging to melt. Although high-quality field measurements, remote sensing snow products, and data assimilation products with high spatio-temporal resolution are available, there has been no systematic evaluation of the snow properties and phenology in ELM. This study comprehensively evaluates ELM snow simulations over the western United States at 0.125∘ resolution during 2001–2019 using the Snow Telemetry (SNOTEL) in situ networks, MODIS remote sensing products (i.e., MCD43 surface albedo product), the spatially and temporally complete (STC) snow-covered area and grain size (MODSCAG) and MODIS dust and radiative forcing in snow (MODDRFS) products (STC-MODSCAG/STC-MODDRFS), and the snow property inversion from remote sensing (SPIReS) product and two data assimilation products of snow water equivalent and snow depth – i.e., University of Arizona (UA) and SNOw Data Assimilation System (SNODAS). Overall the ELM simulations are consistent with the benchmarking datasets and reproduce the spatio-temporal patterns, interannual variability, and elevation gradients for different snow properties including snow cover fraction (fsno), surface albedo (αsur) over snow cover regions, snow water equivalent (SWE), and snow depth (Dsno). However, there are large biases of fsno with dense forest cover and αsur in the Rocky Mountains and Sierra Nevada in winter, compared to the MODIS products. There are large discrepancies of snow albedo, snow grain size, and light-absorbing particle-induced snow albedo reduction between ELM and the MODIS products, attributed to uncertainties in the aerosol forcing data, snow aging processes in ELM, and remote sensing retrievals. Against UA and SNODAS, ELM has a mean bias of −20.7 mm (−35.9 %) and −20.4 mm (−35.5 %), respectively, for spring, and −13.8 mm (−27.8 %) and −10.2 mm (−22.2 %), respectively, for winter. ELM shows a relatively high correlation with SNOTEL SWE, with mean correlation coefficients of 0.69 but negative mean biases of −122.7 mm. Compared to the snow phenology of STC-MODSCAG and SPIReS, ELM shows delayed snow accumulation onset dates by 17.3 and 12.4 d, earlier snow end dates by 35.5 and 26.8 d, and shorter snow durations by 52.9 and 39.5 d, respectively. This study underscores the need for diagnosing model biases and improving ELM representations of snow properties and snow phenology in mountainous areas for more credible simulation and future projection of mountain snowpack.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The importance of delayed neutron precursors in gamma dose calculations for activated primary heat exchanger components in the Molten Salt Breeder Reactor

The Molten Salt Reactor (MSR) Multiphysics Applications technical area in the Nuclear Energy Advanced Modeling and Simulation program has supported the development of 3D Monte Carlo models of the Molten Salt Breeder Reactor (MSBR) over the last couple of years. This MSBR model was previously run with the Shift Monte Carlo code to perform radiation shielding calculations in the reactor cell area. The MSBR is a 2250 MWth (1000 MWe) liquid-fueled molten salt reactor design developed at Oak Ridge National Laboratory in the 1970s. Determining the source terms from activated primary heat exchanger (HX) components is important because delayed and prompt neutron fluxes incident on these components affect the dose rate in the primary HX maintenance areas. This information can be used in the development of remote handling procedures required during shutdown for maintenance. A methodology has been developed and is proposed in this paper to quantify the activated source term from the primary HX components as a result of the movement of the delayed neutron precursors in flowing primary fuel salt through the primary HXs in the MSBR. The goal of this research is to evaluate the gamma dose rates in the maintenance hatches above the primary HX using the activated HX source terms. The study showed that the gamma dose rates are approximately two orders of magnitudes higher when accounting for the neutron activation from the movement of delayed neutron precursors through the HXs than when flowing fuel is not considered. Thus, the movement of delayed neutron precursors must be taken into account for accurately predicting the neutron activation of primary loop components.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Dual Channel Dual Staging: Hierarchical and Portable Staging for GPU-Based In-Situ Workflow

In-situ workflows have emerged as an attractive approach for addressing data movement challenges at very large scales. Since GPU-based architectures dominate the HPC landscapes, porting these in-situ workflows, and, specifically, the inter-application data exchange, to GPU-based systems can be challenging. Technologies such as GPUDirect RDMA (GDR), which is typically used for I/O in GPU applications as an optimization that circumvents the CPU overhead, can be leveraged to support bulk data exchanges between GPU applications. However, current GDR design often lacks performance portability across HPC clusters built with different hardware configurations. Furthermore, the local CPU may also be effectively used as an auxiliary communication mechanism to offload data exchanges. In this paper, we present a dual channel dual staging approach for efficient, scalable, and performance-portable inter-application data exchange for in-situ workflows. This approach exploits the data access pattern within in-situ workflows along with the inherent execution asynchrony to accelerate data exchanges and, at the same time, improve performance portability. Specifically, the dual channel dual staging method leverages both the local CPU and the remote data staging server to build a hierarchical joint staging area and uses this staging area to transform blocking inter-application bulk data exchanges into best-effort local data movements between GPU and CPU. The dual channel dual staging is implemented as a portability extension of the Dataspaces-GPU staging framework. We present an experimental evaluation of its performance, portability, and scalability using this implementation on three leadership GPU clusters. The evaluation results demonstrate that the dual channel dual staging method saves up to 75% in data-exchange time compared to host-based, GDR, and alternate portable designs, while maintaining scalability (up to 512 GPUs) and performance portability across the three platforms.

Zhang, Bo [University of Utah]↗
DOE OSTI2020

Utah FORGE: Phase 3 Magnetotelluric (MT) Data

New high-quality tensor MT data at 122 sites, including the vertical magnetic field and utilizing ultra-remote referencing, have been acquired over the Utah FORGE project area. The results will be used to delineate the densities of faults and fractures in crystalline basement rocks, to define the heat sources, and to derive baseline 3D resistivity structure for later MT monitoring of temporal changes in resistivity structure following well stimulation in the EGS reservoir. There are three files here related to Utah FORGE magnetotelluric (MT) data acquisition and processing. The FORGE MT EDIs zip file contains the observed MT responses in industry-standard EDI format. For each site, there is an EDI response file that utilized a local independent reference for noise cancellation, and a file that utilized a distant reference cancelling noise associated with the DC transmission line of the Delta IPP passing down the west side of Milford Valley. These two site files could be merged as appropriate. The FORGE Model Cell Center file contains the model volume of the 3D Forge MT inversion for characterizing the resistivity structure in the project area. It was derived using finite element inversion methodology described in Wannamaker et al, in the attached FORGE Phase3 Geophysics paper, from the MT observation EDI files. It is ASCII format (.dat) and entries are defined at top of the file in a simple x-y-z-Rho listing in UTM coordinates. The element layers drape the topography so the Rho value layers are not purely horizontal slices. This greatly simplifies the listing.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Advancements in Multiphysics Microdepletion Analysis of an eVinci TM -like Microreactor Leveraging OpenMC-CRAB Workflow

Nuclear microreactors (MRs) are a class of nuclear reactor technology, characterized by reduced dimensions, modular design, and reduced power output in contrast to conventional Light Water Reactors (LWRs). MRs are proposed for supplying electricity and eventual process heat to remote locations, such as military installations and disaster-affected areas. Current research work sponsored by the US Department of Energy Microreactor Program (MRP) is devoted to the development of novel modeling and simulation tools to better support MR vendors and regulatory bodies. Notably, the NRC is projected to utilize the CRAB multiphysics software driver for executing both design and beyond-design-basis accident analyses. Furthermore, the NRC has been utilizing the MELCOR code to calculate mechanistic source terms during accidents. Since MELCOR relies on isotopic inventory and reactor temperature/power profiles under accident conditions, which theoretically can be derived from CRAB, the goal is to establish a comprehensive CRAB-MELCOR computational framework. Past work was focused on testing and demonstrating CRAB's capability to generate results that can be used to inform mechanistic source term calculations in MELCOR. In particular, a computational workflow leveraging OpenMC-generated microscopic cross sections and CRAB was first applied to perform multiphysics microscopic depletion calculation followed by an accident scenario for a stylized microreactor problem. In fiscal year 2024, the research work has been focused on applying the OpenMC-CRAB workflow, which was first tested in fiscal year 2023, to a realistic 3D heat-pipe cooled MR problem representative of the eVinci TM design. The latter computational problem was developed with inputs from WEC to conserve selected neutronic and thermal characteristics of the eVinci TM design without releasing proprietary data. The results of this simulation, encompassing isotopic inventory, power density distribution, and kinetic parameters, will inform both MELCOR and the WEC-developed FATE code for mechanistic source terms calculations. The results from the two codes will then be compared for code verification purposes. This report contains the design characteristics of the realist heat pipe cooled microreactor developed as a use-case for the verification exercise, and the current results for the multiphysics microscopic depletion performed with the OpenMC-CRAB workflow. The results include eigenvalue as a function of time, power distribution at EOL, in addition to nuclides inventory's time evolution and spatial distribution. Finally, we report improvements to the workflow efficiency achieved through a collaboration with the NEAMS programs. Through this collaborative effort, we were able to strongly decrease the computational time for the multiphysics microdepletion calculation (i.e., from 17.4 hours to 5.7 hours on 280 processors) in addition to simplifying the interface to generate isotopics spatial distribution utilizable by FATE and MELCOR. Future work, including the improvement of the current microscopic cross-sections' library and the simulation of an accident scenario at EOL, is also discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Development of an open-source regional data assimilation system in PEcAn v. 1.7.2: application to carbon cycle reanalysis across the contiguous US using SIPNET

Abstract. The ability to monitor, understand, and predict the dynamics of the terrestrial carbon cycle requires the capacity to robustly and coherently synthesize multiple streams of information that each provide partial information about different pools and fluxes. In this study, we introduce a new terrestrial carbon cycle data assimilation system, built on the PEcAn model–data eco-informatics system, and its application for the development of a proof-of-concept carbon “reanalysis” product that harmonizes carbon pools (leaf, wood, soil) and fluxes (GPP, Ra, Rh, NEE) across the contiguous United States from 1986–2019. We first calibrated this system against plant trait and flux tower net ecosystem exchange (NEE) using a novel emulated hierarchical Bayesian approach. Next, we extended the Tobit–Wishart ensemble filter (TWEnF) state data assimilation (SDA) framework, a generalization of the common ensemble Kalman filter which accounts for censored data and provides a fully Bayesian estimate of model process error, to a regional-scale system with a calibrated localization. Combined with additional workflows for propagating parameter, initial condition, and driver uncertainty, this represents the most complete and robust uncertainty accounting available for terrestrial carbon models. Our initial reanalysis was run on an irregular grid of ∼ 500 points selected using a stratified sampling method to efficiently capture environmental heterogeneity. Remotely sensed observations of aboveground biomass (Landsat LandTrendr) and leaf area index (LAI) (MODIS MOD15) were sequentially assimilated into the SIPNET model. Reanalysis soil carbon, which was indirectly constrained based on modeled covariances, showed general agreement with SoilGrids, an independent soil carbon data product. Reanalysis NEE, which was constrained based on posterior ensemble weights, also showed good agreement with eddy flux tower NEE and reduced root mean square error (RMSE) compared to the calibrated forecast. Ultimately, PEcAn's new open-source regional data assimilation framework provides a scalable workflow for harmonizing multiple data constraints and providing a uniform synthetic platform for carbon monitoring, reporting, and verification (MRV) as well as accelerating terrestrial carbon cycle research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

2022 Component Innovation Awardee: Pecos Wind Power

Distributed wind energy systems supply electricity for nearby homes and businesses, often in remote and rural regions. Systems capable of capturing energy in areas with low wind speeds make it possible to deploy these clean energy systems in many geographic locations. Pecos Wind Power's 85-kilowatt (kW) horizontal-axis PW85 wind turbine shows potential to reduce the levelized cost of energy by approximately 55% when compared to typical small wind systems while achieving utility-scale capacity factors of more than 40% in areas with lower wind speeds. To maximize cost competitiveness, the Pecos Wind Power turbine needs a blade optimized for low wind speeds. Through its 2022 Competitiveness Improvement Project (CIP) award, Pecos Wind Power and partner Wetzel Wind Energy Services will model, optimize, fabricate, and validate a 14.5-meter wind turbine blade made specifically for these applications. Three prior CIP awards supported Pecos Wind Power's initial development of the PW85 turbine.

CIP↗
DOE OSTI2019

Sampling Density in Regional Exploration and Environmental Geochemical Studies: A Review

A variety of factors contribute to the proper and efficient evaluation of geochemical programs including sampling medium, sample size and sample fraction, sampling density, digestion procedure, and analytical techniques. Among the aforementioned factors, sampling density is of great importance, affecting project ability to detect anomalous sites, which are either economically viable or environmentally hazardous. It is quite critical to have a sufficient number of samples to delineate geochemical anomalies or baselines and to reveal the relative variations in elemental concentrations in a study area. The resolution of the subsequent maps obtained by sampling greatly depends on sampling density. While a large number of samples may generate redundant data, a small number of samples smooth out the patterns and may completely miss anomalies. This review provides a platform for applied geochemists who desire to design a sampling scheme for a regional geochemical program and do not have the financial resources to perform an orientation survey, which will give them the necessary information for designing, according to project objectives, a cost-effective regional geochemical survey for their study area. It is advisable to integrate during the desktop study all available information, such as geological, structural, geophysical, remote sensing data and topographical data by using different data fusion algorithms to arrive at a sampling density fit-for-purpose of the target area. This in turn facilitates an effective spatial positioning of sample locations. Quantitative analyses of the efficiency of different sampling densities for delineating geochemical patterns have not been well documented, warranting more attention and research.

58 GEOSCIENCES↗
DOE OSTI2020

Framework for Analysis and Quantification of Wide-Area Control Resilience for Power Systems

Wide-area control helps damp the inter-area oscillations in modern power systems. However, compared to traditional local control, it is more vulnerable to cyber attacks due to its dependence on remote real-time-communicated measurements. In this paper, a formal mathematical framework for analyzing resilience of various wide-area controllers under adversarial scenarios is proposed. A novel resilience index based on the $\H_2$ norm of the post-attack closed-loop system is defined. Computation of such an index is, in general, challenging due to the combinatorial nature of the attack profiles and the bilinear nature of the problem. To address these difficulties, a gradient-based path-following-like solution is developed in this paper to solve a relaxed version of the original non-convex problem. Case studies on IEEE 39-bus system are performed to demonstrate the usage of the proposed framework.

Marinovici, Laurentiu D.↗
DOE OSTI2022

Estimating snow cover from high-resolution satellite imagery by thresholding blue wavelengths

We report the extent and duration of snow cover, a critical component of the hydrologic cycle and the global climate system, is expected to shift dramatically under climate change. Therefore, developing high-resolution assessments of snow cover change is crucial for estimating the impact of changing snow cover on watershed and ecosystems processes in cold regions. Remote sensing tools provide a powerful method for mapping snow-covered area (SCA) across a landscape. The most common method for estimating SCA utilizes the normalized difference snow index (NDSI), which relies on spectral measurements in the shortwave-infrared wavelengths (SWIR). NDSI can effectively estimate catchment- to regional-scale SCA, but it cannot be used to assess fine-scale SCA because of current limitations on the spatial resolution of satellite-derived SWIR measurements. Here, we map SCA using a threshold of blue wavelengths and high-resolution satellite imagery. The thresholding method, which we call the Blue Snow Threshold algorithm (BST), has previously been used with digital camera imagery. We refine and automate the algorithm for use with cloud-free high-resolution satellite imagery and find that the BST can be used to assess fine-scale SCA. For validation, we compared BST-derived estimates of SCA to a) airborne lidar surveys, b) Landsat fractional SCA, and c) snow disappearance dates from Snow Telemetry (SNOTEL) stations. When compared to airborne lidar surveys of SCA, the BST predicted SCA had a range of F-scores between 0.81 and 0.94 in four study areas in California and Colorado. We also found general agreement between SCA and snow disappearance at multiple SNOTEL sites across the western United States. Given the relatively recent availability of high-resolution satellite imagery with spectral measurements in the visible wavelengths but lacking in SWIR, the BST offers a reliable and easy-to-apply tool for examining fine-scale snow-related processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

A Review of Ice Particle Shapes in Cirrus formed In Situ and in Anvils

Results from 22 airborne field campaigns, including more than 10 million high–resolution particle images collected in cirrus formed in situ and in convective anvils, are interpreted in terms of particle shapes and their potential impact on radiative transfer. Emphasis is placed on characterizing ice particle shapes in tropical maritime and midlatitude continental anvil cirrus, as well as in cirrus formed in situ in the upper troposphere, and subvisible cirrus in the upper tropical troposphere layer. There is a distinctive difference in cirrus ice particle shapes formed in situ compared to those in anvils that are generated in close proximity to convection. More than half the mass in cirrus formed in situ are rosette shapes (polycrystals and bullet rosettes). Cirrus formed from fresh convective anvils is mostly devoid of rosette–shaped particles. However, small frozen drops may experience regrowth downwind of an aged anvil in a regime with RH ice > ~120% and then grow into rosette shapes. Identifiable particle shapes in tropical maritime anvils that have not been impacted by continental influences typically contain mostly single plate–like and columnar crystals and aggregates. Midlatitude continental anvils contain single–rimed particles, more and larger aggregates with riming, and chains of small ice particles when in a highly electrified environment. Here, the particles in subvisible cirrus are < ~100 μm and quasi–spherical with some plates and rare trigonal shapes. Percentages of particle shapes and power laws relating mean particle area and mass to dimension are provided to improve parameterization of remote retrievals and numerical simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Sensors of world’s largest digital camera snap first 3,200-megapixel images at SLAC

Vera C. Rubin Observatory will conduct the 10-year Legacy Survey of Space and Time (LSST), which will collect 60 petabytes of data to address some of the most pressing questions about the structure and evolution of the universe and the objects in it. LSST is designed to address four science areas: Understanding Dark Matter and Dark Energy Hazardous Asteroids and the Remote Solar System The Transient Optical Sky The Formation and Structure of the Milky Way Vera C. Rubin Observatory is a federal project jointly funded by the National Science Foundation and the Department of Energy Office of Science, with early construction funding received from private donations through the LSST Corporation. The NSF-funded LSST (now Rubin Observatory) Project Office for construction was established as an operating center under the management of the Association of Universities for Research in Astronomy (AURA). The DOE-funded effort to build the Rubin Observatory LSST Camera (LSSTCam) is managed by SLAC.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Detection and attribution of long-term and fine-scale changes in spring phenology over urban areas: A case study in New York State

Spring phenology plays an essential role in climate change, terrestrial ecosystem, and public health. Field-based monitoring and understanding of changes in spring phenology for long periods and in large regions are challenging due to the limited in-site observations. Space-based remotely sensed observations offer great potentials for monitoring decadal spring phenology changes from regional to global scales. However, the coarse-scale remotely sensed observations are insufficient to capture fine-scale spring phenology dynamics, especially in urban areas, and this makes it challenging for understanding the combined effects of climate change and urbanization on spring phenology. We derived the start of phenology season (SOS) in New York State using 30 m Landsat observations from 1990 to 2015 to understand the impact of the environment and urbanization on SOS. The results show that SOS for different years reveals heterogeneous spatial distribution. Most regions of New York State have been experiencing significant spring phenology changes in form of earlier onset of vegetation greening, ranging from 0.2 to 0.6 day/year during 1990 to 2015, and this trend varies slightly with latitudes and urbanization levels. Further, spatial correlation analysis shows that the increase in temperature and urbanization could both promote the advancement of SOS. However, the effect of urbanization (partial correlation coefficient (R) ranges from −0.289 to −0.542) on SOS is greater than the effect of temperature (R ranges from 0.006 to −0.192). The study generates a high spatio-temporal resolution spring phenology dataset for ecological, environmental and public health studies, especially in urban areas, and reveals the importance of better accounting for the urbanization effects when quantifying the SOS dynamics in phenology models.

Landsat↗