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At least 217 records · Page 12

Assessing the Geomorphic Evolution and Hydrographic Changes Induced by Winter Storms along the Louisiana Coast

The influence that cold front passages have on Louisiana coastal environments, including land loss and land building processes, has been the primary topic of this multidisciplinary research. This research has combined meteorological, remote sensing, and coastal expertise from the University of Wisconsin (UW) and Louisiana State University (LSU). Analyzed data sets include remotely sensed radiometric data (AVHRR on NOAA-12,13,14, Multispectral Atmospheric Mapping Sensor (MAMS) and MODIS Airborne Simulator (MAS) on NASA ER-2), U.S. Army Corps of Engineers (USACE) water level data, water quality data from the Coastal Studies Institute (CSI) at LSU, USACE river discharge data, National Weather Service (NWS) and CSI wind in sitzi measurements, geomorphic measurements from aerial photography (NASA ER-2 and Learjet), and CSI ground based sediment burial pipes (for monitoring topographic change along the Louisiana coast) and sediment cores. The work reported here-in is a continuation of an initial investigation into coastal Louisiana landform modification by cold front systems. That initial effort demonstrated the importance of cold front winds in the Atchafalaya Bay sediment plume distribution (Moeller et al.), documented the sediment transport and deposition process of the western Louisiana coast (Huh et al.) and developed tools (e.g. water types identification, suspended solids estimation) from multispectral radiometric data for application to the current study. This study has extended that work, developing a Geomorphic Impact Index (GI(sup 2)) for relating atmospheric forcing to coastal response and new tools to measure water motion and sediment transport.

Menzel, W. Paul↗

National Transonic Facility Characterization Status

This paper describes the current status of the characterization of the National Transonic Facility. The background and strategy for the tunnel characterization, as well as the current status of the four main areas of the characterization (tunnel calibration, flow quality characterization, data quality assurance, and support of the implementation of wall interference corrections) are presented. The target accuracy requirements for tunnel characterization measurements are given, followed by a comparison of the measured tunnel flow quality to these requirements based on current available information. The paper concludes with a summary of which requirements are being met, what areas need improvement, and what additional information is required in follow-on characterization studies.

Bobbitt, C., Jr.↗

Status of the National Transonic Facility Characterization

This paper describes the current activities at the National Transonic Facility to document the test-section flow and to support tunnel improvements. The paper is divided into sections on the tunnel calibration, flow quality measurements, data quality assurance, and implementation of wall interference corrections.

Bobbitt, C., Jr.↗

Status of the National Transonic Facility Characterization (Invited)

This paper describes the current activities at the National Transonic Facility to document the test-section flow and to support tunnel improvements. The paper is divided into sections on the tunnel calibration, flow quality measurements, data quality assurance, and implementation of wall interference corrections.

Bobbitt, C., Jr.↗

Advanced Laser Based Measurements in Porous Media Combustion

We present measurements using dual-pump dual-broadband coherent anti-Stokes Raman scattering spectroscopy (DP-DBB-CARS) inside a porous media burner. This work continues our previous measurements in such combustion systems. The existing setup was significantly modified with the aim of providing improved data quality and data rate, reduction of interferences and additional species information. These changes are presented and discussed in detail. The CARS technique was expanded to a dual-pump dual-broadband CARS system which in principle enables acquisition of temperatures together with relative H2/N2- and O2/N2- species concentrations. Experimental complexity was reduced by the use of a modified spectrometer enabling the detection of both signals, vibrational and rotational CARS, with only one detection system.

Tedder, Sarah A.↗

Community-Based Services that Facilitate Interoperability and Intercomparison of Precipitation Datasets from Multiple Sources

Over the past 12 years, large volumes of precipitation data have been generated from space-based observatories (e.g., TRMM), merging of data products (e.g., gridded 3B42), models (e.g., GMAO), climatologies (e.g., Chang SSM/I derived rain indices), field campaigns, and ground-based measuring stations. The science research, applications, and education communities have greatly benefited from the unrestricted availability of these data from the Goddard Earth Sciences Data and Information Services Center (GES DISC) and, in particular, the services tailored toward precipitation data access and usability. In addition, tools and services that are responsive to the expressed evolving needs of the precipitation data user communities have been developed at the Precipitation Data and Information Services Center (PDISC) (http://disc.gsfc.nasa.gov/precipitation or google NASA PDISC), located at the GES DISC, to provide users with quick data exploration and access capabilities. In recent years, data management and access services have become increasingly sophisticated, such that they now afford researchers, particularly those interested in multi-data set science analysis and/or data validation, the ability to homogenize data sets, in order to apply multi-variant, comparison, and evaluation functions. Included in these services is the ability to capture data quality and data provenance. These interoperability services can be directly applied to future data sets, such as those from the Global Precipitation Measurement (GPM) mission. This presentation describes the data sets and services at the PDISC that are currently used by precipitation science and applications researchers, and which will be enhanced in preparation for GPM and associated multi-sensor data research. Specifically, the GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) will be illustrated. Giovanni enables scientific exploration of Earth science data without researchers having to perform the complicated data access and match-up processes. In addition, PDISC tool and service capabilities being adapted for GPM data will be described, including the Google-like Mirador data search and access engine; semantic technology to help manage large amounts of multi-sensor data and their relationships; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion to various formats (e.g., netCDF, HDF, KML (for Google Earth)); visualization and analysis of Level 2 data profiles and maps; parameter and spatial subsetting; time and temporal aggregation; regridding; data version control and provenance; continuous archive verification; and expertise in data-related standards and interoperability. The goal of providing these services is to further the progress towards a common framework by which data analysis/validation can be more easily accomplished.

Liu, Zhong↗

Technologies and Methods Used at the Laboratory for Atmospheric and Space Physics (LASP) to Serve Solar Irradiance Data

The Laboratory for Atmospheric and Space Physics (LASP) at the University of Colorado in Boulder, USA operates the Solar Radiation and Climate Experiment (SORCE) NASA mission, as well as several other NASA spacecraft and instruments. Dozens of Solar Irradiance data sets are produced, managed, and disseminated to the science community. Data are made freely available to the scientific immediately after they are produced using a variety of data access interfaces, including the LASP Interactive Solar Irradiance Datacenter (LISIRD), which provides centralized access to a variety of solar irradiance data sets using both interactive and scriptable/programmatic methods. This poster highlights the key technological elements used for the NASA SORCE mission ground system to produce, manage, and disseminate data to the scientific community and facilitate long-term data stewardship. The poster presentation will convey designs, technological elements, practices and procedures, and software management processes used for SORCE and their relationship to data quality and data management standards, interoperability, NASA data policy, and community expectations.

Pankratz, Chris↗

NOAA-20 VIIRS on-Orbit Calibration Improvements

The NOAA-20 (N-20) VIIRS has successfully operated for more than two years since its launch in November 2017. Shortly after completing its initial instrument check-outs and post-launch testing (PLT) activities, the N-20 VIIRS sensor data records (SDR) achieved the beta, provisional, and validated maturity status in January, February, and April 2018, respectively. In this paper, we briefly describe the instrument on-orbit operation and calibration activities, provide an overall assessment of its on-orbit performance, and discuss the methodologies developed to maintain and improve sensor calibration and data quality. As illustrated in this paper, the N-20 VIIRS continues to perform with excellent stability, allowing high-quality environmental data records (EDR) to be generated from its well-calibrated SDR.

NOAA-20↗

Toward Comprehensive Uncertainty Predictions for Remote Imaging Spectroscopy

Remote imaging spectroscopy’s role in Earth science will grow in the coming decade as a series of globe-spanning spectroscopy missions launch from NASA, ESA, and other agencies. The nature of remote imaging spectroscopy will change, advancing from short regional studies to address global multi-year questions. The diversity of data will also grow with exposure to a wider range of biomes and atmospheric conditions. To execute these new investigations we must reconcile diverse observing conditions to derive consistent global maps. To this end, rig- orous uncertainty quantification and propagation enables an optimal synthesis of data accounting for observing conditions and data quality. Understanding data uncertainties is also important for principled hypothesis testing, information content assessment, and informed decision making by end users. We survey prior efforts in uncer- tainty quantification for imaging spectroscopy, and describe methods for validating the accuracy of uncertainty predictions. We conclude with a discussion of remaining challenges and promising avenues for future research.

Susiluoto, Jouni↗

Using global aerosol models and satellite data for air quality studies: Challenges and data needs

Aerosol particles, also known as PM2.5 (particle diameter less than 2.5 pm) and PM10 (particle diameter less than 10 pm), are one of the key atmospheric components that determines air quality. Yet, air quality forecasts for PM are still in their infancy and remain a challenging task. It is difficult to simply relate PM levels to local meteorological conditions, and large uncertainties exist in regional air quality model emission inventories and initial and boundary conditions. Especially challenging are periods when a significant amount of aerosol comes from outside the regional modeling domain through long-range transport. In the past few years, NASA has launched several satellites with global aerosol measurement capabilities, providing large-scale chemical weather pictures. NASA has also supported development of global models which simulate atmospheric transport and transformation processes of important atmospheric gas and aerosol species. I will present the current modeling and satellite capabilities for PM2.5 studies, the possibilities and challenges in using satellite data for PM2.5 forecasts, and the needs of future remote sensing data for improving air quality monitoring and modeling.

Chin, Mian↗

Increasing Efficiency at the NTF by Optimizing Model AoA Positioning

The National Transonic Facility (NTF) at NASA Langley Research Center (LaRC) is a national resource for aeronautical research and development. The government, military and private industries rely on the capability of this facility for realistic flight data. Reducing the operation costs and keeping the NTF affordable is essential for aeronautics research. The NTF is undertaking an effort to reduce the time between data points during a pitch polar. This reduction is being driven by the operating costs of a cryogenic facility. If the time per data point can be reduced, a substantial cost savings can be realized from a reduction in liquid nitrogen (LN2) consumption. It is known that angle-of-attack (AoA) positioning is the longest lead-time item between points. In January 2005 a test was conducted at the NTF to determine the cause of the long lead-time so that an effort could be made to improve efficiency. The AoA signal at the NTF originates from onboard instrumentation then travels through a number of different systems including the signal conditioner, digital voltmeter, and the data system where the AoA angle is calculated. It is then fed into a closed loop control system that sets the model position. Each process along this path adds to the time per data point affecting the efficiency of the data taking process. Due to the nature of the closed loop feed back AoA control and the signal path, it takes approximately 18 seconds to take one pitch pause point with a typical AoA increment. Options are being investigated to reduce the time delay between points by modifying the signal path. These options include: reduced signal filtering, using analog channels instead of a digital volt meter (DVM), re-routing the signal directly to the AoA control computer and implementing new control algorithms. Each of these has potential to reduce the positioning time and together the savings could be significant. These timesaving efforts are essential but must be weighed against possible loss of data quality. For example, a reduction in filtering can introduce noise into the signal and using analog channels could result in some loss of accuracy. Data quality assessments need to be performed concurrently with timesaving techniques since data quality parameters are essential in maintaining facility integrity. This paper will highlight time saving efforts being undertaken or studied at the NTF. It will outline the instrumentation and computer systems involved in setting of the model pitch attitude then suggest changes to the process and discuss how these system changes would effect the time between data points. It also discusses the issue of data quality and how the potential efficiency changes in the system could affect it. Lastly, it will discuss the possibility of using an open loop control system and give some pros and cons of this method.

Crawford, Bradley L.↗

Application of the BSRN Data in Validating the GEWEX SRB Data: Quality-Control and Resulting Available Monthly Means

The BSRN data have been used in validation of the satellite-based GEWEX SRB data, and the recent Release 4.0-IP data cover the 34-year period from July 1983 to June 2017. Here we focus on the validation of the shortwave monthly means from 1992 to 2017 against the BSRN Global 1. We first perform the BSRN-recommended quality-control on the original data. We then calculate the monthly-hourly means from which we calculate the monthly means. Twenty-four (24) monthly-hourly means are required to calculate a monthly mean. To guarantee the quality of the monthly mean, we also require that 95% or more hourly means be available in order for a monthly-hourly mean to be calculated. Since the above quality-control significantly reduces the number of available monthly means, we are curious how many monthly means we would get if we relax the quality-control, and how the resulting monthly means would compare with the GEWEX SRB data. In a version we experimented, only constant upper and lower bounds are imposed on various fluxes, and the original data are largely retained. We found that many more monthly means would be available, and the overall bias and RMS would not be significantly different from that of the strict quality-control. With the strict quality-control, if we let Avail (minimum percentage of available hourly means required for a monthly-hourly mean to be computed) change from 3.2% to 95%, the Bias/RMS/N change from -2.77/20.56/9756 to -0.35/13.41/4581, where N is the number of available monthly means, and Bias and RMS are in the unit of W/sq. m. On the other hand, with the lax quality-control, when Avail changes from 3.2% to 95%, the Bias/RMS/N change from -0.82/19.53/9819 to -0.21/14.41/5875. South Pole (SPO) is one of the sites we are particularly interested in. With the strict quality-control, and when Avail changes from 3.2% to 95%, the Bias/RMS/N change from 5.89/15.85/283 to 1.23/5.52/133; with the lax quality-control, the Bias/RMS/N change from 1.17/11.21/284 to 1.88/7.9/177.

Taiping Zhang↗

Deliverable 6.7-Final Technical Report: Development Summary and Evaluation of the Solar Uncertainty Integrator (SUNI) Software

The Data Quality and Uncertainty Integration Project was a three-year effort to address stakeholder needs for assessing solar radiation resource data quality based on existing tools for estimating radiometer measurement uncertainties and assessing post-measurement data quality. The annual research objectives for the project addressed a logical progression of effort needed to achieve the ultimate project goal of developing the Solar Uncertainty Integrator (SUNI) software. This final technical report summarizes the development process for achieving these key research objectives and addresses the outreach and code development efforts in the final year of the project to develop a new solar irradiance data uncertainty integration software package.

14 SOLAR ENERGY↗

ARM Cloud and Precipitation Measurements and Science Group (CPMSG) 2024 Workshop Report

The mission of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility is to improve the understanding and representation of cloud and aerosol processes and their interaction with the Earth's surface in Earth system models (ESMs) by providing comprehensive field observations and supporting advanced data analytics. The ARM Cloud and Precipitation Measurements and Science Group (CPMSG) was chartered in March 2019 to help improve the performance and scientific impact of ARM measurements of clouds and precipitation. The group aims to identify and address gaps in measurement capabilities, maximize the scientific impact of ARM data, and effectively serve the scientific community. To achieve these goals, the group includes experts in cloud and precipitation science, as well as representatives from ARM infrastructure, including instrument mentors, engineers, data quality officers, and data product translators. Prior to CPMSG, early discussions on cloud and precipitation measurements primarily focused on improving radar systems, but have since evolved to include a broader scope involving radiometers and other instruments. Since its formation, the CPMSG has gathered feedback using science traceability matrices. CPMSG aims to keep these as living documents to show the measurement needs, scientific drivers, roadblocks, maturity of measurements and retrievals, and pathways to model improvements. The group meets quarterly to discuss and prioritize measurement and operational improvements.

54 ENVIRONMENTAL SCIENCES↗

Facilitating Data Collection of Maintenance Events to Populate the Hydrogen Component Reliability Database (HyCReD)

The Hydrogen Component Reliability Database (HyCReD) is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety and reliability for hydrogen facilities by implementing component reliability data taxonomies that support hydrogen infrastructure failure rate analysis. The project aims to quantify failure rates of hydrogen components through high-quality data collection and analysis on root causes and maintenance needed. HyCReD provides a common database for cataloging hydrogen component failures which exists for reliability research in many other mature industries [2]. The database fills a gap for the hydrogen community by providing a scientifically rigorous approach to quantitative risk assessment (QRA), prognostic health management (PHM), and reliability-centered maintenance (RCM) analysis. High level results will be aggregated and anonymized to protect company sensitive information; detailed results will be used to help address issues of hydrogen components. These advanced analytics will support accelerated deployment of hydrogen infrastructure by enabling better: design and safety of projects (safety codes and standards development), infrastructure reliability and cost (component failure rates, maintenance protocols), and component R&D needs (robust supply chain). A key to a successful HyCReD implementation is facilitating the ease of reporting and data quality in the database that can be used for analysis. Maintenance data was a previously identified gap in initial efforts to populate and validate the database taxonomies [3]. Collection of maintenance data will be instrumental in identifying failure modes and rates, identifying incipient component failures or reduced performance, cataloging best practices for maintenance routines and methods for prognostic health management, and quantifying the risk and effect of different failure modes. Several key priorities are identified for streamlined data collection to achieve quality and detailed failure data: Applicability, Ease of Use, Accessibility, and Information Security. The HyCReD team has now begun deployment of the database to several companies and groups that have signed non-disclosure agreements to facilitate the data collection of failures in industry hydrogen refueling station infrastructure. This paper will provide an update into the process of HyCReD deployment including the development of a coding guide for facility personnel to reference and ensure data quality and consistency from one station to another as well as implementation of contextually dependent data fields of system taxonomy and formatted entries to provide ease of use. The goal is to communicate the lessons learned from the roll-out to technicians and engineers in the field, and the addition of need for high level of security to protect all stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

FC Site 4.0 - NLR Scanning Lidar (Halo XR+ 235) / Standardized and Quality-Controlled Data

This dataset contains lidar data that have been standardized and quality-controlled through NatLabRockies/FIEXTA/LiDARGO (https://github.com/NatLabRockies/FIEXTA/tree/main/lidargo). Standardization rearranges the lidar data into convenient range vs beamID vs scanID coordinates that facilitate data analysis. The scan geometry (i.e., azimuth, elevation) is shifted on a regular grid based on the most likely angles within the scan file. Quality control of radial wind speed is performed through a generalized version of the dynamic lidar filter (Beck and Kuhn, 2017).

17 WIND ENERGY↗

FC Site 4.2 - NLR Scanning Lidar (Halo XR+ 199) / Standardized and Quality-Controlled Data

This dataset contains lidar data that have been standardized and quality-controlled through NatLabRockies/FIEXTA/LiDARGO (https://github.com/NatLabRockies/FIEXTA/tree/main/lidargo). Standardization rearranges the lidar data into convenient range vs beamID vs scanID coordinates that facilitate data analysis. The scan geometry (i.e., azimuth, elevation) is shifted on a regular grid based on the most likely angles within the scan file. Quality control of radial wind speed is performed through a generalized version of the dynamic lidar filter (Beck and Kuhn, 2017).

17 WIND ENERGY↗

FC Site 1.9 - NLR Scanning Lidar (Halo XR+ 200) / Standardized and Quality-Controlled Data

This dataset contains lidar data that have been standardized and quality-controlled through NatLabRockies/FIEXTA/LiDARGO (https://github.com/NatLabRockies/FIEXTA/tree/main/lidargo). Standardization rearranges the lidar data into convenient range vs beamID vs scanID coordinates that facilitate data analysis. The scan geometry (i.e., azimuth, elevation) is shifted on a regular grid based on the most likely angles within the scan file. Quality control of radial wind speed is performed through a generalized version of the dynamic lidar filter (Beck and Kuhn, 2017).

17 WIND ENERGY↗