Lessons Learned From Performing Quality Control of KSC LC-39B Lightning Protection Tower Meteorological Data
No abstract available
Orcutt, John M.↗
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Assimilation of GPM-Retrieved Marine Surface Meteorology Data for Winter Storms During 2018 Olympic and Paralympic Winter Games
The WMO’s World Weather Research Program (WWRP) Research and Development and Forecast Demonstration Projects (RDP/FDP). Taken place during the Winter Olympics (February-March) of 2018. Focused on the measurement, physics, and improved prediction of heavy orographic snow in the Pyeong Chang region of South Korea.
Li, Xuanli↗
Using Deep Learning to Predict Yearly Wildfire Potential from Antecedent Land Surface and Meteorological Data
No abstract available
White, Andrew T.↗
Meteorological Data from NASA GSFC
Explore the source record for details and available documents.
Leslie R. Lait↗
Meteorological Data Quality Objectives for EPHA Modeling in Complex Terrain
Explore the source record for details and available documents.
Ciolek, John Theodore Jr.↗
Data Report: Meteorological and Evapotranspiration Data from Sagebrush and Pinyon Pine/Juniper Communities at Pahute Mesa, Nevada National Security Site, 2011-2012
Pahute Mesa is a groundwater recharge area at the Nevada National Security Site. Because underground nuclear testing was conducted at Pahute Mesa, groundwater recharge may transport radionuclides from underground test sites downward to the water table; the amount of groundwater recharge is also an important component of contaminant transport models. To estimate the amount of groundwater recharge at Pahute Mesa, an INFIL3.0 recharge-runoff model is being developed. Two eddy covariance (EC) stations were installed on Pahute Mesa to estimate evapotranspiration (ET) to support the groundwater recharge modeling project. This data report describes the methods that were used to estimate ET and collect meteorological data. Evapotranspiration was estimated for two predominant plant communities on Pahute Mesa; one site was located in a sagebrush plant community, the other site in a pinyon pine/juniper community. Annual ET was estimated to be 310±13.9 mm for the sagebrush site and 347±15.9 mm for the pinyon pine/juniper site (March 26, 2011 to March 26, 2012). Annual precipitation measured with unheated tipping bucket rain gauges was 179 mm at the sagebrush site and 159 mm at the pinyon pine/juniper site. Annual precipitation measured with bulk precipitation gauges was 222 mm at the sagebrush site and 227 mm at the pinyon pine/juniper site (March 21, 2011 to March 28, 2012). A comparison of tipping bucket versus bulk precipitation data showed that total precipitation measured by the tipping bucket rain gauges was 17 to 20 percent lower than the bulk precipitation gauges. These differences were most likely the result of the unheated tipping bucket precipitation gauges not measuring frozen precipitation as accurately as the bulk precipitation gauges. In this one-year study, ET exceeded precipitation at both study sites because estimates of ET included precipitation that fell during the winter of 2010-2011 prior to EC instrumentation and the precipitation gauges started collecting data in March 2011.
54 ENVIRONMENTAL SCIENCES↗
High-Resolution Floating Solar PV Data
This dataset contains over two years of 1-minute resolution data collected from four floating solar sites, as well as data from a land-based PV system co-located with one of the floating sites. The dataset includes highly granular module temperature measurements - five modules per floating site, with three sensors per module, totaling 15 module temperature sensors per floating site. In addition to the module temperature data, meteorological data collected at the floating sites is also included, along with traditional PV system-level parameters. The data is intended for analysis of solar energy production, efficiency, and performance degradation over time. For information about the data file usage see the "README" resource below. See "Metadata File" for information about individual files and other metadata information.
Array↗
Subsurface Flow Across Polygonal Tundra Measured by Bromide Tracer, Utqiagvik (Barrow), Alaska, 2015-2016
A bromide tracer study with the primary focus on hydrology in the active layer of polygonal tundra in the Barrow Environmental Observatory in Utqiagvik (Barrow), Alaska from July 2015 to September 2016. Sampling devices placed at various depths in the polygon centers, rims, and troughs were used to monitor tracer concentrations during thaw seasons. The tracer was continually monitored simultaneously on a low- and high-centered polygon throughout thaw seasons. Included is one data file of the bromide tracer concentrations. Also included are measurements taken throughout the experiment - one data file each of frost table depth and precipitation; and twelve water table elevation data files. Water level data, meteorological data, and thaw depth measurements were taken throughout the experiment. Our approach permits a comparison of hydrological behaviors in low- and high-centered polygons over the same time period and meteorological conditions.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 10-year research effort (2012-2022) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
54 ENVIRONMENTAL SCIENCES↗
Recommended Parameter Values for GENII Modeling of Radionuclides in Routine Air and Water Releases
The GENII v2 code is used to estimate dose to individuals or populations from the release of radioactive materials into air or water. Numerous parameter values are required for input into this code. User-defined parameters cover the spectrum from chemical data, meteorological data, agricultural data, and behavioral data. This document is a summary of parameter values that reflect conditions in the United States. Reasonable regional and age-dependent data is summarized. Data availability and quality varies. The set of parameters described address scenarios for chronic air emissions or chronic releases to public waterways. Considerations for the special tritium and carbon-14 models are briefly addressed. GENIIv2.10.0 is the current software version that this document supports.
54 ENVIRONMENTAL SCIENCES↗
General description and operation of the agro-environmental system: Crop management modeling
Input for a data management system to provide farmers with information to improve crop management practices in Virginia requires monitoring of control crops at field stations, crop surveys derived from remotely sensed aircraft data, meteorological data from synchronous satellites, and details of local agricultural conditions. Presently models are under development for determining pest problems, water balance in the soil, stages of plant maturity, and optimum planting date. The status of the Cerospora leafspot model for peanut crop management is considered. Other models under development planned relate to Cylindtocladium Blackrot and Sclerotinia blight of peanuts, cyst nematode (Globerdena solanacearum) of tobacco, and red crown rot of soybeans. A software for program for estimating precipitation and solar radiation on a statewise basis is also being developed.
Gross, E.↗
Evaluation of meterological rocket data
Meteorological rocket data compared with rawinsonde observations
RAWINSONDE MEASUREMENT↗
Air Dispersion Modeling for the INL Application for a Synthetic Minor Sitewide Air Quality Permit to Construct with a Facility Emission Cap Component
The Department of Energy Idaho Operations Office (DOE-ID) is applying for a synthetic minor, Sitewide, air quality permit to construct (PTC) with a facility emission cap (FEC) component from the Idaho Department of Environmental Quality (DEQ) for Idaho National Laboratory (INL) to limit its potential to emit to less than major facility limits for criteria air pollutants (CAPs) and hazardous air pollutants (HAPs) regulated under the Clean Air Act. This document is supplied as an appendix to the application, Idaho National Laboratory Application for a Synthetic Minor Sitewide Air Quality Permit to Construct with a Facility Emissions Cap Component, hereafter referred to as “permit application” (DOE-ID 2015). Air dispersion modeling was performed as part of the permit application process to demonstrate pollutant emissions from the INL will not cause a violation of any ambient air quality standards. This report documents the modeling methodology and results for the air dispersion impact analysis. All CAPs regulated under Section 109 of the Clean Air Act were modeled with the exception of lead (Pb) and ozone, which are not required to be modeled by DEQ. Modeling was not performed for toxic air pollutants (TAPs) as uncontrolled emissions did not exceed screening emission levels for carcinogenic and non-carcinogenic TAPs. Modeling for CAPs was performed with the EPA approved AERMOD dispersion modeling system (Version 14134) (EPA 2004a) and five years (2000-2004) of meteorological data. The meteorological data set was produced with the companion AERMET model (Version 14134) (EPA 2004b) using surface data from the Idaho Falls airport, and upper-air data from Boise International Airport supplied by DEQ. Onsite meteorological data from the Grid 3 Mesonet tower located near the center of the INL (north of INTEC) and supplied by the local National Oceanic and Atmospheric Administration (NOAA) office was used for surface wind directions and wind speeds. Surface data (i.e., land use data that defines roughness, albedo, Bowen ratio, and other parameters) were processed using the AERSURFACE utility (Version 13016) (EPA 2013). Emission sources were modeled as point sources using actual stack locations and dimensions. Emissions, flow rates and exit temperatures were based on the design operating capacity of each source. All structures close enough to produce an area of wake effect were included for all sources. For multi-tiered structures, the heights of the tiers were included or the entire building height was assumed to be equal to the height of the tallest tier. Concentrations were calculated at 1,352 receptor locations provided by DEQ. All receptors were considered for each pollutant and averaging period. Maximum modeled CAP concentrations summed with average background concentration values were presented and compared to National Ambient Air Quality Standards (NAAQS). The background concentration values used were obtained using the Washington State University’s Laboratory for Atmospheric Research North West Airquest web-based retrieval tool (http://lar.wsu.edu/nw airquest/lookup.html). The air dispersion modeling results show the maximum impacts for CAPs are less than applicable standards and demonstrate the INL will not cause a violation of any ambient air quality standards.
54 ENVIRONMENTAL SCIENCES↗
Comparison of Triton SODAR Data to Meteorological Tower Wind Measurement Data in Hebei Province, China
With the increased interest in remote sensing of wind information in recent years, it is important to determine the reliability and accuracy of new wind measurement technologies if they are to replace or supplement conventional tower-based measurements. In view of this, HydroChina Corporation and the United States National Renewable Energy Laboratory (NREL) conducted a comparative test near awind farm in Hebei Province, China. We present the results of an analysis characterizing the measurement performance of a state-of-the-art Sound Detection and Ranging (sodar) device when compared to a traditional tower measurement program. NREL performed the initial analysis of a three-month period and sent the results to HydroChina. When another month of data became available, HydroChina andtheir consultant Beijing Millenium Engineering Software (MLN) repeated NREL's analysis on the complete data set, also adding sensitivity analysis for temperature, humidity, and wind speed (Section 6). This report presents the results of HydroChina's final analysis of the four-month period.
17 WIND ENERGY↗
Calculating Dose Release Factors to Obtain the Worst-Case Maximally Exposed Location by Sector
The aim of this project was to update the SRS Dose Release Factors (DRF's) for the Maximally Exposed Individual (MEI) for 20 area release points onsite. To update, potential MEIs now include onsite locations and modeled stack heights were updated to match onsite operations. The DRF's and MEI locations are used to ensure DOE and EPA compliance is met for dose standards. The Environmental Protection Agency (EPA) requires the use of the computer model CAP88 to estimate doses for demonstrating compliance with 40 CFR 61, the National Emission Standard for Hazardous Air Pollutants (NESHAP). The location of the maximally exposed individual (MEI) by sector and distance is required for execution of CAP88. The worst-case sector is the sector and distance where an offsite individual would receive the highest dose due to a potential release from a designated release location at a facility. The worst-case sector analysis addresses potential ground-level and stack-height releases from 20 areas of Savannah River Site (SRS). Weather patterns were analyzed at each of these areas relative to sixteen compass points. The analysis makes use of recently updated distance data and meteorological data. The computer model, CAP88 is EPA's software system used by the Department of Energy (DOE) to calculate the receptor dose due to routine atmospheric releases via a gaussian plume at the Savannah River Site (SRS). The dose-release factors (DRFs) are used to estimate the offsite and onsite dose from facility-specific releases and represent the dose to a receptor exposed to 1 Ci of a specified radionuclide being released into the atmosphere. The DRFs are simply a ratio of the TED to the release rate and, therefore, are directly scalable. The DRF values listed in the Appendix can be applied to expected release values from each area to estimate the potential dose to an individual adult at each location. NESHAP DRFs have been supplied to Environmental Compliance and Area Closure Projects (EC and ACP) for many years and are periodically updated to include changes in Cap88. estimate the potential dose to an individual adult at each location DRF in mrem Ci{sup -1} are estimated by modeling the total effective dose (TED) in mrem yr{sup -1} assuming an annual atmospheric release rate of 1 Ci yr-1 of the associated radionuclides. TED = Effective Dose (ED) + Committed Effective Dose (CED). TED = DRF/RR. Approach and Methods: Determine possible MEI locations Onsite/Offsite including buildings and farms; Determine the distances from the release area to the possible MEI location and the direction from the release to the MEI location; Using the most recent meteorological data (2007-2011) and parameters, run CAP88 for each release area for each compass sector and previously calculated distances to MEI locations using a 1 Ci release rate for tritium; Use the calculated the air concentration values to determine the MEI for each sector from CAP88. The relationship between air concentration and received dose is directly proportional and can be used to determine which locations to calculate DRF's and a dose for an MEI; The DRFs are found for each compass sector from 20 SRS release areas using CAP88-PC Version 4.0; Each location is calculated with ground level releases evaluated for each area for a list of radionuclides, some with and some without progenies; Compare the DRFs of the potential onsite MEIs to offsite MEIs. Based on the 2018 MEI Report, the Site worst case sector MEI is located 593 mW of B-Area. This MEI location represents a point along the main road that travels through a tract of land leased to the SC National Guard. While this location is estimated to have the highest exposure, minimal radioactivity is released from B-Area. In 2017, SRS requested and was approved by the EPA to change the location for modeling site releases from the Center of Site to H-Area, and to use six stack heights. H-Area emission account for approximately 90% of all radioactive operations onsite. The MEI for H-Area was found to be 11,458 m NNE which locates the Savannah River Ecology Lab Conference Center. Comparisons for 2018 data and 2014 shows the new methods of calculation are more conservative yet still remain well below the DOE 100 mrem limit.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗