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All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Ar-Ar and I-Xe Ages and the Thermal History of IAB Meteorites

Studies of several samples of the large Caddo County IAB iron meteorite reveal andesitic material, enriched in Si, Na, Al and Ca, which is essentially unique among meteorites. This material is believed to have formed from a chondritic source by partial melting and to have further segregated by grain coarsening. Such an origin implies extended metamorphism of the IAB parent body. New Ar-39- Ar-40 ages for silicate from three different Caddo samples are consistent with a common age of 4.50-4.51 Gyr ago. Less well defined Ar-Ar degassing ages for inclusions from two other IABs, EET8333 and Udei Station, are approx.4.32 Gyr, whereas the age for Campo del Cielo varies considerably over approx.3.23-4.56 Gyr. New I-129-Xe-129 ages for Caddo County and EET8333 are 4557.9+/-0.1 Myr and 4557-4560 Myr, respectively, relative to an age of 4562.3 Myr for Shallowater. Considering all reported Ar-Ar degassing ages for IABs and related winonaites, the range is approx.4.32-4.53 Gyr, but several IABs give similar Ar ages of 4.50-4.52 Gyr. We interpret these older Ar ages to represent cooling after the time of last significant metamorphism on the parent body, and the younger ages to represent later 40Ar diffusion loss. The older Ar-Ar ages for IABs are similar to Sm-Nd and Rb-Sr isochron ages reported in the literature for Caddo County. Considering the possibility that IAB parent body formation was followed by impact disruption, reassembly, and metamorphism (e.g., Benedix et al. 2000), the Ar-Ar ages and IAB cooling rates deduced from Ni concentration profiles in IAB metal (Herpfer et al., 1994) are consistent if the time of the post-assembly metamorphism was as late as approx.4.53 Gyr ago. However, I-Xe ages reported for some IABs define much older ages of approx.4558-4566 Myr, which cannot easily be reconciled with the much younger Ar-Ar and Sm-Nd ages. An explanation for the difference in radiometric ages of IABs may reside in combinations of the following: a) I-Xe ages have very high closure temperatures and were not reset during metamorphism approx.4.53 Gyr ago; b) a bias exists in the 40K decay constants which makes these Ar-Ar ages approx.30 Myr too young; c) the reported Sm-Nd and Rb-Sr ages for Caddo are in error by amounts equal to or exceeding their reported 2-sigma uncertainties; and d) about 30 Myr after the initial heating that produced differentiation of Caddo silicate and mixing of silicate and metal, a mild metamorphism of the IAB parent body reset the Ar-Ar ages.

Bogard, Donald D.↗
NASA NTRS2004

Ar-Ar and I-Xe Ages and the Thermal History of IAB Meteorites

Studies of several samples of the large Caddo County IAB iron meteorite reveal andesitic material, enriched in Si, Na, Al and Ca, which is essentially unique among meteorites. This material is believed to have formed from a chondritic source by partial melting and to have further segregated by grain coarsening. Such an origin implies extended metamorphism of the IAB parent body. New Ar-39-Ar-40 ages for silicate from three different Caddo samples are consistent with a common age of 4.50-4.51 Gyr ago. Less well defined Ar-Ar degassing ages for inclusions from two other IABs, EET8333 and Udei Station, are approx.4.32 Gyr, whereas the age for Campo del Cielo varies considerably over approx.3.23-4.56 Gyr. New I-129-Xe-129 ages for Caddo County and EET8333 are 4561.9+/-0.1 Myr and 4560- 4563 Myr, respectively, relative to an age of 4566 Myr for Shallowater. Considering all reported Ar-Ar ages for IABs and related winonaites, the range is approx.4.32-4.53 Gyr, but several IABs give similar Ar ages of 4.50-4.52 Gyr. We interpret these older ages to represent cooling after the time of last significant metamorphism on the parent body, and the younger ages to represent later Ar-40 diffusion loss. These older Ar-Ar ages are similar to Sm-Nd and Rb-Sr isochron ages reported in the literature for Caddo County. Considering the possibility that IAB parent body formation was followed by impact disruption, reassembly, and metamorphism (e.g., Benedix et al. 2000), the time of the post-assembly metamorphism may have been as late as approx.4.53 Gyr ago. However, precise I-Xe ages reported for some IABs define a range of ages of approx.4560 to approx.4576 Myr. The older I-Xe ages exceed the oldest precise radiometric ages of meteorites, appear unrealistic, and s,uggest a bias in the calibration of all I-Xe ages. But even with such a bias, the I-Xe ages of IABs cannot easily be reconciled with the much younger Ar-Ar and Sm-Nd ages and with cooling rates deduced from Ni concentration profiles in IAB metal (Herpfer et al., 1994). An explanation for the difference in radiometric ages of IABs may reside in combinations of the following: a) I-Xe ages have very high closure temperatures and were not reset during metamorphism; b) a bias exists in the K-40 decay constants; c) the reported Sm-Nd and Rb-Sr ages for Caddo are in error by amounts equal to or exceeding their reported 2-sigma uncertainties; and 4) the IAB parent body may have experienced a mild metamorphism approx.30 Myr after the initial heating that produced differentiation of Caddo silicate and mixing of silicate and metal.

Bogard, Donald D.↗
NASA NTRS2004

Ar-Ar and I-Xe Ages and the Thermal History of IAB Meteorites

Studies of several samples of the large Caddo County IAB iron meteorite reveal andesitic material, enriched in Si, Nay Al and Ca, which is essentially unique among meteorites. This material is believed to have formed from a chondritic source by partial melting and to have further segregated by grain coarsening. Such an origin implies extended metamorphism of the IAB parent body. New Ar-39-Ar-40 ages for silicate from three different Caddo samples are consistent with a common age of 4.50- 4.51 Gyr ago. Less well defined Ar-Ar degassing ages for inclusions from two other IABs, EET8333 and Udei Station, are approx.4.32 Gyr, whereas the age for Campo del Cielo varies considerably over approx.3.23-4.56 Gyr. New I-129-Xe-129 ages for Caddo County and EET8333 are 4561.9 +/-0.1 Myr and 4560-4563 Myr, respectively, relative to an age of 4566 Myr for Shallowater. Considering all reported Ar-Ar ages for IABs and related winonaites, the range is approx.4.32-4.53 Gyr, but several IABs give similar Ar ages of 4.50-4.52 Gyr. We interpret these older ages to represent cooling after the time of last significant metamorphism on the parent body, and the younger ages to represent later Ar-40 diffusion loss. These older Ar-Ar ages are similar to Sm-Nd and Rb-Sr isochron ages reported in the literature for Caddo County. Considering the possibility that IAB parent body formation was followed by impact disruption, reassembly, and metamorphism (e.g., Benedix et al. 2000), the time of the post-assembly metamorphism may have been as late as approx.4.53 Gyr ago. However, precise I-Xe ages reported for some IABs define a range of ages of approx.4560 to approx.4576 My. The older I-Xe ages exceed the oldest precise radiometric ages of meteorites, appear unrealistic, and suggest a bias in the calibration of all I-Xe ages. But even with such a bias, the I-Xe ages of IABs cannot easily be reconciled with the much younger Ar-Ar and Sm-Nd ages and with cooling rates deduced from Ni concentration profiles in IAB metal (Herpfer et al., 1994). An explanation for the difference in radiometric ages of IABs may reside in combinations of the following: a) I-Xe ages have very high closure temperatures and were not reset during metamorphism; b) a bias exists in the K-40 decay constants; c) the reported Sm-Nd and Rb-Sr ages for Caddo are in error by amounts equal to or exceeding their reported 2-sigma uncertainties; and 4) the IAB parent body may have experienced a mild metamorphism approx.30 Myr after the initial heating that produced differentiation of Caddo silicate and mixing of silicate and metal. 129 129

Bogard, Donald D.↗
NASA NTRS2006

Ar-Ar and I-XE Ages and the Thermal History of IAB Meteorites

Studies of several samples of the large Caddo County IAB iron meteorite reveal andesitic material, enriched in Si, Na, Al and Ca which is essentially unique among meteorites. This material is believed to have formed from a chondritic source by partial melting and to have further segregated by grain coarsening. Such an origin implies extended metamorphism of the IAB parent body. New Ar-39- Ar-40 ages for silicate from three different Caddo samples are consistent with a common age of 4.50- 4.51 Gyr ago. Less well defined Ar-Ar degassing ages for inclusions from two other IABs, EET8333 and Udei Station, are approx. 4.32 Gyr, whereas the age for Campo del Cielo varies considerably over approx. 3.23-4.56 Gyr. New I-129-Xe-129 ges for Caddo County and EET8333 are 4561.9 plus or minus 0.1 Myr and 4560-4563 Myr, respectively, relative to an age of 4566 Myr for Shallowater. Considering all reported Ar-Ar ages for IABs and related winonaites, the range is approx. 4.32-4.53 Gyr, but several IABs give similar Ar ages of 4.50-4.52 Gyr. We interpret these older ages to represent cooling after the time of last significant metamorphism on the parent body, and the younger ages to represent later 40Ar diffusion loss. These older Ar-Ar ages are similar to Sm-Nd and Rb-Sr isochron ages reported in the literature for Caddo County. Considering the possibility that IAB parent body formation was followed by impact disruption, reassembly, and metamorphism (e.g., Benedix et al. 2000), the time of the postassembly metamorphism may have been as late as approx. 4.53 Gyr ago. However, precise I-Xe ages reported for some IABs define a range of ages of approx. 4560 to approx. 4576 Myr. The older I-Xe ages exceed the oldest precise radiometric ages of meteorites, appear unrealistic, and suggest a bias in the calibration of all I-Xe ages. But even with such a bias, the I-Xe ages of IABs cannot easily be reconciled with the much younger Ar-Ar and Sm-Nd ages and with cooling rates deduced from Ni concentration profiles in IAB metal (Herpfer et al., 1994). An explanation for the difference in radiometric ages of IABs may reside in combinations of the following: a) I-Xe ages have very high closure temperatures and were not reset during metamorphism; b) a bias exists in the K-40 decay constants; c) the reported Sm-Nd and Rb-Sr ages for Caddo are in error by amounts equal to or exceeding their reported 2-sigma uncertainties; and 4) the IAB parent body may have experienced a mild metamorphism approx.30 My after the initial heating that produced differentiation of Caddo silicate and mixing of silicate and metal.

Bogard, Donald D.↗
NASA NTRS1978

Medical Telemetry

Telemetry is the process whereby physiological or other data is acquired by instruments, translated into radio signals and j sent to a receiving station where the signals are decoded and recorded. Extensively used in I space operations, it is finding new Earth applications, among them transmission of medical data between emergency vehicles and hospitals. For example, transmission of an electrocardiogram from an ambulance to a hospital enables a physician to read the telemetered EKG and advise ambulance attendants on emergency procedures. Central Medical Emergency Dispatch (CMED) operates as a regional emergency medical communications center for Cleveland, Ohio and Cuyahoga County. The CMED system includes radio and telephone communications from hospital-to-hospital and from ambulance-to-hospital, but for improved emergency life support CMED sought to add a county-wide telemetry capability. The problem was that there were only eight radio frequencies available for telemetry and there were more than 30 potential users in Cleveland alone. NASA's Lewis Research Center volunteered its expert assistance. The Center's engineers studied the systems of other telemetry using cities, surveyed area hospitals to assure compatibility of telemetry equipment, and advised what types of equipment would be needed in emergency vehicles and at the various hospitals. The Lewis plan suggested that CMED be designated the central coordinating agency for the Cuyahoga County system, monitoring all telemetry frequencies and, when requested, assigning one not in use or one to be used at a sufficient distance that it would create no interference problem.

Source record↗
NASA NTRS2006

Utility of MODIS Aerosol Optical Depth for Estimating PM2.5 Exposure in Environmental Public Health Surveillance

As part of the National Environmental Public Health Tracking Network (EPHTN) the National Center for Environmental Health (NCEH) at the Centers for Disease Control and Prevention (CDC) is leading a project called Health and Environment Linked for Information Exchange (HELIX-Atlanta). The goal of developing the National Environmental Public Health Tracking Network is to improve the health of communities. Currently, few systems exist at the state or national level to concurrently track many of the exposures and health effects that might be associated with environmental hazards. An additional challenge is estimating exposure to environmental hazards such as particulate matter whose aerodynamic diameter is less than or equal to 2.5 micrometers (PM(2.5)) HELIX-Atlanta's goal is to examine the feasibility of building an integrated electronic health and environmental data network in five counties of Metropolitan Atlanta, GA (Clayton, Cobb, DeKalb, Fulton, and Gwinnett counties). Under HELIX-Atlanta, pilot projects are being conducted to develop methods to characterize exposure; link health and environmental data; analyze the relationship between health and environmental factors; and communicate findings. NASA Marshall Space Flight Center (NASA/MSFC) is collaborating with CDC to combine NASA earth science satellite observations related to air quality and environmental monitoring data to model surface estimates of PM(2.5) concentrations that can be linked with clinic visits for asthma. From 1999-2000 there were over 9,400 hospitalizations per year in Georgia with asthma as the primary diagnosis. The majority of these hospitalizations occurred in medical facilities in the five most populous Metro-Atlanta counties. Hospital charges resulting from asthma in Georgia are approximately $59 million dollars annually. There is evidence in the research literature that asthmatic persons are at increased risk of developing asthma exacerbations with exposure to environmental factors, including PM(2.5). Thus, HELIX-Atlanta is focusing on methods for characterizing population exposure to PM(2.5) for the Atlanta metropolitan area that could be used in on-going surveillance. While use of the Air Quality System, (AQS) PM(2.5) data alone could meet HELIX Atlanta, specifications, there are only five AQS sites in the Atlanta area, thus the spatial coverage is not ideal. Also, the AQS ground observations are made at time intervals ranging from one hour to six days leaving some temporal gaps. NASA Moderate Resolution Imaging Spectroradiometer (MODIS) satellite Aerosol Optical Depth (AOD) data have the potential for estimating daily ground level PM(2.5) at 10 km resolution over the metropolitan Atlanta area supplementing the AQS ground observations and filling their spatial and temporal gaps.

Al-Hamdan, Mohammad↗
NASA NTRS2013

It's the Heat AND the Humidity -- Assessment of Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. In a NASA-funded project supporting the National Climate Assessment, we are providing historical and future measures of extreme heat to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The project s emphasis is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM output, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons, 2040 and 2090, are the focus of future assessments; these are compared to the recent past period of 1981-2000. We are characterizing regional-scale temperature and humidity conditions using GCM output for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM output have been analyzed to develop a heat stress climatology based on statistics of extreme heat indicators. Differences between the two future and past periods have been used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes, combined with hourly historical meteorological data at a spatial scale (12 km) much finer than that of GCMs, enable us to create future climate realizations, from which we compute the daily heat stress measures and related spatially-specific climatological fields. These include the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. All output is being provided at the 12 km spatial scale and will also be aggregated to the county level, which is a popular scale of analysis for public health researchers. County-level statistics will be made available by our collaborators at the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. CDC WONDER makes the information resources of the CDC available to public health professionals and the general public. This addition of heat stress measures to CDC WONDER will allow decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. It will also allow public health researchers and policy makers to better include such heat stress measures in the context of national health data available in the CDC WONDER system. The users will be able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

Crosson, William L↗
NASA NTRS2013

Future Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health over the Coterminous U.S.

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981- 2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a 'heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km), to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wideranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S

Quattrochi, Dale A.↗
NASA NTRS2014

Linking Excessive Heat with Daily Heat-Related Mortality over the Coterminous United States

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981- 2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a 'heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km) much finer than that of GCMs, to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices, and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

Quattrochi, Dale A.↗
NASA NTRS2015

Relationships Between Excessive Heat and Daily Mortality over the Coterminous U.S

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. Using National Land Data Assimilation System (NLDAS) meteorological reanalysis data, we have developed several measures of extreme heat to enable assessments of the impacts of heat on public health over the coterminous U.S. These measures include daily maximum and minimum air temperatures, daily maximum heat indices and a new heat stress variable called Net Daily Heat Stress (NDHS) that gives an integrated measure of heat stress (and relief) over the course of a day. All output has been created on the NLDAS 1/8 degree (approximately 12 km) grid and aggregated to the county level, which is the preferred geographic scale of analysis for public health researchers. County-level statistics have been made available through the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. We have examined the relationship between excessive heat events, as defined in eight different ways from the various daily heat metrics, and heat-related and all-cause mortality defined in CDC's National Center for Health Statistics 'Multiple Causes of Death 1999-2010' dataset. To do this, we linked daily, county-level heat mortality counts with EHE occurrence based on each of the eight EHE definitions by region and nationally for the period 1999-2010. The objectives of this analysis are to determine (1) whether heat-related deaths can be clearly tied to excessive heat events, (2) what time lags are critical for predicting heat-related deaths, and (3) which of the heat metrics correlates best with mortality in each US region. Results show large regional differences in the correlations between heat and mortality. Also, the heat metric that provides the best indicator of mortality varied by region. Results from this research will potentially lead to improvements in our ability to anticipate and mitigate any significant impacts of extreme heat events on health.

heat↗
NASA NTRS2014

Variations in Modeled Dengue Transmission over Puerto Rico Using a Climate Driven Dynamic Model

Dengue fever is a mosquito‐borne viral disease reemerging throughout much of the tropical Americas. Dengue virus transmission is explicitly influenced by climate and the environment through its primary vector, Aedes aegypti. Temperature regulates Ae. aegypti development, survival, and replication rates as well as the incubation period of the virus within the mosquito. Precipitation provides water for many of the preferred breeding habitats of the mosquito, including buckets, old tires, and other places water can collect. Because of variations in topography, ocean influences and atmospheric processes, temperature and rainfall patterns vary across Puerto Rico and so do dengue virus transmission rates. Using NASA's TRMM (Tropical Rainfall Measuring Mission) satellite for precipitation input, ground‐based observations for temperature input, and laboratory confirmed dengue cases reported by the Centers for Disease Control and Prevention for parameter calibration, we modeled dengue transmission at the county level across Puerto Rico from 2010‐2013 using a dynamic dengue transmission model that includes interacting vector ecology and epidemiological components. Employing a Monte Carlo approach, we performed ensembles of several thousands of model simulations for each county in order to resolve the model uncertainty arising from using different combinations of parameter values that are not well known. The top 1% of model simulations that best reproduced the reported dengue case data were then analyzed to determine the most important parameters for dengue virus transmission in each county, as well as the relative influence of climate variability on transmission. These results can be used by public health workers to implement dengue control methods that are targeted for specific locations and climate conditions.

Morin, Cory↗
NASA NTRS2018

Calculating the Modal Mineralogy of Aubrite Meteorites Using X-Ray Computed Tomography

The aubrites are a group of differentiated meteorites that formed in extremely reducing conditions, with oxygen fugacities (ƒO2) ranging from ~2 to ~6 log units below the Iron-Wüstite buffer. At these extreme conditions, elements that are lithophile (silica-loving) on Earth can behave as chalcophiles (sulfur-loving) or siderophiles (metal-loving), and FeO-poor silicates and exotic sulfides can form. Elemental partitioning among minerals at these conditions are still not well understood, thus studying aubrites could help better constrain elemental behavior. Only 30 aubrites exist; however, they display various textures, which can be difficult to identify in small samples. Identifying composite clasts can help in understanding the igneous history of the aubrite parent bodies. In order to distinguish different minerals and textures in larger samples, we use X-ray computed tomography (XCT), which is a useful, non-destructive analysis that can produce a 3D representation of a meteorite's textures, structures, and modal mineralogy. This study investigates the Norton County aubrite using XCT. Norton County is a fragmental impact breccia aubrite, and was an observed fall with a main mass of 1.1 tons. This large amount of material offers an opportunity to investigate a great volume of reduced, aubritic sample and study a more diverse variety of clasts. Here we report XCT results of two samples of Norton County (NC 15417) in order to constrain the 3D modal mineralogy of silicates, sulfides, and metals, and to identify unique clasts within the matrix.

Wilbur, Zoe↗
NASA NTRSDate not supplied

The Future of Oaks in the Santa Monica Mountains: A Case Study in Using Remote Sensing Data for Species Distributions Models

The Woolsey Fire began on November 8, 2018, and lasted for almost two weeks, during which it burned almost 100,000 acres of valuable landscape and habitat, including a vast area of woodland. The persistence of key woodland species provides aesthetic, monetary, and ecological value to the landscape through carbon sequestration, air temperature moderation, and erosion mitigation, among other ecosystem services. This study investigated the impact of the Woolsey Fire on native woodland species distributions and identified areas suitable for restoration within the Santa Monica Mountains National Recreation Area. The team partnered with the Resource Conservation District of the Santa Monica Mountains; National Park Service, Santa Monica Mountains National Recreation Area; California Department of Parks and Recreation, Los Angeles County Division; County of Los Angeles Fire Department, Prevention Services Bureau, Forestry Division; County of Los Angeles Department of Regional Planning; and the University of Montana. The Earth observations used include data from Landsat 8 Operational Land Imager, NASA ER-2 Jet Airborne Visible InfraRed Imaging Spectrometer, Shuttle Radar Topography Mission, and RapidEye. The team produced maps of burn severity from the Woolsey Fire, its impact on plant species distributions, and habitat suitability projections for 2050 and 2099 to assist partners in prioritizing areas for restoration. A plant community classification was successfully created using Multiple Endmember Spectral Mixture Analysis (MESMA). Overall accuracy was assessed at 90.54% by comparing the classification to validation pixels derived from ground truth information provided by our partners.

Roger Ly↗
NASA NTRSDate not supplied

Building a Real-Time Flood Prediction Model for Improving Early Warning Systems in Ellicott City, Maryland

As flood events in the United States grow in frequency and intensity, the use of applied remote sensing analyses is increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP National Program partnered with the local government of Howard County, Maryland, to investigate the use of machine learning for advanced flood risk detection, and to test the feasibility of integrating this approach into the county’s flood early warning system. To strengthen the efforts of the Howard County Office of Emergency Management (OEM), the project developed a statistical model capable of hindcasting the two severe flash flood events that devastated Ellicott City and transitioned to a ‘Long Short-Term Memory’ based sequence-to-sequence deep learning model with 8-hour forecast capability. The team combined data inputs from public sources including river and precipitation gauges, NASA and NOAA Earth observations, and numerical weather model products using scripts written in the Google Colaboratory Python scripting environment. In addition to designing the deep learning architecture, the team trained and tested the model, and evaluated its performance using Nash-Sutcliffe Efficiency. The final product, the Sequentially Trained Real-time EstimAted Model (STREAM) predicts stage height for the Hudson Branch gauge in Ellicott City using data products available in near real-time, including the High-Resolution Rapid Refresh model’s accumulated precipitation forecasts supplemented by stream gauge data from the OEM and the U.S. Geological Survey. STREAM was incorporated into an online dashboard in a user-friendly interface capable of triggering the alarms that initiate emergency response protocols up to 8 hours in advance of a predicted severe flood event. The project demonstrated the potential for the integration of open data and Earth observations into a flood risk forecasting tool capable of informing near real-time decision making.

NASA DEVELOP↗
NASA NTRSDate not supplied

Building a Real-Time Predictive Flood Model for Improving Early Warning Systems in Ellicott City, Maryland

As flood events in the United States grow in frequency and intensity, the use of applied remote sensing analyses is increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP National Program partnered with the Howard County government in Maryland to investigate the use of machine learning for advanced flood risk detection, and to test the feasibility of integrating this approach into the county’s flood early warning system. To strengthen the efforts of the Howard County Office of Emergency Management (OEM), the project developed a prediction model capable of hindcasting the two severe flash flood events that devastated Ellicott City, and transitioned to an Long Short-Term Memory (LSTM) based sequence-to-sequence deep learning model with 8-hour forecast capability. The team combined data inputs from public sources including river and precipitation gauges, NASA and NOAA Earth observations, and numerical weather model products using scripts written in the Google Colaboratory Python scripting environment. In addition to designing the deep learning architecture, the team trained and tested the model, and evaluated its performance using the Nash-Sutcliffe Efficiency (NSE). The final product, called the Sequentially Trained Real-time EstimAted Model (STREAM), predicts stage height for the Hudson Branch gauge in Ellicott City using data products available in near real-time, including the High-Resolution Rapid Refresh (HRRR) model’s accumulated precipitation forecasts supplemented by stream gauge data from the OEM and the U.S. Geological Survey. STREAM was incorporated into an online dashboard in a user-friendly interface capable of triggering the alarms that initiate the OEM’s emergency response protocols up to 8 hours in advance of a predicted severe flood event. The project demonstrated the potential for the integration of open data and Earth observations into a flood risk forecasting tool capable of informing near real-time decision making.

Ryan Hammock↗
NASA NTRS2019

Assessing precipitation, evapotranspiration, and NDVI as controls of US Great Plains plant production

Productivity throughout the North American Great Plains grasslands is generally considered to be water limited, with the strength of this limitation increasing as precipitation decreases. We hypothesize that cumulative actual evapotranspiration water loss (AET) from April to July is the precipitation-related variable most correlated to aboveground net primary production (ANPP) in the U.S. Great Plains (GP). We tested this by evaluating the relationship of ANPP to AET, precipitation, and plant transpiration (Tr). We used multi-year ANPP data from five sites ranging from semiarid grasslands in Colorado and Wyoming to mesic grasslands in Nebraska and Kansas, mean annual NRCS ANPP, and satellite-derived normalized difference vegetation index (NDVI) data. Results from the five sites showed that cumulative April-to-July AET, precipitation, and Tr were well correlated (R2: 0.54–0.70) to annual changes in ANPP for all but the wettest site. AET and Tr were better correlated to annual changes in ANPP compared to precipitation for the drier sites, and precipitation in August and September had little impact on productivity in drier sites. April-to-July cumulative precipitation was best correlated (R2 = 0.63) with interannual variability in ANPP in the most mesic site, while AET and Tr were poorly correlated with ANPP at this site. Cumulative growing season (May-to-September) NDVI (iNDVI) was strongly correlated with annual ANPP at the five sites (R2 = 0.90). Using iNDVI as a surrogate for ANPP, we found that county-level cumulative April–July AET was more strongly correlated to ANPP than precipitation for more than 80% of the GP counties, with precipitation tending to perform better in the eastern more mesic portion of the GP. Including the ratio of AET to potential evapotranspiration (PET) improved the correlation of AET to both iNDVI and mean county-level NRCS ANPP. Accounting for how different precipitation-related variables control ANPP (AET in drier portion, precipitation in wetter portion) provides opportunity to develop spatially explicit forecasting of ANPP across the GP for enhancing decision-making by land managers and use of grassland ANPP for biofuels.

Maosi Chen↗
DOE OSTI2020

Community-Scale Energy Efficiency Assessment for Zero Net Energy Using the URBANopt Simulation Platform: Preprint

This project explored an innovative modeling approach for assessing the energy efficiency potential of the existing low-income Oceano neighborhood, in unincorporated San Luis Obispo County, and its effects on renewable generation requirements for achieving zero net energy (ZNE). One particular challenge faced was ascertaining the technical energy savings potential across a large neighborhood in a timely manner. The project overcame this challenge through the use of the URBANopt simulation platform, developed at the National Renewable Energy Laboratory. URBANopt manages the automated model creation, simulation, and result aggregation for different design scenarios of existing or candidate buildings in a large neighborhood. Customized energy efficiency packages considered for the residential and commercial sector in the neighborhood included lighting, HVAC, plug load, water heating, envelope, and energy education measures. As a result of the analysis for the Oceano community, energy efficiency measures that are available through incentive programs may provide a 7.4% reduction in the required distributed energy resource (DER) size, corresponding to a 25,000 ft2 decrease in PV array area, to achieve ZNE. Through this work, a computational tool was developed and is being leveraged by the County of San Luis Obispo (CoSLO). The tool has enabled the CoSLO staff to perform similar analysis of the technical potential for energy efficiency, and an understanding of the DER asset requirements and potential savings in other communities within the county.

building energy modeling↗
DOE OSTI2020

Large-Scale Solar Development: A Playbook for Southwest Virginia

his playbook is an introductory guide for local governments to facilitate large-scale solar projects in Southwest Virginia. In a region that has a long history of energy production, solar technologies offer enormous potential for economic development and job growth. Large-scale solar can take many forms, including rooftop or ground-mounted installations at local corporate offices, nonprofit organizations, or schools. It can also encompass utility-scale projects over many acres on former agricultural or timberlands, mined lands, or industrial sites. Regardless of the type of project, solar is a widely popular, cost-competitive energy choice that helps create sustainable and prosperous communities. This playbook is directed to municipal and county governments that have an essential role to play in encouraging large-scale solar projects. The first section provides an overview of state and national trends, including recent state legislation that will impact local oversight of solar development. This is followed by an overview of the solar project approval process from a developer’s perspective. The next section is an overview of the state and local permitting process for solar projects, followed by other development considerations such as local tax revenue options, financing incentives, and considerations for solar on brownfields and previously mined lands. The playbook concludes with a step-by-step guide for local governments to facilitate large-scale solar development.This playbook is part of the Solar Workgroup of Southwest Virginia’s effort to bring solar energy and associated jobs to the region. Over the past few years, the workgroup has met with stakeholder groups and crafted a strategy for local solar energy development. The workgroup has collaborated with cities and counties to bring SolSmart designation to eight counties and cities, implemented group purchase campaigns for commercial solar, and led research efforts.

14 SOLAR ENERGY↗