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DOE OSTI2024

Development of typical solar years and typical wind years for efficient assessment of renewable energy systems across the U.S.

Weather data plays a critical role in renewable energy analysis. Compared to using multiple Actual Meteorological Years, simulations using a single typical year require significantly fewer computational resources. Previous efforts to create typical weather datasets for renewable energy analysis either lack justified or optimized strategies for selecting and weighting different weather parameters or are limited to a few specific locations. Here, in this study, we developed a dataset comprising Typical Solar Years (TSYs) and Typical Wind Years (TWYs) for over 2000 locations across the U.S., based on data from NASA's POWER project. The strategies for creating TSYs and TWYs were optimized based on the simulated outputs of various PV systems and wind turbines in 16 representative cities. This dataset provides an efficient means for the rapid evaluation and optimization of renewable energy systems throughout the entire U.S. Additionally, the optimal strategies identified in this study can be directly applied to create near-optimal TSYs and TWYs for most locations worldwide. However, readers can also employ the optimization approach presented in this work to develop optimal strategies tailored for particular regions.

NASA POWER↗

NASA NTRS2011

NASA's Internal Space Weather Working Group

Measurements from many of NASA's scientific spacecraft are used routinely by space weather forecasters, both in the U.S. and internationally. ACE, SOHO (an ESA/NASA collaboration), STEREO, and SDO provide images and in situ measurements that are assimilated into models and cited in alerts and warnings. A number of years ago, the Space Weather laboratory was established at NASA-Goddard, along with the Community Coordinated Modeling Center. Within that organization, a space weather service center has begun issuing alerts for NASA's operational users. NASA's operational user community includes flight operations for human and robotic explorers; atmospheric drag concerns for low-Earth orbit; interplanetary navigation and communication; and the fleet of unmanned aerial vehicles, high altitude aircraft, and launch vehicles. Over the past three years we have identified internal stakeholders within NASA and formed a Working Group to better coordinate their expertise and their needs. In this presentation we will describe this activity and some of the challenges in forming a diverse working group.

St. Cyr, O. C.↗

NASA NTRS1979

Solar-terrestrial influences on weather and climate; Proceedings of the Symposium, Ohio State University, Columbus, Ohio, August 24-28, 1978

The book contains most of the invited papers and contributions presented at the symposium/workshop on solar-terrestrial influences on weather and climate. Four main issues dominate the activities of the symposium: whether solar variability relationships to weather and climate is a fundamental scientific question to which answers may have important implications for long-term weather and climate prediction; the sun-weather relationships; other potential solar influences on weather including the 11-year sunspot cycle, the 27-day solar rotation, and special solar events such as flares and coronal holes; and the development of practical use of solar variability as a tool for weather and climatic forecasting, other than through empirical approaches. Attention is given to correlation topics; solar influences on global circulation and climate models; lower and upper atmospheric coupling, including electricity; planetary motions and other indirect factors; experimental approaches to sun-weather relationships; and the role of minor atmospheric constituents.

Mccormac, B. M.↗

DOE OSTI2020

Chicago microclimate and building energy use data

These data comprise three elements: - High resolution, 90 m simulated weather data for 1 year at 15 min. intervals (with known gaps toward the end of each month). These files are in .csv format. - A mapping of individual buildings with individual IDs, their latitude/longitude location, and height. (Excel file) - Energy simulation output of these individual buildings, at 15 min. intervals for a whole year. (.json and other files)

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2014

Worldwide Weather Radar Imagery May Allow Substantial Increase in Meteorite Fall Recovery

Weather radar imagery is a valuable new technique for the rapid recovery of meteorite falls, to include falls which would not otherwise be recovered (e.g. Battle Mountain). Weather radar imagery reveals about one new meteorite fall per year (18 falls since 1998), using weather radars in the United States alone. However, an additional ~75 other nations operate weather radar networks according to the UN World Meteorological Organization (WMO). If the imagery of those radars were analyzed, the current rate of meteorite falls could be improved considerably, to as much as ~3.6 times the current recovery rate based on comparison of total radar areal coverage. Recently, the addition of weather radar imagery, seismometry and internet-based aggregation of eyewitness reports has improved the speed and accuracy of fresh meteorite fall recovery [e.g. 1,2]. This was demonstrated recently with the radar-enabled recovery of the Sutter's Mill fall [3]. Arguably, the meteorites recovered via these methods are of special scientific value as they are relatively unweathered, fresh falls. To illustrate this, a recent SAO/NASA ADS search using the keyword "meteorite" shows that all 50 of the top search results included at least one named meteorite recovered from a meteorite fall. This is true even though only ~1260 named meteorite falls are recorded among the >49,000 individual falls recorded in the Meteoritical Society online database. The US NEXRAD system used thus far to locate meteorite falls covers most of the United States' surface area. Using a WMO map of the world's weather radars, we estimate that the total coverage of the other ~75 national weather radar networks equals about 3.6x NEXRAD's coverage area. There are two findings to draw from this calculation: 1) For the past 16 years during which 18 falls are seen in US radar data, there should be an additional ~65 meteorite falls recorded in worldwide radar imagery. Also: 2) if all of the world's radar data could be analyzed, the rate of recovery of fresh meteorite falls can increase by as much as ~3.6x the current rate. The authors' experience to date indicates that the most effective course of action would be to have local meteorite research groups (outside of the US) form research consortia and develop a working relationship with their nation's weather bureau for access to data. These research consortia could utilize the same, proven methods used for US NEXRAD imagery, internet eyewitness report aggregation, seismometry analysis, etc. to locate meteorite falls. The consortia could then recover and analyze meteorite falls and enrich their own research efforts. It would be beneficial to conduct a global program to coordinate the development of methods and data tools, as well as to coordinate meteorite sample sharing and research. Perhaps an institution such as the Meteoritical Society could lead such an effort.

Fries, Marc↗

NASA NTRSDate not supplied

The Completion of a Geosynchronous Earth Orbit Survey with the Eugene Stansbery-Meter Class Autonomous Telescope

The Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT) is the primary optical sensor used by the NASA Orbital Debris Program Office (ODPO) to statistically characterize the geosynchronous Earth orbit (GEO) debris environment and support future Orbital Debris Engineering Model (ORDEM) releases. The ES-MCAT completed its first optical survey of the GEO region from 2020 to 2022. The primary goal of this survey was to autonomously collect and process GEO data with calculated photometric and astrometric uncertainties. A pointing plan was developed to provide uniform sampling within the region of interest (ROI) while accounting for predicted downtime due to insufficient observing conditions. Detections are autonomously correlated to the Space Surveillance Network (SSN) catalog to determine if objects are correlated targets (CTs) or uncorrelated targets (UCTs), the latter of which are of interest for modeling the GEO orbital debris environment. To assess the size detection sensitivity over time and monitor the general performance of the telescope’s optics and software, the optical throughput of the system and limiting magnitudes are evaluated on a routine basis. While the telescope’s ability to operate autonomously and remotely allowed for the GEO survey to continue throughout the COVID-19 pandemic, travel restrictions hampered routine cleaning of the optics during this time, and the primary mirror degraded enough to require recoating. The mirror was removed in 2022, concluding the first GEO survey. The primary mirror received a new coating designed to be more robust against the harsh environment surrounding the ES-MCAT’s location on Ascension Island, accounting for experience gained during operations over the first GEO survey. In early 2023, the recoated primary mirror was reinstalled, and the second GEO survey was initiated. The primary goal of the second GEO survey is to characterize the evolving GEO debris environment with updated optics, software, and pointing strategies while allowing for the inclusion of non-GEO regimes or those that are outside of the ROI. While the pointing method implemented in the first survey allowed for adequate coverage of the ROI over two years, it has been improved to include pointings that avoid the Moon’s position and the galactic plane to reduce software processing time and maximize the detection capabilities of fainter objects. This method also accounts for the changing weather patterns throughout the year and reduces coverage gaps in the ROI. Provided the success of the first two-year GEO survey using autonomous operations, the ODPO is actively collaborating with the United States Space Force (USSF) to make the ES-MCAT a contributing sensor to the SSN. This paper presents results from the first GEO survey including magnitude distributions and orbital parameters for CTs and UCTs. Details are provided for the automated processing pipeline and the optical system throughput for the previous and current primary mirror coatings. In addition, an updated strategy for the second GEO survey to optimize coverage over the ROI is discussed, as are preliminary results from the ongoing second survey.

Corbin Cruz↗

NASA NTRSDate not supplied

The Completion of a Geosynchronous Earth Orbit Survey with the Eugene Stansbery-Meter Class Autonomous Telescope

Corbin Cruz↗

NASA NTRS2010

The International Space Weather Initiative (ISWI)

The International Heliophysical Year (IHY) provided a successful model for the deployment of arrays of small scientific instruments in new and scientifically interesting geographic locations, and outreach. The new International Space Weather Initiative (ISWI) is designed to build on this momentum to promote the observation, understanding, and prediction space weather phenomena, and to communicate the scientific results to the public.

Davila, Joseph M.↗

DOE OSTI2020

Simulating precipitation in the Northeast United States using a climate-informed K -nearest neighbour algorithm

Not provided.

Water Resources↗

NASA NTRS2017

Space Weathering Rates in Lunar and Itokawa Samples

Space weathering alters the chemistry, microstructure, and spectral proper-ties of grains on the surfaces of airless bodies by two major processes: micrometeorite impacts and solar wind interactions. Investigating the nature of space weathering processes both in returned samples and in remote sensing observations provides information fundamental to understanding the evolution of airless body regoliths, improving our ability to determine the surface composition of asteroids, and linking meteorites to specific asteroidal parent bodies. Despite decades of research into space weathering processes and their effects, we still know very little about weathering rates. For example, what is the timescale to alter the reflectance spectrum of an ordinary chondrite meteorite to resemble the overall spectral shape and slope from an S-type asteroid? One approach to answering this question has been to determine ages of asteroid families by dynamical modeling and determine the spectral proper-ties of the daughter fragments. However, large differences exist between inferred space weathering rates and timescales derived from laboratory experiments, analysis of asteroid family spectra and the space weathering styles; estimated timescales range from 5000 years up to 108 years. Vernazza et al. concluded that solar wind interactions dominate asteroid space weathering on rapid timescales of 10(exp 4)-10(exp 6) years. Shestopalov et al. suggested that impact-gardening of regolith particles and asteroid resurfacing counteract the rapid progress of solar wind optical maturation of asteroid surfaces and proposed a space weathering timescale of 10(exp 5)-10(exp 6) years.

Keller, L. P.↗

DOE OSTI2024

Snow Distribution Patterns Revisited: A Physics-Based and Machine Learning Hybrid Approach to Snow Distribution Mapping in the Sub-Arctic

Snowpack distribution in Arctic and alpine landscapes often occurs in repeating, year-to-year patterns due to local topographic, weather, and vegetation characteristics. Previous studies have suggested that with years of observational data, these snow distribution patterns can be statistically integrated into a snow process modeling workflow. Recent advances in snow hydrology and machine learning (ML) have increased our ability to predict snowpack distribution using in-situ observations, remote sensing data sets, and simple landscape characteristics that can be easily obtained for most environments. Here, we propose a hybrid approach to couple a ML snow distribution pattern (MLSDP) map with a physics-based, snow process model. We trained a random forest ML algorithm on tens of thousands of snow survey observations from a subarctic study area on the Seward Peninsula, Alaska, collected during peak snow water equivalent (SWE). We validated hybrid model outputs using in-situ snow depth and SWE observations, as well as a light detection and ranging data set and a distributed temperature profiling sensor data set. When the hybrid results were compared with the physics-based method, the hybrid method more accurately depicted the spatial patterns of the snowpack, areas of drifting snow, and years when no in-situ observations were used in the random forest ML training data set. The hybrid method also showed improvements in root mean squared error at 61% of locations where time-series estimations of snow depth were observed. These results can be applied to any physics-based model to improve the snow distribution patterning to reflect observed conditions in high latitude and high elevation cold region environments.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2006

Using a Network of Boundary Layer Profilers to Characterize the Atmosphere at a Major Spaceport

Space launch, landing, and ground operations at the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) in east-central Florida are highly sensitive to mesoscale weather conditions throughout the year. Due to the complex land-water interfaces and the important role of mesoscale circulations, a high-resolution network of five 915-MHz Doppler Radar Wind Profilers (DRWP) and 44 wind towers was installed over the KSC/CCAFS area. By using quality-controlled 915-MHz DRAT data along with the near-surface tower observations, the Applied Meteorology Unit and KSC Weather Office have studied the development and evolution of various mesoscale phenomena across KSC/CCAFS such as sea and land breezes, low-level jets, and frontal passages. This paper will present some examples of mesoscale phenomena that can impact space operations at KSC/CCAFS, focusing on the utility of the 915-MHz DRWP network in identifying important characteristics of sea/land breezes and low-level jets.

Case, Jonathan L.↗

NASA NTRS2010

ADAS Update and Maintainability

Since 2000, both the National Weather Service Melbourne (NWS MLB) and the Spaceflight Meteorology Group (SMG) have used a local data integration system (LOIS) as part of their forecast and warning operations. The original LOIS was developed by the Applied Meteorology Unit (AMU) in 1998 (Manobianco and Case 1998) and has undergone subsequent improvements. Each has benefited from three-dimensional (3-D) analyses that are delivered to forecasters every 15 minutes across the peninsula of Florida. The intent is to generate products that enhance short-range weather forecasts issued in support of NWS MLB and SMG operational requirements within East Central Florida. The current LDIS uses the Advanced Regional Prediction System (ARPS) Data Analysis System (AD AS) package as its core, which integrates a wide variety of national, regional, and local observational data sets. It assimilates all available real-time data within its domain and is run at a finer spatial and temporal resolution than current national or regional-scale analysis packages. As such, it provides local forecasters with a more comprehensive understanding of evolving fine-scale weather features. Over the years, the LDIS has become problematic to maintain since it depends on AMU-developed shell scripts that were written for an earlier version of the ADAS software. The goals of this task were to update the NWS MLB/SMG LDIS with the latest version of ADAS, incorporate new sources of observational data, and upgrade and modify the AMU-developed shell scripts written to govern the system. In addition, the previously developed ADAS graphical user interface (GUI) was updated. Operationally, these upgrades will result in more accurate depictions of the current local environment to help with short-range weather forecasting applications, while also offering an improved initialization for local versions of the Weather Research and Forecasting (WRF) model used by both groups.

Watson, Leela R.↗

NASA NTRSDate not supplied

Novel Hourly-Resolved Global Cloud Property Composite from Operational Satellites Imagers

Numerous applications in satellite remote sensing of surface properties, atmospheric state, composition, and radiation require accurate knowledge of the location and characteristics of clouds. Operational satellite imager radiances are valuable for cloud detection and for deriving many different physical parameters that can be used for a variety of weather, aviation, and energy applications. The NASA Satellite ClOud and Radiation Property retrieval System (SatCORPS) applies a suite of algorithms to meteorological satellite data to provide cloud properties, radiative fluxes and other parameters on a global scale. This paper describes a new global high-resolution dataset of cloud properties made available for community use that is constructed from analyses of a constellation of meteorological satellite imagers. Data taken from Meteosat-8/9 and -11, Himawari-8/9, GOES-16, and -17/-18, Aqua, Terra, Suomi-NPP and NOAA-20 are processed and composited on a 3-km grid to provide hourly global coverage. A historical multi-year dataset is available to serve various needs including modeling challenges related to cloud evaluations and parameterizations. Near real-time data products are also currently available between 60N and 60S. Efforts are underway to operationalize polar orbiting satellite cloud detection methods for low-latency applications over polar regions. The cloud detection and retrieval algorithms have been developed over many years to support NASA weather and climate programs such as the Clouds and Earth’s Radiant Energy System (CERES). To improve the utility of the data products, machine learning and other innovative methods are applied in various ways to help minimize data product uncertainties under the most challenging conditions and to improve their consistency at all times of day. A brief description of the methods highlighting the unique aspects of the SatCORPS data products will be presented along with information on their status and availability.

SatCORPS↗

NASA NTRS2019

Chemical Climatology of Atmospheric Pollutants in the Eastern United States: Seasonal/Diurnal Cycles and Contrast Under Clear/Cloudy Conditions for Remote Sensing

We statistically assessed temporal variations of observed concentrations of eight atmospheric pollutants (SO2, NO, NO2, NO(y), O3, CO, NH3, and HNO3) at three urban sites and one rural site in the eastern United States for a ten-year period (4 years for NH3). Diurnal/seasonal patterns of observed mean concentrations and their decade-scale trends under different weather conditions were evaluated. Concentrations of pollutants decreased consistently during the observation period (as long as 1997–2013), although nighttime ozone during winter appears to increase because of reduced NO-O3 titration. This study shows that the decay time of major air pollutant concentrations such as SO2 and NO(x) can be short as a few hours to one day. We also identified substantial differences between the mean concentrations of pollutants at clear sky and overcast conditions that could introduce biases into satellite observations. Surface concentrations of SO2 and CO are distinctly higher under cloud free than under overcast conditions by ∼30% and ∼20% respectively. NO2 shows a complex pattern, but demonstrates lower daytime concentrations under cloud-free skies. All of these estimates are important for understanding the chemical climatology of these atmospheric pollutants, especially their diurnal/seasonal cycles under different weather conditions. For four-year measurements, NH3 shows a substantial difference, with clear sky observations roughly a factor of two higher than those under overcast conditions. To track changes in the future, the full daily cycle of atmospheric pollutants monitored by geostationary satellite such as the future TEMPO mission may better capture patterns and trends.

TEMPO↗

NASA NTRS1985

Severe storm detection with passive 37 GHz observations

The research objective was to determine the information content of satellite passive 37 GHz brightness temperatures on the severity of thunderstorms through the measurement of the attenuation (scattering) signature of precipitation. The severe storm detection potential of satellite-observed passive 37 GHz radiances was evaluated by comparing Nimbus-7 Scanning Multi-channel Microwave Radiometer (SMMR) data to reports of severe weather contained in the NSSFC severe weather log for calendar years 1979 and 1980 over the United States east of the Rocky Mountains. Heavy thunderstorms have a characteristic signature in the form of localized very low 37 GHz T sub B from scattering by precipitation-size ice particles (thick cirrus being transparent at this frequency). The local noon and midnight snapshots taken by the SMMR on alternating days (with incomplete areal coverage of the U.S. on any given day) were scanned to find cases of strong scattering by precipitation, revealed by large differences between the 18 and 37 GHz brightness temperatures, the 37 GHz T sub B being at least 20 C lower than the 18 GHz T sub B. The value of the 37 GHz T sub b was then compared to severe weather reports within one hour of the SMMR observation time, in the vicinity of the SMMR-observed storm. It was found that the degree to which the T sub B were lowered was a fairly good indicator of the probability that the storm was severe. Of 263 storms observed by the SMMR during 1979 and 1980, 54 percent had severe weather associated with them for a T sub b below 203 K, while 8 percent of those above this threshold were severe.

Spencer, R. W.↗

DOE OSTI2020

Biodiesel Ethers: Fatty Acid-Derived Alkyl Ether Fuels as Improved Bioblendstocks for Mixing-Controlled Compression Ignition Engines

In the last 20 years, biodiesel consumption in the United States has swiftly increased to ~2 billion gallons per year as a renewable supplement to fossil fuel. However, further expansion of biodiesel use is currently limited in part by poor cold weather performance, which prevents year-round blending and necessitates blend walls ≤5% v/v. In order to provide a diesel fuel blendstock with improved cold weather performance (cloud point, pour point, and cold filter plug point), while at the same time maintaining other required fuel performance specifications, several biodiesel redox analogues were synthesized and tested. The best performing candidate fuels from this class showed improvement in the derived cetane number (29.3% shorter ignition delay), lower heating value (+4.7 MJ/kg), relative sooting tendency (–7.4 YSI/MJ), and cloud point (15 °C lower) when compared to a B100 biodiesel composed of an identical fatty acid profile. It was observed as a general trend that the reduced form of biodiesel, fatty alkyl ethers (FAEs), shows performance improvements in all fuel property metrics. The suite of improved properties provided by FAEs gives biodiesel producers the opportunity to diversify their portfolio of products derived from lipid and alcohol feedstocks to include long-chain alkyl ethers, a biodiesel alternative with particular applicability for winter weather conditions across the US.

09 BIOMASS FUELS↗

DOE OSTI2020

Mesoscale Modeling to Characterize Eagle Soaring Habitat

Uncovering drivers of risk is crucial to understanding interactions between wildlife and wind turbines, and identifying options for impact minimization. These drivers tie to co-variates linked to behavior and movement patterns that allow us to estimate locations and periods of risk. For volant species, atmospheric flow can have significant influence on flight patterns. For obligate soaring birds, like golden eagles, updraft velocities can inform where eagles are likely to travel, at what altitude, and where conditions are not likely sufficient to sustain soaring flight. This has been an active area of study in recent years, using relatively coarse atmospheric data generally at the 20km x 20km scale or larger. Leveraging a 20-year dataset from the Weather Research and Forecasting Model (WRF) (https://www.mmm.ucar.edu/weather-research-and-forecasting-model), we are quantifying vertical velocities across the continental United States at a 2km x 2km resolution. Wind resource data sets originally were static maps showing the mean annual wind speed over an area. However, for these data sets to be optimally used for various applications they must be high-resolution time series, seamlessly span large geographic contexts, and account for uncertainty in wind speed. The National Renewable Energy Laboratory is producing public available datasets that meet these criteria and will be bias corrected to yield the most accurate wind resource data. This effort is an augment to the current WIND Toolkit which houses a high resolution data set. In the new iteration of the WIND Toolkit, a 20-year dataset will be used to improve the accuracy and estimate uncertainty using ensemble and machine-learning techniques. The resulting product will be the most accurate dataset of its size and at a 2km x 2km spatial and 5-minute temporal resolution. Through this work, a mesoscale vertical velocity layer will be produced by calculating the likelihood of orographic updraft and thermal updraft conditions across the continental United States. Specifically, we will use WRF model output combined with digital elevation maps to predict updrafts and then determine if vertical velocities are sufficient to support Golden Eagle soaring and gliding. Ultimately this data layer will be made available as a GIS layer in the Wind Prospector (maps.nrel.gov/wind-prospector/) tool or a similar framework. Data that will be incorporated include wind speed, direction temperature, relative humidity, barometric pressure, air density, precipitation rate, solar radiation, atmospheric stability, skin temperature, and upward heat flux. These products will advance research on interactions between volant species and wind energy by providing open access to highly resolved data with uncertainty quantification not previously available at this scale.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗