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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2

Browsing Space Weather Data and Models with the Integrated Space Weather Analysis (iSWA) System

The Integrated Space Weather Analysis (iSWA) System is a comprehensive web-based platform for space weather information that combines data from solar, heliospheric and geospace observatories with forecasts based on the most advanced space weather models. The iSWA system collects, generates, and presents a wide array of space weather resources in an intuitive, user-configurable, and adaptable format - thus enabling users to respond to current and future space weather impacts as well as enabling post-impact analysis. iSWA currently provides over 200 data and modeling products, and features a variety of tools that allow the user to browse, combine, and examine data and models from various sources. This presentation will consist of a summary of the iSWA products and an overview of the customizable user interfaces, and will feature several tutorial demonstrations highlighting the interactive tools and advanced capabilities.

Maddox, Marlo M.↗

Flight Test of Weather Data Exchange Using the 1090 Extended Squitter (1090ES) and VDL Mode 3 Data Links

This report describes preliminary results of work done by JHU/APL under contract to the NASA Glenn Research Center to support flight testing of the Universal Access Transceiver (UAT) data link as a medium for weather data exchange. It presents a high level architectural description of the use of UAT to meet the program objectives with an identification of issues associated with the use of this data link, including a high level definition of the changes required to UAT avionics and ground-based receivers and supporting ground infrastructure to support implementation of the recommended architecture with focus on the issues associated with these changes.

Griner, James H., Jr.↗

Systems Study of an Automated Fire Weather Data System

A sensor system applicable to an automated weather station was developed. The sensor provides automated fire weather data which correlates with manual readings. The equipment and methods are applied as an aid to the surveillance and protection of wildlands from fire damage. The continuous readings provided by the sensor system make it possible to determine the periods of time that the wilderness areas should be closed to the public to minimize the possibilities of fire.

Nishioka, K.↗

Gridded daily weather data for North America with comprehensive uncertainty quantification

Abstract Access to daily high-resolution gridded surface weather data based on direct observations and over long time periods is essential for many studies and applications including vegetation, wildlife, soil health, hydrological modelling, and as driver data in Earth system models. We present Daymet V4, a 40-year daily meteorological dataset on a 1 km grid for North America, Hawaii, and Puerto Rico, providing temperature, precipitation, shortwave radiation, vapor pressure, snow water equivalent, and day length. The dataset includes an objective quantification of uncertainty based on strict cross-validation analysis for temperature and precipitation results. The dataset represents several improvements from a previous version, and this data descriptor provides complete documentation for updated methods. Improvements include: reductions in the timing bias of input reporting weather station measurements; improvement to the three-dimensional regression model techniques in the core algorithm; and a novel approach to handling high elevation temperature measurement biases. We show cross-validation analyses with the underlying weather station data to demonstrate the technical validity of new dataset generation methods, and to quantify improved accuracy.

54 ENVIRONMENTAL SCIENCES↗

AWE: Aviation Weather Data Visualization Environment

The two official sources for aviation weather reports both provide weather information to a pilot in a textual format. A number of systems have recently become available to help pilots with the visualization task by providing much of the data graphically. However, two types of aviation weather data are still not being presented graphically. These are airport-specific current weather reports (known as meteorological observations, or METARs) and forecast weather reports (known as terminal area forecasts, or TAFs). Our system, Aviation Weather Environment (AWE), presents intuitive graphical displays for both METARs and TAFs, as well as winds aloft forecasts. We start with a computer-generated textual aviation weather briefing. We map this briefing onto a cartographic grid specific to the pilot's area of interest. The pilot is able to obtain aviation-specific weather for the entire area or for his specific route. The route, altitude, true airspeed, and proposed departure time can each be modified in AWE. Integral visual display of these three elements of weather reports makes AWE a useful planning tool, as well as a weather briefing tool.

Spirkovska, Lilly↗

Weather data at The Morton Arboretum 2017-2023

We have been monitoring long-term weather patterns using two weather stations at The Morton Arboretum to link environmental conditions to tree growth and other tree responses. This data package contains weather data at The Morton Arboretum from 2017-08-23 to 2023-12-31; data is located in the "MortonWeatherData2017_2023.csv" file. The two weather stations are located on each side of The Arboretum (e.g., the Nursery station on the East side and the Ware Field station on the West side; the two weather stations are 3.23 km apart and coordinates are included in the "Location_metadata.csv" file). Measured variables include rain accumulation, air temperature, relative humidity, three soil moisture/temperature measurements at various depths (10, 30, and 50 cm for the Nursery weather station, and 10, 25, and 50 cm for the Ware Field), solar radiation, saturation vapor pressure, and vapor pressure deficit.

54 ENVIRONMENTAL SCIENCES↗

Spatial Sampling of Weather Data for Regional Crop Yield Simulations

Field-scale crop models are increasingly applied at spatio-temporal scales that range from regions to the globe and from decades up to 100 years. Sufficiently detailed data to capture the prevailing spatio-temporal heterogeneity in weather, soil, and management conditions as needed by crop models are rarely available. Effective sampling may overcome the problem of missing data but has rarely been investigated. In this study the effect of sampling weather data has been evaluated for simulating yields of winter wheat in a region in Germany over a 30-year period (1982-2011) using 12 process-based crop models. A stratified sampling was applied to compare the effect of different sizes of spatially sampled weather data (10, 30, 50, 100, 500, 1000 and full coverage of 34,078 sampling points) on simulated wheat yields. Stratified sampling was further compared with random sampling. Possible interactions between sample size and crop model were evaluated. The results showed differences in simulated yields among crop models but all models reproduced well the pattern of the stratification. Importantly, the regional mean of simulated yields based on full coverage could already be reproduced by a small sample of 10 points. This was also true for reproducing the temporal variability in simulated yields but more sampling points (about 100) were required to accurately reproduce spatial yield variability. The number of sampling points can be smaller when a stratified sampling is applied as compared to a random sampling. However, differences between crop models were observed including some interaction between the effect of sampling on simulated yields and the model used. We concluded that stratified sampling can considerably reduce the number of required simulations. But, differences between crop models must be considered as the choice for a specific model can have larger effects on simulated yields than the sampling strategy. Assessing the impact of sampling soil and crop management data for regional simulations of crop yields is still needed.

upscaling↗

A New Source of Space Weather Data

The twin STEREO spacecraft were launched on October 26,2006 and, after spending several weeks in alignment orbits, became operational in heliocentric orbits on January 2 1,2007. The spacecraft are now in orbits similar to Earth's and are separating from each other at a rate of about 45 degrees per year as viewed from the sun. The STEREO spacecraft are each equipped with a complement of EUV, and white light imagers as well as particles and fields in situ instruments and a radio burst tracker. In addition to full resolution data downloaded once per day, each spacecraft broadcasts a real time telemetry 'beacon' stream containing compressed images and typically one minute averages of solar wind measurements and radio intensities. These real time data streams are received by a mix of NOAA and NASA-managed tracking stations and the data is transmitted by these stations to the STEREO Science Center at NASA Goddard Space Flight Center where they are processed into useable parameters with a latency of less than five minutes from receipt. As the two spacecraft recede from the sun-Earth line, triangulation of the imaging and radio measurements should allow better estimate of the speed and direction of coronal mass ejections, allowing a more precise estimate of their arrival at Earth. In situ particles and fields measurements, particularly for the spacecraft (Behind) trailing Earth in its orbit, will sample the solar wind that will eventually co-rotate around to the sun-Earth line. Late in the prime mission when the spacecraft are very far (>90 degrees) from the sun-Earth line, observations from the Behind spacecraft, will be particularly valuable for providing a preview of active regions well beyond the sun's East limb (as seen from Earth). Continually updated STEREO space weather data can be viewed and downloaded at http:/lstereo-ssc.nascom.nasa.govldata/beacon/.

Kaiser, Michael L.↗

Five Years of Dissolved Oxygen, Temperature, Salinity, Depth, Weather Data from a Transitioning Wetland at Beaver Creek, Washington, USA

Groundwater dissolved oxygen (DO) variability in coastal system remains poorly understood despite its importance for biogeochemical cycling and ecosystem modeling. Here we investigate the temporal variability in groundwater DO and its hydro-climatic drivers across hourly to seasonal timescales in a transitioning wetland at Beaver Creek, Washington, USA. The site is transitioning from a freshwater forest to a brackish tidal wetland following removal of a barrier in 2014 that prevented tides from accessing the freshwater creek. By utilizing novel optical dissolved oxygen instrumentation (Opti O2, LLC) we obtained continuous, high-frequency (5-minute), in-situ measurements of DO from the flood-plain from June 26th, 2019 through September 30th, 2024. This 63 month dataset is comprised of groundwater dissolved oxygen, temperature, water level and salinity timeseries from the floodplain. This dataset also includes rainfall, air pressure, air temperature, and solar radiation data collected with a co-located Campbell ClimaVUE50 weather sensor. All data is contained within a single csv (2019-06-26 to 2024-09-30 Beaver Creek DO, saln, BGS, temp, weather.csv) that can easily be viewed either using software such as Excel or using any text editor.

54 ENVIRONMENTAL SCIENCES↗

AWE: Aviation Weather Data Visualization

The two official sources for aviation weather reports both require the pilot to mentally visualize the provided information. In contrast, our system, Aviation Weather Environment (AWE) presents aviation specific weather available to pilots in an easy to visualize form. We start with a computer-generated textual briefing for a specific area. We map this briefing onto a grid specific to the pilot's route that includes only information relevant to his flight route that includes only information relevant to his flight as defined by route, altitude, true airspeed, and proposed departure time. By modifying various parameters, the pilot can use AWE as a planning tool as well as a weather briefing tool.

Spirkovska, Lilly↗

Block Island Environmental Monitoring Data (Weather, Waves & Sensor Depth)

This dataset contains meteorological, oceanographic, and sensor-depth data collected near Block Island during the 2016 and 2017 RODEO field seasons to provide environmental context for concurrent acoustic and survey operations. It includes buoy-derived wind and wave time series, in-situ water temperature logger records, and depth (pressure) records from a sensor mounted on the vertical line array.

17 WIND ENERGY↗

Aircraft Icing Weather Data Reporting and Dissemination System

The long-term operational concept of this research is to develop an onboard aircraft system that assesses and reports atmospheric icing conditions automatically and in a timely manner in order to improve aviation safety and the efficiency of aircraft operations via improved real-time and forecast weather products. The idea is to use current measurement capabilities on aircraft equipped with icing sensors and in-flight data communication technologies as a reporting source. Without requiring expensive avionics upgrades, aircraft data must be processed and available for downlink. Ideally, the data from multiple aircraft can then be integrated (along with other real-time and modeled data) on the ground such that aviation-centered icing hazard metrics for volumes of airspace can be assessed. As the effect of icing on different aircraft types can vary, the information should be displayed in meaningful ways such that multiple types of users can understand the information. That is, information must be presented in a manner to allow users to understand the icing conditions with respect to individual concerns and aircraft capabilities. This research provides progress toward this operational concept by: identifying an aircraft platform capable of digitally capturing, processing, and downlinking icing data; identifying the required in situ icing data processing; investigating the requirements for routing the icing data for use by weather products; developing an icing case study in order to gain insight into major air carrier needs; developing and prototyping icing display concepts based on the National Center for Atmospheric Research's existing diagnostic and forecast experimental icing products; and conducting a usability study for the prototyped icing display concepts.

Bass, Ellen J.↗

CROCUS Weather Data at Chicago State University Prairie Site

Vaisala WXT sensor is an all-in-one weather instrument that provides 6 of the most important weather parameters: barometric pressure, temperature, relative humidity, rainfall, wind speed and direction. Temperature, pressure, relative humidity, and rainfall are sampled at 1 second frequency, while wind speed/direction is measured at ten per second (10Hz) frequency. These measurements are useful for looking at characterizing local weather, identifying unique weather events, and studying local turbulence, especially given the high temporal resolution of the wind measurements. These measurements are collected at Chicago State University (CSU) at a prarie site on campus in Chicago, Illinois. Data is available in the netCDF data format, we encourage data users review documentation through Project Pythia to understand how to work with netCDF data https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html. The data is aggregated into daily frequency to make it easier to process multiple days, and compress the higher-resolution fields. Each file contains one day's worth of data (24 hours, starting at 0000 UTC). File naming convention includes the project (CROCUS), location (CSU), data level (raw, a1), date (year, month, day), and hour (0000).

54 ENVIRONMENTAL SCIENCES↗

Weather Data Receiver

Northern Video Graphics, Inc. developed a low-cost satellite receiving system for users such as independent meteorologists, agribusiness firms, small airports or flying clubs, marine vessels and small TV stations. Called Video Fax, it is designed for use with certain satellites; the GOES (Geostationary Operational Environmental Satellite) spacecraft operated by the National Oceanic and Atmospheric Administration, the European Space Agency's Meteosat and Japan's Geostationary Meteorological Satellite. By dictum of the World Meteorological Organization, signals from satellites are available to anyone without cost so the Video Fax user can acquire signals directly from the satellite and cut out the middle man, enabling savings. Unit sells for about one-fifth the cost of the equipment used by TV stations. It consists of a two-meter antenna; a receiver; a microprocessor-controlled display computer; and a video monitor. Computer stores data from the satellites and converts it to an image which is displayed on the monitor. Weather map can be preserved as signal data on tape, or it can be stored in a video cassette as a permanent image.

Source record↗

CROCUS Weather Data at University of Illinois - Chicago Tower

Vaisala WXT sensor is an all-in-one weather instrument that provides 6 of the most important weather parameters: barometric pressure, temperature, relative humidity, rainfall, wind speed and direction. Temperature, pressure, relative humidity, and rainfall are sampled at 1 second frequency, while wind speed/direction is measured at ten per second (10Hz) frequency. These measurements are useful for looking at characterizing local weather, identifying unique weather events, and studying local turbulence, especially given the high temporal resolution of the wind measurements. These measurements are collected at the University of Illinois in Chicago, Illinois, on the meteorological tower near the greenhouse on campus. Data is available in the netCDF data format, we encourage data users review documentation through Project Pythia to understand how to work with netCDF data https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html. File naming convention includes the project (CROCUS), location (UIC), data level (raw, a1), date (year, month, day), and hour (0000).

54 ENVIRONMENTAL SCIENCES↗