Search NASA⌕ Search

SEARCH · Search NASA

Results for “Weather Applications”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Application of Suomi-NPP Green Vegetation Fraction and NUCAPS for Improving Regional Numerical Weather Prediction

The NASA SPoRT Center is working to incorporate Suomi‐NPP products into its research and transition activities to improve regional numerical weather prediction (NWP). Specifically, SPoRT seeks to utilize two data products from NOAA/NESDIS: (1) daily global VIIRS green vegetation fraction (GVF), and (2) NOAA Unique CrIS and ATMS Processing System (NUCAPS) temperature and moisture retrieved profiles. The goal of (1) is to improve the representation of vegetation in the Noah land surface model (LSM) over existing climatological GVF datasets in order to improve the land‐atmosphere energy exchanges in NWP models and produce better temperature, moisture, and precipitation forecasts. The goal of (2) is to assimilate NUCAPS retrieved profiles into the Gridpoint Statistical Interpolation (GSI) data assimilation system to assess the impact on a summer pre‐frontal convection case. Most regional NWP applications make use of a monthly GVF climatology for use in the Noah LSM within the Weather Research and Forecasting (WRF) model. The GVF partitions incoming energy into direct surface heating/evaporation over bare soil versus evapotranspiration processes over vegetated surfaces. Misrepresentations of the fractional coverage of vegetation during anomalous weather/climate regimes (e.g., early/late bloom or freeze; drought) can lead to poor NWP model results when land‐atmosphere feedback is important. SPoRT has been producing a daily MODIS GVF product based on the University of Wisconsin Direct Broadcast swaths of Normalized Difference Vegetation Index (NDVI). While positive impacts have been demonstrated in the WRF model for some cases, the reflectances composing these NDVI do not correct for atmospheric aerosols nor satellite view angle, resulting in temporal noisiness at certain locations (especially heavy vegetation). The method behind the NESDIS VIIRS GVF is expected to alleviate the issues seen in the MODIS GVF real‐time product, thereby offering a higher‐quality dataset for modeling applications. SPoRT is evaluating the VIIRS GVF data against the MODIS real‐time and climatology GVF in both WRF and the NASA Land Information System. SPoRT has a history of assimilating hyperspectral infrared retrieved profiles

Numerical Weather Prediction↗
DOE OSTI2025

WRF-ELM v1.0: a regional climate model to study land–atmosphere interactions over heterogeneous land use regions

Abstract. The Energy Exascale Earth System Model (E3SM) Land Model (ELM) is a state-of-the-art land surface model that simulates the intricate interactions between the terrestrial land surface and other components of the Earth system. Originating from the Community Land Model (CLM) version 4.5, ELM has been under active development, with added new features and functionality, including plant hydraulics, radiation–topography interaction, subsurface multiphase flow, and more explicit land use and management practices. This study integrates ELM v2.1 with the Weather Research and Forecasting (WRF; WRF-ELM) model through a modified Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) framework, enabling affordable high-resolution regional modeling by leveraging ELM's innovative features alongside WRF's diverse atmospheric parameterization options. This framework includes a top-level driver for variable communication between WRF and ELM and Earth System Modeling Framework (ESMF) caps for the WRF atmospheric component and ELM workflow control, encompassing initialization, execution, and finalization. Importantly, this LILAC–ESMF framework demonstrates a more modular approach compared to previous coupling efforts between WRF and land surface models. It maintains the integrity of ELM's source code structure and facilitates the transfer of future developments in ELM to WRF-ELM. To test the ability of the coupled model to capture land–atmosphere interactions over regions with a variety of land uses and land covers, we conducted high-resolution (4 km) WRF-ELM ensemble simulations over the Great Lakes region (GLR) in the summer of 2018 and systematically compared the results against observations, reanalysis data, and WRF-CTSM (WRF coupled with the Community Terrestrial Systems Model). In general, the coupled WRF-ELM model has reasonably captured the spatial distribution of surface state variables and fluxes across the GLR, particularly over the natural vegetation areas. The evaluation results provide a baseline reference for further improvements in ELM in the regional application of high-resolution weather and climate predictions. Our work serves as an example to the model development community for expanding an advanced land surface model's capability to represent fully-coupled land–atmosphere interactions at fine spatial scales. The development and release of WRF-ELM marks a significant advancement for the ELM user community, providing opportunities for fine-scale regional representation, parameter calibration in coupled mode, and examination of new schemes with atmospheric feedback.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

AWIPS II Application Development, a SPoRT Perspective

The National Weather Service (NWS) is deploying its next‐generation decision support system, called AWIPS II (Advanced Weather Interactive Processing System II). NASA's Short‐term Prediction Research and Transition (SPoRT) Center has developed several software 'plug‐ins' to extend the capabilities of AWIPS II. SPoRT aims to continue its mission of improving short‐term forecasts by providing NASA and NOAA products on the decision support system used at NWS weather forecast offices (WFOs). These products are not included in the standard Satellite Broadcast Network feed provided to WFOs. SPoRT has had success in providing support to WFOs as they have transitioned to AWIPS II. Specific examples of transitioning SPoRT plug‐ins to WFOs with newly deployed AWIPS II systems will be presented. Proving Ground activities (GOES‐R and JPSS) will dominate SPoRT's future AWIPS II activities, including tool development as well as enhancements to existing products. In early 2012 SPoRT initiated the Experimental Product Development Team, a group of AWIPS II developers from several institutions supporting NWS forecasters with innovative products. The results of the team's spring and fall 2013 meeting will be presented. Since AWIPS II developers now include employees at WFOs, as well as many other institutions related to weather forecasting, the NWS has dealt with a multitude of software governance issues related to the difficulties of multiple remotely collaborating software developers. This presentation will provide additional examples of Research‐to‐Operations plugins, as well as an update on how governance issues are being handled in the AWIPS II developer community.

Burks, Jason E.↗
NASA NTRS2007

Satellite-Based Model Parameterization of Diabatic Heating

Future meteorological satellites are expected to provide much needed fine-scale information that can improve the accuracy of weather and climate models. As one application of this improved capability, we introduce the concept of a generalized parameterization framework using satellite datasets that will increase the accuracy and the computational efficiency of weather and climate modeling. In an atmospheric model, several different parameterizations usually are used to reproduce the various physical processes. However, it is generally unrealistic to separate the processes in this artificial way since the observations and physics make no such artificial separation. Thus, we propose a new unified parameterization framework to remove the unrealistic separation between parameterizations.

Pielke, Roger, Sr.↗
NASA NTRS2018

Extending Terrestrial Weather R2O/O2R to Space Weather at NASA's SPoRT Center

SPoRT (Short-Term Prediction Research and Transition Center)'s R2O/O2R (Research-to-Operations/Operations-to-Research) paradigm that has resulted in 15 plus years of success for terrestrial weather can be applied to space weather challenges. Given strong collaborations with NOAA (National Oceanic and Atmospheric Administration), SWPC (Space Weather Prediction Center), National Weather Service partners and seed-funded testbed activity, there is an opportunity to establish a bridge between NASA research community and operational forecasters for near-Earth applications. Starting local with strong space weather group at MSFC (Marshall Space Flight Center) and MAG4 (Magnetogram Forecast) with opportunities to strategically expand interaction to other groups generating space weather projects within NASA, university, and private sector community, using the Supercomputer for Satellite Simulations and Data Assimilation Studies (S4).

research-to-operations↗
DOE OSTI2026

Subseasonal Forecasting and MJO Teleconnections in Machine Learning Weather Prediction Models

Abstract In recent years, machine‐learning (ML) models trained on reanalysis data have rivaled physics‐based forecast models in terms of performance skill for global weather forecasting. With increased rollout stability, the question of how these models perform for subseasonal to seasonal (S2S, week 3–8) forecasting has emerged. In this study we run a large set of subseasonal hindcasts over 2004–2023 to evaluate two ML weather forecast models at the S2S time scale, SFNO‐HENS (Nvidia, fully ML) and NeuralGCM (Google Research, hybrid). Corresponding hindcasts from the European Centre for Medium‐Range Weather Forecasts (ECMWF) are used as a baseline for comparison to a physics‐based model. Because our focus is on predicting moisture transport over the Western United States between October and March, we evaluate the models' prediction skill for the Madden‐Julian Oscillation (MJO) and its associated teleconnections in the North Pacific. We find that both ML models are competitive with the ECWMF model, with comparable skill in predicting the North Pacific large‐scale circulation and the MJO at week 3 and beyond. Even though overall the mid‐latitude subseasonal prediction skill remains low, the ML models exhibit interesting behavior such as a realistic propagation of the MJO across the Maritime Continent and realistic teleconnections. A SFNO‐HENS sensitivity experiment with altered initial conditions in the tropics demonstrates the stability of the model, and it illustrates the capability of ML models to represent important physical processes of the atmosphere at the S2S time scale. Plain Language Summary Predicting weather patterns and precipitation a few weeks in advance (subseasonal time scale) is of great interest for stakeholders such as water managers in the Southwest United States (US), where arid conditions prevail. Subseasonal forecasts from traditional weather forecast models exhibit low skill in the region, limiting their applicability. Here we examine whether the recent breakthrough in weather forecasting made with machine learning/artificial intelligence models can translate to improved subseasonal forecasts. Recently‐developed machine learning models exhibit comparable skill to a state‐of‐the‐art physics‐based model for predicting weather patterns in the North Pacific/North America region, and associated moisture transport. The same applies to their skill in predicting the tropical pattern, the Madden‐Julian Oscillation, and its important remote perturbations over the midlatitude East Pacific and Southwest US. Additionally, a perturbation experiment carried out with one of the machine learning models illustrates their ability to not only predict the evolution of atmospheric fields, but also to learn and represent physical processes such as tropics‐extratropics Rossby wave propagation. Key Points Two machine learning weather forecast models exhibit state‐of‐the‐art prediction skill at the subseasonal time scale in the Pacific sector The models equal ECWMF in terms of Madden‐Julian oscillation (MJO) prediction skill, and they accurately predict the MJO propagation and associated teleconnections The two machine‐learning models represent key physical processes for subseasonal prediction, despite being trained for weather forecasting

Peings, Yannick↗
DOE OSTI2024

Hourly dynamic line ratings for existing transmission across the contiguous United States (preliminary results) [Slides]

The thermal rating of a transmission line depends on the rate at which heat generated by current flow through the line can be dissipated into the environment by convective and radiative cooling, keeping the conductor below a maximum operating temperature. Static or seasonal line ratings assume nearly-worst-case weather conditions (high ambient air temperature, high solar irradiance, and low wind speed), resulting in a low risk of "overrating" a line (i.e., allowing more current to flow than the line is designed for) but a high fraction of time when the line is "underrated" (i.e., able to flow more current while staying below the maximum temperature). Dynamic transmission line ratings (DLR) use real-time measurements of weather conditions, line sag, or line temperature to determine the thermal rating of transmission lines at hourly or higher time resolution, allowing for increased ratings during some (cold, windy, and/or dark) periods and correcting for overrating during other (hot, calm, and/or sunny) periods. Many studies have explored the benefits of DLR, but typically for small collections of transmission lines under a limited sample of weather conditions, leaving open the question of how widely applicable the benefits of DLR might be over diverse geographies and weather conditions. Here, we combine geospatial data on tens of thousands of transmission line routes across the contiguous United States with high-resolution hourly historical weather data for 2007-2013 to estimate the impact of DLR and other weather-adjusted rating systems. We compare static and dynamic line ratings to intermediate ratings adjusted by ambient temperature, day/night irradiance, clear-sky irradiance, and/or measured irradiance, illustrating the benefits of incorporating progressively more detailed weather data into the calculated line ratings. Moving from nighttime-adjusted ratings to clear-sky-adjusted ratings provides more benefit than moving from clear-sky-adjusted ratings to measured-irradiance-adjusted ratings. Depending on the assumed static windspeed for irradiance-adjusted-ratings, DLR either corrects for overrated hours or provides substantially increased ratings in the majority of hours on the majority of lines.

14 SOLAR ENERGY↗
NASA NTRS2004

Lunar and Planetary Science XXXV: Mars: Remote Sensing and Terrestrial Analogs

The session "Mars: Remote Sensing and Terrestrial Analogs" included the following:Physical Meaning of the Hapke Parameter for Macroscopic Roughness: Experimental Determination for Planetary Regolith Surface Analogs and Numerical Approach; Near-Infrared Spectra of Martian Pyroxene Separates: First Results from Mars Spectroscopy Consortium; Anomalous Spectra of High-Ca Pyroxenes: Correlation Between Ir and M ssbauer Patterns; THEMIS-IR Emissivity Spectrum of a Large Dark Streak near Olympus Mons; Geomorphologic/Thermophysical Mapping of the Athabasca Region, Mars, Using THEMIS Infrared Imaging; Mars Thermal Inertia from THEMIS Data; Multispectral Analysis Methods for Mapping Aqueous Mineral Depostis in Proposed Paleolake Basins on Mars Using THEMIS Data; Joint Analysis of Mars Odyssey THEMIS Visible and Infrared Images: A Magic Airbrush for Qualitative and Quantitative Morphology; Analysis of Mars Thermal Emission Spectrometer Data Using Large Mineral Reference Libraries ; Negative Abundance : A Problem in Compositional Modeling of Hyperspectral Images; Mars-LAB: First Remote Sensing Data of Mineralogy Exposed at Small Mars-Analog Craters, Nevada Test Site; A Tool for the 2003 Rover Mini-TES: Downwelling Radiance Compensation Using Integrated Line-Sight Sky Measurements; Learning About Mars Geology Using Thermal Infrared Spectral Imaging: Orbiter and Rover Perspectives; Classifying Terrestrial Volcanic Alteration Processes and Defining Alteration Processes they Represent on Mars; Cemented Volcanic Soils, Martian Spectra and Implications for the Martian Climate; Palagonitic Mars: A Basalt Centric View of Surface Composition and Aqueous Alteration; Combining a Non Linear Unmixing Model and the Tetracorder Algorithm: Application to the ISM Dataset; Spectral Reflectance Properties of Some Basaltic Weathering Products; Morphometric LIDAR Analysis of Amboy Crater, California: Application to MOLA Analysis of Analog Features on Mars; Airborne Radar Study of Soil Moisture at a Mars Analog Site: Tohachi Wash/Little Colorado River; and Antarctic Dry Valleys: Modification of Rocks and Soils and Implications for Mars The Arkaroola Mars Analogue Region, South Australia.

Source record↗
NASA NTRS2011

Next Generation Grating Spectrometer Sounders for LEO and GEO

AIRS and MODIS are widely used for weather, climate, composition, carbon cycle, cross-calibration, and applications. The community asking for new capability in the 2020 timeframe, capabilities desired: (1) Hyperspectral UV to LWIR, High Spatial ?1km IFOV (2) Maximize Synergies of Solar Reflected and IR. Synergies with OCO-2. We expect more users and applications of next gen LEO IR Sounder than GEO. These include: weather, climate, GHG monitoring, aviation, disaster response. There is a new direction for imagers and sounders: (1) Separate Vis/NIR/SWIR from MWIR/LWIR instruments reduces technology risk and complexity. (2) Expect Costs to be lower than CrIS & VIIRS Some additional ideas to reduce costs include: (1) minimum set of requirements (2) mini-grating spectrometers. supports constellation for higher revisit (3) new technology to reduce instrument size (large format fpa's) (4) hosted payloads

Hyperspectral↗
DOE OSTI2024

Review of data-driven models for quantifying load shed by non-residential buildings in the United States

Shifting and shedding power demand in buildings can be cost-effective techniques for grids to function reliably and for end users to earn compensation. Grid operators reimburse customers in proportion to the quantity of load shed. Simple data-driven methods are used to quantify this shed, which is the difference between a measured load during the event and modeled "baseline" that would have occurred in absence of the event. These methods have evolved over the years and in many cases have been integrated with building physics, to make them a hybrid between physics based and empirical models. However, there is no comprehensive analysis that provides guidance to building operators, grid operators and researchers in selecting appropriate models based on their specific needs and available data. Here, this work aims to fill this gap by critically assessing the performance of baseline models put forward from the year 2000 through 2023. The literature reviewed includes reports generated by grid operators, reports from national laboratories and academic journal articles. The work outlines modeling features like the inputs, training period, estimation method, adjustments to fine tune the predictions and metrics to evaluate the performance. A comprehensive list of 50 models has been provided. For each model, the study explores the applicability of the model to weather sensitive buildings, variability in the building profile, timing of the event, and whether the building reduces energy consumption before an event. The work identifies the situations in which a particular model works and draws lessons based on evidence of performance. Finally, recommendations to aid in model selection are given.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

The Impact of Stochastic Perturbations in Physics Variables for Predicting Surface Solar Irradiance

We present a probabilistic framework tailored for solar energy applications referred to as the Weather Research and Forecasting-Solar ensemble prediction system (WRF-Solar EPS). WRF-Solar EPS has been developed by introducing stochastic perturbations into the most relevant physical variables for solar irradiance predictions. In this study, we comprehensively discuss the impact of the stochastic perturbations of WRF-Solar EPS on solar irradiance forecasting compared to a deterministic WRF-Solar prediction (WRF-Solar DET), a stochastic ensemble using the stochastic kinetic energy backscatter scheme (SKEBS), and a WRF-Solar multi-physics ensemble (WRF-Solar PHYS). The performances of the four forecasts are evaluated using irradiance retrievals from the National Solar Radiation Database (NSRDB) over the contiguous United States. We focus on the predictability of the day-ahead solar irradiance forecasts during the year of 2018. The results show that the ensemble forecasts improve the quality of the forecasts, compared to the deterministic prediction system, by accounting for the uncertainty derived by the ensemble members. However, the three ensemble systems are under-dispersive, producing unreliable and overconfident forecasts due to a lack of calibration. In particular, WRF-Solar EPS produces less optically thick clouds than the other forecasts, which explains the larger positive bias in WRF-Solar EPS (31.7 W/m 2 ) than in the other models (22.7–23.6 W/m 2 ). This study confirms that the WRF-Solar EPS reduced the forecast error by 7.5% in terms of the mean absolute error (MAE) compared to WRF-Solar DET, and provides in-depth comparisons of forecast abilities with the conventional scientific probabilistic approaches (i.e., SKEBS and a multi-physics ensemble). Guidelines for improving the performance of WRF-Solar EPS in the future are provided.

14 SOLAR ENERGY↗
NASA NTRS1973

Extraterrestrial solar energy and its possible variations

Values of the solar constant and solar spectrum have been adopted as design standards for NASA space vehicles and as engineering standards by IES/ASTM. High resolution spectral data for the UV and visible range, normalized to these standards have been derived. Applications of these results for weather analysis, air pollution, ozone production, and atmospheric energy exchange are reviewed. Indications of possible variations in solar energy, total and spectral, and their influence on the earth-atmosphere system are examined. Programs for future studies of these variations from satellites and high-altitude aircraft are discussed.

Thekaekara, M. P.↗
NASA NTRS1986

The role of space borne imaging radars in environmental monitoring: Some shuttle imaging radar results in Asia

The synoptic view afforded by orbiting Earth sensors can be extremely valuable for resource evaluation, environmental monitoring and development planning. For many regions of the world, however, cloud cover has prevented the acquisition of remotely sensed data during the most environmentally stressful periods of the year. This paper discusses how synthetic aperture imaging radar can be used to provide valuable data about the condition of the Earth's surface during periods of bad weather. Examples are given of applications using data from the Shuttle Imaging Radars (SIR) A and B for agriculture land use and crop condition assessment, monsoon flood boundary and flood damage assessment, water resource monitoring and terrain modeling, coastal forest mapping and vegetation penetration, and coastal development monitoring. Recent SIR-B results in Bangladesh are emphasized, radar system basics are reviewed and future SAR systems discussed.

Imhoff, M.↗
NASA NTRS1989

Design of catalytic monoliths for closed-cycle carbon dioxide lasers

Pulsed carbon dioxide (CO2) lasers have many applications in aeronautics, space research, weather monitoring and other areas. Full exploitation of the potential of these lasers in hampered by the dissociation of CO2 that occurs during laser operation. The development of closed-cycle CO2 lasers requires active CO-O2 recombination (CO oxidation) catalyst and design methods for implementation of catalysts in CO2 laser systems. A monolith catalyst section model and associated design computer program, LASCAT, are presented to assist in the design of a monolith catalyst section of a closed cycle CO2 laser system. Using LASCAT,the designer is able to specify a number of system parameters and determine the monolith section performance. Trade-offs between the catalyst activity, catalyst dimensions, monolith dimensions, pressure drop, O2 conversion, and other variables can be explored and adjusted to meet system design specifications. An introduction describes a typical closed-cycle CO2 system, and indicates some advantages of a closed cycle laser system over an open cycle system and some advantages of monolith support over other types of supports. The development and use of a monolith catalyst model is presented. The results of a design study and a discussion of general design rules are given.

Herz, R. K.↗
NASA NTRS1990

A computer program for the design of optimum catalytic monoliths for CO2 lasers

Pulsed CO2 lasers have many applications in aeronautics, space research, weather monitoring and other areas. Full exploitation of the potential of these lasers is hampered by the dissociation of CO2 that occurs during laser operation. The development of closed-cycle CO2 lasers requires active CO-O2 recombination (CO oxidation) catalysts and design methods for implementation of catalysts inside lasers. The performance criteria and constraints involved in the design of catalyst configurations for use in a closed-cycle laser are discussed, and several design studies performed with a computerized design program that was written are presented. Trade-offs between catalyst activity and dimensions, flow channel dimensions, pressure drop, O2 conversion and other variables are discussed.

Guinn, K.↗
NASA NTRS1989

'Design of CO-O2 recombination catalysts for closed-cycle CO2 lasers'

Pulsed CO2 lasers have many applications in aeronautics, space research, weather monitoring and other areas. Full exploitation of the potential of these lasers is hampered by the dissociation of CO2 that occurs during laser operation. The development of closed-cycle CO2 lasers requires active CO-O2 recombination (CO oxidation) catalysts and design methods for implementation of catalysts inside lasers. This paper will discuss the performance criteria and constraints involved in the design of monolith catalyst configurations for use in a closed-cycle laser and will present a design study performed with a computerized design program that had been written. Trade-offs between catalyst activity and dimensions, flow channel dimensions, pressure drop, O2 conversion and other variables will be discussed.

Guinn, K.↗
NASA NTRS1969

Highlights 1969

This video includes Mariners to Mars; Orbiting Solar Observatory; Orbiting Geophysical Observatory; sounding rockets; weather satellites - Tiros and Nimbus; applications technology; advanced research; space shuttle research; V/STOL; jet noise abatement; and Apollo 9, 10, 11, and 12 missions.

Source record↗
NASA NTRS1996

Quality and Control of Water Vapor Winds

Water vapor imagery from the geostationary satellites such as GOES, Meteosat, and GMS provides synoptic views of dynamical events on a continual basis. Because the imagery represents a non-linear combination of mid- and upper-tropospheric thermodynamic parameters (three-dimensional variations in temperature and humidity), video loops of these image products provide enlightening views of regional flow fields, the movement of tropical and extratropical storm systems, the transfer of moisture between hemispheres and from the tropics to the mid- latitudes, and the dominance of high pressure systems over particular regions of the Earth. Despite the obvious larger scale features, the water vapor imagery contains significant image variability down to the single 8 km GOES pixel. These features can be quantitatively identified and tracked from one time to the next using various image processing techniques. Merrill et al. (1991), Hayden and Schmidt (1992), and Laurent (1993) have documented the operational procedures and capabilities of NOAA and ESOC to produce cloud and water vapor winds. These techniques employ standard correlation and template matching approaches to wind tracking and use qualitative and quantitative procedures to eliminate bad wind vectors from the wind data set. Techniques have also been developed to improve the quality of the operational winds though robust editing procedures (Hayden and Veldon 1991). These quality and control approaches have limitations, are often subjective, and constrain wind variability to be consistent with model derived wind fields. This paper describes research focused on the refinement of objective quality and control parameters for water vapor wind vector data sets. New quality and control measures are developed and employed to provide a more robust wind data set for climate analysis, data assimilation studies, as well as operational weather forecasting. The parameters are applicable to cloud-tracked winds as well with minor modifications. The improvement in winds through use of these new quality and control parameters is measured without the use of rawinsonde or modeled wind field data and compared with other approaches.

Jedlovec, Gary J.↗