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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Seasonal and Geographical Variations in Fundamental Weather Patterns during Extreme Precipitation as Identified from Omega Equation Forcing

Abstract We investigate the large-scale weather patterns during extreme precipitation (PEx) events over the conterminous United States (CONUS) by applying a version of the quasigeostrophic (QG) omega equation. This work aims to develop a climatology of the weather patterns most related to PEx events during current climate. Extreme events are examined for each of seven regions defined by consistent annual cycles of precipitation and spanning the CONUS. For the CONUS we train several self-organizing maps (SOM) on a pressure–time series of vertical velocity from each of the advective forcing terms in the QG omega equation for each extreme event. The unsupervised learning of the SOM allows us to identify the most descriptive set of nine patterns in vertical velocity associated with precipitation extremes. This method finds multiple frontal- and cyclone-driven patterns while grouping primarily convective events into one pattern. Frontal events include a synoptic pattern consistent with West Coast atmospheric river events as well as pattern groups linked to developing and to mature (“occluded”) frontal cyclones. The primary patterns found during PEx events vary seasonally and geographically. Frontal cyclone patterns are most common during PEx events during summer in the part of the Great Plains and during winter for the Northeast, Southeast, Pacific Northwest, and Southwest. Convection is the most common pattern during summer in all regions. Except in the Southeast, the annual cycles of monthly number of PEx events and average precipitation match well, partially validating our choice of regions to aggregate PEx events.

Meteorology & Atmospheric Sciences↗
NASA NTRS1976

Classification and machine recognition of severe weather patterns

Forecasting and warning of severe weather conditions are treated from the vantage point of pattern recognition by machine. Pictorial patterns and waveform patterns are distinguished. Time series data on sferics are dealt with by considering waveform patterns. A severe storm patterns recognition machine is described, along with schemes for detection via cross-correlation of time series (same channel or different channels). Syntactic and decision-theoretic approaches to feature extraction are discussed. Active and decayed tornados and thunderstorms, lightning discharges, and funnels and their related time series data are studied.

Wang, P. P.↗
DOE OSTI2024

A weather pattern responsible for increasing wildfires in the western United States

Abstract The western United States (U.S.) has been experiencing more severe wildfires, in part due to climate change, but the underlying synoptic patterns and their modulation in driving fire weather is unclear. Here we investigated the relationship between weather regimes (WRs) and fire weather indices, specifically vapor pressure deficit (VPD) and the Canadian Forest Fire Weather Index. By identifying five singular WRs using k-means clustering, we found that a particular regime (WR-2), one characterized by a distinct tripolar wave train pattern over the continental U.S., has exhibited an increased frequency since 1980. The ascribed WR-2 regime was found to be mainly responsible for rising trends in the fire weather indices, especially VPD. Further, the average fire indices of the WR-2 regime played a more important role than the frequency in shaping the rising trends in the fire weather indices. The increased frequency of the WR-2 WR was mainly attributed to anthropogenic forcing and, the year-to-year variation of the frequency was associated with sea surface temperature anomalies over the subtropical eastern Pacific. Human-induced climate change might have furthered the exacerbation of wildfire danger in the western U.S. by modulating the behaviors of WRs and fire weather indices.

Zhang, Wei (ORCID:0000000221698749)↗
NASA NTRS1975

Signatures analysis and recognition of severe weather patterns

The feasibility of designing a prediction and warning system for severe weather conditions on the basis of time series analysis and pattern recognition is examined. Data accumulated by Taylor (1972) on the rate of atmospherics produced by severe, tornado-producing storms that struck Oklahoma City during April 1970 are analyzed by time series analysis and pattern recognition. Power spectra, cross-power spectra, coherence functions, and time-varying patterns are analyzed.

Wang, P. P.↗
DOE OSTI2025

Linking large-scale weather patterns to observed and modeled turbine hub-height winds offshore of the US West Coast

The US West Coast holds great potential for wind power generation, although its potential varies due to the complex coastal climate. Characterizing and modeling turbine hub-height winds under different weather conditions are vital for wind resource assessment and management. This study uses a two-stage machine learning algorithm to identify five large-scale meteorological patterns (LSMPs): post-trough, post-ridge, pre-ridge, pre-trough, and California high. The LSMPs are linked to offshore wind patterns, specifically at lidar buoy locations within lease areas for future wind farm development off Humboldt and Morro Bay. While each LSMP is associated with characteristic large-scale atmospheric conditions and corresponding differences in wind direction, diurnal variation, and jet features at the two lidar sites, substantial variability in wind speeds can still occur within each LSMP. Wind speeds at Humboldt increase during the post-trough, pre-ridge, and California-high LSMPs and decrease during the remaining LSMPs. Morro Bay has smaller responses in mean speeds, showing increased wind speed during the post-trough and California-high LSMPs. Besides the LSMPs, local factors, including the land–sea thermal contrast and topography, also modify mean winds and diurnal variation. The High-Resolution Rapid Refresh model analysis does a good job of capturing the mean and variation at Humboldt but produces large biases at Morro Bay, particularly during the pre-ridge and California-high LSMPs. The findings are anticipated to guide the selection of cases for studying the influence of specific large-scale and local factors on California offshore winds and to contribute to refining numerical weather prediction models, thereby enhancing the efficiency and reliability of offshore wind energy production.

17 WIND ENERGY↗
NASA NTRS1980

Climatological relationships of severe duststorms in the Great Plains to synoptic weather patterns: A potential for predictability

A data base provided by 35 severe duststorms that occurred between 1968 and 1977 in the central and southern Great Plains allowed construction of a classification scheme of meteorological causes of duststorms, and a telescopic forecast technique for medium range (6 to 48 hour) prediction of severe cyclogenic duststorms. In addition, areal coverage definitions for duststorms based on characteristics of the storms, and a hierarchy of weather causes of severe duststorms were developed. The man machine mix forecast correctly predicted six of seven duststorms observed during the 1976-77 winter, with one overforecast; the machine-only forecast correctly predicted four of the seven duststorms, with one overforecast. Both techniques had problems correctly predicting the duration of severe duststorms.

Woiceshyn, P. M.↗
NASA NTRS1976

Time series analysis of sferics rate data associated with severe weather patterns

Data obtained by an electronic transducer measuring the rate of occurrence of electrical disturbances in the atmosphere (the sferic rate in the form of a time series) over the life of electrical storms are analyzed. It is found that the sferic rate time series are not stationary. The sferics rate time series has a complete life cycle associated with a particular storm. The approach to recognition of a spectral pattern is somewhat similar to real-time recognition of the spoken word.

Wang, P. P.↗
NASA NTRS1998

Martian Meteorology: Determination of Large Scale Weather Patterns from Surface Measurements

We employed numerical modelling of the martian atmosphere, and our expertise in understanding martian atmospheric processes, to better understand the coupling between lower and upper atmosphere processes. One practical application of this work has been our involvement with the ongoing atmospheric aerobraking which the Mars Global Surveyor (MGS) spacecraft is currently undergoing at Mars. Dr. Murphy is currently a member of the Mars Global Surveyor (MGS) Aerobraking Atmospheric Advisory Group (AAG). He was asked to participate in this activity based upon his knowledge of martian atmospheric dynamical processes. Aerobraking is a process whereby a spacecraft, in an elliptical orbit, passes through the upper layers of the atmosphere (in this instance Mars). This passage through the atmosphere 'drags' upon the spacecraft, gradually reducing its orbital velocity. This has the effect, over time, of converting the elliptical orbit to a circular orbit, which is the desired mapping orbit for MGS. Carrying out aerobraking eliminates the need for carrying large amounts of fuel on the spacecraft to execute an engine burn to achieve the desired orbit. Eliminating the mass of the fuel reduces the cost of launch. Damage to one of MGS's solar panels shortly after launch has resulted in a less aggressive extended in time aerobraking phase which will not end until March, 1999. Phase 1 extended from Sept. 1997 through March 1998. During this time period, Dr. Murphy participated almost daily in the AAG meetings, and beginning in December 1997 lead the meeting several times per week. The leader of each of the daily AAG meetings took the results of that meeting current state of the atmosphere, identification of any time trends or spatial patterns in upper atmosphere densities, etc.) forward to the Aerobraking Planning Group (APG) meeting, at which time the decision was made to not chance MGS orbit, to lower the orbit to reach higher densities (greater 'drag'), or raise the orbit to avoid experiencing excessive, possibly damaging densities.

Murphy, James R.↗
NASA NTRS1998

Martian Meteorology: Determination of Large Scale Weather Patterns from Surface Measurements

We employed numerical modelling of the martian atmosphere, and our expertise in understanding martian atmospheric processes, to better understand the coupling between lower and upper atmosphere processes. One practical application of this work has been our involvement with the ongoing atmospheric aerobraking which the Mars Global Surveyor (MGS) spacecraft is currently undergoing at Mars. Dr. Murphy is currently a member of the Mars Global Surveyor (MGS) Aerobraking Atmospheric Advisory Group (AAG). He was asked to participate in this activity based upon his knowledge of martian atmospheric dynamical processes. Aerobraking is a process whereby a spacecraft, in an elliptical orbit, passes through the upper layers of the atmosphere (in this instance Mars). This passage through the atmosphere 'drags'upon the spacecraft, gradually reducing its orbital velocity. This has the effect, over time, of converting the elliptical orbit to a circular orbit, which is the desired mapping orbit for MGS. Carrying out aerobraking eliminates the need for carrying large amounts of fuel on the spacecraft to execute an engine burn to achieve the desired orbit. Eliminating the mass of the fuel reduces the cost of launch. Damage to one of MGS's solar panels shortly after launch has resulted in a less aggressive extended in time aerobraking phase which will not end until March, 1999. Phase I extended from Sept. 1997 through March 1998. During this time period, Dr. Murphy participated almost daily in the AAG meetings, and beginning in December 1997 lead the meeting several times per week. The leader of each of the daily AAG meetings took the results of that meeting (current state of the atmosphere, identification of any time trends or spatial patterns in upper atmosphere densities, etc.) forward to the Aerobraking Planning Group (APG) meeting, at which time the decision was made to not change MGS orbit, to lower the orbit to reach higher densities (greater 'drag'), or raise the orbit to avoid experiencing excessive, possibly damaging densities.

Murphy, James R.↗
DOE OSTI2019

Atmospheric Blocking and Other Large-Scale Precursor Patterns of Landfalling Atmospheric Rivers in the North Pacific: A CESM2 Study

Atmospheric rivers, narrow channels of strong winds carrying abundant moisture and spanning thousands of kilometers, often result in flooding. The broader weather patterns that precede atmospheric river formation can determine which regions the storms will impact, but our understanding of such processes remains insufficient. In this study, atmospheric river events in the North Pacific region are identified, and their precursor weather patterns are examined in observational data sets and within a global climate model. The analysis shows that when a large area of high pressure forms over Alaska and far eastern Siberia, the preferred path of storms crossing the North Pacific is diverted toward the south. The southward-shifted storms, some of which develop into atmospheric rivers, guide moist air toward the U.S. west coast and can produce extreme precipitation. The climate model performs reasonably well at representing atmospheric rivers and their associated precursor weather patterns. These results highlight important connections between atmospheric rivers and the large-scale weather patterns than can precede them by more than a week. Knowledge of such patterns has the potential to improve predictions of damaging wind and extreme precipitation events.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

Integration of Weather Avoidance and Traffic Separation

This paper describes a dynamic convective weather avoidance concept that compensates for weather motion uncertainties; the integration of this weather avoidance concept into a prototype 4-D trajectory-based Airborne Separation Assurance System (ASAS) application; and test results from a batch (non-piloted) simulation of the integrated application with high traffic densities and a dynamic convective weather model. The weather model can simulate a number of pseudo-random hazardous weather patterns, such as slow- or fast-moving cells and opening or closing weather gaps, and also allows for modeling of onboard weather radar limitations in range and azimuth. The weather avoidance concept employs nested "core" and "avoid" polygons around convective weather cells, and the simulations assess the effectiveness of various avoid polygon sizes in the presence of different weather patterns, using traffic scenarios representing approximately two times the current traffic density in en-route airspace. Results from the simulation experiment show that the weather avoidance concept is effective over a wide range of weather patterns and cell speeds. Avoid polygons that are only 2-3 miles larger than their core polygons are sufficient to account for weather uncertainties in almost all cases, and traffic separation performance does not appear to degrade with the addition of weather polygon avoidance. Additional "lessons learned" from the batch simulation study are discussed in the paper, along with insights for improving the weather avoidance concept. Introduction

Consiglio, Maria C.↗
NASA NTRS1995

Looking at Earth from Space: Teacher's Guide with Activities for Earth and Space Science

The Maryland Pilot Earth Science and Technology Education Network (MAPS-NET) project was sponsored by the National Aeronautics and Space Administration (NASA) to enrich teacher preparation and classroom learning in the area of Earth system science. This publication includes a teacher's guide that replicates material taught during a graduate-level course of the project and activities developed by the teachers. The publication was developed to provide teachers with a comprehensive approach to using satellite imagery to enhance science education. The teacher's guide is divided into topical chapters and enables teachers to expand their knowledge of the atmosphere, common weather patterns, and remote sensing. Topics include: weather systems and satellite imagery including mid-latitude weather systems; wave motion and the general circulation; cyclonic disturbances and baroclinic instability; clouds; additional common weather patterns; satellite images and the internet; environmental satellites; orbits; and ground station set-up. Activities are listed by suggested grade level and include the following topics: using weather symbols; forecasting the weather; cloud families and identification; classification of cloud types through infrared Automatic Picture Transmission (APT) imagery; comparison of visible and infrared imagery; cold fronts; to ski or not to ski (imagery as a decision making tool), infrared and visible satellite images; thunderstorms; looping satellite images; hurricanes; intertropical convergence zone; and using weather satellite images to enhance a study of the Chesapeake Bay. A list of resources is also included.

Steele, Colleen↗
DOE OSTI2026

Comparing Synoptic Pattern Evolution for Flash‐Flood‐Producing and Non‐Flash‐Flood‐Producing Mesoscale Convective Systems in the United States

Understanding how the short-term evolution of synoptic weather patterns influence Mesoscale Convective Systems (MCSs) is essential, as these systems are responsible for over half of central U.S. flash floods, leading to substantial socioeconomic and water resource management impacts. This study analyzes long-term MCS data, flash flood reports, and atmospheric reanalyses from 2007 to 2017 using a machine learning clustering algorithm to examine how the synoptic weather patterns evolve prior to MCS initiation. While the clusters reflect seasonal and regional differences in MCS occurrence, they do not consistently distinguish between MCSs that do and do not produce flash floods. Systems in the southern Great Plains are more flood-prone when a synoptic-scale forcing, located near the system, drives strong water vapor transport from the nearby moisture source. More generally under different synoptic weather patterns, a broader precipitating area is the most dominant factor governing MCS flash flood potential.

atmospheric dynamics↗
NASA NTRS1998

Impact of the 1997-1998 El-Nino of Regional Hydrology

The 1997-1998 El-Nino brought with it a range of severe local-regional hydrological phenomena. Record high temperatures and extremely dry soil conditions in Texas is an example of this regional effect. The El-Nino and La-Nina change the continental weather patterns considerably. However, connections between continental weather anomalies and regional or local anomalies have not been established to a high degree of confidence. There are several unique features of the recent El-Nino and La-Nina. Due to the recognition of the present El-Nino well in advance, there have been several coupled model studies on global and regional scales. Secondly, there is a near real-time monitoring of the situation using data from satellite sensors, namely, SeaWIFS, TOVS, AVHRR and GOES. Both observations and modeling characterize the large scale features of this El-Nino fairly well. However the connection to the local and regional hydrological phenomenon still needs to be made. This paper will use satellite observations and analysis data to establish a relation between local hydrology and large scale weather patterns. This will be the first step in using satellite data to perform regional hydrological simulations of surface temperature and soil moisture.

Lakshmi, Venkataraman↗
NASA NTRS2024

Mars Climate Monitoring Mission

For future missions to Mars, Nasa wants a better understanding of the regular weather patterns on Mars. Current models of martian weather are not up to the task of predicting weather that could impair future martian prospects. To improve our models, we need accurate data, measured directly from orbiters or surface stations, like rovers or probes. One solution is to send a web of permanent surface weather stations to various locations on the surface, in order to get accurate data about large-scale martian weather patterns. Such data could be used to improve our models which could greatly aid in improving the safety of future exploration. Such a mission, though, would have countless moving parts, from launch till landing. We created this short animation to demonstrate how such a mission might be carried out, what it might tell us, and how that information could prove critically useful for future martian exploration, including human missions to the surface.

Mars↗
DOE OSTI2018

On-line optimization scheme for HVAC demand response

A computer-implemented method of optimizing demand-response (DR) of a heating, ventilation, and air-conditioning (HVAC) system of a building, includes determining (30, 31, 32) a value of an objective function F.sub.ij of a HVAC system for each of a plurality of DR strategies j for each of a plurality of weather patterns i that is a weighted sum of an energy cost of the HVAC system and a thermal comfort loss of the HVAC system, assigning (33, 34, 35, 36) a likelihood score L.sub.i,j to each of a selected subset of near-optimal DR strategies j for each weather pattern i, and selecting (37, 38) those near-optimal DR strategies with large overall likelihood scores L.sub.j to create an optimal strategy pool of DR strategies. An optimal strategy pool can be searched (39) in real-time for an optimal DR strategy for a given weather pattern.

42 ENGINEERING↗
DOE OSTI2026

Emergence of Diverse Failure Patterns in Weathering‐Induced Landslides: Insights From Particle Finite Element Simulations

Weathering is a fundamental driver of landslide evolution over geological timescales. Despite its ubiquity and importance, quantifying how weathering drives the progressive destabilization of rock slopes remains challenging. In this work, we develop a unified computational framework based on the particle finite element method to investigate the evolution of weathering‐induced landslides, from long‐term weathering to short‐term slope failure and runout dynamics. The framework integrates key processes, including weathering front propagation, time‐dependent strength degradation, rupture surface development, and post‐failure runout dynamics. Through numerical simulation experiments, we elucidate how interactions among weathering characteristics (type, intensity, and rate law), bedrock strength, fracture distribution, and slope geometry govern the failure modes and kinematics of weathering‐induced landslides. Simulations show that matrix‐dominated weathering leads to shallow translational failures, whereas fracture‐dominated weathering produces deep‐seated rotational and compound landslides. Pre‐existing fractures and slope morphology also strongly influence the movement of destabilized landmasses, affecting the failure pattern (e.g., kinematic mode and rupture surface geometry) and post‐failure behavior (e.g., runout velocity). We further demonstrate that the failure time and volume of weathered slopes are governed by the competition between gravitational driving forces and cohesive resisting forces during progressive destabilization. These findings provide new insights into the fundamental mechanisms that drive the emergence of diverse failure patterns of weathering‐induced landslides with important implications for landslide hazard assessment.

Wang, Liang [Eidgenoessische Technische Hochschule↗
DOE OSTI2024

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↗