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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Storm Surge and Ponding Explain Mangrove Dieback in Southwest Florida Following Hurricane Irma

Mangroves buffer inland ecosystems from hurricane winds and storm surge. However, their ability to withstand harsh cyclone conditions depends on plant resilience traits and geomorphology. Using airborne lidar and satellite imagery collected before and after Hurricane Irma, we estimated that 62% of mangroves in southwest Florida suffered canopy damage, with largest impacts in tall forests (>10 m). Mangroves on well-drained sites (83%) resprouted new leaves within one year after the storm. By contrast, in poorly-drained inland sites, we detected one of the largest mangrove diebacks on record (10,760 ha), triggered by Irma. We found evidence that the combination of low elevation (median = 9.4 cm asl), storm surge water levels (>1.4 m above the ground surface), and hydrologic isolation drove coastal forest vulnerability and were independent of tree height or wind exposure. Our results indicated that storm surge and ponding caused dieback, not wind. Tidal restoration and hydrologic management in these vulnerable, low-lying coastal areas can reduce mangrove mortality and improve resilience to future cyclones.

David Lagomasino↗
NASA NTRS2022

Leveraging Pre-storm Soil Moisture Estimates for Enhanced Land Surface Model Calibration in Ungauged Hydrologic Basins

Despite long-standing efforts, hydrologists still lack robust tools for calibrating land surface model (LSM) streamflow estimates within ungauged basins. Using surface soil moisture estimates from the Soil Moisture Active Passive Level 4 Soil Moisture (L4_SM) product, precipitation observations, and streamflow gauge measurements for 617 medium-scale (200-10,000 km2) basins in the contiguous United States, we measure the temporal (Spearman) rank correlation between antecedent (i.e., pre-storm) surface soil moisture (ASM) and the storm-scale runoff coefficient (RC; the fraction of storm-scale precipitation accumulation converted into streamflow). In humid and semi-humid basins, this rank correlation is shown to be sufficiently strong to allow for the substitution of storm-scale RC observations (available only in basins that are both lightly regulated and gauged) with high-quality ASM values (available quasi-globally from L4_SM) in streamflow calibration procedures. Using this principle, we define a new, basin-wise LSM streamflow calibration approach based on L4_SM alone and successfully apply it to identify LSM configurations that produce a high rank correlation with observed RC. However, since the approach cannot detect RC bias, it is less successful in identifying LSM configurations with low mean-absolute error. Plain Text Summary Accurately forecasting the fraction of rainfall that runs off into streams, as opposed to infiltrates into the soil, is critical for flash-flood prediction, water-resource monitoring, and tracking the transport of nutrients from agricultural fields into local waterways. Such forecasting is typically performed by hydrologic models that attempt to represent the physical processes responsible for surface runoff generation. However, to provide accurate streamflow forecasts, these models typically need to be calibrated against actual streamflow observations. This is problematic given the relatively poor, and declining, global availability of stream gauges. This paper presents a novel model calibration strategy that uses soil moisture from remote sensing and numerical modeling in place of streamflow observations during calibration. This transition has significant practical advantages because, unlike streamflow observations, the soil moisture data are continuously available across space. Our results demonstrate that this new approach can significantly improve hydrologic models within humid and semi-humid basins lacking sufficient ground-based instrumentation for traditional streamflow calibration.

hydrologic models↗
NASA NTRSDate not supplied

Study the Vertical Structure and Transportation of the Extreme African Dust Storms using MERRA-2 Data

The Modern-Era Retrospective Analysis for Research and Application, Version 2 (MERRA-2) provides the first long-term global reanalysis to assimilate space-based observations of aerosols and represents their interactions with other physical processes in the climate system. In this study, we have examined the variations of atmospheric aerosols for the last 20 years since 2002 using the sub-daily MERRA-2 data and found seven extreme African dust storms that were transported westward across the Atlantic Ocean from the Sahara, crossing 70o-80oW. In particular, the well-known ‘Godzilla’ dust storm occurred in June 2020, and its dust cloud, with the highest-on-record aerosol optical depths, was transported toward the Americas. This storm greatly degraded air quality over large areas of the Caribbean Basin and the United States. The air quality index reached unhealthy levels for sensitive groups in more than ten U.S. states. In our study, the vertical structure and transport characteristics of the dust layers during this extreme dust event are investigated. The geopotential height and temperature were found anomalously low (around 600 hPa) over the Atlantic Ocean off northwest Africa before the June 2020 dust storm. This anomalous circulation pattern was persistent for more than 12 days starting from around May 30, breaking the regular easterly waves that transport dust from the Sahara Desert to the west. To verify the data quality, daily MERRA-2 PM2.5 data were calculated and compared with PM2.5 observations from the U.S. Environmental Protection Agency (EPA) at several selected ground stations in Florida. We provide this case study to illustrate how to effectively use various MERRA-2 data services at Goddard Earth Sciences Data and Information Services Center (GES DISC) where MERRA-2 data are archived, hoping to help data users in exploring their own topics of interest using data services at GES DISC.

data management, reanalysis↗
NASA NTRS2022

What Is Unusual About the Third Largest Geomagnetic Storm of Solar Cycle 24?

We report on the solar and interplanetary (IP) causes of the third largest geomagnetic storm (26 August 2018) in solar cycle 24. The underlying coronal mass ejection (CME) originating from a quiescent filament region becomes a 440 km/s magnetic cloud (MC) at 1 au after ∼5 days. The prolonged CME acceleration (for ∼24 hr) coincides with the time profiles of the post-eruption arcade intensity and reconnected flux. Chen et al. (2019, https://doi.org/10.3847/1538-4357/ab3f36) obtain a lower speed since they assumed that the CME does not accelerate after ∼12 hr. The presence of multiple coronal holes near the filament channel and the high-speed wind from them seem to have the combined effect of producing complex rotation in the corona and IP medium resulting in a high-inclination MC. The Dst time profile in the main phase steepens significantly (rapid increase in storm intensity) coincident with the density increase (prominence material) in the second half of the MC. Simulations using the Comprehensive Inner Magnetosphere-Ionosphere model show that a higher ring current energy results from larger dynamic pressure (density) in MCs. Furthermore, the Dst index is highly correlated with the main-phase time integral of the ring current injection that includes density, consistent with the simulations. A complex temporal structure develops in the storm main phase if the underlying MC has a complex density structure during intervals of southward IP magnetic field. We conclude that the high intensity of the storm results from the prolonged CME acceleration, complex rotation of the CME flux rope, and the high density in the 1-au MC.

N. Gopalswamy↗
NASA NTRS2023

Comparing Magnetopause Predictions From Two MHD Models During A Geomagnetic Storm and A Quiet Period

Magnetopause location is an important prediction of numerical simulations of the magnetosphere, yet the models can err, either under-predicting or over-predicting the motion of the boundary. This study compares results from two of the most widely used magnetohydrodynamic (MHD) models, the Lyon–Fedder–Mobarry (LFM) model and the Space Weather Modeling Framework (SWMF), to data from the GOES 13 and 15 satellites during the geomagnetic storm on 22 June 2015, and to THEMIS A, D, and E during a quiet period on 31 January 2013. The models not only reproduce the magnetopause crossings of the spacecraft during the storm, but they also predict spurious magnetopause motion after the crossings seen in the GOES data. We investigate the possible causes of the over-predictions during the storm and find the following. First, using different ionospheric conductance models does not significantly alter predictions of the magnetopause location. Second, coupling the Rice Convection Model (RCM) to the MHD codes improves the SWMF magnetopause predictions more than it does for the LFM predictions. Third, the SWMF produces a stronger ring current than LFM, both with and without the RCM and regardless of the LFM spatial resolution. During the non-storm event, LFM predicts the THEMIS magnetopause crossings due to the southward interplanetary magnetic field better than the SWMF. Additionally, increasing the LFM spatial grid resolution improves the THEMIS predictions, while increasing the SWMF grid resolutions does not.

magnetohydrodynamics↗
NASA NTRS2024

Search Technology for Optimal Rescue Missions (STORM)

Natural disasters, such as earthquakes, hurricanes, and wildfires are responsible for the deaths of 60,000 to 90,000 people per year. Today, search and rescue (SAR) operations heavily rely on humans to find and deliver life-saving supplies to those affected by these disasters. However, these operations have limits in visibility, navigation, communication systems, and data availability in the area affected, as well as endangering the SAR personnel. Search Technology for Optimal Rescue Missions (STORM) discusses a new system for SAR teams using autonomous drones able to find and deliver supplies to people, without risking more lives in the process. The concept includes the use of two drone types, STORM Search and STORM Rescue, which will survey and locate survivors and be able to drop equipment to the survivors identified, respectively. These two types of drones were optimized in drone design and durability (such as the use of dihedral wings and a toroidal propeller), detection and navigation systems (sturdy thermal and Light Detection and Ranging [LiDAR] cameras), automation and system design (Machine Learning and Computer Vision), server-drone communication (Meshnets), weight, and cost. Once implemented, the STORM concept is expected to improve, ease, and speed up SAR operations, and most important of all, rescue lives that would have never been currently possible to find.

Astha Ingole↗
NASA NTRS1996

Magnetic Storms

This talk provides a brief summary of the first conference devoted entirely to magnetic storms. Topics cover the relevant phenomena at the Sun/corona, propogation of these structures through interplanetary space, the response of the magnetosphere to interaction with these interplanetary structures, the formation of the storm time ring current (in particular the oxygen content of the ring-current), and storm ionospheric effects and ground based effects.

magnetic storms magnetosphere storm time ring curr↗
NASA NTRS1997

(abstract) Application of the GPS Worldwide Network in the Study of Global Ionospheric Storms

Ionospheric storm dynamics as a response to the geomagnetic storms is a very complicated global process involving many different mechanisms. Studying ionospheric storms will help us to understand the energy coupling process between the Sun and Earth and possibly also to effectively forecast space weather changes. Such a study requires a worldwide monitoring system. The worldwide GPS network, for the first time, makes near real-time global ionospheric TEC measurements a possibility.

GPS ionospheric storms communications geomagnetic ↗
DOE OSTI2024

Current Practices in Distribution Utility Resilience Planning for Hurricanes and Non-Winter Storms

This report is part of a series of hazard-focused case studies examining common practices in electric utility resilience planning. We use standard terminology defining resilience as the ability to anticipate, withstand, absorb, and recover from hazards that cause long duration outages. We distinguish between reliability and resilience using IEEE 1366-2022, which defines "major events" as "an event that exceeds reasonable design and/or operational limits of the electric power system." Resilience planning is focused on "major event days" and reliability planning is focused on non-major event days. Utility resilience plans are assessed according to common recommended resilience components that we have identified in existing resilience frameworks. The focus of this report is on hurricanes and severe storms in which the primary hazards are precipitation or high winds. We exclude winter storms with primary hazards of ice and extreme cold, as they are a unique set of hazards with different resilience considerations. Standalone reports focusing on wildfires and winter storms have been published in parallel with this report. This report can be used as a starting point for understanding potential investment prioritization processes and investment options. This report is intended to improve utility resilience planning by supporting constructive dialogue among utilities, regulators, and other stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Satellite Imagery of PV Site Storm Damage

"This repository contains multiple data sets focused on visible damage to photovoltaic (PV) installations following extreme weather events such as hailstorms and hurricanes. Data sets are split into two categories: the first category, the ‘manually labeled’ data, was compiled by researchers manually, and contains manually identified PV sites exposed to storms. The second data set, the ‘aggregated’ data, is a compilation of the manually labeled PV sites and deep learning-identified PV sites. The hail damage data set focuses on post-storm PV damage following a September 24, 2023 hailstorm in Austin, TX, which caused over $600 million in damages in the Austin metro area. The hurricane damage data set focuses on post-storm PV damage following Hurricanes Irma and Maria in Puerto Rico and the US Virgin Islands. Hurricanes Irma and Maria were back-to-back category 5 hurricanes, which pummeled the Caribbean and southeastern United States in September 2017, causing an estimated $115.2 billion in damages."

14 SOLAR ENERGY↗
NASA NTRS1996

The Distant Tail Behavior During High Speed Solar Wind Streams and Magnetic Storms

We have examined the ISEE-3 distant tail data during three intense (Dst< -100(sub n)T) magnetic storms and have identified the tail response to high speed solar wind streams, interplanetary magnetic clouds, and near-Earth storms. The three storms have a peak Dst ranging from -150 to -220 nT, and occur on Jan. 9, Feb. 4, and Aug. 8, 1993.

ISEE-3 solar wind streams solar wind magnetic clou↗
NASA NTRS2014

Forcing of the Coupled Ionosphere-Thermosphere (IT) System During Magnetic Storms

Poynting flux shows peaks around auroral zone AND inside polar cap. Energy enters IT system at all local times in polar cap. Track-integrated flux at DMSP often peaks at polar latitudes- probably due to increased area of polar cap during storm main phases. center dot lon temperatures at DMSP show large increases in polar region at all local times; cusp and auroral zones do not show distinctively high Ti. center dot I on temperatures in the polar cap are higher than in the auroral zones during quiet times. center dot Neutral densities at GRACE and GOCE show maxima at polar latitudes without clear auroral signatures. Response is fast, minutes from onset to density peaks. center dot GUVI observations of O/N2 ratio during storms show similar response as direct measurements of ion and neutral densities, i.e. high temperatures in polar cap during prestorm quiet period, heating proceeding from polar cap to lower latitudes during storm main phase. center dot Discrepancy between maps of Poynting flux and of ion temperatures/neutral densities suggests that connection between Poynting flux and Joule heating is not simple.

Magnetic Storms↗
NASA NTRS2016

Automated Storm Tracking and the Lightning Jump Algorithm Using GOES-R Geostationary Lightning Mapper (GLM) Proxy Data

This study develops a fully automated lightning jump system encompassing objective storm tracking, Geostationary Lightning Mapper proxy data, and the lightning jump algorithm (LJA), which are important elements in the transition of the LJA concept from a research to an operational based algorithm. Storm cluster tracking is based on a product created from the combination of a radar parameter (vertically integrated liquid, VIL), and lightning information (flash rate density). Evaluations showed that the spatial scale of tracked features or storm clusters had a large impact on the lightning jump system performance, where increasing spatial scale size resulted in decreased dynamic range of the system's performance. This framework will also serve as a means to refine the LJA itself to enhance its operational applicability. Parameters within the system are isolated and the system's performance is evaluated with adjustments to parameter sensitivity. The system's performance is evaluated using the probability of detection (POD) and false alarm ratio (FAR) statistics. Of the algorithm parameters tested, sigma-level (metric of lightning jump strength) and flash rate threshold influenced the system's performance the most. Finally, verification methodologies are investigated. It is discovered that minor changes in verification methodology can dramatically impact the evaluation of the lightning jump system.

lightning jump↗
NASA NTRS2017

Development of High-Resolution Dynamic Dust Source Function - A Case Study with a Strong Dust Storm in a Regional Model

A high-resolution dynamic dust source has been developed in the NASA Unified-Weather Research and Forecasting (NU-WRF) model to improve the existing coarse static dust source. In the new dust source map, topographic depression is in 1-km resolution and surface bareness is derived using the Normalized Difference Vegetation Index (NDVI) data from Moderate Resolution Imaging Spectroradiometer (MODIS). The new dust source better resolves the complex topographic distribution over the Western United States where its magnitude is higher than the existing, coarser resolution static source. A case study is conducted with an extreme dust storm that occurred in Phoenix, Arizona in 0203 UTC July 6, 2011. The NU-WRF model with the new high-resolution dynamic dust source is able to successfully capture the dust storm, which was not achieved with the old source identification. However the case study also reveals several challenges in reproducing the time evolution of the short-lived, extreme dust storm events.

Dynamic dust source↗
NASA NTRS2014

Changes to Saturn's Zonal-Mean Tropospheric Thermal Structure After the 2010-2011 Northern Hemisphere Storm

We use far-infrared (20-200 micrometers) data from the Composite Infrared Spectrometer on the Cassini spacecraft to determine the zonal-mean temperature and hydrogen para-fraction in Saturn's upper troposphere from observations taken before and after the large northern hemisphere storm in 2010-2011. During the storm, zonal mean temperatures in the latitude band between approximately 25 deg N and 45 deg N (planetographic latitude) increased by about 3 K, while the zonal mean hydrogen para-fraction decreased by about 0.04 over the same latitudes, at pressures greater than about 300 mbar. These changes occurred over the same latitude range as the disturbed cloud band seen in visible images. The observations are consistent with low para-fraction gas being brought up from the level of the water cloud by the strong convective plume associated with the storm, while being heated by condensation of water vapor, and then advected zonally by the winds near the plume tops in the upper troposphere.

Saturn↗
DOE OSTI2024

Storm surges and extreme sea levels: Review, establishment of model intercomparison and coordination of surge climate projection efforts (SurgeMIP).

Coastal flood damage is primarily the result of extreme sea levels. Climate change is expected to drive an increase in these extremes. While proper estimation of changes in storm surges is essential to estimate changes in extreme sea levels, there remains low confidence in future trends of surge contribution to extreme sea levels. Alerting local populations of imminent extreme sea levels is also critical to protecting coastal populations. Both predicting and projecting extreme sea levels require reliable numerical prediction systems. The SurgeMIP (surge model intercomparison) community has been established to tackle such challenges. Efforts to intercompare storm surge prediction systems and coordinate the community 's prediction and projection efforts are introduced. An overview of past and recent advances in storm surge science such as physical processes to consider and the recent development of global forecasting systems are briefly introduced. Selected historical events and drivers behind fast increasing service and knowledge requirements for emergency response to adaptation considerations are also discussed. The community 's initial plans and recent progress are introduced. These include the establishment of an intercomparison project, the identification of research and development gaps, and the introduction of efforts to coordinate projections that span multiple climate scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

STORM Super-Resolution Visualization of Self-Assembled γPFD Chaperone Ultrastructures in Methanocaldococcus jannaschii

Gamma-prefoldin (γPFD), a unique chaperone found in the extremely thermophilic methanogen Methanocaldococcus jannaschii, self-assembles into filaments in vitro, which so far have been observed using transmission electron microscopy and cryo-electron microscopy. Utilizing three-dimensional stochastic optical reconstruction microscopy (3D-STORM), here we achieve ~20 nm resolution by precisely locating individual fluorescent molecules, hence resolving γPFD ultrastructure both in vitro and in vivo. Through CF647 NHS ester labeling, we first demonstrate the accurate visualization of filaments and bundles with purified γPFD. Next, by implementing immunofluorescence labeling after creating a 3xFLAG-tagged γPFD strain, we successfully visualize γPFD in M. jannaschii cells. Through 3D-STORM and two-color STORM imaging with DNA, we show the widespread distribution of filamentous γPFD structures within the cell. These findings provide valuable insights into the structure and localization of γPFD, opening up possibilities for studying intriguing nanoscale components not only in archaea but also in other microorganisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Antecedent Hydrologic Conditions Reflected in Stream Lithium Isotope Ratios During Storms

Antecedent hydrological conditions are recorded through the evolution of dissolved lithium isotope signatures (δ 7 Li) by juxtaposing two storm events in an upland watershed subject to a Mediterranean climate. Discharge and δ 7 Li are negatively correlated in both events,but mean δ 7 Li ratios and associated ranges of variation are distinct between them. We apply a previously developed reactive transport model (RTM) for the site to these event-scale flow perturbations, but observed shifts in stream δ 7 Li are not reproduced. To reconcile the stability of the subsurface solute weathering profile with our observations of dynamic stream δ 7 Li signatures, we couple the RTM to a distribution of fluid transit times that evolve based on storm hydrographs. The approach guides appropriate flux-weighting of fluid from the RTM over a range of flow path lengths, or equivalently fluid residence times. This flux-weighted RTM approach accurately reproduces dynamic storm δ 7 Li-discharge patterns distinguished by the antecedent conditions of the watershed.

58 GEOSCIENCES↗