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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

A Multi-sensor Evaluation of Precipitation Uncertainty for Landslide-triggering Storm Events

Extreme precipitation can have profound consequences for communities, resulting in natural hazards such as rainfall-triggered landslides that cause casualties and extensive property damage. A key challenge to understanding and predicting rainfall triggered landslides comes from observational uncertainties in the depth and intensity of precipitation preceding the event. Practitioners and researchers must select among a wide range of precipitation products, often with little guidance. Here we evaluate the degree of precipitation uncertainty across multiple precipitation products for a large set of landslide triggering storm events and investigate the impact of these uncertainties on predicted landslide probability using published intensity-duration thresholds. The average intensity, peak intensity, duration, and NOAA-Atlas return periods are compared ahead of reported landslides across the continental US and Canada. Precipitation data are taken from four products that cover disparate measurement methods: near real-time and post-processed satellite (IMERG), radar (MRMS), and gauge-based (NLDAS-2). Landslide-triggering precipitation was found to vary widely across precipitation products with the depth of individual storm events diverging by as much as 296mm with an average range of 51mm. Peak intensity measurements, which are typically influential in triggering landslides, were also highly variable with an average range of 7.8262745mm/hr and as much as 57mm/hr. The two products more reliant upon ground-based observations (MRMS and NLDAS-2) performed better at identifying landslides according to published intensity duration storm thresholds, but all products exhibited hit-ratios of greater than 0.56. A greater proportion of landslides were predicted when including only manually-verified landslide locations. We recommend practitioners consider low-latency products like MRMS for investigating landslides, given their near-real time data availability and good performance in detecting landslides. Practitioners would be well-served considering more than one product as a way to confirm intense storm signals and minimize the influence of noise and false alarms.

Precipitation inter-comparison↗
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 ↗
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↗
NASA NTRS1966

An analysis of eight flights by U-2 aircraft over severe storms in Oklahoma

The method and results of the analysis of photographic records of the summit areas of severe storms obtained from a U-2 aircraft flying at an altitude of 65,000 ft. over Oklahoma are described. Comparison of the heights of storm cells protruding through the main anvil cirrus deck of a squall line with the predictions of simple "parcel" theory suggests the latter may be used to indicate the maximum development attainable (but not necessarily attained) by a squall line on a given day. It is suggested that temperatures approaching -1OO°C. may occur in the domes of giant quasi-steady storm cells reaching altitudes of 55,000 - 60,000 ft. bounded by a thin shell of extremely stable air, which is not inconsistent with the rather smooth texture of dome summits sometimes shown by the U-2 photographs.

CLOUD PHOTOGRAPHY↗
NASA NTRS1971

The developing stages of the Martian yellow storm of 1971

A history of the yellow storm on Mars which occurred in 1971 is presented. It is compared to the Great 1956 Yellow Cloud, and possible yellow storms are predicted for 1973. Photographs of the stages of evolution and the path of the storm are included.

Capen, C. F.↗
NASA NTRS1971

Geomagnetic storm fields near a synchronous satellite.

An apparent early recovery of the main phase of geomagnetic storms at the distance of the synchronous satellite is examined in terms of changing electric current distributions in the magnetosphere during magnetic storms. It is suggested that a rapid recession of the edge of the plasma sheet (after the advance toward the earth during an early epoch of the main phase) is partly responsible for the early recovery. Relevant plasma sheet variations during geomagnetic storms are found to be in agreement with the inferred variations.

Kawasaki, K.↗
NASA NTRS1972

Mars' great storm of 1971.

Description of the development of this planet-wide storm and its subsequent decline through mid-January 1972. The initial core of the disturbance extended northeast to southwest. Preliminary examination of photographic data indicates that the storm, yellow in color, spread completely around the planet in about 16 days. During the storm, red- and green-light photographs recorded Mars as brighter than normal, while in blue it was only slightly brighter, and in the ultraviolet there was no significant change. The history of yellow clouds is discussed. They seem to germinate in specific areas in the southern hemisphere, such as the Hellas-Noachis region. Another yellow cloud is predicted for July or August of 1973.

Capen, C. F.↗