Search NASA⌕ Search

SEARCH · Search NASA

Results for “HURRICANE”

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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Hurricane Ike Deposits on the Bolivar Peninsula, Galveston Bay, Texas

In September 2008, Hurricane Ike made landfall on Galveston Bay, close to the NASA Johnson Space Center (JSC). The storm flooded much of the area with a storm surge ranging from 11 -20 feet. The Bolivar peninsula, the southeastern coast of Galveston Bay, experienced the brunt of the surge. Several agencies collected excellent imagery baselines before the storm and complementary data a few days afterward that helped define the impacts of the storm. In April of 2011, a team of scientists and astronauts from JSC conducted field mapping exercises along the Bolivar Peninsula, the section of the Galveston Bay coast most impacted by the storm. Astronauts routinely observe and document coastal changes from orbit aboard the International Space Station. As part of their basic Earth Science training, scientists at the Johnson Space Center take astronauts out for field mapping exercises so that they can better recognize and understand features and processes that they will later observe from the International Space Station. Using pre -storm baseline images of the Bolivar Peninsula near Rollover Pass and Gilchrist (NOAA/Google Earth Imagery and USGS aerial imagery and lidar data), the astronauts mapped current coastline positions at defined locations, and related their findings to specific coastal characteristics, including channel, jetties, and other developments. In addition to mapping, we dug trenches along both the Gulf of Mexico coast as well as the Galveston Bay coast of the Bolivar peninsula to determine the depth of the scouring from the storm on the Gulf side, and the amount of deposition of the storm surge deposits on the Bay side of the peninsula. The storm signature was easy to identify by sharp sediment transitions and, in the case of storm deposits, a layer of storm debris (roof shingles, PVC pipes, etc) and black, organic rich layers containing buried sea grasses in areas that were marshes before the storm. The amount of deposition was generally about 20 -25 cm; the local areas experiencing obvious deposition are readily obvious in post -Ike imagery of the region. We used a March 2010 aerial photograph from the NOAA -Google Earth collection because construction and vegetation recovery was minimal. Based on the before and after aerial imagery and the trenching data collected over two days, we can begin to characterize the material transported and deposited by Hurricane Ike along one stretch of the Bolivar peninsula. We summarize the results from our mapping and trenching data. The basic data collected 2.5 years after the storm are ephemeral as the storm deposits become reworked and overprinted by coastal processes, vegetation regrowth and reconstruction.

Evans, Cynthia A.↗
NASA NTRS2014

Hurricane Karl's Structure and Some Thoughts for 2014 Strategy

Karl has interesting data, but far below the standards we should be able to achieve in HS3. We need to fly AV-1 over hurricanes in 2014. Most of the cold cloud shield in the inner core of hurricanes should be safe for AV-1 to fly. Significant convection occupies a small region, but we sometimes unnecessarily apply the 5000-ft separation rule to the entire cold cloud shield.

Cecil, Dan↗
NASA NTRS2014

Hurricane Sandy and Adaptation Pathways in New York: Lessons from a First-Responder City

Two central issues of climate change have become increasingly evident: Climate change will significantly affect cities; and rapid global urbanization will increase dramatically the number of individuals, amount of critical infrastructure, and means of economic production that are exposed and vulnerable to dynamic climate risks. Simultaneously, cities in many settings have begun to emerge as early adopters of climate change action strategies including greenhouse gas mitigation and adaptation. The objective of this paper is to examine and analyze how officials of one city - the City of New York - have integrated a flexible adaptation pathways approach into the municipality's climate action strategy. This approach has been connected with the City's ongoing response to Hurricane Sandy, which struck in the October 2012 and resulted in damages worth more than US$19 billion. A case study narrative methodology utilizing the Wise et al. conceptual framework (see this volume) is used to evaluate the effectiveness of the flexible adaptation pathways approach in New York City. The paper finds that Hurricane Sandy serves as a ''tipping point'' leading to transformative adaptation due to the explicit inclusion of increasing climate change risks in the rebuilding effort. The potential for transferability of the approach to cities varying in size and development stage is discussed, with elements useful across cities including the overall concept of flexible adaptation pathways, the inclusion of the full metropolitan region in the planning process, and the co-generation of climate-risk information by stakeholders and scientists.

adaptation pathways↗
NASA NTRS2017

Collaborative, Rapid Mapping of Water Extents During Hurricane Harvey Using Optical and Radar Satellite Sensors

On August 25, 2017, Hurricane Harvey made landfall between Port Aransas and Port O'Connor, Texas, bringing with it unprecedented amounts of rainfall and record flooding. In times of natural disasters of this nature, emergency responders require timely and accurate information about the hazard in order to assess and plan for disaster response. Due to the extreme flooding impacts associated with Hurricane Harvey, delineations of water extent were crucial to inform resource deployment. Through the USGS's Hazards Data Distribution System, government and commercial vendors were able to acquire and distribute various satellite imagery to analysts to create value-added products that can be used by these emergency responders. Rapid-response water extent maps were created through a collaborative multi-organization and multi-sensor approach. One team of researchers created Synthetic Aperture Radar (SAR) water extent maps using modified Copernicus Sentinel data (2017), processed by ESA. This group used backscatter images, pre-processed by the Alaska Satellite Facility's Hybrid Pluggable Processing Pipeline (HyP3), to identify and apply a threshold to identify water in the image. Quality control was conducted by manually examining the image and correcting for potential errors. Another group of researchers and graduate student volunteers derived water masks from high resolution DigitalGlobe and SPOT images. Through a system of standardized image processing, quality control measures, and communication channels the team provided timely and fairly accurate water extent maps to support a larger NASA Disasters Program response. The optical imagery was processed through a combination of various band thresholds and by using Normalized Difference Water Index (NDWI), Modified Normalized Water Index (MNDWI), Normalized Difference Vegetation Index (NDVI), and cloud masking. Several aspects of the pre-processing and image access were run on internal servers to expedite the provision of images to analysts who could focus on manipulating thresholds and quality control checks for maximum accuracy within the time constraints. The combined results of the radar- and optical-derived value-added products through the coordination of multiple organizations provided timely information for emergency response and recovery efforts.

SERVIR↗
NASA NTRS2019

Assessing Dual-Polarization Radar Estimates of Extreme Rainfall During Hurricane Harvey

Hurricane Harvey hit the Texas Gulf Coast as a major hurricane on August 25, 2017 before exiting the state as a tropical storm on August 29, 2017. Left in its wake was historic flooding, with some locations measuring more than 60 inches of rain over a five-day period. The WSR-88D radar (KHGX) maintained operations for the entirety of the event. Rain gauge data from the Harris County Flood Warning System (HCFWS) was used for validation with the full radar data set to retrieve daily and event-total precipitation estimates for the period August 25-29, 2017. The KHGX precipitation estimates were then compared to the HCFWS gauges. Three different hybrid polarimetric rainfall retrievals were used, along with attenuation-based retrieval that employs the radar-observed differential propagation. An advantage of using a attenuation-based retrieval is its immunity to partial beam blockage and calibration errors in reflectivity and differential reflectivity. All of the retrievals are susceptible to changes in the observed Drop Size Distribution (DSD). No in situ DSD data were available over the study area, so changes in the DSD were interpreted by examining the observed radar data. We examined the parameter space of two key values in the attenuation retrieval to test the sensitivity of the rain retrieval. Selecting a value of α=0.015 and β=0.600 and β=0.625 provided the best overall results, relative to the gauges, but more work needs to be done to develop an automated technique to account for changes in the ambient DSD.

David B Wolff↗
NASA NTRS2019

Assessing Dual-Polarization Radar Estimates of Extreme Rainfall During Hurricane Harvey

Hurricane Harvey hit the Texas Gulf Coast as a major hurricane on 25 August 2017 before exiting the state as a tropical storm on 29 August 2017. Left in its wake was historic flooding, with some locations measuring more than 60 in. (150 cm) of rain over a 5-day period. The WSR-88D radar (KHGX) maintained operations for the entirety of the event. Rain gauge data from the Harris County Flood Warning System (HCFWS) was used for validation with the full radar dataset to retrieve daily and event-total precipitation estimates for the period 25–29 August2017. The KHGX precipitation estimates were then compared with the HCFWS gauges. Three different hybrid polarimetric rainfall retrievals were used, along with attenuation-based retrieval that employs the radar-observed differential propagation. An advantage of using a attenuation-based retrieval is its immunity to partial beam blockage and calibration errors in reflectivity and differential reflectivity. All of the retrievals are susceptible to changes in the observed drop size distribution (DSD). No in situ DSD data were available over the study area, so changes in the DSD were interpreted by examining the observed radar data. We examined the parameter space of two key values in the attenuation retrieval to test the sensitivity of the rain retrieval. Selecting a value ofa50.015 andb50.600 provided the best overall results, relative to the gauges, but more work needs to be done to develop an automated technique to account for changes in the ambient DSD.

David Billings Wolff↗
NASA NTRS2020

Drop Size Distribution Measurements in Outer Rainbands of Hurricane Dorian at the NASA Wallops Precipitation-Research Facility

Hurricane rainbands are very efficient rain producers, but details on drop size distributions are still lacking. This study focuses on the rainbands of hurricane Dorian as they traversed the densely instrumented NASA precipitation-research facility at Wallops Island, VA, over a period of 8 h. Drop size distribution (DSD) was measured using a high-resolution meteorological particle spectrometer (MPS) and 2D video disdrometer, both located inside a double-fence wind shield. The shape of the DSD was examined using double-moment normalization, and compared with similar shapes from semiarid and subtropical sites. Dorian rainbands had a superexponential shape at small normalized diameter values similar to those of the other sites. NASA’s S-band polarimetric radar performed range height-indicator (RHI) scans over the disdrometer site, showing some remarkable signatures in the melting layer (bright-band reflectivity peaks of 55 dBZ, a dip in the copolar correlation to 0.85 indicative of 12–15 mm wet snow, and a staggering reflectivity gradient above the 0 °C level of −10 dB/km, indicative of heavy aggregation). In the rain layer at heights < 2.5 km, polarimetric signatures indicated drop break-up as the dominant process, but drops as large as 5 mm were detected during the intense bright-band period.

Merhala Thurai↗
NASA NTRSDate not supplied

Evolution of Drop Size Distributions during Hurricane Harvey and Their Effects on Rain Intensity

Hurricane Harvey hit the Texas Gulf Coast as a major hurricane on August 25, 2017, before exiting the state as a tropical storm on August 29, 2017. Left in its wake was historic flooding over southeast Texas with some locations measuring more than 60 inches of rain. The Houston NEXRAD radar (KHGX) maintained operations for the entirety of the event and is utilized in this study to better understand the evolution of the drop size distribution (DSD) in the lower (liquid) portions of the storm and how changes in the DSD were tied to observed and measured changes in rain intensities. From the KHGX dual-polarimetric radar data several DSD parameters were retrieved, including three different rain rate retrievals, as well as the mass-weighted mean-drop diameter Dm, and the normalized intercept parameter NW of the gamma distribution. Two of the rain retrievals are popular hybrid approaches, where reflectivity, differential and specific differential phase are used. The other is an attenuation-based retrieval. In a previous study, it was found that both hybrid retrievals significantly underestimated the rainfall during the heaviest rain periods, while the attenuation-based retrieval, with proper adjustment, agreed quite well with a large network of gauges from the Harris County Flood Warning System. Using Dm and NW as proxies for drop size and concentration, respectively, we will show that the heaviest rain intensities were associated in areas of the storm where there was a large concentration of large drops present. It is envisaged that results of this study can be used to develop a near-real-time tuning of the attenuation-based retrieval, thus providing timely, and possibly life-saving warnings during inundating rainfall.

David B. Wolff↗
NASA NTRS2021

Tracking the Rates and Mechanisms of Canopy Damage and Recovery Following Hurricane Maria Using Multitemporal Lidar Data

Hurricane Maria, a Category 4 storm, snapped and uprooted canopy trees, removed large branches, and defoliated vegetation across Puerto Rico. The magnitude of forest damages and the rates and mechanisms of forest recovery following Maria provide important benchmarks for understanding the ecology of extreme events. We used airborne Lidar data acquired before (2017) and after Maria (2018, 2020) to quantify landscape-scale changes in forest structure along a 439-ha elevational gradient (100–800 m) in the Luquillo Experimental Forest. Damages from Maria were widespread, with 73% of the study area losing ≥ 1 m in canopy height (mean = −7.1 m). Taller forests at lower elevations suffered more damage than shorter forests above 600 m. Yet only 13.5% of the study area had canopy heights ≤ 2 m in 2018, a typical threshold for forest gaps, highlighting the importance of damaged trees and advanced regeneration on post-storm forest structure. Heterogeneous patterns of regrowth and recruitment yielded shorter and more open forests by 2020. Nearly 45% of forests experienced initial height loss > 1 m (2017–2018) followed by rapid height gain > 1 m (2018–2020), whereas 21.6% of forests with initial height losses showed little or no height gain, and 17.8% of forests exhibited no height changes larger than ± 1 m in either period. Canopy layers < 10 m tall accounted for most increases in canopy height and fractional cover between 2018 and 2020, with gains split evenly between height growth and lateral crown expansion by surviving individuals. These findings benchmark rates of gap formation, crown expansion, and canopy closure following hurricane damage and highlight the diversity of ecosystem impacts from heterogeneous spatial patterns and vertical stratification of forest regrowth following a major disturbance event.

forest structure↗
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 NTRS2021

Tracking the Rates and Mechanisms of Canopy Damage and Recovery Following Hurricane Maria Using Multitemporal Lidar Data

Hurricane Maria, a Category 4 storm, snapped and uprooted canopy trees, removed large branches, and defoliated vegetation across Puerto Rico. The magnitude of forest damages and the rates and mechanisms of forest recovery following Maria provide important benchmarks for understanding the ecology of extreme events. We used airborne Lidar data acquired before (2017) and after Maria (2018, 2020) to quantify landscape-scale changes in forest structure along a 439-ha elevational gradient (100–800 m) in the Luquillo Experimental Forest. Damages from Maria were widespread, with 73% of the study area losing ≥ 1 m in canopy height (mean = −7.1 m). Taller forests at lower elevations suffered more damage than shorter forests above 600 m. Yet only 13.5% of the study area had canopy heights ≤ 2 m in 2018, a typical threshold for forest gaps, highlighting the importance of damaged trees and advanced regeneration on post-storm forest structure. Heterogeneous patterns of regrowth and recruitment yielded shorter and more open forests by 2020. Nearly 45% of forests experienced initial height loss > 1 m (2017–2018) followed by rapid height gain > 1 m (2018–2020), whereas 21.6% of forests with initial height losses showed little or no height gain, and 17.8% of forests exhibited no height changes larger than ± 1 m in either period. Canopy layers < 10 m tall accounted for most increases in canopy height and fractional cover between 2018 and 2020, with gains split evenly between height growth and lateral crown expansion by surviving individuals. These findings benchmark rates of gap formation, crown expansion, and canopy closure following hurricane damage and highlight the diversity of ecosystem impacts from heterogeneous spatial patterns and vertical stratification of forest regrowth following a major disturbance event.

forest structure↗
NASA NTRSDate not supplied

The Impact of All-Sky Hyperspectral Infrared Radiance Assimilation on the Simulation and Forecast of Hurricane Sally in GEOS

Hyperspectral infrared (IR) radiance observations have been one of the major data sources assimilated in the data assimilation system over the last 20 years. However, observations peaking in the lower and mid-troposphere are underutilized in clear-sky radiance data assimilation as the quality control procedure removes a significant portion of cloud-affected observations from the assimilation. To include these cloud-affected observations, one approach is to assimilate them directly under all-sky conditions. The framework for all-sky assimilation of hyperspectral IR radiance observations has been developed in GEOS. The preliminary evaluation of simulated cloud-affected IR observations has been conducted, along with the corresponding sensitivities with respect to all hydrometeors. The symmetric cloud effect has been used as a cloud proxy in the observation error modeling, providing a balanced representation that mitigates the discrepancies between observations and model simulations for IR all-sky assimilation. The observation errors vary for different cloud conditions and have been modeled as cloud amount dependent and inter-channel correlated. Preliminary evaluation of model simulations for IR all-sky assimilation indicates that the simulated brightness temperature tends to have broader structures and lacks small-scale details. Excessive clouds generated by the model are also observed. To address this issue, Hurricane Sally (2020), which formed near the Bahamas, is used as a case study. Several cloud overlap schemes and cloud lookup tables (LUTs), along with other important aspects of all-sky IR radiance assimilation, will be evaluated and tested, aiming to improve the impact on Hurricane Sally's simulation and forecast.

Wei Gu↗