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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 109 records · Page 6
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NASA NTRS2010

An Estimate of the North Atlantic Basin Tropical Cyclone Activity for the 2010 Hurricane Season

Estimates are presented for the tropical cyclone activity expected for the 2010 North Atlantic basin hurricane season. It is anticipated that the 2010 season will be more active than the 2009 season, reflecting increased frequencies more akin to that of the current more active phase that has been in vogue since 1995. Averages (+/- 1 sd) during the current more active phase are 14.5+/-4.7, 7.8+/-3.2, 3.7+/-1.8, and 2+/- 2, respectively, for the number of tropical cyclones (NTC), the number of hurricanes (NH), the number of major hurricanes (NMH), and the number of United States (U.S.) land-falling hurricanes (NUSLFH). Based on the "usual" behavior of the 10-yma parametric first differences, one expects NTC = 19+/-2, NH = 14+/-2, NMH = 7+/-2, and NUSLFH = 4+/-2 for the 2010 hurricane season; however, based on the "best guess" 10-yma values of surface-air temperature at the Armagh Observatory (Northern Ireland) and the Oceanic Nino Index, one expects NTC > or equals 16, NH > or equals 14, NMH > or equals 7, and NUSLFH > or equals 6.

Wilson, Robert M.↗
NASA NTRS2010

Development, Capabilities, and Impact on Wind Analyses of the Hurricane Imaging Radiometer (HIRAD)

The Hurricane Imaging Radiometer (HIRAD) is a new airborne microwave remote sensor for hurricane observations that is currently under development by NASA Marshall Space Flight Center in partnership with the NOAA Atlantic Oceanographic and Meteorological Laboratory/Hurricane Research Division, the University of Central Florida, the University of Michigan, and the University of Alabama in Huntsville. The instrument is being test flown in January and is expected to participate in the tropical cyclone experiment GRIP (Genesis and Rapid Intensification Processes) in the 2010 season. HIRAD is being designed to study the wind field in some detail within strong hurricanes and to enhance the real-time airborne ocean surface winds observation capabilities of NOAA and USAF Weather Squadron hurricane hunter aircraft currently using the operational Stepped Frequency Microwave Radiometer (SFMR). Unlike SFMR, which measures wind speed and rain rate along the ground track at a single point directly beneath the aircraft, HIRAD will provide images of the surface wind and rain field over a wide swath (approximately 3 x the aircraft altitude) with approximately 2 km resolution. This paper describes the HIRAD instrument and the physical basis for its operations, including chamber test data from the instrument. The potential value of future HIRAD observations will be illustrated with a summary of Observing System Simulation Experiments (OSSEs) in which measurements from the new instrument as well as those from existing instruments (air, surface, and space-based) are simulated from the output of a detailed numerical model, and those results are used to construct simulated H*Wind analyses. Evaluations will be presented on the impact on H*Wind analyses of using the HIRAD instrument observations to replace those of the SFMR instrument, and also on the impact of a future satellite-based HIRAD in comparison to instruments with more limited capabilities for observing strong winds through heavy rain. Potential impact on numerical prediction of hurricane intensity will also be discussed.

Miller, T.↗
NASA NTRS2013

Thermal Modeling and Analysis of the Hurricane Imaging Radiometer (HIRad)

The Hurricane Imaging Radiometer (HIRad) is a payload carried by an unmanned aerial vehicle (UAV) at altitudes up to 60,000 ft with the purpose of measuring ocean surface wind speeds and near ocean surface rain rates in hurricanes. The payload includes several components that must maintain steady temperatures throughout the flight. Minimizing the temperature drift of these components allows for accurate data collection and conclusions to be drawn concerning the behavior of hurricanes. HIRad has flown on several different UAVs over the past two years during the fall hurricane season. Based on the data from the 2011 flight, a Thermal Desktop model was created to simulate the payload and reproduce the temperatures. Using this model, recommendations were made to reduce the temperature drift through the use of heaters controlled by resistance temperature detector (RTD) sensors. The suggestions made were implemented for the 2012 hurricane season and further data was collected. The implementation of the heaters reduced the temperature drift for a portion of the flight, but after a period of time, the temperatures rose. With this new flight data, the thermal model was updated and correlated. Detailed analysis was conducted to determine a more effective way to reduce the temperature drift. The final recommendations made were to adjust the set temperatures of the heaters for 2013 flights and implement hardware changes for flights beyond 2013.

Mauro, Stephanie↗
NASA NTRS2013

Modeling and Analysis of the Hurricane Imaging Radiometer (HIRAD)

The Hurricane Imaging Radiometer (HIRad) is a payload carried by an unmanned aerial vehicle (UAV) at altitudes up to 60,000 ft with the purpose of measuring ocean surface wind speeds and near ocean surface rain rates in hurricanes. The payload includes several components that must maintain steady temperatures throughout the flight. Minimizing the temperature drift of these components allows for accurate data collection and conclusions to be drawn concerning the behavior of hurricanes. HIRad has flown on several different UAVs over the past two years during the fall hurricane season. Based on the data from the 2011 flight, a Thermal Desktop model was created to simulate the payload and reproduce the temperatures. Using this model, recommendations were made to reduce the temperature drift through the use of heaters controlled by resistance temperature detector (RTD) sensors. The suggestions made were implemented for the 2012 hurricane season and further data was collected. The implementation of the heaters reduced the temperature drift for a portion of the flight, but after a period of time, the temperatures rose. With this new flight data, the thermal model was updated and correlated. Detailed analysis was conducted to determine a more effective way to reduce the temperature drift. The final recommendations made were to adjust the set temperatures of the heaters for 2013 flights and implement hardware changes for flights beyond 2013.

Mauro, Stephanie↗
DOE OSTI2022

Proactive Posturing of Large Power Grid for Mitigating Hurricane Impacts

In the past decade, natural disasters such as hurricanes have challenged the operation and control of U.S. power grid more. It is crucial to develop proactive strategies to assist grid operators for better emergency response and minimized electricity service interruptions. In this paper, we propose a proactive posturing methodology of power system elements, and formulated a Security-Constrained Optimal Power Flow (SCOPF) that informed by cross-domain hurricane modeling and its potential impacts on the grid elements. Simulation results based on real-world power grid and historical hurricane event validated the applicability of the proposed optimization formulation, and show potential to enable grid operators and planners with interactive cross-domain data analytics in mitigating hurricane impacts.

power system emergency response, security constrai↗
DOE OSTI2022

Understory plant communities show resistance to drought, hurricanes, and experimental warming in a wet tropical forest

Global climate change has led to rising temperatures and to more frequent and intense climatic events, such as storms and droughts. Changes in climate and disturbance regimes can have non-additive effects on plant communities and result in complicated legacies we have yet to understand. This is especially true for tropical forests, which play a significant role in regulating global climate. We used understory vegetation data from the Tropical Responses to Altered Climate Experiment (TRACE) in Puerto Rico to evaluate how plant communities responded to climate warming and disturbance. The TRACE understory vegetation was exposed to a severe drought (2015), 2 years of experimental warming (4°C above ambient in half of the plots, 2016–2017 and 2018–2019), and two major hurricanes (Irma and María, September 2017). Woody seedlings and saplings were censused yearly from 2015 to 2019, with an additional census in 2015 after the drought ended. We evaluated disturbance-driven changes in species richness, diversity, and composition across ontogeny. We then used Bayesian predictive trait modeling to assess how species responded to disturbance and how this might influence the functional structure of the plant community. Our results show decreased seedling richness after hurricane disturbance, as well as increased sapling richness and diversity after warming. We found a shift in species composition through time for both seedlings and saplings, yet the individual effects of each disturbance were not significant. At both ontogenetic stages, we observed about twice as many species responding to experimental warming as those responding to drought and hurricanes. Predicted changes in functional structure point to disturbance-driven functional shifts toward a mixture of fast-growing and drought-tolerant species. Our findings demonstrate that the tropical forest understory community is more resistant to climatic stressors than expected, especially at the sapling stage. However, early signs of changes in species composition suggest that, in a warming climate with frequent droughts and hurricanes, plant communities might shift over time toward fast-growing or drought-tolerant species.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Impacts of Hurricane Disturbance on Water Quality across the Aquatic Continuum of a Blackwater River to Estuary Complex

Hurricanes cause landscape-scale disturbances that affect biogeochemical cycling and water quality in coastal ecosystems. During Hurricane Irma’s passage through northern Florida, water movements driven by wind velocities up to 105 km h-1 caused a salinity peak in an estuary/blackwater river complex. Water quality was monitored across the 15 km site to detect the magnitude and duration of disturbance. Saline water intruded 15 km inland into a freshwater portion of the river that peaked at a salinity of 2 psu. Due to the volume of precipitation from the hurricane, significant runoff of freshwater and dissolved organic matter (DOM) caused a decrease in salinity, dissolved oxygen (DO), and Chlorophyll-a concentrations while increasing turbidity and fluorescent dissolved organic matter (fDOM). The disturbance caused rapid changes observed by in-situ water quality monitors over a 3-week period, but some effects persisted for longer periods as shown by 3-month weekly water sampling. This disturbance caused shifts in DOM loading, altered salinity dynamics, and reshaped landscapes due to wind and wave surge both in upland marsh and downstream estuary. Hurricane disturbance temporarily and abruptly alters the aquatic continuum, and observations of system response can help us understand the mechanisms associated with ecosystem resilience and recovery.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

NEXRAD-In-Space: A Geostationary Orbiting Doppler Radar for Hurricane Monitoring and Studies

Under NASA's Earth Science Technology Program, a novel mission concept has been developed for detailed monitoring of hurricanes, cyclones, and severe storms from a geostationary orbit: "NEXRAD in Space" (NIS). By operating in the Geostationary Earth Orbit (GEO), NIS would enable rapid-update sampling (less than or equal to 1 hour cadence) of three dimenional fields of 35 GHz (Ka-band) radar reflectivity factor (Z) and line-of-sight Doppler velocity (VD) profiles, at mesoscale horizontal resolutions (approx. 10 km) over a circular Earth region of approximately 5300 km in diameter (equivalent to much of an oceanic basin, such as the Atlantic). NIS GEO-radar concept was chosen as one of only four potential post-2020 missions for the Weather Focus area in the 2007-2016 NASA Science Mission Directorate (SMD) Science Plan. The results of the first project aiming at developing the NIS concept highlighted the enormous potential of such mission, and the technological challenges presented by it. In essence, it is because of its rapid-cadence capability that NIS science planning is focusing on hurricane monitoring and prediction. Hurricanes, or generically tropical cyclones (TCs), have always been among the most devastating natural phenomena. This has been painfully reiterated in recent years with a number of powerful TCs landfalling in North America and elsewhere. In April 2007, the first NIS Science Workshop was convened at the University of Miami to galvanize the scientific community's interest in NIS's measurement capabilities for improved TC monitoring and prediction. The general consensus of the workshop was that a GEO Doppler radar would provide a major breakthrough in regards to the observation of TCs, and, when combined with cloud-resolving numerical weather prediction (NWP) models. This paper presents brief summaries of the instrument concept, the current technology status, the anticipated impacts on hurricane monitoring and model prediction, and the future science and technology roadmap.

precipitation↗
NASA NTRS2015

Validation of Rain Rate Retrievals for the Airborne Hurricane Imaging Radiometer (HIRAD)

The NASA Hurricane and Severe Storm Sentinel (HS3) mission is an aircraft field measurements program using NASA's unmanned Global Hawk aircraft system for remote sensing and in situ observations of Atlantic and Caribbean Sea hurricanes. One of the principal microwave instruments is the Hurricane Imaging Radiometer (HIRAD), which measures surface wind speeds and rain rates. For validation of the HIRAD wind speed measurement in hurricanes, there exists a comprehensive set of comparisons with the Stepped Frequency Microwave Radiometer (SFMR) with in situ GPS dropwindsondes [1]. However, for rain rate measurements, there are only indirect correlations with rain imagery from other HS3 remote sensors (e.g., the dual-frequency Ka- & Ku-band doppler radar, HIWRAP), which is only qualitative in nature. However, this paper presents results from an unplanned rain rate measurement validation opportunity that occurred in 2013, when HIRAD flew over an intense tropical squall line that was simultaneously observed by the Tampa NEXRAD meteorological radar (Fig. 1). During this experiment, Global Hawk flying at an altitude of 18 km made 3 passes over the rapidly propagating thunderstorm, while the TAMPA NEXRAD perform volume scans on a 5-minute interval. Using the well-documented NEXRAD Z-R relationship, 2D images of rain rate (mm/hr) were obtained at two altitudes (3 km & 6 km), which serve as surface truth for the HIRAD rain rate retrievals. A preliminary comparison of HIRAD rain rate retrievals (image) for the first pass and the corresponding closest NEXRAD rain image is presented in Fig. 2 & 3. This paper describes the HIRAD instrument, which 1D synthetic-aperture thinned array radiometer (STAR) developed by NASA Marshall Space Flight Center [2]. The rain rate retrieval algorithm, developed by Amarin et al. [3], is based on the maximum likelihood estimation (MLE) technique, which compares the observed Tb's at the HIRAD operating frequencies of 4, 5, 6 and 6.6 GHz with corresponding theoretical Tb values from a forward radiative transfer model (RTM). The optimum solution is the integrated rain rate that minimizes the difference between RTM and observed values. Because the excess Tb from rain comes from the direct upwelling and the indirect reflected downwelling paths through the atmosphere, there are several assumptions made for the 2D rain distribution in the antenna incident plane (crosstrack to flight direction). The opportunity to knowing 2D rain surface truth from NEXRAD at two different altitudes will enable a comprehensive evaluation to be preformed and reported in this paper.

hurricane↗
NASA NTRS2018

Hurricane Imaging Radiometer (HIRAD) Wind Speed Retrievals and Assessment Using Dropsondes

The Hurricane Imaging Radiometer (HIRAD) is an experimental C-band passive microwave radiometer designed to map the horizontal structure of surface wind speed fields in hurricanes. New data processing and customized retrieval approaches were developed after the 2015 Tropical Cyclone Intensity (TCI) experiment, which featured flights over Hurricanes Patricia, Joaquin, Marty, and the remnants of Tropical Storm Erika. These new approaches produced maps of surface wind speed that looked more realistic than those from previous campaigns. Dropsondes from the High Definition Sounding System (HDSS) that was flown with HIRAD on a WB-57 high altitude aircraft in TCI were used to assess the quality of the HIRAD wind speed retrievals. The root mean square difference between HIRAD-retrieved surface wind speeds and dropsonde-estimated surface wind speeds was 6.0 meters per second. The largest differences between HIRAD and dropsonde winds were from data points where storm motion during dropsonde descent compromised the validity of the comparisons. Accounting for this and for uncertainty in the dropsonde measurements themselves, we estimate the root mean square error for the HIRAD retrievals as around 4.7 meters per second. Prior to the 2015 TCI experiment, HIRAD had previously flown on the WB-57 for missions across Hurricanes Gonzalo (2014), Earl (2010), and Karl (2010). Configuration of the instrument was not identical to the 2015 flights, but the methods devised after the 2015 flights may be applied to that previous data in an attempt to improve retrievals from those cases.

wind retrieval↗
DOE OSTI2020

Data Requirements for Application of Risk-Based Dynamic Contingency Analysis to Evaluate Hurricane Impact to Electrical Infrastructure in Puerto Rico

This paper presents a risk-based dynamic contingency analysis framework that was used to evaluate the hurricane impact to electrical infrastructure in Puerto Rico. PNNL developed a scalable risk-based framework for identifying high-voltage transmission resilience improvements by classifying and prioritizing high-risk power grid contingencies (system failures) under hurricane impact. The risk-based framework is founded on grid outage definitions with their associated probabilities of occurrence from hurricane events, in combination with an impact assessment derived from detailed dynamic cascading failure analysis. This paper focuses on a discussion around data requirements for transmission resilience planning for hurricane events, derived from the development of the risk-based framework and its application to Puerto Rico. This paper launches an important first step in encouraging the engineering community and power system industry to move towards establishing resilience planning as a routine practice. Since actual results for Puerto Rico contain sensitive information, sample simulation results will be used to illustrate the data requirements and risk-based dynamic cascading framework on the Puerto Rico power grid, as well as demonstrate the potential for such a simulation framework. The paper includes a discussion on the lessons learned, importance and need for improved datasets that are not usually considered in traditional power system planning. The paper will also elaborate on how the scalable simulation framework and datasets might be expanded to larger footprints and leveraged for modelling other types of natural disasters.

DCAT, Puerto Rico, hurricane, Power System Stabili↗
DOE OSTI2025

Turbulence-Resolving Simulations of Hurricane Laura (2020): Insights Into Extreme Winds and Eyewall Turbulence

Extreme weather events pose significant risks to coastal and offshore energy infrastructure. In this work, we investigate the structure of mean winds and turbulence near the surface ( z < 300 m) that occurred during Hurricane Laura in 2020 on the US Gulf Coast. To this end, we perform turbulence-resolving simulations (..delta..x = 33.33 m) that encompass the entire eyewall of Hurricane Laura by introducing a novel method that we will refer to as Moving-Mesoscale to Static-LES Integrated Coupling (MOSAIC). The simulation results are validated against surface, boundary-layer, and mid-tropospheric observations. Our analysis of the extreme wind conditions near the surface indicates that the mean wind and turbulence profiles vary greatly at and near the eyewall, resulting in extreme values of mean wind speed (U > 50 m * s-1) and turbulence kinetic energy (k ~ 50 m2 * s-2) at altitudes above 50 m . To investigate in detail the nature of turbulence within the eyewall of the storm, we conduct higher-resolution simulations (..delta..x = 11.11 m) of a portion of the hurricane. We provide a comprehensive statistical description of turbulence in the eyewall region, highlighting the need to employ ..delta..x ~ 10 m grid spacing to capture the integral length-scales near the surface, second- and higher-order central moments (i.e., skewness and kurtosis), and spectral coherence in the flow accurately. These numerical simulations provide the most detailed description of mean winds and turbulent conditions within the eyewall of a historical tropical cyclone to date, illustrating how high-resolution simulations can enhance limited turbulence measurements in hurricanes and giving insight into the extreme conditions threatening offshore and coastal infrastructure.

17 WIND ENERGY↗
DOE OSTI2026

Hurricane wind field representation shapes storm surge and building-scale flood hazard estimates

Coastal flood hazard estimates rely on precise hurricane wind forecasts to assess damage and risk. Here, we demonstrate that errors in hurricane wind field representation can lead to significant biases in storm surge and property-level damage estimates. Using Hurricane Ian (2022) as a case study, we compare widely used parametric, reanalysis, and hybrid wind datasets. Improved wind field accuracy reduces storm surge and damage estimate bias by up to 70\%. Our results underscore the importance of accurately predicting hurricane wind structure in hazard assessments.

Coastal Flooding↗
DOE OSTI2024

Influence of Eastern Pacific Hurricanes on the Southwest US Wildfire Environment

Abstract While some previous studies examined the contribution of Eastern Pacific (EP) hurricanes toward precipitation in the arid Southwest US (SWUS), their potential to influence wildfires in that region has not been explored. Here we show, using observations and simulations from the Energy Exascale Earth System Model (E3SM), that recurving EP hurricanes modulate the wildfire environment in the SWUS by increasing precipitation and soil moisture, and reducing the vapor pressure deficit. This is especially the case during late season months of September–October when the likelihood of storms to recurve and make landfall increases. Further, analysis of burnt area observations reveals that for the months of September–October, recurving EP hurricanes may significantly reduce the prevalence of wildfires in the SWUS. Finally, E3SM simulations indicate that late season EP hurricanes have been on the decline, with important implications for wildfires in the SWUS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Attribution of 2020 hurricane season extreme rainfall to human-induced climate change

Abstract The 2020 North Atlantic hurricane season was one of the most active on record, causing heavy rains, strong storm surges, and high winds. Human activities continue to increase the amount of greenhouse gases in the atmosphere, resulting in an increase of more than 1 °C in the global average surface temperature in 2020 compared to 1850. This increase in temperature led to increases in sea surface temperature in the North Atlantic basin of 0.4–0.9 °C during the 2020 hurricane season. Here we show that human-induced climate change increased the extreme 3-hourly storm rainfall rates and extreme 3-day accumulated rainfall amounts during the full 2020 hurricane season for observed storms that are at least tropical storm strength (>18 m/s) by 10 and 5%, respectively. When focusing on hurricane strength storms (>33 m/s), extreme 3-hourly rainfall rates and extreme 3-day accumulated rainfall amounts increase by 11 and 8%, respectively.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Social-ecological interactions in a disaster context: Puerto Rican farmer households’ food security after Hurricane Maria

Islands are uniquely vulnerable to extreme weather events and food insecurity, and have additional response challenges due to their limited landmasses and economies, isolation, colonial legacies, and high dependence of food imports. Domestic farmers have a key role in producing food for island communities like Puerto Rico, which can safeguard food security when food importation may be challenging. Nevertheless, in the context of disaster, farmers themselves may be vulnerable to food insecurity and unable to contribute to domestic markets. This paper examines Puerto Rican farmers households’ food security in the aftermath of 2017’s Hurricane Maria using a social-ecological lens. Survey data from 405 farmers gathered eight months after Maria, coupled with biophysical data from the hurricane’s impacts (winds, rains, and landslides), were analyzed. Overall, 69% of farmers experienced at least one month of food insecurity in the aftermath of Hurricane Maria, and 38% reported persistent food insecurity (three months or more). A multinomial logistic regression suggests that biophysical impacts, but especially social factors, such as age and constraint access to external sources of support, are linked with persistent food insecurity. This suggests that the biophysical impacts of the hurricane interact with existing infrastructure and social resources to affect farmer vulnerability and the food environment in different ways. Thus, strengthening adaptive capacity in multiple domains can help farmers and vulnerable populations better navigate the disruptions faced during disasters to alleviate food insecurity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Quantifying the Impacts of Land-Cover Change on the Hydrologic Response to Hurricane Ida in the Lower Mississippi River Basin

Abstract The Lower Mississippi River basin (LMRB) has experienced significant changes in land cover and is one of the most vulnerable regions to hurricanes in the United States. Here, we study the impacts of land-cover change on the hydrologic response to Hurricane Ida in LMRB. By using an integrated surface–subsurface hydrologic model, Energy Exascale Earth System Model (E3SM) Land Model coupled with the three-dimensional ParFlow subsurface flow model (ELM-ParFlow), we simulate the effects of land-cover change on the flood volume and peak timing induced by rainfall from Hurricane Ida. The results show that land-cover changes from 1850 to 2015, which resulted in a smoother surface and less vegetation, exacerbated both flood peak time and volume induced by Hurricane Ida. The effects of land-cover changes can be decomposed into two mechanisms: a smoother surface routes more water faster to a watershed outlet and less vegetation allows more water to contribute to surface runoff. By comparing scenarios in which the two mechanisms were isolated, we found that changes in soil moisture due to vegetation cover change have more dominant effects on floods in the southern part and changes in Manning’s coefficient have the largest effect on floods in the northern part of the LMRB. The study provides important insights into the complex relationship between land-use, land-cover, and hydrologic processes in coastal regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Using satellite data to assess Hurricane Helene’s impact on vegetation by land use in the CSRA

Many regions within Georgia, South Carolina, and North Carolina experienced record-breaking rainfall and catastrophic winds due to Hurricane Helene. Helene made landfall on Florida’s big bend on September 26 th , 2024, as a category 4 hurricane, and tracked northward through Georgia and the southern Appalachian Mountains before dissipating on September 29 th , 2024. One significant impact of the hurricane was severe damage to tree canopies across the southeastern United States. This study utilizes satellite-based remotely sensed data provided by the National Aeronautical and Space Administration (NASA) to examine the resilience of these tree canopies following the hurricane. Specifically, the Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), Land Cover Type, Soil Moisture Active Passive (SMAP), and the Global Precipitation Measurement (GPM) mission datasets were employed to study the tree canopy’s response to such events in the Central Savannah River Area (CSRA). A significant increase was observed in the LAI in November of 2024. This increase in LAI was likely influenced by warmer-than-average temperatures throughout October of 2024, along with a second record-breaking rainfall event in the CSRA on November 6th, 2024. The LAI increase was then broken down into land cover type to understand which areas contributed most. The complex nature and resilience of trees became evident, offering opportunities for further exploration and application in urban planning, emergency response, and environmental management.

54 ENVIRONMENTAL SCIENCES↗