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At least 145 records · Page 8

Explicit Finite Element Modeling of Multilayer Composite Fabric for Gas Turbine Engine Containment Systems, Phase II: Ballistic Impact Testing - Part 2

This report summarizes the ballistic impact testing that was conducted to provide validation data for the development of numerical models of blade-out events in fabric containment systems. The ballistic impact response of two different fiber materials - Kevlar(TradeName) 49 and Zylon(TradeName) AS (as spun) was studied by firing metal projectiles into dry woven fabric specimens using a gas gun. The shape, mass, orientation, and velocity of the projectile were varied and recorded. In most cases, the tests were designed so the projectile would perforate the specimen, allowing measurement of the energy absorbed by the fabric. The results for both Zylon and Kevlar presented here represent a useful set of data for the purposes of establishing and validating numerical models to predict the response of fabrics under conditions that simulate those of a jet engine blade-release situation. In addition, some useful empirical observations were made regarding the effects of projectile orientation and the relative performance of the different fabric materials.

Zylon↗

Off-Nominal Event Analysis in Autonomous Flights Based on Explainable Artificial Intelligence

A key objective in the Urban Air Mobility program at NASA is to intelligently perform an autonomous flight in a complex urban environment under all weather conditions with guaranteed levels of safety. To accomplish this, the mission manager (central decision-making module) of the vehicle needs to make informed decisions between various Courses of Action (CoA) based on its' interpretation of the inputs it receives. If an off-nominal event is detected either based on the amalgamation of sensor data or the use of machine learning models, the mission manager may greatly benefit from identification of the input features that most likely contributed to that specific event. Such an understanding is usually not possible to obtain from the classical machine learning models (deep learning) due to the inherent black box like structure. However, this understanding is achieved using eXplainable Artificial Intelligence (XAI) models that provide a human interpretable rationale for the predictions made. This work presents a game theory inspired XAI model for the off-nominal assessment of autonomous flights. The proposed approach based on Shapley values is model agnostic, provides local as well as global explanation and satisfies the four axioms (efficiency, symmetry, dummy, additivity) to achieve fair contribution. The versatility of the approach is first demonstrated on a simulated dataset in which the significance of each input to flight phase prediction is clearly identified. Subsequently, data from simulated flight trajectories are fed into the model which reveal the input features that most likely contributed to a rotor failure event thereby empowering the mission manager to take the appropriate CoA.

autonomy↗

Off-Nominal Event Analysis in Autonomous Flights Based on Explainable Artificial Intelligence

A key objective in the Urban Air Mobility program at NASA is to intelligently perform an autonomous flight in a complex urban environment under all weather conditions with guaranteed levels of safety. To accomplish this, the mission manager (central decision-making module) of the vehicle needs to make informed decisions between various Courses of Action (CoA) based on its' interpretation of the inputs it receives. If an off-nominal event is detected either based on the amalgamation of sensor data or the use of machine learning models, the mission manager may greatly benefit from identification of the input features that most likely contributed to that specific event. Such an understanding is usually not possible to obtain from the classical machine learning models (deep learning) due to the inherent black box like structure. However, this understanding is achieved using eXplainable Artificial Intelligence (XAI) models that provide a human interpretable rationale for the predictions made. This work presents a game theory inspired XAI model for the off-nominal assessment of autonomous flights. The proposed approach based on Shapley values is model agnostic, provides local as well as global explanation and satisfies the four axioms (efficiency, symmetry, dummy, additivity) to achieve fair contribution. The versatility of the approach is first demonstrated on a simulated dataset in which the significance of each input to flight phase prediction is clearly identified. Subsequently, data from simulated flight trajectories are fed into the model which reveal the input features that most likely contributed to a rotor failure event thereby empowering the mission manager to take the appropriate CoA.

autonomy↗

Gravitational microlensing of gamma-ray bursts

A Monte Carlo code is developed to calculate gravitational microlensing in three dimensions when the lensing optical depth is low or moderate (not greater than 0.25). The code calculates positions of microimages and time delays between the microimages. The majority of lensed gamma-ray bursts should show a simple double-burst structure, as predicted by a single point mass lens model. A small fraction should show complicated multiple events due to the collective effects of several point masses (black holes). Cosmological models with a significant fraction of mass density in massive compact objects can be tested by searching for microlensing events in the current BATSE data. Our catalog generated by 10,000 Monte Carlo models is accessible through the computer network. The catalog can be used to take realistic selection effects into account.

Mao, Shude↗

Thermospheric composition changes seen during a geomagnetic storm

The largest magnitude winds observed using the instruments on board the Dynamics Explorer 2 (DE-2) satellite were measured during the large geomagnetic storm that occurred on November 24, 1982. Neutral temperatures exceeded 2000 K during this storm, and these high temperatures, combined with the very large observed winds and the very full instrumental coverage available in both hemispheres, make it a unique event to study. This paper presents results obtained using these DE-2 data and a time dependent simulation of the event made using the NCAR Thermosphere/Ionosphere General Circulation Model (NCAR-TIGCM). In general, the agreement between model calculations and the data is very good, implying that most of the important physical processes controlling the energetics and dynamics of the thermosphere are reasonably well represented in the model. The modeled summer hemisphere changes in the mass mixing ratio of N2 (Psi(N2)) are in very good agreement with the averaged data in both hemispheres. This paper describes model-experiment comparisons for the November 24, 1982 geomagnetic storm changes.

Burns, A. G.↗

The need for enhanced initial moisture information in simulations of a complex summertime precipitation event

Initial simulations of the June 28, 1986 Cooperative Huntsville Meteorological Experiment case illustrate the need for mesoscale moisture information in a summertime situation in which deep convection is organized by weak large scale forcing. A methodology is presented for enhancing the initial moisture field from a combination of IR satellite imagery, surface-based cloud observations, and manually digitized radar data. The Mesoscale Atmospheric Simulation Model is utilized to simulate the events of June 28-29. This procedure insures that areas known to have precipitation at the time of initialization will be nearly saturated on the grid scale, which should decrease the time needed by the model to produce the observed Bonnie (a relatively weak hurricane that moved on shore two days before) convection. This method will also result in an initial distribution of model cloudiness (transmissivity) that is very similar to that of the IR satellite image.

Waight, Kenneth T., III↗

A NICER View of the Massive Pulsar PSR J0740+6620 Informed by Radio Timing and XMM-Newton Spectroscopy

We report on Bayesian estimation of the radius, mass, and hot surface regions of the massive millisecond pulsar PSR J0740+6620, conditional on pulse-profile modeling of Neutron Star Interior Composition Explorer X-ray Timing Instrument event data. We condition on informative pulsar mass, distance, and orbital inclination priors derived from the joint North American Nanohertz Observatory for Gravitational Waves and Canadian Hydrogen Intensity Mapping Experiment/Pulsar wideband radio timing measurements of Fonseca et al. We use XMM-Newton European Photon Imaging Camera spectroscopic event data to inform our X-ray likelihood function. The prior support of the pulsar radius is truncated at 16 km to ensure coverage of current dense matter models. We assume conservative priors on instrument calibration uncertainty. We constrain the equatorial radius and mass of PSR J0740+6620 to be-+12.390.981.30km and-+2.0720.0660.067Me respectively, each reported as the posterior credible interval bounded by the 16% and 84% quantiles, conditional on surface hot regions that are non-overlapping spherical caps of fully ionized hydrogen atmosphere with uniform effective temperature; a posteriori, the temperature is=-+TlogK5.99100.060.05([])for each hot region. All software for the X-ray modeling framework is open-source and all data, model, and sample information is publicly available, including analysis notebooks and model modules in the Python language. Our marginal likelihood function of mass and equatorial radius is proportional to the marginal joint posterior density of those parameters(within the prior support)and can thus be computed from the posterior samples.

Millisecond pulsars↗

Comparison of Satellite Rainfall Estimates and Rain Gauge Measurements in Italy, and Impact on Landslide Modeling

Landslides can be triggered by intense or prolonged rainfall. Rain gauge measurements are commonly used to predict landslides even if satellite rainfall estimates are available. Recent research focuses on the comparison of satellite estimates and gauge measurements. The rain gauge data from the Italian network (collected in the system database Verifica Rischio Frana" (VRF)) are compared with the National Aeronautics and Space Administration (NASA) Tropical Rainfall Measuring Mission (TRMM) products. For the purpose, we couple point gauge and satellite rainfall estimates at individual grid cells, evaluating the correlation between gauge and satellite data in different morpho-climatological conditions. We then analyze the statistical distributions of both rainfall data types and the rainfall events derived from them. Results show that satellite data underestimates ground data, with the largest differences in mountainous areas. Power-law models, are more appropriate to correlate gauge and satellite data. The gauge and satellite-based products exhibit different statistical distributions and the rainfall events derived from them differ. In conclusion, satellite rainfall cannot be directly compared with ground data, requiring local investigation to account for specific morpho-climatological settings. Results suggest that satellite data can be used for forecasting landslides, only performing a local scaling between satellite and ground data.

landslide; satellite rainfall; TRMM; rain gauges; ↗

Flood and Landslide Applications of High Time Resolution Satellite Rain Products

Experimental, potentially real-time systems to detect floods and landslides related to heavy rain events are described. A key basis for these applications is high time resolution satellite rainfall analyses. Rainfall is the primary cause for devastating floods across the world. However, in many countries, satellite-based precipitation estimation may be the best source of rainfall data due to insufficient ground networks and absence of data sharing along many trans-boundary river basins. Remotely sensed precipitation from the NASA's TRMM Multi-satellite Precipitation Analysis (TMPA) operational system (near real-time precipitation at a spatial-temporal resolution of 3 hours and 0.25deg x 0.25deg) is used to monitor extreme precipitation events. Then these data are ingested into a macro-scale hydrological model which is parameterized using spatially distributed elevation, soil and land cover datasets available globally from satellite remote sensing. Preliminary flood results appear reasonable in terms of location and frequency of events, with implementation on a quasi-global basis underway. With the availability of satellite rainfall analyses at fine time resolution, it has also become possible to assess landslide risk on a near-global basis. Early results show that landslide occurrence is closely associated with the spatial patterns and temporal distribution of TRMM rainfall characteristics. Particularly, the number of landslides triggered by rainfall is related to rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms. For the purpose of prediction, an empirical TMPA-based rainfall intensity-duration threshold is developed and shown to have skill in determining potential areas of landslides. These experimental findings, in combination with landslide surface susceptibility information based on satellite-based land surface information, form a starting point towards a potential operational landslide monitoring/warning system around the globe.

Adler, Robert F.↗

A study of the break-up characteristics of Chena River Basin using ERTS imagery

The author has identified the following significant results. The Chena River Basin was selected because of the availability of ground truth data for comparison. Very good agreement for snow distribution and rates of ablation was found between the ERTS-1 imagery, the snowmelt model, and field measurements. Monitoring snowmelt rates for relatively small basins appears to be practical. The main limitation of the ERTS-1 imagery is the interval of coverage. More frequent overflights providing coverage are needed for the study of transient hydrologic events. ERTS-1 data is most useful when used in conjunction with snowmelt prediction models and existing snow course data. These results should prove very useful in preliminary assessment of hydrologic conditions in ungaged watersheds and will provide a tool for month-to-month volume forecasting.

Carlson, R. F.↗

Advances in Entry Modeling for Impact Risk Assessment

A summary of recent advancements in the detailed modeling of asteroid atmospheric entry processes made through NASA’s Asteroid Threat Assessment Project (ATAP) is presented. Understanding, and accurately modeling these processes and their associated uncertainties is critical to predicting all downstream impact effects, such as blast wave and thermal damage footprints. Furthermore, there is (perhaps thankfully) a dearth of empirical data for large impactors of the kind that would pose a threat to human populations, on which to anchor and/or validate models used in risk assessments. Therefore, we must rely heavily on detailed theoretical and numerical modeling to develop robust assessments for decision makers. To that end, ATAP has made some significant progress in advancing the capabilities in this area. Two areas in particular are highlighted in the present work: meteoroid ablation mechanisms, and bolide luminosity. The first research area – meteoroid ablation mechanisms – has focused on performing novel high-enthalpy wind tunnel experiments on meteorites and meteorite analogs, and utilizing the resulting data to develop high-fidelity models for impactor mass loss at scale. These efforts have resulted in several insights. Of note, these data suggest a differential vaporization process where volatiles are liberated preferentially when the asteroidal material is subject to high heat, while refractory components remain in the molten layer on the surface. A numerical model has been developed which considers this phenomena, and its effect on the bulk impactors effective heat of ablation is examined. The second research thrust that is discussed is focused on accurate modeling of impactor radiation phenomena. While another submission to the conference will discuss the application of our approach to thermal ground damage modeling, here, we present an overview of our extensive efforts to utilize available ground- and space-based observations of large bolides (~1m diameter, and above) to inform and validate our detailed modeling approaches. These methods have been shown to accurately reconstruct the detailed spectra for the Benesov bolide, as well as approximate the burn footprint for the Tunguska event. Recent effort has focused on reconciling light curve data from multiple sources (all-sky camera networks, GLM, US government sensors), using our validated model, and providing a calibrated model for luminous efficiency which can then be utilized to infer impactor properties such as shape, mass, and composition. This work will be demonstrated through an exemplar case study focusing on a large bolide event with observational data (e.g. Chelyabinsk, Flensburg, etc.). Finally, our team’s assessment on the current maturity of atmospheric entry models, and priorities for future research will be provided.

ATAP↗

Cloud-Based Time Series Analysis of Extremes: Use Cases and Applications

"Extreme weather events, such as hurricanes, tornadoes, floods, droughts, heatwaves, and blizzards, can cause widespread damage, disrupting ecosystems, agricultural production, and economies. The frequency and intensity of these events have been increasing, likely due to climate change, raising concerns and the need for more accurate analysis and predictions. NASA's Goddard Earth Sciences Data and Information Services Center (GES DISC) has migrated its long-term historical datasets, including precipitation data from MERRA-2 reanalysis, GLDAS land data assimilation, and IMERG satellite observations, to the cloud. This cloud-stored data enables scientists and researchers to utilize cloud computing for advanced modeling and forecasting of extreme weather events, eliminating the need to download large datasets. In this presentation, we will provide an overview of the cloud-based data and services managed by GES DISC; demonstrate methods for accessing and analyzing time series data stored in the cloud; and compare results across various datasets to address critical questions related to extreme precipitation. We will present use cases including: 1. Determining the average total precipitation in California during January and February from 2000 to 2024, and identifying anomalous precipitation in 2021. 2. Calculating the 10, 20, 50, and 100-year return periods for maximum daily rainfall based on 25 years of historical precipitation data (2000-2024) for Maryland.

time series↗

Evaluation of the Event Driven Phenology Model Coupled with the VegET Evapotranspiration Model Through Comparisons with Reference Datasets in a Spatially Explicit Manner

A new model coupling scheme with remote sensing data assimilation was developed for estimation of daily actual evapotranspiration (ET). The scheme represents a mix of the VegET, a physically based model to estimate ET from a water balance, and an event driven phenology model (EDPM), where the EDPM is an empirically derived crop specific model capable of producing seasonal trajectories of canopy attributes. In this experiment, the scheme was deployed in a spatially explicit manner within the croplands of the Northern Great Plains. The evaluation was carried out using 2007-2009 land surface forcing data from the North American Land Data Assimilation System (NLDAS) and crop maps derived from remotely sensed data of NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). We compared the canopy parameters produced by the phenology model with normalized difference vegetation index (NDVI) data derived from the MODIS nadir bi-directional reflectance distribution function (BRDF) adjusted reflectance (NBAR) product. The expectations of the EDPM performance in prognostic mode were met, producing determination coefficient (r2) of 0.8 +/-.0.15. Model estimates of NDVI yielded root mean square error (RMSE) of 0.1 +/-.0.035 for the entire study area. Retrospective correction of canopy dynamics with MODIS NDVI brought the errors down to just below 10% of observed data range. The ET estimates produced by the coupled scheme were compared with ones from the MODIS land product suite. The expected r2=0.7 +/-.15 and RMSE = 11.2 +/-.4 mm per 8 days were met and even exceeded by the coupling scheme0 functioning in both prognostic and retrospective modes. Minor setbacks of the EDPM and VegET performance (r2 about 0.5 and additional 30 % of RMSR) were found on the peripheries of the study area and attributed to the insufficient EDPM training and to spatially varying accuracy of crop maps. Overall the experiment provided sufficient evidence of soundness and robustness of the EDPM and VegET coupling scheme, assuring its potential for spatially explicit applications.

Kovalskyy, V.↗

Exploring NASA OMI Level 2 Data With Visualization

Satellite data products are important for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if the satellite data are well utilized and interpreted, such as model inputs from satellite, or extreme events (such as volcano eruptions, dust storms, etc.).Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite data products provided by NASA and other organizations. Such obstacles may be avoided by allowing users to visualize satellite data as images, with accurate pixel-level (Level-2) information, including pixel coverage area delineation and science team recommended quality screening for individual geophysical parameters. We present a prototype service from the Goddard Earth Sciences Data and Information Services Center (GES DISC) supporting Aura OMI Level-2 Data with GIS-like capabilities. Functionality includes selecting data sources (e.g., multiple parameters under the same scene, like NO2 and SO2, or the same parameter with different aggregation methods, like NO2 in OMNO2G and OMNO2D products), user-defined area-of-interest and temporal extents, zooming, panning, overlaying, sliding, and data subsetting, reformatting, and reprojection. The system will allow any user-defined portal interface (front-end) to connect to our backend server with OGC standard-compliant Web Mapping Service (WMS) and Web Coverage Service (WCS) calls. This back-end service should greatly enhance its expandability to integrate additional outside data-map sources.

Level 2↗

Exploring NASA OMI Level 2 Data With Visualization

Satellite data products are important for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if the satellite data are well utilized and interpreted, such as model inputs from satellite, or extreme events (such as volcano eruptions, dust storms,... etc.). Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite data products provided by NASA and other organizations. Such obstacles may be avoided by allowing users to visualize satellite data as "images", with accurate pixel-level (Level-2) information, including pixel coverage area delineation and science team recommended quality screening for individual geophysical parameters. We present a prototype service from the Goddard Earth Sciences Data and Information Services Center (GES DISC) supporting Aura OMI Level-2 Data with GIS-like capabilities. Functionality includes selecting data sources (e.g., multiple parameters under the same scene, like NO2 and SO2, or the same parameter with different aggregation methods, like NO2 in OMNO2G and OMNO2D products), user-defined area-of-interest and temporal extents, zooming, panning, overlaying, sliding, and data subsetting, reformatting, and reprojection. The system will allow any user-defined portal interface (front-end) to connect to our backend server with OGC standard-compliant Web Mapping Service (WMS) and Web Coverage Service (WCS) calls. This back-end service should greatly enhance its expandability to integrate additional outside data/map sources.

Aura↗

Global Kinetic Modeling of Banded Electron Structures in the Plasmasphere

Significant fluxes of 10 eV to 30 keV electrons have been detected in the plasmasphere, appearing as banded structures in energy with broad spatial extents and slowly evolving over several days. It is thought that these populations are decaying plasma sheet electrons injected into the corotating region of near-Earth space. This capture can occur when the convective electric field drops rapidly and the Alfven boundary suddenly outward, trapping the inner edge of the plasma sheet along closed drift paths. Our bounce-averaged kinetic model of superthermal electron transport is able to simulate this capture and the subsequent drift, diffusion, and decay of the plasma cloud. Results of this simulation will be shown and discussed, from the initial injection during the elevated convection to the final loss of the particles. It is thought that not only Coulomb collisions but also wave-particle interactions play a significant role in altering the plasma cloud. Quasilinear diffusion is currently being incorporated into the model and the importance of this mechanism will be examined. Also, the high anisotropy of the trapped population could be unstable and generate plasma waves. These and other processes will be investigated to determine the final fate of the cloud and to quantify where, how, and when the energy of the plasma cloud is deposited. Comparisons with CRRES observations of these events are shown to verify the model and explain the data.

Liemohn, M. W.↗

Remote Sensing of Urban Land Cover/Land Use Change, Surface Thermal Responses, and Potential Meteorological and Climate Change Impacts

City growth influences the development of the urban heat island (UHI), but the effect that local meteorology has on the UHI is less well known. This paper presents some preliminary findings from a study that uses multitemporal Landsat TM and ASTER data to evaluate land cover/land use change (LULCC) over the NASA Marshall Space Flight Center (MFSC) and its Huntsville, AL metropolitan area. Landsat NLCD data for 1992 and 2001 have been used to evaluate LULCC for MSFC and the surrounding urban area. Land surface temperature (LST) and emissivity derived from NLCD data have also been analyzed to assess changes in these parameters in relation to LULCC. Additionally, LULCC, LST, and emissivity have been identified from ASTER data from 2001 and 2011 to provide a comparison with the 2001 NLCD and as a measure of current conditions within the study area. As anticipated, the multi-temporal NLCD and ASTER data show that significant changes have occurred in land covers, LST, and emissivity within and around MSFC. The patterns and arrangement of these changes, however, is significant because the juxtaposition of urban land covers within and outside of MSFC provides insight on what impacts at a local to regional scale, the inter-linkage of these changes potentially have on meteorology. To further analyze these interactions between LULCC, LST, and emissivity with the lower atmosphere, a network of eleven weather stations has been established across the MSFC property. These weather stations provide data at a 10 minute interval, and these data are uplinked for use by MSFC facilities operations and the National Weather Service. The weather data are also integrated within a larger network of meteorological stations across north Alabama. Given that the MSFC weather stations will operate for an extended period of time, they can be used to evaluate how the building of new structures, and changes in roadways, and green spaces as identified in the MSFC master plan for the future, will potentially affect land cover LSTs across the Center. Moreover, the weather stations will also provide baseline data for developing a better understanding of how localized weather factors, such as extreme rainfall and heat events, affect micrometeorology. These data can also be used to model the interrelationships between LSTs and meteorology on a longer term basis to help evaluate how changes in these parameters can be quantified from satellite data collected in the future. In turn, the overall integration of multi-temporal meteorological information with LULCC, and LST data for MSFC proper and the surrounding Huntsville urbanized area can provide a perspective on how urban land surface types affect the meteorology in the boundary layer and ultimately, the UHI. Additionally, data such as this can be used as a foundation for modeling how climate change will potentially impact local and regional meteorology and conversely, how urban LULCC can or will influence changes on climate over the north Alabama area.

Quattrochi, Dale A.↗

Remote Sensing of Urban Land Cover/Land Use Change, Surface Thermal Responses, and Potential Meteorological and Climate Change Impacts

City growth influences the development of the urban heat island (UHI), but the effect that local meteorology has on the UHI is less well known. This paper presents some preliminary findings from a study that uses multitemporal Landsat TM and ASTER data to evaluate land cover/land use change (LULCC) over the NASA Marshall Space Flight Center (MFSC) and its Huntsville, AL metropolitan area. Landsat NLCD data for 1992 and 2001 have been used to evaluate LULCC for MSFC and the surrounding urban area. Land surface temperature (LST) and emissivity derived from NLCD data have also been analyzed to assess changes in these parameters in relation to LULCC. Additionally, LULCC, LST, and emissivity have been identified from ASTER data from 2001 and 2011 to provide a comparison with the 2001 NLCD and as a measure of current conditions within the study area. As anticipated, the multi-temporal NLCD and ASTER data show that significant changes have occurred in land covers, LST, and emissivity within and around MSFC. The patterns and arrangement of these changes, however, is significant because the juxtaposition of urban land covers within and outside of MSFC provides insight on what impacts at a local to regional scale, the inter-linkage of these changes potentially have on meteorology. To further analyze these interactions between LULCC, LST, and emissivity with the lower atmosphere, a network of eleven weather stations has been established across the MSFC property. These weather stations provide data at a 10 minute interval, and these data are uplinked for use by MSFC facilities operations and the National Weather Service. The weather data are also integrated within a larger network of meteorological stations across north Alabama. Given that the MSFC weather stations will operate for an extended period of time, they can be used to evaluate how the building of new structures, and changes in roadways, and green spaces as identified in the MSFC master plan for the future, will potentially affect land cover LSTs across the Center. Moreover, the weather stations will also provide baseline data for developing a better understanding of how localized weather factors, such as extreme rainfall and heat events, affect micrometeorology. These data can also be used to model the interrelationships between LSTs and meteorology on a longer term basis to help evaluate how changes in these parameters can be quantified from satellite data collected in the future. In turn, the overall integration of multi-temporal meteorological information with LULCC, and LST data for MSFC proper and the surrounding Huntsville urbanized area can provide a perspective on how urban land surface types affect the meteorology in the boundary layer and ultimately, the UHI. Additionally, data such as this can be used as a foundation for modeling how climate change will potentially impact local and regional meteorology and conversely, how urban LULCC can or will influence changes on climate over the north Alabama area.

Quattrochi, Dale A.↗