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At least 559 records · Page 31

An AeroCom–AeroSat study: intercomparison of satellite AOD datasets for aerosol model evaluation

To better understand and characterize current uncertainties in the important observational constraint of climate models of aerosol optical depth (AOD), we evaluate and intercompare 14 satellite products, representing nine different retrieval algorithm families using observations from five different sensors on six different platforms. The satellite products (super-observations consisting of 1°×1° daily aggregated retrievals drawn from the years 2006, 2008 and 2010) are evaluated with AErosol RObotic NETwork (AERONET) and Maritime Aerosol Network (MAN) data. Results show that different products exhibit different regionally varying biases (both under- and overestimates) that may reach ±50 %, although a typical bias would be 15 %–25 % (depending on the product). In addition to these biases, the products exhibit random errors that can be 1.6 to 3 times as large. Most products show similar performance, although there are a few exceptions with either larger biases or larger random errors. The intercomparison of satellite products extends this analysis and provides spatial context to it. In particular, we show that aggregated satellite AOD agrees much better than the spatial coverage (often driven by cloud masks) within the 1°×1° grid cells. Up to ∼50 % of the difference between satellite AOD is attributed to cloud contamination. The diversity in AOD products shows clear spatial patterns and varies from 10 % (parts of the ocean) to 100 % (central Asia and Australia). More importantly, we show that the diversity may be used as an indication of AOD uncertainty, at least for the better performing products. This provides modellers with a global map of expected AOD uncertainty in satellite products, allows assessment of products away from AERONET sites, can provide guidance for future AERONET locations and offers suggestions for product improvements. We account for statistical and sampling noise in our analyses. Sampling noise, variations due to the evaluation of different subsets of the data, causes important changes in error metrics. The consequences of this noise term for product evaluation are discussed.

Aerosol↗

Moving With Parasites: Relationships Between Animal Movement and Infectious Disease Across Systems and Scales

Animal movement patterns are important for ecological processes such as population dynamics and infectious disease transmission. Because animals move in response to environmental cues like temperature and precipitation, changes to the environment – whether they are seasonal, interannual, or long-term – can change these processes, leading to changes in population sizes or infectious disease prevalence across space and time. My work uses a combination of simulation modeling and data analysis at multiple spatial and temporal scales to understand the environment-movement-disease connection in diverse animal taxa and environments. In this seminar, I will highlight the diverse ways that the environment can influence infectious disease dynamics via changes to animal movement patterns, including through a global study of migration in ungulate populations, a study of American White Ibis adapting to urban environments in South Florida, and examples of avian influenza prevalence in wild waterfowl. Together, these examples highlight that understanding environment-movement interactions can help predict how infectious disease dynamics might change in the future, as changes to climate, land use, and habitats alter animal movement patterns.

Animal movement↗

Los Angeles Urban Development: Utilizing NASA Earth Observations to Evaluate the Impact of Tree Coverage on Urban Heat Mitigation

Over the last several decades the city of Los Angeles, California, has been experiencing increased temperatures resulting from the urban heat island effect. This is largely due to the expansion of developed areas which allow for the trapping of heat, posing dangerous health risks. As a solution, many organizations have turned to urban greening and tree planting initiatives to help cool vulnerable communities. NASA DEVELOP has partnered with City Plants and the City of Los Angeles, Office of Forest Management to study the role of trees in urban environments and their relation to the mitigation of local urban heat islands. This team used NASA Earth observation data spanning from 2016 to 2022, including land surface temperature and Normalized Difference Vegetation Index (NDVI) data collected from Landsat 8 Thermal Infrared Sensor (TIRS) and International Space Station (ISS) ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS), respectively. Data from the National Agriculture Imagery Program (NAIP) were also used to obtain a supervised classification of tree canopy cover. Our analysis reveals a spatial and temporal connection between temperature and vegetation, suggesting that areas with more vegetation are less likely to suffer high summertime temperatures. Results also highlight the impacts of tree planting programs, such as the Vermont Corridor planting project, which increased tree canopy cover by up to 5% in the community between 2016 and 2022. These findings support the implementation of urban greening practices and inform residents and officials about how investing in trees will help mitigate increasing heat within Los Angeles.

Urban heat island↗

Improvements to the Modeling of the TREAT Reactor and Experiments

This paper summarizes the latest improvements and lessons learned from the modeling and simulation of the transient test reactor at Idaho National Laboratory using the MAM- MOTH reactor physics application. MAMMOTH is a MOOSE-based, Finite Element Method application that specializes in the analysis of the spatial dynamics behavior of nuclear reactors. Since early 2018 several transient tests have been conducted at TREAT, thus providing the opportunity to apply and benchmark modern modeling and simulation tools. MAMMOTH was used to provide predictions of the power coupling factor between the core and the experiment for various experiments. Even though the power coupling factor predictions agree very well with the experimental data, within the bounds of the experimental uncertainty, one shortcoming was the underprediction of the total energy deposited in the core and in the experiment. Determination of the sources for this discrepancy are ongoing, but several key problems have been identified and resolved, thus providing valuable insights for future research. This paper discusses several of these lessons learned. First, the heat capacity data for the TREAT fuel has some significant problems due to limitations of the measurement techniques used circa 1960s. The sensitivity of the peak power and the total energy deposition to various representations of the heat capacity is approximately 5%. Second, the effects of the biological shield and thermal column on the modeling of the core are non-negligible, since they affect the mean generation time and the effective reflection of neutrons back into the core, which is suspected to be important during the core heat up. Matching the reactor period resolves the fact that the reduced spatial domain used in the MAMMOTH model underpredicts the mean generation time. The neutron reflection from these regions is marginally improved with the use of an albedo boundary condition. Third, modeling of the control rod movement with a multi-scheme method is introduced and its current limitations are exposed. Fourth, we explore the effects of using a homogenized model with Superhomogenization equivalence and how that differs from fully heterogeneous simulations. Finally, the energy condensation effects for this graphite core are significant. Solutions with 10 and 26 energy groups show the benefits of using a finer coarse group structure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Electrifying Road Trips to and from National Parks in the Western United States

We evaluate charging infrastructure requirement for electrified long-distance travels to/from national parks in the Western U.S. We conduct a high-resolution spatial and temporal analysis of road trips in the region, accounting for detailed travel volume and pattern, the type of electric vehicles, heterogeneous energy consumption rates depending on driving conditions, charging technology (e.g., power and speed), and charging behavior. The scope includes on-route (or way-point) charging as well as destination charging (in national parks). We estimate the locations and sizes of required charging stations in the entire Western U.S. to enable electrified road trips to/from national parks. We also examine environmental justice and energy equity aspects of projected charging infrastructure (for national parks) in the context of the overall vehicle electrification and charging infrastructure build-out.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

Improved Hierarchical Optimization-Based Classification of Hyperspectral Images Using Shape Analysis

A new spectral-spatial method for classification of hyperspectral images is proposed. The HSegClas method is based on the integration of probabilistic classification and shape analysis within the hierarchical step-wise optimization algorithm. First, probabilistic support vector machines classification is applied. Then, at each iteration two neighboring regions with the smallest Dissimilarity Criterion (DC) are merged, and classification probabilities are recomputed. The important contribution of this work consists in estimating a DC between regions as a function of statistical, classification and geometrical (area and rectangularity) features. Experimental results are presented on a 102-band ROSIS image of the Center of Pavia, Italy. The developed approach yields more accurate classification results when compared to previously proposed methods.

Classification↗

The X-Ray Core of the Low-Luminosity Radio Galaxy 3C346 and ASCA Spectroscopy to Test BL LAC/Radio Galaxy Unification

Radio galaxies are relatively faint sources for Advanced Spacecraft for Cosmology Astrophysics (ASCA), and so in order to get the best possible results from the observations two things have been necessary, both of which delayed the fast preparation of papers. Firstly, the best possible data screening and background subtraction were necessary to improve the signal-to-noise, and all our several initial analysis trials were discarded in favor of using FTOOLS versions 4.1 and above. Secondly, we found that the ASCA spectra were statistically too poor to discriminate well between non-thermal and thermal models, never mind the mixture of the two which we expected on the basis of our ROSAT spatial separation of components in radio galaxies. This means that in each case we have needed to combine the ASCA spectroscopy with analysis of data from other X-ray or radio observations in order to exploit the ASCA data to the full. Our analysis for 3C 346 has yielded the cleanest final result. This powerful radio galaxy at a redshift of 0.161, lies in a poor cluster, which we have separated well from the dominant X-ray component of unresolved emission using a spatial analysis of archival ROSAT data. We were then able to fix the thermal component in our ASCA spectral analysis, and have found evidence that the unresolved emission varied by 32 +/- 13% over the 18 months between the ROSAT and ASCA observations. The unresolved X-ray emission does not suffer from intrinsic absorption, and we have related it to radio structures on both milliarcsecond scales and the arcsecond scales which Chandra can resolve. The source is a target of a Chandra AO2 proposal which we have recently submitted to follow up on our ASCA (and ROSAT) work. 3C 346's orientation to the line of sight is uncertain. However, the absence of X-ray absorption, and the radio/optical/X-ray colors, when combined with with previous radio evidence that the source is a foreshortened radio galaxy of the FRII class, suggest that the radio jets are seen at an angle to the line of sight of about 30 deg, intermediate between the radio-galaxy and quasar classes. The relatively hard ASCA response has allowed us to place an upper limit of 5.6 x 10(exp 43) ergs/ s on the 2-10 keV luminosity of any central X-ray component absorbed bN, gas which might be obscuring the broad-line emission region. Attached to this report is an almost final draft of a paper which we have prepared for submission to the Astrophysical Journal. Our combined ASCA and ROSAT results for NGC 6251 rule out our previously preferred flat-spectrum model and inverse-Compton interpretation for the source based on ROSAT data alone, but a softer X-ray spectrum and moderate absorption bring all the available data (including our early VLA HI measurements) into consistency, and we are reasonably confident that we understand the processes responsible for the X-ray emission. We have made some more sensitive HI absorption measurements which are currently being analyzed, and our plans are to publish our ASCA analysis in conjunction with the new HI results. The ASCA data for NGC 4261 have been difficult to interpret. A re-analysis of our ROSAT data with a wider range of physical parameters brings the ROSAT and ASCA results into reasonable agreement only if the emission from hot gas dominates more than suggested by our earlier work, which is itself unexpected since the radio core is bright and a large jet-related X-ray component would bring the source into agreement with results for others of its type. However, we have recently received our Chandra A01 data for this source, with the spatial resolution which allows us to separate thermal and non-thermal emission components. Our ASCA results will be re-interpreted once the analysis of our Chandra data is complete. The interpretation of the ASCA data for BL Lac object 3C 371 is ongoing, in conjunction with analysis of archival multifrequency data. Radio galaxies are complex in their X-ray properties, and hindsight has shown that the spatial resolution of ASCA is too poor for a reliable interpretation of the data without drawing on other observations. However, the ASCA spectra have made a useful contribution to the interpretation of these sources, and the groundwork is now there for more sensitive work using Chandra and XMM-Newton.

Worrall, Diana↗

Quantifying the influence of natural climate variability on in situ measurements of seasonal total and extreme daily precipitation

Abstract While various studies explore the relationship between individual sources of climate variability and extreme precipitation, there is a need for improved understanding of how these physical phenomena simultaneously influence precipitation in the observational record across the contiguous United States. In this work, we introduce a single framework for characterizing the historical signal (anthropogenic forcing) and noise (natural variability) in seasonal mean and extreme precipitation. An important aspect of our analysis is that we simultaneously isolate the individual effects of seven modes of variability while explicitly controlling for joint inter-mode relationships. Our method utilizes a spatial statistical component that uses in situ measurements to resolve relationships to their native scales; furthermore, we use a data-driven procedure to robustly determine statistical significance. In Part I of this work we focus on natural climate variability: detection is mostly limited to DJF and SON for the modes of variability considered, with the El Niño/Southern Oscillation, the Pacific–North American pattern, and the North Atlantic Oscillation exhibiting the largest influence. Across all climate indices considered, the signals are larger and can be detected more clearly for seasonal total versus extreme precipitation. We are able to detect at least some significant relationships in all seasons in spite of extremely large (> 95%) background variability in both mean and extreme precipitation. Furthermore, we specifically quantify how the spatial aspect of our analysis reduces uncertainty and increases detection of statistical significance while also discovering results that quantify the complex interconnected relationships between climate drivers and seasonal precipitation.

54 ENVIRONMENTAL SCIENCES↗

High Spatial Resolution Thermal Infrared Remote Sensing Data for Analysis of the Atlanta, Georgia, Urban Heat Island Effect and Its Impacts on the Environment

The twenty-first century is the first "urban century" according to the United Nations Development Program. The focus of cities reflects awareness of the growing percentage of the world's population that lives in urban areas. In environmental terms, cities are the original producers of many of the global problems related to waste disposal, air and water pollution, and associated environmental and ecological challenges. Expansion of cities, both in population and areal extent, is a relentless process. In 2000, approximately 3 billion people representing about 40% of the global population, resided in urban areas. Urban population will continue to rise substantially over the next several decades according to UN estimates, and most of this growth will Occur in developing countries. The UN estimates that by 2025, 60% of the world's population will live in urban areas. As a consequence, the number of"megacities" (those cities with populations of 10 million inhabitants or more) will increase by 100 by 2025. Thus, there is a critical need to understand urban areas and what their impacts are on environmental, ecological and hydrologic resources, as well as on the local, regional, and even global climate. One of the more egregious side effects of urbanization is the increase in surface and air temperatures that lead to deterioration in air quality. In the United States, under the more stringent air quality guidelines established by the U.S. Environmental Protection Agency in 1997, nearly 300 counties in 34 states will not meet these new air quality standards for ground level ozone. Mitigation of the urban heat island (UHI) effect is actively being evaluated as a possible way to reduce ground ozone levels in cities and assist states in improving air quality. Foremost in the analysis of how the UHI affects air quality and other environmental factors is the use of remote sensing technology and data to characterize urban land covers in sufficient detail to quantifiably measure the impact of increased urban heating on air quality. The urban landscape impacts surface thermal energy exchanges that determine development of the UHI. This paper will illustrate how we are using high spatial remote sensing data collected over the Atlanta, Georgia metropolitan area in conjunction with other geographic information, to perform a detailed urban land cover classification and to determine the contribution of these land covers to the urban heat island effect. Also, the spatial arrangement of the land covers and the impact on urban heating from these selected patterns of development are evaluated. Additionally, this paper will show how these data are being used as inputs to improve air quality modeling for Atlanta, including potential benefits from UHI mitigation.

Quattrochi, Dale A.↗

Spatial–Temporal Patterns of Historical, Near-Term, and Projected Drought in the Conterminous United States

Major droughts in the United States have heavily impacted the hydrologic system, negatively effecting energy and food production. Improved understanding of historical drought is critical for accurate forecasts. Data from global climate models (GCMs), commonly used to assess drought, cannot effectively evaluate local patterns because of their low spatial scale. This research leverages downscaled (~4 km grid spacing) temperature and precipitation estimates from nine GCMs’ data under the business-as-usual scenario (Representative Concentration Pathway 8.5) to examine drought patterns. Drought severity is estimated using the Palmer Drought Severity Index (PDSI) with the Thornthwaite evapotranspiration method. The specific objectives were (1) To reproduce historical (1966–2005) drought and calculate near-term to future (2011–2050) drought patterns over the conterminous USA. (2) To uncover the local variability of spatial drought patterns in California between 2012 and 2018 using a network-based approach. Our estimates of land proportions affected by drought agree with the known historical drought events of the mid-1960s, late 1970s to early 1980s, early 2000s, and between 2012 and 2015. Network analysis showed heterogeneity in spatial drought patterns in California, indicating local variability of drought occurrence. The high spatial scale at which the analysis was performed allowed us to uncover significant local differences in drought patterns. This is critical for highlighting possible weak systems that could inform adaptation strategies such as in the energy and agricultural sectors.

54 ENVIRONMENTAL SCIENCES↗

Distribution of gas in the inner comae of comets

In order to understand the physical and chemical processes which produce the observed spatial morphology of the cometary coma, it is necessary to analyze observational data with physically meaningful models. Thus, a coupled program of theoretical modeling and complementary observational data analysis was undertaken regarding the spatial distributions of neutral gases in the coma. More, specifically, the particular topics of interest are: (1) the theoretical modeling of the nonequilibrium dynamics of the inner coma with emphasis on the region of the coma from the transition from collisional fluid flow out to the free-flow region and on observable conditions in the coma (i.e., density, outflow speed, and temperature); and (2) the model analysis of an important set of long-slit CCD spectra of comets. The side-by-side development of models along with the observation and analysis of data is an important and integral part of this project. The scientific community has in hand valuable observational and in situ data regarding one comet, Halley. It is important to use Halley as the benchmark by which other remotely observed comet data can be understood. Therefore, the self-consistant analysis of data with appropriate models is of the utmost importance. The data analysis work includes the analysis of the spatial profiles of (OI), NH2, CN, and C2.

Combi, Michael↗

A new technique for enlargement and reconstruction of digital sensor imagery

A new image enlargement and reconstruction routine, the digital image enlarging balanced reconstruction algorithm (DIEBRA), is described. Using a highly modified form of 'balanced' two-dimensional polynomial interpolation, this program enlarges digital imagery, creating synthetic high spatial resolution images. Statistical analysis shows the DIEBRA-generated imagery to be significantly closer to true high spatial resolution imagery at all frequencies than imagery generated by a cubic convolutional reconstruction filter.

Rhea, W. Joseph↗

High Spatial Resolution Airborne Multispectral Thermal Infrared Remote Sensing Data for Analysis of Urban Landscape Characteristics

We have used airborne multispectral thermal infrared (TIR) remote sensing data collected at a high spatial resolution (i.e., 10m) over several cities in the United States to study thermal energy characteristics of the urban landscape. These TIR data provide a unique opportunity to quantify thermal responses from discrete surfaces typical of the urban landscape and to identify both the spatial arrangement and patterns of thermal processes across the city. The information obtained from these data is critical to understanding how urban surfaces drive or force development of the Urban Heat Island (UHI) effect, which exists as a dome of elevated air temperatures that presides over cities in contrast to surrounding non-urbanized areas. The UHI is most pronounced in the summertime where urban surfaces, such as rooftops and pavement, store solar radiation throughout the day, and release this stored energy slowly after sunset creating air temperatures over the city that are in excess of 2-4'C warmer in contrast with non-urban or rural air temperatures. The UHI can also exist as a daytime phenomenon with surface temperatures in downtown areas of cities exceeding 38'C. The implications of the UHI are significant, particularly as an additive source of thermal energy input that exacerbates the overall production of ground level ozone over cities. We have used the Airborne Thermal and Land Applications Sensor (ATLAS), flown onboard a Lear 23 jet aircraft from the NASA Stennis Space Center, to acquire high spatial resolution multispectral TIR data (i.e., 6 bandwidths between 8.2-12.2 (um) over Huntsville, Alabama, Atlanta, Georgia, Baton Rouge, Louisiana, Salt Lake City, Utah, and Sacramento, California. These TIR data have been used to produce maps and other products, showing the spatial distribution of heating and cooling patterns over these cities to better understand how the morphology of the urban landscape affects development of the UHI. In turn, these data have been used by government officials, urban planners, and other decision-makers, to make more informed decisions on how to mitigate the UHI and its subsequent impacts.

Quattrochi, Dale A.↗

Plasma injection at synchronous orbit and spatial and temporal auroral morphology

Analysis of ATS 5 particle spectrograms and simultaneous meridian-scanning photometer data obtained at the base of the ATS field line has revealed systematic relationships between temporal and spatial auroral morphology and particle-injection events. The details of these relationships depend on previous injection events, the local time of the observatory with respect to current-injection events, and the extent and magnitude of current injections. A persistent zone of weak aurora is related to steady plasma-sheet drizzle, and the equatorward edge of this aurora delineates field lines threading the inner edge of the plasma sheet. Auroras associated with injection events superimpose on this preexisting pattern, with the lowest latitude of new precipitation depending on local time. In general, plasma energization is not required between the equatorial plane and the ionosphere to account for observed auroral intensities. The data indicate occasional occurrence of enhanced loss-cone fluxes, suggesting low-altitude field-aligned acceleration. A summary figure shows how various characteristic auroral-precipitation regions are related to the shape, extent, and orientation of the substorm injection boundary and to the subsequent drift paths of injected plasma.

Eather, R. H.↗

Flexural rigidity of the Basin and Range-Colorado Plateau-Rocky Mountain transition from coherence analysis of gravity and topography

Stochastic inversion for flexural loads and flexural rigidity of the continental elastic layer can be accomplished most effectively by using the coherence of gravity and topography. However, the spatial resolution of coherence analysis has been limited by use of two-dimensional periodogram spectra from very large (greater than 10(exp 5)sq km) windows that generally include multiple tectonic features. Using a two-dimensional spectral estimator based on the maximum entropy method, the spatial resolution of flexural proerties can be enhanced by a factor of 4 or more, enabling more detailed analysis at the scale of individual tectonic features. This new approach is used to map the spatial variation of flexural rigidity along the Basin and Range transition to the Colorado Plateau and Middle Rocky Mountains physiographic provinces. Large variations in flexural isostatic responses are found, with rigidities ranging from as low as 8.7 x 10(exp 20) N m (elastic thickness (T(sub e) = 4.6 km) in the Basin and Range to as high as 4.1 x 10(exp 24) N m T(sub e) = 77 km) in the Middle Rocky Mountains. These results compare favorably woith independent determinations of flexural rigidity in the region. Areas of low flexural rigidity correlate strongly with areas of high surface heat flow, as is expected from the contingence of flexural rigidity on a temperature-dependent flow law. Also, late Cenozoic normal faults with large displacements are found primarily in area of low flexural rigidity region. The highest flexural rigidity is found within the Archean Wyoming craton, where evidence suggests that deeply rooted cratonic lithosphere may play a role in determining the distribution of tectonism at the surface.

Lowery, Anthony R.↗

Radar Derived Spatial Statistics of Summer Rain: Data Reduction and Analysis - Volume 2

Data reduction and analysis procedures are discussed along with the physical and statistical descriptors used. The statistical modeling techniques are outlined and examples of the derived statistical characterization of rain cells in terms of the several physical descriptors are presented. Recommendations concerning analyses which can be pursued using the data base collected during the experiment are included.

Konrad, T. G.↗

Use of ordination and classification procedures to evaluate phytoplankton communities during Superflux II

Cluster analysis and an ordination procedure were performed on two data matrices to investigate real and environmental spatial relationships. Multiple regression analysis was used to relate the measured environmental variables to the phytoplankton community changes. Qualitative type phytoplankton data proved to be less structured in both of these spaces, relative to the biomass data. The salinity gradients of the northern transects covaried significantly with the phytoplankton association changes. In the southern transects the light variable was most important in explaining the variance in the ordination axes. These data suggest the close relationships between phytoplankton community changes and the physical hydrology of the area.

Rutledge, C. K.↗

A Thermal Analysis Approach for the Mars Odyssey Spacecraft's Solar Array

There are numerous challenges associated with placing a spacecraft in orbit around Mars. Often. trades must be made such as the mass of the payload and the amount of fuel that can be carried. One technique employed to more efficiently place a spacecraft in orbit while maximizing payload mass (minimizing fuel use) is aerobraking. The Mars Odyssey Spacecraft made use of aerobraking to gradually reduce its orbit period from a highly elliptical insertion orbit to its final science orbit. Aerobraking introduces its own unique challenges, in particular, predicting the thermal response of the spacecraft and its components during each aerobraking drag pass. This paper describes the methods used to perform aerobraking thermal analysis using finite element thermal models of the Mars Odyssey Spacecraft's solar array. To accurately model the complex behavior during aerobraking, the thermal analysis must be tightly coupled to the spatially varying, time dependent aerodynamic heating analysis. Also, to properly represent the temperatures prior to the start of the drag pass. the model must include the orbital solar and planetary heat fluxes. It is critical that the thermal behavior be predicted accurately to maintain the solar array below its structural flight allowable temperature limit. The goal of this paper is to describe a thermal modeling method that was developed for this purpose.

Dec, John A.↗