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At least 667 records · Page 37

Integration of Thermoelectric Generator and Wireless Sensor Node Simulators

This report focuses on integrating TEG and WSN simulators with DC-DC converter as an interface. Here DC stands for direct current. DC-DC converter is essential to balance a wide range of analog, digital, and radio loads acting on the energy source. Also, the voltage level generated by TEGs under varying temperature conditions could be low, irregular, and insufficient to operate WSN, therefore DC-DC is required to boost up the voltage to a desired level. Most of the main problems of DC-DC converters used in TEG system are related to impedance matching between the internal resistance of TEG and the input resistance of DC-DC converter. This report would address the issue associated with dynamic impedance matching under varying temperature conditions in the effort to integrate TEG and WSN. In this effort, dynamic impedance matching algorithms like perturb and observe (P&O) and extremum seeking control (ESC) algorithms will de implemented and compared to achieve maximum peak power tracking (MPPT). In addition, the report will summarize the experimental study performed at BSU on profiling behavior of WSN prototype.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Novel Technique for Distributed Measuring of Strain in the Vadose Zone

Characterizing water content and pressure changes in the vadose zone is important to understanding a variety of geologic processes, ranging from permeability, to evapotranspiration, and aquifer recharge. Changes in water content, or pressure, cause strain in the solid porous medium of the vadose zone, and it is possible that measuring those strains could be used a characterization tool. The Coherence-length-gated Microwave Photonics Interferometry (CMPI) technique measures strain at high resolution along many intervals defined by pairs of reflectors distributed along an optical fiber. This technique has recently been developed at Clemson University, and it has the spatial, and temporal resolution to characterize the strains that are expected to occur with hydrologic changes in the vadose zone. However, the technique has never been used to measure strain in porous media, so its capabilities remain uncertain. The objective of this thesis is to evaluate the ability of using CMPI to measure strain changes in the vadose zone. The research approach consists of conducting laboratory tests using a column filled with sand that was subjected to changes in water content and pressure. An optical fiber with CMPI reflectors was deployed in a high surface area ribbon and used to measure strain along the axis of the column. The column was made from 8-inch, Schedule 40 PVC pipe (75 cm tall, 20 cm inner diameter) and filled with medium-grained sand (K = 2.5x10-6 m/s, porosity = 0.28, Coefficient of Uniformity = 2, van Genuchten (n = 4.34 and  = 0.00039 m-1), Young’s Modulus = 18 – 47 MPa). Five pressure and four temperature sensors attached to probes inserted into the wall. The optical fiber includes five reflectors spaced 10 cm apart on the inside and outside of the column along the vertical axis. Strain measurements are made between pairs of reflectors. The reflectors are created in 250-micron-diameter acrylate-coated single mode Corning SMF28e+ optical fiber using a femtosecond laser. The optical fiber was laminated between two pieces of polyester film creating a large surface area to transfer strain from the porous media to the optical fiber. The experiments were conducted by filling the column from the bottom or infiltrating water from the top. The water was allowed to equilibrate to room temperature prior to each test in order to limit thermoelastic strain. Five injection tests with a rate of 250 ml/min and three infiltration tests at varying rates were conducted, and the results show patterns of strain and pressure are generally similar. Hydrologic conditions define three zones based on the pressure magnitude and distribution. 1.) Ambient Zone where the pressure heads are quasi-static and the pressure gradient is roughly unity (head gradient of zero). This is the uppermost zone and is characterized by negative pressures. 2.) Transition Zone where the pressures increase from ambient to zero, are changing relatively rapidly and the pressure gradient is relatively steep (pressure head gradients of 2). The Transition zone is 10 to 15 cm thick. 3.) Positive Pressure Zone where the pressure is positive, the rate of change is slower than in the transition zone and the gradient is flatter (pressure head gradient 1.1 to 1.2). This is the lowest zone in the column. Injection of water causes the pressure to increase and the three zones to move upward. The Transition zone moves at a rate of approximately 0.0002 m/s +/- .00005, according to analyses of pressure profiles. This is the same as the average velocity of the water calculated as volumetric flux/effective porosity =5.4x10-5 m/s/0.28. Strain signals in the range of 10s  were observed with a noise level of generally less than 0.1  (signal to noise ratio of greater than 100) during injection and drainage. The spatial and temporal distributions of strain caused by injection depend on the location of the moving pressure zones. The locations of the different pressure zones were determined from pressure profiles at different times and these data were transferred to strain time series. This showed that strain in the Ambient pressure zone is either unchanged or slightly compressive, whereas strain in Transition zone is tensile and roughly proportional to the pressure change, and strain ranges from tensile to compressive in the Positive Pressure zone. In general, the strain is variable at the top of the Positive Pressure zone, but it appears to be consistently tensile lower in the zone. The spatial distribution of strain causes three distinct stages in the strain times series measured between pairs of CMPI reflectors. The strain is unchanged or slightly compressive during Stage 1, it increases (positive strain is tensile) approximately linearly at a rate of 0.02 to 0.03 μ/s during the Stage 2, and then flattens out in Stage 3. The strain increases again during Stage 4 of the time series. The pressure also changes in stages. It is unchanged during Stage 1 and then increases relatively rapidly at a rate of between 4 and 10 Pa/s during Stage 2 and continues to increase during Stages 3 and 4, but at a rate slightly slower than during Stage 2 (from 2.5 to 3.5 Pa/s). The rates of pressure and strain change are consistent with basic analyses. The rate of pressurization is similar to the calculated velocity of flow in the saturated zone, and this is similar to the measured velocity of the strain increase. The ratio of the pressurization rate and strain rate during Stage 2 (2.5 (Pa/s) /0.03 (μ/s)) is 80 MPa, which is approximately equal to the upper range expected considering the uniaxial compression and the Young’s Modulus of the sand. An interesting effect occurs when the upper surface of the sand becomes saturated. Significant compression (several 10s of ) occurs as the pressure and saturation increase at the upper surface. Compression occurs throughout the column, but the effect is greatest at the top of the column. The rate of compression is fastest slightly before ponding occurs, but it slows markedly and nearly stops when water starts to accumulate at the surface (ponding). This effect reverses when the surface of the sand is drained, resulting in tension throughout the column. The compression caused by this effect can be as large or larger than the tensile strain that accumulated during filling. This effect was unexpected because increasing pressure is normally associated with tensile strain. Nevertheless, this effect was observed consistently in all tests where the pressure changes at the upper surface, including tests where water was injected from below or infiltrated from above. This effect behaves as if the pore pressure at the upper surface of the sand exerts a normal force on the boundary (increasing pore pressure exerts a downward compression on the boundary). The results of these laboratory experiments indicate that CMPI can measure strain caused by fluid pressure changes in the vadose zone with a signal to noise ratio of 100 or more. Injection and drainage cause a strain signal that is complex, but repeatable. The magnitudes of the strain signal are consistent with magnitudes that are expected based on poroelastic calculations using independently measured properties of the sand. These results indicate that the CMPI technique with an optical fiber laminated in a polyester ribbon generates data that represent the strain distribution during hydrologic processes of imbibition and drainage in variably saturated sand. This suggests that distributed strain measurements using CMPI could be a viable approach for evaluating processes in the vadose zone, laying the groundwork for future field implementation.

47 OTHER INSTRUMENTATION↗

Monitoring and prediction of porosity in laser powder bed fusion using physics-informed meltpool signatures and machine learning

In this work we accomplished the monitoring and prediction of porosity in laser powder bed fusion (LPBF) additive manufacturing process. This objective was realized by extracting physics-informed meltpool signatures from an in-situ dual-wavelength imaging pyrometer, and subsequently, analyzing these signatures via computationally tractable machine learning approaches. Porosity in LPBF occurs despite extensive optimization of processing conditions due to stochastic causes. Hence, it is essential to continually monitor the process with in-situ sensors for detecting and mitigating incipient pore formation. In this work a tall cuboid-shaped part (10 mm × 10 mm × 137 mm, material ATI 718Plus) was built with controlled porosity by varying laser power and scanning speed. This test caused various types of porosity, such as lack-of-fusion and keyhole formation, with varying degrees of severity in the part. The meltpool was continuously monitored using a dual-wavelength imaging pyrometer installed in the machine. Physically intuitive process signatures, such as meltpool length, temperature distribution, and ejecta (spatter) characteristics, were extracted from the meltpool images. Subsequently, relatively simple machine learning models, e.g., K-Nearest Neighbors, were trained to predict both the severity and type of porosity as a function of these physics-informed meltpool signatures. These models resulted in a prediction accuracy exceeding 95% (statistical F1-score). The same analysis was carried out with a complex, black-box deep learning convolutional neural network which directly used the meltpool images instead of physics-informed features. The convolutional neural network produced a comparable F1-score in the range of 89–97%. Finally, these results demonstrate that using pragmatic, physics-informed meltpool signatures within a simple machine learning model is as effective for flaw prediction in LPBF as using a complex and computationally demanding black-box deep learning model.

36 MATERIALS SCIENCE↗

Global distribution of stratospheric aerosols by satellite measurements

A description is given of the first-ever global stratospheric aerosol climatology which is being developed by the earth-orbiting SAM II and SAGE satellite-based sensors. These sensors use the technique of solar occulation; that is, for every spacecraft sunrise and sunset, the modulation of solar intensity caused by the intervening earth-limb is measured. These data are mathematically inverted to yield vertical profiles of aerosol extinction coefficients with 1 km resolution. The data show seasonal variations which are similar in each hemisphere, with strong correlation between aerosol extinction and the corresponding temperature field. Typical values of extinction in the stratosphere are found to be about 0.0001 to 0.0002 per km at 1 micrometer; stratospheric optical depths at this wavelength are about 0.002. The peak extinction in the stratospheric aerosol layer follows the tropopause with altitude, with peak extinction ratios about 10 km above the local tropopause.

Mccormick, M. P.↗

Pyroelectric Energy Scavenging Techniques for Self-Powered Nuclear Reactor Wireless Sensor Networks

Recent advances in technologies for harvesting waste thermal energy from ambient environments present an opportunity to implement truly wireless sensor nodes in nuclear power plants. These sensors could continue to operate during extended station blackouts and during periods when operation of the plant s internal power distribution system has been disrupted. The energy required to power the wireless sensors must be generated using energy harvesting techniques from locally available energy sources, and the energy consumption within the sensor circuitry must therefore be low to minimize power and hence the size requirements of the energy harvester. Harvesting electrical energy from thermal energy sources can be achieved using pyroelectric or thermoelectric conversion techniques. Recent modeling and experimental studies have shown that pyroelectric techniques can be cost competitive with thermoelectrics in self powered wireless sensor applications and, using new temperature cycling techniques, has the potential to be several times as efficient as thermoelectrics under comparable operating conditions. The development of a new thermal energy harvester concept, based on temperature cycled pyroelectric thermal-to-electrical energy conversion, is outlined. This paper outlines the modeling of cantilever and pyroelectric structures and single element devices that demonstrate the potential of this technology for the development of high efficiency thermal-to-electrical energy conversion devices.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Application of Weibull analysis to SSME hardware

Generally, it has been documented that the wearing of engine parts forms a failure distribution which can be approximated by a function developed by Weibull. The purpose here is to examine to what extent the Weibull distribution approximates failure data for designated engine parts of the Space Shuttle Main Engine (SSME). The current testing certification requirements will be examined in order to establish confidence levels. An examination of the failure history of SSME parts/assemblies (turbine blades, main combustion chamber, or high pressure fuel pump first stage impellers) which are limited in usage by time or starts will be done by using updated Weibull techniques. Efforts will be made by the investigator to predict failure trends by using Weibull techniques for SSME parts (turbine temperature sensors, chamber pressure transducers, actuators, and controllers) which are not severely limited by time or starts.

Gray, L. A. B.↗

Embedment of sensors in ceramic structures

Ceramic materials such as silicon carbide (SiC) are attractive for many nuclear applications due to their ability to withstand high temperatures, which inherently improve the thermal efficiency of the power conversion cycle and can in some cases provide high-temperature process heat. SiC is particularly attractive because of its high-temperature strength retention, stability under neutron irradiation, and low neutron absorption. The TCR program has recently demonstrated the ability to fabricate monolithic SiC components with complex geometries using a binder jet additive manufacturing technique followed by densification using chemical vapor infiltration (CVI). This technology presents an opportunity to embed sensors within ceramic components at critical locations that allow for enhanced process monitoring and control of advanced nuclear energy systems. The challenges with embedding sensors in ceramic components are to identify appropriate materials that can survive the CVI process, remain embedded after cooling to room temperature, and be suitable for operation in a high-temperature nuclear environment. This report summarizes the sensors that are being considered for embedding within ceramics, the sensor embedding process, material compatibility studies, and characterization of the embedded components. Material selection is first guided by computational thermodynamics and is confirmed by embedding coupons and examining material interactions using electron microscopy. This work shows that a wide range of refractory metals, as well as certain fiber optic sensors, can be successfully embedded in 3D-printed SiC. Future work will involve testing of functional sensors including thermocouples and optical fiber-based, spatially distributed temperature/strain sensors.

36 MATERIALS SCIENCE↗

Pilot-Scale Validation of Distributed Optical Fiber Sensors for Underground Pipeline Monitoring

Monitoring parameters such as hoop strain, pressure, and acoustic vibrations is key to detecting potential leaks, intrusions, or structural issues. Distributed optical fiber sensor (DOFS) systems provide a compelling solution for continuous, real-time monitoring over long distances. This paper details the development and pilot-scale implementation of DOFS systems for underground pipeline monitoring, evolving from a proof-of-concept stage. Multiple custom-designed DOFS interrogator units—such as optical frequency-domain reflectometry (OFDR), Brillouin optical time-domain analysis (BOTDA), and multimodal interferometer-based fiber acoustic sensor systems were tested to measure the key parameters, such as hoop strain, pipe pressure, surrounding soil temperature, and acoustic vibrations. The underground product pipeline’s outer diameter is 30 inches, the wall thickness is 1.28 inches, and 3 feet deep from the surface. The fiber deployment strategies and sensing data acquisition methods for these systems are discussed. The results demonstrate the effectiveness of DOFS in detecting hoop strain, temperature changes, and acoustic vibrations, showcasing their potential for real-time monitoring and enhancing pipeline safety. These findings from pilot-scale testing offer valuable insights into advancing pipeline monitoring technologies and improving the reliability of underground pipeline systems.

fiber optic sensors↗

Airborne flux measurements of Biogenic Isoprene over California

Biogenic Volatile Organic Compound (BVOC) fluxes were measured onboard the CIRPAS Twin Otter aircraft as part of the California Airborne BVOC Emission Research in Natural Ecosystem Transects (CABERNET) campaign during June 2011. The airborne virtual disjunct eddy covariance (AvDEC) approach used measurements from a PTR-MS and a wind radome probe to directly determine fluxes of isoprene, MVK+MAC, methanol, monoterpenes, and MBO over ~10,000-km of flight paths focusing on areas of California predicted to have the largest emissions of isoprene. The Fast Fourier Transform (FFT) approach was used to calculate fluxes over long transects of more than 15 km, most commonly between 50 and 150 km. The Continuous Wavelet Transformation (CWT) approach was used over the same transects to also calculate "instantaneous" fluxes with localization of both frequency and time independent of non-stationarities. Vertical flux divergence of isoprene is expected due to its relatively short lifetime and was measured directly using "racetrack" profiles at multiple altitudes. It was found to be linear and in the range 5% to 30% depending on the ratio of aircraft altitude to PBL height (z/zi). Fluxes were generally measured by flying consistently 1 at 400 m ±50 m (a.g.l.) altitude, and extrapolated to the surface according to the determined flux divergence. The wavelet-derived surface fluxes of isoprene averaged to 2 km spatial resolution showed good correspondence to Basal Emission Factor (BEF) landcover datasets used to drive biogenic VOC (BVOC) emission models. The surface flux of isoprene was close to zero over Central Valley crops and desert shrublands, but was very high (up to 15 mg m-2 h-1) above oak woodlands, with clear dependence of emissions on temperature and oak density. Isoprene concentrations of up to 8 ppb were observed at aircraft height on the hottest days and over the dominant source regions. While isoprene emissions from agricultural crop regions, shrublands, and coniferous forests were extremely low, high concentrations of methanol and monoterpenes were found above some of these regions. These observations demonstrate the ability to measure fluxes from specific sources by eddy covariance from an aircraft, and suggest the utility of measurements using fast response chemical sensors to constrain emission inventories and map out source distributions for a much broader array of trace gases than was observed in this study. This paper reports the first regional direct eddy covariance fluxes of isoprene. The emissions of VOCs measured from aircraft with 2 km spatial resolution can quantify the distribution of major sources providing the observations required for testing statewide emission inventories of these important trace gases. These measurements will be used in a future study to assess BVOC emission models and their driving variable datasets.

Misztal, P.↗

Fluctuating pressures measured beneath a high-temperature, turbulent boundary layer on a flat plate at Mach number of 5

Fluctuating pressures were measured beneath a Mach 5, turbulent boundary layer on a flat plate with an array of piezoresistive sensors. The data were obtained with a digital signal acquisition system during a test run of 4 seconds. Data sampling rate was such that frequency analysis up to 62.5 kHz could be performed. To assess in situ frequency response of the sensors, a specially designed waveguide calibration system was employed to measure transfer functions of all sensors and related instrumentation. Pressure time histories were approximated well by a Gaussian prohibiting distribution. Pressure spectra were very repeatable over the array span of 76 mm. Total rms pressures ranged from 0.0017 to 0.0046 of the freestream dynamic pressure. Streamwise, space-time correlations exhibited expected decaying behavior of a turbulence generated pressure field. Average convection speed was 0.87 of freestream velocity. The trendless behavior with sensor separation indicated possible systematic errors.

Parrott, Tony L.↗

Thermal forcing on the tropical Pacific from satellite data

Monthly fields of latent heat flux and surface solar irradiance derived from spaceborne sensors were combined to estimate the surface thermal forcing on the tropical Pacific from 1980 to 1983. The annual cycle and the anomalies associated with 1982-1983 ENSO episode were examined. Along the equator and during the early phase of the episode the reduction of solar irradiance into the ocean is found to be compensated to some extent by the decrease in evaporative cooling. The distribution of correlation coefficients demonstrated that outside the equatorial waveguides, surface thermal forcing plays a significant role in the seasonal change of sea surface temperature and surface solar irradiance is main driving force. Significant correlation is also found between anomalous latent heat flux and anomalous change of sea surface temperature over a broad area in the equatorial and southern tropical Pacific, indicating that surface thermal forcing may play a larger role than expected in the anomalous sea surface temperature change, particularly in the reestablishment of the cold tongue at end of the episode.

Liu, W. Timothy↗

Modeling of H2 Dispersion at ARIES

Hydrogen is a versatile and clean energy carrier that can be produced from various renewable sources such as wind, solar, and hydropower and help decarbonize electricity grids, industry, and transportation. Using the Hydrogen Research Facility under Advanced Research on Integrated Energy Systems (ARIES) at the National Renewable Energy Laboratory's (NREL) Flatirons campus as a test bench, the study examines the feasibility, useability, and value of using computational fluid dynamics (CFD) techniques to model hydrogen dispersion. The ARIES facility was chosen because controlled hydrogen releases can be performed at a rate of 27 kg-H2/hr. Site-specific atmospheric and weather condition data such as wind speed and temperature were used as inputs to the model. The results show statistical distributions and ranges of hydrogen concentrations at locations throughout the domain. Wind conditions are found to significantly impact the release behavior, including the hydrogen cloud's direction and concentrations. At low wind speeds (below 1 mph), hydrogen forms a cloud and at higher wind speeds (> 2-4 mph) hydrogen plume stretches in the direction of wind momentum. From >100 simulations for ARIES site-specific conditions, statistical quantities combined with a clustering algorithm were used to propose sensor location at various elevations from ground.

dispersion↗

The Effects of Rainfall Inhomogeneity on Climate Variability of Rainfall Estimated from Passive Microwave Sensors

Passive microwave rainfall estimates that exploit the emission signal of raindrops in the atmosphere are sensitive to the inhomogeneity of rainfall within the satellite field of view (FOV). In particular, the concave nature of the brightness temperature (T(sub b)) versus rainfall relations at frequencies capable of detecting the blackbody emission of raindrops cause retrieval algorithms to systematically underestimate precipitation unless the rainfall is homogeneous within a radiometer FOV, or the inhomogeneity is accounted for explicitly. This problem has a long history in the passive microwave community and has been termed the beam-filling error. While not a true error, correcting for it requires a priori knowledge about the actual distribution of the rainfall within the satellite FOV, or at least a statistical representation of this inhomogeneity. This study first examines the magnitude of this beam-filling correction when slant-path radiative transfer calculations are used to account for the oblique incidence of current radiometers. Because of the horizontal averaging that occurs away from the nadir direction, the beam-filling error is found to be only a fraction of what has been reported previously in the literature based upon plane-parallel calculations. For a FOV representative of the 19-GHz radiometer channel (18 km X 28 km) aboard the Tropical Rainfall Measuring Mission (TRMM), the mean beam-filling correction computed in this study for tropical atmospheres is 1.26 instead of 1.52 computed from plane-parallel techniques. The slant-path solution is also less sensitive to finescale rainfall inhomogeneity and is, thus, able to make use of 4-km radar data from the TRMM Precipitation Radar (PR) in order to map regional and seasonal distributions of observed rainfall inhomogeneity in the Tropics. The data are examined to assess the expected errors introduced into climate rainfall records by unresolved changes in rainfall inhomogeneity. Results show that global mean monthly errors introduced by not explicitly accounting for rainfall inhomogeneity do not exceed 0.5% if the beam-filling error is allowed to be a function of rainfall rate and freezing level and does not exceed 2% if a universal beam-filling correction is applied that depends only upon the freezing level. Monthly regional errors can be significantly larger. Over the Indian Ocean, errors as large as 8% were found if the beam-filling correction is allowed to vary with rainfall rate and freezing level while errors of 15% were found if a universal correction is used.

Kummerow, Christian↗

Iron charge states observed in the solar wind

Solar wind measurements from the ULECA sensor of the Max-Planck-Institut/University of Maryland experiment on ISEE-3 are reported. The low energy section of approx the ULECA sensor selects particles by their energy per charge (over the range 3.6 keV/Q to 30 keV/Q) and simultaneously measures their total energy with two low-noise solid state detectors. Solar wind Fe charge state measurements from three time periods of high speed solar wind occurring during a post-shock flow and a coronal hole-associated high speed stream are presented. Analysis of the post-shock flow solar wind indicates the charge state distributions for Fe were peaked at approx +16, indicative of an unusually high coronal temperature (3,000,000 K). In contrast, the Fe charge state distribution observed in a coronal hole-associated high speed stream peaks at approx -9, indicating a much lower coronal temperature (1,400,000 K). This constitutes the first reported measurements of iron charge states in a coronal hole-associated high speed stream.

Ipavich, F. M.↗

Polarized View of Supercooled Liquid Water Clouds

Supercooled liquid water (SLW) clouds, where liquid droplets exist at temperatures below 0 C present a well known aviation hazard through aircraft icing, in which SLW accretes on the airframe. SLW clouds are common over the Southern Ocean, and climate-induced changes in their occurrence is thought to constitute a strong cloud feedback on global climate. The two recent NASA field campaigns POlarimeter Definition EXperiment (PODEX, based in Palmdale, California, January-February 2013) and Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS, based in Houston, Texas in August- September 2013) provided a unique opportunity to observe SLW clouds from the high-altitude airborne platform of NASA's ER-2 aircraft. We present an analysis of measurements made by the Research Scanning Polarimeter (RSP) during these experiments accompanied by correlative retrievals from other sensors. The RSP measures both polarized and total reflectance in 9 spectral channels with wavelengths ranging from 410 to 2250 nm. It is a scanning sensor taking samples at 0.8deg intervals within 60deg from nadir in both forward and backward directions. This unique angular resolution allows for characterization of liquid water droplet size using the rainbow structure observed in the polarized reflectances in the scattering angle range between 135deg and 165deg. Simple parametric fitting algorithms applied to the polarized reflectance provide retrievals of the droplet effective radius and variance assuming a prescribed size distribution shape (gamma distribution). In addition to this, we use a non-parametric method, Rainbow Fourier Transform (RFT),which allows retrieval of the droplet size distribution without assuming a size distribution shape. We present an overview of the RSP campaign datasets available from the NASA GISS website, as well as two detailed examples of the retrievals. In these case studies we focus on cloud fields with spatial features varying between glaciated and liquid phases at altitudes as high as 10 km, which correspond to temperatures close to the homogeneous freezing temperature of pure water drops (about -35 C or colder). The multimodal droplet size distributions retrieved from RSP data in these cases are consistent with the multi-layer cloud structure observed by correlative Cloud Physics Lidar (CPL) measurements.

Clouds↗

A component decomposition model for evaluating atmospheric effects in remote sensing

A radiance value of a target pixel recorded by a remote sensor can be decomposed into three components: (1) attenuated target signature, (2) pure atmospheric radiation, and (3) the contribution made by the ground through the atmospheric scattering process. Given the meteorological and optical parameters of a layer-structured atmosphere, its transmittance and radiance distribution can be accurately calculated with a plane-parallel radiative transfer model. For a uniform surface, the ground contribution can be obtained by comparing radiances for an atmosphere over a black but nonemitting surface and the same atmosphere with an underlying ground of given albedo or temperature. For an inhomogeneous surface, the first two components remain the same as long as the surface is a plane. The third may be estimated using the locally averaged top-of-atmosphere radiance. An atmospheric point spread function is calculated by a Monte Carlo approach and is used for retrieving the ground signature through a deconvolution procedure.

Li, S.↗

Mapping Arid Vegetation Species Distributions in the White Mountains, Eastern California, Using AVIRIS, Topography, and Geology

Our challenge is to model plant species distributions in complex montane environments using disparate sources of data, including topography, geology, and hyperspectral data. From an ecologist's point of view, species distributions are determined by local environment and disturbance history, while spectral data are 'ancillary.' However, a remote sensor's perspective says that spectral data provide picture of what vegetation is there, topographic and geologic data are ancillary. In order to bridge the gap, all available data should be used to get the best possible prediction of species distributions using complex multivariate techniques implemented on a GIS. Vegetation reflects local climatic and nutrient conditions, both of which can be modeled, allowing predictive mapping of vegetation distributions. Geologic substrate strongly affects chemical, thermal, and physical properties of soils, while climatic conditions are determined by local topography. As elevation increases, precipitation increases and temperature decreases. Aspect, slope, and surrounding topography determine potential insolation, so that south-facing slopes are warmer and north-facing slopes cooler at a given elevation. Topographic position (ridge, slope, canyon, or meadow) and slope angle affect sediment accumulation and soil depth. These factors combine as complex environmental gradients, and underlie many features of plant distributions. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data, digital elevation models, digitized geologic maps, and 378 ground control points were used to predictively map species distributions in the central and southern White Mountains, along the western boundary of the Basin and Range province. Minimum Noise Fraction (MNF) bands were calculated from the visible and near-infrared AVIRIS bands, and combined with digitized geologic maps and topographic variables using Canonical Correspondence Analysis (CCA). CCA allows for modeling species 'envelopes' in multidimensional environmental space, which can then be projected across entire landscapes.

VandeVen, C.↗