Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “surface complexation modeling”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Large-eddy simulation of a boundary layer with concave streamwise curvature

Turbulence modeling continues to be one of the most difficult problems in fluid mechanics. Existing prediction methods are well developed for certain classes of simple equilibrium flows, but are still not entirely satisfactory for a large category of complex non-equilibrium flows found in engineering practice. Direct and large-eddy simulation (LES) approaches have long been believed to have great potential for the accurate prediction of difficult turbulent flows, but the associated computational cost has been prohibitive for practical problems. This remains true for direct simulation but is no longer clear for large-eddy simulation. Advances in computer hardware, numerical methods, and subgrid-scale modeling have made it possible to conduct LES for flows or practical interest at Reynolds numbers in the range of laboratory experiments. The objective of this work is to apply ES and the dynamic subgrid-scale model to the flow of a boundary layer over a concave surface.

Lund, Thomas S.↗
NASA NTRS2002

Length Scale and Gravity Effects on Microgravity Boiling Heat Transfer

Boiling is a complex phenomenon where hydrodynamics, heat transfer, mass transfer, and interfacial phenomena are tightly interwoven. An understanding of boiling and critical heat flux in microgravity environments is of importance to space based hardware and processes such as heat exchange, cryogenic fuel storage and transportation, electronic cooling, and material processing due to the large amounts of heat that can be removed with relatively little increase in temperature. Although research in this area has been performed in the past four decades, the mechanisms by which heat is removed from surfaces in microgravity are still unclear. In earth gravity, buoyancy is an important parameter that affects boiling heat transfer through the rate at which bubbles are removed from the surface. A simple model describing the bubble departure size based on a quasistatic force balance between buoyancy and surface tension is given by the Fritz [I] relation: Bo(exp 1/2) = 0.0208 theta where Bo is the ratio between buoyancy and surface tension forces. For small, rapidly growing bubbles, inertia associated with the induced liquid motion can also cause bubble departure. In microgravity, the magnitude of effects related to natural convection and buoyancy are small and physical mechanisms normally masked by natural convection in earth gravity such as Marangoni convection can substantially influence the boiling and vapor bubble dynamics. CHF (critical heat transfer) is also substantially affected by microgravity. In 1 g environments, Bo has been used as a correlating parameter for CHF. Zuber's CHF model for an infinite horizontal surface assumes that vapor columns formed by the merger of bubbles become unstable due to a Helmholtz instability blocking the supply of liquid to the surface. The jets are spaced lambda(sub D) apart, where lambda(sub D) = 2pi square root of 3[(sigma)/(g(rho(sub l) - rho(sub v)](exp 1/2) = 2pi square root of 3 L Bo(exp -1/2) = square root of 3 lambda(sub c) and is the wavelength that amplifies most rapidly. The critical wavelength, lambda(sub c), is the wavelength below which a vapor layer underneath a liquid layer is stable. For heaters with Bo smaller than about 3 (heaters smaller than lambda(sub D)), the above model is not applicable, and surface tension effects dominate. Bubble coalescence is thought to be the mechanism for CHF under these conditions. Small Bo can result by decreasing the size of a heater in earth gravity, or by operating a large heater in a lower gravity environment. In the microgravity of space, even large heaters can have low Bo, and models based on Helmholtz instability should not be applicable. The macrolayer model of Haramura and Katto is dimensionally equivalent to Zuber's model and has the same dependence on gravity, so it should not be applicable as well. The goal of this work is to determine how boiling heat transfer mechanisms in a low-g environment are altered from those at higher gravity levels. Boiling data using a microheater array was obtained under gravity environments ranging from 1.8 g to 0.02 g with heater sizes ranging from 2.7 mm to 1 mm. The boiling behavior for 2.7 mm at 0.02 g looked quite similar to boiling on the 1 mm heater at 1 g-the formation of a large primary bubble surrounded by smaller satellite bubbles was observed under both conditions. The similarity suggests that for heaters smaller than some fraction of I(sub c), coalescence and surface tension dominate boiling heat transfer. It also suggests that microgravity boiling can be studied by studying boiling on very small heaters.

Kim, Jungho↗
NASA NTRS2014

Towards Full Aircraft Airframe Noise Prediction: Lattice Boltzmann Simulations

Computational results for an 18%-scale, semi-span Gulfstream aircraft model are presented. Exa Corporation's lattice Boltzmann PowerFLOW(trademark) solver was used to perform time-dependent simulations of the flow field associated with this high-fidelity aircraft model. The simulations were obtained for free-air at a Mach number of 0.2 with the flap deflected at 39 deg (landing configuration). We focused on accurately predicting the prominent noise sources at the flap tips and main landing gear for the two baseline configurations, namely, landing flap setting without and with gear deployed. Capitalizing on the inherently transient nature of the lattice Boltzmann formulation, the complex time-dependent flow features associated with the flap were resolved very accurately and efficiently. To properly simulate the noise sources over a broad frequency range, the tailored grid was very dense near the flap inboard and outboard tips. Extensive comparison of the computed time-averaged and unsteady surface pressures with wind tunnel measurements showed excellent agreement for the global aerodynamic characteristics and the local flow field at the flap inboard and outboard tips and the main landing gear. In particular, the computed fluctuating surface pressure field for the flap agreed well with the measurements in both amplitude and frequency content, indicating that the prominent airframe noise sources at the tips were captured successfully. Gear-flap interaction effects were remarkably well predicted and were shown to affect only the inboard flap tip, altering the steady and unsteady pressure fields in that region. The simulated farfield noise spectra for both baseline configurations, obtained using a Ffowcs-Williams and Hawkings acoustic analogy approach, were shown to be in close agreement with measured values.

Khorrami, Mehdi R.↗
NASA NTRS2017

Daily Kilometer-Scale MODIS Satellite Maps of PM2.5 Describe Wintertime Episodes

The San Joaquin Valley (SJV) suffers from severe health-endangering episodes of PM2.5 aerosol loadings in wintertime; episodes last approximately 5 days and differ in geographical distribution and composition. PM2.5 stations are scattered; consequently the use of remote sensing to map variable regional patterns of these varying respirable aerosol concentrations is desirable. High-precision AOT retrievals can capture column particulate loading. However,PM2.5 mapping is challenging due to several reasons: particularly thin mixed layers (ML) and thus relatively low aerosol optical thickness (AOT) close to current measurement limits, variable and a typical composition of the aerosols, and complex surface bidirectional reflectance. However, the West does present some advantages in analysis. Air basins are isolated from long-distance transport, and experience predominant strong meteorological subsidence. Thus these Western basin regions have fewer problematic cases of overriding aerosol layers detached from the surface. To counter such local overriding, Chu et al. have described an approach for the Eastern US, and He et al have described a synoptic classification approach useful in Shanghai. The Bay Area Air Quality Management District (BAAQMD) expands our experience with the use of AOT, with lower PM2.5 and several isolated sub-basins. We have prepared daily maps of episodes in each region. We present also a sequence of increasingly detailed statistical models, AOT initially appears to contribute little information; however, inclusion of weather information reveals its utility. Lyapustin and Wang's MultiAngle Implementation of Atmospheric Correction (MAIAC) retrieval for AOT provided the most useful operational remote sensing information for these regions. It provides high (1-km) spatial resolution maps and a high percentage of availability. Empirical regression methods have found that random effects regression models (aka mixed effects models, ME) employing AOT provide good estimates of ground PM2.5 concentrations.Here, we attempt to extend these methods and evaluate the usefulness of AOT with greater physical analysis, based on DISCOVER-AQ4 experience.

Chatfield, Robert B.↗
NASA NTRS2017

Using Neural Networks to Improve the Performance of Radiative Transfer Modeling Used for Geometry Dependent Surface Lambertian-Equivalent Reflectivity Calculations

Surface Lambertian-equivalent reflectivity (LER) is important for trace gas retrievals in the direct calculation of cloud fractions and indirect calculation of the air mass factor. Current trace gas retrievals use climatological surface LER's. Surface properties that impact the bidirectional reflectance distribution function (BRDF) as well as varying satellite viewing geometry can be important for retrieval of trace gases. Geometry Dependent LER (GLER) captures these effects with its calculation of sun normalized radiances (I/F) and can be used in current LER algorithms (Vasilkov et al. 2016). Pixel by pixel radiative transfer calculations are computationally expensive for large datasets. Modern satellite missions such as the Tropospheric Monitoring Instrument (TROPOMI) produce very large datasets as they take measurements at much higher spatial and spectral resolutions. Look up table (LUT) interpolation improves the speed of radiative transfer calculations but complexity increases for non-linear functions. Neural networks perform fast calculations and can accurately predict both non-linear and linear functions with little effort.

Geometry Dependent LER (GLER) capture↗
NASA NTRS1984

Terrestrial nitrous oxide cycles and atmospheric effects

The basic processes that cause N2O emission from soils are briefly discussed, and the rate of the processes is shown to vary widely in space and time, depending on soil, climate, and agrotechnical conditions. Although significant amounts of N2O are indeed emitted from the land, the complexity of the soil processes involved and the wide variation of measured rates still prevents the quantitative evaluation, global budgeting, and reliable prediction of atmospheric N2O. Increased atmospheric N2O abundance increases the levels of odd-nitrogen in the stratosphere, which, in turn, decreases the stratospheric ozone density via a catalytic cycle. Using appropriate atmospheric models and current chemical kinetic data, it has been found that the dependence of ozone reduction on N2O increase is nearly linear; a simulated doubling of N2O leads to a predicted decrease of about 14 percent in total ozone column density. A 10 percent increase in N2O yields a predicted increase in nonmelanoma skin cancer of several percent, and a possible raising of surface temperature of 0.03 K.

Whitten, R. C.↗
NASA NTRS1993

Temporal changes in endmember abundances, liquid water and water vapor over vegetation at Jasper Ridge

Imaging spectrometry offers a new way of deriving ecological information about vegetation communities from remote sensing. Applications include derivation of canopy chemistry, measurement of column atmospheric water vapor and liquid water, improved detectability of materials, more accurate estimation of green vegetation cover and discrimination of spectrally distinct green leaf, non-photosynthetic vegetation (NPV: litter, wood, bark, etc.) and shade spectra associated with different vegetation communities. Much of our emphasis has been on interpreting Airborne Visible/Infrared Imaging Spectrometry (AVIRIS) data spectral mixtures. Two approaches have been used, simple models, where the data are treated as a mixture of 3 to 4 laboratory/field measured spectra, known as reference endmembers (EM's), applied uniformly to the whole image, to more complex models where both the number of EM's and the types of EM's vary on a per-pixel basis. Where simple models are applied, materials, such as NPV, which are spectrally similar to soils, can be discriminated on the basis of residual spectra. One key aspect is that the data are calibrated to reflectance and modeled as mixtures of reference EM's, permitting temporal comparison of EM fractions, independent of scene location or data type. In previous studies the calibration was performed using a modified-empirical line calibration, assuming a uniform atmosphere across the scene. In this study, a Modtran-based calibration approach was used to map liquid water and atmospheric water vapor and retrieve surface reflectance from three AVIRIS scenes acquired in 1992 over the Jasper Ridge Biological Preserve. The data were acquired on June 2nd, September 4th and October 6th. Reflectance images were analyzed as spectral mixtures of reference EM's using a simple 4 EM model. Atmospheric water vapor derived from Modtran was compared to elevation, and community type. Liquid water was compare to the abundance of NPV, Shade and Green Vegetation (VG) for select sites to determine whether a relationship existed, and under what conditions the relationship broke down. Temporal trends in endmember fractions, liquid water and atmospheric water vapor were investigated also. The combination of spectral mixture analysis and the Modtran based atmospheric/liquid water models was used to develop a unique vegetation community description.

Roberts, Dar A.↗
NASA NTRS2004

Neural network uncertainty assessment using Bayesian statistics: a remote sensing application

Neural network (NN) techniques have proved successful for many regression problems, in particular for remote sensing; however, uncertainty estimates are rarely provided. In this article, a Bayesian technique to evaluate uncertainties of the NN parameters (i.e., synaptic weights) is first presented. In contrast to more traditional approaches based on point estimation of the NN weights, we assess uncertainties on such estimates to monitor the robustness of the NN model. These theoretical developments are illustrated by applying them to the problem of retrieving surface skin temperature, microwave surface emissivities, and integrated water vapor content from a combined analysis of satellite microwave and infrared observations over land. The weight uncertainty estimates are then used to compute analytically the uncertainties in the network outputs (i.e., error bars and correlation structure of these errors). Such quantities are very important for evaluating any application of an NN model. The uncertainties on the NN Jacobians are then considered in the third part of this article. Used for regression fitting, NN models can be used effectively to represent highly nonlinear, multivariate functions. In this situation, most emphasis is put on estimating the output errors, but almost no attention has been given to errors associated with the internal structure of the regression model. The complex structure of dependency inside the NN is the essence of the model, and assessing its quality, coherency, and physical character makes all the difference between a blackbox model with small output errors and a reliable, robust, and physically coherent model. Such dependency structures are described to the first order by the NN Jacobians: they indicate the sensitivity of one output with respect to the inputs of the model for given input data. We use a Monte Carlo integration procedure to estimate the robustness of the NN Jacobians. A regularization strategy based on principal component analysis is proposed to suppress the multicollinearities in order to make these Jacobians robust and physically meaningful.

Neural Networks (Computer)↗
NASA NTRS2012

Development and Validation of an Interactive Liner Design and Impedance Modeling Tool

The Interactive Liner Impedance Analysis and Design (ILIAD) tool is a LabVIEW-based software package used to design the composite surface impedance of a series of small-diameter quarter-wavelength resonators incorporating variable depth and sharp bends. Such structures are useful for packaging broadband acoustic liners into constrained spaces for turbofan engine noise control applications. ILIAD s graphical user interface allows the acoustic channel geometry to be drawn in the liner volume while the surface impedance and absorption coefficient calculations are updated in real-time. A one-dimensional transmission line model serves as the basis for the impedance calculation and can be applied to many liner configurations. Experimentally, tonal and broadband acoustic data were acquired in the NASA Langley Normal Incidence Tube over the frequency range of 500 to 3000 Hz at 120 and 140 dB SPL. Normalized impedance spectra were measured using the Two-Microphone Method for the various combinations of channel configurations. Comparisons between the computed and measured impedances show excellent agreement for broadband liners comprised of multiple, variable-depth channels. The software can be used to design arrays of resonators that can be packaged into complex geometries heretofore unsuitable for effective acoustic treatment.

Howerton, Brian M.↗
NASA NTRS2012

Instrumentation for the Characterization of Inflatable Structures

Current entry, descent, and landing technologies are not practical for heavy payloads due to mass and volume constraints dictated by limitations imposed by launch vehicle fairings. Therefore, new technologies are now being explored to provide a mass- and volume-efficient solution for heavy payload capabilities, including Inflatable Aerodynamic Decelerators (IAD) [1]. Consideration of IADs for space applications has prompted the development of instrumentation systems for integration with flexible structures to characterize system response to flight-like environment testing. This development opportunity faces many challenges specific to inflatable structures in extreme environments, including but not limited to physical flexibility, packaging, temperature, structural integration and data acquisition [2]. In the spring of 2012, two large scale Hypersonic Inflatable Aerodynamic Decelerators (HIAD) will be tested in the National Full-Scale Aerodynamics Complex s 40 by 80 wind tunnel at NASA Ames Research Center. The test series will characterize the performance of a 3.0 m and 6.0 m HIAD at various angles of attack and levels of inflation during flight-like loading. To analyze the performance of these inflatable test articles as they undergo aerodynamic loading, many instrumentation systems have been researched and developed. These systems will utilize new experimental sensing systems developed by the HIAD ground test campaign instrumentation team, in addition to traditional wind tunnel sensing techniques in an effort to improve test article characterization and model validation. During the 2012 test series the instrumentation systems will target inflatable aeroshell static and dynamic deformation, structural strap loading, surface pressure distribution, localized skin deflection, and torus inflation pressure. This paper will offer an overview of inflatable structure instrumentation, and provide detail into the design and implementation of the sensors systems that will be utilized during the 2012 HIAD ground test campaign.

Swanson, Gregory T.↗
NASA NTRSDate not supplied

Validation of Machine Learning Algorithms for Hyperspectral Inversion of Common Water Quality Indicators

The upcoming transition to a diverse suite hyperspectral airborne and orbiting optical sensors will provide an unprecedented opportunity to measure inland water quality characteristics at a fidelity not previously achievable. This presentation will assess prototype deep learning models trained on synthetic hyperspectral data and validated with collocated in-situ measurements. Synthesized data is becoming increasingly popular for use in data-driven approaches to complex problems, and can compliment real data to increase performance on complex and unusual phenomenon, reduce or test bias, and experiment to demonstrate explainability. We will present insights from hyperspectral inversions of Chlorophyl-a, Phycocyanin, and concentration of non-algal particles using selected orbiting and airborne sensors over diverse, optically complex aquatic scenarios. We analyze how various optical water types affect fidelity of results and where improvements can be made as we prototype for globally operational water quality algorithms which can be leveraged by upcoming hyperspectral missions such as the Surface Biology and Geology (SBG) mission.

Surface Biology and Geology (SBG)↗
NASA NTRS1991

The effects of Reynolds number, rotor incidence angle and surface roughness on the heat transfer distribution in a large-scale turbine rotor passage

A combined experimental and computational program was conducted to examine the heat transfer distribution in a turbine rotor passage geometrically similar to the Space Shuttle Main Engine (SSME) High Pressure Fuel Turbopump (HPFTP). Heat transfer was measured and computed for both the full span suction and pressure surfaces of the rotor airfoil as well as for the hub endwall surface. The objective of the program was to provide a benchmark-quality database for the assessment of rotor heat transfer computational techniques. The experimental portion of the study was conducted in a large scale, ambient temperature, rotating turbine model. The computational portion consisted of the application of a well-posed parabolized Navier-Stokes analysis of the calculation of the three-dimensional viscous flow through ducts simulating a gas turbine package. The results of this assessment indicate that the procedure has the potential to predict the aerodynamics and the heat transfer in a gas turbine passage and can be used to develop detailed three dimensional turbulence models for the prediction of skin friction and heat transfer in complex three dimensional flow passages.

Blair, M. F.↗
NASA NTRS1992

Venus steep-sided domes: Relationships between geological associations and possible petrogenetic models

Venus domes are characterized by steep sides, a circular shape, and a relatively flat summit area. In addition, they are orders of magnitude larger in volume and have a lower height/diameter ratio than terrestrial silicic lava domes. The morphology of the domes is consistent with formation by lava with a high apparent viscosity. Twenty percent of the domes are located in or near tessera (highly deformed highlands), while most other (62 percent) are located in and near coronae (circular deformational features thought to represent local mantle upwelling). These geological associations provide evidence for mechanisms of petrogenesis and several of these models are found to be plausible: remelting of basaltic or evolved crust, differentiation of basaltic melts, and volatile enhancement and eruption of basaltic foams. Hess and Head have shown that the full range of magma compositions existing on the Earth is plausible under various environmental conditions on Venus. Most of the Venera and Vego lander compostional data are consistent with tholeiitic basalt; however, evidence for evolved magmas was provided by Venera 8 data consistent with a quartz monzonite composition. Pieters et al. have examined the color of the Venus surface from Venera lander images and interpret the surface there to be oxidized. Preliminary modeling of dome growth has provided some interpretations of lava rheology. Viscosity values obtained from these models range from 10(exp 14) - 10(exp 17) pa*s, and the yield strength has been calculated to be between 10(exp 4) and 10(exp 6) Pa, consistent with terrestrial silicic rocks. The apparent high viscosity of the dome lavas suggests that the domes have a silicic composition or must augment their viscosity with increased visicularity or crystal content. Sixty-two percent of the Venus domes are associated with coronae, circular features that have been proposed as sites of mantle upwelling, and 20 percent of the domes are located near tessera, relatively high areas of complex deformed terrain. We have investigated several models that are consistent with these geologic associations. The first case involves the differentiation of basalt in a magma reservoir in the crust, perhaps produced by partial melting within a mantle plume. The second case is melting at the base of thickened basaltic crust, and the final case is volatile exsolution and enhancement within a basaltic magma reservoir. The association of domes with tessera might be explained by crustal remelting, while the association with coronae may be consistent with chemical differentiation of a magma reservoir or the exsolution and concentration of volatiles in the reservoir before eruption.

Pavri, B.↗
NASA NTRS2007

Applications of Time-Reversal Processing for Planetary Surface Communications

Due to the power constraints imposed on wireless sensor and communication networks deployed on a planetary surface during exploration, energy efficient transfer of data becomes a critical issue. In situations where groups of nodes within a network are located in relatively close proximity, cooperative communication techniques can be utilized to improve the range, data rate, power efficiency, and lifetime of the network. In particular, if the point-to-point communication channels on the network are well modeled as frequency non-selective, distributed or cooperative beamforming can employed. For frequency-selective channels, beamforming itself is not generally appropriate, but a natural generalization of it, time-reversal communication (TRC), can still be effective. Time-reversal processing has been proposed and studied previously for other applications, including acoustical imaging, electromagnetic imaging, underwater acoustic communication, and wireless communication channels. In this paper, we study both the theoretical advantages and the experimental performance of cooperative TRC for wireless communication on planetary surfaces. We give a brief introduction to TRC and present several scenarios where TRC could be profitably employed during planetary exploration. We also present simulation results illustrating the performance of cooperative TRC employed in a complex multipath environment and discuss the optimality of cooperative TRC for data aggregation in wireless sensor networks

Barton, Richard J.↗
NASA NTRS2015

Characterizing the Vertical Processes of Ozone in Colorado's Front Range Using the GSFC Ozone Dial

Although characterizing the interactions of ozone throughout the entire troposphere are important for health and climate processes, there is a lack of routine measurements of vertical profiles within the United States. In order to monitor this lower ozone more effectively, the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center TROPospheric OZone DIfferential Absorption Lidar (GSFC TROPOZDIAL) has been developed and validated within the Tropospheric Ozone Lidar Network (TOLNet). Two scientifically interesting ozone episodes are presented that were observed during the 2014 Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER AQ) campaign at Ft. Collins,Colorado.The first case study, occurring between 22-23 July 2014, indicates enhanced concentrations of ozone at Ft. Collins during nighttime hours, which was due to the complex recirculation of ozone within the foothills of the Rocky Mountain region. Although quantifying the ozone increase a loft during recirculation episodes has been historically difficult, results indicate that an increase of 20 -30 ppbv of ozone at the Ft. Collins site has been attributed to this recirculation. The second case, occurring between Aug 4-8th 2014, characterizes a dynamical exchange of ozone between the stratosphere and the troposphere. This case, along with seasonal model parameters from previous years, is used to estimate the stratospheric contribution to the Rocky Mountain region. Results suggest that a large amount of stratospheric air is residing in the troposphere in the summertime near Ft. Collins, CO. The results also indicate that warmer tropopauses are correlated with an increase in stratospheric air below the tropopause in the Rocky Mountain Region.

Sullivan, John T.↗
NASA NTRS1983

A dynamic model of thundercloud electric fields

A description is given of the first results obtained with a new type of dynamic electrical model of a thundercloud that allows the charge rearrangement produced in arc breakdown, as well as the conduction and displacement currents, to be calculated with realistic generator configurations. The model demonstrates the great complexity of behavior of thunderclouds owing to the interaction of the nonlinear breakdown mechanisms, the energy stored in the electric field, and a conductivity that varies with altitude. It is also seen that dynamic charge distributions and electric fields are quite different from static distributions. It is noted that these differences affect the initial conditions before and after lightning strokes. The conduction current density to the ionosphere is very much larger in the dynamic cases than in static simulations. Such basic properties of thunderclouds as the production of cloud-to-ground strokes are seen as compatible only with a very limited range of thundercloud models. Another finding is that coronal and convection currents cause the electric fields at the surface to be much smaller than they would be in their absence.

Nisbet, J. S.↗
NASA NTRS2009

Assessing the Potential to Derive Air-Sea Freshwater Fluxes from Aquarius-Like Observations of Surface Salinity

A state-of-the-art numerical model is used to investigate the possibility of determining freshwater flux fields from temporal changes io sea-surface salinity (SSS), a goal of the satellite salinity-measuring mission, Aquarius/SAC-D. Because the estimated advective temporal scale is usually longer than the Aquarius/SAC-D revisit time, the possibility of producing freshwater flux estimates from temporal salinity changes is first examined by using a correlation analysis. For the mean seasonal cycle, the patterns of the correlations between the freshwater fluxes and surface salinity temporal tendencies are mainly zonally oriented, and are highest where the local precipitation is also relatively high. Nonseasonal (deviations from the monthly mean) correlations are highest along mid-latitude moon tracks and are relatively small in the tropics. The complex correlation patterns presented here suggest that a global retrieval of the difference between evaporation and precipitation (E-P) from salinity changes requires more complex techniques than a simple consideration of local balance with surface forcing.

Zhen, Li↗
NASA NTRS2019

Applicability of Spectral Decomposition by Varimax-Rotated, Principal Component Analysis to the Surface Biology and Geology (SBG) VNIR Mission Concept

Cyanobacterial and Harmful Algal Blooms (CyanoHABs) are a growing concern in coastal and inland waters. But, spectral interference from multiple constituents in optically complex waters can hamper application of remote sensing using traditional image processing methods. The Kent State University (KSU) spectral decomposition method can be applied to multispectral and hyperspectral remote sensing images (e.g. HICO and the NASA Glenn HSI2) to partition and identify signals related to cyanobacteria, algae, pigment degradation products and suspended sediment in each pixel. Fundamental to the use of remote sensing data is the ability to extract independent signals from correlated hyperspectral VNIR data cubes. The Kent State University varimax-rotated, principal component analysis method (VPCA) is important to integrate into the SBG VNIR mission concept because it provides greater specificity, a software-based SNR boost relative to hardware performance, and can assist with Cal/Val, Modeling and Applications. We present examples of the hyperspectral application of the KSU VPCA method with relevance to SBG. The information extracted by VPCA can be validated spectrally or spatially with laboratory and/or in situ sensors, which capture spatial or time series of information at discrete points within remote sensing images. Comparisons show hyperspectral sensors extract more components than multispectral ones, but more independent information can be extracted from multispectral sensors by VPCA than traditional band ratio approaches. The spectral decomposition method is capable of enhancing the signal to noise ratio (SNR) of the NASA Glenn, second-generation hyperspectral imager by a factor of 7x to 20x, with a spectral reproducibility of ±3%. The spectral decomposition method, when compared against existing remote sensing monitoring methods exhibits both greater specificity and a lower detection limit. The method has been validated with multispectral images in Lake Erie to quantify the Microcystis CyanoHAB and from the Indian River Lagoon, Florida to quantify the Brown Tide resulting from A. lagunesnsis. Field operations in the Western Basin of Lake Erie were conducted using a bbe Fluoroprobe to collect vertical profiles and horizontal tows along a transect from the Toledo to the Detroit Lighthouse during coincident satellite overpasses. Extraction of pixel values from the MODIS Aqua sensor yields agreement between in situ field and lab-based measures of cyanobacterial, cryptophyte, diatoms and green algae, suspended sediment and pigment degradation products with R2>0.8.

hyperspectral↗