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At least 433 records · Page 24

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NASA NTRS2023

Remote Sensing of Dissolved Organic Carbon (DOC) Stocks, Fluxes and Transformations Along the Land-Ocean Aquatic Continuum: Advances, Challenges, and Opportunities

From stream headwaters to the deep ocean, dissolved organic carbon (DOC) is ubiquitous across the world’s aquatic systems, where it fulfills important biogeochemical and ecological functions. Importantly, DOC is a dynamic component of the carbon cycle and represents a global reservoir (mass of carbon) equivalent in size to the atmospheric CO 2 pool. The mobilization, transport, and transformations of DOC along the land-ocean aquatic continuum biogeochemically connect terrestrial landscapes, freshwater and marine ecosystems, and the atmosphere. As a result, DOC budgets are vulnerable to climate- and human-driven changes. Having the ability to quantify DOC stocks, fluxes, and transformations consistently and accurately in aquatic systems is therefore critical to our understanding of DOC’s functions in the environment and of their susceptibility to change. In recent years, optical techniques and synoptic earth observations have opened new doors to achieve this objective on a global scale. In this review, we explore how in situ measurements, earth observations, and the models they inform have facilitated the large-scale quantification of DOC stocks, fluxes, and transformations along the land-ocean aquatic continuum and how they have helped shape our current understanding of the global DOC cycle. The review also explores the limitations and challenges we still face today, and discusses how upcoming and future sensors are expected to provide new insights into our understanding of the global DOC cycle.

Dissolved organic carbon↗

NASA NTRSDate not supplied

Correlations Between Porosity, Spatter, and Process Metrics for Powder Bed Fusion Laser Beam Metallic Additive Manufacturing

Components fabricated using the powder bed fusion laser beam metallic (PBF-LB/M)additive manufacturing process are the result of a multitude of weld passes conducted sequentially. Qualifying components for aerospace applications requires a thorough understanding of the process-structure-properties relationships. Porosity defects are known to have a strong adverse effect on the mechanical properties of a component. In particular, porosity defects created by lack of fusion have high aspect ratio morphologies leading to stress concentrations that become crack initiation sites. In the present work, the occurrence of spatter induced lack of fusion porosity was studied using synchronized in-situ process monitoring, additive manufacturing model-based process metrics, and high-resolution X-ray computed tomography. The results show that lack of fusion porosity is statistically correlated with unremoved welding spatter ejecta of the PBF-LB/M process and process metrics related to the hatching strategy.

Qualification↗

NASA NTRS2012

Calibration of Two-dimensional Floodplain Modeling in the Atchafalaya River Basin Using SAR Interferometry

Two-dimensional (2D) satellite imagery has been increasingly employed to improve prediction of floodplain inundation models. However, most focus has been on validation of inundation extent, with little attention on the 2D spatial variations of water elevation and slope. The availability of high resolution Interferometric Synthetic Aperture Radar (InSAR) imagery offers unprecedented opportunity for quantitative validation of surface water heights and slopes derived from 2D hydrodynamic models. In this study, the LISFLOOD-ACC hydrodynamic model is applied to the central Atchafalaya River Basin, Louisiana, during high flows typical of spring floods in the Mississippi Delta region, for the purpose of demonstrating the utility of InSAR in coupled 1D/2D model calibration. Two calibration schemes focusing on Manning s roughness are compared. First, the model is calibrated in terms of water elevations at a single in situ gage during a 62 day simulation period from 1 April 2008 to 1 June 2008. Second, the model is calibrated in terms of water elevation changes calculated from ALOS PALSAR interferometry during 46 days of the image acquisition interval from 16 April 2008 to 1 June 2009. The best-fit models show that the mean absolute errors are 3.8 cm for a single in situ gage calibration and 5.7 cm/46 days for InSAR water level calibration. The optimum values of Manning's roughness coefficients are 0.024/0.10 for the channel/floodplain, respectively, using a single in situ gage, and 0.028/0.10 for channel/floodplain the using SAR. Based on the calibrated water elevation changes, daily storage changes within the size of approx 230 sq km of the model area are also calculated to be of the order of 107 cubic m/day during high water of the modeled period. This study demonstrates the feasibility of SAR interferometry to support 2D hydrodynamic model calibration and as a tool for improved understanding of complex floodplain hydrodynamics

Hahn Chul Jung↗

NASA NTRS2001

Continuous Measurements and Quantitative Constraints: Challenge Problems for Discrete Modeling Techniques

We present some diagnosis and control problems that are difficult to solve with discrete or purely qualitative techniques. We analyze the nature of the problems, classify them and explain why they are frequently encountered in systems with closed loop control. This paper illustrates the problem with several examples drawn from industrial and aerospace applications and presents detailed information on one important application: In-Situ Resource Utilization (ISRU) on Mars. The model for an ISRU plant is analyzed showing where qualitative techniques are inadequate to identify certain failure modes and to maintain control of the system in degraded environments. We show why the solution to the problem will result in significantly more robust and reliable control systems. Finally, we illustrate requirements for a solution to the problem by means of examples.

Goodrich, Charles H.↗

NASA NTRS1993

AVIRIS calibration and application in coastal oceanic environments

The Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) is a test-bed for future spacecraft sensors such as the High-Resolution Imaging Spectrometer and the Moderate-Resolution Imaging Spectrometers planned for the Earth Observing System. To use this sensor for ocean applications, S/N was increased by spatial averaging of images. Post-flight recalibration was accomplished by measuring in situ the water-leaving radiance at flight time, modeling its transmission to the aircraft, and adding modeled atmospheric radiance to that value. The preflight calibration curve was then adjusted until aircraft and modeled total radiance values matched. Water-leaving radiance values from the recalibrated AVIRIS imagery were consistent with in situ data supporting the validity of the approach. Imagery of the absorption coefficient at 415 nm and backscattering coefficient at 671 nm were used to depict the dissolved and particulate constituents of the Tampa Bay plume during late, ebb-tidal conditions.

Carder, Kendall L.↗

NASA NTRSDate not supplied

Airborne observations in support of a satellite observation-based OH product

This presentation outlines work to date analyzing airborne observations to improve a satellite observation-based hydroxyl radical (OH) column product by interrogating model chemistry processes. Anderson et al., 2023, established a machine learning method to combine satellite observations of O3, CO, NO2, HCHO, H2O, and aerosol optical depth, along with analyzed sea surface temperatures, for the prediction of tropospheric column OH (TCOH). Since the TCOH machine learning model was trained on output from the MERRA-2 GMI model simulation, we seek to identify if any model deficiencies may yield errors in the TCOH prediction. By evaluating F0AM box model simulations and neural networks trained to reproduce in situ OH concentrations, together with output reaction rates and interpretability metrics, respectively, we validate the Anderson et al. TCOH model and assess the largest contributors to uncertainties.

Hydroxyl, oxidizing capacity, troposphere, airborn↗

NASA NTRS1991

Application of TOPEX/Poseidon altimetry measurements to observational and modeling studies of the low-frequency upper ocean mass and heat circulation in the tropical Pacific

The main purpose of the proposed work is to describe the seasonal and interannual variability of the upper ocean mass and heat transport in the tropical Pacific and to understand the mechanisms responsible for these transports. This will be done through a combination of experimental and modeling approaches. Remotely sensed sea level and derived current, observed on the basin scale, will be compared, analyzed, and combined with routine and enhanced in situ measurements of thermal and current field, as well as with model solutions forced by satellite-derived estimates of momentum and heat fluxes. The practical scientific rationale for this work stems from the unique data sets collected by (or easily available to) the investigator's team and from the team members' complementary backgrounds (physical oceanography and meteorology) and expertise (in situ and satellite-observation analysis and numerical ocean modeling).

Picaut, Joel↗

NASA NTRS1991

The modeling of CO2 lidar backscatter from stratospheric aerosols

Factors that affect modeling for the scattering properties of stratospheric aerosols at CO2 laser wavelengths are discussed. Particular attention is given to the relevant stratospheric aerosol measurements, both in situ and remote, and of the techniques for modeling optical properties at wavelengths close to 10.6 microns. The results obtained by such modeling are compared with published CO2 lidar data.

Kent, G. S.↗

NASA NTRS2011

Understanding Geospace on a Grand Scale: The Global Ionoshphere/Thermosphere Constellation

We present the concept of a constellation of polar orbiting satellites equally spaced in longitude (local time) to systematically sample both the neutral and ionzed gas components of the Earth in circular orbits near 350 km, including their density, temperature, and velocities. The instrumentation would include techniques to measure the height of the ionospheric "F-peak" and its variations along the orbit. The number of satellites (l2? 24? 48?) and their configuration would be determined from modeling analysis and expected geophysical phenomena, including their drivers and characteristic time scales. Together with imaging data from separate satellites, the array of satellites with in situ probes would be expected to provide a new picture of (1) high latitude electrodynamics and atmospheric processes and associated coupling with magnetospheric mass and momentum input, (2) the response of the global ionosphere and thermosphere to magnetic storms, and (3) global neutral wind circulation patterns, neutral density structure, tides, planetary waves, and gravity waves. The comprehensive measurements gathered by the IT-Constellation envisioned here would provide a major leap forward in each of these areas, addressing global physical processes and providing fundamental, new knowledge of Geospace. In particular, by its very nature, the constellation addresses "system science", revealing how the ionosphere-thermosphere connects globally to the magnetosphere above and the troposphere below. We present this concept as the next logical step in observing the "whole" space environment using in situ probes in conjunction with imagers. We invite modelers to not only comment on this concept but also to become actively engaged in helping to define it.

Pfaff, Robert↗

NASA NTRS2014

Inter-Comparison of SMOS and Aquarius Sea Surface Salinity: Effects of the Dielectric Constant and Vicarious Calibration

Two spaceborne instruments share the scientific objective of mapping the global Sea Surface Salinity (SSS). ESA's Soil Moisture and Ocean Salinity (SMOS) and NASA's Aquarius use L-band (1.4 GHz) radiometry to retrieve SSS. We find that SSS retrieved by SMOS is generally lower than SSS retrieved by Aquarius, except for very cold waters where SMOS SSS is higher overall. The spatial distribution of the differences in SSS is similar to the distribution of sea surface temperature. There are several differences in the retrieval algorithm that could explain the observed SSS differences. We assess the impact of the dielectric constant model and the ancillary sea surface salinity used by both missions for calibrating the radiometers and retrieving SSS. The differences in dielectric constant model produce differences in SSS of the order of 0.3 psu and exhibit a dependence on latitude and temperature. We use comparisons with the Argo in situ data to assess the performances of the model in various regions of the globe. Finally, the differences in the ancillary sea surface salinity products used to perform the vicarious calibration of both instruments are relatively small (0.1 psu), but not negligible considering the requirements for spaceborne remote sensing of SSS.

radiometry↗

NASA NTRS2005

Aerosol properties computed from aircraft-based observations during the ACE- Asia campaign: A case study of lidar ratio closure and aerosol radiative effects - 2

For a vertical profile with three distinct layers (marine boundary, pollution and dust), observed during the ACE-Asia campaign, we carried out a comparison between the modeled lidar ratio vertical profile and that obtained from collocated airborne NASA AATS-14 sunphotometer and shipborne Micro-Pulse Lidar (MPL) measurements. Vertically resolved lidar ratio was calculated from two size distribution vertical profiles - one obtained by inversion of sunphotometer-derived extinction spectra, and one measured in-situ - combined with the same refractive index model based on aerosol chemical composition. The aerosol model implies single scattering albedos of 0.78 - 0.81 and 0.93 - 0.96 at 0.523 microns (the wavelength of the lidar measurements), in the pollution and dust layers, respectively. The lidar ratios calculated from the two size distribution profiles have close values in the dust layer; they are however, significantly lower than the lidar ratios derived from combined lidar and sunphotometer measurements, most probably due to the use of a simple nonspherical model with a single particle shape in our calculations. In the pollution layer, the two size distribution profiles yield generally different lidar ratios. The retrieved size distributions yield a lidar ratio which is in better agreement with that derived from lidar/sunphotometer measurements in this layer, with still large differences at certain altitudes (the largest relative difference was 46%). We explain these differences by non-uniqueness of the result of the size distribution retrieval and lack of information on vertical variability of particle refractive index. Radiative transfer calculations for this profile showed significant atmospheric radiative forcing, which occurred mainly in the pollution layer. We demonstrate that if the extinction profile is known then information on the vertical structure of absorption and asymmetry parameter is not significant for estimating forcing at TOA and the surface, while it is of importance for estimating vertical profiles of radiative forcing and heating rates.

Kuzmanoski, Maja↗

NASA NTRS2019

How Well Does NASA GEOS Model Perform in Simulating Dust Deposition into the Tropical Atlantic Ocean?

Massive dust emitted from North Africa can transport long distances across the tropical Atlantic Ocean, reaching the Americas. Dust deposition along the transit adds microorganisms and essential nutrients to marine ecosystem, which has important implications for biogeochemical cycle and climate. However, assessing the dust-ecosystemclimate interactions has been hindered in part by the paucity of dust deposition measurements and large uncertainties associated with oversimplified representations of dust processes in current models. We have recently produced a unique dataset of seasonal dust deposition flux and dust loss frequency into the tropical Atlantic Ocean at a nominal resolution of 200 km x 500 km by using the decade-long (2007-2016) record of aerosol three-dimensional distribution from four satellite sensors, namely CALIOP, MODIS, MISR, and IASI. On the basis of the ten-year average, the yearly dust deposition into the tropical Atlantic Ocean is estimated at 98-153 Tg. The dust deposition shows large spatial and temporal (on seasonal and interannual scale) variability. The satellite observations also yield an estimate of annual mean dust loss frequency of 0.052 ~ 0.078 d-1, a useful diagnostic that makes it possible to disentangle the dust transport and removal processes from the dust emissions when identifying the major factors contributing to the uncertainties and biases in the model simulated dust deposition. In this study, we use the dataset along with in situ and remote sensing observations to assess how well NASA GEOS model performs in simulating trans-Atlantic dust transport and deposition. We found that the GEOS modeling of dust deposition falls within the range of satellite-based estimates. However, this reasonable agreement in dust deposition is a compensation of the model's underestimate of dust emissions and overestimate of dust removal efficiency. Further, the overestimate of dust removal efficiency results largely from the model's overestimate of rainfall rate. Our results provide insights into the model's deficiencies at process level, which could better guide model improvements.

Yu, Hongbin↗

NASA NTRS1999

Estimation of Non-Seasonal Oceanic Mass Redistribution and its Geodynamic Effects from the Topex/Poseidon Observation

Mass redistribution in terms of angular momentum will change the Earth's rotation under the conservation of angular momentum. It also changes the external gravitational field according to Newton's gravitational law. These small geodynamic variations can be measured very accurately by modem space geodetic techniques. We report on new estimates of the oceanic tidal angular momentum and hence the tidal variations in the Earth's rotation rate and polar motion. These are deduced from the new tidal solutions GOT99 and TPXO.3, plus M2 and Mf estimates (with error bars) from TPXO.4a. Comparisons with observed diurnal/semidiurnal tidal variations are generally similar to previous model estimates. Comparisons of models and observations of Mf polar motion are confused, with neither models nor observations agreeing among themselves or with each other. Part of this is caused by differences in Mf currents; model TPXO.4 shows current-intensive Rossby modes along western boundaries of major basins, which are indeed expected on theoretical grounds. Unfortunately, there are no reliable in situ observations of Mf currents useful for comparing models. On non-tidal oceanic mass redistribution we compute the principal components of the multi-year T/P sea surface height (SSH) field using EOF (empirical orthogonal functions) taking into consideration of the latitude-dependent area weighting. Emphasis is placed upon non-seasonal and interannual oscillations on regional scales, including ENSO and the North Atlantic Oscillation. Steric corrections to the observed SSH due to sea surface temperature changes (which has no geodynamic effects) is now under study using POCM ocean model output.

Chao, Benjamin F.↗

NASA NTRS1981

Jovian magnetic models and the polarization angle of Jovian decimetric radiation

A comparative study of the direction of linear polarization of Jovian decimetric (synchrotron) radiation as measured astronomically and as determined from a model of the inner Jovian magnetosphere is discussed. It is noted that the model depicts the radiation as coming from rings of relativistic electrons in the Jovimagnetic equator at varying radial distances from the center of the planet. The equator is determined through each of two magnetic representations - the O4 model of Acuna and Ness (1976) and the P10-11 model of Smith et al. (1976) - derived from in situ Pioneer magnetometer measurements. Deviations from a (planar) dipole equator are found to occur at nearly all longitudes in both models; no evidence is found for a longitudinally localized magnetic anomaly.

Birmingham, T. J.↗

NASA NTRS2022

Simultaneous Retrieval of Selected Optical Water Quality Indicators From Landsat-8, Sentinel-2, and Sentinel-3

Constructing multi-source satellite-derived water quality (WQ) products in inland and nearshore coastal waters from the past, present, and future missions is a long-standing challenge. Despite inherent differences in sensors’ spectral capability, spatial sampling, and radiometric performance, research efforts focused on formulating, implementing, and validating universal WQ algorithms continue to evolve. This research extends a recently developed machine-learning (ML) model, i.e., Mixture Density Networks (MDNs) (Pahlevan et al., 2020; Smith et al., 2021), to the inverse problem of simultaneously retrieving WQ indicators, including chlorophyll-a (Chla), Total Suspended Solids (TSS), and the absorption by Colored Dissolved Organic Matter at 440 nm (a cdom (440)), across a wide array of aquatic ecosystems. We use a database of in situ measurements to train and optimize MDN models developed for the relevant spectral measurements (400–800 nm) of the Operational Land Imager (OLI), MultiSpectral Instrument (MSI), and Ocean and Land Color Instrument (OLCI) aboard the Landsat-8, Sentinel-2, and Sentinel-3 missions, respectively. Our two performance assessment approaches, namely hold-out and leave-one-out, suggest significant, albeit varying degrees of improvements with respect to second-best algorithms, depending on the sensor and WQ indicator (e.g., 68%, 75%, 117% improvements based on the hold-out method for Chla, TSS, and a cdom (440), respectively from MSI-like spectra). Using these two assessment methods, we provide theoretical upper and lower bounds on model performance when evaluating similar and/or out-of-sample datasets. To evaluate multi-mission product consistency across broad spatial scales, map products are demonstrated for three near-concurrent OLI, MSI, and OLCI acquisitions. Overall, estimated TSS and a cdom (440) from these three missions are consistent within the uncertainty of the model, but Chla maps from MSI and OLCI achieve greater accuracy than those from OLI. By applying two different atmospheric correction processors to OLI and MSI images, we also conduct matchup analyses to quantify the sensitivity of the MDN model and best-practice algorithms to uncertainties in reflectance products. Our model is less or equally sensitive to these uncertainties compared to other algorithms. Recognizing their uncertainties, MDN models can be applied as a global algorithm to enable harmonized retrievals of Chla, TSS, and a cdom (440) in various aquatic ecosystems from multi-source satellite imagery. Local and/or regional ML models tuned with an apt data distribution (e.g., a subset of our dataset) should nevertheless be expected to outperform our global model.

Machine learning↗

NASA NTRSDate not supplied

Ice Growth Model and Lunar Tanker for Polar Water Extraction

In-Situ Resource Utilization (ISRU) is a major component of sustainable and cost-effective missions to the Moon and beyond. Ever since it has been identified in the Permanently Shadowed Regions (PSRs) of the Moon, water has become a resource of interest for it’s wide range of uses such as life support and hydrogen and oxygen rocket propellant. It is ice-bound in the regolith, so separation typically involves heating to sublimation temperatures and capturing at very low pressure. One option is to then store it in ice form and transport it out of the PSR and into a sunlit ridge. From here, processes such as electrolysis can be performed. An understanding of frost growth dynamics under rarefied conditions is necessary for successful water production, though. An analytical model was developed using a Diffusion-Limited Aggregation (DLA) approach to evaluate bulk thermal conductivity changes of frost under varying conditions. This model will be evaluated using a one-dimensional frost growth experiment on a horizontal, flat plate under vacuum and cryogenic conditions. The tests will measure frost growth rate and bulk density, and the thermal conductivity of the ice layer as a function of thickness for different plate temperatures. The test data will then be used to validate and improve the analytical model.

Lunar water↗

NASA NTRS1995

Planetary and Primitive Object Strength Measurement and Sampling Apparatus

Support is requested for continuation of a program of dynamic impact (harpoon) coring of planetary, comet, or asteroid surface materials. We have previously demonstrated that good quality cores are obtainable for planetary materials with compressive strengths less than 200 MPa. Since the dynamics of penetration are observable on a Discovery class spacecraft, which images the sampling operation, these data can be used with a model developed under this project, to measure in-situ strength and frictional strength of the crust of the object. During the last year we have developed a detailed analytic model of penetrator mechanics. Progress is reported for the solid penetrators experiments, the CIT penetrator model, and the impact spall sampling apparatus.

Ahrens, Thomas J.↗

NASA NTRS2012

Inferring Land Surface Model Parameters for the Assimilation of Satellite-Based L-Band Brightness Temperature Observations into a Soil Moisture Analysis System

The Soil Moisture and Ocean Salinity (SMOS) satellite mission provides global measurements of L-band brightness temperatures at horizontal and vertical polarization and a variety of incidence angles that are sensitive to moisture and temperature conditions in the top few centimeters of the soil. These L-band observations can therefore be assimilated into a land surface model to obtain surface and root zone soil moisture estimates. As part of the observation operator, such an assimilation system requires a radiative transfer model (RTM) that converts geophysical fields (including soil moisture and soil temperature) into modeled L-band brightness temperatures. At the global scale, the RTM parameters and the climatological soil moisture conditions are still poorly known. Using look-up tables from the literature to estimate the RTM parameters usually results in modeled L-band brightness temperatures that are strongly biased against the SMOS observations, with biases varying regionally and seasonally. Such biases must be addressed within the land data assimilation system. In this presentation, the estimation of the RTM parameters is discussed for the NASA GEOS-5 land data assimilation system, which is based on the ensemble Kalman filter (EnKF) and the Catchment land surface model. In the GEOS-5 land data assimilation system, soil moisture and brightness temperature biases are addressed in three stages. First, the global soil properties and soil hydraulic parameters that are used in the Catchment model were revised to minimize the bias in the modeled soil moisture, as verified against available in situ soil moisture measurements. Second, key parameters of the "tau-omega" RTM were calibrated prior to data assimilation using an objective function that minimizes the climatological differences between the modeled L-band brightness temperatures and the corresponding SMOS observations. Calibrated parameters include soil roughness parameters, vegetation structure parameters, and the single scattering albedo. After this climatological calibration, the modeling system can provide L-band brightness temperatures with a global mean absolute bias of less than 10K against SMOS observations, across multiple incidence angles and for horizontal and vertical polarization. Third, seasonal and regional variations in the residual biases are addressed by estimating the vegetation optical depth through state augmentation during the assimilation of the L-band brightness temperatures. This strategy, tested here with SMOS data, is part of the baseline approach for the Level 4 Surface and Root Zone Soil Moisture data product from the planned Soil Moisture Active Passive (SMAP) satellite mission.

Reichle, Rolf H.↗