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NASA NTRSDate not supplied

High Temperature Material Property Data and Challenges to Thermal Process Model Predictions and In-Situ/Ex-Situ Measurements for Metallic Additive Manufacturing

Understanding and predicting performance properties of parts produced by metallic additive manufacturing has improved significantly over the past decade; however, difficult to measure material properties and process outcomes continue to be challenges. The qualification or certification of aerospace parts require extensive measures to quantify variable part properties in order to buy down the risk of component failure. The variability, inherent to the additive manufacturing, process adds unwanted uncertainty in the production of load critical structural components. Process modeling has proven valuable in providing predictions and context for understanding outcomes of the additive manufacturing process; however, these physically informed process models require material properties at temperatures that are difficult to measure and rarely available. Further, calibrating or validating such models is difficult because the process itself is challenging to measure. This talk will explore some of the challenges resulting from difficult to acquire input data by relating thermal process model predictions to in-situ and ex-situ optical microscopy measurements.

Process Model↗
NASA NTRS1999

Autonomous Formation Flying from Ground to Flight

The cost of on-orbit operations remains a significant and increasingly visible concern in the support of satellite missions. Headway has been made in automating some ground operations; however, increased mission complexity and more precise orbital constraints have compelled continuing human involvement in mission design and maneuver planning operations. AI Solutions, Inc. in cooperation with the National Aeronautics and Space Administration's (NASA) Goddard Space Flight Center (GSFC) has tackled these more complex problems through the development of AutoCon as a tool for an automated solution. NASA is using AutoCon to automate the maneuver planning for the Earth Orbiter-1 (EO-1) mission. AutoCon was developed originally as a ground system tool. The EO-1 mission will be using a scaled version of AutoCon on-board the EO-1 satellite to command orbit adjustment maneuvers. The flight version of AutoCon plans maneuvers based on formation flying algorithms developed by GSFC, JPL, and other industry partners. In its fully autonomous mode, an AutoCon planned maneuver will be executed on-board the satellite without intervention from the ground. This paper describes how AutoCon automates maneuver planning for the formation flying constraints of the EO-1 mission. AutoCon was modified in a number of ways to automate the maneuver planning on-board the satellite. This paper describes how the interface and functionality of AutoCon were modified to support the on-board system. A significant component of this modification was the implementation of a data smoother, based on a Kalman filter, that ensures that the spacecraft states estimated by an on-board GPS receiver are as accurate as possible for maneuver planning. This paper also presents the methodology use to scale the AutoCon functionality to fit and execute on the flight hardware. This paper also presents the modes built that allow the incremental phasing in of autonomy. New technologies for autonomous operations are usually received with significant, and probably appropriate trepidation. A number of safeguards have been designed in both AutoCon and the interfacing systems to alleviate the potential of mission-impacting anomalies from the on-board autonomous system. This paper describes the error checking, input data integrity validation and limits set on maneuvers in AutoCon and the on-board system.

Chapman, Keith B.↗
NASA NTRS2008

Constellation Program Life-cycle Cost Analysis Model (LCAM)

The Constellation Program (CxP) is NASA's effort to replace the Space Shuttle, return humans to the moon, and prepare for a human mission to Mars. The major elements of the Constellation Lunar sortie design reference mission architecture are shown. Unlike the Apollo Program of the 1960's, affordability is a major concern of United States policy makers and NASA management. To measure Constellation affordability, a total ownership cost life-cycle parametric cost estimating capability is required. This capability is being developed by the Constellation Systems Engineering and Integration (SE&I) Directorate, and is called the Lifecycle Cost Analysis Model (LCAM). The requirements for LCAM are based on the need to have a parametric estimating capability in order to do top-level program analysis, evaluate design alternatives, and explore options for future systems. By estimating the total cost of ownership within the context of the planned Constellation budget, LCAM can provide Program and NASA management with the cost data necessary to identify the most affordable alternatives. LCAM is also a key component of the Integrated Program Model (IPM), an SE&I developed capability that combines parametric sizing tools with cost, schedule, and risk models to perform program analysis. LCAM is used in the generation of cost estimates for system level trades and analyses. It draws upon the legacy of previous architecture level cost models, such as the Exploration Systems Mission Directorate (ESMD) Architecture Cost Model (ARCOM) developed for Simulation Based Acquisition (SBA), and ATLAS. LCAM is used to support requirements and design trade studies by calculating changes in cost relative to a baseline option cost. Estimated costs are generally low fidelity to accommodate available input data and available cost estimating relationships (CERs). LCAM is capable of interfacing with the Integrated Program Model to provide the cost estimating capability for that suite of tools.

Prince, Andy↗
NASA NTRS1999

Autonomous Formation Flying from the Ground to Flight

The cost of on-orbit operations remains a significant and increasingly visible concern in the support of satellite missions. Headway has been made in automating some ground operations; however, increased mission complexity and more precise orbital constraints have compelled continuing human involvement in mission design and maneuver planning operations. AI Solutions, Inc. in cooperation with the National Aeronautics and Space Administration's (NASA) Goddard Space Flight Center (GSFC) has tackled these more complex problems through the development of AutoCon(TM) as a tool for an automated solution. NASA is using AutoCon(TM) to automate the maneuver planning for the Earth Orbiter-1 (EO-1) mission. AutoCon(TM) was developed originally as a ground system tool. The EO-1 mission will be using a scaled version of AutoCon(TM) on-board the EO-1 satellite to command orbit adjustment maneuvers. The flight version of AutoCon(TM) plans maneuvers based on formation flying algorithms developed by GSFC, JPL, and other industry partners. In its fully autonomous mode, an AutoCon(TM) planned maneuver will be executed on-board the satellite without intervention from the ground. This paper describes how AutoCon(TM) automates maneuver planning for the formation flying constraints of the EO-1 mission. AutoCon(TM) was modified in a number of ways to automate the maneuver planning on-board the satellite. This paper describes how the interface and functionality of AutoCon(TM) were modified to support the on-board system. A significant component of this modification was the implementation of a data smoother, based on a Kalman filter, that ensures that the spacecraft states estimated by an on-board GPS receiver are as accurate as possible for maneuver planning. This paper also presents the methodology used to scale the AutoCon(TM) functionality to fit and execute on the flight hardware. This paper also presents the modes built into the system that allow the incremental phasing in of autonomy. New technologies for autonomous operations are usually received with significant, and probably appropriate, trepidation. A number of safeguards have been designed in both AutoCon(TM) and the interfacing systems to alleviate the potential of mission-impacting anomalies from the on-board autonomous system. This paper describes the error checking, input data integrity validation, and limits set on maneuvers in AutoCon(TM) and the on-board system.

Chapman, Keith B.↗
NASA NTRSDate not supplied

A Climate and History Case Study of 18th- and 19th-Century Multidecadal Droughts in East Africa Using a new Tree-Ring Drought Atlas

Historians and paleoclimatologists have both identified the decades spanning the late-18th and early-19th centuries in many East African regions as a period of prolonged and severe drought. A challenge that emerges from both the historical evidence and the paleolimnological data that have been primarily used to characterize this drought period, however, concerns the dating of events and the characterization of their spatial character; both oral traditions and lake-core proxies cannot typically offer hydroclimate estimates with seasonal or annual resolution, nor can they provide gridded reconstructions on the order of 1° latitude and longitude. The new East African Drought Atlas (EADA) incorporates far-field dendroclimatic records and several local East African tree-ring chronologies to provide estimates of the self-calibrating Palmer Drought Severity Index (scPDSI) on a 0.5° latitude-longitude grid. We present the Point-by-Point Regression technique that was used to create the EADA, the rationale for the employed input data network, and the calibration and validation skill of the derived hydroclimatic field reconstruction. We use the EADA to characterize the timing of two decadal-scale droughts, centered over the Uganda and Kenya regions, which occurred in the late 18th century and early in the 19th century and were separated by a shorter, but pronounced wet period. We characterize the spatial patterns of the associated events and the dynamical causes that that the patterns imply. The reconstructed droughts are also compared to historical and paleolimnological data to evaluate the robustness of the reconstruction and the degree of agreement across the different sources of information.

Droughts↗
NASA NTRSDate not supplied

A Climate and History Case Study of 18th- and 19th-Century Multidecadal Droughts in East Africa Using a new Tree-Ring Drought Atlas

Historians and paleoclimatologists have both identified the decades spanning the late-18th and early-19th centuries in many East African regions as a period of prolonged and severe drought. A challenge that emerges from both the historical evidence and the paleolimnological data that have been primarily used to characterize this drought period, however, concerns the dating of events and the characterization of their spatial character; both oral traditions and lake-core proxies cannot typically offer hydroclimate estimates with seasonal or annual resolution, nor can they provide gridded reconstructions on the order of 1° latitude and longitude. The new East African Drought Atlas (EADA) incorporates far-field dendroclimatic records and several local East African tree-ring chronologies to provide estimates of the self-calibrating Palmer Drought Severity Index (scPDSI) on a 0.5° latitude-longitude grid. We present the Point-by-Point Regression technique that was used to create the EADA, the rationale for the employed input data network, and the calibration and validation skill of the derived hydroclimatic field reconstruction. We use the EADA to characterize the timing of two decadal-scale droughts, centered over the Uganda and Kenya regions, which occurred in the late 18th century and early in the 19th century and were separated by a shorter, but pronounced wet period. We characterize the spatial patterns of the associated events and the dynamical causes that that the patterns imply. The reconstructed droughts are also compared to historical and paleolimnological data to evaluate the robustness of the reconstruction and the degree of agreement across the different sources of information.

Droughts↗
NASA NTRS2010

Land Surface Phenology from MODIS: Characterization of the Collection 5 Global Land Cover Dynamics Product

Information related to land surface phenology is important for a variety of applications. For example, phenology is widely used as a diagnostic of ecosystem response to global change. In addition, phenology influences seasonal scale fluxes of water, energy, and carbon between the land surface and atmosphere. Increasingly, the importance of phenology for studies of habitat and biodiversity is also being recognized. While many data sets related to plant phenology have been collected at specific sites or in networks focused on individual plants or plant species, remote sensing provides the only way to observe and monitor phenology over large scales and at regular intervals. The MODIS Global Land Cover Dynamics Product was developed to support investigations that require regional to global scale information related to spatiotemporal dynamics in land surface phenology. Here we describe the Collection 5 version of this product, which represents a substantial refinement relative to the Collection 4 product. This new version provides information related to land surface phenology at higher spatial resolution than Collection 4 (500-m vs. 1-km), and is based on 8-day instead of 16-day input data. The paper presents a brief overview of the algorithm, followed by an assessment of the product. To this end, we present (1) a comparison of results from Collection 5 versus Collection 4 for selected MODIS tiles that span a range of climate and ecological conditions, (2) a characterization of interannual variation in Collections 4 and 5 data for North America from 2001 to 2006, and (3) a comparison of Collection 5 results against ground observations for two forest sites in the northeastern United States. Results show that the Collection 5 product is qualitatively similar to Collection 4. However, Collection 5 has fewer missing values outside of regions with persistent cloud cover and atmospheric aerosols. Interannual variability in Collection 5 is consistent with expected ranges of variance suggesting that the algorithm is reliable and robust, except in the tropics where some systematic differences are observed. Finally, comparisons with ground data suggest that the algorithm is performing well, but that end of season metrics associated with vegetation senescence and dormancy have higher uncertainties than start of season metrics.

Land cover dynamics↗
NASA NTRS2019

Assimilating microwave cloudy observations into NASA GEOS model using a novel Bayesian Monte Carlo technique

Despite the importance of clouds and their influence on atmospheric water and energy balance, Numerical Weather Prediction (NWP) centers systematically exclude cloud information from the assimilation process and only assimilate clear-sky radiances (Janiskov´a et al. 2012). In order to ensure that only clear sky radiances are assimilated, strict cloud detection thresholds are applied before radiances are fed into data assimilation (DA) systems. This process not only excludes a large portion of satellite radiances, but causes loss of information in the regions that are of high interest to meteorologists and are most challenging for weather forecasts (Errico et al. 2007; Haddad et al. 2015). Although, in recent years there has been great advances in the operational weather forecasting, the prediction of tropical cyclones (TC), especially the intensity of TCs, remains challenging. According to Aksoy et al. (2013), in addition to the model deficiencies, another important factor that contributes to this challenge includes lack of observations in the peripheral environment (rain- bands) of TCs mainly because of the selective assimilation of existing observations. Satellite observations provide more than 90 % of the input data for the initialization of NWP models but more than 75 % of satellite observations are discarded due to the cloud contamination as well as land, snow, and ice emissivity issues (Bauer et al. 2010).

Rainband↗
NASA NTRS2011

Structure of the Upper Troposphere-Lower Stratosphere (UTLS) in GEOS-5

This study examines the structure of the upper troposphere and lower stratosphere in the GEOS-5 data assimilation system. Near-real time analyses, with a horizontal resolution of one-half or one quarter degree and a vertical resolution of about 1km in the tropopause region are examined with an emphasis on spatial structures at and around the tropopause. The contributions of in-situ observations of temperature and microwave and infrared radiances to the analyses are discussed, with some focus on the interplay between these types of observations. For a historical analysis (Merra) performed with GEOS-5, the impacts of changing observations on the assimilation system are examined in some detail - this documents some aspects of the time dependence of analysis that must be taken into account in the isolation of true geophysical trends. Finally, some sensitivities of the ozone analyses to input data and correlated errors between temperature and ozone are discussed.

Pawson, Steven↗
NASA NTRS1996

User's Guide for MSAP2D: A Program for Unsteady Aerodynamic and Aeroelastic (Flutter and Forced Response) Analysis of Multistage Compressors and Turbines

This guide describes the input data required for using MSAP2D (Multi Stage Aeroelastic analysis Program - Two Dimensional) computer code. MSAP2D can be used for steady, unsteady aerodynamic, and aeroelastic (flutter and forced response) analysis of bladed disks arranged in multiple blade rows such as those found in compressors, turbines, counter rotating propellers or propfans. The code can also be run for single blade row. MSAP2D code is an extension of the original NPHASE code for multiblade row aerodynamic and aeroelastic analysis. Euler equations are used to obtain aerodynamic forces. The structural dynamic equations are written for a rigid typical section undergoing pitching (torsion) and plunging (bending) motion. The aeroelastic equations are solved in time domain. For single blade row analysis, frequency domain analysis is also provided to obtain unsteady aerodynamic coefficients required in an eigen analysis for flutter. In this manual, sample input and output are provided for a single blade row example, two blade row example with equal and unequal number of blades in the blade rows.

Reddy, T. S. R.↗
NASA NTRS1991

Lunar regolith densification

Core tube samples of the lunar regolith obtained during the Apollo missions showed a rapid increase in the density of the regolith with depth. Various hypotheses have been proposed for the possible cause of this phenomenon, including the densification of the loose regolith material by repeated shaking from the seismic tremors which have been found to occur at regular monthly intervals when the moon and earth are closest to one another. A test bed was designed to study regolith densification. This test bed uses Minnesota Lunar Simulant (MLS) to conduct shaking experiments in the geotechnical centrifuge with an inflight shake table system. By reproducing realistic in-situ regolith properties, the experiment also serves to test penetrator concepts. The shake table system was designed and used for simulation experiments to study effects of earthquakes on terrestrial soil structures. It is mounted on a 15 g-ton geotechnical centrifuge in which the self-weight induced stresses are replicated by testing an n-th scale model in a gravity field which is n times larger than Earth's gravity. A similar concept applies when dealing with lunar prototypes, where the gravity ratio required for proper simulation of lunar gravity effects is that between the centrifugal acceleration and the lunar gravity. Records of lunar seismic tremors, or moonquakes, were obtained. While these records are being prepared for use as the input data to drive the shake table system, records from the El Centro earthquake of 1940 are being used to perform preliminary tests, using a soil container which was previously used for earthquake studies. This container has a laminar construction, with the layers free to slide on each other, so that the soil motion during the simulated earthquake will not be constrained by the otherwise rigid boundaries. The soil model is prepared by pluviating the MLS from a hopper into the laminar container to a depth of 6 in. The container is mounted on the shake table and the centrifuge is operated to generate an acceleration of 10 times Earth's gravity or 60 times the lunar gravity, thus simulating a lunar regolith thickness of 30 ft. The shake table is then operated using the scaled 'moonquake' as the input motion. One or more model moonquakes are used in each experiment, after which the soil is analyzed for its density profile with depth. This is accomplished by removing from the soil bed a column of soil contained within a thin rubber sleeve which has been previously embedded vertically in the soil during pluviation. This column of soil is transferred to a gamma ray device, in which the gamma ray transmission transversely through the soil is measured and compared with standard calibration samples. In this manner, the density profile can be determined. Preliminary results to date are encouraging, and the Center plans to study the effects of duration of shaking, intensity of the shaking motion, and the frequency of the motion.

Ko, Hon-Yim↗
NASA NTRS2021

Quantifying Uncertainties in Nighttime Light Retrievals From Suomi-NPP and NOAA-20 VIIRS Day/Night Band Data

Satellite observations of nighttime lights (NTL) from Suomi-NPP and NOAA-20 VIIRS Day/Night Band data have been widely used to estimate human activities. Long-term changes such as urban development and abrupt short-term changes such as power outages have been monitored from temporal NTL acquired by satellites. While high temporal NTL variation has been found across NTL data of varying temporal scale (e.g., daily, monthly, and annual composites), the sources of measurement error and uncertainty are poorly understood. This paper quantifies the sources of VIIRS-derived NTL uncertainty due to view-illumination geometry, surface Bidirectional Reflectance Distribution Function (BRDF)/albedo, and the effects of snow cover, lunar irradiance, aerosol loading, cloud mask, vegetation, geometry, and ephemeral artifacts (e.g., the Aurora Borealis). Based on this current assessment of NASA Black Marble retrievals (VNP46, Collection V001), we found that angular and atmospheric effects dominate retrieval uncertainty. Errors introduced by upstream data inputs (e.g., a coarser nighttime snow cover flag and misclassification errors in the existing VIIRS nighttime cloud mask) were also found to impact retrieval quality. Despite these challenges, a consistent daily NTL time series record can be routinely generated from top-of-atmosphere VNP46 radiances. Key recommendations include: (1) the use of lunar-BRDF adjusted and atmospherically corrected NTL (i.e., as identified as high-quality retrievals in the VNP46 QA fields), (2) development and improvement to the VIIRS snow cover and cloud masks algorithms to accurately reflect NTL retrieval conditions, (3) characterizing seasonal variations in NTL due to vegetation and snow, (4) reducing geometric effects due to the spatial mismatch of gridded pixel and observation footprint, (5) employing angularly-consistent NTL observations from multiple VIIRS instruments (i.e., Suomi-NPP and NOAA-20) to reduce pixel-based uncertainties and address persistent data gaps, and (6) being mindful of surface-reflected radiance from aurora events at mid-to-high latitudes.

Zhuosen Wang↗
NASA NTRS2006

Probabilistic Classification Using Elemental Abundance Distributions and Lossless Image Compression in Apollo 17 Lunar Dust Samples from Mare Serenitatis

We have previously outlined a strategy for the detection of fossils [Storrie-Lombardi and Hoover, 2004] and extant microbial life [Storrie-Lombaudi and Hoover, 20051 during robotic missions to Mars using co-registered structural and chemical signatures. Data inputs included image lossless compression indices to estimate relative textural complexity and elemental abundance distributions. Two exploratory classification algorithms (principal component analysis and hierarchical cluster analysis) provide an initial tentative classification of all targets. Nonlinear stochastic neural networks are then trained to produce a Bayesian estimate of algorithm classification accuracy. The strategy previously has been successful in distinguishing regions of biotic and abiotic alteration of basalt glass from unaltered samples. [Storrie-Lombardi and Fisk, 2004; Storrie-Lombardi and Fisk, 2004] Such investigations of abiotic versus biotic alteration of terrestrial mineralogy on Earth are compromised by .the difficulty finding mineralogy completely unaffected by the ubiquitous presence of microbial life on the planet. The renewed interest in lunar exploration offers an opportunity to investigate geological materials that may exhibit signs of aqueous alteration, but are highly unlikely to contain contaminating biological weathering signatures. We here present an extension of our earlier data set to include lunar dust samples obtained during the Apollo 17 mission. Apollo 17 landed in the Taurus-Littrow Valley in Mare Serenitatis. Most of the rock samples from this region of the lunar highlands are basalts comprised primarily of plagioclase and pyroxene and selected examples of orange and black volcanic glass. SEM images and elemental abundances (C6, N7, O8, Na11, Mg12, Al13, Si14, P15, S16, Cll7, K19, Ca20, Fe26) for a series of targets in the lunar dust samples are compared to the extant cyanobacteria, fossil trilobites, Orgueil meteorite, and terrestrial basalt targets previously discussed. The data set provides a first step in producing a quantitative probabilistic methodology for geobiological analysis of returned lunar samples or in situ exploration.

Storrie-Lombardi, Michael C.↗
NASA NTRSDate not supplied

Lidar and UAS Measurements of Winds for the NASA Advanced Air Mobility Mission

The envisioned future of Advanced Air Mobility involves low-altitude operation of a new class of air vehicles. The low altitudes of the flight paths would have these vehicles spending most of their operation in conditions where unpredictable wind and turbulence effects may occur. Wind measurements will hence be critical to ensure safe and efficient operations for AAM. Such wind measurement could be used as a monitoring system for warning of hazardous wind events, as data input to forecasting models, or as a research tool to understand wind effects in complex environments. To meet this need NASA is evaluating wind sensing technologies with a capability to probe the atmospheric boundary layer. Doppler lidar is a leading candidate ground-based sensor, as shown by the decades-long history of being an effective tool for many wind studies. However, there is a need to re-assess the Doppler wind lidars for the AAM application which involves evaluating wind effects as vehicles operate in and out of vertiports, notably regarding spatial resolution. Meeting the needs for spatial resolution may involve the use of dual-Doppler techniques, rather than just single Doppler lidar. The study was furthermore motivated by looking toward the future of AAM, in which the air vehicles involved can also provide wind measurements. Airborne wind measurements, obtained directly from vehicle-mounted anemometers or indirectly from vehicle navigation data, offer a means to compare remotely sensed wind lidar with in-situ measurements. The following sections report on results of wind measurements obtained using lidar and the small uninhabited aircraft systems (sUAS’s) operating in the same volume of air.

Adam Medina↗
NASA NTRS2017

Early Season Large-Area Winter Crop Mapping Using MODIS NDVI Data, Growing Degree Days Information and a Gaussian Mixture Model

Knowledge on geographical location and distribution of crops at global, national and regional scales is an extremely valuable source of information applications. Traditional approaches to crop mapping using remote sensing data rely heavily on reference or ground truth data in order to train/calibrate classification models. As a rule, such models are only applicable to a single vegetation season and should be recalibrated to be applicable for other seasons. This paper addresses the problem of early season large-area winter crop mapping using Moderate Resolution Imaging Spectroradiometer (MODIS) derived Normalized Difference Vegetation Index (NDVI) time-series and growing degree days (GDD) information derived from the Modern-Era Retrospective analysis for Research and Applications (MERRA-2) product. The model is based on the assumption that winter crops have developed biomass during early spring while other crops (spring and summer) have no biomass. As winter crop development is temporally and spatially non-uniform due to the presence of different agro-climatic zones, we use GDD to account for such discrepancies. A Gaussian mixture model (GMM) is applied to discriminate winter crops from other crops (spring and summer). The proposed method has the following advantages: low input data requirements, robustness, applicability to global scale application and can provide winter crop maps 1.5-2 months before harvest. The model is applied to two study regions, the State of Kansas in the US and Ukraine, and for multiple seasons (2001-2014). Validation using the US Department of Agriculture (USDA) Crop Data Layer (CDL) for Kansas and ground measurements for Ukraine shows that accuracies of greater than 90% can be achieved in mapping winter crops 1.5-2 months before harvest. Results also show good correspondence to official statistics with average coefficients of determination R(exp. 2) greater than 0.85.

mixture model↗
NASA NTRS2015

Global Soil Moisture from the Aquarius/SAC-D Satellite: Description and Initial Assessment

Aquarius satellite observations over land offer a new resource for measuring soil moisture from space. Although Aquarius was designed for ocean salinity mapping, our objective in this investigation is to exploit the large amount of land observations that Aquarius acquires and extend the mission scope to include the retrieval of surface soil moisture. The soil moisture retrieval algorithm development focused on using only the radiometer data because of the extensive heritage of passive microwave retrieval of soil moisture. The single channel algorithm (SCA) was implemented using the Aquarius observations to estimate surface soil moisture. Aquarius radiometer observations from three beams (after bias/gain modification) along with the National Centers for Environmental Prediction model forecast surface temperatures were then used to retrieve soil moisture. Ancillary data inputs required for using the SCA are vegetation water content, land surface temperature, and several soil and vegetation parameters based on land cover classes. The resulting global spatial patterns of soil moisture were consistent with the precipitation climatology and with soil moisture from other satellite missions (Advanced Microwave Scanning Radiometer for the Earth Observing System and Soil Moisture Ocean Salinity). Initial assessments were performed using in situ observations from the U.S. Department of Agriculture Little Washita and Little River watershed soil moisture networks. Results showed good performance by the algorithm for these land surface conditions for the period of August 2011-June 2013 (rmse = 0.031 m(exp 3)/m(exp 3), Bias = −0.007 m(exp 3)/m(exp 3), and R = 0.855). This radiometer-only soil moisture product will serve as a baseline for continuing research on both active and combined passive-active soil moisture algorithms. The products are routinely available through the National Aeronautics and Space Administration data archive at the National Snow and Ice Data Center.

Soil MOisture↗
NASA NTRS2005

Interannual Variability of Tropical Ocean Evaporation: A Comparison of Microwave Satellite and Assimilation Results

Remote sensing methodologies for turbulent heat fluxes over oceans depend on driving bulk formulations of fluxes with measured surface winds and estimated near surface thermodynamics from microwave sensors of the Special Sensor Microwave Imager (SSM/I) heritage. We will review recent work with a number of SSM/I-based algorithms and investigate the ability of current data sets to document global, tropical ocean-averaged evaporation changes in association with El Nino and La Nina SST changes. We show that in addition to interannual signals, latent heat flux increases over the period since late 1987 range from approx. .1 to .6 mm/ day are present; these represent trends 2 to 3 times larger than the NCEP Reanalysis. Since atmospheric storage cannot account for the difference, and since compensating evapotranspiration changes over land are highly unlikely to be this large, these evaporation estimates cannot be reconciled with ocean precipitation records such as those produced by the Global Precipitation Climatology Project, GPCP. The reasons for the disagreement include less than adequate intercalibration between SSM/I sensors providing winds and water vapor for driving the algorithms, biases due to the assumption that column integrated water vapor mirrors near surface water vapor variations, and other factors as well. The reanalyses have their own problems with spin-up during assimilation, lack of constraining input data at the ocean surface, and amplitude of synoptic transients.

Robertson, Franklin R.↗