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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.

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NASA NTRS2017

Assessment of Version 4 of the SMAP Passive Soil Moisture Standard Product

NASAs Soil Moisture Active Passive (SMAP) mission launched on January 31, 2015 into a sun-synchronous 6 am6 pm orbit with an objective to produce global mapping of high-resolution soil moisture and freeze-thaw state every 2-3 days. The SMAP radiometer began acquiring routine science data on March 31, 2015 and continues to operate nominally. SMAPs radiometer-derived standard soil moisture product (L2SMP) provides soil moisture estimates posted on a 36-km fixed Earth grid using brightness temperature observations and ancillary data. A beta quality version of L2SMP was released to the public in October, 2015, Version 3 validated L2SMP soil moisture data were released in May, 2016, and Version 4 L2SMP data were released in December, 2016. Version 4 data are processed using the same soil moisture retrieval algorithms as previous versions, but now include retrieved soil moisture from both the 6 am descending orbits and the 6 pm ascending orbits. Validation of 19 months of the standard L2SMP product was done for both AM and PM retrievals using in situ measurements from global core calval sites. Accuracy of the soil moisture retrievals averaged over the core sites showed that SMAP accuracy requirements are being met.

SMAP↗
NASA NTRS2017

AMSR2 Soil Moisture Product Validation

The Advanced Microwave Scanning Radiometer 2 (AMSR2) is part of the Global Change Observation Mission-Water (GCOM-W) mission. AMSR2 fills the void left by the loss of the Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E) after almost 10 years. Both missions provide brightness temperature observations that are used to retrieve soil moisture. Merging AMSR-E and AMSR2 will help build a consistent long-term dataset. Before tackling the integration of AMSR-E and AMSR2 it is necessary to conduct a thorough validation and assessment of the AMSR2 soil moisture products. This study focuses on validation of the AMSR2 soil moisture products by comparison with in situ reference data from a set of core validation sites. Three products that rely on different algorithms were evaluated; the JAXA Soil Moisture Algorithm (JAXA), the Land Parameter Retrieval Model (LPRM), and the Single Channel Algorithm (SCA). Results indicate that overall the SCA has the best performance based upon the metrics considered.

microwave↗
NASA NTRS2017

Strategies for Validating Satellite Soil Moisture Products Using in Situ Networks: Lessons from the USDA-ARS Watersheds

There are a variety of soil moisture station designs and networks deployed throughout the world, each with varying applications and uses. The purpose of satellite validation of soil moisture products, a dense network of soil moisture networks are required with soil moisture sensors at the near surface (approx. 5 cm or less) to correspond to the satellite footprints and signals. The USDA- Agricultural Research Service operates a collection of soil moisture networks as a part of the Long Term Agro-ecosystem Research (LTAR) network to this end. These networks have been used to validate products from AMSR-E, SMOS, Aquarius, and SMAP. A review of these results and a synopsis of successful scaling strategies are discussed.

soil moisture↗
NASA NTRS2018

An Assessment of the Differences Between Spatial Resolution and Grid Size for the SMAP Enhanced Soil Moisture Product over Homogeneous Sites

Satellite-based passive microwave remote sensing typically involves a scanning antenna that makes measurements at irregularly spaced locations. These locations can change on a day to day basis. Soil moisture products derived from satellite-based passive microwave remote sensing are usually resampled to a fixed Earth grid that facilitates their use in applications. In many cases the grid size is finer than the actual spatial resolution of the observation, and often this difference is not well understood by the user. Here, this issue was examined for the Soil Moisture Active Passive (SMAP) enhanced version of the passive-based soil moisture product, which has a grid size of 9-km and a nominal spatial resolution of 33-km. In situ observations from core validation sites were used to compute comparison metrics. For sites that satisfied the established reliability and scaling criteria, the impact of validating the 9-km grid product with in situ data collected over a 9-km versus a 33-km domain was very small for the sites studied (0.039 cu. m/cu. m unbiased root mean square difference for the 9-km case versus 0.037 cu. m/cu. m for the 33-km case). This result does not mean that the resolution of the product is 9-km but that for the conditions studied here the soil moisture estimated from in situ observations over 9-km is a close approximation of the soil moisture estimated from in situ observations over the 33-km resolution. The implication is that using the enhanced SMAP product at its grid resolution of 9-km should not introduce large errors in most applications.

Soil moisture↗
NASA NTRS2018

The SMAP Mission Combined Active-Passive Soil Moisture Product at 9 Km and 3 Km Spatial Resolutions

The NASA Soil Moisture Active Passive (SMAP) mission was launched on January 31st, 2015. The spacecraft was to provide high-resolution (3 km and 9 km) global soil moisture estimates at regular intervals by combining for the first time L-band radiometer and radar observations. On July 7th, 2015, a component of the SMAP radar failed and the radar ceased operation. However, before this occurred the mission was able to collect and process ~2.5 months of the SMAP high-resolution active-passive soil moisture data (L2SMAP) that coincided with the Northern Hemisphere's vegetation green-up and crop growth season. In this study, we evaluate the SMAP high-resolution soil moisture product derived from several alternative algorithms against in situ data from core calibration and validation sites (CVS), and sparse networks. The baseline algorithm had the best comparison statistics against the CVS and sparse networks. The overall unbiased root-mean-square-difference is close to the 0.04 cu. m/cu. m the SMAP mission requirement. A 3 km spatial resolution soil moisture product was also examined. This product had an unbiased root-mean-square-difference of ~0.053 cu. m/cu. m. The SMAP L2SMAP product for ~2.5 months is now validated for use in geophysical applications and research and available to the public through the NASA Distributed Active Archive Center (DAAC) at the National Snow and Ice Data Center (NSIDC). The L2SMAP product is packaged with the geo-coordinates, acquisition times, and all requisite ancillary information. Although limited in duration, SMAP has clearly demonstrated the potential of using a combined L-band radar-radiometer for proving high spatial resolution and accurate global soil moisture.

high resolution soil moisture↗
NASA NTRS2017

Development and Assessment of the SMAP Enhanced Passive Soil Moisture Product

Launched in January 2015, the National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) observatory was designed to provide frequent global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using a radar and a radiometer operating at L-band frequencies. Despite a hardware mishap that rendered the radar inoperable shortly after launch, the radiometer continues to operate nominally, returning more than two years of science data that have helped to improve existing hydrological applications and foster new ones.Beginning in late 2016 the SMAP project launched a suite of new data products with the objective of recovering some high-resolution observation capability loss resulting from the radar malfunction. Among these new data products are the SMAP Enhanced Passive Soil Moisture Product that was released in December 2016, followed by the SMAPSentinel-1 Active-Passive Soil Moisture Product in April 2017.This article covers the development and assessment of the SMAP Level 2 Enhanced Passive Soil Moisture Product (L2_SM_P_E). The product distinguishes itself from the current SMAP Level 2 Passive Soil Moisture Product (L2_SM_P) in that the soil moisture retrieval is posted on a 9 km grid instead of a 36 km grid. This is made possible by first applying the Backus-Gilbert optimal interpolation technique to the antenna temperature (TA) data in the original SMAP Level 1B Brightness Temperature Product to take advantage of the overlapped radiometer footprints on orbit. The resulting interpolated TA data then go through various correctioncalibration procedures to become the SMAP Level 1C Enhanced Brightness Temperature Product (L1C_TB_E). The L1C_TB_E product, posted on a 9 km grid, is then used as the primary input to the current operational SMAP baseline soil moisture retrieval algorithm to produce L2_SM_P_E as the final output. Images of the new product reveal enhanced visual features that are not apparent in the standard product. Based on in situ data from core validation sites and sparse networks representing different seasons and biomes all over the world, comparisons between L2_SM_P_E and in situ data were performed for the duration of April 1, 2015 October 30, 2016. It was found that the performance of the enhanced 9 km L2_SM_P_E is equivalent to that of the standard 36 km L2_SM_P, attaining a retrieval uncertainty below 0.040 m(exp 3)/m(exp 3) unbiased root-mean-square error (ubRMSE) and a correlation coefficient above 0.800. This assessment also affirmed that the Single Channel Algorithm using the V-polarized TB channel (SCA-V) delivered the best retrieval performance among the various algorithms implemented for L2_SM_P_E, a result similar to a previous assessment for L2_SM_P.

Enhanced↗
NASA NTRS2018

Follow-up Imaging of Disk Candidates from the Disk Detective Citizen Science Project: New Discoveries and False Positives in WISE Circumstellar Disk Surveys

The Disk Detective citizen science project aims to find new stars with excess 22 m emission from circumstellar dust in the All WISE data release from the Wide-field Infrared Survey Explorer. We evaluated 261 Disk Detective objects of interest with imaging with the Robo-AO adaptive optics instrument on the 1.5 m telescope at Palomar Observatory and with RetroCam on the 2.5 m du Pont Telescope at Las Campanas Observatory to search for background objects at 0 15–12 separations from each target. Our analysis of these data leads us to reject 7% of targets. Combining this result with statistics from our online image classification efforts implies that at most7.9%±0.2% of All WISE-selected infrared excesses are good disk candidates. Applying our false-positive rates to other surveys, we find that the infrared excess searches of McDonald et al. and Marton et al. all have false-positiverates >70%. Moreover, we find that all 13 disk candidates in Theissen & West with W4 signal-to-noise ratio >3are false positives. We present 244 disk candidates that have survived vetting by follow-up imaging. Of these,213 are newly identified disk systems. Twelve of these are candidate members of comoving pairs based on Gaia astrometry, supporting the hypothesis that warm dust is associated with binary systems. We also note the discovery of 22 m excess around two known members of the Scorpius–Centaurus association, and we identifyknown disk host WISEA J164540.79-310226.6 as a likely Sco-Cen member. Thirty of these disk candidates arecloser than 125 pc (including 26 debris disks), making them good targets for both direct-imaging exoplanetsearches.

Wide-field Infrared Survey Explorer↗
NASA NTRS2019

Seasonal Dependence of SMAP Radiometer-Based Soil Moisture Performance as Observed over Core Validation Sites

The NASA SMAP (Soil Moisture Active Passive) mission provides a global coverage of soil moisture measurements based on its L-band microwave radiometer every 2-3 days at about 40 km resolution. The soil moisture retrieval algorithms model the brightness temperature as a function of soil moisture, surface conditions and vegetation. External data sources inform the algorithms about the surface conditions and vegetation, which enable the retrieval of soil moisture. The inversion process contains uncertainties related to radiometer measurements, forward model assumptions and ancillary data sources. This study focuses on the uncertainties that depend on the seasonal evolution of the surface conditions and vegetation. This study compares the SMAP and core validation site (CVS) soil moisture values over a period of three years to extract the evolution of performance metrics over time. The analysis showed that most CVS that include managed agriculture exhibit significant time-dependent seasonal bias. This bias was linked to seasonal temperature cycle, which is a proxy to several features that can cause seasonally dependent errors in the SMAP product.

core validation site↗
NASA NTRS2019

Version 4 of the SMAP Level-4 Soil Moisture Algorithm and Data Product

The NASA Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides global, 3-hourly, 9-km resolution estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture with a mean latency of ~2.5 days. The underlying L4_SM algorithm assimilates SMAP radiometer brightness temperature (Tb) observations into the NASA Catchment land surface model using a spatially-distributed ensemble Kalman filter. Version 4 of the L4_SM modeling system includes a reduction in the upward recharge of surface soil moisture from below under non-equilibrium conditions, resulting in reduced bias and improved dynamic range of L4_SM surface soil moisture compared to earlier versions. This change and additional technical modifications to the system reduce the mean and standard deviation of the observation-minus-forecast Tb residuals and overall soil moisture analysis increments while maintaining the skill of the L4_SM soil moisture estimates versus independent in situ measurements; the average, bias-adjusted RMSE in Version 4 is 0.039 m(exp 3) m(exp -3) for surface and 0.026 m(exp 3) m(exp -3) for root-zone soil moisture. Moreover, the coverage of assimilated SMAP observations in Version 4 is near-global owing to the use of additional satellite Tb records for algorithm calibration. L4_SM soil moisture uncertainty estimates are biased low (by 0.01-0.02 m(exp 3) m(exp -3)) against actual errors (computed versus in situ measurements). L4_SM runoff estimates, an additional product of the L4_SM algorithm, are biased low (by 35 mm year (exp -1)) against streamflow measurements. Compared to Version 3, bias in Version 4 is reduced by 46% for surface soil moisture uncertainty estimates and by 33% for runoff estimates.

RMSE↗
NASA NTRS2020

The High-Energy Emission from HD 93129A Near Periastron

We conducted an observational campaign towards one of the most massive and luminous colliding wind binaries in the Galaxy, HD 93129A, close to its periastron passage in 2018. During this time the source was predicted to be in its maximum of high-energy emission. Here we present our data analysis from the X-ray satellites Chandra and NuSTAR and the γ-ray satellite AGILE. High-energy emission coincident with HD 93129A was detected in the X-ray band up to 18 keV, whereas in the γ-ray band only upper limits were obtained. We interpret the derived fluxes using a non-thermal radiative model for the wind-collision region. We establish a conservative upper limit for the fraction of the wind kinetic power that is converted into relativistic electron acceleration, f(NT,e) < 0.02. In addition, we set a lower limit for the magnetic field in the wind-collision region as BWCR > 0.3 G. We also argue a putative interpretation of the emission from which we estimate f(NT,e) ≈ 0.006 and B(WCR) ≈ 0.5 G. We conclude that multi-wavelength, dedicated observing campaigns during carefully selected epochs are a powerful tool for characterising the relativistic particle content and magnetic field intensity in colliding wind binaries.

S del Palacio↗
NASA NTRS2021

Investigation of Ionic Liquids Isolated Iron for Ductile Iron Castings

As research continues for missions beyond low-Earth orbit, in-situ resource utilization (ISRU) methods are critical. For Lunar and Martian colonization, the ability to manufacture mechanical and structural components with local resources is essential. Ionic liquids (IL) are being studied at NASA Marshall Space Flight Center (MSFC) to harvest elemental metals from meteorites and regolith oxides. In this investigation, the viability of casting ductile iron using ionic liquids sourced iron and nickel was explored given ductile iron’s range of applications and performance as an as-cast alloy. Ingots were produced using commercial elements to simulate the use of IL iron with carbon sourced from the by-products of a life support system currently tested at MSFC. Samples were cast and compared to commercial ductile iron with phase transformation diagrams,microstructures, and hardness. Results showed ionic liquids sourced elements are a viable source of elemental alloying materials for a range of ductile iron alloys.

Ionic Liquids↗
NASA NTRS2020

Assessing the Impact of Soil Layer Depth Specification on the Observability of Modeled Soil Moisture and Brightness Temperature

The utility of hydrologic land surface models (LSMs) can be enhanced by using information from observational platforms, but mismatches between the two are common.This study assesses the degree to which model agreement with observations (observability) is affected by two mechanisms in particular: 1) physical incongruities between the support volumes being characterized and 2) inadequateor inconsistent parameterizations of physical processes. The Noah and Noah-MP LSMs by default characterize surface soil moisture (SSM) in the top 10 cm of the soil column. This depth may be reasonable when comparing against soil moisture from in situ probes centered at 5 cm,but it is notably different from the 5 cm (or less) sensing depth of NASA’s Soil Moisture Active Passive (SMAP) satellite mission. These depth inconsistencies are examined by using thinner model layers in the Noah and Noah-MP LSMs and comparing resultant simulations to in situ and SMAP soil moisture. In addition, a forward radiative transfer model to simulate microwave brightness temperatures (Tbs) is used to facilitate direct comparisons of LSM-based and SMAP-based L-band Tb retrievals. Observability is quantified using Kolmogorov-Smirnov distance values, calculated from empirical cumulative distribution functions of SSM and Tb time series. Experiment results depend on the particular subspace being analyzed (SSM or Tb). This study concludes that therole of increasedsoil layer discretizationon LSM observability is secondary to the influence of component parameterizations, the effects of which dominate systematic differences with observations

SMAP↗
NASA NTRS1993

Use of the Airborne Visible/Infrared Imaging Spectrometer to Calibrate the Optical Sensor on Board the Japanese Earth Resources Satellite-1

In this paper, we describe an experiment to calibrate the Optical Sensor on board the Japanese Earth Resources Satellite-1 with data acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). This experiment establishes the suitability of AVIRIS for the calibration of spaceborne sensors in the 400 to 2500 nm spectral region.

spaceborne↗
NASA NTRS1993

Inflight Calibration of AVIRIS in 1992 and 1993

In order to pursue the quantitative research objective of AVIRIS, the spectral, radiometric characteristic of the sensor must be known at the time of flight data acquisition. AVIRIS is rigorously calibrated in the laboratory. In addition, three times each year these characteristics of AVIRIS are validated through an inflight calibration experiment. Absolute radiometric calibration and signal-to-noise results are present for the inflight calibration experiment orchestrated in 1992 and 1993.

Chrien, Tom↗
NASA NTRS1995

(abstract) The 1994 TIMS Airborne Calibration Experiment: Castaic Lake, California

This summary describes the 9 March 1994 TIMS airborne calibration experiment conducted at Castaic Lake, California. TIMS was flown on the NASA/ARC C-130 with the new retractable air fence installed in the TIMS instrument bay. The purpose of this experiment was to determine is the fence would reduce the air turbulence in the TIMS instrument bay, thereby reducing the errors in calibration caused by wind-blast cooling of the blackbody reference sources internal to TIMS. Previous experiments have indicated that the wind blast effect could cause TIMS to over-estimate surface temperatures by more than 10°C. A suite of twelve flight was designed to subject the TIMS/air fence system to different wind conditions and air temperatures. The TIMS flights were supported by a ground-truth team, who measured lake surface temperatures from a boat, and a atmosphere characterization team, who launched an airsonde and measured solar irradiance with a Reagan Sun Photometer.

TIMS↗