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All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Behavioral Health and Performance Laboratory Standard Measures (BHP-SM)

The Spaceflight Standard Measures is a NASA Johnson Space Center Human Research Project (HRP) project that proposes to collect a set of core measurements, representative of many of the human spaceflight risks, from astronauts before, during and after long-duration International Space Station (ISS) missions. The term "standard measures" is defined as a set of core measurements, including physiological, biochemical, psychosocial, cognitive, and functional, that are reliable, valid, and accepted in terrestrial science, are associated with a specific and measurable outcome known to occur as a consequence of spaceflight, that will be collected in a standardized fashion from all (or most) crewmembers. While such measures might be used to define standards of health and performance or readiness for flight, the prime intent in their collection is to allow longitudinal analysis of multiple parameters in order to answer a variety of operational, occupational, and research-based questions. These questions are generally at a high level, and the approach for this project is to populate the standard measures database with the smallest set of data necessary to indicate further detailed research is required. Also included as standard measures are parameters that are not outcome-based in and of-themselves, but provide ancillary information that supports interpretation of the outcome measures, e.g., nutritional assessment, vehicle environmental parameters, crew debriefs, etc. The project's main aim is to ensure that an optimized minimal set of measures is consistently captured from all ISS crewmembers until the end of Station in order to characterize the human in space. -This allows the HRP to identify, establish, and evaluate a common set of measures for use in spaceflight and analog research to: develop baselines, systematically characterize risk likelihood and consequences, and assess effectiveness of countermeasures that work for behavioral health and performance risk factors. -By standardizing the battery of measures on all crewmembers, it will allow the HRP to evaluate countermeasures that work for one physiological system and ensure another system is not negatively affected. -These measures, named "Standard Measures," will serve as a data repository and be available to other studies under data sharing agreements.

Williams, Thomas J.↗
NASA NTRSDate not supplied

Examination of L-Band Brightness Temperature Forecasts in the SMAP Level-4 Soil Moisture Analysis

The NASA Soil Moisture Active Passive (SMAP) mission [4] has been providing L-band (1.4 GHz) passive microwave brightness temperature (Tb) observations since April 2015. By assimilating the Tb observations into the NASA Catchment land surface model [5] using a spatially distributed ensemble Kalman filter, the NASA Global Modeling and Assimilation Office generates the SMAP Level-4 Soil Moisture (L4_SM) product, which provides global, 3-hourly, 9-km resolution estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture with ~2.5-day latency for use in research and applications [6]. The L4_SM product also includes estimates of soil temperature, land surface fluxes, and assimilation diagnostics such as the model forecast and observed Tb values [7]. The output from the L4_SM system is routinely monitored by the L4_SM team. Such monitoring provides valuable information; instances of unusually large Tb observation-minus-forecast (O-F) residuals can indicate events during which soil moisture conditions are poorly described in the land modeling system [7,8]. For example, repeated occurrences of very large Tb O-F values in central Australia were traced back to deficiencies in the gauge-based precipitation product used in the land modeling system through L4_SM Version 5; this discovery prompted the use, beginning in Version 6, of satellite- and gauge-based precipitation observations outside of North America [9]. Recently, a statistical analysis of the Tb O-F residuals revealed systematic errors in the “tau-omega” L-band radiative transfer model that converts the land-model simulated soil moisture and temperature into the forecast Tb prior to the L4_SM analysis. The L4_SM analysis is built on the ensemble Kalman filter and assumes unbiased forecast errors. The presence of systematic Tb forecast errors could thus adversely impact the quality of the analyzed soil moisture. In this paper, we examine the Tb O-F residuals of the latest Version 7 L4_SM data (Science Version ID Vv7030 and Vv7032) [10,11,12]. In the L4_SM Version 7 algorithm, key parameters of the L-band radiative transfer model, including soil roughness, scattering albedo, and a (seasonally varying) climatology of vegetation opacity, are obtained from the SMAP Level-2 Radiometer retrieval product (Version 5) [1]. Additionally, we also use ground measurements of surface soil moisture and soil temperature from the SMAP core validation sites as in situ reference of soil conditions [2,3]. As part of the L4_SM system calibration, the seasonally-varying bias between the model forecast Tb and the observed values is removed prior to the assimilation of the SMAP Tb observations [7]. That is, the L4_SM system is designed to only correct errors in synoptic-scale and interannual variations from the long-term mean seasonal cycle while maintaining the model’s (potentially erroneous) climatology. The Tb O-F residuals examined here are thus computed using SMAP Tb observations after they are rescaled to the mean seasonal cycle of Tb from the modeling system without SMAP data assimilation. Consequently, the long-term average of the Tb O-F residuals has a global mean of only 0.13 K and locally small values, ranging from -1 to 3 K. Despite the small time-average values of the Tb O-F residuals, the model forecast Tb was nevertheless found to exhibit undesirable systematic errors. At some locations, the time-average Tb O-F values strongly depend on surface soil moisture (SM). At the Yanco SMAP core validation site, for example, the Tb O-F residuals typically range from 5 to 15 K under dry soil moisture conditions (SM < 0.15 m3 m-3) yet are predominantly negative under wet soil moisture conditions (SM > 0.25 m3 m-3), with values ranging from 0 to -40 K. This results in soil moisture analysis increments that persistently make the soil drier under dry SM conditions and persistently make the soil wetter under wet SM conditions, suggesting an error in the dynamic range of the simulated Tb, soil moisture or soil temperature. In this paper, we describe the higher-order systematic Tb forecast errors in more detail, examine their impact on the L4_SM product quality, and explore potential avenues to further improve the L4_SM algorithm.

Rolf Reichle↗
DOE OSTI2025

Isolation of Inner-Sphere Aquo Complexes of Samarium(II)

The cis-anti-cis and cis-syn-cis isomers of [Sm(dicyclohexano-18-crown-6)(H 2 O) 2 ]I 2 exhibiting trans water molecules bound to the Sm 2+ ion have been isolated and characterized. Sm 2+ possesses an electrochemical potential sufficient for water reduction, and thus these complexes add to the recent body of evidence that the oxidation of Sm 2+ by water can operate by a mechanism that is not straightforward. These complexes are obtained by the direct addition of stoichiometric amounts of water to solutions of the respective Sm(dicyclohexano-18-crown-6)I 2 isomers under an inert atmosphere. The parent complex, Sm(dicyclohexano-18-crown-6)I 2 , lacking coordinating water molecules can be obtained through rigorous exclusion of water. It was determined that the bulky cyclohexano-substituents deter intramolecular interactions between [Sm(dicyclohexano-18-crown-6)(H 2 O) 2 ]I 2 complexes and slow the oxidization of the metal centers. The extent of the stability of these complexes to the presence of water has been further probed through cyclic voltammetry, where it was found that the redox potential of both isomers of [Sm(dicyclohexano-18-crown-6)(H 2 O) 2 ]I 2 maintains quasi-reversible behavior with a 50,000-fold excess of water to Sm 2+ in solution with the cis-syn-cis complex being quasi-reversible at even higher concentrations of water. Solution-phase spectroscopy of these complexes in acetonitrile shows a corresponding hypsochromic shift of the Sm 2+ 4f → 5d transition typically observed in the visible region from Sm 2+ complexes. Here, the crystalline compounds obtained in this study support solid-state spectroscopic trends observed from other Sm 2+ crown-ether complexes containing iodide counterions, wherein the proximity of the iodide ions to the metal center determines whether the complex can exhibit 4f → 4f photoluminescence.

Crystals↗
NASA NTRS2019

Uncertainty in Soil Moisture Retrievals: an Ensemble Approach Using SMOS L-Band Microwave Data

The uncertainty of soil moisture (SM) retrievals from satellite brightness temperature (TB) observations depends primarily on the choice of radiative transfer model (RTM) parameters, prior SM information and TB inputs. This paper studies the sensitivity of several (quasi-)operational and experimental SM retrieval products from the Soil Moisture Ocean Salinity (SMOS) mission to these choices at 11 reference sites, located in 7 watersheds across the United States (US). Different literature-based RTM parameter sets cause large biases between retrievals. Whereas typical RTM parameter sets are calibrated for SM retrievals, it is shown that a parameter set carefully optimized for TB forward modeling can also be used for retrieving SM. It is also shown that the inclusion of dynamic prior SM estimates in a Bayesian retrieval scheme can strongly improve SM retrievals, regardless of the choice of RTM parameters, and that the use of multi-angular and multi-polarization TB does not necessarily lead to superior retrievals compared to retrievals based on TB data at a single incidence angle and polarization. The second part of this paper evaluates ensemble uncertainty metrics for SM retrievals obtained by propagating a wide range of RTM parameters through the RTM. As expected for bounded variables, the spread in the ensemble SM retrievals is smallest for wet and dry SM values and highest for intermediate SM values. After removal of the strong long-term mean bias associated with the RTM parameter values for individual ensemble members, the remaining anomaly ensemble SM spread of 0.037 cu m/cu m approximates the actual time series unbiased root-mean-square-difference of 0.042 cu m/cu m between ensemble mean retrievals and in situ reference data across the reference sites. However, the temporal variability in the anomaly ensemble spread reveals higher-order biases in the retrieval error, which should be accounted for when characterizing retrieval error.

Jan Quets↗
NASA NTRS1994

Pre-bombardment crystallization ages of basaltic clasts from Antarctic howardites EET87503 and EET87513

Igneous clasts of basaltic eucrites are found in both howardites and polymict eucrites. We have studied the Rb-Sr and Sm-Nd isotopic systematics of a number of such clasts, of metamorphic grades 1-6, using the classification of Takeda and Graham. Here, we report Rb-Sr, (147)Sm-(143)Nd, and (145)Sm-(142)Nd studies of clast, 53 from Antarctic howardite EET87503. Although there is no evidence of disturbance of trace element systematics by Antarctic weathering, the Rb-Sr and conventional Sm-Nd isotopic systematics are severely disturbed, which we ascribe to thermal metamorphism. The Ar-Ar age spectrum shows ages ranging from approximately 3.85-3.55 Ga in an unusual 'down stairstep'. The (146)Sm-(142)Nd systematics, however, show the presence of live (146)Sm(t(sub 1/2) = 103 Ma), with (146)Sm/(144)Sm = 0.0061 +/- 0.0007 at the time of crystallization. This result is very similar to that previously obtained for basaltic clast, 18 from howardite EET87513 (paired with EET87503), which has concordant Rb-Sr and Sm-Nd ages of approximately 4.5 Ga. Thus, the two clasts are nearly the same age, and we conclude further than the EET87503,53 clast crystallized within 33 +/- 19 Ma of the LEW86010 angrite by comparing initial (146)Sm/(144)Sm to that of the angrite. We suggest that disturbances in the isotopic systematics of EET87503,53 are consanguineous with pyroxene homogenization.

Nyquist, L. E.↗
NASA NTRS2018

AMSR2 Soil Moisture Downscaling Using Temperature and Vegetation Data

Soil moisture (SM) applications in terrestrial hydrology require higher spatial resolution soil moisture products than those provided by passive microwave remote sensing instruments (grid resolution of 9 km or larger). In this investigation, an innovative algorithm that uses visible/infrared remote sensing observations to downscale Advanced Microwave Scanning Radiometer 2 (AMSR2) coarse spatial resolution SM products was developed and implemented for use with data provided by the Advanced Microwave Scanning Radiometer 2 (AMSR2). The method is based on using the Normalized Difference Vegetation Index (NDVI) modulated relationships between day/night SM and temperature change at corresponding times. Land surface model output variables from the North America Land Data Assimilation System (NLDAS), remote sensing data from the Moderate-Resolution Imaging Spectroradiometer (MODIS), and Advanced Very High Resolution Radiometer (AVHRR) were used in this methodology. The functional relationships developed using NLDAS data at a grid resolution of 12.5 km were applied to downscale AMSR2 JAXA (Japan Aerospace Exploration Agency) SM product (25 km) using MODIS land surface temperature (LST) and NDVI observations (1 km) to produce the 1 km SM estimates. The downscaled SM estimates were validated by comparing them with ISMN (International Soil Moisture Network) in situ SM in the Black Bear-Red Rock watershed, central Oklahoma between 2015-2017. The overall statistical variables of the downscaled AMSR2 SM validation R2, slope, RMSE and bias, demonstrate good accuracy. The downscaled SM better characterized the spatial and temporal variability of SM at watershed scales than the original SM product.

AMSR2; passive microwave soil moisture; soil moist↗
NASA NTRS2022

Multi-Frequency Radiometer-Based Soil Moisture Retrieval and Algorithm Parameterization Using In Situ Sites

L-band brightness temperature (TB) has been shown to provide the best sensitivity to soil moisture (SM) although C- and X-band based products offer a longer time-series from satellite-based measurements. Currently, global coverage SM is routinely produced from spaceborne measurements using all three frequency bands, but despite continued validation efforts of the products, the relative characteristics and performance of these observations have not been fully established. Therefore, this study focused on the parametrization of SM retrieval algorithms at L-, C- and X-bands using TB observations from the L-band radiometer on NASA's SM Active Passive (SMAP) mission and the C- and X-band channels of JAXA's Advanced Microwave Scanning Radiometer 2 (AMSR2) onboard the GCOM-W satellite. These can be applied in global SM retrieval algorithms using either one of the frequencies or a combination of them. The reference in situ SM data was obtained from 12 core validation sites across various land cover types around the world. The investigation highlighted the known challenges of retrieving SM from C- and X-band data compared to the higher sensitivity of the L-band data. Even with a site-specific retrieval algorithm parameterization, the mean correlation of the C- and X-band retrievals for the core validation site SM measurement were much lower than that for L-band, being 0.52 (0.54) and 0.45 (0.47) for vertical (horizontal) polarization, respectively, while for the L-band retrieval the corresponding values were 0.81 (0.77). The parameterization exercise showed that matching the C- and X-band TB measurements with an emission model was not difficult; the problem was relating the observations to SM under the influence of large roughness and vegetation effects. As a result, parameter optimization produced values for some sites that were not realistic or did not allow any practical sensitivity to SM at C- and X-band. Considering the L-band observations, the parameter optimization resulted in superior bias performance as compared to the operational SMAP product parameterization, but the sensitivity to SM changes (R and unbiased root mean square difference) did not improve markedly, or in some cases degraded at the expense of a smaller bias.

passive microwave↗
NASA NTRS2023

Assimilation of Blended Satellite Soil Moisture Data Products to Further Improve Noah-MP Model Skills

Microwave satellite remote sensing has enabled observations of soil moisture (SM) at the global scale, and multiple SM data products have been developed in the past decades. However, single-sensor-based measurements are insufficient for continuous spatiotemporal coverage. In the context of its climate program, the Climate Change Initiative, the European Space Agency (ESA) has developed robust, long term, global scale, multi instrument satellite derived time series of climate data record for key component of the climate system, including soil moisture (CCI), while the Soil Moisture Operational Product System (SMOPS) was specifically developed by National Oceanic and Atmospheric Administration (NOAA) to offer the real time blended SM datasets through merging all available individual products. Before combining, all individual SM data ingested into both SMOPS and CCI blended products are scaled to Global Land Data Assimilation System (GLDAS) 0-10 cm SM climatology. Benefiting from land surface model evolution and the availability of high-quality forcing data, GLDAS has become more comprehensive to track SM changes and dynamic trends. The development of GLDAS and the scaling procedure in CCI and SMOPS leave an open scientific and operational question: do the blended satellite SM data products have added value comparing to the GLDAS product? This study clearly reveals that both CCI and SMOPS can provide the reliable SM observations with independent information, although their climatology matches well with GLDAS. Relative to assimilation of GLDAS 0-10 cm SM data, Noah-MP model can be further improved by assimilating the blended satellite SM observations with respect to the quality-controlled in situ measurements. The strong consistency of results presented in this paper proves that the blended satellite SM data products are more useful than the GLDAS product in terms of improving Noah-MP model performance.

Jifu Yin↗
NASA NTRSDate not supplied

Systematic Errors in Simulated L-Band Brightness Temperature in the SMAP Level-4 Soil Moisture Analysis

The NASA Soil Moisture Active Passive (SMAP) mission has been providing L-band (1.4 GHz) brightness temperature (Tb) observations since April 2015. By assimilating the Tb observations into the NASA Catchment land surface model using a spatially distributed ensemble Kalman filter (EnKF), the SMAP 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 ~2.5-day latency for use in research and applications. The EnKF-based L4_SM analysis assumes unbiased forecast errors. Consequently, the seasonally varying bias between the model forecast Tb and the observed values is removed prior to the assimilation of the SMAP Tb observations. The L4_SM system is thus designed to only correct errors in synoptic-scale and interannual variations from the long-term mean seasonal cycle while maintaining the model’s (possibly wrong) climatology. In this paper, we examine the Tb observation-minus-forecast (O-F) residuals from the L4_SM Version 7 product (computed after rescaling the Tb observations to the mean seasonal cycle of the simulated Tb). The long-term average of the Tb O-F residuals has a global mean of only 0.13 K and locally small values, ranging from -1 to 3 K. The model forecast Tb, however, still exhibits undesirable systematic errors relative to the (rescaled) Tb observations. At some locations, the time-average Tb O-F values strongly depend on surface soil moisture (SM). At the Yanco SMAP core validation site, for example, the Tb O-F residuals typically range from 5 to 15 K under dry soil moisture conditions (SM < 0.15 m3 m-3) yet are predominantly negative under wet soil moisture conditions (SM > 0.25 m3 m-3), with values ranging from 0 to -40 K. This results in soil moisture analysis increments that persistently make the soil drier under dry SM conditions and persistently make the soil wetter under wet SM conditions, suggesting an error in the dynamic range of the simulated Tb, soil moisture or soil temperature. In this paper, we describe the higher-order systematic Tb forecast errors in more detail, examine their impact on the L4_SM product quality, and explore potential avenues to improve the L4_SM algorithm.

Rolf Reichle↗
DOE OSTI2025

Influence of Soil Moisture on the Development of Organized Convective Systems in South America

Abstract This study investigates the role of soil moisture (SM) on the initiation and organization of convective systems using the convection‐permitting ICOsahedral Non‐hydrostatic (ICON) model. We conduct two sets of experiments: a Control experiment with interactive SM and a fixed SM experiment (FixedSM) with invariable SM conditions. We focus on two regions in South America: the Amazon and southeastern South America (SESA). Larger organized convective systems are associated with greater SM heterogeneity in both regions, though other large‐scale synoptic influences affect the robustness of this relationship in SESA. These results remain largely unaffected by disabling the effects of precipitation on SM in the FixedSM experiment, and complementary analyses using satellite‐based estimates of SM and precipitation support these findings. Spatial compositing of mesoscale environments in the Amazon shows the presence of well‐defined SM gradients, at a length scale of a few hundred kilometers, many hours before convective system detection. Larger SM gradients correspond to larger gradients in thermodynamic variables, particularly surface temperature and sensible heat flux, and are associated with larger convective systems. Overall, our findings suggest that surface heterogeneities such as SM gradients not only affect deep convection initiation, as previously suggested, but they can also encourage the growth and organization of convective systems into larger clusters, particularly in the absence of significant synoptic influences.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2010

Mixed Layer Sub-Mesoscale Parameterization - Part 1: Derivation and Assessment

Several studies have shown that sub-mesoscales (SM 1km horizontal scale) play an important role in mixed layer dynamics. In particular, high resolution simulations have shown that in the case of strong down-front wind, the re-stratification induced by the SM is of the same order of the de-stratification induced by small scale turbulence, as well as of that induced by the Ekman velocity. These studies have further concluded that it has become necessary to include SM in ocean global circulation models (OGCMs), especially those used in climate studies. The goal of our work is to derive and assess an analytic parameterization of the vertical tracer flux under baroclinic instabilities and wind of arbitrary directions and strength. To achieve this goal, we have divided the problem into two parts: first, in this work we derive and assess a parameterization of the SM vertical flux of an arbitrary tracer for ocean codes that resolve mesoscales, M, but not sub-mesoscales, SM. In Part 2, presented elsewhere, we have used the results of this work to derive a parameterization of SM fluxes for ocean codes that do not resolve either M or SM. To carry out the first part of our work, we solve the SM dynamic equations including the non-linear terms for which we employ a closure developed and assessed in previous work. We present a detailed analysis for down-front and up-front winds with the following results: (a) down-front wind (blowing in the direction of the surface geostrophic velocity) is the most favorable condition for generating vigorous SM eddies; the de-stratifying effect of the mean flow and re-stratifying effect of SM almost cancel each other out,

Canuto, V. M.↗