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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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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Short-Term Retrospective Land Data Assimilation Schemes

Subsurface moisture and temperature and snow/ice stores exhibit persistence on various time scales that has important implications for the extended prediction of climatic and hydrologic extremes. Hence, to improve their specification of the land surface, many numerical weather prediction (NWP) centers have incorporated complex land surface schemes in their forecast models. However, because land storages are integrated states, errors in NWP forcing accumulates in these stores, which leads to incorrect surface water and energy partitioning. This has motivated the development of Land Data Assimilation Schemes (LDAS) that can be used to constrain NWP surface storages. An LDAS is an uncoupled land surface scheme that is forced primarily by observations, and is therefore less affected by NWP forcing biases. The implementation of an LDAS also provides the opportunity to correct the model's trajectory using remotely-sensed observations of soil temperature, soil moisture, and snow using data assimilation methods. The inclusion of data assimilation in LDAS will greatly increase its predictive capacity, as well as provide high-quality land surface assimilated data.

Houser, P. R.↗
NASA NTRS1981

Soil moisture applications of the heat capacity mapping mission

Results are presented of ground, aircraft and satellite investigations conducted to evaluate the potential of the Heat Capacity Mapping Mission (HCMM) to monitor soil moisture and the depth of shallow ground water. The investigations were carried out over eastern South Dakota to evaluate the relation between directly measured soil temperatures and water content at various stages of canopy development, aircraft thermal scanner measurements of apparent canopy temperature and the reliability of actual HCMM data. The results demonstrate the possibility of evaluating soil moisture on the basis of HCMM apparent canopy temperature and day-night soil temperature difference measurements. Limitations on the use of thermal data posed by environmental factors which influence energy balance interactions, including phase transformations, wind patterns, topographic variations and atmospheric constituents are pointed out.

Heilman, J. L.↗
DOE OSTI2022

Castanha et al. 2018: Hopland Lysimeter 13C-Labeled Root Litter Decomposition Study.

The breakdown and decomposition of plant inputs are critical for nutrient cycling, soil development, and climate-ecosystem feedbacks, but uncertainties persist in how the rates and products of litter decomposition are affected by soil temperature, rhizosphere, and depth of input. To elucidate these questions we measured the effects of soil warming (+ 4 °C), rhizosphere, and depth of litter placement on the decomposition of Avena fatua (wild oat grass) root litter in a Mediterranean grassland ecosystem. Field lysimeters were subjected to three environmental treatments (heating, control, and plant removal) and three 13C-labeled root litter addition treatments (to A horizon, to B horizon, and no-addition disturbance control) for each of two harvest time points. We buried root litter in February 2014 and measured loss of 13C in CO2 from the soil surface and in leachate as dissolved organic carbon (DOC) over two growing seasons. At the end of each of the 2014 and 2015 growing seasons we recovered the 13C remaining in the soil. Loss of root litter C occurred almost entirely via heterotrophic respiration, with an estimated < 2% lost as DOC during the initial decay period. The added roots were broken down and incorporated into bulk soil material very quickly; only ~ 30% of added root was visible after 6 months. In the first growing season, decomposition occurred faster in the B than in the A horizon, the latter having greater moisture limitation. Subsequently, there was almost no further decomposition in the B horizon. After two growing seasons, less than 20% of the added root litter C remained in the A or B horizons of all environmental treatments. Heating did not stimulate decomposition, likely because it exacerbated the moisture limitation. However, while plots without plants dried down more slowly than plots with plants, their decomposition rate was not significantly greater, possibly due to the lack of rhizosphere processes such as priming. We conclude that in this Mediterranean grassland ecosystem, soil moisture, which is affected by season, depth, heating, and rhizosphere, plays a dominant role in mediating the effect of those factors on root litter decomposition, which after two seasons did not differ by depth or by treatment.The files in this dataset comprise (1) 13C-labeled litter additions made to each plot, (2) litter recovery after each of 2 growing seasons, (3) periodical soil flux measurements, (4) leachate measurements, and continuously monitored soil (5) temperature and (6) moisture.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

MVACS Robotic Arm

The primary purpose of the Mars Volatiles and Climate Surveyor (MVACS) Robotic Arm is to support to the other MVACS science instruments by digging trenches in the Martian soil; acquiring and dumping soil samples into the thermal evolved gas analyzer (TEGA); positioning the Soil Temperature Probe (STP) in the soil: positioning the Robotic Arm Air Temperature Sensor (RAATS) at various heights above the surface, and positioning the Robotic Arm Camera (RAC) for taking images of the surface, trench, soil samples, magnetic targets and other objects of scientific interest within its workspace.

robotics robotic arm sampling MVACS↗
NASA NTRS2000

BOREAS TE-6 Allometry Data

The BOREAS TE-6 team collected several data sets in support of its efforts to characterize and interpret information on the plant biomass, allometry, biometry, sapwood, leaf area index, net primary production, soil temperature, leaf water potential, soil CO2 flux, and multivegetation imagery of boreal vegetation. This data set includes tree measurements conducted on the above-ground biomass of trees in the BOREAS NSA and SSA during the growing seasons of 1994 and 1995 and the derived allometric relationships/equations. The data are stored in ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distrobuted Activity Archive Center (DAAC).

Hall, Forrest G.↗
NASA NTRS2000

BOREAS TE-6 Biomass and Foliage Area Data

The BOREAS TE-6 team collected several data sets in support of its efforts to characterize and interpret information on the plant biomass, allometry, biometry, sapwood, leaf area index, net primary production, soil temperature, leaf water potential, soil CO, flux, and multivegetation imagery of boreal vegetation. This data set contains measurements of estimates of the standing biomass and leaf area index for the plant species at the TF, CEV, and AUX sites in the SSA and NSA during the growing seasons of 1994 and 1995. The data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Activity Archive Center (DAAC).

Hall, Forrest G.↗
NASA NTRS2000

BOREAS TE-6 1994 Soil and Air Temperatures in the NSA

The BOREAS TE-6 team collected several data sets to examine the influence of vegetation, climate, and their interactions on the major carbon fluxes for boreal forest species. This data set contains measurements of the air temperature at a single height and soil temperature at several depths in the NSA from 25-May to 08-Oct- 1994. Chromel-Constantan thermocouple wires run by a miniprogrammable data logger (Model 21X, Campbell Scientific, Inc., Logan, UT) provided direct measurements of temperature. The data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distrobuted Activity Archive Center (DAAC).

Hall, Forrest G.↗
NASA NTRS2021

Evaluation of High Mountain Asia-Land Data Assimilation System (Version 1) from 2003 to 2016, Part I: A Hyper-Resolution Terrestrial Modeling System

This first paper of the two-part series focuses on demonstrating the accuracy of a hyper-resolution, offline terrestrial modeling system used for the High Mountain Asia (HMA) region. To this end, this study systematically evaluates four sets of model simulations at point scale, basin scale, and domain scale obtained from different spatial resolutions including 0.01° (∼1-km) and 0.25° (∼25-km). The assessment is conducted via comparisons against ground-based observations and satellite-derived reference products. The key variables of interest include surface net shortwave radiation, surface net longwave radiation, skin temperature, near-surface soil temperature, snow depth, snow water equivalent, and total runoff. In the evaluation against ground-based measurements, the superiority of the 0.01° estimates are mostly demonstrated across relatively complex terrain. Specifically, hyper-resolution modeling improves the skill in meteorological forcing estimates (except precipitation) by 9% relative to coarse-resolution estimates. The model forced by downscaled forcings in its entirety yields the highest skill in model output states as well as precipitation, which improves the skill obtained by coarse-resolution estimates by 7%. These findings, on one hand, corroborate the importance of employing the hyper-resolution versus coarse-resolution modeling in areas characterized by complex terrain. On the other hand, by evaluating four sets of model simulations forced with different precipitation products, this study emphasizes the importance of accurate hyper-resolution precipitation products to drive model simulations.

Yuan Xue↗
NASA NTRS2022

Evaluation of High Mountain Asia-Land Data Assimilation System (version 1) from 2003 to 2016: 2. The impact of assimilating satellite-based snow cover and freeze/thaw observations into a land surface model

This second paper of the two-part series focuses on demonstrating the impact of assimilating satellite-based snow cover and freeze/thaw observations into the hyper-resolution, offline terrestrial modeling system used for the High Mountain Asia (HMA) region from 2003 to 2016. To this end, this study systematically evaluates a total of six sets of 0.01° (∼1 km) model simulations forced by different precipitation forcings, with and without the dual assimilation scheme enabled, at point-scale, basin-scale, and domain-scale. The key variables of interest include surface net shortwave radiation, surface net longwave radiation, skin temperature, near-surface soil temperature, snow depth, snow water equivalent (SWE), and total runoff. First, the point-scale assessment is mainly conducted via evaluating against ground-based measurements. In general, the assimilation enabled estimates are better than no-assimilation counterparts. Second, the basin-scale runoff assessment demonstrates that across three snow-dominated basins, the assimilation enabled experiment yields systematic improvements in all goodness-of-fit statistics through mitigating the negative effects brought by the fixed long-term precipitation correction factors. For example, when forced by the bias-corrected precipitation, the assimilation-enabled experiment improves the bias by 69%, the root-mean-squared error by 30%, and the unbiased root-mean-squared error by 18% (relative to the no-assimilation counterpart). Finally, the domainscale assessment is conducted via evaluating against satellite-based SWE and skin temperature products. Both sets of domain-scale analysis further corroborate the findings in the point-scale evaluations. Overall, this study suggests the benefits of the proposed multi-variate assimilation system in improving the cryospherichydrological process within a land surface model for use in HMA.

Yuan Xue↗
NASA NTRS2022

Evaluation of High Mountain Asia-Land Data Assimilation System (version 1) from 2003 to 2016: 2. The impact of assimilating satellite-based snow cover and freeze/thaw observations into a land surface model

This second paper of the two-part series focuses on demonstrating the impact of assimilating satellite-based snow cover and freeze/thaw observations into the hyper-resolution, offline terrestrial modeling system used for the High Mountain Asia (HMA) region from 2003 to 2016. To this end, this study systematically evaluates a total of six sets of 0.01° (∼1 km) model simulations forced by different precipitation forcings, with and without the dual assimilation scheme enabled, at point-scale, basin-scale, and domain-scale. The key variables of interest include surface net shortwave radiation, surface net longwave radiation, skin temperature, near-surface soil temperature, snow depth, snow water equivalent (SWE), and total runoff. First, the point-scale assessment is mainly conducted via evaluating against ground-based measurements. In general, the assimilation enabled estimates are better than no-assimilation counterparts. Second, the basin-scale runoff assessment demonstrates that across three snow-dominated basins, the assimilation enabled experiment yields systematic improvements in all goodness-of-fit statistics through mitigating the negative effects brought by the fixed long-term precipitation correction factors. For example, when forced by the bias-corrected precipitation, the assimilation-enabled experiment improves the bias by 69%, the root-mean-squared error by 30%, and the unbiased root-mean-squared error by 18% (relative to the no-assimilation counterpart). Finally, the domain-scale assessment is conducted via evaluating against satellite-based SWE and skin temperature products. Both sets of domain-scale analysis further corroborate the findings in the point-scale evaluations. Overall, this study suggests the benefits of the proposed multi-variate assimilation system in improving the cryospheric-hydrological process within a land surface model for use in HMA.

Yuan Xue↗
NASA NTRS1992

Soil surface CO2 fluxes and the carbon budget of a grassland

Measurements of soil surface CO2 fluxes are reported for three sites within the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) area, and simple empirical equations are fit to the data to provide predictions of soil fluxes from environmental observations. A prototype soil chamber, used to make the flux measurements, is described and tested by comparing CO2 flux measurements to a 40-L chamber, a 1-m/cu chamber, and eddy correlation. Results suggest that flux measurements with the prototype chamber are consistent with measurements by other methods to within about 20 percent. A simple empirical equation based on 10-cm soil temperature, 0- to 10-cm soil volumetric water content, and leaf area index predicts the soil surface CO2 flux with a rms error of 1.2 micro-mol sq m/s for all three sites. Further evidence supports using this equation to evaluate soil surface CO2 during the 1987 FIFE experiment. The soil surface CO2 fluxes when averaged over 24 hours are comparable to daily gross canopy photosynthetic rates. For 6 days of data the net daily accumulation of carbon is about 0.6 g CO2 sq m/d; this is only a few percent of the daily gross accumulation of carbon by photosynthesis. As the soil became drier in 1989, the net accumulation of carbon by the prairie increased, suggesting that the soil flux is more sensitive to temperature and drought than the photosynthetic fluxes.

Norman, J. M.↗
NASA NTRS1972

Fixation of virgin lunar surface soil

Two systems are shown to be suitable for fixing loose particulate soils with a polymer film, without visually detectable disturbance of the soil particle spatial relationships. A two-component system is described, which uses a gas monomer condensible at the soil temperature and a gas phase catalyst acting to polymerize the monomer. A one-component system using a monomer which polymerizes spontaneously on and within the top few millimeters of the soil is also considered. The two-component system employs a simpler apparatus, but it operates over a narrower temperature range (approximately -40 to -10 C). Other two-component systems were identified which may operate at soil temperatures as high as +100 C, at relatively narrow temperature ranges of approximately 30 C. The one-component system was demonstrated to operate successfully with initial soil temperatures from -70 C or lower to +150 C.

Conley, J. M.↗
NASA NTRS1982

Spatial variability of soil hydraulics and remotely sensed soil parameters

The development of methods to correctly interpret remotely sensed information about soil moisture and soil temperature requires an understanding of water and energy flow in soil, because the signals originate from the surface, or from a shallow surface layer, but reflect processes in the entire profile. One formidable difficulty in this application of soil physics is the spatial heterogeneity of natural soils. Earlier work has suggested that the heterogeneity of soil hydraulic properties may be described by the frequency distribution of a single scale factor. The sensitivity of hydraulic and energetic processes to the variation of this scale factor is explored with a suitable numerical model. It is believed that such an analysis can help in deciding how accurately and extensively basic physical properties of field soils need to be known in order to interpret thermal or radar waveband signals. It appears that the saturated hydraulic conductivity needs to be known only to its order of magnitude, and that the required accuracy of the soil water retention function is about 0.02 volume fraction. Furthermore, the results may be helpful in deciding how the total scene or view field, as perceived through a sensor, is composed from the actual mosaic of transient soil properties, such as surface temperature or surface soil moisture. However, the latter proposition presupposes a random distribution of permanent properties, a condition that may not be met in many instances, and no solution of the problem is apparent.

Lascano, R. J.↗
DOE OSTI2024

Temperature, Humidity, and Time-Lapse Video Data from Yosemite National Park, Water Year 2024

This dataset contains time-lapse imagery and distributed measurements of air temperature, relative humidity, dew point, and soil temperature across Yosemite National Park from October 2023 to September 2024. Instruments were deployed at 10 sites in two cross-valley transects as part of the DOE Grant: Seasonal Cycles Unravel Mysteries of Missing Mountain Water organized by Jessica Lundquist (University of Washington), Rosemary Carroll (Desert Research Institute), and Ethan Gutmann (National Center for Atmospheric Research). The data are intended to support hydrologic modeling efforts to better resolve the fate of mountain water, and are published to support studies of surface climate or hydrologic processes in complex terrain. Measurements were collected with low-cost data loggers installed 2 m high on evergreen trees or buried just below the soil surface. A time-lapse camera at one site captures valley-scale seasonal snow cover variability.Dataset files are organized by site and variable (air measurements, ground measurements, or time-lapse video). Air and ground measurements are packaged in LoggerData.zip, and time-lapse imagery is compiled into a short video stored in TimelapseVideos.zip. File-level metadata contains details for each file included in the dataset. A data dictionary provides units and descriptions for column or row names in all files. The locations metadata file describes site characteristics, locations, and associated GPS methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Much stronger tundra methane emissions during autumn-freeze than spring-thaw

Warming in the Arctic has been more apparent in the non-growing season than in the typical growing season. In this context, methane (CH 4 ) emissions in the non-growing season, particularly in the shoulder seasons, account for a substantial proportion of the annual budget. However, CH 4 emissions in spring and autumn shoulders are often underestimated by land models and measurements due to limited data availability and unknown mechanisms. This study investigates CH 4 emissions during spring thaw and autumn freeze using eddy covariance CH 4 measurements from three Arctic sites with multi-year observations. We find that the shoulder seasons contribute to about a quarter (25.6±2.3%, mean ± standard deviation) of annual total CH 4 emissions. Our study highlights the three to four times higher contribution of autumn freeze CH 4 emission to total annual emission than that of spring thaw. Autumn freeze exhibits significantly higher CH 4 flux (0.88±0.03 mg m -2 h -1 ) than spring thaw (0.48±0.04 mg m -2 h -1 ). The mean duration of autumn freeze (58.94±26.39 days) is significantly longer than that of spring thaw (20.94±7.79 days), which predominates the much higher cumulative CH 4 emission during autumn freeze (1212.31±280.39 mg m -2 yr -1 ) than that during spring thaw (307.39±46.11 mg m -2 yr -1 ). Near-surface soil temperatures cannot completely reflect the freeze-thaw processes in deeper soil layers and appears to have a hysteresis effect on CH 4 emissions from early spring thaw to late autumn freeze. Therefore, it is necessary to consider commonalities and differences in CH 4 emissions during spring thaw versus autumn freeze to accurately estimate CH 4 source from tundra ecosystems for evaluating carbon-climate feedback in Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Geophysical survey associated with NEON AOP survey, East River, CO 2018

The package contains data layers developed and used in Falco et al. 2024: “EcoImaging: Advanced Sensing to Investigate Plant and Abiotic Hierarchical Spatial Patterns in Mountainous Watersheds". The package is part of the DOE Watershed Function Science Focus Area (SFA) project and includes geophysical measurements collected at the East River, Colorado, in conjunction with the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) survey conducted in June 2018. This dataset provide soil geophysical information and were used to investigate soil-plant relationships. The dataset consists of: - NEON_2018_EMI_survey.zip: the electromagnetic induction (EMI) survey as shape-file; - NEON_plot_TDR.csv: plot‑level data from Time‑Domain Reflectometry (TDR) measurements, providing: * volumetric water content (VWC) in percent (%); * soil temperature in degrees Celsius (°C); - file level metadata (flmd.csv) - data dictionary (dd.csv) file This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗