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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

(abstract) Monitoring the Freeze/Thaw Transitions in Taiga Forests Using ERS-1 SAR

Automated recording stations have been installed at the Bonanza Creek Experimental Forest, a Long Term Ecological Research (LTER) site located near Fairbanks, Alaska, in a forest stand of the Tanana River floodplain underlain by discontinuous permafrost. These stations provide a continuous record of dielectric constant and temperature of tree trunks, and soil moisture and temperature profiles down to the root zone. Along with the weather stations deployed at the same location, these measurements provide a continuous record of the environmental and phenologic conditions of the forest during a complete seasonal cycle. At the same time, ERS-1 SAR imaged the study site repeatedly from space to provide radar backscatter measurements of the forest approximately three times a month. Here, we examine the temporal dynamic of ERS-1 SAR measurements in relation with the changing environmental and phenologic state of the forest canopy and of the forest ground layers during the winter/spring and fall/winter transitions of 1992 and 1993. During these transitions, we examine whether changes in radar backscatter observed by ERS-1 may be related to freezing or thawing of the soil and vegetation in order to determine the start and end of the growing season for the forest. The results of this analysis are used in turn to determine whether similar changes are observed over larger regions. Mosaics of SAR data generated along three different North-South Alaskan ERS-1 transects that intercept with our study site are used in combination with hourly air temperature and daily precipitation rates gathered at airport weather stations by the National Weather Service. Results obtained using ERS-1 data collected from January 1992 to mid-1993 will be discussed.

permafrost temporal dynamics Alaska ecology radar ↗
NASA NTRS1982

Evapotranspiration and remote sensing

There are three things required for evapotranspiration to occur: (1) energy (580 cal/gm) for the change of phase of the water; (2) a source of the water, i.e., adequate soil moisture in the surface layer or in the root zone of the plant; and (3) a sink for the water, i.e., a moisture deficit in the air above the ground. Remote sensing can contribute information to the first two of these conditions by providing estimates of solar insolation, surface albedo, surface temperature, vegetation cover, and soil moisture content. In addition there have been attempts to estimate precipitation and shelter air temperature from remotely sensed data. The problem remains to develop methods for effectively using these sources of information to make large area estimates of evapotranspiration.

Schmugge, T. J.↗
NASA NTRS1997

The Aggregate Description of Semi-Arid Vegetation with Precipitation-Generated Soil Moisture Heterogeneity

Meteorological measurements in the Walnut Gulch catchment in Arizona were used to synthesize a distributed, hourly-average time series of data across a 26.9 by 12.5 km area with a grid resolution of 480 m for a continuous 18-month period which included two seasons of monsoonal rainfall. Coupled surface-atmosphere model runs established the acceptability (for modelling purposes) of assuming uniformity in all meteorological variables other than rainfall. Rainfall was interpolated onto the grid from an array of 82 recording rain gauges. These meteorological data were used as forcing variables for an equivalent array of stand-alone Biosphere-Atmosphere Transfer Scheme (BATS) models to describe the evolution of soil moisture and surface energy fluxes in response to the prevalent, heterogeneous pattern of convective precipitation. The calculated area-average behaviour was compared with that given by a single aggregate BATS simulation forced with area-average meteorological data. Heterogeneous rainfall gives rise to significant but partly compensating differences in the transpiration and the intercepted rainfall components of total evaporation during rain storms. However, the calculated area-average surface energy fluxes given by the two simulations in rain-free conditions with strong heterogeneity in soil moisture were always close to identical, a result which is independent of whether default or site-specific vegetation and soil parameters were used. Because the spatial variability in soil moisture throughout the catchment has the same order of magnitude as the amount of rain failing in a typical convective storm (commonly 10% of the vegetation's root zone saturation) in a semi-arid environment, non-linearitv in the relationship between transpiration and the soil moisture available to the vegetation has limited influence on area-average surface fluxes.

White, Cary B.↗
NASA NTRS1981

Investigation of remote sensing techniques of measuring soil moisture

Major activities described include development and evaluation of theoretical models that describe both active and passive microwave sensing of soil moisture, the evaluation of these models for their applicability, the execution of a controlled field experiment during which passive microwave measurements were acquired to validate these models, and evaluation of previously acquired aircraft microwave measurements. The development of a root zone soil water and soil temperature profile model and the calibration and evaluation of gamma ray attenuation probes for measuring soil moisture profiles are considered. The analysis of spatial variability of soil information as related to remote sensing is discussed as well as the implementation of an instrumented field site for acquisition of soil moisture and meteorologic information for use in validating the soil water profile and soil temperature profile models.

Newton, R. W.↗
NASA NTRS1984

Biosphere/atmosphere Interactions

Vegetation influences the energy, mass and momentum exchange between land-surface and atmosphere and, in that way, may significantly affect weather and climate. The morphology and physiology of the vegetation determine the surface albedo, precipitation interception and interception loss, stomatal control of transpiration, moisture storage in the root zone and, through the vegetation roughness height, the aerodynamic resistance to the transfers of latent and sensible heat and momentum between land-surface and atmosphere. That the albedo and soil moisture have a large influence on the atmospheric circulation and rainfall was demonstrated in sensitivity experiments with general circulation models. Moreover, through its effect on the convergence of the horizontal water vapor transport in the planetary boundary layer, the surface roughness height has a large influence on rainfall.

Mintz, Y.↗
NASA NTRS2010

Satellite Gravimetry Applied to Drought Monitoring

Near-surface wetness conditions change rapidly with the weather, which limits their usefulness as drought indicators. Deeper stores of water, including root-zone soil wetness and groundwater, portend longer-term weather trends and climate variations, thus they are well suited for quantifying droughts. However, the existing in situ networks for monitoring these variables suffer from significant discontinuities (short records and spatial undersampling), as well as the inherent human and mechanical errors associated with the soil moisture and groundwater observation. Remote sensing is a promising alternative, but standard remote sensors, which measure various wavelengths of light emitted or reflected from Earth's surface and atmosphere, can only directly detect wetness conditions within the first few centimeters of the land s surface. Such sensors include the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) C-band passive microwave measurement system on the National Aeronautic and Space Administration's (NASA) Aqua satellite, and the combined active and passive L-band microwave system currently under development for NASA's planned Soil Moisture Active Passive (SMAP) satellite mission. These instruments are sensitive to water as deep as the top 2 cm and 5 cm of the soil column, respectively, with the specific depth depending on vegetation cover. Thermal infrared (TIR) imaging has been used to infer water stored in the full root zone, with limitations: auxiliary information including soil grain size is required, the TIR temperature versus soil water content curve becomes flat as wetness increases, and dense vegetation and cloud cover impede measurement. Numerical models of land surface hydrology are another potential solution, but the quality of output from such models is limited by errors in the input data and tradeoffs between model realism and computational efficiency. This chapter is divided into eight sections, the next of which describes the theory behind satellite gravimetry. Following that is a summary of the GRACE mission and how hydrological information is gleaned from its gravity products. The fourth section provides examples of hydrological science enabled by GRACE. The fifth and sixth sections list the challenging aspects of GRACE derived hydrology data and how they are being overcome, including the use of data assimilation. The seventh section describes recent progress in applying GRACE for drought monitoring, including the development of new soil moisture and drought indicator products, and that is followed by a discussion of future prospects in satellite gravimetry based drought monitoring.

Rodell, Matthew↗
NASA NTRS2018

Assimilation of Satellite Derived Soil Moisture Profiles into a Crop Modeling System for Robust Yield Estimates

Soil Moisture Measurement - Remote Sensing. - Microwave (MW) Remote Sensing: Physically based and quantitative in nature; Based on difference in dielectric constant; Coarse spatial resolution 25-40 km; Shallow SM estimation depth 0-5 cm (approx.); All weather capabilities (e.g. Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E), Soil Moisture and Ocean Salinity (SMOS), Soil Moisture Active Passive (SMAP) etc.) - Thermal Infrared (TIR) Remote Sensing: Indirect SM retrieval through energy flux estimations; Relatively better spatial resolution 1-10 km; Root-zone moisture retrieval capability; Can not penetrate through clouds, hence data gaps (e.g. Surface Energy Balance Algorithm for Land (SEBAL), Atmospheric Land Exchange Inverse (ALEXI) etc.)

SERVIR↗
NASA NTRS1981

Modeling the terrestrial hydrology for the global atmosphere - The future role of satellite data

A global terrestrial hydrology model has been developed for the transport and storage of moisture and heat in the ground surface layer where the hydrological parameters react to diurnal and seasonal changes in the atmosphere. The spatial and temporal variability of land surface features is considered in the model by means of large scale parameterizations. The model can be either forced by the atmosphere using conventional meteorological data or coupled to an atmospheric general circulation model (GCM) for interactive studies. The global surface is divided into 4 deg longitude by 5 deg latitude cells while the ground is represented by a thin surface layer, a bulk layer (the root zone), and a deep layer (the ground water zone). Results are presented from a seven-day global experiment which was conducted utilizing the GLAS GCM (NASA Goddard Laboratory for Atmospheric Sciences). The model has demonstrated its capability to predict, over a large region, the overall soil moisture storage and major flux exchanges with the atmosphere above and the ground water below.

Lin, J. D.↗
NASA NTRS2011

Improving Simulated Soil Moisture Fields Through Assimilation of AMSR-E Soil Moisture Retrievals with an Ensemble Kalman Filter and a Mass Conservation Constraint

Model simulated soil moisture fields are often biased due to errors in input parameters and deficiencies in model physics. Satellite derived soil moisture estimates, if retrieved appropriately, represent the spatial mean of soil moisture in a footprint area, and can be used to reduce model bias (at locations near the surface) through data assimilation techniques. While assimilating the retrievals can reduce model bias, it can also destroy the mass balance enforced by the model governing equation because water is removed from or added to the soil by the assimilation algorithm. In addition, studies have shown that assimilation of surface observations can adversely impact soil moisture estimates in the lower soil layers due to imperfect model physics, even though the bias near the surface is decreased. In this study, an ensemble Kalman filter (EnKF) with a mass conservation updating scheme was developed to assimilate the actual value of Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture retrievals to improve the mean of simulated soil moisture fields by the Noah land surface model. Assimilation results using the conventional and the mass conservation updating scheme in the Little Washita watershed of Oklahoma showed that, while both updating schemes reduced the bias in the shallow root zone, the mass conservation scheme provided better estimates in the deeper profile. The mass conservation scheme also yielded physically consistent estimates of fluxes and maintained the water budget. Impacts of model physics on the assimilation results are discussed.

Li, Bailing↗
NASA NTRS2021

Validation of Soil Moisture Data Products from the NASA SMAP Mission

The National Aeronautics and Space Administration (NASA)Soil Moisture Active Passive(SMAP) mission has been validatingits soil moisture (SM) products since the start of data production onMarch 31, 2015. Prior to launch, the mission defined a set of criteria for core validation sites (CVS) that enable the testing of the key mission SM accuracy requirement(unbiased root-mean-square error <0.04 m3/m3). Thevalidation approach also includes other (“sparse network”) in situSM measurements, satellite SM products, model-based SM products, and field experiments. Over the past six years, the SMAP SM products have been analyzed with respect to thesereference data,and the analysis approaches themselves have been scrutinizedin an effort to best understand the products’ performance. Validation of themost recent SMAP Level 2 and 3 SMretrievalproducts (R17000) shows that the L-band (1.4 GHz) radiometer-based SM record continues to meet mission requirements. The products aregenerallyconsistentwith SM retrievals from the European Space Agency (ESA)Soil Moisture Ocean Salinity mission, althoughthere aredifferencesin some regions. The high-resolution (3-km) SM retrieval product,generated by combining Copernicus Sentinel-1 data with SMAP observations,performswithin expectations. Currently, however,there is limited availability of3-kmCVSdatato support extensive validation at this spatial scale. The most recent (version 5)SMAP Level4 SMdata assimilation productprovidingsurface and root-zone SM with complete spatio-temporal coverageat 9-km resolution also meets performance requirements. The SMAP SM validation program will continue throughout the mission life; futureplans include expanding ittoforestedand high-latituderegions

SMAP↗
NASA NTRS1979

Use of thermal infrared and colour infrared imagery to detect crop moisture stress

The author has identified the following significant results. In the presence of variable plant cover (primarily percent cover) and variable available water content, the remotely sensed apparent temperatures correlate closely with plant cover and poorly with soil water. To the extent that plant cover is not systematically related to available soil water, available water in the root zone values may not be reliably predicted from the thermal infrared data. On the other hand, if plant cover is uniform and the soil surface is shown in a minor way, the thermal data indicate plant stress and consequently available water in the soil profile.

Mckenzie, R. C.↗
NASA NTRS2011

Improving Numerical Weather Predictions of Summertime Precipitation Over the Southeastern U.S. Through a High-Resolution Initialization of the Surface State

It is hypothesized that high-resolution, accurate representations of surface properties such as soil moisture and sea surface temperature are necessary to improve simulations of summertime pulse-type convective precipitation in high resolution models. This paper presents model verification results of a case study period from June-August 2008 over the Southeastern U.S. using the Weather Research and Forecasting numerical weather prediction model. Experimental simulations initialized with high-resolution land surface fields from the NASA Land Information System (LIS) and sea surface temperature (SST) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) are compared to a set of control simulations initialized with interpolated fields from the National Centers for Environmental Prediction 12-km North American Mesoscale model. The LIS land surface and MODIS SSTs provide a more detailed surface initialization at a resolution comparable to the 4-km model grid spacing. Soil moisture from the LIS spin-up run is shown to respond better to the extreme rainfall of Tropical Storm Fay in August 2008 over the Florida peninsula. The LIS has slightly lower errors and higher anomaly correlations in the top soil layer, but exhibits a stronger dry bias in the root zone. The model sensitivity to the alternative surface initial conditions is examined for a sample case, showing that the LIS/MODIS data substantially impact surface and boundary layer properties.

Case, Jonathan L.↗
NASA NTRS2016

Climate-Induced Mortality of Siberian Pine and Fir in the Lake Baikal Watershed, Siberia

Siberian pine (Pinus sibirica) and fir (Abies sibirica) (so called ''dark needle conifers", DNC) showed decreased radial growth increment within the Lake Baikal watershed since the 1980s with increasing mortality recorded since the year 2000. Tree ring width was strongly correlated with vapor pressure deficit, aridity and root zone moisture. Water stress from droughts made trees more susceptible to insect attacks causing mortality in about 10% of DNC stands within the Lake Baikal watershed. Within Siberia DNC mortality increased in the southern part of the DNC range. Biogeographically, tree mortality was located within the DNC - forest-steppes transition. Tree mortality was significantly correlated with drought and soil moisture anomalies. Within the interior of the DNC range mortality occurred within relief features with high water stress risk (i.e., steep convex south facing slopes with shallow well-drained soils). In general, DNC mortality in Siberia was induced by increased aridity and severe drought (inciting factors) in synergy with biotic attacks (contributing factor). In future climate scenarios with predicted increase in aridity DNC could be eliminated from the southern part of its current range and will be replaced by drought-resistant conifers and broadleaf species (e.g., Larix sibirica, Pinus silvestris, and Betula pubescence).

Conifer Mortality↗
NASA NTRS2016

Climate-Induced Mortality of Siberian Pine and Fir in the Lake Baikal Watershed, Siberia

Siberian pine (Pinus sibirica) and fir (Abies sibirica) (so called "dark needle conifers", DNC) showed decreased radial growth increment within the Lake Baikal watershed since the 1980s with increasing mortality recorded since the year 2000. Tree ring width was strongly correlated with vapor pressure deficit, aridity and root zone moisture. Water stress from droughts made trees more susceptible to insect attacks causing mortality in about 10% of DNC stands within the Lake Baikal watershed. Within Siberia DNC mortality increased in the southern part of the DNC range. Biogeographically, tree mortality was located within the DNC - forest-steppes transition. Tree mortality was significantly correlated with drought and soil moisture anomalies. Within the interior of the DNC range mortality occurred within relief features with high water stress risk (i.e., steep convex south facing slopes with shallow well-drained soils). In general, DNC mortality in Siberia was induced by increased aridity and severe drought (inciting factors) in synergy with biotic attacks (contributing factor). In future climate scenarios with predicted increase in aridity DNC could be eliminated from the southern part of its current range and will be replaced by drought-resistant conifers and broadleaf species (e.g., Larix sibirica, Pinus silvestris, and Betula pubescence).

Viacheslav I Kharuk↗
NASA NTRS2019

Consistency Between NASS Surveyed Soil Moisture Conditions and SMAP Soil Moisture Observations

The USDA National Agricultural Statistics Survey (NASS) collects and publishes crop growth status and soil moisture conditions in major US agricultural regions. The operationally-produced weekly reports are based on survey information. The surveys are based on visual assessments and ? in the case of soil moisture ? report soil moisture levels in one of four categories (Very Short, Short, Adequate and Surplus). In this study, we show that these reports have remarkable correspondence with the NASA Soil Moisture Active Passive (SMAP) Level-4 Soil Moisture (L4SM) product. This consistency allows the combining the two distinct types of data to produce a value-added combination, which is mapped fields rather than State-by-State tables and it is refreshed daily rather than weekly. In this study classification thresholds are derived for L4SM by mapping cumulative distribution functions of L4SM surface and root-zone SM to the categorical NASS SM conditions. The results show that, year-over-year, the SMAP cumulative SM distributions are consistent with the NASS SM conditions and, furthermore, that the temporal evolution of the SMAP-derived thresholds is consistent with the seasonal crop growth cycles from year to year. The results signify that the SMAP SM retrievals are relatable to SM estimation conducted in agriculture by land managers and farmers, which underlines the general applicability of the SMAP data.

Andreas Colliander↗
NASA NTRS2018

Larch (Larix dahurica Turcz) growth response to climate change in the Siberian permafrost zone

Larch-dominant communities are the most extensive high-latitude forests in Eurasia and are experiencing the strongest impacts from warming temperatures. We analyzed larch (Larix dahurica Turcz) growth index (GI) response to climate change. The studied larch-dominant communities are located within the permafrost zone of Northern Siberia at the northern tree limit (ca. N 67° 38′, E 99° 07′). Methods included dendrochronology, analysis of climate variables, root zone moisture content, and satellitederived gross (GPP) and net (NPP) primary productivity. It was found that larch response to warming included a period of increased annual growth increment (GI) (from the 1970s to ca. 1995) with a follow on GI decline. Increase in GI correlated with summer air temperature, whereas an observed decrease in GI was caused by water stress (vapor pressure deficit and drought increase). Water stress impact on larch growth in permafrost was not observed before the onset of warming (ca. 1970). Water limitation was also indicated by GI dependence on soil moisture stored during the previous year. Water stress was especially pronounced for stands growing on rocky soils with low water-holding capacity. GPP of larch communities showed an increasing trend, whereas NPP stagnated. A similar pattern of GI response to climate warming has also been observed for Larix sibirica Ledeb, Pinus sibirica Du Tour, and Abies sibirica Ledeb in the forests of southern Siberia. Thus, warming in northern Siberia permafrost zone resulted in an initial increase in larch growth from the 1970s to the mid-1990s. After that time, larch growth increment has decreased. Since ca. 1990, water stress at the beginning of the vegetative period became, along with air temperature, a main factor affecting larch growth within the permafrost zone.

Larix dahurica↗
NASA NTRS2005

Porous media matric potential and water content measurements during parabolic flight

Control of water and air in the root zone of plants remains a challenge in the microgravity environment of space. Due to limited flight opportunities, research aimed at resolving microgravity porous media fluid dynamics must often be conducted on Earth. The NASA KC-135 reduced gravity flight program offers an opportunity for Earth-based researchers to study physical processes in a variable gravity environment. The objectives of this study were to obtain measurements of water content and matric potential during the parabolic profile flown by the KC-135 aircraft. The flight profile provided 20-25 s of microgravity at the top of the parabola, while pulling 1.8 g at the bottom. The soil moisture sensors (Temperature and Moisture Acquisition System: Orbital Technologies, Madison, WI) used a heat-pulse method to indirectly estimate water content from heat dissipation. Tensiometers were constructed using a stainless steel porous cup with a pressure transducer and were used to measure the matric potential of the medium. The two types of sensors were placed at different depths in a substrate compartment filled with 1-2 mm Turface (calcined clay). The ability of the heat-pulse sensors to monitor overall changes in water content in the substrate compartment decreased with water content. Differences in measured water content data recorded at 0, 1, and 1.8 g were not significant. Tensiometer readings tracked pressure differences due to the hydrostatic force changes with variable gravity. The readings may have been affected by changes in cabin air pressure that occurred during each parabola. Tensiometer porous membrane conductivity (function of pore size) and fluid volume both influence response time. Porous media sample height and water content influence time-to-equilibrium, where shorter samples and higher water content achieve faster equilibrium. Further testing is needed to develop these sensors for space flight applications.

Parabolic Flight↗
NASA NTRS2017

Estimating Surface Soil Moisture from SMAP Observations Using a Neural Network Technique

A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to March 2017 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observing System Model version 5 (GEOS-5) land modeling system, and Moderate Resolution Imaging Spectroradiometer-based vegetation water content. The NN was trained on GEOS-5 soil moisture target data, making the NN estimates consistent with the GEOS-5 climatology, such that they may ultimately be assimilated into this model without further bias correction. Evaluated against in situ soil moisture measurements, the average unbiased root mean square error (ubRMSE), correlation and anomaly correlation of the NN retrievals were 0.037 m(exp. 3)m(exp. -3), 0.70 and 0.66, respectively, against SMAP core validation site measurements and 0.026 m(exp. 3)m(exp. -3), 0.58 and 0.48, respectively, against International Soil Moisture Network (ISMN) measurements. At the core validation sites, the NN retrievals have a significantly higher skill than the GEOS-5 model estimates and a slightly lower correlation skill than the SMAP Level-2 Passive (L2P) product. The feasibility of the NN method was reflected by a lower ubRMSE compared to the L2P retrievals as well as a higher skill when ancillary parameters in physically-based retrievals were uncertain. Against ISMN measurements, the skill of the two retrieval products was more comparable. A triple collocation analysis against Advanced Microwave Scanning Radiometer 2 (AMSR2) and Advanced Scatterometer (ASCAT) soil moisture retrievals showed that the NN and L2P retrieval errors have a similar spatial distribution, but the NN retrieval errors are generally lower in densely vegetated regions and transition zones.

Soil Moisture Remote Sensing↗