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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

Dual frequency microwave radiometer measurements of soil moisture for bare and vegetated rough surfaces

Controlled ground-based passive microwave radiometric measurements on soil moisture were conducted to determine the effects of terrain surface roughness and vegetation on microwave emission. Theoretical predictions were compared with the experimental results and with some recent airborne radiometric measurements. The relationship of soil moisture to the permittivity for the soil was obtained in the laboratory. A dual frequency radiometer, 1.41356 GHz and 10.69 GHz, took measurements at angles between 0 and 50 degrees from an altitude of about fifty feet. Distinct surface roughnesses were studied. With the roughness undisturbed, oats were later planted and vegetated and bare field measurements were compared. The 1.4 GHz radiometer was less affected than the 10.6 GHz radiometer, which under vegetated conditions was incapable of detecting soil moisture. The bare surface theoretical model was inadequate, although the vegetation model appeared to be valid. Moisture parameters to correlate apparent temperature with soil moisture were compared.

Lee, S. L.↗
NASA NTRS1981

Some effects of topography, soil moisture, and sea-surface temperature on continental precipitation as computed with the GISS coarse mesh climate model

The effects of terrain elevation, soil moisture, and zonal variations in sea/surface temperature on the mean daily precipitation rates over Australia, Africa, and South America in January were evaluated. It is suggested that evaporation of soil moisture may either increase or decrease the model generated precipitation, depending on the surface albedo. It was found that a flat, dry continent model best simulates the January rainfall over Australia and South America, while over Africa the simulation is improved by the inclusion of surface physics, specifically soil moisture and albedo variations.

Spar, J.↗
NASA NTRS2011

Microwave Processing of Planetary Surfaces for Volatile Extraction

In-Situ Resource Utilization will be necessary for sustained exploration of space. Volatiles are present in planetary soils, but water by far has the strongest potential for effective utilization. The presence of water at the lunar poles, Mars, and possibly on Phobos opens the possibility of producing LOX for propellant. Water is also a useful radiation shielding material and water (and oxygen) are expendables that are also required for habitation in space. Because of the strong function of water vapor pressure with temperature, heating soil effectively liberates water vapor by sublimation. Microwave energy will penetrate soil and heat from within much more efficiently than heating from the surface with radiant heat. This is especially true under vacuum conditions since the heat transfer rate is very low. The depth of microwave penetration is a strong function of the microwave frequency and to a lesser extent on soil dielectric properties. Methods for measuring the complex electric permittivity and magnetic permeability are being developed and have been measured for some lunar soil simulants at 0.5, 2.45, and 10 GHz from room temperature down to liquid nitrogen temperature. A new method for delivery of microwaves deep into a planetary surface is being prototyped with laboratory experiments and modeled with COMSOL MultiPhysics. We have plans to set up a planetary testbed in a large vacuum chamber in the coming year. Recent results will be presented.

Ethridge, Edwin C.↗
NASA NTRS1980

Effect of soil texture on the microwave emission from soils

The intensity brightness temperature of the microwave emission from the soil is determined primarily by its dielectric properties. The large difference between the dielectric constant of water and that of dry soil produces a strong dependence of the soil's dielectric constant on its moisture content. This dependence is effected by the texture of the soil because the water molecules close to the particle surface are tightly bound and do not contribute significantly to the dielectric properties. Since this surface area is a function of the particle size distribution (soil texture), being larger for clay soils with small particles, and smaller for sandy soils with larger particles; the dielectric properties will depend on soil texture. Laboratory measurements of the dielectric constant for soils are summarized. The dependence of the microwave emission on texture is demonstrated by measurements of brightness temperature from an aircraft platform for a wide range of soil textures. It is concluded that the effect of soil texture differences on the observed values can be normalized by expressing the soil moisture values as a percent field capacity for the soil.

Schmugge, T. J.↗
NASA NTRS2020

Using a Simple Water Balance Framework to Quantify the Impact of Soil Moisture Initialization on Subseasonal Evapotranspiration and Air Temperature Forecasts

Past studies have shown that accurate soil moisture initialization can contribute significant skill to near-surface air temperature (T2M) forecasts at subseasonal leads. The mechanisms by which soil moisture contributes such skill are examined here with a simple water balance-based model that captures the essence of soil moisture behavior in a state-of-the-art subseasonal-to-seasonal (S2S) forecasting system. The simple model successfully transforms initial soil moisture contents into average “forecasted” ET values at 16-30 day lead that agree well, during summer, with the values forecasted by the full NASA GEOS S2S system, indicating that soil moisture initialization dominates over forecasted meteorology in determining ET fluxes at subseasonal leads. When the simple model’s ET anomalies are interpreted in terms of T2M anomalies, a similar conclusion is reached for T2M: soil moisture initialization explains much (about 50% in the eastern half of the continental US) of the T2M anomalies produced by the full GEOS S2S system at 16-30 day lead, and the T2M forecasts produced by the simple model capture about half of the skill attained by the full system. The simple model’s framework is particularly conducive to an analysis of uncertainty in forecasts. Drier soils are generally found to induce larger uncertainty in ET (and thus T2M) forecasts, a result linked to the functional form relating ET to soil moisture in the simple model and verified by an analysis of the ensemble spreads within the forecasts produced by the full GEOS S2S system

Randal D Koster↗
NASA NTRS1981

Analysis of soil moisture extraction algorithm using data from aircraft experiments

A soil moisture extraction algorithm is developed using a statistical parameter inversion method. Data sets from two aircraft experiments are utilized for the test. Multifrequency microwave radiometric data surface temperature, and soil moisture information are contained in the data sets. The surface and near surface ( or = 5 cm) soil moisture content can be extracted with accuracy of approximately 5% to 6% for bare fields and fields with grass cover by using L, C, and X band radiometer data. This technique is used for handling large amounts of remote sensing data from space.

Burke, H. H. K.↗
NASA NTRS2019

Soil Moisture Data Assimilation

Accurate knowledge of soil moisture at the continental scale is important for improving predictions of weather, agricultural productivity and natural hazards, but observations of soil moisture at such scales are limited to indirect measurements, either obtained through satellite remote sensing or from meteorological networks. Land surface models simulate soil moisture processes, using observation-based meteorological forcing data, and auxiliary information about soil, terrain and vegetation characteristics. Enhanced estimates of soil moisture and other land surface variables, along with their uncertainty, can be obtained by assimilating observations of soil moisture into land surface models. These assimilation results are of direct relevance for the initialization of hydro-meteorological ensemble forecasting systems. The success of the assimilation depends on the choice of the assimilation technique, the nature of the model and the assimilated observations, and, most importantly, the characterization of model and observation error. Systematic differences between satellite-based microwave observations or satellite-retrieved soil moisture and their simulated counterparts require special attention. Other challenges include inferring root-zone soil moisture information from observations that pertain to a shallow surface soil layer, propagating information to unobserved areas and downscaling of coarse information to finer-scale soil moisture estimates. This chapter summarizes state-of-the-art solutions to these issues with conceptual data assimilation examples, using techniques ranging from simplified optimal interpolation to spatial ensemble Kalman filtering. In addition, operational soil moisture assimilation systems are discussed that support numerical weather prediction at ECMWF and provide value-added soil moisture products for the NASA Soil Moisture Active Passive mission.

radar backscatter↗
NASA NTRS1988

Estimating soil water evaporation using radar measurements

Field studies were conducted to evaluate the application of radar reflectivity as compared with the shortwave reflectivity (albedo) used in the Idso-Jackson equation for the estimation of daily evaporation under overcast sky and subhumid climatic conditions. Soil water content, water potential, shortwave and radar reflectivity, and soil and air temperatures were monitored during three soil drying cycles. The data from each cycle were used to calculate daily evaporation from the Idso-Jackson equation and from two other standard methods, the modified Penman and plane of zero-flux. All three methods resulted in similar estimates of evaporation under clear sky conditions; however, under overcast sky conditions, evaporation fluxes computed from the Idso-Jackson equation were consistently lower than the other two methods. The shortwave albedo values in the Idso-Jackson equation were then replaced with radar reflectivities and a new set of total daily evaporation fluxes were calculated. This resulted in a significant improvement in computed soil evaporation fluxes from the Idso-Jackson equation, and a better agreement between the three methods under overcast sky conditions.

Sadeghi, Ali M.↗
NASA NTRS1989

Mapping freeze/thaw boundaries with SMMR data

Nimbus 7 Scanning Multichannel Microwave Radiometer (SMMR) data are used to map daily freeze/thaw patterns in the upper Midwest for the Fall of 1984. The combination of a low 37 GHz radiobrightness and a negative 10.7, 18, and 37 GHz spectral gradient, Partial Derivative of Tb with Respect to f, appears to be an effective discriminant for classifying soil as frozen or thawed. The 37 GHz emissivity is less sensitive to soil moisture than are the lower frequency emissivities so that the 37 GHz radiobrightness appears to track soil surface temperature relatively well. The negative gradient for frozen ground is a consequence of volume scatter darkening at shorter microwave wavelengths. This shorter wavelength darkening is not seen in thawed moist soils.

Zuerndorfer, B. W.↗
NASA NTRS2021

PRELIMINARY MODEL FOR SOIL MOISTURE RETRIEVAL USING P-BAND RADIOMETER OBSERVATIONS

Soil Moisture is an important geophysical variable that needs reliable quantification for applications in hydrology, meteorology and agriculture. L-band radiometry has proved to be one of the best methods in soil moisture estimation using microwave signals. However, they provide measurements that correspond to a shallow depth of 5 cm and are also affected by the presence of overlaying vegetation and roughness. In contrast, P-band radiometry is expected to provide moisture information on a deeper layer of soil. Moreover, these lower frequency measurements are expected to be less affected by soil roughness and vegetation contributions. Consequently, this pilot study uses the Polarimetric P-band Multi beam Radiometer(PPMR) at 740 MHz to evaluate the response of theP-band radiometer over a realistic range of surface condition sat the field scale. A preliminary framework of P-band MicrowaveEmission of theBiosphere (P-MEB) has been developed as a forward model that simulates brightness temperature from soil moisture and other ancillary data collected from the field. This paper presents the model for the bare soil condition observed during June 2018 to August 2018. The results show that H-polarized PPMR data has better correlation to the soil moisture over a depth of 10 cm than the V-polarized PPMR data. A model is under improvement by incorporating a more suitable effective temperature formulation.

Edward J Kim↗
NASA NTRS2021

Argentina Food Security & Agriculture: Crop Monitoring and Forecasting for Argentina using NASA Satellite Observations

Early harvest information helps guide agricultural commodity assessments in Argentina, providing valuable planning information to identify potentially food-insecure regions, anticipate transportation and storage demands, predict price fluctuations, and project commodity trends. However, crop yield estimates are currently subjective, based on interviews with qualified informants (i.e., farmers, agribusiness actors). In partnership with the Buenos Aires Grain Exchange, we leveraged Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Soil Moisture Active Passive (SMAP), and Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM IMERG) NASA Earth observations to develop a Google Earth Engine (GEE) toolset to monitor vegetation growth. The first component of the toolset produces spatial and temporal maps of temperature, precipitation, soil moisture, and the Normalized Difference Vegetation Index (NDVI), allowing users to visualize the influence of the region’s climate and weather. Next, we developed an autoregressive model to predict NDVI several months in advance. Lastly, we created a linear regression model of crop yield and NDVI for soybeans, corn, and wheat, and input the forecasted NDVI to generate a predicted crop yield output. The NDVI forecasting model produced accurate predictions at two, four, and six months when examining the most recent growing season. In the crop yield model, soybeans exhibited moderately strong correlation, wheat had consistent weak correlation, and corn varied from weak to strong correlation depending on zone. This information is vital for vegetation growth monitoring by identifying areas of high growth and allocating resources to areas of lower growth to efficiently maximize crop yields.

DEVELOP Tech Paper↗
NASA NTRS1973

Study of thermal properties of the lunar regolith based on in situ temperature measurements and experiments on soil simulants

The experimental design and the development of a theory to interpret the experimental data from measurements of the thermal conductivity of lunar core samples. Measurements conducted while the lunar material is still in the core tube reduce the possibility of physical and chemical disturbances to the sample. The sample was heated externally by radiation at a known rate, the variation of temperature was measured at the surface of the core sample, and thermal conductivity was determined by comparing the observed temperature with the theoretically expected one.

Langseth, M. G.↗
NASA NTRSDate not supplied

FORWARD AND INVERSE L-BAND RADIATIVE TRANSFER MODELING OVER THE DRY CHACO, USING SMOS OBSERVATIONS, LAND SURFACE MODELING AND IN SITU DATA

Passive microwave L-band remote sensing is well known for its sensitivity to surface soil moisture over land.The signal is also affected by other dynamic variables such as vegetation and soil salinity. In this research, L-band microwave observations of the Soil Moisture Ocean Salinity (SMOS) mission are used to explore soil surface salinity, moisture and vegetation, in the Argentinean Dry Chaco, an area with possible emerging dryland salinity. A Radiative Transfer Model (RTM) with inclusion of a correction to the soil’s dielectric constant for salinity was used in forward and inverse mode, using either in situ data or Catchment Land Surface Model (CLSM) simulations as RTM input. The forward analysis pointed out shortcomings in the modeled soil moisture and soil surface temperature estimates. The impact of salinity on forward simulations over the Dry Chaco was limited.The RTM inversion using 10 years of SMOS brightness temperature observations resulted in realistic estimates of vegetation and roughness, both with and withouto ptimizing a correction term for the dielectric constant in terms of salinity equivalents. However,the retrieval of the correction term to the dielectric constant was very uncertain and not representative of soil surface salinity, but rather of open water, texture uncertainty or soil moisture bias.

L-band↗
NASA NTRS1975

Detection of soil moisture and snow characteristics from Skylab

The author has identified the following significant results. The most significant result is the good response of the passive radiometers, particularly the L-band radiometer, to changing soil moisture conditions near the surface of the earth. Radiometer response was very good for the five complete data sets consisting of three passes across Texas and two passes across Kansas. When data from the five different passes were combined, the correlation between the S194 radiometric temperature and soil moisture content remained high with a value of -0.96. The performance of the S193 passive radiometer was less consistent; however, one data set gave a very high correlation of -0.95. The scatterometer response to soil moisture at incidence angles near 30 deg was not as good as for the radiometers.

Eagleman, J. R.↗
NASA NTRS1982

Simulating soybean canopy temperature as affected by weather variables and soil water potential

Hourly weather data for several clear sky days during summer at Phoenix and Baltimore which covered a wide range of variables were used with a plant atmosphere model to simulate soybean (Glycine max L.) leaf water potential, stomatal resistance and canopy temperature at various soil water potentials. The air and dew point temperatures were found to be the significant weather variables affecting the canopy temperatures. Under identical weather conditions, the model gives a lower canopy temperature for a soybean crop with a higher rooting density. A knowledge of crop rooting density, in addition to air and dew point temperatures is needed in interpreting infrared radiometric observations for soil water status. The observed dependence of stomatal resistance on the vapor pressure deficit and soil water potential is fairly well represented. Analysis of the simulated leaf water potentials indicates overestimation, possibly due to differences in the cultivars.

Choudhury, B. J.↗
NASA NTRS2011

Utilization of Ancillary Data Sets for Conceptual SMAP Mission Algorithm Development and Product Generation

The planned Soil Moisture Active Passive (SMAP) mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council's Decadal Survey, Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond [1]. Scheduled to launch late in 2014, the proposed SMAP mission would provide high resolution and frequent revisit global mapping of soil moisture and freeze/thaw state, utilizing enhanced Radio Frequency Interference (RFI) mitigation approaches to collect new measurements of the hydrological condition of the Earth's surface. The SMAP instrument design incorporates an L-band radar (3 km) and an L band radiometer (40 km) sharing a single 6-meter rotating mesh antenna to provide measurements of soil moisture and landscape freeze/thaw state [2]. These observations would (1) improve our understanding of linkages between the Earth's water, energy, and carbon cycles, (2) benefit many application areas including numerical weather and climate prediction, flood and drought monitoring, agricultural productivity, human health, and national security, (3) help to address priority questions on climate change, and (4) potentially provide continuity with brightness temperature and soil moisture measurements from ESA's SMOS (Soil Moisture Ocean Salinity) and NASA's Aquarius missions. In the planned SMAP mission prelaunch time frame, baseline algorithms are being developed for generating (1) soil moisture products both from radiometer measurements on a 36 km grid and from combined radar/radiometer measurements on a 9 km grid, and (2) freeze/thaw products from radar measurements on a 3 km grid. These retrieval algorithms need a variety of global ancillary data, both static and dynamic, to run the retrieval models, constrain the retrievals, and provide flags for indicating retrieval quality. The choice of which ancillary dataset to use for a particular SMAP product would be based on a number of factors, including its availability and ease of use, its inherent error and resulting impact on the overall soil moisture or freeze/thaw retrieval accuracy, and its compatibility with similar choices made by the SMOS mission. All decisions regarding SMAP ancillary data sources would be fully documented by the SMAP Project and made available to the user community.

freeze/thaw↗
NASA NTRS2011

Microwave Processing of Planetary Surfaces for the Extraction of Volatiles

In-Situ Resource Utilization will be necessary for sustained exploration of space. Volatiles are present in planetary soils, but water by far has the most potential for effective utilization. The presence of water at the lunar poles, Mars, and possibly on Phobos opens the possibility of producing LOX for propellant. Water is also a useful radiation shielding material , and valuable to replenish expendables (water and oxygen) required for habitation in space. Because of the strong function of water vapor pressure with temperature, heating soil effectively liberates water vapor by sublimation. Microwave energy will penetrate soil and heat from within much more efficiently than heating from the surface with radiant heat. This is especially true under vacuum conditions since the heat transfer rate is very low. The depth of microwave penetration is a strong function of the microwave frequency and to a lesser extent on soil dielectric properties. Methods for complex electric permittivity and magnetic permeability measurement are being developed and used for measurements of lunar soil simulants. A new method for delivery of microwaves deep into a planetary surface is being prototyped with laboratory experiments and modeled with COMSOL MultiPhysics. We are planning to set up a planetary testbed in a large vacuum chamber in the coming year. Recent results are discussed.

Ethridge, Edwin C.↗