SEARCH · Search NASA

Results for “Soil functions”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16

All sources NASA NTRS DOE OSTI

NASA NTRS1998

Assimilation of Goes-Derived Skin Temperature Tendencies into Mesoscale Models to Improve Forecasts of near Surface Air Temperature and Mixing Ratio

A technique has been developed for assimilating GOES-FR skin temperature tendencies into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature chance closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. An advantage of this technique for short-range forecasts (0-48 h) is that it does not require a complex land-surface formulation within the atmospheric model. As a result, the need to specify poorly known soil and vegetative characteristics is eliminated. The GOES assimilation technique has been incorporated into the PSU/NCAR MM5. Results will be presented to demonstrate the ability of the assimilation scheme to improve short- term (0-48h) simulations of near-surface air temperature and mixing ratio during the warm season for several selected cases which exhibit a variety of atmospheric and land-surface conditions. In addition, validation of terms in the simulated surface energy budget will be presented using in situ data collected at the Southern Great Plains (SGP) Cloud And Radiation Testbed (CART) site as part of the Atmospheric Radiation Measurements Program (ARM).

Lapenta, William M.↗

NASA NTRS1973

A theoretical model for lunar surface material thermal conductivity.

This paper presents a theoretical thermal conductivity model for the uppermost layer of lunar surface material under the lunar vacuum environment. The model assumes that the lunar soil can be simulated by spherical particles in contact with each other and that the effective thermal conductivity is a function of depth, temperature, porosity, particle dimension, and mechanical-thermal properties of the solid particles. Two modes of heat transport are considered, conduction and radiation - with emphasis on the contact resistance between particles. The model gives effective conductivity values that compare favorably with the experimental data from lunar surface samples obtained on Apollo 11 and 12 missions.

Khader, M. S.↗

NASA NTRS1979

Orbiting passive microwave sensor simulation applied to soil moisture estimation

A sensor/scene simulation program was developed and used to determine the effects of scene heterogeneity, resolution, frequency, look angle, and surface and temperature relations on the performance of a spaceborne passive microwave system designed to estimate soil water information. The ground scene is based on classified LANDSAT images which provide realistic ground classes, as well as geometries. It was determined that the average sensitivity of antenna temperature to soil moisture improves as the antenna footprint size increased. Also, the precision (or variability) of the sensitivity changes as a function of resolution.

Newton, R. W.↗

NASA NTRS1991

The implementation and validation of improved landsurface hydrology in an atmospheric general circulation model

Landsurface hydrological parameterizations are implemented in the NASA Goddard Institute for Space Studies (GISS) General Circulation Model (GCM). These parameterizations are: (1) runoff and evapotranspiration functions that include the effects of subgrid scale spatial variability and use physically based equations of hydrologic flux at the soil surface, and (2) a realistic soil moisture diffusion scheme for the movement of water in the soil column. A one dimensional climate model with a complete hydrologic cycle is used to screen the basic sensitivities of the hydrological parameterizations before implementation into the full three dimensional GCM. Results of the final simulation with the GISS GCM and the new landsurface hydrology indicate that the runoff rate, especially in the tropics is significantly improved. As a result, the remaining components of the heat and moisture balance show comparable improvements when compared to observations. The validation of model results is carried from the large global (ocean and landsurface) scale, to the zonal, continental, and finally the finer river basin scales.

Johnson, Kevin D.↗

NASA NTRS1994

Sample Acquisition and Instrument Deployment (SAID)

This report details the interim progress for contract NASW-4818, Sample Acquisition and Instrument Deployment (SAID), a robotic system for deploying science instruments and acquiring samples for analysis. The system is a conventional four degree of freedom manipulator 2 meters in length. A baseline design has been achieved through analysis and trade studies. The design considers environmental operating conditions on the surface of Mars, as well as volume constraints on proposed Mars landers. Control issues have also been studied, and simulations of joint and tip movements have been performed. A passively braked shape memory actuator with the ability to measure load has been developed. The wrist also contains a mechanism which locks the lid output to the bucket so that objects can be grasped and released for instrument deployment. The wrist actuator has been tested for operational power and mechanical functionality at Mars environmental conditions. The torque which the actuator can produce has been measured. Also, testing in Mars analogous soils has been performed.

Boyd, Robert C.↗

NASA NTRS2012

Space Weathering of Lunar Rocks

All materials exposed at the lunar surface undergo space weathering processes. On the Moon, boulders make up only a small percentage of the exposed surface, and areas where such rocks are exposed, like central peaks, are often among the least space weathered regions identified from remote sensing data. Yet space weathered surfaces (patina) are relatively common on returned rock samples, some of which directly sample the surface of larger boulders. Because, as witness plates to lunar space weathering, rocks and boulders experience longer exposure times compared to lunar soil grains, they allow us to develop a deeper perspective on the relative importance of various weathering processes as a function of time.

Noble, S. K.↗

NASA NTRS2013

Lateral Variations in Lunar Weathering Patina on Centimeter to Nanometer Scales

Noble, S. K.↗

NASA NTRSDate not supplied

Comparison of Multivariate Time Series Prediction Techniques for Emulating Noah-LSM Soil Moisture Outputs

Land surface models are crucial tools for many earth science applications including numerical weather prediction, water resource and crop monitoring, and climatological analysis. Given a set of atmospheric forcings, seasonal data, and static parameters, models like Noah-LSM solve for land surface quantities including skin temperature, sensible heat flux, and soil moisture. While these calculations are theoretically robust, they are often computationally expensive. Since artificial neural networks (ANNs) are universal function approximators, they can learn to emulate the output of a deterministic numerical model given a time series of input forcings, with the learned ANN having substantially shorter execution time. The ANN could efficiently parameterize other models, generate ensembles, and provide first-guess inputs for retrievals. As such, with the goal of developing a model that efficiently mimics the output of Noah-LSM given NLDAS2 forcings on a region covering much of the central US, we examine and compare several neural network architectures for the multi-horizon multivariate time series forecasting problem. Recent literature includes a diverse set of approaches including autoregressive architectures like LSTM and GRU, parametric and non-parametric statistical predictors (ForecastNet and MQRNN), self-attention (LSTM-attention-LSTM), and temporal convovlution (DeepTCN). We implement several of these models for the Noah-LSM prediction task, highlighting the features and challenges for each and providing practical insight on the training process.

Mitchell Dodson↗

NASA NTRS2022

Modeling the Errors of a Time Series Algorithm for Retrieving Soil Moisture in the NISAR Mission

The National Aeronautics and Space Administration (NASA) - Indian Space Research Organization (ISRO) Synthetic Aperture Radar (NISAR) mission plan to launch a SAR operating at L- and S-band with a 12-day repeat frequency. A global soil moisture product at 200 m spatial resolution derived from 200 m NISAR radar measurements is currently under development. Although several retrieval algorithms are being investigated, this paper focuses on a “time series ratio” retrieval approach. In order to understand and assess the performance of this algorithm, an error model has been developed and is reported in this paper. The model is applied to examine errors as a function of the instrument characteristics and for a given location. Initial progress in including vegetation effects and in predicting errors as a function of spatial location is also described.

NISAR↗

NASA NTRS1980

A comparison of radiative transfer models for predicting the microwave emission from soils

Two general types of numerical models for predicting microwave emission from soils are compared-coherent and noncoherent. In the former, radiation in the soil is treated coherently, and the boundary conditions on the electric fields across the layer boundaries are used to calculate the radiation intensity. In the latter, the radiation is assumed to be noncoherent, and the intensities of the radiation are considered directly. The results of the two approaches may be different because of the effects of interference, which can cause the transmitted intensity at the surface (i.e., emissivity) to be sometimes higher and sometimes lower for the coherent case than for the noncoherent case, depending on the relative phases of reflected fields from the lower layers. This coupling between soil layers in the coherent models leads to greater soil moisture sampling depths observed with this type of model, and is the major difference that is found between the two types of models. In noncoherent models, the emissivity is determined by the dielectric constraint at the air/soil interface. The subsequent differences in the results are functions of both the frequency of the radiation being considered and the steepness of the moisture gradient near the surface. The calculations were performed at frequencies of 1.4 and 19.4 GHz and for two sets of soil profiles. Little difference was observed between the models at 19.4 GHz; and only at the lower frequency were differences apparent because of the greater soil moisture sampling depth at this frequency.

Schmugge, T. J.↗

NASA NTRS1977

Interpretations of optical observations of Mercury and the moon

Optical, thermal and radar remote-sensing measurements indicate that Mercury is covered with a relatively thick layer of soil similar in texture and thickness to lunar regolith. Photometric limb profiles measured by Mariner 10 imply that the small-scale slopes on Mercury are about half those on the moon, probably because of differing gravity. The differential photometric functions of Mercury and the moon have a latitudinal dependence which can be completely accounted for by shadowing in craters. The lack of polar darkening on Mercury in spite of the presence of a magnetic field implies that the dominant soil-darkening process on Mercury, and by extension, on the moon is not dependent on the solar wind, but probably is deposition of material evaporated by meteorite impacts. Recent measurements of Mercury's spectral reflectivity in the IR and vacuum UV are both consistent with the surface rocks of Mercury being lower in FeO than those of the moon. Based on laboratory experiments the average FeO content on the surface of Mercury is estimated to be between 3 and 6%.

Hapke, B.↗

NASA NTRS1999

Simulated Surface Energy Budgets Over the Southeastern US: The GHCC Satellite Assimilation System and the NCEP Early Eta

A technique has been developed for assimilating GOES-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. An advantage of this technique for short-range forecasts (0-48h) is that it does not require a complex land-surface formulation within the atmospheric model. As a result, we can avoid having to specify land surface characteristics such as vegetation resistances, green fraction, leaf area index, soil physical and hydraulic characteristics, stream flow, runoff, and the vertical and horizontal distribution of soil moisture.

Lapenta, William M.↗

NASA NTRS2000

Through form to function: root hair development and nutrient uptake

Root hairs project from the surface of the root to aid nutrient and water uptake and to anchor the plant in the soil. Their formation involves the precise control of cell fate and localized cell growth. We are now beginning to unravel the complexities of the molecular interactions that underlie this developmental regulation. In addition, after years of speculation, nutrient transport by root hairs has been demonstrated clearly at the physiological and molecular level, with evidence for root hairs being intense sites of H(+)-ATPase activity and involved in the uptake of Ca(2+), K(+), NH(4)(+), NO(3)(-), Mn(2+), Zn(2+), Cl(-) and H(2)PO(4)(-).

Review, Tutorial↗

NASA NTRS2000

Use of Geostationary Satellite Data to Force Land Surface Schemes within Atmospheric Mesoscale Models

A technique has been developed for assimilating GOES-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. The technique has been employed on a semi-operational basis at the GHCC within the PSU/NCAR MM5. Assimilation has been performed on a grid centered over the Southeastern US since November 1998. Results from the past year show that assimilation of the satellite data reduces both the bias and RMSE for simulations of surface air temperature and relative humidity. These findings are based on comparison of assimilation runs with a control using the simple 5-layer soil model available in MM5. A significant development in the past several months was the inclusion of the detailed Oregon State University land surface model (OSU/LSM) as an option within MM5. One of our working hypotheses has been that the assimilation technique, although simple, may provide better short-term forecasts than a detailed LSM that requires significant number initialized parameters. Preliminary results indicate that the assimilation out performs the OSU/LSM as it is incorporated in MM5. Details will be presented at the symposium.

Lapenta, William M.↗

NASA NTRS1979

Applications of HCMM data to soil moisture snow and estuarine current studies

The author has identified the following significant results. Additional analyses of Luverne, Minnesota ground data revealed that soil moisture variations are independent of elevation effects. Tidal fluctuations in the Potomac River and Delaware Bay were examined as a function of surface temperature. Preliminary findings suggest that temperature boundaries are sufficient to detect various stages of the tidal cycle in Delaware Bay, but are as yet uncertain for prediction in the Potomac River. At least three additional cases are needed to completely evaluate the tidal cycle. An alphanumeric printout at a scale of 1:1,000,000 compares closely with a 1:1,000,000 scale DMD image of the Chesapeake Bay region.

Wiesnet, D. R.↗

NASA NTRS1981

Winter wheat: A model for the simulation of growth and yield in winter wheat

The basic ideas and constructs for a general physical/physiological process level winter wheat simulation model are documented. It is a materials balance model which calculates daily increments of photosynthate production and respiratory losses in the crop canopy. The partitioning of the resulting dry matter to the active growing tissues in the plant each day, transpiration and the uptake of nitrogen from the soil profile are simulated. It incorporates the RHIZOS model which simulates, in two dimensions, the movement of water, roots, and soluble nutrients through the soil profile. It records the time of initiation of each of the plant organs. These phenological events are calculated from temperature functions with delays resulting from physiological stress. Stress is defined mathematically as an imbalance in the metabolite supply; demand ratio. Physiological stress is also the basis for the calculation of rates of tiller and floret abortion. Thus, tillering and head differentiation are modeled as the resulants of the two processes, morphogenesis and abortion, which may be occurring simulaneously.

Baker, D. N.↗

NASA NTRS1983

Amalthea - Implications of the temperature observed by Voyager

The temperature profile of Amalthea's surface layer is modeled as a function of location and time of day, assuming a triaxial ellipsoid shape and thermal properties similar to those of the lunar soil. Although the major heat source is direct insolation, temperatures are slightly increased by thermal radiation from Jupiter, sunlight reflected from the planet, and charged particle bombardment. Possible sources of error in the model are discussed in detail, including satellite shape effects, unusually low emissivity, uncommonly rough surface, abnormal thermal inertia, charged particle flux variability, and Joule heating. Voyager 1 IRIS observations suggest that the Amalthean surface has an emissivity near unity, but cannot put any useful limits on the thermal inertia of the Amalthean surface layer.

Simonelli, D. P.↗

NASA NTRS1984

Directional reflectance factor distributions of a cotton row crop

The directional reflectance factor distribution spanning the entire exitance hemisphere was measured for a cotton row crop (Gossypium barbadense L.) with 39 percent ground cover. Spectral directional radiances were taken in NOAA satellite 7 AVHRR bands 1 and 2 using a three-band radiometer with restricted 12 deg full angle field of view at half peak power points. Polar co-ordinate system plots of directional reflectance factor distributions and three-dimensional computer graphic plots of scattered flux were used to study the dynamics of the directional reflectance factor distribution as a function of spectral band, geometric structure of the scene, solar zenith and azimuth angles, and optical properties of the leaves and soil. The factor distribution of the incomplete row crops was highly polymodal relative to that for complete vegetation canopies. Besides the enhanced reflectance for the antisolar point, a reflectance minimum was observed towards the forwardscatter direction in the principle plane of the sun. Knowledge of the mechanics of the observed dynamics of the data may be used to provide rigorous validation for two- or three-dimensional radiative transfer models, and is important in interpreting aircraft and satellite data where the solar angle varies widely.

Kimes, D. S.↗