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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Estimates of monthly mean soil moisture for 1979-1989

This technical report presents estimated monthly mean global soil moisture distributions for 1979-1989. The soil moisture datasets were prepared as part of the boundary conditions for an atmospheric general circulation model (GEOS-1). Also included are the 11-year averages of monthly mean soil moisture, surface air temperature, monthly total precipitation, evapotranspiration, and potential evapotranspiration. The standard deviation of the monthly mean soil moisture is provided as a measure of year-to-year variability.

Schemm, J.↗
NASA NTRS1993

Atmospheric moisture fields derived by satellite observations over the tropical Pacific Ocean

Values of precipitable water are retrieved over the tropical and subtropical Pacific Ocean from TOVS infrared and microwave channel brightness temperature and OLR observations by means of stepwise linear regression. The most useful temperature and moisture sensing channels are pre-selected from sensitivity tests of a radiative transfer model. Numerous models are developed and tested against collocated radiosonde observations and Nimbus-7 SMMR precipitable water estimates. For RAOB comparisons, the best estimator used 15 TOVS predictors and captured 71.1 deg percent of the variance (+0.62 g/sq cm standard error) for column precipitable water; for precipitable water of 700-500 mb bulk layer, these values were 71.7 percent and +/- 0.17 g/sq cm. Little skill of estimated precipitable water was obtained for moisture above 500 mb. Regressions were less skillful against SMMR, unless collocation parameters were tightly controlled; SMMR was less acceptable than RAOB's because of observational drift and errors. Generally, the most skillful predictors were boundary layer brightness temperatures of TOVS channels and satellite estimated stability indices. 'Moisture channels' were hardly useful except for estimating middle and upper tropospheric moisture. Additional regression models were constructed testing the sensitivity to different observational and meteorological characteristics. Models which used some in situ observations surface observations or stabilities calculated from RAOB, were the most successful. The best of these explained 87.5 percent of the variance but the regression selected almost no TOVS channels, relying instead on conventional RAOB and surface observations. A set of four regression models were developed, stratifying atmospheric characteristics on the basis of collocated OLR values. These models improved the variance explained by 5.0 percent; the model associated with the highest OLR values (275 W/sq m less than or equal to OLR; that is, no cloud) showed only marginal skill. Precipitable water fields were generated from the best TOVS-only model for seven days in January 1983 and compared with SMMR-estimated fields. OLR fields and ECMWF precipitable water analysis. The TOVS regression model compared favorably to the SMMR analysis in amplitudes and features. It revealed more evolving synoptic signal than the ECMWF analysis. In synoptically active regions, it differed with respect to the OLR analysis, primarily because of actual differences in the vertical distribution of water vapor.

Chung, Hyosang↗
NASA NTRS1995

Application of IEM model on soil moisture and surface roughness estimation

Monitoring spatial and temporal changes of soil moisture are of importance to hydrology, meteorology, and agriculture. This paper reports a result on study of using L-band SAR imagery to estimate soil moisture and surface roughness for bare fields. Due to limitations of the Small Perturbation Model, it is difficult to apply this model on estimation of soil moisture and surface roughness directly. In this study, we show a simplified model derived from the Integral Equation Model for estimation of soil moisture and surface roughness. We show a test of this model using JPL L-band AIRSAR data.

Shi, Jiancheng↗
NASA NTRS1994

Impact of land-surface moisture variability on local shallow convective cumulus and precipitation in large-scale models

Numerical experiments using state-of-the-art high-resolution mesoscale cloud model showed that land-surface moisture significantly affects the timing of onset of clouds and the intensity and distribution of precipitation. In general, landscape discontinuity enhances shallow convective precipitation. Two mechanisms that are strongly modulated by land-surface moisture-namely, random turbulent thermal cells and organized sea-breeze-like mesoscale circulations-also determine the horizontal distribution of maximum precipitation. However, interactions between shallow cumulus and land-surface moisture are highly nonlinear and complicated by different factors, such as atmospheric thermodynamic structure and large-scale background wind. This analysis also showed that land-surface moisture discontinuities seem to play a more important role in a relatively dry atmsophere, and that the strongest precipitation is produced by a wavelength of land-surface forcing equivalent to the local Rossby radius of deformation. A general trend between the maximum precipitation and the normalized maximum latent heat flux was identified. In general, large values of mesoscale latent heat flux imply strongly developed mesoscale circulations and intense cloud activity, accompanied by large surface latent heat fluxes that transport more water vapor into the atmosphere.

Chen, Fei↗
NASA NTRS1994

Temperature-moisture biases in ECMWF analyses based on clear sky longwave simulations constrained by SSMI and MSU measurements and comparisons to ERBE estimates

Clear sky longwave radiation fluxes for the summer of 1988 and winter of 1989 have been simulated with a radiative transfer model that includes detailed treatment of atmospheric gas absorption. The input data to the model are humidity and temperature profiles from European Center for Medium-Range Weather Forecasts (ECMWF) analyses and surface temperature measurements from the International Satellite Cloud Climatology Project. To reduce the inherent uncertainties in humidity profiles, the ECMWF moisture fields have been adjusted, based on the climatological relationship between the moisture profile and total precipitable water (PW), so that the ECMWF PW is equal to that derived from Special Sensor Microwave Imager (SSMI) data. SSMI and ECMWF PW patterns are generally similar, but significant differences in magnitude are found in the low latitudes, particularly over the subtropical oceans in the Southern Hemisphere. At the same time the tropospheric brightness temperature (T(sub B)) at 53.74 GHz has been computed using a microwave transfer model with ECMWF temperature and humidity fields as inputs. The comparison of computed T(sub B) with the Microwave Sounding Unit (MSU) channel 2 T(sub B) revealed differences larger than 1.5 K over most of the oceans, suggesting that the ECMWF model atmosphere has a cold bias. Maximum biases greater than 3 K are found in low latitudes. After removing the bias from the ECMWF temperature field, a new set of temperature profiles yielding brightness temperature equal to MSU channel 2 T(sub B) has been obtained. Simulation results clearly demonstrate that inclusion of satellite estimates of PW and T(sub B) enhances the accuracy of the clear sky LW flux simulation, substantially reducing the differences from Earth Radiation Budget Experiment (ERBE) estimates. Global averages indicate that the model-derived top-of-atmosphere (TOA) clear sky fluxes from the adjusted moisture and temperature profiles are in very good agreement with satellite-measured ERBE values, differing by only 1.4 W/sq m. By contrast, the calculation using only ECMWF analyses without any adjustments gives a significant underestimation of TOA clear sky fluxes up to 10.7 W/sq m compared to the satellite measurements, suggesting that the constraint method can significantly improve the accuracy in the radiation budget simulation. The results also indicate that the ECMWF-based simulation errors are, at least for the two seasons studied, mainly attributed to the error in the temperature field rather than to errors in the moisture field.

Sohn, Byung-Ju↗
NASA NTRS1995

Observation of local cloud and moisture feedbacks over high ocean and desert surface temperatures

New data on clouds and moisture, made possible by reanalysis of weather satellite observations, show that the atmosphere reacts to warm clusters of very high sea surface temperatures in the western Pacific Ocean with increased moisture, cloudiness, and convection, suggesting a negative feedback limiting the sea surface temperature rise. The reverse was observed over dry and hot deserts where both moisture and cloudiness decrease, suggesting a positive feedback perpetuating existing desert conditions. In addition, the observations show a common critical surface temperature for both oceans and land; the distribution of atmospheric moisture is observed to reach a maximum value when the daily surface temperatures approach 304 +/- 1 K. These observations reveal complex dynamic-radiative interactions where multiple processes act simultaneously at the surface as well as in the atmosphere to regulate the feedback processes.

Chahine, Moustafa T.↗
NASA NTRS1996

On Soil Moisture Retrieval and Target Decomposition

In an earlier study, an empirical model was developed to infer soil moisture and surface roughness from radar data. The inversion technique was extensively tested over bare surfaces by comparing the estimated soil moisture to in situ measurements. The overall root mean square (RMS) error in the soil moisture estimate was found to be about 3.5% and the RMS error in the RMS height estimate was less than 0.35 cm absolute for bare or slightly vegetated surfaces. However, inversion results indicate that significant amounts of vegetation cause the algorithm to underestimate soil moisture and overestimate RMS height. Among the areas over which the inversion cannot be applied, the areas with intermediate vegetation cover are of particular interest as both the vegetation and the underlying bare surface affect the backscatter. This paper concentrates mostly on these areas. Using the full polarimetric information and the Cloude target decomposition approach, three different components of the target backscattering can be isolated. One of these three components can be identified as the surface component in the case of intermediate vegetation cover. Once the surface component of the scattering is isolated, the bare surface inversion can then be applied.

Dubois, Pascale C.↗
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 NTRS1993

Microstrip Ring Resonator for Soil Moisture Measurements

Accurate determination of spatial soil moisture distribution and monitoring its temporal variation have a significant impact on the outcomes of hydrologic, ecologic, and climatic models. Development of a successful remote sensing instrument for soil moisture relies on the accurate knowledge of the soil dielectric constant (epsilon(sub soil)) to its moisture content. Two existing methods for measurement of dielectric constant of soil at low and high frequencies are, respectively, the time domain reflectometry and the reflection coefficient measurement using an open-ended coaxial probe. The major shortcoming of these methods is the lack of accurate determination of the imaginary part of epsilon(sub soil). In this paper a microstrip ring resonator is proposed for the accurate measurement of soil dielectric constant. In this technique the microstrip ring resonator is placed in contact with soil medium and the real and imaginary parts of epsilon(sub soil) are determined from the changes in the resonant frequency and the quality factor of the resonator respectively. The solution of the electromagnetic problem is obtained using a hybrid approach based on the method of moments solution of the quasi-static formulation in conjunction with experimental data obtained from reference dielectric samples. Also a simple inversion algorithm for epsilon(sub soil) = epsilon'(sub r) + j(epsilon"(sub r)) based on regression analysis is obtained. It is shown that the wide dynamic range of the measured quantities provides excellent accuracy in the dielectric constant measurement. A prototype microstrip ring resonator at L-band is designed and measurements of soil with different moisture contents are presented and compared with other approaches.

Sarabandi, Kamal↗
NASA NTRS1996

On Soil Moisture Retrieval and Target Decomposition

In an earlier study, an empirical model was developed to infer soil moisture and surface roughness from radar data. The inversion technique was extensively tested over bare surfaces by comparing the estimated soil moisture to in situ measurements. The overall RMS error in the soil moisture estimate was found to be 3.5% and the RMS error in the RMS height estimate was less than 0.35 cm absolute for bare or slightly vegetated surfaces. However, inversion results indicate that significant amounts of vegetation cause the algorithm to underestimate soil moisture and overestimate RMS height. Among the areas over which the inversion cannot be applied, the areas with intermediate vegetation cover are of particular interest as both the vegetation and the underlying bare surface affect the backscatter. This paper concentrates mostly on these areas. Using the full polarimetric information and the Cloude target decomposition approach. Three different components of the target backscattering can be isolated. One of these three components can be identified as the surface component in the case of intermediate vegetation cover. Once the surface component of the scattering is isolated, the bare surface inversion can then be applied.

Dubois, Pascale C.↗
NASA NTRS1999

Soil Moisture, Coastline Curvature, and Sea Breeze Initiated Precipitation Over Florida

Land surface-atmosphere interaction plays a key role in the development of summertime convection and precipitation over the Florida peninsula. Land-ocean temperature contrasts induce sea-breeze circulations along both coasts. Clouds develop along sea-breeze fronts, and significant precipitation can occur during the summer months. However, other factors such as soil moisture distribution and coastline curvature may modulate the timing, location, and intensity of sea breeze initiated precipitation. Here, we investigate the role of soil moisture and coastline curvature on Florida precipitation using the 3-D Goddard Cumulus Ensemble (GCE) cloud model coupled with the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model. This study utilizes data from the Convection and Precipitation Electrification Experiment (CaPE) collected on 27 July 1991. Our numerical simulations suggest that a realistic distribution of soil moisture influences the location and intensity of precipitation but not the timing of precipitation. In contrast, coastline curvature affects the timing and location of precipitation but has little influence on peak rainfall rates. However, both factors (soil moisture and coastline curvature) are required to fully account for observed rainfall amounts.

Baker, R. David↗
NASA NTRS1997

Estimation of Bare Surface Soil Moisture and Surface Roughness Parameter Using L-Band SAR Image Data

An algorithm based on a fit of the single-scattering Integral Equation Method (IEM) was developed to provide estimation of soil moisture and surface roughness parameter (a combination of rms roughness height and surface power spectrum) from quasi-polarized synthetic aperture radar (SAR) measurements. This algorithm was applied to a series of measurements acquired at L-band (1.25 GHz) from both AIRSAR (Airborne Synthetic Aperture Radar operated by Jet Propulsion Laboratory) and SIR-C (Spaceborne Imaging Radar-C) over a well-managed watershed in southwest Oklahoma. It was found that the two co-polarized backscattering coefficients and their combinations would provide the best input to the algorithm for estimation of soil moisture and roughness parameter. Application of the inversion algorithm to the co-polarized measurements of both AIRSAR and SIR-C resulted in estimated values of soil moisture and roughness parameter for bare and short-vegetated fields that compared favorably with those sampled on the ground. The root-mean-square (rms) errors of the comparison were found to be 3.4% and 1.9 dB for soil moisture and surface roughness parameter, respectively.

Shi, Jian-Cheng↗
NASA NTRS1997

The Impact of Microwave-Derived Surface Soil Moisture on Watershed Hydrological Modeling

The usefulness of incorporating microwave-derived soil moisture information in a semi-distributed hydrological model was demonstrated for the Washita '92 experiment in the Little Washita River watershed in Oklahoma. Initializing the hydrological model with surface soil moisture fields from the ESTAR airborne L-band microwave radiometer on a single wet day at the start of the study period produced more accurate model predictions of soil moisture than a standard hydrological initialization with streamflow data over an eight-day soil moisture drydown.

ONeill, P. E.↗
NASA NTRS2001

A Methodology for Surface Soil Moisture and Vegetation Optical Depth Retrieval Using the Microwave Polarization Difference Index

A methodology for retrieving surface soil moisture and vegetation optical depth from satellite microwave radiometer data is presented. The procedure is tested with historical 6.6 GHz brightness temperature observations from the Scanning Multichannel Microwave Radiometer over several test sites in Illinois. Results using only nighttime data are presented at this time, due to the greater stability of nighttime surface temperature estimation. The methodology uses a radiative transfer model to solve for surface soil moisture and vegetation optical depth simultaneously using a non-linear iterative optimization procedure. It assumes known constant values for the scattering albedo and roughness. Surface temperature is derived by a procedure using high frequency vertically polarized brightness temperatures. The methodology does not require any field observations of soil moisture or canopy biophysical properties for calibration purposes and is totally independent of wavelength. Results compare well with field observations of soil moisture and satellite-derived vegetation index data from optical sensors.

Owe, Manfred↗
NASA NTRS2004

Potential Predictability of U.S. Summer Climate with "Perfect" Soil Moisture

The potential predictability of surface-air temperature and precipitation over the United States continent was assessed for a GCM forced by observed sea surface temperatures and an estimate of observed ground soil moisture contents. The latter was obtained by substituting the GCM simulated precipitation, which is used to drive the GCM's land-surface component, with observed pentad-mean precipitation at each time step of the model's integration. With this substitution, the simulated soil moisture correlates well with an independent estimate of observed soil moisture in all seasons over the entire US continent. Significant enhancements on the predictability of surface-air temperature and precipitation were found in boreal late spring and summer over the US continent. Anomalous pattern correlations of precipitation and surface-air temperature over the US continent in the June-July-August season averaged for the 1979-2000 period increased from 0.01 and 0.06 for the GCM simulations without precipitation substitution to 0.23 and 0.3 1, respectively, for the simulations with precipitation substitution. Results provide an estimate for the limits of potential predictability if soil moisture variability is to be perfectly predicted. However, this estimate may be model dependent, and needs to be substantiated by other modeling groups.

Yang, Fanglin↗
NASA NTRS2002

[The evaluation of the error of the thermal pulse technique used to measure moisture content of root substrates in space greenhouse]

Point thermopulse probes were used to monitor moisture level in the root substrates during cultivation of higher plants in a space greenhouse. Investigated were performance data of the thermopulse moisture probe in integration with the space greenhouse. It was shown that within the substrate moisture range from 20 up to 100% of the full saturation the technique error does not exceed 1.5%. The thermopulse technique bears much promise for metrologic monitoring of the root substrate moisture content in space greenhouses no matter water and air supply technology.

Flight Experiment↗
NASA NTRS2003

Temperature and moisture conditions for life in the extreme arid region of the Atacama desert: four years of observations including the El Nino of 1997-1998

The Atacama along the Pacific Coast of Chile and Peru is one of the driest and possibly oldest deserts in the world. It represents an extreme habitat for life on Earth and is an analog for life in dry conditions on Mars. We report on four years (September 1994-October 1998) of climate and moisture data from the extreme arid region of the Atacama. Our data are focused on understanding moisture sources and their role in creating suitable environments for photosynthetic microorganisms in the desert surface. The average air temperature was 16.5 degrees C and 16.6 degrees C in 1995 and 1996, respectively. The maximum air temperature recorded was 37.9 degrees C, and the minimum was -5.7 degrees C. Annual average sunlight was 336 and 335 W m(-2) in 1995 and 1996, respectively. Winds averaged a few meters per second, with strong fohn winds coming from the west exceeding 12 m s(-1). During our 4 years of observation there was only one significant rain event of 2.3 mm, which occurred near midnight local time. We suggest that this event was a rainout of a heavy fog. It is of interest that the strong El Nino of 1997-1998 brought heavy rainfall to the deserts of Peru, but did not bring significant rain to the central Atacama in Chile. Dew occurred at our station frequently following high nighttime relative humidity, but is not a significant source of moisture in the soil or under stones. Groundwater also does not contribute to surface moisture. Only the one rain event of 2.3 mm resulted in liquid water in the soil and beneath stones for a total of only 65-85 h over 4 years. The paucity of liquid water under stones is consistent with the apparent absence of hypolithic (under-stone) cyanobacteria, the only known primary producers in such extreme deserts.

Biogenesis↗
NASA NTRS2005

A comparison of soil moisture sensors for space flight applications

Plants will be an important part of future long-term space missions. Automated plant growth systems require accurate and reliable methods of monitoring soil moisture levels. There are a number of different methods to accomplish this task. This study evaluated sensors using the capacitance method (ECH2O), the heat-pulse method (TMAS), and tensiometers, compared to soil water loss measured gravimetrically in a side-by-side test. The experiment monitored evaporative losses from substrate compartments filled with 1- to 2-mm baked calcinated clay media. The ECH2O data correlated well with the gravimetric measurements, but over a limited range of soil moisture. The averaged TMAS sensor data overstated soil moisture content levels. The tensiometer data appeared to track evaporative losses in the 0.5- to 2.5-kPa range of matric potential that corresponds to the water content needed to grow plants. This small range is characteristic of large particle media, and thus high-resolution tensiometers are required to distinguish changing moisture contents in this range.

NASA Center KSC↗