Thomas J. Schmugge

New Mexico State University

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Thomas J. Jackson

United States Department of Agriculture

William P. Kustas

Agricultural Research Service

Andrew N. French

Agricultural Research Service

A. Rango

Agricultural Research Service

James R. Wang

Goddard Space Flight Center

Kenta Ogawa

Honda (Japan)

T. J. Jackson

Agricultural Research Service

Tsan Mo

NOAA National Environmental Satellite Data and Information Service

Jerry C. Ritchie

Beltsville Agricultural Research Center

Frédéric Jacob

Institut de Recherche pour le Développement

Cooperative Institutions

Agricultural Research Service

Goddard Space Flight Center

United States Department of Agriculture

Centre National de la Recherche Scientifique

Beltsville Agricultural Research Center

University of Maryland, College Park

Texas A&M University

Center For Remote Sensing (United States)

Naval Research Laboratory Information Technology Division

Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement

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Microwave Emission From Snow and Glacier Ice

Journal of Glaciology (1976)

Tzu‐Ching Chang P. Gloersen Thomas J. Schmugge T. T. Wilheit H. Jay Zwally

Abstract The microwave emission from a model snow field, consisting of randomly spaced ice spheres which scatter independently, is calculated. Mie scattering and radiative transfer theory are applied in a manner similar to that used in calculating microwave and optical properties of clouds. The extinction coefficient is computed as a function of both microwave wavelength and ice-particle radius. Volume scattering by the individual ice particles in the snow field significantly decreases the computed emission for particle radii greater than a few hundredths of the microwave wavelength. Since the mean annual temperature and the accumulation rate of dry polar firn mainly determine the grain sizes upon which the microwave emission depends, these two parameters account for the main features of the 1.55 cm emission observed from Greenland and Antarctica with the Nimbus-5 scanning radiometer. For snow particle sizes normally encountered, most of the calculated radiation emanates from a layer on the order of 10 m in thickness at a wavelength of 2.8 cm, and less at shorter wavelengths. A marked increase in emission from wet versus dry snow is predicted, a result which is consistent with observations. The model results indicate that the characteristic grain sizes in the radiating layers, dry-firn accumulation rales, areas of summer melting, and physical temperatures, can be determined from multispectral microwave observations.

Firn

Accumulation zone

10.1017/s0022143000031415

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Citations (241)

SOIL MOISTURE VARIATION PATTERNS OBSERVED IN HAND COUNTY, SOUTH DAKOTA¹

JAWRA Journal of the American Water Resources Association (1982)

Manfred Owe E. Bruce Jones Thomas J. Schmugge

ABSTRACT: Sail moisture data were taken during nine sampling events (1976‐1978) at a test site in South Dakota as part of the ground truth used in NASA's aircraft experiments studying the microwave sensing of soil moisture. This portion of the study dealt only with the spatial variability observed with regard to the ground data. Samples were taken over three surface depths at each point, and the data reported as the mean field moisture content within each of three surface horizons. The results shed additional light on the relationship between ground sampling and remote sensing of soil moisture. First, it was found that it is best to partition data of well drained sites from poorly drained areas when attempting to characterize the surface moisture content throughout an area of varying soil and cover conditions. It was also found that the moisture coefficient of variation within a field decreased as the mean field soil moisture increased, and that the standard deviation was at a maximum in the mid‐range of observed moisture conditions (15‐25 percent). Within field sample variation also decreases as the sample is integrated over a greater surface depth. It was determined that a sampling intensity of 10 samples per kilometer was adequate to characterize the mean field soil moisture at all three depths along a transect in the areas of moderate to good drainage‐.

10.1111/j.1752-1688.1982.tb00100.x

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A Parameterization of the Effect of Surface Roughness on Microwave Emission

IEEE Transactions on Geoscience and Remote Sensing (1987)

Tsan Mo Thomas J. Schmugge

A simple model is developed to represent the net effect of surface roughness on the microwave emission from soils. The reflectivity of a rough soil surface is defined in a theoretical model that includes both coherent and incoherent reflectivities in terms of the statistical properties of the rough surface, i.e., the surface height standard deviation σ and its horizontal correlation length l. It is shown that the rough surface reflectivity obtained from this theoretical model can be presented in a form that is simply the reflectivity R o of a smooth surface attenuated by a "rough thickness" G. It is found that the rough thickness G can be parameterized as a function of the statistical slope ratio m (=σ/l) of a rough surface by a simple power-law relationship. Since the slope of a rough surface can be determined experimentally, the rough thickness G can be quantitatively estimated from the parametric representation. Model calculations show that this simple model can provide reasonably accurate results of predicted brightness temperatures that agree well with field measurements within experimental uncertainty.

Rough surface

10.1109/tgrs.1987.289860

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Observations of coherent emissions from soils

Radio Science (1998)

Thomas J. Schmugge Thomas J. Jackson Peggy O’Neill M. B. Parlange

Observations of the microwave emissions at 1.413 GHz (L band) and 2.65 GHz (S band) from a silt loam soil exhibited an oscillatory behavior in time as the soil was being irrigated. The oscillations are attributed to interference between reflections from the air‐soil interface and the wet soil‐dry soil interface as the latter moved down in the soil. The magnitude of the first oscillation at L band was 56 K, and at S band it was 40 K, with oscillation damping out after about three cycles to the brightness temperature expected for the wet soil. The emission was modeled using a coherent model, and the results show qualitative and quantitative agreement with the observations.

Oscillation (cell signaling)

Silt

10.1029/97rs02614

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Calculations of the Microwave Brightness Temperature of Rough Soil Surfaces: Bare Field

IEEE Transactions on Geoscience and Remote Sensing (1987)

Tsan Mo Thomas J. Schmugge James R. Wang

A model for simulating the remotely sensed microwave brightness temperatures of soils with rough surfaces is developed. The surface emissivity of the soil media is calculated from one minus its reflectivity, which is obtained by the integration of the bistatic scattering coefficients for rough soil surfaces. The soil brightness temperature is obtained from the product of the surface emissivity and the effective soil temperature, which is calculated with measured soil moisture profiles and soil temperature profiles at various soil depths. The roughness of a soil surface is characterized by two parameters, the surface height standard deviation a and its horizontal correlation length l. The model calculations are compared to the measured angular variations of the polarized brightness temperatures at both L-band (1.4 GHz) and C-band (5 GHz) frequencies. A nonlinear least squares fitting method is used to match the model calculations with the data, and the best fit results produce the parameter values of a and l that best characterize the surface roughness. The effect of rough surface shadowing is also incorporated into the model by introducing a shadowing function S(θ), which represents the probability that a point on a rough surface is not shadowed by other parts of the surface. The model results for horizontal polarization are in excellent agreement with the data, both qualitatively and quantitatively. For vertical polarization, some discrepancies exist between the calculations and data. Possible causes of the discrepancy are discussed.

10.1109/tgrs.1987.289780

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Combining Optical and Microwave Remote Sensing for Mapping Energy Fluxes in a Semiarid Watershed

Remote Sensing of Environment (1998)

William P. Kustas Xiwu Zhan Thomas J. Schmugge

Bowen ratio

10.1016/s0034-4257(97)00176-4

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Citations (97)

Correction to ‘Passive microwave sensing of soil moisture under vegetation canopies’ by Thomas J. Jackson, Thomas J. Schmugge, and James R. Wang

Water Resources Research (1983)

Thomas J. Jackson Thomas J. Schmugge James R. Wang

10.1029/wr019i001p00297

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Remote estimation of soil moisture availability and fractional vegetation cover for agricultural fields

Agricultural and Forest Meteorology (1990)

Toby N. Carlson Eileen M. Perry Thomas J. Schmugge

Radiometric dating

Radiometry

Plant cover

10.1016/0168-1923(90)90100-k

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Citations (268)

Remote sensing of stored precipitation, i.e., soil moisture and snow

Thomas J. Schmugge

The characteristics and performance of spaceborne precipitation radar systems are discussed. The development of a model is discussed. Examples of simulation results are given. It was found that the accuracy of rain rate estimates is improved by using higher resolution radar.

Rain rate

Source

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Parameterization of Surface Heat Fluxes Above a Forest with Satellite Thermal Sensing

Wilfried Brutsaert A.Y. Hsu Thomas J. Schmugge

The authors discuss the feasibility of determining the surface flux of sensible heat from forests with surface temperatures measured by satellites together with temperature soundings in the unstable atmospheric boundary layer (ABL). The latent heat flux is derived from the sensible heat flux by means of the energy budget. The study makes use of data collected during HAPEX-MOBILHY (Hydrologic Atmospheric Pilot Experiment-Modelization du Bilan Hydrique). The methodology is based on turbulence similarity for the unstable ABL. The surface temperature data were derived from measurements by the advanced very high resolution radiometer (AVHRR) aboard the NOAA-9 satellite; the atmospheric profiles were obtained by radiosondes.

Advanced very-high-resolution radiometer

Atmospheric models

10.1109/igarss.1992.578500

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