Anthony W. England

Special problems in the estimation of power-law spectra as applied to topographical modeling

An increasing number of topographical studies find that natural surfaces possess power-law roughness spectra. Power-law spectra introduce unique difficulties in the spectral estimation process. The authors describe how an improper window choice allows leakage that yields a spectral estimate that is insensitive to the spectral slope. In addition, the commonly used Fourier-based spectral estimates have higher variances than other available estimators. Higher variance is particularly problematic when data records are short, as is often the case in remote sensing studies. The authors show that Capons spectral estimator has less variance than Fourier-based estimators and measures the spectral slope more accurately. The authors also show how estimates of a 2D roughness spectrum can be obtained from estimates of the 1D spectrum for the isotropic power-law case. >

Radiobrightness decision criteria for freeze/thaw boundaries

A freeze indicator (FI), based on a low 37-GHz radiobrightness and a low 10.7, 18, and 37-GHz radiobrightness spectral gradient, has been used to classify frozen surfaces in the northern Great Plains. By modeling the radiometer beampatterns as Gaussian, freeze/thaw boundaries can be located at the (fine) resolution of the 37-GHz channel. The performance of the freeze indicator, and subsequent boundary location estimate, depends on the accuracy of the boundary decision criteria. It is shown that decision criteria based on clustering and unsupervised classification yield good performance. A simple algorithm for registering coarse-resolution FI boundaries to equivalent boundaries in fine-resolution 37-GHz radiobrightness images is also presented. >

A land surface process/radiobrightness model with coupled heat and moisture transport for prairie grassland

The authors present a biophysically based, one-dimensional hydrology/radiobrightness (1dWR) model for prairie grassland that is subject to solar heating, radiant heating and cooling, precipitation, and sensible and latent heat exchanges with the atmosphere. The 1dH/R model consists of two modules, a one-dimensional hydrology (1dH) module that estimates the temperature and moisture profiles of the soil and the canopy and a microwave emission module that predicts radiobrightness (R). The authors validate the 1dH/R model by comparing its predictions with data from a field experiment. The model was forced by meteorological and sky radiance data from their Radiobrightness Energy Balance Experiment (REBEX-1) on prairie grassland near Sioux Falls, SD, during the fall and winter of 1992-1993. Model predictions were compared with 995 consecutive REBEX-1 observations over a 14-day period in October. Average errors (predicted-measured) for canopy temperature are 1.1 K with a variance of 3.72 K/sup 2/, for soil temperatures at 2-, 4-, 8-, 16-, 32-, and 64-cm depths are 2 K with a variance of 4 K/sup 2/, and for H-polarized brightnesses are 0.06 K with a variance of 1.30 K/sup 2/ at 19 GHz and 6.01 K with a variance of 6.04 K/sup 2/ at 37 GHz. The model overestimates the 37-GHz brightness because they have not included scatter darkening within the vegetation canopy in the model. They use the 1dH/R model to simulate a 60-day dry-down of prairie grassland in summer. For grass with a column density of 3.7 kg/m/sup 2/ and soil with an initially uniform moisture content of 38% by volume, the upper 5 mm of soil dries to 27% by the end of the simulation. The corresponding L-band brightness increases from an initial 143 K to a final 163 K. In contrast, none of the special sensor microwave/imager (SSM/I) radiobrightnesses nor the radiobrightness thermal inertia (RTI) technique, either at L-band or at any SSM/I frequency, exhibits significant sensitivity to the soil dry-down.

Vegetation canopy anisotropy at 1.4 GHz

We investigate anisotropy in 1.4-GHz brightness induced by a field corn vegetation canopy. We find that both polarizations of brightness are isotropic in azimuth during most of the growing season. When the canopy is senescent, the brightness is a strong function of row direction. On the other hand, the 1.4-GHz brightness is anisotropic in elevation: an isotropic zero-order radiative transfer model could not reproduce the observed change in brightness with incidence angle. Significant scatter darkening was found. The consequence of unanticipated scatter darkening would be a wet bias in soil moisture retrievals through a combination of underestimation of soil brightness (at H-pol) and underestimation of vegetation biomass (at V-pol). A new zero-order parameterization was formulated by allowing the volume scattering coefficient to be a function of incidence angle and polarization. The small magnitude of the scattering coefficients allows the zero-order model to retain its limited physical significance.

A land-surface process/radiobrightness model with coupled heat and moisture transport for freezing soils

Phase change of water is an important sink and source of energy and moisture within soils as well as a significant influence upon soil temperature and moisture profiles. These profiles play a crucial role in governing energy and moisture fluxes between bare soils and the atmosphere. They also codetermine radiobrightness, so that the difference between modeled and observed radiobrightness becomes a measure of error in a models estimate of temperature or moisture. The authors present a physically based, coupled-heat and moisture-transport, one-dimensional hydrology/radiobrightness (1 dH/R) model for bare, freezing and thawing, moist soils that are subject to insolation, radiant heating and cooling, and sensible and latent heat exchanges with the atmosphere. They use this model to examine thermal, hydrologic, and Special Sensor Microwave/Imager (SSMI) radiobrightness signatures for a three-month, dry-down simulation in the fall and winter of the northern United States Great Plains as part of an investigation of the effects of coupling heat and moisture transport. Given a typical initial moisture content of 38%, they find that coupled transport results in a reduction of ice in the surface soil by 21%. The range of diurnal variations in temperature are not significantly affected by coupled transport. Diurnal variations in the 19-GHz, H-polarized radiobrightness can be greater in the coupled transport case by 37 K. Total diurnal variation can exceed 57 K during periods of diurnal freezing and thawing.

Freeze/thaw classification for prairie soils using SSM/I radiobrightnesses

Data from the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) have been used to classify snow-free soils in the northern Great Plains as either frozen or thawed. The technique is based on differing sensitivities among SMMR radiobrightness frequencies to liquid moisture and volume scattering in the upper few millimeters of bare soil. The SMMR is no longer active. A current near-equivalent is the Special Sensor Microwave/Imager (SSM/I). The authors demonstrate that SSM/I radiobrightnesses also exhibit differential sensitivities to liquid water and volume scattering in frozen soil despite their higher frequencies. They find that the best classification discriminants for SSM/I data are a combination of the 37-GHz V-pol radiobrightnesses and the 19-to-37-GHz V-pol spectral gradients. They also examine the sensitivity of the classification to atmospheric emission and absorption and find little effect.

A land surface process/radiobrightness model with coupled heat and moisture transport in soil

Heat and moisture transport in soil are coupled processes that jointly determine temperature and moisture profiles. The authors present a physically based, one-dimensional (1D), coupled heat and moisture transport hydrology (1-DH) model for bare, unfrozen, moist soils subject to insolation, radiant heating and cooling, and sensible and latent heat exchanges with the atmosphere. A 60-day simulation is conducted to study the effect of dry-down on soil temperature and moisture distributions in summer for bare soil in the Midwest United States. Given a typical initial moisture content of 38% by volume, the authors find that temperature differences between the water transport and no water transport cases exhibit a diurnal oscillation with a slowly increasing amplitude, but never exceed 4.4 K for the 60-day period. However, moisture content of the surface decreases significantly with time for the water transport case and becomes only about 21% at the end of the same period. The 1-DH model is linked to a radiobrightness (1-DH/R) model as a potential means for soil moisture inversion. The model shows that radiobrightness thermal inertia (RTI) correlates with soil moisture if the two radiobrightnesses are taken from times near the thermal extremes, e.g., 2 a.m. and 2 p.m., and that RTI appears temperature-dependent at the ending stages of the drydown simulations where soils are dry and their moisture contents vary slowly. Near times of thermal crossover, the RTI technique is insensitive to soil moisture.

Sensitivity of a 1.4 GHz direct-sampling digital radiometer

This paper presents a novel direct RF sampling receiver architecture that will greatly facilitate the implementation of higher spatial resolution satellite radiometers for improved near-term climate forecasting. Direct-sampling is especially suitable for integration onto the distributed, multiple element platform used in L-band synthetic thinned array radiometry (STAR). To evaluate the direct-sampling concept, the authors have developed a statistical model that predicts the worst case radiometric sensitivity for a 1.4 GHz digital receiver. Theoretical results show that only 2-3 bits of converter resolution are needed to approach the performance of an ideal analog radiometer and that sampling jitter will not significantly degrade the performance of STAR.

Mapping freeze/thaw boundaries with SMMR data

Abstract Nimbus 7 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, ∂T b ∂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.

Brightness Temperatures of Snow Melting/Refreezing Cycles: Observations and Modeling Using a Multilayer Dense Medium Theory-Based Model

The ability of electromagnetic models to accurately predict microwave emission of a snowpack is complicated by the need to account for, among other things, nonindependent scattering by closely packed snow grains, stratigraphic variations, and the occurrence of wet snow. A multilayer dense medium model can account for the first two effects. While microwave remote sensing is well known to be capable of binary wet/dry discrimination, the ability to model brightness as a function of wetness opens up the possibility of ultimately retrieving a percentage wetness value during such hydrologically significant melting conditions. In this paper, the first application of a multilayer dense medium radiative transfer theory (DMRT) model is proposed to simulate emission from both wet and dry snow during melting and refreezing cycles. Wet snow is modeled as a mixture of ice particles surrounded by a thin film of water embedded in an air background. Melting/refreezing cycles are studied by means of brightness temperatures at 6.7, 19, and 37 GHz recorded by the University of Michigan Truck-Mounted Radiometer System at the Local Scale Observation Site during the Cold Land Processes Experiment-1 in March 2003. Input parameters to the DMRT model are obtained from snow pit measurements carried out in conjunction with the microwave observations. The comparisons between simulated and measured brightness temperatures show that the electromagnetic model is able to reproduce the brightness temperatures with an average percentage error of 3% (~8 K) and a maximum relative percentage error of around 8% (~20 K)