A radiative transfer model for simulating the measured brightness temperatures over vegetation‐covered fields is studied. The model treats the vegetation as a uniform layer, or canopy, with a constant temperature over a moist soil which emits polarized microwave radiation. The equation of radiative transfer is solved analytically subject to boundary conditions at the soil surface and canopy top. Scattering by the vegetation is primarily in the forward direction and given by a single scattering albedo ω*. The effect of soil surface roughness is introduced by modifying the smooth surface reflectivity with a roughness height parameter h and polarization mixing factor Q. The analytic formula for the microwave emission has four parameters, h, Q, τ0* (effective canopy optical thickness), and ω*. The model provides a good representation of the observed angular variations for both the horizontally and vertically polarized brightness temperatures at 1.4 GHz and 5 GHz frequencies over fields covered with grass, soybean, and corn. The effective canopy optical thickness is found to be directly proportional to the amount of water present in the vegetation canopy, while the effective canopy single scattering albedo depends on the type of vegetation.

An algorithm for estimating moisture content of a bare soil from the observed brightness temperature at 1.4 GHz is discussed and applied to a limited data base. The method is based on a radiative transfer model calculation, which has been successfully used in the past to account for many observational results, with some modifications to take into account the effect of surface roughness. Besides the measured brightness temperatures, the three additional inputs required by the method are the effective soil thermodynamic temperature, the precise relation between moisture content and the smooth field brightness temperatures and a pair of parameters related to surface roughness. The procedures of estimating surface roughness parameters and of obtaining moisture content from observed brightness temperature are discussed. The algorithm is applied to observations from truck mounted and airborne radiometers. The estimated moisture contents compare favorably with the observations in the top 2 cm layer.

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In this study, we present an improved physical model to retrieve snowfall rate over land using brightness temperature observations from the National Oceanic and Atmospheric Administration's (NOAA) Advanced Microwave Sounder Unit-B (AMSU-B) at 89 GHz, 150 GHz, 183.3±1 GHz, 183.3±3 GHz, and 183.3±7 GHz. The retrieval model is applied to the New England blizzard of March 5, 2001 which deposited about 75 cm of snow over much of Vermont, New Hampshire, and northern New York.In this improved physical model, prior retrieval assumptions about snowflake shape, particle size distributions, environmental conditions, and optimization methodology have been updated. Here, single scattering parameters for snow particles are calculated with the Discrete-Dipole Approximation (DDA) method instead of assuming spherical shapes.Five different snow particle models (hexagonal columns, hexagonal plates, and three different kinds of aggregates) are considered. Snow particle size distributions are assumed to vary with air temperature and to follow aircraft measurements described by previous studies.Brightness temperatures at AMSU-B frequencies for the New England blizzard are calculated using these DDA calculated single scattering parameters and particle size distributions. The vertical profiles of pressure, temperature, relative humidity and hydrometeors are provided by MM5 model simulations. These profiles are treated as the a priori data base in the Bayesian retrieval algorithm. In algorithm applications to the blizzard data, calculated brightness temperatures associated with selected database profiles agree with AMSU-B observations to within about ±5 K at all five frequencies.Retrieved snowfall rates compare favorably with the near-concurrent National Weather Service (NWS) radar reflectivity measurements. The relationships between the NWS radar measured reflectivities Z e and retrieved snowfall rate R for a given snow particle model are derived by a histogram matching technique. All of these Z e -R relationships fall in the range of previously established Z e -R relationships for snowfall. This suggests that the current physical model developed in this study can reliably estimate the snowfall rate over land using the AMSU-B measured brightness temperatures.1

Remote measurements of soil moisture contents over bare fields and fields covered with orchard grass, corn, and soybean were made during October 1979 with 1.4 GHz and 5 GHz microwave radiometers mounted on a truck. Ground truth of soil moisture content, ambient air and soil temperatures was acquired concurrently with the radiometric measurements. The biomass of the vegetation was sampled about once a week. The measured brightness temperatures over bare fields were compared with those of radiative transfer model calculations using as inputs the acquired soil moisture and temperature data with appropriate values of dielectric constants for soil‐water mixtures. Good agreement was found between the calculated and the measured results over 10°‐70° incident angles. The presence of vegetation was found to reduce the sensitivity of soil moisture sensing. At 1.4 GHz the sensitivity reduction ranged from ∼20% for 10‐cm tall grassland to over 60% for the dense soybean field. At 5 GHz the corresponding reduction in sensitivity ranged from ∼70% to ∼90%.