Xiaolan Xu

The Effects of Layers in Dry Snow on Its Passive Microwave Emissions Using Dense Media Radiative Transfer Theory Based on the Quasicrystalline Approximation (QCA/DMRT)

A model for the microwave emissions of multilayer dry snowpacks, based on dense media radiative transfer (DMRT) theory with the quasicrystalline approximation (QCA), provides more accurate results when compared to emissions determined by a homogeneous snowpack and other scattering models. The DMRT model accounts for adhesive aggregate effects, which leads to dense media Mie scattering by using a sticky particle model. With the multilayer model, we examined both the frequency and polarization dependence of brightness temperatures (Tbs) from representative snowpacks and compared them to results from a single-layer model and found that the multilayer model predicts higher polarization differences, twice as much, and weaker frequency dependence. We also studied the temporal evolution of Tb from multilayer snowpacks. The difference between Tbs at 18.7 and 36.5 GHz can be 5 K lower than the single-layer model prediction in this paper. By using the snowpack observations from the Cold Land Processes Field Experiment as input for both multi- and single-layer models, it shows that the multilayer Tbs are in better agreement with the data than the single-layer model. With one set of physical parameters, the multilayer QCA/DMRT model matched all four channels of Tb observations simultaneously, whereas the single-layer model could only reproduce vertically polarized Tbs. Also, the polarization difference and frequency dependence were accurately matched by the multilayer model using the same set of physical parameters. Hence, algorithms for the retrieval of snowpack depth or water equivalent should be based on multilayer scattering models to achieve greater accuracy.

Electromagnetic Scattering by Bicontinuous Random Microstructures With Discrete Permittivities

For electromagnetic (EM) scattering by dense media, the traditional approach is to use particles of spheres or ellipsoids that are densely and randomly packed in a background medium. The particles have discrete permittivities that are different from the background medium. The dense-medium model has been applied to the microwave remote sensing of terrestrial snow. In this paper, we propose a different approach of using a bicontinuous medium with discrete permittivities and study the EM scattering properties using analytical and numerical methods. The bicontinuous medium is a continuous representation of interfaces between inhomogeneities within the medium. Discrete permittivities are then assigned to the inhomogeneities of the structure. The analytical approach is based on the Born approximation using the derived analytical correlation functions. The numerical method is based on the numerical Maxwell model of 3-D (NMM3D) approach. In particular, the discrete-dipole approximation and the conjugate gradient-squared method accelerated by the fast Fourier transform technique are used in solving the volume integral equation. Scattering results of analytical and numerical approaches are compared. Numerical results are illustrated using parameters in microwave remote sensing of terrestrial snow. In the NMM3D simulations, three kinds of convergence tests are conducted, viz., convergence with respect to the discretization size, convergence with respect to the sample size, and convergence with respect to the number of realization. The NMM3D results indicate that the scattering by the bicontinuous medium with a broader size distribution has a weaker frequency dependence than that by the medium with a more narrow size distribution. The frequency-dependence power law index can be lower than two, which is very much lower than the power of four in Rayleigh scattering. The NMM3D results also exhibit fairly large cross-polarization returns which account for the local nonisotropic microstructures of bicontinuous media, although the medium is statistically isotropic.

Models of L-Band Radar Backscattering Coefficients Over Global Terrain for Soil Moisture Retrieval

Physical models for radar backscattering coefficients are developed for the global land surface at L-band (1.26 GHz) and 40 ° incidence angle to apply to the soil moisture retrieval from the upcoming soil moisture active passive mission data. The simulation of land surface classes includes 12 vegetation types defined by the International Geosphere-Biosphere Programme scheme, and four major crops (wheat, corn, rice, and soybean). Backscattering coefficients for four polarizations (HH/VV/HV/350611873VH) are produced. In the physical models, three terms are considered within the framework of distorted Born approximation: surface scattering, double-bounce volume-surface interaction, and volume scattering. Numerical solutions of Maxwell equations as well as theoretical models are used for surface scattering, double-bounce reflectivity, and volume scattering of a single scatterer. To facilitate fast, real-time, and accurate inversion of soil moisture, the outputs of physical model are provided as lookup tables (with three axes; therefore called datacube). The three axes are the real part of the dielectric constant of soil, soil surface root mean square (RMS) height, and vegetation water content (VWC), each of, which covers the wide range of natural conditions. Datacubes for most of the classes are simulated using input parameters from in situ and airborne observations. This simulation results are found accurate to the co-pol RMS errors of to 3.4 dB (six woody vegetation types), 1.8 dB (grass), and 2.9 dB (corn) when compared with airborne data. Validated with independent spaceborne phased array type L-band synthetic aperture radars and field-based radar data, the datacube errors for the co-pols are within 3.4 dB (woody savanna and shrub) and 1.5 dB (bare surface). Assessed with spaceborne Aquarius scatterometer data, the mean differences range from ~ 1.5 to 2 dB. The datacubes allow direct inversion of sophisticated forward models without empirical parameters or formulae. This capability is evaluated using the time-series inversion algorithm over grass fields.

Electromagnetic Computation in Scattering of Electromagnetic Waves by Random Rough Surface and Dense Media in Microwave Remote Sensing of Land Surfaces

Active and passive microwave remote sensing has been used for monitoring the soil moisture and snow water equivalent. In the interactions of microwaves with bare soil, the effects are determined by scattering of electromagnetic waves by random rough surfaces. In the interactions of microwaves with terrestrial snow, the effects are determined by volume scattering of dense media characterized by densely packed particles. In this paper, we review the electromagnetic full-wave simulations that we have conducted for such problems. In volume scattering problems, one needs many densely packed scatterers in a random medium sample to simulate the physical solutions. In random rough surface scattering problems, one needs many valleys and peaks in the sample surface. In random media and rough surface problems, the geometric characterizations of the media and computer generations of statistical samples of the media are also challenges besides electromagnetic computations. In the scattering of waves by soil surfaces, we consider the soil to be a lossy dielectric medium. The random rough surface is characterized by Gaussian random processes with exponential correlation functions. Surfaces of exponential correlation functions have fine-scale structures that cause significant radar backscattering in active microwave remote sensing. Fine-scale features also cause increase in emission in passive microwave remote sensing. We apply Monte Carlo simulations of solving full 3-D Maxwells equations for such a problem. A hybrid UV/PBTG/SMCG method is developed to accelerate method of moment solutions. The results are illustrated for coherent waves and incoherent waves. We also illustrate bistatic scattering, backscattering, and emissivity which are signatures measured in microwave remote sensing. For the case of scattering by terrestrial snow, snow is a dense medium with densely packed ice grains. We have used two models: densely packed particles and bicontinuous media. For the case of densely packed particles, we used the Metropolis shuffling method to simulate the positions of particles. The particles are also allowed to have adhesive properties. The Foldy-Lax equations of multiple scattering are used to study scattering from the densely packed spherical particles. The results are illustrated for the coherent waves and incoherent waves. For the case of bicontinuous media, the method developed by Cahn is applied to construct the interfaces from a large number of stochastic sinusoidal waves with random phases and directions. The volume scattering problem is then solved by using CGS-FFT. We illustrate the results of frequency and polarization dependence of such dense media scattering.

Electromagnetic Models of Co/Cross Polarization of Bicontinuous/DMRT in Radar Remote Sensing of Terrestrial Snow at X- and Ku-band for CoReH2O and SCLP Applications

In this paper, we study the scattering properties of the terrestrial dry snow by modeling the snow structure as Bi-continuous media. The model is applied to study the snow scattering characteristics at X-band and Ku-band that are two frequencies in the proposed Cold Regions Hydrology High-resolution Observatory (CoReH2O) mission by ESA and the proposed Snow and Cold Land Process (SCLP) mission by NASA. There are two variables in the Bi-continuous media that can be adjusted to generate various snow microstructures. The different snow structures are illustrated. The extinction properties and phase matrices are studied through the Monte Carlo simulations. For each realization, the Maxwell Equations are solved numerically to take into account the coherent wave interactions among the inhomogeneties. We demonstrated the frequency dependences of scattering coefficients, which can vary depending on the setup parameters of the bicontinuous media. The power law are compared with experiment data of extinction coefficients of terrestrial snow. The calculated extinction and phase matrices are combined in the Dense Media Radiative Transfer theory (DMRT). We obtain the 1st order solution by using the iterative method. The surface scattering from the snow-ground interface is included by searching the look up table of NMM3D. The results of co-polarization and cross polarization are compared with the POLSCAT Ku-band airborne data and X-band TerraSAR-X satellite data in North Slope, Alaska.

Dense Media Radiative Transfer Applied to SnowScat and SnowSAR

The dense media radiative transfer (DMRT) theory is applied to data analysis of recent measurements of multifrequency microwave backscatter from the snow cover on earth. Measurement includes ground-based campaign (SnowScat) and airborne mission (SnowSAR). Both the quasi-crystalline approximation (QCA) model and the bicontinuous model are used for a multilayer snow medium. Two size parameters are used for both models. Grain size and stickiness parameter are used for QCA model. The bicontinuous model has two parameters: the mean wave number 〈ζ〉 and the parameter b. The mean wave number 〈ζ〉 corresponds to the inverse of the grain size, while the b parameter controls the width of the wave number distribution and is related to the clustering property. The bicontinuous model is used to generate the microstructures of snow by computer, and Maxwell equations are solved numerically for each sample of computer-generated structure to calculate the extinction coefficient and the phase matrix. Other geometric descriptors of the bicontinuous medium include correlation functions and specific surface areas, both of which can be calculated from the parameters 〈ζ〉 and b. In making comparisons, we use ground measurements of specific surface area, grain size, densities, and layering of snow cover as input for the theoretical models. The geometric properties and the scattering properties of the bicontinuous model are also compared with past models. In making the multifrequency comparisons, we use the same physical parameters of all three frequencies: 1) X band; 2) Ku bands of 13.3 GHz; and 3) 16.7 GHz. It is emphasized that the DMRT models provide frequency, size, and angular dependence that depart from the classical model of Rayleigh scattering and are in better agreement with experimental observations.

Active and Passive Vegetated Surface Models With Rough Surface Boundary Conditions From NMM3D

In this paper, we derive an expression of the brightness temperatures of a vegetated surface based on the tau-omega model with the rough surface boundary condition that replaces the conventional exp(-h) model by NMM3D (Numerical Simulations of 3D Maxwell equations). A purpose of the paper is that the same physical rough surface scattering model based on NMM3D and the same physical parameters of rms heights and correlation lengths can be used for both passive and active remote sensing of the same scene of vegetated surfaces. The bistatic scattering of rough surfaces are decomposed into the coherent wave and the co-polarization and the cross-polarization of the incoherent waves to quantify the contribution of each of these components. Numerical results are illustrated for a variety of roughness conditions. Comparisons are made with the exp(-h) model. Results are compared with the experimental passive measurements of PORTOS 1993 for bare soil cases. Data cubes for grassland are calculated for both active and passive signatures at L band. Comparisons are then made with the L band PALS data for the grassland of SGP99 using these data cubes.

Modeling multi-layer effects in passive microwave remote sensing of dry snow using Dense Media Radiative Transfer Theory (DMRT) based on quasicrystalline approximation

The Dense Media Radiative Transfer theory (DMRT) of Quasicrystalline Approximation of Mie scattering by sticky particles is used to study the multiple scattering effects in layered snow in microwave remote sensing. Results are illustrated for various snow profile characteristics. Polarization differences and frequency dependences of multilayer snow model are significantly different from that of the single-layer snow model. Comparisons are also made with CLPX data using snow parameters as given by the VIC model.

Microwave Scattering and Medium Characterization for Terrestrial Snow With QCA–Mie and Bicontinuous Models: Comparison Studies

Comparison studies are made between the QCA-Mie model and the bicontinuous model in microwave scattering from terrestrial snow. Both the scattering properties and the medium characterization are compared. For QCA, we use the multisize and the sticky particle models. For the bicontinuous model, we use the probability distribution function for the wavenumber. We compare the scattering rate and the angular distribution of scattering using the mean cosine of scattering and show that the two models have similar properties. In medium characterization, we use the pair distribution functions used in QCA to derive the correlation functions. We show that both the Percus-Yevick pair functions and the bicontinuous model have tails in the correlation functions that are distinctly different from the traditional exponential correlation functions. The methodologies of using ground measurements of grain size distributions and correlation functions to obtain model parameters are addressed.

Freeze/Thaw Detection and Validation Using Aquarius’ L-Band Backscattering Data

The seasonal cycle of landscape freeze/thaw (FT) state across mid- to high latitudes influences critical processes such as the land surface energy balance, carbon cycle dynamics related to vegetation growth, and hydrological partitioning between surface runoff and infiltration. In this paper, we produce the first daily FT classification for the 2011-2014 period based on L-band radar measurements from Aquarius. The radar FT algorithm used in this paper is based on a seasonal threshold approach, which is also the baseline algorithm applied to higher-resolution (3 km) radar measurements from NASAs Soil Moisture Active/Passive (SMAP) mission (Launched January 31, 2015). The lower frequency (L-band) radar backscatter measurements from Aquarius provide enhanced sensitivity to FT conditions in vegetation canopy, snow and surface soil layers, although the relative radar penetration depth and sensitivity of the FT signal to these landscape elements will vary according to surface moisture and vegetation biomass conditions, and underlying land cover and terrain heterogeneity [1], [2]. Evaluation of the seasonal threshold FT algorithm using Aquarius was performed using surface air and soil temperatures from selected stations in the Snow Telemetry (SnoTel) network. Analysis identified good agreement during the fall freeze-up period with flag agreement exceeding the 80% SMAP accuracy target when summarized on a monthly basis. Disagreement was greater during the spring thaw transition due in part to uncertainty in characterizing thaw from in situ measurements. Unlike the fall season, stronger agreement in the spring was identified when the reference state was characterized with air temperature compared to soil temperature.