Zhang Li-xin

Improvement of snow depth retrieval for FY3B-MWRI in China

The primary objective of this work is to develop an operational snow depth retrieval algorithm for the FengYun3B Microwave Radiation Imager (FY3B-MWRI) in China. Based on 7-year (2002–2009) observations of brightness temperature by the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and snow depth from Chinese meteorological stations, we develop a semi-empirical snow depth retrieval algorithm. When its land cover fraction is larger than 85%, we regard a pixel as pure at the satellite passive microwave remote-sensing scale. A 1-km resolution land use/land cover (LULC) map from the Data Center for Resources and Environmental Sciences, Chinese Academy of Sciences, is used to determine fractions of four main land cover types (grass, farmland, bare soil, and forest). Land cover sensitivity snow depth retrieval algorithms are initially developed using AMSR-E brightness temperature data. Each grid-cell snow depth was estimated as the sum of snow depths from each land cover algorithm weighted by percentages of land cover types within each grid cell. Through evaluation of this algorithm using station measurements from 2006, the root mean square error (RMSE) of snow depth retrieval is about 5.6 cm. In forest regions, snow depth is underestimated relative to ground observation, because stem volume and canopy closure are ignored in current algorithms. In addition, comparison between snow cover derived from AMSR-E and FY3B-MWRI with Moderate-resolution Imaging Spectroradiometer (MODIS) snow cover products (MYD10C1) in January 2010 showed that algorithm accuracy in snow cover monitoring can reach 84%. Finally, we compared snow water equivalence (SWE) derived using FY3B-MWRI with AMSR-E SWE products in the Northern Hemisphere. The results show that AMSR-E overestimated SWE in China, which agrees with other validations.

A method to estimate crop effects at higher frequencies by modeling and microwave radiometric data

To use the 0th-order τ-ω model to retrieve soil moisture from radiometric data at frequencies higher than the C band, the characteristics of the effective single scattering albedo ω and the opacity τ of vegetation must be studied. In this paper, the ω and τ values of corn for the C, X, and Ku bands were retrieved by matching the simulations of a high-order matrix-doubling model to the τ-ω model. First, the brightness temperature of the matrix-doubling was validated by a truck-mounted radiometer in a field experiment, where the vegetation emission contributions were validated with aluminum foil to mask the soil emission. Then an emissivity database of corn fields for different growing seasons was established for a variety of soil conditions. With the transmissivity of corn determined from the database, the effective single scattering albedos of corn for different heights at the C, X, and Ku bands and at a 55° viewing angle were derived. To verify the accuracy of the derived ω and τ values, we used SMEX02/PSR aircraft data and the Qp model to retrieve the soil moisture; the RMSE between the retrieval and the measurements was 4.76% at the C band and 5.36% at the X band.

The coherent microwave emission of freezing soil: Experimental research and model simulation

Interference effect happens in layered medium. The brightness temperature oscillation has been observed during the freezing process of over-saturated soil, which could be explained by interference effect and a three layer coherent model. The modeled BT is qualitatively in consistent with the measurement. It is shown that the interference must be considered when measuring frozen soil with ground based microwave radiometer especially when using the frequency is low.

Simulation of the emission of frozen soil by using IEM

Seasonal freeze/thaw cycles of soils influence the ground thermal and hydrological characteristics, which have significant impact on the balance of heat and moisture at interface between soil and atmosphere. Microwave remote sensing of frozen soil is of primary importance. In this study, microwave emission of frozen soil was simulated for evaluating the surface and subsurface effect, including surface roughness and dielectric properties, on the brightness temperature at AMSR-E frequencies. First a dielectric constant model of frozen soil newly proposed was employed to obtain dielectric properties for frozen soil. We simulated the interface emission by using integral equation model (IEM) to reach the total emission. It is found that emission signatures of soil layer are quite different at frozen or thaw status at AMSR-E frequencies. The importance of each emission component was demonstrated at different frequencies and polarizations under different surface conditions.