Investigation of the Sensitivity of Microwave Land Surface Emissivity to Soil Texture in MLEM

Abstract

This study analyzes the spectral characteristics of desert surface emissivity according to soil classification and the influence of mineral materials and soil texture information using simulation results from the microwave land emissivity model (MLEM). It also aims at exploring the feasibility of reducing the simulation error in MLEM by refining the soil classification characteristic parameters (such as soil composition content, distribution of particle size, etc.). The surface emissivity of the Taklimakan Desert is derived, to our knowledge for the first time, from FY-3B/MWRI (FengYun-3B Microwave Radiation Imager), and then the spectral characteristics of the study area for different soil types are further analyzed according to soil classification. In addition, emissivity spectra of the four most widely mineral materials in the desert area are reproduced using an MLEM under different conditions. Results showed that microwave land emissivity is highly correlated with the soil type and changes are markedly affected by the soil water content, soil texture, mineral composition, and soil particle size. For the desert soil, the emissivity of horizontal/vertical polarization is affected by the frequency in those soils dominated by large-size particles. However, for those dominated by smaller particles, the surface emissivity is almost constant or appears to be somehow dependent on the frequency. Moreover, the season effect on emissivity characteristics is clear, especially for soils composed of small-size particles. The emissivity of horizontal polarization shows stronger seasonal variation than that of vertical polarization. The study findings also showed that refining soil texture information (soil component content, distribution of particle size) improves the simulation accuracy in desert areas. For example, for the soil dominated by clay and clay loam, the simulation error is reduced from 6–9% to less than 6%. The latter is evident, especially for soil types containing a large number of small particles, such as clay and clay loam, for which the simulation error is reduced. All in all, our study contributes to a better understanding of the influencing factors of soil texture and stratification of the near-surface soil, helping to improve microwave land surface emissivity prediction by the studied here model. As MLEM consists of an important part of the global meteorological data assimilation and weather forecast system, results can also help towards increasing the use of satellite data in desert areas and in improving the accuracy of numerical weather forecast models.