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

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.

Microwave Land Emissivity Calculations over the Qinghai-Tibetan Plateau Using FY-3B/MWRI Measurements

The Qinghai-Tibetan plateau plays an important role in climate change with its unique characteristics, and the surface emissivity is an important parameter to describe the surface characteristics. It is also very important for the accurate retrieval of surface and atmospheric parameters. Different types of surface features have their own radiation characteristics due to their differences in structure, water content and roughness. In this study, the microwave land surface emissivity (10.65, 18.7, 23.8, 36.5 and 89 GHz) of the Qinghai-Tibetan Plateau was calculated using the simplified microwave radiation transmission equation under clear atmospheric conditions based on Level 1 brightness temperatures from the Microwave Radiation Imager onboard the FY-3B meteorological satellite (FY-3B/MWRI) and the National Centers for Environmental Prediction Final (NCEP-FNL) Global Operational Analysis dataset. Furthermore, according to the IGBP (International Geosphere-Biosphere Program) classified data, the spectrum and spatial distribution characteristics of microwave surface emittance in Qinghai-Tibetan plateau were further analyzed. The results show that almost all 16 types of emissivity from IGBP at dual-polarization (vertical and horizontal) increase with the increase of frequency. The spatial distribution of the retrieving results is in line with the changes of surface cover types on the Qinghai-Tibetan plateau, showing the distribution characteristics of large polarization difference of surface emissivity in the northwest and small polarization difference in the southeast, and diverse vegetation can be clearly seen in the retrieving results. In addition, the emissivity is closely related to the type of land surface. Since the emissivity of vegetation is higher than that of bare soil, the contribution of bare soil increases and the surface emissivity decreases as the density of vegetation decreases. Finally, the source of retrieval error was analyzed. The errors in calculating the surface emissivity might mainly come from spatiotemporal collocation of reanalysis data with satellite measurements, the quality of these auxiliary datasets and cloud and precipitation pixel discrimination scheme. Further quantitative analysis of these errors is required, and even standard procedures may need to be improved as well to improve the accuracy of the calculation.