Evaluation and Application of SMRT Model for L-Band Brightness Temperature Simulation in Arctic Sea Ice

• Published in: Remote sensing (Basel, Switzerland) Vol. 15; no. 15; p. 3889
• Main Authors: Fan, Yanfei, Li, Lele, Chen, Haihua, Guan, Lei
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.08.2023
• Subjects: Accuracy; Algorithms; Arctic; Arctic research; Brightness; Brightness temperature; Climate change; Correlation coefficient; Correlation coefficients; L-band TB; Mathematical models; Microstructure; Moisture effects; Monolayers; Multilayers; Parameters; Polar environments; Radiative transfer; Remote sensing; Salinity; Salinity effects; Satellites; Sea ice; Simulation; Simulation methods; SMOS; Snow; snow microwave radiative transfer model; Soil moisture; Substrates; Thermal insulation; Ultrahigh frequencies; Arctic Ocean; Arctic region
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs15153889

Using L-band microwave radiative transfer theory to retrieve ice and snow parameters is one of the focuses of Arctic research. At present, due to limitations of frequency and substrates, few operational microwave radiative transfer models can be used to simulate L-band brightness temperature (TB) in Arctic sea ice. The snow microwave radiative transfer (SMRT) model, developed with the support of the European Space Agency in 2018, has been used to simulate high-frequency TB in polar regions and has obtained good results, but no studies have shown whether it can be used appropriately in the L-band. Therefore, in this study, we systematically evaluate the ability of the SMRT model to simulate L-band TB in the Arctic sea ice and snow environment, and we show that the results are significantly optimized by improving the simulation method. In this paper, we first consider the thermal insulation effect of snow by adding the thermodynamic equation, then use a reasonable salinity profile formula for multi-layer model simulation to solve the problem of excessive L-band penetration in the SMRT single-layer model, and finally add ice lead correction to resolve the large influence it has on the results. The improved SMRT model is evaluated using Operation IceBridge (OIB) data from 2012 to 2015 and compared with the snow-corrected classical L-band radiative transfer model for Arctic sea ice proposed in 2010 (KA2010). The results show that the SMRT model has better simulation results, and the correlation coefficient (R) between SMRT-simulated TB and Soil Moisture and Ocean Salinity (SMOS) satellite TB is 0.65, and the RMSE is 3.11 K. Finally, the SMRT model with the improved simulation method is applied to the whole Arctic from November 2014 to April 2015, and the simulated R is 0.63, and the RMSE is 5.22 K. The results show that the SMRT multi-layer model is feasible for simulating L-band TB in the Arctic sea ice and snow environment, which provides a basis for the retrieval of Arctic parameters.