Research on sea surface temperature retrieval by the one-dimensional synthetic aperture microwave radiometer, 1D-SAMR

Due to the low spatial resolution of sea surface temperature(T_S)retrieval by real aperture microwave radiometers,in this study,an iterative retrieval method that minimizes the differences between brightness temperature(T_B)measured and modeled was used to retrieve sea surface temperature with a one-dimensional synthetic aperture microwave radiometer,temporarily named 1 D-SAMR.Regarding the configuration of the radiometer,an angular resolution of 0.43°was reached by theoretical calculation.Experiments on sea surface temperature retrieval were carried out with ideal parameters;the results show that the main factors affecting the retrieval accuracy of sea surface temperature are the accuracy of radiometer calibration and the precision of auxiliary geophysical parameters.In the case of no auxiliary parameter errors,the greatest error in retrieved sea surface temperature is obtained at low T_S scene(i.e.,0.7106 K for the incidence angle of 35°under the radiometer calibration accuracy of0.5 K).While errors on auxiliary parameters are assumed to follow a Gaussian distribution,the greatest error on retrieved sea surface temperature was 1.3305 K at an incidence angle of 65°in poorly known sea surface wind speed(W)(the error on W of 1.0 m/s)over high W scene,for the radiometer calibration accuracy of 0.5 K.

Sea surface temperature retrieval based on simulated microwave polarimetric measurements of a one-dimensional synthetic aperture microwave radiometer

Compared with traditional real aperture microwave radiometers,one-dimensional synthetic aperture microwave radiometers have higher spatial resolution.In this paper,we proposed to retrieve sea surface temperature using a one-dimensional synthetic aperture microwave radiometer that operates at frequencies of 6.9 GHz,10.65 GHz,18.7 GHz and 23.8 GHz at multiple incidence angles.We used the ERA5 reanalysis data provided by the European Centre for Medium-Range Weather Forecasts and a radiation transmission forward model to calculate the model brightness temperature.The brightness temperature measured by the spaceborne one-dimensional synthetic aperture microwave radiometer was simulated by adding Gaussian noise to the model brightness temperature.Then,a backpropagation(BP)neural network algorithm,a random forest(RF)algorithm and two multiple linear regression algorithms(RE1 and RE2)were developed to retrieve sea surface temperature from the measured brightness temperature within the incidence angle range of 0°-65°.The results show that the retrieval errors of the four algorithms increase with the increasing Gaussian noise.The BP achieves the lowest retrieval errors at all incidence angles.The retrieval error of the RE1 and RE2 decrease first and then increase with the incidence angle and the retrieval error of the RF is contrary to that of RE1 and RE2.