Integrated Retrieval of Surface and Atmospheric Variables in the Arctic From FY-3D MWRI With a Time-Constraint Optimal Estimation Method

Integrated retrieval using the optimal estimation (OE) method iteratively finds a set of geographical parameters that best match the observations. However, this method becomes more challenging over the ice surface due to the highly sensitive parameters such as sea ice concentration (SIC) and multiyear ice concentration (MYIC). In this study, a new time constraint that captures the distinct temporal characteristics of SIC and MYIC is incorporated into the OE method. The integrated retrievals, using both the original and time-constraint OE method (referred to as OE and OE-Z, respectively), were conducted based on FengYun-3D (FY-3D) microwave radiation imager (MWRI) data. Compared to other radiometer-based SIC and MYIC products, OE-Z outperforms OE, with the correlations increasing from 0.91 to 0.96 for SIC and from 0.41 to 0.49 for MYIC. The time constraint in OE-Z effectively mitigates the anomalous retrievals in SIC and MYIC, resulting in smoother and more reasonable time series than OE. Improvements in SIC and MYIC lead to enhanced simulation of surface microwave emission, thus improving the retrieval of atmospheric parameters. In comparison with the MOSAiC total water vapor (TWV) measurements, the RMSE in OE-Z reduces from 1.72 to 1.66 kg/m², and the correlation increases from 0.46 to 0.50. The simulated brightness temperature (TB) biases in OE-Z reduce from 0.71 to 0.31 K at 36 GHz and from −8.95 to −7.72 K at 89 GHz. This emphasizes the importance of imposing suitable constraints on highly sensitive parameters in integrated retrieval.