Enhanced Rayleigh Scattering Calibration for FY-3D MERSI II Sensor With Extensive and Long Term Ocean Samples

Accurate radiometric calibration is crucial for satellite sensors, ensuring reliable remote sensing data. However, current calibration methods often rely on a limited number of samples, leading to uncertainties in calibration process. In this study, we presented a comprehensive approach for calibrating FY-3D MERSI-II sensor by leveraging an extensive dataset of over 110 000 dark pixel samples collected from three diverse oceanic regions. Through a meticulous data screening process, we identified suitable calibration samples to enhance the robustness of our approach. Employing a radiative transfer model, we conducted forward modeling to calibrate the sensor's observations. Notably, our coefficients of determination (
$\mathit{{R}}^{2}$
) establish the efficacy of the Rayleigh scattering method for channels CH09, CH10, and CH11, demonstrating a strong correlation between the spectral range of 443 and 555 nm. The calibration results revealed improved accuracy, with mean absolute BIAS values ranging from 1.329% to 11.265% across different seas, highlighting the wavelength-dependent uncertainty. Our approach effectively addresses the limitations associated with a limited number of referenced points, thereby enhancing the reliability of calibrated results. This research significantly contributes to advancing radiometric calibration for the FY-3D MERSI II sensor by explicitly emphasizing usage of over 110 000 dark pixels during the calibration process. These findings not only enhance the accuracy of satellite-based oceanic observations but also provide valuable insights into calibration methodologies for future studies.