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

Abstract

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.

Keywords

• MERSI-II
• Rayleigh scattering
• uncertainty analysis