Recalibration and Reprocessing of the Long-Term FY-3 MERSI Historical Data

The MEdium Resolution Spectral Imager (MERSI) onboard the Fengyun-3 (FY-3) series satellites can provide the long-term series data with favorable spectral and spatial resolution on the global scale since 2008. Such datasets are valuable for the studies of climate change. However, due to the lack of stable and reliable onboard calibration equipment and inconsistent in-orbit calibration methods, the MRESI historical data have poor long-term stability and unreliable accuracy, which affects the quantitative application of the data. This study reveals the overall status of the FY-3A/B/C MERSI-I historical data and proposes the recalibration methods for the reflective solar bands (RSBs) and thermal emission bands (TEBs). For the RSBs, by using FY-3A as the radiative transfer reference, an integrated transfer calibration method is developed for the calibration of FY-3B, which is then used to recalibrate FY-3C. The degradation tracking model of FY-3 MERSI-I is established first in the recalibration process by integrating multiple calibration methods. Then, based on the overlapping observations over the Libyan Desert, the linear consistency transfer model of the reference and target satellites is established, and the consistent correction coefficient between them is obtained. For the TEBs, a retrospective transfer recalibration scheme is proposed to achieve the reevaluation of the in-orbit radiometric calibration parameters based on intercalibration and to conduct the recalibration of historical data without permanent dependence on reference instruments. All the historical data of FY-A/B/C MERSI-I (from February 2008 to March 2017) are reprocessed with the same calibration method. The reprocessed datasets show remarkable improvements in calibration accuracy and stability compared with the operational datasets. The overall radiometric biases are found to be small and highly stable during the entire mission cycle of the instrument. The calibration biases of reprocessed data are less than 3% and 0.5 K for the RSBs and TEBs, respectively, much better than those of the operational datasets. There are also substantial improvements in the seasonal fluctuations and deviation discontinuities. This reprocessed long-term MERSI data with high intersensor consistency can provide valuable insights into global climate monitoring and model assessment.