Calibration Optimization for Long-Term Consistency of the FY-3B Infrared Atmospheric Sounder

The Feng Yun-3B (FY-3B) Infrared Atmospheric Sounder (IRAS) provides key infrared observations for numerical weather prediction (NWP) and climate applications, but long-term consistency is affected by three factors: spectral response function (SRF) central wavenumber shifts, changes in the nonlinear coefficient of the instrument in orbit, and fixed brightness-temperature (BT) uniformity screening. We propose a three-step refinement chain consisting of SRF central wavenumber shift correction (SSC), in-orbit nonlinearity-coefficient optimization (NCO), and channel-dependent adaptive quality control (AQC). First, SSC conducts fine adjustment of SRF central wavenumbers by jointly minimizing mean bias and standard deviation, reducing uncertainty by about 10–25% in sensitive absorption channels. Second, NCO refines the quadratic term under two-point anchoring constraints, recentering mean biases toward zero without changing linear gain. Third, AQC applies channel-dependent BT-uniformity thresholds to suppress scene-driven variance while preserving sample representativeness. Using FY-3B/IRAS and Meteorological Operational Satellite Programme-A/Infrared Atmospheric Sounding Interferometer (Metop-A/IASI) simultaneous nadir overpass (SNO) matchups from 2010–2019, the integrated SSC–NCO–AQC chain substantially improves cross-calibration consistency: most CO2 channels show mean biases reduced from >1 K to <0.2 K, with narrower uncertainty envelopes, while window channels remain stable. The results support more reliable long-term radiometric consistency and cross-year comparability for FY-3B/IRAS.