Long-Term Consistent Recalibration of VIRR Solar Reflectance Data Record for Fengyun Polar-Orbiting Satellites

The visible infrared radiometer (VIRR) is the first instrument with longest measurements equipped on the Fengyun (FY) polar-orbiting satellites. Through re-processing of the historic VIRR measurements, long-term (over 20 yr) global data can be integrated from multiple participating VIRRs on a consistent radiometric scale, which are valuable to climate and climate change studies. Due to lack of an onboard calibration system for VIRR, the reflective solar bands must be vicariously calibrated. This study applied the multi-site vicarious approach for consistent calibration of the VIRR visible (VIS) and near-infrared (NIR) data, and produced calibration coefficients for five VIRRs on FY-1C/D and FY-3A/B/C. The data quality was then evaluated with observations. The reflectance predicted by using the radiative transfer model over multiple invariant desert and ocean targets was used to derive the calibration slope via a weighted fitting scheme, in which the weights are the inverse of the variance from a radiative transfer simulation evaluated with reference to Aqua moderate resolution imaging spectroradiometer (MODIS). The sensor-specific calibration coefficients were derived on a daily basis by using piecewise polynomials. The calibration reference of the VIRR solar band record was further traced to the Aqua MODIS Collection 6.1 reference calibration with a systema-tic correction derived from the Libya4 desert. The VIRR record was compared with the Aqua MODIS C6.1 calibration over the polar region based on simultaneous nadir overpass observations. The lifetime relative difference for each sensor are within 3.3% and 4.5% for channels 1 and 2. Invariant deserts were also employed to evaluate the stability and consistency of the VIRR record. In general, the means of the directional and spectral corrected reflectance for each sensor are within 1% of the 20-yr average, implying that the VIRR reflectance of the invariant targets is consistent to within 1% among the sensors for channels 1 and 2. The VIRR data thus derived are reliable.