A thermal radiation directionality correction method for the surface upward longwave radiation of geostationary satellite based on a time-evolving kernel-driven model

• Published in: Remote sensing of environment Vol. 294; p. 113599
• Main Authors: Qin, Boxiong, Cao, Biao, Roujean, Jean-Louis, Gastellu-Etchegorry, Jean-Philippe, Ermida, Sofia L., Bian, Zunjian, Du, Yongming, Hu, Tian, Li, Hua, Xiao, Qing, Chen, Shuisen, Liu, Qinhuo
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 15.08.2023; Elsevier
• Subjects: ABI/GOES-16; Engineering Sciences; Environmental Engineering; Environmental Sciences; Geostationary satellite; Signal and Image processing; Surface upward longwave radiation; Thermal radiation directionality correction; Time-evolving Kernel Driven Model; Geostationary satellite; Thermal radiation directionality correction; Time-evolving Kernel Driven Model; ABI/GOES-16; Surface upward longwave radiation; Surface Upward Longwave Radiation; Thermal Radiation Directionality Correction; Geostationary Satellite
• ISSN: 0034-4257; 1879-0704
• DOI: 10.1016/j.rse.2023.113599

Thermal radiation directionality (TRD) characterizes the anisotropic signature of most surface targets in the thermal infrared domain. It causes significant uncertainties in estimating surface upward longwave radiation (SULR) from space observations. In this regard, kernel-driven models (KDMs) are suitable to remove TRD effects from remote sensing dataset as they are computationally efficient. However, KDMs requires simultaneous multi-angle observations as inputs to be well calibrated, which yields a difficulty with geostationary satellites as they can only provide a single-angle observation. To overcome this issue, we proposed a six-parameter time-evolving KDM that combines a four-parameter SULR diurnal variation model and a two-parameter TRD amplitude model to correct the TRD effect for single-angle estimated SULR dataset of geostationary satellites. The significant daytime TRD effect when solar zenith angle is within 60° can be effectively eliminated. The modeling accuracy of the time-evolving KDM is evaluated using a simulated SULR dataset generated by the 3D Discrete Anisotropic Radiative Transfer (DART) model; the TRD correction method based on the new time-evolving KDM is validated using a two-year single-angle estimated SULR dataset derived from data of the Advanced Baseline Imager (ABI) onboard Geostationary Operational Environmental Satellite-16 (GOES-16) against in situ measurements at 20 AmeriFlux sites. Results show that the proposed time-evolving KDM has a high accuracy with an R2 > 0.999 and a small RMSE = 1.5 W/m2; the TRD correction method based on the time-evolving KDM can greatly reduce the GOES-16 SULR uncertainty caused by the TRD effect with an RMSE decrease of 4.5 W/m2 (22.1%) and mean bias error decrease of 7.9 W/m2 (62.7%). Hence, the proposed TRD correction method is practically efficient for the operational TRD correction of SULR products generated from the geostationary satellites (e.g., GOES-16, FY-4A, Himawari-8, MSG). •A 6-parameter time-evolving kernel-driven model for SULR was proposed.•The multi-temporal observations of ABI/GOES-16 are utilized to drive new model.•The TRD effect of SULR product of geostationary satellite was corrected for the first time.•The RMSE and MBE decreased by 22.1% and 62.7% for the ABI/GOES-16 SULR .