| 07 Apr 2026
Optimization of the Fast Layer Transmittance Algorithm in RTTOV v13.1 for Strong Water Vapor Absorption Channels of the FY-3F HIRAS-II Instrument Using LBLRTM v12.11
Abstract. Fast and accurate calculation of atmospheric transmittance is essential for infrared atmospheric remote sensing and satellite data assimilation. However, fast radiative transfer models show significant errors in strong water vapour absorption channels (e.g., near 6.7 μm). An important reason is that the numerical instability encountered during the regression of transmittance coefficients when dealing with lower and middle atmosphere. To address this, this study proposes an optimized scheme to calculate atmospheric transmittance vertical profiles for the RTTOV (Radiative Transfer for TOVS) fast transmittance algorithm. The method introduces a physically motivated transmittance threshold to sub-select training samples and employs cumulative transmittance-based weighting factor within a weighted least squares regression to recalibrate the transmittance coefficients. It aims to optimize the calculation scheme for transmittance coefficients of the Hyperspectral Infrared Atmospheric Sounder-II (HIRAS-II) instrument onboard Fengyun 3F satellite (FY-3F). The method is assessed by calculations on the training profile datasets provided within the RTTOV model framework. By comparing transmittance and brightness temperature calculations at 6.7 microns from this method with those from a line-by-line model and observations from HIRAS-II, the results show that the accuracy of the forward model for the 6.7 μm absorption channel is significantly enhanced by applying a threshold-based noise reduction method. This improvement enhances the stability and reliability of the transmittance calculations for this strong absorption band. Further accuracy enhancements are obtained by incorporating weighting corrections into the calculations of transmittance coefficients. The root mean square error (RMSE) and bias of the observation minus background (OMB) time series for FY-3F HIRAS-II demonstrate that the transmittance coefficient calculation scheme with weighting factor correction improves the forward model accuracy, which is more consistent with RTTOV simulation results. The OMB bias at the 6.7 μm absorption peak channel performs better than that of RTTOV, while the OMB bias on both sides of the 6.7 μm absorption peak channel remains consistent with RTTOV.
1. The authors state that LSM3 slightly outperforms LSM2. However, from a theoretical perspective, weighted ordinary least squares (LSM2) is mathematically equivalent to ordinary least squares with weighted variables (LSM3). Could you please explain why a performance difference is observed in practice?
2. Page 5, Line 156 & Page 6, Line 168: Maybe change ‘.when ...’ to ‘.When...’.
3. Page 6, Eq.(6): The weight factor is defined as a function of transmittance (i.e., W ∝ τ). Is this derived from an iterative optimization procedure, or other physical assumptions? Could you please add a description to clarify the principle behind this specific choice?
4. Page7, Lines 202-214 & Lines 215-220: This part needs to be carefully revised. It appears to be a repetition of content, where two consecutive paragraphs convey essentially the same meaning with slightly different wording.
5. Page 13, Line 331-332: The authors used a semi-empirical threshold of 10-4 as the screening criterion. However, it is not entirely clear whether this threshold is specifically selected for the FY-3F HIRAS-II instrument based on dedicated analysis, or adopted from previous studies as a generally applicable value. Could you please provide more quantitative evidence to support this choice if possible?
6. Figure quality: Most of the comparison figures (e.g., Figs. 5, 6, etc.) appear noticeably blurred and contain more than 15*3 lines in a single image, making it difficult for readers to distinguish between different schemes and symbols. To improve readability, I suggest select a limited number of representative profiles (e.g., Profiles 81, 82, 83) to illustrate the key findings, and move others to the appendix or supplementary material.
7. Figure caption: Different methods are described using words in Fig. 5 (e.g., ‘pentagrams’, ‘circles’, ‘triangles’), while symbols in Fig. 9 (e.g., ‘✯’, ‘○’, ‘△’). For reasons of consistency, please unify the notation style (i.e., either textual descriptions or symbols).