## 5 Conclusions  
We proposed a retrieval window for Fs retrieval near 757 nm, which avoids the overfitting of singular vectors to the SIF spectrum. By employing a Doppler shift correction algorithm based on standard reference spectra, we eliminated the Doppler shift between satellite spectra and discussed for the first time the impact of the Doppler effect on data-driven methods. The inversion window assigns two distinctly different slope characteristics to specific singular vectors by introducing weak O\({}_{2}\) absorption bands, thereby restricting the fit of singular vectors to the SIF spectrum in the forward model. A linear forward model was proposed for this window, which ignores the influence of atmospheric absorption on the SIF spectrum. The construction of the forward model utilized the first five physically meaningful singular vectors and was validated using EVI. A comparison of retrieval results before and after Doppler shift correction revealed that eliminating the Doppler shift between satellite spectra further enhances the sensitivity of data-driven methods to Fs.  
The validation of the retrieval results was conducted using MODIS GPP and VI. Our retrieval results demonstrated higher goodness-of-fit and \(p\)-value with GPP and VI at high spatiotemporal resolutions. Specifically, at a 0.1\({}^{\circ}\) spatial resolution on a monthly scale, the goodness-of-fit generally improved by more than 55% compared to the Caltech SIF product.  
The introduction of O\({}_{2}\) absorption bands brought about a slight noise increase while enhancing the sensitivity of the data-driven algorithm. Consequently, retrieval performance in low SIF regions was compromised. However, due to the more serious issue of Fs underestimation caused by low sensitivity, our retrieval results generally exhibited higher signal-to-noise ratios in most scenarios.  
Due to the difficulty in balancing signal-to-noise ratio (SNR) and spectral resolution, SIF retrieval results from satellites equipped with high spectral resolution payloads, such as GOSAT, often have higher root m0/mean square error (RMSE). However, these spectra have deeper Fraunhofer line depths, making them more sensitive to the filling effect caused by SIF signals. In this study, by optimizing window selection and correcting for Doppler shifts, we further explored the retrieval potential of high spectral resolution payloads for SIF signals, significantly improving the SNR of the retrieval results at high spatiotemporal resolutions. Combined with the short revisit cycle of the GOSAT satellite, this approach enables accurate monitoring of SIF signals at high temporal resolutions.  
[PERSON] and [PERSON] wrote the paper. [PERSON] conceived and designed the research. [PERSON] led the design of the data verification scheme and contributed to the paper writing. [PERSON] supplied code for data visualization. [PERSON] was responsible for data acquisition. [PERSON] was responsible for data pre-processing. [PERSON] is responsible for data verification. [PERSON] is responsible for sorting out the code and saving the data. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China (42271403), the University Synergy Innovation Program of Anhui Province (GXXT-2022-001), and Information Materials and Intelligent Sensing Laboratory of Anhui Province (IMIS20208).  
The raw data supporting the conclusions of this article will be made available by the authors on request due to we do not have a data repository website.  
We would like to thank JAXA, NIES, and MOE for providing the GOSAT data, and NASA for the MODIS GPP and VI products. We are grateful to G.C. Toon for the merged solar pseudo-transmittance spectrum. Special thanks to Caltech for providing the GOSAT SIF products and quality screening strategy.  
The authors declare no conflicts of interest.