Supercontinuum lidar (SC lidar) is a type of lidar with both broad spectrum and laser characteristics. SC lidar combines the advantages of passive spectrometers and monochromatic lidars, offering significant potential for atmospheric multi-element monitoring. However, the broader application of SC lidar depends on increasing its laser’s average output power. In this article, we use numerical simulation to establish the SC lidar function and models for background radiation during both daytime and nighttime. We also analyze the contributions of various noise sources and perform sensitivity analysis on parameters influencing atmospheric radiation transmission. Finally, we discuss the power requirements for spaceborne greenhouse gas detection applications using SC lidar (Fig. 1).

We present an SC lidar equation in section 2.1, based on the traditional lidar equation. The supercontinuum laser source used in this paper is from NKT Photonics, with its spectral power density shown in Fig. 2. Additional parameters of SC lidar are shown in Table 1. Solar radiation is considered the primary background noise during the day, while lunar radiation and nighttime light (NTL) radiation are the main nighttime background noises (Sections 2.2 and 2.3). Lunar irradiance is calculated by multiplying solar irradiance by lunar albedo (Fig. 3), empirically fitted based on the robotic lunar observatory (ROLO) model. National aeronautics and space administration (NASA)’s Black Marble product, specifically the monthly moonlight and atmosphere-corrected NTL composite (VNP46A3), is used to calculate nighttime light intensity. By combining the distribution ratios of nighttime light sources with VNP46A3 products, we obtain characteristic nighttime light radiance spectra for cities like Las Vegas and Guangzhou (Fig. 4). The SCIATRAN radiative transfer model is then used to simulate the SC lidar backscatter signal power, as well as the solar and lunar radiation intensities. The baseline results are shown in Fig. 5.

We use the signal-to-noise ratio (SNR) to evaluate error contributions and conduct sensitivity analyses. Besides background radiation, SC lidar performance is influenced by internal detector noise, such as dark current noise and shot noise [Eq. (7)]. The total SNR is defined in Eq. (8). To estimate the contribution of each noise term to the total noise, we calculate the derivative of various noise sources relative to the total noise at an altitude of 120 km (Table 3). Solar radiation dominates daytime noise, while dark current noise is the main factor at night. Surprisingly, lunar and NTL radiation contribute minimally to the total nighttime noise compared to the lidar signal power. Sensitivity analysis of variables such as atmosphere models, solar zenith angle (SZA), aerosol models, dark current density, and surface reflectance (Figs. 6 and 7) show that water vapor absorption bands are highly sensitive to changes in all selected parameters, particularly the atmospheric model [Fig. 6(a)]. Other spectral bands show minimal sensitivity to atmospheric model changes. SZA affects solar intensity; thus, as SZA increases, solar intensity decreases, leading to higher SNR [Fig. 6(b)]. We examine six aerosol scenarios with varying types and visibilities [Figs. 6(c) and (d)], finding that SNR decreases sequentially across maritime (23 km), maritime (50 km), rural (50 km), rural (23 km), urban (50 km), and urban (23 km) scenarios. Notably, aerosol influences at nighttime are greater than during the day. Reducing dark current density improves SNR [Figs. 7(a) and (b)], as dark current noise significantly influences nighttime SNR. High surface reflectivity also enhances SNR [Figs. 7(c) and (d)]. To estimate the total peak power needed for spaceborne SC lidar applications, we conduct experiments under the following conditions: 1) daytime with SZA is 30°, 70°, 89° and iD=160 fA/Hz; 2) nighttime with iD=160 fA/Hz, 20 fA/Hz. We adjust the total peak power to obtain multiple results and fit the polynomial relationship between measurement altitudes and SNR at different wavelengths. Using four SNR thresholds (2, 5, 10, and 20 dB), we calculate the maximum measurement altitude R_max, assuming the lidar backscatter signal is usable when the SNR exceeds the threshold. We select three bands (Fig. 8) to assess the effect of lidar total peak power on measurement altitude, as shown in Fig. 9. Assuming an orbit altitude of 500 km, the minimum total peak powers required for the three bands are shown in Tables 4 and 5. With an SNR threshold of 2 dB, the average total peak power must reach 3.32×10⁷ W during the day and 3.46×10⁶ W at night to ensure usable backscatter signals for the three bands. Finally, we use the IMAP-DOAS method to retrieve baseline SC lidar echo signals. The CO₂ retrieval errors under varying SC lidar total peak power and dark current scenarios are shown in Fig. 10. The results indicate that SC lidar’s total peak power needs to reach 1×10⁸ W to achieve an XCO₂ precision of better than 2×10^－6.

Through simulation experiments and error analysis, the following conclusions are drawn: 1) Solar background radiation and dark current noise are the primary sources of errors, while lunar and NTL radiation have limited influence. 2) Sensitivity analysis shows that during the day, changes in most parameters are not significant except for SZA due to the influence of solar radiation. At night, various parameters have a more noticeable effect on SNR. 3) The total peak power of SC lidar is the main obstacle to its application. The minimum required total peak power is 1×10⁸ W. Further research is essential for future SC lidar applications.