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Abstract
The potential of spaceborne Brillouin scattering lidar for generating global ocean optical profiles was studied herein. We analyzed the global distributions of the maximum detectable depths and corresponding optimum wavelengths for spaceborne Brillouin scattering lidar during the day and night, simulated the global vertical profile distributions of the seawater sound speed and Brillouin scattering frequency shift, and discussed the effects of the system parameters and water environment parameters in Case II water on the lidar detection performance and proportion of Brillouin scattering lidar penetrating the upper mixed layer on the global scale. The laser emission wavelength of 490 nm is suitable for detecting open ocean waters, and 540 nm is suitable for detecting coastal waters. The detection depth of the Brillouin scattering lidar operating at night is approximately 10 m greater than that during the day. The vertical profile distributions of the seawater sound and the Brillouin scattering frequency shift decrease as the depth increases from 0 to 200 m in the mid-low latitude regions. The proportions of spaceborne Brillouin scattering lidar penetrating the upper mixed layer in January-February-March, April-May-June, July-August-September, and October-November-December are 75.15%, 76.80%, 59.12%, and 73.10%, respectively. The results indicate that spaceborne Brillouin scattering lidar has great potential for the wide-range and long-term monitoring of upper-ocean water bodies, which would be a good complement to passive satellite ocean color remote sensing technology and the traditional measurement methods of Argo floats, gliders, XBT, and AUV.
© 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
1. Introduction
The upper boundary layer of the ocean prominently contributes to the global marine ecosystem and climate system since it contains significant information about many dynamic and thermodynamic processes and mediates the exchange of mass, momentum, heat, and gas flux between the atmosphere and the underlying ocean [1,2]. Thus, it is essential to obtain vertical profile data, such as temperature, salinity, density, sound speed, chlorophyll-a, etc., of upper-ocean water bodies. Presently, passive ocean color remote sensing has been widely used to observe the global carbon cycle, primary productivity, and environmental changes in oceans and coastal zones [3–5], and its related remote sensing technologies and retrieval algorithms are relatively mature. Nevertheless, the passive satellite remote sensing technique cannot provide vertical profile distribution information of ocean water bodies, nor can it provide full-time day and night observations of the ocean. Existing scientific research on the vertical profile of ocean water bodies is based on data from Argo floats, gliders, expendable bathythermographs (XBTs), autonomous underwater vehicles (AUVs), etc. [6–8]. These observation platforms are relatively time-consuming, labor-intensive, and low-resolution. Therefore, the development of novel observation technologies and methods for detecting the vertical profile information of the upper-ocean water body is urgent. With recent advances in laser techniques, lidar has been widely used as an effective approach for detecting ocean environment parameters because of its advantages of high spatiotemporal resolution, continuous day-night observation, and ability to obtain vertical profile information of water bodies. In particular, the Brillouin scattering lidar can obtain not only the intensity information of the backscattered signal in seawater but also the frequency spectrum information of the ocean water body; this information can be used to retrieve the vertical profile structures of the temperature, salinity, sound speed, phytoplankton biomass, etc. Related studies have been reported in recent years [9–16], and the results indicate that the application of Brillouin scattering in ocean laser remote sensing is significantly important for understanding the physicochemical phenomena and processes of the upper ocean. However, the current research mainly focuses on Brillouin scattering spectrum measurements in the laboratory and small-scale ocean vertical profile detection experiments of shipborne and airborne Brillouin scattering lidar. Recently, the spaceborne lidar platform has shown great potential in the global optical profile detection of ocean water bodies [17,18]. Simultaneously, the design and development of spaceborne lidar require plenty of preliminary theoretical and experimental research. However, there are few reports on the potential of spaceborne Brillouin scattering lidar for detecting global ocean optical profiles.
In this study, the potential of spaceborne Brillouin scattering lidar for global ocean optical profiles is described. The global distributions of the maximum detectable depths and corresponding optimum wavelengths for spaceborne Brillouin scattering lidar are analyzed considering the signal-to-noise ratio (SNR) and signal-measurement error. Subsequently, the global vertical profile distributions of the seawater sound speed and Brillouin scattering frequency shift are further analyzed through theoretical simulation. Finally, we discuss the effects of the lidar system parameters and water environment parameters in Case II water on lidar detection performance and the proportion of Brillouin scattering lidar penetrating the upper mixed layer at the global scale.
2. Brillouin scattering lidar system and theoretical analysis
2.1 Configuration of Brillouin scattering lidar system
The oceanic Brillouin scattering lidar system commonly comprises a laser transmitting and receiving system, optical processing and detecting system, and data acquisition and processing system, as shown in Fig. 1. The laser source employs an injection seeded and Q-switched Nd:YAG pulse laser with the light frequency doubled to 532 nm through a second harmonic generator (SHG). The transmitting pulsed laser beam passes through a nonpolarizing beam splitter (BS), and most of the laser pulse energy passes through the high-reflectivity mirror M1 into the seawater. The rest of the laser pulse energy enters the photomultiplier tube (PMT), which is used for monitoring the laser energy stability. The backscattered signals are received by the telescope and then are incident into the optical processing and detecting system. The optical processing and detection system includes a beam collimation system, pinhole filter, Fabry-Perot etalon, intensified charge-coupled device (ICCD), computer, and time schedule controller (TSC). The backscattered signals form a fine structure of the spectral concentric rings after passing through the collimation system and Fabry-Perot etalon, which are recorded by an ICCD camera. Subsequently, Brillouin scattering spectral characteristics can be obtained, and further inversion of the ocean environmental parameters can be performed based on the data acquisition and processing system.
Fig. 1. Configuration of an oceanic Brillouin scattering lidar system including a laser transmitting and receiving system, an optical processing and detecting system, and a data acquisition and processing system. BS: beam splitter, PMT: photomultiplier tube, M1 and M2: mirrors, L1 and L2: beam collimation system, S: pinhole filter, F-P: Fabry-Perot etalon, ICCD: intensified charge-coupled device, PC: computer, TSC: time schedule controller.
2.2 Brillouin scattering signal intensity and spectral characteristics
Spaceborne Brillouin scattering lidar transmits pulse laser beams that directly penetrate the ocean after passing through the atmosphere and air-sea interface. In the ocean, the backscattered signal is generated by water molecule and suspended particle scattering, which is collected by a telescope. Under the condition of neglecting the effects of multiple scattering and using time-of-flight technology, the depth-dependent lidar signal can be described by the quasi-single scattering equation [10,19,20]:
From the perspective of the physical mechanism, spontaneous Brillouin scattering arises from the interaction between the incident laser and periodic mass density fluctuations due to the acoustic waves with a sound velocity ${V_S}$ within the optical property range of the medium. The scattered field equation can be obtained by inserting the acoustic wave equation into the coupled wave equation [21].
The first term on the right-hand side corresponds to the Stokes component, whereas the second term is the anti-Stokes component. Thus, the Brillouin scattering frequency shift can be expressed as follows:
where the parameters ${V_S}$ and ${n}$ are related to the functions of ocean salinity, temperature, and pressure. The sound velocity of the seawater is given by [22,23]:2.3 Bio-optical model and optimal detection wavelength
For spaceborne oceanic lidar, the attenuation coefficient in the water $({K_{lidar}})$ can be regarded as the spectral attenuation for downward irradiance $({K_d})$ due to the relatively large lidar spot diameter on the ocean surface caused by the transmitter beam divergence, the height of the spaceborne platform and the relatively large receiver field of view [19,24,25]. The spectral diffuse attenuation coefficient is the contribution of pure water $({K_w})$ and biogenic components $({K_{bio}})$, which can be expressed as [26]:
where the parameters ${{a}_{w}}$ and ${{b}_{w}}$ are defined as the absorption and scattering coefficients of pure water, respectively. ${{K}_{{bio}}}$ is a function of chlorophyll concentration and can be expressed in the following form:The power of the Brillouin scattering signal can be obtained by Eq. (1), which can be used to further compute the number of received Brillouin scattering photons.
where $\Delta {t}$ is the laser pulse width, and the parameters h and ${\nu }$ are defined as the Planck constant and laser frequency, respectively. Furthermore, there are not only backscattered signals but there is also solar spectral radiance noise in the received lidar signal. The received number of photons based on the solar spectral radiance is given by [27]:Then, the SNR and signal-measurement error $\delta$ of Brillouin scattering lidar based on Eqs. (9) and (11) can be expressed as [29,30]:
where the parameter M is defined as the integrated number of laser shots, and its value is 1. The pulse energy decreases with increasing penetration depth when the output laser propagates in seawater. Thus, the theoretical maximum detectable depth of lidar can be defined as the depth where the return signal is hard to distinguish from the background noise and SNR(z) = 1. The maximum detectable depth related to the laser emission wavelength λ can be expressed in the following form:The optical parameters of the water corresponding to different laser wavelengths are different based on the analysis of the bio-optical model, which results in different penetration depths for different detectable wavelengths. Thus, the optimum detectable wavelength ${{\lambda }_{0}}$ during the day and night can be obtained by comparing the maximum penetration depth of different wavelengths, which is given by:
3. Results
3.1 Brillouin scattering lidar return signal photons and SNR simulation
Spaceborne oceanic lidar transmits laser beams that directly penetrate the ocean after passing through the atmosphere and air-sea interface. Thus, the evaluation of received photons in Brillouin scattering lidar requires the transmission of the laser through the atmosphere and ocean surface, ocean optical parameters, and lidar system parameters, as shown in Table 1.
Figure 2(a) shows the variation in the simulated received photons for spaceborne Brillouin scattering lidar with the ocean depth when ignoring the solar spectral radiation. As the laser penetration depth in the ocean increases, the number of received photons decreases because of the pulse energy loss during laser transmission in seawater, and the maximum detectable depth of lidar is 76 m under the conditions of a laser incident wavelength of 532 nm and chlorophyll concentration of $\textrm{0}.05\; \textrm{mg}/{\textrm{m}^\textrm{3}}$. However, it is necessary to consider the background noise caused by solar spectral radiation during the day and night in real application scenarios, and the simulation results are shown in Fig. 2(b). Based on the analysis of Eq. (14), the lidar maximum detectable depth is defined as the depth where SNR=1 and the corresponding signal-measurement error δ of the Brillouin scattering lidar system is 100%. The maximum detectable depths of spaceborne Brillouin scattering lidar during the day (blue line) and night (red line) are 61 m and 73 m, respectively. For further analysis, the lidar detectable depths during the day and night are 60 m and 52 m, respectively, when the signal-measurement error of the lidar system is 50%. The lidar detectable depths during the day and night are 50 m and 45 m, respectively, when the signal-measurement error of the lidar system is 30%. The simulation results indicate that the background noise caused by solar spectral radiation has a significant impact on the detection performance of lidar.
Fig. 2. Simulation of the received photons (a) and SNR (b) for spaceborne Brillouin scattering lidar under the conditions of a laser incident wavelength of 532 nm and chlorophyll concentration of 0.1 $\textrm{mg/}{\textrm{m}^\textrm{3}}$.
3.2 Global distribution of the maximum detectable depths and corresponding optimum wavelengths for spaceborne Brillouin scattering lidar
Based on the abovementioned single profile of received photons and SNR, the global distribution of the maximum detectable depth for spaceborne Brillouin scattering lidar at different wavelengths was further analyzed. The spatiotemporal distribution of ${\textrm{K}_\textrm{d}}\mathrm{(\lambda )}$ in global oceanic water is mainly dominated by changes in the chlorophyll concentration. The global oceanic chlorophyll concentration data are from the level 3 2019 annual mean chlorophyll product MODIS-Aqua [31], which has a horizontal resolution of 9 km×9 km. The input laser wavelength range of 400-600 nm was selected based on the high transmittance in the wavelength range of the oceanic detection window, which was divided into 40 bands with an interval of 5 nm. Thus, the global distribution of the maximum detectable depths and corresponding optimum wavelengths for Brillouin scattering lidar can be obtained by comparing the penetration depths of 40 laser bands, as shown in Fig. 3. Figures 3(a) and 3(b) show the global distributions of the maximum detectable depths for Brillouin scattering lidar during the day and night, respectively. There is a noticeable performance difference in the penetration depth of the lidar due to the different background noise intensities during the day and night. Furthermore, the maximum detectable depths of lidar in different regions have remarkable spatial distribution characteristics. In detail, the maximum detectable depths of lidar in the mid-to-high latitudes ($\textrm{4}{\textrm{0}^\textrm{o}}\mathrm{N\sim 8}{\textrm{0}^\textrm{o}}\textrm{N},\; 4{\textrm{0}^\textrm{o}}\mathrm{S\sim 8}{\textrm{0}^\textrm{o}}\textrm{S}$) and coastal regions during the day and night are relatively shallow, while the penetration depth of lidar shows deeper detectable performance in the mid-low latitude areas ($\textrm{4}{\textrm{0}^\textrm{o}}\mathrm{N\sim 4}{\textrm{0}^\textrm{o}}\textrm{S}$). Figures 3(c) and 3(d) show the global distributions of the corresponding optimum detectable wavelengths during the day and night, respectively.
Fig. 3. The global distributions of the maximum detectable depths during the day (a) and night (b) for Brillouin scattering lidar and the corresponding optimum detectable wavelengths during the day (c) and night (d).
Statistical analysis was performed on the global distribution of the optimum detectable wavelengths (Figs. 3(c) and 3(d)) to further confirm the coverage percentage of the ocean area at different wavelengths, and the results are shown in Fig. 4. Figure 4(a) shows that the coverage percentage of the ocean area varies with the laser incident wavelength during the day and night. The laser wavelength of 490 nm accounted for the largest coverage proportions of 27.44% and 27.54% during the day and night, respectively. In the wavelength range from 520 nm to 580 nm, which is suitable for detecting coastal waters, the laser wavelength of 540 nm accounts for the largest coverage percentages of 2.97% and 3.05% during the day and night, respectively. Figures 4(b) and 4(c) show that the wavelengths range from 480 nm to 490 nm with maximum coverages of 47.45% and 47.46% during the day and night, respectively. The coverage percentage of the ocean area at wavelengths ranging from 470 nm to 490 nm is 76.41% and 76.28% during the day and night, respectively, which is suitable for detecting open ocean waters. Based on the above analysis, if a dual-wavelength spaceborne Brillouin scattering oceanic lidar is developed, the recommended wavelengths include a laser emission wavelength of 490 nm that is suitable for detecting open ocean waters and a laser emission wavelength of 540 nm that is suitable for detecting coastal waters.
Fig. 4. The statistical global distributions of the optimum detectable wavelengths during the day and night (a) and the coverage percentages of the ocean area at different laser detectable wavebands during the day (b) and night (c).
The global distributions of the maximum detectable depths at laser emission wavelengths of 490 nm and 540 nm were further analyzed, and the results are shown in Fig. 5. Figure 5(a) shows the global distribution of the maximum penetration depths using 490 nm during the day. The lidar penetration depth ranges from 100 m to 120 m in oligotrophic waters, while the penetration depth ranges from 50-100 m in usual open ocean waters. The lidar penetration depth is less than 20 m in eutrophic coastal waters. Figure 5(b) shows the global distribution of the maximum detectable depths using 490 nm during the night. The detectable depth of lidar ranges from 120 m to 160 m in oligotrophic waters, while the detectable depth ranges from 60-110 m in usual open ocean waters. The detectable depth of lidar is less than 30 m in eutrophic coastal waters. The global distributions of the maximum penetration depths at the laser emission wavelength of 540 nm during the day and night are shown in Figs. 5(c) and 5(d), respectively. The laser emission wavelength of 540 nm has better detectable performance than 490 nm in eutrophic coastal waters. Furthermore, the detectable depth of lidar during the night is deeper than during the day due to the different background noise intensities during the day and night.
Fig. 5. The global distributions of the maximum detectable depths at the laser emission wavelength of 490 nm during the day (a) and night (b). The global distributions of the maximum penetration depths using 540 nm during the day (c) and night (d).
3.3 Brillouin scattering spectral characteristics analyses
The global distributions of the maximum detectable depths and corresponding optimal wavelengths for spaceborne Brillouin scattering oceanic lidar have been analyzed based on the intensity information of the received signal. It is also extremely significant to analyze the spectral characteristics of the received Brillouin scattering lidar signal. Thus, the effects of seawater temperature and salinity on the sound speed and Brillouin scattering frequency shift are further studied through theoretical simulation and compared to the experimental results that have been reported [12,15,32,33] to verify the accuracy of the simulation model. The results are presented in Fig. 6. The theoretical simulation result in Fig. 6(a) indicates that the sound speed increases from 1485 to 1580 m/s when the seawater temperature increases from 5 to 40°C, while the experimental result shows that the sound speed increases from 1470 to 1560 m/s as the seawater temperature increases from 5 to 40°C. Figure 6(b) presents the changed behavior of the Brillouin scattering frequency shift with seawater temperature. In detail, the theoretical simulation result indicates that the Brillouin scattering frequency shift varies from 7.51 to 7.90 GHz with increasing seawater temperature, and the experimental result shows that the Brillouin scattering frequency shift increases from 7.41 to 7.85 GHz as the seawater temperature increases from 5 to 40°C. The sound speed varies from 1528.8 to 1539.8 m/s as the seawater salinity increases from 30 to 40 PSU in the simulation, and the experimental result shows good agreement with the simulation result, as shown in Fig. 6(c). Figure 6(d) shows that the Brillouin scattering frequency shift varies from 7.703 to 7.768 GHz when the seawater salinity increases from 30 to 40 PSU in the simulation, and the Brillouin scattering frequency shift varies from 7.694 to 7.758 GHz as the seawater salinity increases from 30 to 40 PSU in the experiment. The simulation results in Fig. 6 show good agreement with the experimental results, verifying the accuracy of the simulation model.
Fig. 6. The sound speed varies with the seawater temperature (a) and salinity (c), and the Brillouin scattering frequency shift varies with the seawater temperature (b) and salinity (d).
3.4 Global vertical profile distributions of the seawater sound speed and Brillouin scattering frequency shift
The analysis in Section 3.3 indicates that seawater temperature and salinity have a significant effect on the sound speed and Brillouin scattering frequency shift. Thus, based on Eqs. (4) and (5), the global vertical profile distributions of the seawater sound speed and Brillouin scattering frequency shift can be obtained by using the global temperature and salinity profile data provided by the China Argo Real-time Data Center [34]. Figure 7(a) presents the global vertical profile distribution of the seawater temperature at depths of 0 m, 50 m, 100 m, 150 m, and 200 m. The overall seawater temperature trend decreases as the depth increases from 0 to 200 m in the mid-low latitude regions, while it exhibits slight variations in the mid-to-high latitude areas. The global vertical profile distribution of seawater salinity varies from 31 to 39 PSU, as shown in Fig. 7(b). It is apparent from Fig. 7(c) that the vertical profile distribution of the seawater sound speed shows an overall downward trend as the depth increases from 0 to 200 m in the mid-low latitude regions. The global distribution of the surface seawater Brillouin scattering frequency shift varies from 7.25 to 7.75 GHz, and the vertical profile of the Brillouin scattering frequency shift exhibits a significant decreasing trend with increasing depth in the mid-low latitude regions, as shown in Fig. 7(d). Furthermore, the global vertical profile distribution of the seawater Brillouin scattering frequency shift shows the same variation tendency as that in the global vertical profile distributions of the seawater temperature, salinity, and sound speed at depths of 0 to 200 m. This phenomenon further verifies the functional relationship between the Brillouin scattering frequency shift and seawater temperature, salinity, and sound speed. Thus, we can retrieve the vertical profile of seawater temperature, salinity, and sound speed from the vertical profile distribution of the Brillouin scattering frequency shift collected by spaceborne Brillouin scattering lidar in the future.
Fig. 7. The global vertical profile distributions of the seawater temperature (a), salinity (b), sound speed (c), and Brillouin scattering frequency shift (d) at depths of 0 to 200 m.
4. Discussion
4.1 Effects of the lidar system parameters on the lidar detection performance
Different lidar system parameters have different effects on the detection performance. Here, the effects of the laser output pulse energy and aperture of the receiving telescope on the lidar detection performance are emphatically analyzed. Figures 8(a) and 8(b) show that the maximum detectable depths of lidar vary with the laser output pulse energy during the day and night, respectively. The laser output pulse energy is set to 0.05 J, 0.1 J, 0.5 J, 1 J, and 2 J under the condition that the other system parameters in Table 1 remain unchanged. As shown in Fig. 8(a), the maximum detectable depth of lidar increases from 24 m to 61 m as the laser output pulse energy increases from 0.05 J to 2 J during the day. The maximum detectable depth of lidar increases from 36 m to 73 m as the laser output pulse energy increases from 0.05 J to 2 J during the night, as shown in Fig. 8(b).
Fig. 8. The maximum detectable depth of lidar varies with the laser output pulse energy during the day (a) and night (b).
The maximum detectable depth of lidar varies with the aperture of the receiving telescope during the day and night, as shown in Fig. 9. The aperture of the receiving telescope is set to 0.2 m, 0.5 m, 1 m, 2 m, and 4 m under the condition that the other system parameters in Table 1 remain unchanged. Figure 9(a) shows that the maximum detectable depth of lidar increases from 27 m to 69 m as the aperture of the receiving telescope increases from 0.2 m to 4 m during the day. As shown in Fig. 9(b), the maximum detectable depth of lidar increases from 28 m to 88 m as the aperture of the receiving telescope increases from 0.2 m to 4 m during the night. The simulation results in Figs. 8 and 9 indicate that the laser output pulse energy and the aperture of the receiving telescope have a significant impact on the detection performance of lidar.
Fig. 9. The maximum detectable depths of lidar vary with the aperture of the receiving telescope during the day (a) and night (b).
4.2 Effects of the water environment parameters on the lidar detection performance in Case II water
The main factors affecting beam attenuation in Case I water bodies are pure seawater and chlorophyll concentration, while the effects of pure seawater, chlorophyll (Chl-a), colored dissolved organic matter (CDOM), and suspended particulate matter (SPM) on beam attenuation need to be considered in Class II water bodies, where the CDOM and SPM components contribute greatly to beam attenuation [35,36]. In this section, the effects of the CDOM and SPM concentrations in Case II water on lidar detection performance are discussed. The maximum detectable depths of lidar vary with the CDOM concentration during the day and night, as shown in Fig. 10. The CDOM absorption coefficient at 532 nm is set to 0.015 m-1, 0.036 m-1, 0.057 m-1, 0.077 m-1, 0.098 m-1 and 0.119 m-1 under the condition that the chlorophyll concentration of 0.5 mg/m3, SPM concentration of 1 g/m3 and other system parameters in Table 1 remain unchanged. Figure 10(a) shows that the maximum detectable depth of lidar decreases from 15.8 m to 10 m as the CDOM absorption coefficient at 532 nm increases from 0.015 m-1 to 0.119 m-1 during the day. The maximum detectable depth of lidar decreases from 19 m to 12 m, with the CDOM absorption coefficient at 532 nm increasing from 0.015 m-1 to 0.119 m-1 during the night, as shown in Fig. 10(b).
Fig. 10. The maximum detectable depths of lidar vary with the CDOM absorption coefficient at 532 nm during the day (a) and night (b).
The maximum detectable depths of lidar vary with the SPM concentration during the day and night, as shown in Fig. 11. The SPM concentration is set to 1 g/m3, 4 g/m3, 7 g/m3, 10 g/m3, 13 g/m3, and 16 g/m3 under the condition that the chlorophyll concentration of 0.5 mg/m3, CDOM absorption coefficient of 0.015 m-1 at 532 nm and other system parameters in Table 1 remain unchanged. Figure 11(a) shows that the maximum detectable depth of lidar decreases from 12.2 m to 8.2 m as the SPM concentration increases from 1 g/m3 to 16 g/m3 during the day. The maximum detectable depth of lidar decreases from 14.8 m to 10 m as the SPM concentration increases from 1 g/m3 to 16 g/m3 during the night, as shown in Fig. 11(b). Comparatively, only the beam attenuation of pure seawater and chlorophyll concentrations in Case I water are considered. Under the circumstance that a chlorophyll concentration of 0.5 mg/m3 and other system parameters in Table 1 remain unchanged, the maximum detection depths of lidar during the day and night are 40 m and 50 m, respectively. The simulation results in Figs. 10 and 11 indicate that the CDOM and SPM components in Case II water have significant impacts on the lidar detection performance.
Fig. 11. The maximum detectable depths of lidar vary with the SPM concentration during the day (a) and night (b).
4.3 Comparing the global spatiotemporal distribution of the maximum detectable depth for Brillouin scattering lidar and the mixed layer depth
The global distribution of the maximum detectable depths and corresponding optimum wavelengths for spaceborne Brillouin scattering lidar is analyzed in Section 3.2. The spatiotemporal variabilities of the mixed layer depth (MLD) are of primary significance because this depth contains key information about the dynamic and thermodynamic processes in the upper ocean. Whether lidar can penetrate the upper ocean mixed layer to obtain ocean environment parameters and optical profiles, such as temperature, salinity, sound speed, backscattering coefficient, etc., is a primary. These parameters can help us understand the dynamic and thermodynamic processes in the upper ocean. Thus, the global spatiotemporal distribution of the maximum detectable depth at the laser emission wavelength of 490 nm during the night and the mixed layer depth was further used for comparative analysis in this section. The global oceanic chlorophyll concentration data are from the level 3 2019 seasonal mean chlorophyll product MODIS-Aqua [31], and the global distribution of the 2019 seasonal mean ocean mixed layer depth is from the China Argo Real-time Data Center [34]. JFM, AMJ, JAS, and OND are the four seasons of January-February-March, April-May-June, July-August-September, and October-November-December, respectively.
Figures 12(a) and 12(b) present the global distributions of the maximum detectable depth at the laser emission wavelength of 490 nm during the night and the mixed layer depth in January-February-March, respectively. A comparative analysis was performed between the maximum detectable depth of lidar in Fig. 12(a) and the mixed layer depth in Fig. 12(b), and the result is shown in Fig. 12(c). The proportion of the lidar that completely penetrates the upper mixed layer (>100% MLD) is 75.15% in the global ocean. The proportion of the maximum detectable depths of lidar that are less than 50% of the mixed layer depth (< 50% MLD) is 15.21%, while the percentage of the laser penetration depths ranging from 50% to 100% of the mixed layer depth (50∼100% MLD) is 9.64% in the global ocean.
Fig. 12. The global distributions of the maximum detectable depths at the laser emission wavelength of 490 nm during the night (a) and the mixed layer depth (b) in January-February-March. (c) The percentage of lidar penetrating the upper mixed layer in the global ocean.
Figures 13(a) and 13(b) show the global distributions of the maximum detectable depths using 490 nm during the night and the mixed layer depth in April-May-June, respectively. In detail, the maximum detectable depth of lidar is relatively shallow in the mid-to-high latitudes, while the mixed layer depth is deeper in the mid-to-high latitudes. The penetration depth of lidar shows deeper detectable performance in mid-low latitude areas ($\textrm{4}{\textrm{0}^\textrm{o}}\mathrm{N\sim 4}{\textrm{0}^\textrm{o}}\textrm{S}$), while the mixed layer depth is relatively shallow in mid-low latitude regions ($\textrm{4}{\textrm{0}^\textrm{o}}\mathrm{N\sim 4}{\textrm{0}^\textrm{o}}\textrm{S}$). Thus, the ocean mixed layers in mid-low latitudes are more vulnerable to lidar penetration. As shown in Fig. 13(c), the percentage of the lidar that completely penetrates the upper mixed layer (>100% MLD) is 76.80% in the global ocean. The percentage of the lidar penetration depths that are less than 50% of the mixed layer depth (< 50% MLD) is 17.24%, while the percentages of the 50∼60% MLD, 70∼80% MLD, 80∼90% MLD, and 90∼100% MLD results are 0.97%, 1.16%, 1.45%, 2.11%, and 3.95%, respectively.
Fig. 13. The global distributions of the maximum detectable depths at the laser emission wavelength of 490 nm during the night (a) and the mixed layer depth (b) in April-May-June. (c) The percentage of lidar penetrating the upper mixed layer in the global ocean.
Figures 14(a) and 14(b) present the global distributions of the maximum detectable depths at the laser emission wavelength of 490 nm during the night and the mixed layer depth in July-August-September, respectively. It is apparent from Fig. 14(b) that the ocean mixed layer depth in the mid-to-high latitudes ($\textrm{4}{\textrm{0}^\textrm{o}}\mathrm{S\sim 8}{\textrm{0}^\textrm{o}}\textrm{S}$) is relatively deep compared to those in January-February-March and April-May-June. The results of the corresponding data analysis are shown in the pie chart (Fig. 14(c)). The lidar completely penetrates the upper mixed layer (>100% MLD), accounting for 59.12% of the global ocean. The lidar detectable depth is 50% to 100% of the mixed layer depth (50∼100% MLD), which accounts for 18.64% of the global ocean. The proportion of the lidar penetration depths that are less than 50% of the mixed layer depth (< 50% MLD) is 22.24%.
Fig. 14. The global distributions of the maximum detectable depths at the laser emission wavelength of 490 nm during the night (a) and the mixed layer depth (b) in July-August-September. (c) The percentage of lidar penetrating the upper mixed layer in the global ocean.
Fig. 15. The global distributions of the maximum detectable depths at the laser emission wavelength of 490 nm during the night (a) and the mixed layer depth (b) in October-November-December. (c) The percentage of lidar penetrating the upper mixed layer in the global ocean.
Figures 15(a) and 15(b) show the global distributions of the maximum detectable depths using 490 nm during the night and the mixed layer depth in October-November-December, respectively. The mixed layer depths in most of the global ocean are within the range of 10 m to 200 m. Then, a comparative analysis was performed between the lidar detectable depth in Fig. 15(a) and the mixed layer depth in Fig. 15(b), and the result is shown in Fig. 15(c). The percentage of the lidar that completely penetrates the upper mixed layer (>100% MLD) is 73.10% in the global ocean. The lidar detectable depth is 50% to 100% of the mixed layer depth (50∼100% MLD), which accounts for 10.74% of the global ocean. The proportion of the lidar penetration depths that are less than 50% of the mixed layer depth (< 50% MLD) accounts for 16.16% of the global ocean.
Based on the above comparative analysis of the lidar maximum detectable depth and the mixed layer depth for the four seasons, we concluded that the mean annual proportion of lidar penetrating the mixed layer accounts for 71.04% of the global ocean, with a range of 59.12∼76.80%. This means that the spaceborne Brillouin scattering lidar can penetrate the upper mixed layer to obtain the ocean environment parameters and optical profiles in most of the global ocean.
5. Conclusions
In this research, the potential of spaceborne Brillouin scattering lidar for generating global ocean optical profiles is studied. We found that the background noise caused by the solar spectral radiation, lidar system parameters, and the CDOM and SPM components in Case II water have significant effects on the lidar detection performance. Laser emission wavelengths of 490 nm and 540 nm are suitable for detecting open ocean waters and coastal waters, respectively. The detection depth of Brillouin scattering lidar operating at night is approximately 10 meters greater than that operating during the day. The vertical profile distribution of seawater sound and the Brillouin scattering frequency shift decrease as the depth increases from 0 to 200 m in the mid-low latitude regions. The percentages of spaceborne Brillouin scattering lidar that completely penetrate the upper mixed layer in January-February-March, April-May-June, July-August-September, and October-November-December are 75.15%, 76.80%, 59.12%, and 73.10%, respectively. These theoretical simulation results indicate that the spaceborne Brillouin scattering lidar has tremendous potential for wide-range and long-term monitoring of upper-ocean water bodies.
Funding
Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (GML2019ZD0602); National Science and Technology Major Project (05-Y30B01-9001-19/20-2); National Key Research and Development Program of China (2016YFC1400902); Second Institute of Oceanography, State Oceanic Administration (QNYC1803); National Natural Science Foundation of China (61991454); National Natural Science Foundation of China (41901305); Natural Science Foundation of Zhejiang Province (LQ19D060003).
Acknowledgments
The authors are grateful for all the suggestions from the anonymous reviewers, which helped us significantly improve the quality of the paper.
Disclosures
The authors declare no conflicts of interest.
Data availability
Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.
References
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