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Rapid assessment of algal blooms in bays and estuaries has been difficult due to lack of timely shipboard measurements and lack of spatial resolution from current ocean color satellites. Airborne measurements may fill the gap, yet they are often hindered by the high cost and difficulty in deployment. Here we demonstrate the capacity of a low-cost, low-altitude unmanned aerial vehicle (UAV) in assessing an intense phytoplankton ( Phaeocystis globosa ) bloom (chlorophyll concentrations ranged from 7.3 to 45.6 mg/m 3 ) in Weitou Bay in the western Taiwan Strait. The UAV was equipped with a hyperspectral sensor to measure the water color with a footprint of 5 m at every 30 m distance along the flight track. A novel approach was developed to obtain remote sensing reflectance ( R rs ) from the UAV at-sensor radiometric measurements. Compared with concurrent and co-located field measured R rs (14 stations in total), the UAV-derived R rs showed reasonable agreement with root mean square difference ranging 0.0028–0.0043 sr − 1 (relative difference ~ 20–32%) of such turbid waters for the six MODIS bands (412–667 nm). The magnitude of the bloom was further evaluated from the UAV-derived R rs . For the bloom waters, the estimated surface chlorophyll a concentration ( Chl ) ranged 6–98 mg/m 3 , which is 3–50 times of the Chl under normal conditions. This effort demonstrates for the first time a successful retrieval of both water color ( i.e. , R rs ) and Chl in a nearshore environment from UAV hyperspectral measurements, which advocates the use of UAVs for rapid assessment of water quality, especially for nearshore or difficult-to-reach waters, due to its flexibility, low cost, high spatial resolution, and sound accuracy. [ABSTRACT FROM AUTHOR]

In summer 2014, a toxic Karenia brevis bloom (red tide) occurred in the NE Gulf of Mexico, during which vertical migration of K. brevis has been observed from glider measurements. The current study shows that satellite observations from the Visible Infrared Imaging Radiometer Suite (VIIRS) can capture changes in surface reflectance and chlorophyll concentration occurring within 2 h, which may be attributed this K. brevis vertical migration. The argument is supported by earlier glider measurements in the same bloom, by the dramatic changes in the VIIRS-derived surface chlorophyll, and by the consistency between the short-term reflectance changes and those reported earlier from field-measured K. brevis vertical migration. Estimates using the quasi-analytical algorithm also indicate significant increases in both total absorption coefficient and backscattering coefficient in two hours. The two observations in a day from a single polar-orbiting satellite sensor are thus shown to be able to infer phytoplankton vertical movement within a short timeframe, a phenomenon difficult to capture with other sensors as each sensor can provide at most one observation per day, and cross-sensor inconsistency may make interpretation of merged-sensor data difficult. These findings strongly support geostationary satellite missions to study short-term bloom dynamics. [ABSTRACT FROM AUTHOR]

Satellites have generated extensive data of remote sensing reflectance spectra (R rs (λ)) covering diverse water classes or types across global waters. Spectral classification of satellite R rs (λ) data allows for the distinguishing and grouping of waters with characteristic bio-optical/biogeochemical features that may influence the productivity of a given water body. This study reports new satellite water class products (Level-2 and Level-3) from the Visible Infrared Imaging Radiometer Suite (VIIRS). We developed and implemented a hyperspectral scheme that accounts for the R rs (λ) spectral shapes and globally resolves oceanic, coastal, and inland waters into 23 water classes. We characterized the light absorption and scattering coefficients, chlorophyll-a concentration, diffuse attenuation coefficient, and suspended particulate matter for individual water classes. It is shown that the water classes are separable by their distinct bio-optical and biogeochemical properties. Furthermore, validation result suggests that the VIIRS water class products are accurate globally. Finally, we examined the spatial and temporal variability of the water classes in case studies for a demonstration of applications. The water class data in open oceans reveal that the subtropical ocean gyres have experienced dramatic expansion over the last decade. In addition, the water class data appear to be a valuable (and qualitative) indicator for water quality in coastal and inland waters with compelling evidence. We stress that this new satellite product is an excellent addition to the aquatic science database, despite the need for continuous improvement toward perfection. • First mission-long satellite water class products are created from VIIRS satellite. • A reflectance shape-based algorithm was used to resolve the global water classes. • The water classes feature distinct bio-optical and biogeochemical qualities. • Matchup analysis shows the water class products are reliable globally. • Great potentials are shown for aquatic ecology and water quality applications. [ABSTRACT FROM AUTHOR]

Satellite-derived remote-sensing reflectance ( R rs ) can be used for mapping biogeochemically relevant variables, such as the chlorophyll concentration and the Inherent Optical Properties (IOPs) of the water, at global scale for use in climate-change studies. Prior to generating such products, suitable algorithms have to be selected that are appropriate for the purpose. Algorithm selection needs to account for both qualitative and quantitative requirements. In this paper we develop an objective methodology designed to rank the quantitative performance of a suite of bio-optical models. The objective classification is applied using the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Using in situ R rs as input to the models, the performance of eleven semi-analytical models, as well as five empirical chlorophyll algorithms and an empirical diffuse attenuation coefficient algorithm, is ranked for spectrally-resolved IOPs, chlorophyll concentration and the diffuse attenuation coefficient at 489 nm. The sensitivity of the objective classification and the uncertainty in the ranking are tested using a Monte-Carlo approach (bootstrapping). Results indicate that the performance of the semi-analytical models varies depending on the product and wavelength of interest. For chlorophyll retrieval, empirical algorithms perform better than semi-analytical models, in general. The performance of these empirical models reflects either their immunity to scale errors or instrument noise in R rs data, or simply that the data used for model parameterisation were not independent of NOMAD. Nonetheless, uncertainty in the classification suggests that the performance of some semi-analytical algorithms at retrieving chlorophyll is comparable with the empirical algorithms. For phytoplankton absorption at 443 nm, some semi-analytical models also perform with similar accuracy to an empirical model. We discuss the potential biases, limitations and uncertainty in the approach, as well as additional qualitative considerations for algorithm selection for climate-change studies. Our classification has the potential to be routinely implemented, such that the performance of emerging algorithms can be compared with existing algorithms as they become available. In the long-term, such an approach will further aid algorithm development for ocean-colour studies. [ABSTRACT FROM AUTHOR]

Aquatic color radiometry remote sensing of coastal and inland water bodies is of great interest to a wide variety of research, management, and commercial entities as well as the general public. However, most current satellite radiometers were primarily designed for observing the global ocean and not necessarily for observing coastal and inland waters. Therefore, deriving coastal and inland aquatic applications from existing sensors is challenging. We describe the current and desired state of the science and highlight unresolved issues in four fundamental elements of aquatic satellite remote sensing namely, mission capability, in situ observations, algorithm development, and operational capacity. We discuss solutions, future plans, and recommendations that directly affect the science and societal impact of future missions with capability for observing coastal and inland aquatic systems. [ABSTRACT FROM AUTHOR]

For the past three decades, polar-orbiting ocean color satellites have provided local, regional to global scale estimates of oceanic net primary production that have greatly aided studies of ocean carbon cycling, food web dynamics and climate change. Despite considerable progress, accurate estimates of daily ocean productivity from space have not been realized because polar-orbiting satellites are unable to account for variations in phytoplankton physiology and carbon fixation rates from changing incident irradiance levels over the course of the day. Here we have attempted to exploit the unique short-temporal measurements provided by the Korean Geostationary Ocean Color Imager (GOCI), to obtain for the first time, diurnal and daily measurements of surface- and euphotic-column integrated Net Primary Productivity (NPP). These estimates are based on the Absorption Based Productivity Model (AbPM), and are calibrated with a bio-optical database of measurements made at different times of the day during the Korea-US Ocean Color (KORUS-OC) cruise in May–June 2016. Photo-physiological rate estimates, varied across different water types encountered around the Korean Peninsula, but on account of their limited number, were regionally scaled through the use of dynamic optical-biogeochemical (O-BGC) Biomes. Comparisons of GOCI derived estimates of daily and weekly integrated NPP against in-situ measurements, clearly underscore the superiority of geostationary over polar-orbiting ocean color satellites, which consider the strong short-term fluctuations in phytoplankton light absorption and incident irradiance fields over the course of the day. • The first attempt to model hourly NPP based on GOCI measurements using AbPM. • A novel dynamic optical-biogeochemical Biome is proposed to better estimate ϕ m. • The estimated NPP is highly consistent with that from field measurements. • The NPP estimated from GOCI matches better with field data than from other satellites. [ABSTRACT FROM AUTHOR]

Abstract: Retrievals of water quality parameters from satellite measurements over optically shallow waters have been problematic due to bottom contamination of the signals. As a result, large errors are associated with derived water column properties. These deficiencies greatly reduce the ability to use satellites to assess the shallow water environments around coral reefs and seagrass beds. Here, a modified version of an existing algorithm is used to derive multispectral diffuse attenuation coefficient (Kd) from MODIS/Aqua measurements over optically shallow waters in the Florida Keys. Results were validated against concurrent in situ data (Kd(488) from 0.02 to 0.20m−1, N=22, R2 =0.68, Mean Ratio=0.93, unbiased RMS=31%), and showed significant improvement over current products when compared to the same in situ data (N=13, R2 =0.37, Mean Ratio=1.61, unbiased RMS=50%). The modified algorithm was then applied to time series of MODIS/Aqua data over the Florida Keys (in particular, the Florida Keys Reef Tract), whereby spatial and temporal patterns of water clarity between 2002 and 2011 were elucidated. Climatologies, time series, anomaly images, and empirical orthogonal function analysis showed primarily nearshore–offshore gradients in water clarity and its variability, with peaks in both at the major channels draining Florida Bay. ANOVA revealed significant differences in Kd(488) according to distance from shore and geographic region. Excluding the Dry Tortugas, which had the lowest climatological Kd(488), water was clearest at the northern extent of the Reef Tract, and Kd(488) significantly decreased sequentially for every region along the tract. Tests over other shallow-water tropical waters such as the Belize Barrier Reef also suggested general applicability of the algorithm. As water clarity and light availability on the ocean bottom are key environmental parameters in determining the health of shallow-water plants and animals, the validated new products provide unprecedented information for assessing and monitoring of coral reef and seagrass health, and could further assist ongoing regional zoning efforts. [Copyright &y& Elsevier]

Water clarity is a well-established first-order indicator of water quality and has been used globally by water regulators in their monitoring and management programs. Assessments of water clarity in lakes over large temporal and spatial scales, however, are rare, limiting our understanding of its variability and the driven forces. In this study, we developed and validated a robust Secchi disk depth (Z SD) algorithm for lakes across China based on two water color parameters, namely Forel-Ule Index (FUI) and hue angle α, retrieved from MODIS data. The MODIS Z SD model shows good results when compared with in-situ measurements from 17 lakes, with a 27.4% mean relative difference (MRD) in the validation dataset. Compared with other empirical Z SD models, our FUI and α-based model demonstrates improved performance and adaptability over a wide range of water clarity and trophic states. This algorithm was subsequently applied to MODIS measurements to provide a comprehensive assessment of water clarity in large lakes (N = 153) across China for the first time. The mean summer Z SD of the studied lakes between 2000 and 2017 demonstrated marked spatial and temporal variations. Spatially, the Z SD of large lakes presented a distinct spatial pattern of "high west and low east" over China. This spatial pattern was found to be associated with the significant differences in lake depth and altitude between west and east China while China's population, GDP, temperature, and precipitation distribution have also contributed to a certain extent. Temporally, the Z SD of most lakes increased during this period, with an overall mean rate of 3.3 cm/yr for all lakes. Here, 38.6% (N = 59) of the lakes experienced a significant increase in their Z SD value during the past 18 years while only 8.5% (N = 13) showed a significant decreasing trend. Significant increases in lake Z SD were observed in west China, which were found to correlate with the increase of air temperature and lake surface area. This is possibly a response of the lakes in west China to climate change. In the lake systems of east China, which are predominately used as a drinking water source, the increase in lake Z SD was found to be strongly correlated with changes in local GDP (gross domestic production), NDVI (normalized difference vegetation index) and lake surface area, suggesting a combined effect of the implemented management practices and climatic variability. The results of this study provide important information for water quality conservation and management in China, and also highlight the value of satellite remote sensing in monitoring water quality over lakes at a large scale and long-term. • Developed a Z SD estimation algorithm for lakes in a wide range of water clarity based on FUI and α retrieved from MODIS data. • Revealed significant spatial and temporal patterns of water clarity in 153 large lakes across China between 2000 and 2017. • Water clarity in most of the lakes increased during the past 18-year period, especially in west China. • Significant increases of lake clarity in west China are attributed to the climate change. • Local GDP growth can contribute to the increase of lake clarity in east China. [ABSTRACT FROM AUTHOR]

Upwelling in the Equatorial Pacific nurtures an expansive, westward-stretching chlorophyll-rich tongue (CRT), supporting 18% of the annual global new production. Surrounding the CRT are the oligotrophic subtropical gyres to the north and south, which are suggested to be expanding under global warming. Yet, how this productive CRT has changed, expanding or contracting, remains unknown. By applying the empirical mode decomposition (EMD) method to 20-year monthly measurements of chlorophyll-a concentration from MODIS-Aqua satellite (2002-2022), we demonstrate that the CRT exhibited a significant westward extension, at an average expanding rate of 1.87 ( ± 0.82) × 10 5  km 2 /yr. The westward extension of the CRT is attributed to strengthened equatorial upwelling and a strengthened South Equatorial Current from 2002 to 2022, driven by intensified easterly trade winds as the Pacific Decadal Oscillation predominantly remains in its negative phase during this period. Interestingly, EMD analysis on central locations of the Pacific gyres suggested simultaneous extension of the gyres and the CRT during 2002-2022, with the gyres extending poleward. Our findings imply a broader cover of productive water along the equator, while its impact on tropical climate, ecosystems, and carbon cycle deserves further investigation., Competing Interests: Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Remotely sensed inherent optical properties (IOPs) are key proxies for synoptic mapping of primary production and carbon export in the global ocean. However, the IOPs inversion algorithms are scarcely evaluated in the Southern Ocean (SO) because of limited field observations. In this study, the performance of two widely used semi-analytical algorithms (SAAs), i.e., the quasi-analytical algorithm (QAA) and the generalized IOP model (GIOP), were evaluated using a compiled in situ bio-optical dataset in SO, as well as measurements from the Visible Infrared Imaging Radiometer Suite (VIIRS). Evaluations with in situ data show that QAA and GIOP have comparable performance in retrieving the total absorption coefficient (a(λ)), absorption coefficients of phytoplankton (a ph (λ)), and that of detritus and colored dissolved organic matter (a dg (λ)). Overall, it was found that remotely sensed a(λ) and a ph (λ) by both SAAs agreed well with field measurements, with the mean absolute percentage difference (MAPD) of derived a(λ) and a ph (λ) in the blue-green bands being ∼20% and ∼40%, respectively. However, derived a dg (λ) by both SAAs were higher than the measured values at the lower end (a dg (443) < ∼0.01 m -1 ), but lower at the higher end (a dg (443) > ∼0.02 m -1 ), with MAPD of ∼60%. Results of this effort suggest confident products of a(λ) and a ph (λ) from VIIRS in SO, but more dedicated efforts on the measurements and evaluation of a dg (λ) in SO would be desired.

Single-photon lidar has emerged as a strong technology for bathymetric measurements. However, its heightened sensitivity additionally makes it susceptible to solar radiation noise, particularly in the green light wavelength where solar radiation is strong, posing challenges for its daytime operation. To address this issue, a single-photon underwater lidar system is proposed and demonstrated. This scheme has these features. 1) Underwater applications not only mitigate the impact of the air-water interface on laser transmission but also significantly attenuate solar radiation reaching the lidar due to the absorption and scattering properties of water. 2) The telescope is designed with a small aperture and narrow field of view to significantly suppress solar radiation. 3) A combination of a narrowband laser and narrowband filter technique is effectively employed to minimize residual solar radiation, thus enabling continuous bathymetric observation capabilities during both day and night. 4) After acquiring the backscattered signal from the bottom, a water depth extraction algorithm utilizing bi-Gaussian fitting is proposed. To demonstrate the robustness of the lidar and the effectiveness of the algorithm, the underwater single-photon lidar system is deployed on a ship to conduct cruise surveys of two bays in the nearshore area, as well as a full-day stationary observation experiment. The lidar measurements are highly consistent with the synchronized sonar observations. The full-day stationary observation experiment showcased its capability to deliver continuous measurements throughout the day and night. These results demonstrate the potential of the system in various applications, including high-precision underwater terrain mapping, obstacle avoidance for underwater platforms, and underwater target imaging.

A novel oceanic fluorescence lidar technique has been proposed and demonstrated for remotely sensing the volume scattering function at 180° (βf), which can be used to further retrieve the profiles of the absorption coefficient of phytoplankton (aph) at 532 nm and chlorophyll concentration (Chl). This scheme has these features. 1) The single-photon detection technology is employed to enhance the detection sensitivity to the single-photon level, enabling the oceanic lidar to obtain fluorescence backscatter profiles. 2) In terms of algorithms, the Raman backscattered signals of the water are utilized to normalize the backscattered signals of chlorophyll fluorescence, effectively minimizing the depth-dependent variation of the differential lidar attenuation coefficient ( Δ K l i d a r f r ). To reduce the contamination of fluorescence signals in the Raman backscatter signals, a Raman filter with a bandwidth of 6 nm was chosen. Subsequently, a perturbation method is utilized to invert the βf of the fluorescence lidar. Finally, aph and Chl profiles can be inverted based on empirical models. 3) The value of Δ K l i d a r f r used in inversion is obtained through a semi-analytic Monte Carlo simulation. According to theoretical analysis, the maximum relative error of βf for Chl ranging from 0.01 mg/m 3 to 10 mg/m 3 is less than 13 %. To validate this approach, a field experiment was conducted aboard the R/V Tan Kah Kee in the South China Sea from September 4th to September 5th, 2022, resulting in continuous subsurface profiles of βf, aph, and Chl. These measurements confirm the robustness and reliability of the oceanic single-photon fluorescence lidar system and the inversion algorithm.

The attenuation coefficient of natural waters plays a significant role in our understanding of hydrology from both the oceanographic and biological point of view. The advent of near-continuous observations by sophisticated space-based lidars now offers an unprecedented opportunity to characterize attenuation coefficients over open oceans on global and regional scales. At present, however, literature reports of lidar-derived attenuation coefficient estimates (klidar, m -1 ) in oceanic waters are very limited. In this study, we present a global survey of klidar derived from ATLAS/ICESat-2 nighttime measurements. Our results augment the existing passive sensor ocean color data set with a new diurnal component and extend the record to now include previously unavailable polar nighttime observations. The values of ATLAS measured klidar at 532 nm are between 0.045 and 0.39 m -1 with the higher values (>0.15 m -1 ) correlated with coastal waters and sea ice covered oceans. The average klidar in clearest oligotrophic ocean gyres is ∼0.058 ± 0.012 m -1 at 532 nm. The results reported here demonstrate the feasibility of using ATLAS/ICESat-2 lidar measurements for global klidar studies, which will in turn provide critical insights that enable climate models to correctly describe the amount of light present under sea ice, and for heat deposition studies in the upper ocean.

A lidar technique has been proposed and demonstrated for remotely sensing particulate beam attenuation coefficient (cp) profiles using the Raman backscattered signal from water. In Raman lidar, the backscatter coefficient at 180° can be considered constant, allowing for the determination of the lidar attenuation coefficient (Klidar) from the Raman backscattered signal. This scheme has these features. 1) The bandwidth of the filter that used to extract the Raman component from the backscattered signal of the lidar was optimized to ensure sufficient lidar signal strength while minimizing the influence of chlorophyll fluorescence on inversion. 2) A receiving telescope with narrow field of view (FOV) and small aperture was utilized to suppress multi-scattering components in the backscattered signal. 3) A relationship between the beam attenuation coefficient (c) and Klidar was established after simulations via a semi-analytic Monto Carlo. 4) The value of cp was obtained by subtracting the attenuation coefficient of pure seawater (cw) from c. According to the theoretical analysis, the maximum relative error of cp is less than 15% for chlorophyll concentrations up to 10 mg/m 3 . Due to the water Raman backscattered signal being several orders of magnitude lower than the elastic backscattered signal, a single-photon detector is required to significantly improve the detection sensitivity to the single-photon level. To validate this approach, a field experiment was conducted aboard the R/V Tan Kah Kee in the South China Sea from September 4th to September 5th, 2022, and continuous subsurface profiles of cp were obtained. These measurements confirm the robustness and reliability of the oceanic single-photon Raman lidar system and the inversion method.

Measuring the characteristics of seawater constituent is in great demand for studies of marine ecosystems and biogeochemistry. However, existing techniques based on remote sensing or in situ samplings present various tradeoffs with regard to the diversity, synchronism, temporal-spatial resolution, and depth-resolved capacity of their data products. Here, we demonstrate a novel oceanic triple-field-of-view (FOV) high-spectral-resolution lidar (HSRL) with an iterative retrieval approach. This technique provides, for the first time, comprehensive, continuous, and vertical measurements of seawater absorption coefficient, scattering coefficient, and slope of particle size distribution, which are validated by simulations and field experiments. Furthermore, it depicts valuable application potentials in the accuracy improvement of seawater classification and the continuous estimation of depth-resolved particulate organic carbon export. The triple-FOV HSRL with high performance could greatly increase the knowledge of seawater constituents and promote the understanding of marine ecosystems and biogeochemistry., (Copyright © 2023 Kai Zhang et al.)

The effective sea-surface skylight reflectance (ρ) is an important parameter for removing the contribution of surface-reflected radiance when measuring water-leaving radiance (Lw) using the above-water approach (AWA). Radiative simulations and field measurements show that ρ varies spectrally. To improve the determination of Lw (and then remote sensing reflectance, Rrs) from the AWA, we further developed a wavelength-dependent model for ρ to remove surface-reflected radiance, which is applied with a spectral optimization approach for the determination of Rrs. Excellent agreement was achieved between the AWA-derived and skylight-blocked approach (SBA)-obtained Rrs (coefficient of determination > 0.92, mean absolute percentage deviation < ∼ 11% for Rrs > 0.0005 sr -1 ), even during high wave conditions. We found that the optimization approach with the new ρ model worked very well for a wide range of water types and observation geometries. For developing remote sensing algorithms and evaluating satellite products, it would be beneficial to apply this approach to current and historical above-water in situ measurements of Rrs to improve the quality of these data. In addition, this approach could also increase the number of useable spectra where previously rendered unusable when processed with a traditional scheme.

Small water bodies are an important part of the Earth's freshwater system, protecting biodiversity and providing ecosystem services. Because of various surrounding features, it is unknown to what extent we can obtain accurate remote-sensing reflectance ( R rs ) of such an environment by the conventional above-water approach (AWA). In this study, we used both AWA and the skylight-blocked approach (SBA) side-by-side to measure R rs in a typical small water body. It was found that the variation of R rs in the UV-blue domain from AWA is around 50% and is inconsistent with the variation of the total absorption coefficient ( a t ) obtained from water samples; on the contrary, the variation of R rs obtained from SBA is highly consistent, with a coefficient of variation under ∼5 % . These results highlight the large uncertainties in the measured R rs from AWA due to the complexity of such an environment and further echo the robustness of SBA to measure R rs in the field, even in such challenge environments.

Water-leaving albedo (α w (λ)) is an important component of the ocean surface albedo and is conventionally estimated based on remotely sensed chlorophyll-a concentration (Chl) (termed Chl-α w ). We show that estimated α w (λ) by Chl-α w could be significantly biased in global oceans, because there is no guarantee of closure between the modeled remote sensing reflectance (R rs (λ)) from Chl-inferred inherent optical properties (IOPs) and the input R rs (λ) that is used to derive Chl. We thus propose a simple and improved scheme, termed Chl-α w &#95;new, and show that the step to infer IOPs from Chl is not necessary, where α w (λ) can be accurately estimated from satellite-measured R rs (λ) and a Chl-based look-up-table (LUT) for the bidirectional relationships of angular R rs (λ). Evaluations with both HydroLight simulations and satellite measurements show that Chl-α w &#95;new is equivalent to the recently developed α w scheme based on IOPs (IOPs-α w , [Remote Sens. Environ. 269, 112807]), where both schemes could significantly improve the estimation of α w (λ) compared to Chl-α w . Comparisons among Chl-α w , Chl-α w &#95;new, and IOPs-α w highlight that optical closure of R rs (λ) is essential for accurate remote sensing of α w (λ), while the model for R rs (λ) bidirectionality has rather minor impacts. The impact of improved α w (λ) estimations on the solar flux exchanges at the air-sea interface is preliminarily evaluated in this effort, where the use of Chl-α w &#95;new could increase the estimation of reflected solar radiation by over 68.7% in turbid waters compared to that using Chl-α w , highlighting the necessity of incorporating accurate α w schemes into the coupled ocean-atmosphere models, especially for regional models in coastal oceans.

Water-leaving albedo (αw(λ)) is an important component of the ocean surface albedo. Direct measurement of αw(λ) in the field is not yet available due to difficulties in removing the contribution of surface-reflected solar radiation. Following the concept of the skylight-blocked approach (SBA), a novel system, termed α w SBA, is proposed in this study to directly measure Ew(λ), where a wide-angle black cone is used to block the surface-reflected radiance. The shading errors associated with the cone and the measuring system are examined via Monte-Carlo (MC) simulations for a wide range of water inherent optical properties (IOPs), solar zenith angle, and different configurations of the α w SBA system (i.e., half cone angle, and the length of supporting arm). Based on sensitive analysis using MC simulations, an optimal configuration of α w SBA is recommended. We further propose a mathematical expression to parameterize the shading error (ɛ), along with an error correction scheme (α w OPT). It is found that, with the optimal configuration and α w OPT, the uncertainties of obtained αw(λ) by α w SBA are generally less than 7% for a wide range of waters with different IOPs and particulate scattering phase functions.

In this study, six algorithms (both empirical and semi-analytical) developed for the estimation of Kd in the ultraviolet (UV) domain (specifically 360, 380, and 400 nm) were evaluated from a dataset of 316 stations covering oligotrophic ocean and coastal waters. In particular, the semi-analytical algorithm (Lee et al. 2013) used remote sensing reflectance in these near-blue UV bands estimated from a recently developed deep learning system as the input. For Kd(380) in a range of 0.018 - 2.34 m -1 , it is found that the semi-analytical algorithm has the best performance, where the mean absolute relative difference (MARD) is 0.19, and the coefficient of determination (R 2 ) is 0.94. For the empirical algorithms, the MARD values are 0.23-0.90, with R 2 as 0.70-0.92, for this evaluation dataset. For a VIIRS and in situ matchup dataset (N = 62), the MARD of Kd(380) is 0.21 (R 2 as 0.94) by the semi-analytical algorithm. These results indicate that a combination of deep learning system and semi-analytical algorithms can provide reliable Kd(UV) for past and present satellite ocean color missions that have no spectral bands in the UV, where global Kd(UV) products are required for comprehensive studies of UV radiation on marine primary productivity and biogeochemical processes in the ocean.

Reliable in situ water-leaving radiance (Lw) measurements are critical for calibrating and validating the ocean color products from remote platforms (e.g., satellite). In an experimental effort, Wei et al. [Opt. Express29, 2780 (2021)10.1364/OE.413784] reported that the on-water radiometry allows for high-precision radiance determination. Zibordi [Opt. Express29, 19214 (2021)10.1364/OE.421786] questioned the use of the "1% radiometry" term in the former and commented on the data collection with the sensor's optical window submerged in water. This reply responds to the comments and discusses the on-water data processing protocol, which shows the obtained Lw is not affected by the questions raised therein.

For waters with stratified chlorophyll concentration (Chl), numerical simulations were carried out to gain insight into the forward models of subsurface reflectance and empirical algorithms for Chl from the ocean color. It is found that the Gordon and Clark (1980) forward model for reflectance using an equivalent homogeneous water with a weighted average Chl (⟨ C h l ⟩) as the input works well, but depending on the contribution of gelbstoff, the difference in reflectance between stratified and the equivalent homogeneous water can be more than 10%. Further, the attenuation of upward light is better approximated as ∼1.5 t i m e s that of the diffuse attenuation coefficient of downwelling irradiance. On the other hand, although the forward model for reflectance developed in Zaneveld et al. [Opt. Express13, 9052 (2005)] using equivalent homogeneous water with a weighted average of the backscattering to absorption ratio as the input also works well, this model cannot be used to obtain equivalent ⟨ C h l ⟩ for reflectance. Further, for empirical Chl algorithms designed for "Case 1" waters, it has been discovered that, for surface Chl in a range of ∼0.06-22.0 m g / m 3 , the predictability of surface Chl is basically the same as that of ⟨ C h l ⟩ from the blue-green band ratio or the band difference of reflectance. Because ⟨ C h l ⟩ is wavelength and weighting-formula dependent, and it is required to have profiles of both Chl and the optical properties, these results emphasize that for empirical Chl algorithms, it is easier, less ambiguous, and certainly more straightforward and simple to use surface Chl for algorithm development and then its evaluation, rather than to use ⟨ C h l ⟩, regardless of whether or not the water is stratified.

In this paper, with a revised POLYMER (POLYnomial based approach applied to MERIS data) atmospheric correction model, we present a novel scheme (two-angle atmospheric correction algorithm, termed as TAACA) to remove atmospheric contributions in satellite ocean color measurements for coastal environments, especially when there are absorbing aerosols. TAACA essentially uses the same water properties as a constraint to determine oceanic and atmospheric properties simultaneously using two same-day consecutive satellite images having different sun-sensor geometries. The performance of TAACA is first evaluated with a synthetic dataset, where the retrieved remote-sensing reflectance (Rrs) by TAACA matches very well (the coefficient of determination (R 2 ) ≥ 0.98) with the simulated Rrs for each wavelength, and the unbiased root mean square error (uRMSE) is ∼12.2% for cases of both non-absorbing and strongly absorbing aerosols. When this dataset is handled by POLYMER, for non-absorbing aerosol cases, the R 2 and uRMSE values are ∼0.99 and ∼7.5%, respectively, but they are ∼0.92 and ∼39.5% for strongly absorbing aerosols. TAACA is further assessed using co-located VIIRS measurements for waters in Boston Harbor and Massachusetts Bay, and the retrieved Rrs from VIIRS agrees with in situ measurements within ∼27.3% at the visible wavelengths. By contrast, a traditional algorithm resulted in uRMSE as 3890.4% and 58.9% at 410 and 443 nm, respectively, for these measurements. The Rrs products derived from POLYMER also show large deviations from in situ measurements. It is envisioned that more reliable Rrs products in coastal waters could be obtained from satellite ocean color measurements with a scheme like TAACA, especially when there are strongly absorbing aerosols.

Low-power, lightweight, off-the-shelf imaging spectrometers, deployed on above-water fixed platforms or on low-altitude aerial drones, have significant potential for enabling fine-scale assessment of radiometrically derived water quality properties (WQPs) in oceans, lakes, and reservoirs. In such applications, it is essential that the measured water-leaving spectral radiances be corrected for surface-reflected light, i.e., glint. However, noise and spectral characteristics of these imagers, and environmental sources of fine-scale radiometric variability such as capillary waves, complicate the glint correction problem. Despite having a low signal-to-noise ratio, a representative lightweight imaging spectrometer provided accurate radiometric estimates of chlorophyll concentration-an informative WQP-from glint-corrected hyperspectral radiances in a fixed-platform application in a coastal ocean region. Optimal glint correction was provided by a spectral optimization algorithm, which outperformed both a hardware solution utilizing a polarizer and a subtractive algorithm incorporating the reflectance measured in the near infrared. In the same coastal region, this spectral optimization approach also provided the best glint correction for radiometric estimates of backscatter at 650 nm, a WQP indicative of suspended particle load.

Coastal water clarity varies at high temporal and spatial scales due to weather, climate, and human activity along coastlines. Systematic observations are crucial to assessing the impact of water clarity change on aquatic habitats. In this study, Secchi disk depths (Z SD ) from Boston Harbor, Buzzards Bay, Cape Cod Bay, and Narragansett Bay water quality monitoring organizations were compiled to validate Z SD derived from Landsat 8 (L8) imagery, and to generate high spatial resolution Z SD maps. From 58 L8 images, acceptable agreement was found between in situ and L8 Z SD in Buzzards Bay (N = 42, RMSE = 0.96 m, MAPD = 28%), Cape Cod Bay (N = 11, RMSE = 0.62 m, MAPD = 10%), and Narragansett Bay (N = 8, RMSE = 0.59 m, MAPD = 26%). This work demonstrates the value of merging in situ Z SD with high spatial resolution remote sensing estimates for improved coastal water quality monitoring., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)