Neural network spectral relationship to improve an inherent optical properties data processing system for residual error correction.

The residual error was a critical indicator to measure the data quality of ocean color products, which allows a user to decide the valuable envisioned application of these data. To effectively remove the residual errors from satellite remote sensing reflectance (Rrs) using the inherent optical data processing system (IDAS), we expressed the residual error spectrum as an exponential plus linear function, and then we developed neural network models to derive the corresponding spectral slope coefficients from satellite Rrs data. Coupled with the neural network models-based spectral relationship, the IDAS algorithm (IDASnn) was more effective than an invariant spectral relationship-based IDAS algorithm (IDAScw) in reducing the effects of residual errors in Rrs on IOPs retrieval for our synthetic, field, and Chinese Ocean Color and Temperature Scanner (COCTS) data. Particularly, due to the improved spectral relationship of the residual errors, the IDASnn algorithm provided more accurate and smoother spatiotemporal ocean color product than the IDAScw algorithm for the open ocean. Furthermore, we could monitor the data quality with the IDASnn algorithm, suggesting that the residual error was exceptionally large for COCTS images with low effective coverage. The product effective coverage should be rigorously controlled, or the residual error should be accurately corrected before temporal and spatial analysis of the COCTS data. Our results suggest that an accurate spectral relationship of residual errors is critical to determine how well the IDAS algorithm corrects for residual error.

Remote sensing of seawater optical properties and the subsurface phytoplankton layer in coastal waters using an airborne multiwavelength polarimetric ocean lidar.

The vertical profiles of the seawater optical properties and subsurface phytoplankton layer observed during an airborne lidar flight experiment carried out on 29 January 2021 in the coastal waters near Qionghai city were studied. We employed a hybrid inversion model combining the Klett and perturbation retrieval methods to estimate the seawater optical properties, while the vertical subsurface phytoplankton layer profiles were obtained by an adaptive evaluation. The airborne lidar data preprocessing scheme and inversion of the seawater optical properties were described in detail, and the effects of water environment parameters on the airborne lidar detection performance in coastal waters were discussed. The obtained seawater optical properties and phytoplankton layer profiles exhibit characteristic spatiotemporal distributions. The vertical stratification of seawater optical properties along a flight track from 19.19°N to 19.27°N is more pronounced than that from 19.27°N to 19.31°N. The subsurface phytoplankton layer appears along the flight track at water depths of 5-14 m with a thickness of 2-8.3 m. The high concentrations of chlorophyll, colored dissolved organic matter (CDOM), and suspended particulate matter (SPM) in coastal waters are the main factors leading to the shallower detection depth for airborne lidar. A 532 nm laser emission wavelength is more suitable than 486 nm for investigating coastal waters. The 532 nm receiving channel with 25 mrad receiving field of view achieves a better detection performance than that with 6 mrad. These results indicate that lidar technology has great potential for the wide-range and long-term monitoring of coastal waters.

Forward volume scattering function (0.03°-60°) measured using an oblique-incidence particle sizer.

The forward volume scattering function (VSF) is an inherent optical property important in ocean lidar and underwater imaging and communication. The scattered power within 60° contains >90% of total scattered power, making it essential for determining the asymmetry parameter g. Thus, the new oblique-incidence-design Bettersize BT-3000 particle sizer was utilized to measure forward VSF (0.03°-60°) synchronously. A double-exponential model was then used to construct the full-angle-range VSF (0°-180°). The g value calculated therefrom had an uncertainty of <1%. Calibration was implemented using 11-µm beads alone, and the BT-3000's performance was validated.

Detecting subsurface phytoplankton layer in Qiandao Lake using shipborne lidar.

Qiandao Lake is located in the northern edge of subtropics, and its water body is thermally stratified in summer. It is of great scientific significance to study the vertical physical and chemical indexes and phytoplankton characteristics of the Qiandao Lake to reveal the aquatic ecosystem structure of the thermally stratified lake. Conventional observation uses in-situ profile instruments, which is time consuming and labor intensive. In recent years, lidar has shown increasing oceanic applications; however, it has not yet been extensively applied in inland water. There are no studies using lidar for detecting subsurface plankton layer in Qiandao Lake. In this study, we investigated the applicability of this technology for identifying subsurface plankton layer. A simple and fast phytoplankton layer detection method was introduced. The lidar-detected layer was found to well correspond with that of the in-situ measured subsurface chlorophyll maximum layer (SCML) and phycocyanin maximum layer. Primary results show that lidar and our detection method are effective for subsurface phytoplankton layer detection. They can serve as a good monitoring tool for studying inland water stratification.

Iterative retrieval method for ocean attenuation profiles measured by airborne lidar.

Lidar remote sensing for ocean optical properties has been increasingly applied because of its ability to provide vertical structure information, which cannot be directly obtained by ocean color remote sensing. However, the application of this technology demands an inversion method to infer two quantities, i.e., attenuation and backscatter, from a single measurement. Here, a new iterative retrieval method is demonstrated to deduce the attenuation coefficient from ocean lidar return signals. One calculates the logarithmic backscatter-to-attenuation ratio k by an iterative solution based on a bio-optical model. Procedural examples of lidar-processing results-from raw data to attenuation-are presented, and the inversion results are compared with in situ measurements. The correlation coefficient R between the lidar-retrieval and in situ measurements is 0.8, and the root mean square error (RMSE) is 0.032. We then map the vertical structure of the lidar-retrieved attenuation along airborne lidar flight tracks and discuss the influences of k, the reference depth zm, and the reference value αm. Consequently, the reference value has little influence on the results for high-optical-thickness water, and k is the main error source in lidar return inversion. Primary results indicate that this method provides a more accurate k and improves the inversion accuracy of the lidar attenuation coefficient.

Subsurface plankton layers observed from airborne lidar in Sanya Bay, South China Sea.

In recent years, airborne lidar has been used in a wide range of oceanic applications, including detection of bathymetry, bubbles, internal waves, and schools of fish. However, it has not yet been extensively applied in Chinese seas. For example, there have been no studies to detect subsurface plankton layers in the South China Sea (SCS) by airborne lidar. In this study, we investigated this technology's applicability for identifying subsurface plankton layers in Sanya Bay, SCS. Three airborne lidar flight experiments were carried out in March 2018 and in September 2017. Shipboard synchronous measurements were carried out in March 2018 to validate the lidar measurements. The method that is presented here can be used to detect a subsurface plankton layer, which is characterized by depth, thickness, and intensity. Compared with chlorophyll-a profile synchronously measured by shipborne fluorometer, there was a consistent relationship. The subsurface plankton layer depth error was less than 0.7 m. Next, the spatial distribution and seasonal variation of lidar measured subsurface plankton layers in Sanya Bay, SCS, was analyzed. The results showed that airborne lidar can potentially detect subsurface plankton layer within 50 meters deep in relatively clear water. This will enhance our understanding of biogeochemical processes in these optically complex aquatic systems.

High-Frequency Observation of Water Spectrum and Its Application in Monitoring of Dynamic Variation of Suspended Materials in the Hangzhou Bay.

In situ measurement of water spectrum is the basis of the validation of the ocean color remote sensing. The traditional method to obtain the water spectrum is based on the shipboard measurement at limited stations, which is difficult to meet the requirement of validation of ocean color remote sensing in the highly dynamic coastal waters. To overcome this shortage, continuously observing systems of water spectrum have been developed in the world. However, so far, there are still few high-frequency observation systems of the water spectrum in coastal waters, especially in the highly turbid and high-dynamic waters. Here, we established a high-frequency water-spectrum observing system based on tower in the Hangzhou Bay. The system measures the water spectrum at a step of 3 minutes, which can fully match the satellite observation. In this paper, we primarily developed a data processing method for the tower-based high-frequency water spectrum data, to realize automatic judgment of clear sky, sun glint, platform shadow, and weak illumination, etc. , and verified the processing results. The results show that the normalized water-leaving radiance spectra obtained through tower observation have relatively high consistency with the shipboard measurement results, with correlation coefficient of more than 0. 99, and average relative error of 9.96%. In addition, the long-term observation capability of the tower-based high-frequency water-spectrum observing system was evaluated, and the results show that although the system has run for one year, the normalized water-leaving radiance obtained by this system have good consistency with the synchronously measurement by Portable spectrometer ASD in respect of spectral shape and value, with correlation coefficient of more than 0.90 and average relative error of 6.48%. Moreover, the water spectra from high-frequency observation by the system can be used to effectively monitor the rapid dynamic variation in concentration of suspended materials with tide. The tower-based high-frequency water-spectrum observing system provided rich in situ spectral data for the validation of ocean color remote sensing in turbid waters, especially for validation of the high temporal-resolution geostationary satellite ocean color remote sensing.

Research ReportDiurnal global ocean surface pCO2 and air-sea CO2 flux reconstructed from spaceborne LiDAR data.

The ocean absorbs a significant amount of carbon dioxide (CO2) from the atmosphere, helping regulate Earth's climate. However, our knowledge of ocean CO2 sink levels remains limited. This research focused on assessing daily changes in ocean CO2 sink levels and air-sea CO2 exchange, using a new technique. We used LiDAR technology, which provides continuous measurements during day and night, to estimate global ocean CO2 absorption over 23 years. Our model successfully reproduced sea surface partial pressure of CO2 data. The results suggest the total amount of CO2 absorbed by oceans is higher at night than during the day. This difference arises from a combination of factors like temperatures, winds, photosynthesis, and respiration. Understanding these daily fluctuations can improve predictions of ocean CO2 uptake. It may also help explain why current carbon budget calculations are not fully balanced-an issue scientists have grappled with. Overall, this pioneering study highlights the value of LiDAR's unique day-night ocean data coverage. The findings advance knowledge of ocean carbon cycles and their role in climate regulation. They underscore the need to incorporate day-night variability when assessing the ocean's carbon sink capacity.

The carbon sink of the Coral Sea, the world's second largest marginal sea, weakened during 2006-2018.

The latest reports show that the ocean absorbs approximately 26 % of anthropogenic CO2 and that the carbon sink of the global ocean (air-sea CO2 flux) is continually increasing, while variations in different marginal seas are complicated. The Coral Sea, the second largest marginal sea in the world, is characterized by a generally oligotrophic basin and borders the biodiversity hotspot of Great Barrier Reef. In this study, we proposed a semianalytical method and reconstructed the first high-resolution satellite-based pCO2 and air-sea CO2 flux dataset from 2006 to 2018 for the Coral Sea. This dataset performed well in the basin (RMSE<10 µatm, R2 > 0.72) and coral reef areas (RMSE<12 µatm, R2 > 0.8) based on validation by a massive independent dataset. We found that sea surface pCO2 is increasing (1.8 to 2.7 µatm/year) under the forcing of increasing atmospheric CO2, and the pCO2 growth rate in water is faster than that in the atmosphere. The combination of increasing sea surface pCO2, high pCO2 seawater from coral reef areas, and the low depletion capacity of the oligotrophic basin led to a gradual weakening of the carbon sink in the Coral Sea, with the 2016 carbon sink being 52 % of that in 2006. This weakening was more pronounced after strong El Niño events (e.g., 2007, 2010, and 2016), with the corresponding high SST and low wind speed further weakening the carbon sink. This understanding of the long-term change in the Coral Sea provides new insight on the carbonate system variation and carbon sink capacity evolution in seawater under increasing atmospheric CO2.

Atmospheric correction of satellite ocean color imagery using the ultraviolet wavelength for highly turbid waters.

Instead of the conventionally atmospheric correction algorithms using the near-infrared and shortwave infrared wavelengths, an alternative practical atmospheric correction algorithm using the ultraviolet wavelength for turbid waters (named UV-AC) is proposed for satellite ocean color imagery in the paper. The principle of the algorithm is based on the fact that the water-leaving radiance at ultraviolet wavelengths can be neglected as compared with that at the visible light wavelengths or even near-infrared wavelengths in most cases of highly turbid waters due to the strong absorption by detritus and colored dissolved organic matter. The UV-AC algorithm uses the ultraviolet band to estimate the aerosol scattering radiance empirically, and it does not need any assumption of the water's optical properties. Validations by both of the simulated data and in situ data show that the algorithm is appropriate for the retrieval of the water-leaving radiance in turbid waters. The UV-AC algorithm can be used for all the current satellite ocean color sensors, and it is especially useful for those ocean color sensors lacking the shortwave infrared bands. Moreover, the algorithm can be used for any turbid waters with negligible water-leaving radiance at ultraviolet wavelength. Based on our work, we recommend the future satellite ocean color remote sensors setting the ultraviolet band to perform the atmospheric correction in turbid waters.

Evaluation of the aerosol models for SeaWiFS and MODIS by AERONET data over open oceans.

The operational atmospheric correction algorithm for Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) uses the predefined aerosol models to retrieve aerosol optical properties, and their accuracy depends on how well the aerosol models can represent the real aerosol optical properties. In this paper, we developed a method to evaluate the aerosol models (combined with the model selection methodology) by simulating the aerosol retrieval using the Aerosol Robotic Network (AERONET) data. Our method can evaluate the ability of aerosol models themselves, independent of the sensor performance. Two types of aerosol models for SeaWiFS and MODIS operational atmospheric correction algorithms are evaluated over global open oceans, namely the GW1994 models and Ahmad2010 models. The results show that GW1994 models significantly overestimate the aerosol optical thicknesses and underestimate the Ångström exponent, which is caused by the underestimation of the scattering phase function. However, Ahmad2010 models can significantly reduce the overestimation of the aerosol optical thickness and the underestimation of the Ångström exponent as a whole, but this improvement depends on the backscattering angle. Ahmad2010 models have a significant improvement in the retrieval of the aerosol optical thickness at a backscattering angle less than 140°. For a backscattering angle larger than 140°, GW1994 models are better at retrieving the aerosol optical thickness than the Ahmad2010 models.

Changes in riverine organic carbon input to the ocean from mainland China over the past 60 years.

Compared to rivers in Europe and North America, Chinese rivers that discharge into oceans have different organic carbon (OC) transport characteristics. Out of the top 25 largest rivers worldwide, three (Changjiang, Huanghe, and Zhujiang rivers) are located in China, along with numerous small rivers. Thus, synthesized estimates of total riverine OC flux from Chinese rivers into marginal seas are critical but remain deficient. In this study, we developed relationships between riverine OC (dissolved OC, or DOC, and particulate OC, or POC) and basin characteristic variables (basin population density, precipitation, and riverine suspended sediment concentration) to estimate annual riverine DOC and POC fluxes during 1953-2016. The results showed that rivers in mainland China transported 9.63 Tg C of OC to the marginal seas in 2008, with 4.61 Tg C of DOC and 5.02 Tg C of POC. Of this transported OC, 14.28% DOC and 17.49% POC were transported by small southeastern rivers, whose drainage areas covered only 6.68% of the total. Because of intensifying human activities, DOC export increased but POC export decreased during 1953-2016. Additionally, basin population growth and reservoir water capacity were the major factors for increasing DOC flux and decreasing POC flux, respectively. Overall, the DOC/POC ratio increased for OC transport in Chinese rivers. Therefore, this study is important for understanding human-induced impacts on environmental change and the carbon cycle in marginal seas.

Impact of ENSO events on phytoplankton over the Sulu Ridge.

Phytoplankton response to interannual climate variability has an important regulatory effect on the regional marine ecological environment and carbon cycle. In this study, we focused on the phytoplankton response in the upwelling region of the Sulu Ridge to the El Niño-Southern Oscillation (ENSO) based on monthly remote sensing chlorophyll-a concentration (Chl-a) and physical parameters from various sources from September 1997 to December 2017. We selected two El Niño events in 1997/1998 and 2015/2016 and two La Niña events in 1998/1999 and 2010/2011 to examine the response of Chl-a to ENSO events in this region. Results showed that El Niño and La Niña could enhance and inhibit the growth of phytoplankton in the Sulu Ridge in winter, respectively. For other seasons, the influence of ENSO on the Chl-a was inconsistent. Specifically, during El Niño events, the largest Chl-a increases occurred in winter, and the low sea surface temperature (SST) center appeared northwest of Sulu Ridge. The significant decrease of SST (~1.5 °C) during El Niño events in winter in the northeastern Sulu Ridge was mainly caused by the increase in Ekman transport (ET) and Ekman pumping velocity (EPV), which brought nutrient-rich subsurface water to the surface layer through the thin barrier layer and enhanced Chl-a. During La Niña events, the SST was higher (~0.8 °C) than the average and the high SST center generally appeared in the middle of the Sulu Ridge with the east-west direction in winter, which was resulted from the intensification of barrier layer thickness (BLT) and the decrease of ET, thus reducing the Chl-a. The different responses to El Niño and La Niña events indicate the high sensitivity of Chl-a in this region to the ENSO.

Ecological anomalies in the East China Sea: impacts of the Three Gorges Dam?

In this study, we examined possible impacts of the Yangtze River Three Gorges Dam (TGD), the world largest hydroelectric construction, on the adjacent marine ecosystem of the East China Sea (ECS) during its initial water storage period. The TGD filled the first one-third of its storage capacity of 39 billion m3 in 10 days in June 2003, causing an abrupt reduction in the river flow into the ECS. Noticeable changes in the microbial community structure including pico-sized autotrophs, heterotrophic bacteria and microbial diversity in the estuary and the ECS were observed 2 months later. Although causes for these changes could be multiple, the sudden decrease of river runoff and an ensuing intrusion of ECS ocean currents were postulated to be among the major ones.

Coastal and inland water monitoring using a portable hyperspectral laser fluorometer.

The potential for a ship-mounted laser fluorometer to provide rapid, non-intrusively measurements in both coastal and lake conditions are investigated. The instrument consists of a high pulse repetition frequency (10-kHz) microchip laser for fluorescence excitation, a broadband hyperspectral micro spectrometer for spectral detection, and a confocal reflective fluorescent probe for signal collection; it weighs only about 1.7kg. Chlorophyll a (chl-a) and colored dissolved organic matter (CDOM) measured by the new instrument were observed to agree well with those measured by traditional time-consuming laboratory methods in Hangzhou Bay seawater and Qiandao Lake inland water. Subsequently, laser fluorescence distribution and characteristics of chl-a and CDOM in these regions were analyzed, which will improve our understanding of biogeochemical processes in these optically complex aquatic systems. The portable system is promising for water environment monitoring, especially in coastal and inland water.

Detection of water quality parameters in Hangzhou Bay using a portable laser fluorometer.

A field, light-weight laser fluorometer based on the method of laser induced fluorescence was developed for water quality monitoring. The basic instrument configuration uses a high pulse repetition frequency microchip laser, a confocal reflective fluorescent probe and a broadband hyperspectral micro spectrometer; it weights only about 1.7 kg. Simultaneous estimates of three important water quality parameters, namely, chlorophyll a (chl-a), colored dissolved organic matter (CDOM), and total suspended matter (TSM) measured by the laser fluorometer were observed to agree well with those measured by traditional methods (0.27-0.84 µg L(-3) chl-a, R(2)=0.88; 0.104-0.295 m(-)(1) CDOM absorption, R(2)=0.90; and 59.8-994.9 mg L(-)(3) TSM, R(2)=0.86) in Hangzhou Bay water. Subsequently, distribution and characteristics of CDOM and chl-a laser fluorescence in Hangzhou Bay were analyzed, which will enhance our understanding of biogeochemical processes in this complex estuarine system at high-resolution, high-frequency and long-term scale.

Variation of dissolved organic carbon transported by two Chinese rivers: The Changjiang River and Yellow River.

Real-time monitoring of riverine dissolved organic carbon (DOC) and the associated controlling factors is essential to coastal ocean management. This study was the first to simulate the monthly DOC concentrations at the Datong Hydrometric Station for the Changjiang River and at the Lijin Hydrometric Station for the Yellow River from 2000 to 2013 using a multilayer back-propagation neural network (MBPNN), along with basin remote-sensing products and river in situ data. The average absolute error between the modeled values and in situ values was 9.98% for the Changjiang River and 10.84% for the Yellow River. As an effect of water dilution, the variations of DOC concentrations in the two rivers were significantly negatively affected by discharge, with lower values reported during the wet season. Moreover, vegetation growth status and agricultural activities, represented by the gross primary product (GPP) and cropland area percent (CropPer) in the river basin, respectively, also significantly affected the DOC concentration in the Changjiang River, but not the Yellow River. The monthly riverine DOC flux was calculated using modeled DOC concentrations. In particular, the riverine DOC fluxes were affected by discharge, with 71.06% being reported for the Changjiang River and 90.71% for the Yellow River. Over the past decade, both DOC concentration and flux in the two rivers have not shown significant changes.

A new simple concept for ocean colour remote sensing using parallel polarisation radiance.

Ocean colour remote sensing has supported research on subjects ranging from marine ecosystems to climate change for almost 35 years. However, as the framework for ocean colour remote sensing is based on the radiation intensity at the top-of-atmosphere (TOA), the polarisation of the radiation, which contains additional information on atmospheric and water optical properties, has largely been neglected. In this study, we propose a new simple concept to ocean colour remote sensing that uses parallel polarisation radiance (PPR) instead of the traditional radiation intensity. We use vector radiative transfer simulation and polarimetric satellite sensing data to demonstrate that using PPR has two significant advantages in that it effectively diminishes the sun glint contamination and enhances the ocean colour signal at the TOA. This concept may open new doors for ocean colour remote sensing. We suggest that the next generation of ocean colour sensors should measure PPR to enhance observational capability.