Intercomparison of ocean colour band-ratio algorithms for chlorophyll concentration in the Subtropical Front east of New Zealand

This study intercompared the performance of eight band-ratio chlorophyll-a algorithms which together can be used to process measurements from the ocean colour satellite sensors CZCS, OCTS, SeaWiFS, MODIS, MERIS, and GLI. The study area included Subtropical, Subtropical Front and Subantarctic waters east of New Zealand, and Case 1 waters of the New Zealand northeast continental shelf. Over 170 co-incident measurements of spectral normalised water-leaving radiance and near-surface concentration of chlorophyll-a were made on nine research voyages between 1998 and 2000. The studentised bootstrap method was used to identify statistically significant bias in algorithm products relative to in situ measurements. The band-ratio algorithms used by CZCS, OCTS and SeaWiFS missions systematically underestimated chlorophyll-a concentration in the offshore regions by between 21% and 45%, but showed no systematic bias in the continental shelf waters. The band-ratio algorithms applicable to the MODIS and MERIS sensors had no clear bias with respect to in situ measurements in offshore waters, but had a positive bias of 20% over the continental shelf. The proposed GLI band-ratio algorithm led to estimates that were negatively biased with respect to in situ measurement offshore (− 30%), and positively biased over the continental shelf (20%). The results were consistent with unusually high values of absorption in the blue part of the spectrum (443-490 nm) compared to the green part (∼ 550 nm) by phytoplankton pigments in the offshore waters, and high chlorophyll-specific absorption over the continental shelf.     

Remote sensing of phytoplankton pigments: A comparison of empirical and theoretical approaches

Algorithms that have been used on a routine basis for remote sensing of the phytoplankton pigment, chlorophyll- a, from ocean colour data from satellite sensors such as the CZCS (Coastal Zone Color Scanner), SeaWiFS (Sea Viewing Wide Field-of-View Sensor) and OCTS (Ocean Colour and Temperature Scanner) are all of an empirical nature. However, there exist theoretical models that allow ocean colour to be expressed as a function of the inherent optical properties of seawater, such as the absorption coefficient and the backscattering coefficient. These properties can in turn be expressed as functions of chlorophyll- a, at least for the so-called Case 1 waters in which phytoplankton may be considered to be the single, independent variable responsible for most of the variations in the marine optical properties. Here, we use such a theoretical approach to model variations in ocean colour as a function of chlorophyll- a concentration, and compare the results with some empirical models in routine use. The parameters of phytoplankton absorption necessary for the implementation of the ocean colour model are derived from our database of over 700 observations of phytoplankton absorption spectra and concurrent measurements of phytoplankton pigments by HPLC (High Performance Liquid Chromatography) techniques. Since there are reports in the literature that significant differences exist in the performance of the algorithms in polar regions compared with lower latitudes, the model is first implemented using observations made at latitudes less than 50. It is then applied to the Labrador Sea, a high-latitude environment. Our results show that there are indeed differences in the performance of the algorithm at high latitudes, and that these differences may be attributed to changes in the optical characteristics of phytoplankton that accompany changes in the taxonomic composition of their assemblages. The sensitivities of the model to assumptions made regarding absorption by coloured dissolved organic matter (or yellow substances) and backscattering by particles are examined. The importance of Raman scattering on ocean colour and its influence on the algorithms are also investigated.     

The ESA Medium Resolution Imaging Spectrometer MERIS a review of the instrument and its mission

Following the successful operations of the ERS-1 and 2 satellites which are mainly dedicated to physical oceanography and ice observations from space, the European Space Agency (ESA) developed a multidisciplinary Earth observation instrument within its polar Earth Observation Programme with a focus on biological ocean observations. The Medium Resolution Imaging Spectrometer (MERIS) will be launched onboard Envisat-1 in the 1999-2000 time frame, providing a European remote sensing capability for observing for example oceanic biology and marine water quality through observations of water colour. MERIS will have a medium spectral and high radiometric resolution and a dual spatial resolution, within a global mission, covering open ocean and coastal zone waters, important aspects of the atmosphere, and large ecosystems over land. The global mission of MERIS will have a major contribution to scientific projects aimed at greater understanding of the role of oceans and ocean productivity in the climate system and our ability to forecast change through models. Secondary objectives of the MERIS mission will be directed to the measurement of atmospheric parameters associated with clouds, water vapour and aerosols in addition to land surface parameters, important in particular for the understanding of vegetation processes. In advance of the launch of MERIS, algorithms are being developed for the interpretation of MERIS observations and dedicated studies are ongoing to establish the means of validating the data products. The aim of this paper is to provide a comprehensive overview of the MERIS concept, its mission and data products in context of the driving scientific requirements.     

Remote monitoring of aerosols with ocean colour sensors: then and now

Synoptic coverage of the temporal and spatial variability of aerosol distribution patterns can only be achieved with satellites. Results from the first ocean colour sensor, the Coastal Zone Color Scanner (CZCS), indicate an annual cycle of the major mineral aerosol plumes that is consistent with the published literature. Seasonality and interannual aerosol variability observed with the CZCS agrees well with that found by ground data measurements and other satellite platforms used to monitor aerosols. The successor to the CZCS—the Sea viewing Wide Field of view Sensor (SeaWiFS)—provides estimates of aerosol load and particle size, both on a global scale. Seasonal maps of both of these aerosol optical properties are in accord with well-known distribution patterns and also with independent satellite estimates. These results indicate that ocean colour sensors are capable of monitoring the variability of global aerosol loads and, more recently, with the retrieval of aerosol particle size, they can be used to characterize different aerosol events.     

MERIS potential for coastal zone applications

The Medium Resolution Imaging Spectrometer (MERIS) will be flown on the Envisat mission in 1999 and will provide the user community with a unique instrument for monitoring important water quality parameters in coastal waters. The instrument will be of special interest for coastal zone research projects such as the International Geosphere Biosphere Program (IGBP), Land Ocean Interactions in the Coastal Zone (LOICZ) and for environmental impact monitoring, assessment and management programmes. MERIS characteristics include nine spectral channels (out of 15) covering the visible spectral range (410-705nm) which are optimized to the radiance level of water surfaces. Within this range there are bands dedicated to mapping concentrations of suspended particulate matter, phytoplankton, gelbstoff (or coloured dissolved organic matter) and bands for determining sunlight-stimulated fluorescence of phytoplankton chlorophyll. Its spatial resolution of 300m and revisit period of 3 days are well suited to the observation of most of the phenomena which are of interest for coastal water quality research and management. New algorithms will have to be developed for computing the different water constituents from the observations and for atmospheric correction of turbid waters. Examples of applications, for which the design of MERIS is optimized, are presented.     

Sea surface colour in the field of biological oceanography

Abstract

Variations of marine surface optical properties (generally grouped under the term ‘sea surface colour’) are due to dissolved and suspended materials, with different absorption and scattering characteristics, present in sea water. Remote assessments of sea surface colour, therefore, can be used to determine the presence and abundance of water constituents such as biological pigments, suspended sediments or other products of organic matter degradation (the so-called yellow substance). In open sea waters, the pigments due to biological activities, and particularly phytoplankton chlorophyll-like pigments, are the main contributors to surface colour. Hence, observations in the visible spectrum can provide synoptic and repetitive information on parameters linked to biological production and patchiness, or bio-geo-chemical cycles in general. Since water constituents act as tracers of various marine processes, bio-optical patterns on the sea surface can also provide indications about the relationships existing between forcing mechanisms and biological response in the marine environment. These capabilities render optical remote sensing an invaluable tool in the field of biological oceanography, although atmospheric processes and signal ambiguities in the water column may pose severe limitations on this technique. The feasibility and potential of passive remote sensing in the visible spectrum have been demonstrated primarily by the Coastal Zone Color Scanner (CZCS) experiment. Important results of this experiment have been reported in the study of coastal phenomena, sediment transport, frisheries, upwelling, climatic events, and factors controlling the distribution, growth and fate of phytoplankton. On these latter topics, indications of a strong coupling between dynamical and bio-optical conditions of the marine environment are emerging from the analysis of CZCS image series, for open ocean, near-coastal and enclosed basin conditions. Examples of such studies, covering regions of both the North Atlantic and North Pacific Oceans and of the Mediterranean Sea, provide clues on the promises of large-scale sea surface colour assessments in the field of biological oceanography.     

Ocean transparency from space: Validation of algorithms estimating Secchi depth using MERIS, MODIS and SeaWiFS data

Ocean transparency, often measured using Secchi disk, is a useful index of water quality or productivity and is used in many environmental studies. The spaceborne ocean color sensors provide synoptic and regular radiometric data and can be used for applying environmental policies if the data is converted into relevant biogeochemical properties. We adapted and developed semi-analytical and empirical algorithms to estimate the Secchi depth from satellite ocean color data in both coastal and oceanic waters. The development of the algorithms is based on the use of a comprehensive in situ bio-optical dataset. The algorithms are validated using an extensive set of coincident satellite estimates and in situ measurements of the Secchi depth (so-called matchups). More than 400 matchups are compiled for the MERIS, MODIS and SeaWiFS sensors. The comparison between Secchi depth retrievals from remote sensing data and in situ measurements yields determination coefficients (R²) between 0.50 and 0.73, depending on the sensor and algorithm. The type II linear regression slopes and intercepts vary between 0.95 and 1.46, and between − 0.8 and 6.2 m, respectively. While semi-analytical algorithms provide the most promising results on in situ data, the empirical one proves to be more robust on remote sensing data because it is less sensitive to error due to erroneous atmospheric corrections. Using ocean color archives, one can derive maps of ocean transparency for different areas. Our climatology of the Secchi depth based on ocean color for the transition zone between the North Sea and Baltic Sea is compared to an historical dataset.     

Assessment of SeaWiFS,MODIS, and MERIS ocean colour products in the South China Sea

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Medium Resolution Imaging Spectrometer (MERIS) remote-sensing radiometric and chlorophyll-a (chl-a) concentration products for the South China Sea (SCS) from October 2003 to May 2010 were assessed using in situ data. A strict spatiotemporal match-up method was used to minimize the temporal variability effects of atmosphere and seawater around the measurement site. A comparison of the remote-sensing reflectance (R_rs(λ)) of the three sensors with in situ values from the open waters of the SCS showed that the mean absolute percentage difference varied from 13% to 55% in the 412–560 nm spectral range. Generally, the MERIS radiometric products exhibited higher typical uncertainties and bias than the SeaWiFS and MODIS products. The R_rs(443) to R_rs(555/551/560) band ratios of the satellite data were in good agreement with in situ observations for these sensors. The SeaWiFS, MODIS, and MERIS chl-a products overestimated in situ values by 74%, 42%, and 120%, respectively. MODIS retrieval accuracy was better than those of the other sensors, with MERIS performing the worst. When the match-up criteria were relaxed, the assessment results degraded systematically. Therefore, strict spatiotemporal match-up is recommended to minimize the possible influences of small-scale variation in geophysical properties around the measurement site. Coastal and open-sea areas in the SCS should be assessed separately because their biooptical properties are different and the results suggest different atmospheric correction problems.     

Four years of ocean colour remote sensing with MOS-IRS

The imaging spectrometer MOS on IRS-P3 was launched in March 1996 as the first example of a new generation of ocean colour sensors. It consists of three different spectrometers in the visible/near-infrared spectral region with 18 channels. The IRS-P3 mission is focused on the remote sensing of case 2 water, particularly the derivation of different water constituents in coastal waters. Due to the more complex spectral behaviour of case 2 water, a new methodological approach was developed which works directly with satellite measured top-of-atmosphere radiance and accounts for the correlation of the different water constituents as well as for the spectral shape.

This paper gives an overview of the mission, the scientific goals and the development and improvement of the retrieval algorithms. The potential of the algorithm is demonstrated and examples of selected European coasts are shown. Derived maps of water constituents are presented.     

Estimation of optical properties of nearshore water

Most of the existing satellite sensors lack the spectral capabilities to discriminate phytoplankton pigments in water bodies. New satellite sensors (i.e. SeaWIFS) and future sensors on board EOS withnarrow bandwidths will provide fine spectral resolution necessary to distinguish optical properties of nearshore waters provided sea data are available. This will enable spaceborne water color sensors to discriminate bloom forming phytoplankton species. The objective was to develop a library of absorption spectra for the most common phytoplankton species found within the Hudson/Raritan Estuary and coastal waters of New Jersey. Both culture-grown and field samples of phytoplankton were concentrated and analyzedusing chemical and spectrometric techniques. Using spectral derivative and polynomial regression analysis, it was possible to identify wavelengths that could be used to characterize the pigment compositions of phytoplankton species in the estuary.     

Solving the ocean color problem using a genetic programming approach

The ocean color problem consists in evaluating ocean components concentrations (phytoplankton, sediment and yellow substance) from sunlight reflectance or luminance values at selected wavelengths in the visible band. The interest of this application increases with the availability of new satellite sensors. Moreover, monitoring phytoplankton concentrations is a key point for a wide set of problems ranging from greenhouse effect to industrial fishing and signaling toxic algae blooms. To our knowledge, it is the first attempt at this regression problem with genetic programming (GP). We show that GP outperforms traditional polynomial fits and rivals artificial neural nets in the case of open ocean waters. We improve previous works by also solving a range of coastal waters types, providing detailed results on estimation errors. To our knowledge, we are the firsts to publish numerical results regarding coastal waters. Experiments were conducted with a dynamic fitness GP algorithm in order to speed up computing time through a process of progressive learning.     

Examining the consistency of products derived from various ocean color sensors in open ocean (Case 1) waters in the perspective of a multi-sensor approach

During its lifetime, a space-borne ocean color sensor provides world-wide information about important biogeochemical properties of the upper ocean every 2 to 4 days in cloudless regions. Merging simultaneous or complementary data from such sensors to obtain better spatial and temporal coverage is a recurring objective, but it can only be reached if the consistency of the sensor-specific products, as delivered by the various Space Agencies, has first been carefully examined. The goal of the present study is to provide a procedure for establishing a coherency of open ocean (Case-1 waters) data products, for which the various data processing methods are sufficiently similar. The development of the procedure includes a detailed comparison of the marine algorithms used (after atmospheric corrections) by space agencies for the production of standard products, such as the chlorophyll concentration, [Chl], and the diffuse attenuation coefficient, K_d. The MODIS-Aqua, SeaWiFS and MERIS [Chl] products agree over a wide range, between ∼ 0.1 and 3 mg m^− 3, whereas increasing divergences occur for oligotrophic waters ([Chl] (from 0.02 to 0.09 mg m^− 3). For the K_d(490) coefficient, different algorithms are in use, with differing results. Based on a semi-analytical reflectance model and hyperspectral approach, the present work proposes a harmonization of the algorithms allowing the products of the various sensors to be comparable, and ultimately, meaningfully merged (the merging procedures themselves are not examined). Additional potential products, obtained by using [Chl] as an intermediate tool, are also examined and proposed. These products include the thickness of the layer heated by the sun, the depth of the euphotic zone, and the Secchi disk depth. The physical limitations in the predictive skill of such downward extrapolations, made from information concerning only the upper layer, are stressed.     

Bathymetric and bottom effects on CZCS chlorophyll-like pigment estimation: Data from the Kerkennah Shelf (Tunisia)

The Coastal Zone Color Scanner (CZCS)-retrieved chlorophyll-like pigments for the Mediterranean Sea show zones of high concentrations (10mgm-3) such as the shallow Kerkennah Shelf, off the southern Tunisian coast. This occurrence pointing to probable erroneous estimates, exaggerated by the effect of the bottom signal is discussed in the general framework of the applicability of water colour techniques to coastal areas, as a source of environmental data suitable for inclusion in a multi-purpose Geographic Information System (GIS). The state of knowledge on the Kerkennah Shelf test site, organized into a regional geo-referenced data base (including CZCS and TM imagery), is presented. A two-flow model has been applied to in situ reflectance measurements, to derive some information on the interplay between water colour and bottom typology. The results have been used to evaluate nature, intensity and extent of the sedimentary and vegetated sea bottom effect on the chlorophyll-like pigment concentrations derived from CZCS in the Kerkennah area. Finally, the applicability of satellite-derived ocean colour data to coastal zone mapping is discussed in some detail.     

The atmospheric correction of water colour and the quantitative retrieval of suspended particulate matter in Case II waters: Application to MERIS

The remote sensing of turbid waters (Case II) using the Medium Resolution Imaging Spectrometer (MERIS) requires new approaches for atmospheric correction of the data. Unlike the open ocean (Case I waters) there are no wavelengths where the water-leaving radiance is zero. A coupled hydrological atmospheric model is described here. The model solves the water-leaving radiance and atmospheric path radiance in the near-infrared (NIR) over Case II turbid waters. The theoretical basis of this model is described, together with its place in the proposed MERIS processing architecture. Flagging procedures are presented that allow seamless correction of both Case I waters, using conventional models, and Case II waters using the proposed model. Preliminary validation of the model over turbid waters in the Humber estuary, UK is presented using Compact Airborne Spectrographic Imager (CASI) imagery to simulate the MERIS satellite sensor. The results presented show that the atmospheric correction scheme has superior performance over the standard single scattering approach, which assumes that water-leaving radiance in the NIR is zero. Despite problems of validating data in such highly dynamic tidal waters, the results show that retrievals of sediments within 50% are possible from algorithms derived from the theoretical models.     

Non-isotropy of the upward radiance field in typical coastal (Case 2) waters

The in-water radiance field has been computed in typical Case 2 waters by using radiative transfer models and appropriate inherent optical properties (IOPs) combined with realistic boundary conditions. In particular, the bi-directional structure of the subsurface upward flux has been investigated in view of remote sensing applications related to ocean colour. In Case 2 waters, the IOPs are not controlled by the phytoplankton (or chlorophyll) concentration; rather they are essentially determined by the abundance of terrigenous optically active materials, either particulate or dissolved. Based on field data and related IOPs, two extreme situations were selected as representative instances of sedimentdominated and yellow-substance-dominated Case 2 waters. This study shows that even in very turbid natural waters, the upward radiance field is not isotropic and remains Sun-angle dependent. More than 100 successive events are needed to reach a quasi-isotropic, illumination independent, upward radiance field. In contrast, with a high yellow substance content resulting in high absorption (compared to scattering), single scattering prevails in such waters and this leads to strongly featured radiance fields that are heavily dependent on the Sun's position. It is necessary to account for these effects when interpreting waterleaving radiances as detected from space, and, perhaps more importantly, when carrying out at-sea radiometric measurements in support of calibration of remote ocean colour sensors. For this purpose, a practical approach and mean values of relevant coefficients are proposed to describe the bi-directional structure of the upward radiance field in the two extreme situations of strongly scattering or strongly absorbing waters.     

Atmospheric correction for inland waters—application to SeaWiFS

Inland waters are an increasingly valuable natural resource that has major impact and benefits for population and environment. The new generation of ocean colour sensors has better spatial resolution, and hence are suitable for monitoring water quality of lakes. As an alternative to standard algorithms developed for oceans, which often fail over inland waters, we propose here a scheme based on aerosol remote sensing over land. The ocean colour sensors have spectral bands that allow characterization of aerosols over dark land pixels (vegetation in the blue and in the red spectral bands). It is then possible to use a representative aerosol model (aerosol optical thickness and aerosol type) for atmospheric correction over inland waters after validating the spatial homogeneity of the aerosol model in the lake vicinity. The performance of this new algorithm is shown in Sea‐viewing Wide Field‐of‐view Sensor (SeaWiFS) scenes of Lakes Balaton (Hungary) and Constance (Germany). We demonstrate the good spatial homogeneity of the aerosols and the meaningfulness of the water‐leaving reflectances derived over these two lakes.

We also addressed the particularity of Fresnel reflection computation. The direct to diffuse term of this Fresnel contribution is reduced because of the limited size of the lake. Based on the primary scattering approximation, we propose a simple formulation of this component. A specific Fresnel correction needs to be developed to fulfil the accuracy requirements.     

Spectral variations in the near-infrared ocean reflectance

The optical properties of natural waters beyond the visible range, in the near-infrared (NIR, 700-900 nm), have received little attention because they are often assumed to be mostly determined by the large absorption coefficient of pure water, and because of methodological difficulties. It is now growingly admitted that the NIR represents a potential optical source of unambiguous information about suspended sediments in turbid waters, thence the need for better understanding the NIR optical behaviour of such waters. It has recently been proposed (Ruddick et al., Limnology and Oceanography. 51, 1167-1179, 2006) that the variability in the shape of the surface ocean reflectance spectrum in the NIR is negligible in turbid waters. In the present study, we show, based on both in situ and remote sensing data, that the shape of the ocean reflectance spectrum in the NIR does vary in turbid to extremely turbid waters. Space-borne ocean reflectance data were collected using 3 different sensors (SeaWiFS, MODIS/Aqua and MERIS) over the Amazon, Mackenzie and Rio de la Plata turbid river plumes during extremely clear atmospheric conditions so that reliable removal of gas and aerosol effects on reflectance could be achieved. In situ NIR reflectance data were collected in different European estuaries where extremely turbid waters were found. In both data sets, a flattening of the NIR reflectance spectrum with increasing turbidity was observed. The ratio of reflectances at 765 nm and 865 nm, for instance, varied from ca. 2 down to 1 in our in situ data set, while a constant value of 1.61 had been proposed based on theory in a previous study. Radiative transfer calculations were performed using a range of realistic values for the seawater inherent optical properties, to determine the possible causes of variations in the shape of the NIR reflectance spectrum. Based on these simulations, we found that the most significant one was the gradual increase in the contribution of suspended sediments to the color of surface waters, which often leads to the flattening of the reflectance spectrum. Changes in the scattering and absorption properties of particles also contributed to variations in the shape of the NIR surface ocean reflectance spectrum. The impact of such variations on the interpretation of ocean color data is discussed.     

Remote sensing of phytoplankton pigment distribution in the United States northeast coast

Phytoplankton pigments constitute many more compounds than chlorophyll a that can be applied to study phytoplankton diversity, populations, and primary production. In this study, field measurements were applied to develop ocean color satellite algorithms of phytoplankton pigments from in-water radiometry measurements. The match-up comparisons showed that the satellite-derived pigments from our algorithms agree reasonably well (e.g. 30-55% of uncertainty for SeaWiFS and 37-50% for MODIS-Aqua) to field data, with better agreement (e.g. 30-38% of uncertainty for SeaWiFS and 39-44% for MODIS-Aqua) for pigments abundant in diatoms. The seasonal and spatial variations of satellite-derived phytoplankton biomarker pigments, such as fucoxanthin, which is abundant in diatoms, peridinin, which is found only in peridinin-containing dinoflagellates, and zeaxanthin, which is primarily from cyanobacteria in coastal waters, revealed that higher densities of diatoms are more likely to occur on the inner shelf and during winter-spring and obscure other abundant phytoplankton groups. However, relatively higher densities of other phytoplankton, such as dinoflagellates and cyanobacteria, are likely to occur on the mid- to outer-continental shelf and during summer. Seasonal variation of riverine discharge may play an important role in stimulating algal blooms, in particular diatoms, while higher abundances of cyanobacteria coincide with warmer water temperatures and lower nutrient concentrations.     

Detection of turbid waters and absorbing aerosols for the MODIS ocean color data processing

Atmospheric correction for the ocean color products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) uses two near-infrared (NIR) bands centered at 748 and 869 nm for identifying aerosol type and correcting aerosol contributions at the MODIS visible wavelengths. The ocean is usually assumed to be black for open oceans at these two NIR bands with modifications for the productive waters and aerosols are assumed to be non- or weakly absorbing. For cases with strongly absorbing aerosols and cases with the significant NIR ocean contributions, the derived ocean color products will have significant errors, e.g., the derived MODIS normalized water-leaving radiances are biased low considerably. Both cases lead to a significant drop of the sensor-measured radiance at the short visible wavelengths, and they both have similar and indistinguishable radiance characteristics at the short visible wavelengths. To properly handle such cases, the strongly absorbing aerosols and turbid waters need to be identified. Therefore, an appropriate approach (different from the standard procedure) may be carried out. In this paper, we demonstrate methods to identify the turbid waters and strongly absorbing aerosols using combinations of MODIS-measured radiances at the short visible, NIR, and short wave infrared (SWIR) bands. The algorithms are based on the fact that for the turbid waters the ocean has significantly large contributions at the NIR bands, whereas at the SWIR bands the ocean is still black due to much stronger water absorption. With detection of the turbid waters, the strongly absorbing aerosols can then be identified using the MODIS measurements at the short visible and NIR bands. We provide results and discussions for test and evaluation of the algorithm performance with various examples in the coastal regions for the turbid waters and for various absorbing aerosols (e.g., volcano ash plumes, dust, smoke). The proposed algorithms are efficient in the data processing, and can be carried out prior to the atmospheric correction procedure.     

Diurnal variability of ocean optical properties during a coastal algal bloom: implications for ocean colour remote sensing

Understanding the diurnal variability of ocean optical properties is critical for better interpretation of satellite ocean colour data and characterizing biogeochemical processes. The daytime variability of ocean optical properties throughout an algal bloom event is analysed in this article based on in situ observations from dawn to dusk at a fixed coastal site in the South China Sea. Diurnal variability during the sunlit period of the ocean optical properties is found to be significant. During the 6 hours around noon, the temporal variability (defined by the coefficient of variation) of phytoplankton absorption, coloured dissolved organic matter and non-algal particle absorption, and particle backscattering at 443 nm can reach 21% ± 15%, 12% ± 9%, and 17% ± 9%, respectively. The diurnal variability during the bloom is much more pronounced than that of the non-bloom phase. With atmospheric radiative transfer modelling, it is further demonstrated that the geostationary satellite detection of within-day optical variability in algae-dominated waters depends on the reliability of the aerosol retrieval. The implications of the diurnal bio-optical variability for the retrieval, validation, and interpretation of satellite ocean colour products are also discussed.