Detecting the red tide algal blooms from satellite ocean color observations in optically complex Northeast-Asia Coastal waters

Over the last few decades, the coastal regions throughout the world have experienced incidences of algal blooms, which are harmful or otherwise toxic because of their potential threat to humans as well as marine organisms, owing to accelerated eutrophication from human activities and certain oceanic processes. Previous studies have found that correct identification of these blooms remains a great challenge with the standard bio-optical algorithms applied to satellite ocean color data in optically complex coastal waters containing high concentrations of the interfered dissolved organic and particulate inorganic materials. Here a new method called the red tide index (RI) is presented which is capable of identifying potential areas of harmful algal blooms (HABs) from SeaWiFS ocean color measurements representing the typical Case-2 water environments off the Korean and Chinese coasts. The RI method employs the water-leaving radiances (L_w), collected from in-situ radiometric measurements of three SeaWiFS bands centered at 443 nm, 510 nm and 555 nm, to achieve derivation of indices that are then related to absorbing characteristics of harmful algae (i.e., L_w at 443 nm) from which a best fit with a cubic polynomial function with correlation coefficient of R² = 0.91 is obtained providing indices of higher ranges for HABs and lower and slightly reduced ranges for turbid and non-bloom waters. Similar indices derived from the use of remote sensing reflectance (R_rs), normalized water-leaving radiance (nL_w) and combination of both are found rather inadequate to characterize the variability of the encountered bloom. In order to quantify the HABs in terms of chlorophyll (Chl), an empirical relationship is established between the RI and in-situ Chl in surface waters from about 0.4-71 mg m^− 3, which yields a Red tide index Chlorophyll Algorithm (RCA) based on an exponential function with correlation coefficient R² = 0.92. The established methods were extensively tested and compared with the performances of standard Ocean Chlorophyll 4 (OC4) algorithm and Local Chlorophyll Algorithm (LCA) using SeaWiFS images collected from typical red tide waters of Korean South Sea (KSS), East China Sea (ECS), Yellow Sea (YS) and Bohai Sea (BS) during 1999-2002. The standard spectral ratio algorithms, the OC4 and LCA, yielded large errors in Chl retrievals for coastal areas, besides providing false information about the encountered HABs in KSS, ECS, YS and BS waters. On the contrary, the RI coupled with the standard spectral ratios yielded comprehensive information about various ranges of algal blooms, while RCA Chl showing a good agreement with in-situ data led to enhanced understanding of the spatial and temporal variability of the recent HAB occurrences in high scattering and absorbing waters off the Korean and Chinese coasts.     

An assessment of the black ocean pixel assumption for MODIS SWIR bands

Recent studies show that an atmospheric correction algorithm using shortwave infrared (SWIR) bands improves satellite-derived ocean color products in turbid coastal waters. In this paper, the black pixel assumption (i.e., zero water-leaving radiance contribution) over the ocean for the Moderate Resolution Imaging Spectroradiometer (MODIS) SWIR bands at 1240, 1640, and 2130 nm is assessed for various coastal ocean regions. The black pixel assumption is found to be generally valid with the MODIS SWIR bands at 1640 and 2130 nm even for extremely turbid waters. For the MODIS 1240 nm band, however, ocean radiance contribution is generally negligible in mildly turbid waters such as regions along the U.S. east coast, while some slight radiance contributions are observed in extremely turbid waters, e.g., some regions along the China east coast, the estuary of the La Plata River. Particularly, in the Hangzhou Bay, the ocean radiance contribution at the SWIR band 1240 nm results in an overcorrection of atmospheric and surface effects, leading to errors of MODIS-derived normalized water-leaving radiance at the blue reaching ~ 0.5 mW cm^− 2 μm^− 1 sr^− 1. In addition, we found that, for non-extremely turbid waters, i.e., the ocean contribution at the near-infrared (NIR) band < ~ 1.0 mW cm^− 2 μm^− 1 sr^− 1, there exists a good relationship in the regional normalized water-leaving radiances between the red and the NIR bands. Thus, for non-extremely turbid waters, such a red-NIR radiance relationship derived regionally can possibly be used for making corrections for the regional NIR ocean contributions without using the SWIR bands, e.g., for atmospheric correction of ocean color products derived from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS).     

A simple band ratio technique to quantify the colored dissolved and detrital organic material from ocean color remotely sensed data

Spectral reflectances of the ocean, R, as derived from ocean color remote sensing data at four wavelengths (412, 443, 490, and 555 nm), can be used to form two ratios of spectral reflectance, namely R(412)/R(443), and R(490)/R(555), thereafter denoted R₄₄₃⁴¹² and R₅₅₅⁴⁹⁰. The former is mainly sensitive to the colored dissolved organic material (CDOM), albeit influenced by the algal content as depicted by the chlorophyll concentration, ([Chl]); in contrast, the latter is essentially depending on [Chl], although it is also influenced by CDOM. Therefore the signatures of CDOM and [Chl] which are not truly separable, can nevertheless be identified by considering simultaneously the two ratios. The concomitant variations in these ratios can be established via a bio-optical model developed for Case 1 waters. This model implicitly includes a “mean” relationship between CDOM and [Chl], and thus produces a unique curve relating R₄₄₃⁴¹² to R₅₅₅⁴⁹⁰. Deviations with respect to this mean relationship can be introduced through a factor Φ, with Φ > 1 (excess) or < 1 (deficit), applied to the CDOM-[Chl] ratio. A family of R₄₄₃⁴¹²-R₅₅₅⁴⁹⁰ curves is thus generated, in correspondence with the discrete values given to Φ; this “grid” (or numerically, a 2-D lookup table) allows the Φ-[Chl] couple to be unambiguously derived for any R₄₄₃⁴¹²-R₅₅₅⁴⁹⁰ couple. By applying this straightforward algorithm to actual reflectance ratios derived from ocean color imagery, the relative anomalies in CDOM with respect to its standard (Chl-related) values can be efficiently assessed. Within the global ocean (discarding the coastal zones), the Φ factor is widely varying, between at least ? and 3, and is roughly log-normally distributed around ~ 1 (no anomaly). The spatial distributions of the Φ factor in the whole ocean are strongly featured according to latitude, season, and hydrographic regimes, and these features are regularly reproducible, from year to year (2002-2007). This simple method is also validated against available in situ data, and its results compare favorably, for instance, to those of the GSM (Garver-Siegel-Maritorena) inversion method, in terms of retrieved CDOM concentrations and distribution patterns.     

Ocean sand ridge signatures in the Bohai Sea observed by satellite ocean color and synthetic aperture radar measurements

Satellite measurements from Synthetic Aperture Radar (SAR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua platform are used to study the ocean sand ridges in the eastern Bohai Sea in China. Even though the imaging mechanisms for SAR and MODIS-Aqua remote sensing are different, the sand ridges are shown to have exactly the same patterns in images from both sensors. Therefore, the location, extension and coverage of the ocean sand ridges can be detected and cross-examined by both SAR and MODIS-Aqua observations. Satellite images show quite different sand ridge distribution pattern from the published bathymetry map (based on in situ data) that shows six sand ridges in the area. 10 finger-shaped sand ridges are identified from satellite observations. The tidal-current/sand-ridge interaction driven physical and optical changes are assessed and evaluated. The existence of sand ridges causes enhanced water diffuse attenuation coefficient K_d(490) and elevated normalized water-leaving radiance at the red and near-infrared (NIR) wavelengths. The sea surface over the sand ridges experiences significant seasonal variability of water turbidity and shows remarkable differences from nearby ocean regions. During winter, K_d(490) values are about 2-3 m^− 1 over the ridges, while the maximum K_d(490) in the neighboring oceans is approximately 1.5 m^− 1. In summer, the enhancement of the sea surface turbidity is less significant than that which occurs in winter.     

An assessment of chlorophyll-a algorithms available for SeaWiFS in coastal and open areas of the Bay of Bengal and Arabian Sea

Three ocean colour algorithms, OC4v6, Carder and OC5 were tested for retrieving Chlorophyll-a (Chla) in coastal areas of the Bay of Bengal and open ocean areas of the Arabian Sea. Firstly, the algorithms were run using ~ 80 in situ Remote Sensing Reflectance, (R_rs(λ)) data collected from coastal areas during eight cruises from January 2000 to March 2002 and the output was compared to in situ Chla. Secondly, the algorithms were run with ~ 20 SeaWiFS R_rs(λ) and the results were compared with coincident in situ Chla. In both cases, OC5 exhibited the lowest log₁₀-RMS, bias, had a slope close to 1 and this algorithm appears to be the most accurate for both coastal and open ocean areas. Thirdly the error in the algorithms was regressed against Total Suspended Material (TSM) and Coloured Dissolved Organic Material (CDOM) data to assess the co-variance with these parameters. The OC5 error did not co-vary with TSM and CDOM. OC4v6 tended to over-estimate Chla > 2 mg m⁻³ and the error in OC4v6 co-varied with TSM. OC4v6 was more accurate than the Carder algorithm, which over-estimated Chla at concentrations > 1 mg m⁻³ and under-estimated Chla at values < 0.5 mg m⁻³. The error in Carder Chla also co-varied with TSM. The algorithms were inter-compared using > 5500 SeaWiFS R_rs(λ) data from coastal to offshore transects in the Northern Bay of Bengal. There was good agreement between OC4v6 and OC5 in open ocean waters and in coastal areas up to 2 mg m⁻³. There was a strong divergence between Carder and OC5 in open ocean and coastal waters. OC4v6 and Carder tended to over-estimate Chla in coastal areas by a factor of 2 to 3 when TSM > 25 g m⁻³. We strongly recommend the use of OC5 for coastal and open ocean waters of the Bay of Bengal and Arabian Sea. A Chla time series was generated using OC5 from 2000 to 2003, which showed that concentrations at the mouths of the Ganges reach a maxima (~ 5 mg m⁻³) in October and November and were 0.08 mg m⁻³ further offshore increasing to 0.2 mg m⁻³ during December. Similarly in early spring from February to March, Chla was 0.08 to 0.2 mg m⁻³ on the east coast of the Bay.     

Combining the triangle method with thermal inertia to estimate regional evapotranspiration — Applied to MSG-SEVIRI data in the Senegal River basin

Spatially distributed estimates of evaporative fraction and actual evapotranspiration are pursued using a simple remote sensing technique based on a remotely sensed vegetation index (NDVI) and diurnal changes in land surface temperature. The technique, known as the triangle method, is improved by utilizing the high temporal resolution of the geostationary MSG-SEVIRI sensor. With 15 min acquisition intervals, the MSG-SEVIRI data allow for a precise estimation of the morning rise in land surface temperature which is a strong proxy for total daytime sensible heat fluxes. Combining the diurnal change in surface temperature, dT_s with an interpretation of the triangular shaped dT_s − NDVI space allows for a direct estimation of evaporative fraction. The mean daytime energy available for evapotranspiration (R_n − G) is estimated using several remote sensors and limited ancillary data. Finally regional estimates of actual evapotranspiration are made by combining evaporative fraction and available energy estimates. The estimated evaporative fraction (EF) and actual evapotranspiration (ET) for the Senegal River basin have been validated against field observations for the rainy season 2005. The validation results showed low biases and RMSE and R² of 0.13 [−] and 0.63 for EF and RMSE of 41.45 W m^− 2 and R² of 0.66 for ET.     

Impact of sea ice on the retrieval of water-leaving reflectance, chlorophyll a concentration and inherent optical properties from satellite ocean color data

Two physical phenomena by which satellite remotely sensed ocean color data are contaminated by sea ice at high latitudes are described through simulations and observations: (1) the adjacency effect that occurs along sea ice margins and (2) the sub-pixel contamination by a small amount of sea ice within an ocean pixel. The signal at the top of the atmosphere (TOA) was simulated using the 6S radiative transfer code that allows modeling of the adjacency effect for various types of sea ice surrounding an open water area. In situ sea ice reflectance spectra used in the simulations were measured prior to and during the melt period as part of the 2004 Canadian Arctic Shelf Exchange Study (CASES). For sub-pixel contamination, the TOA signal was simulated for various surface reflectances obtained by linear mixture of both sea ice and water-leaving reflectances (ρ_w). The standard atmospheric correction algorithm was then applied to the simulated TOA spectra to retrieve ρ_w spectra from which chlorophyll a concentrations (CHL) and inherent optical properties (IOPs) were derived. The adjacency effect was associated with large errors (> 0.002) in the retrieval of ρ_w as far as 24 km from an ice edge in the blue part of the spectrum (443 nm). Therefore, for moderate to high CHL (> 0.5 mg m^− 3), any pixel located within a distance of ∼ 10-20 km from the ice edge were unreliable. It was also found necessary to consider the adjacency effect when the total absorption coefficient (a_t) was to be retrieved using a semi-analytical algorithm. a_t(443) was underestimated by more than 35% at a distance of 20 km from an ice edge for CHL > 0.5 mg m^− 3. The effect on the retrieval of the particle backscattering coefficient (b_bp) was important only for clear waters (CHL ∼ 0.05 mg m^− 3). In contrast, sub-pixel contamination by a small amount of sea ice produced systematic underestimation of ρ_w in the blue because of incorrect interpretation of enhanced reflectance in the near infrared that is attributed to higher concentrations of atmospheric aerosols. In general, sub-pixel contamination was found to result in overestimations of CHL and a_t, and underestimations of b_bp. A simple method was proposed to flag pixels contaminated by adjacency effect.     

New models for retrieving and partitioning the colored dissolved organic matter in the global ocean: Implications for remote sensing

Despite the importance of CDOM to upper ocean biogeochemical processes and optics, our current understanding of its spatial and temporal distributions and the factors controlling these distributions is very limited. This eventually prevents an understanding of its relationship to the pool of dissolved organic carbon in coastal and open oceans. This work aims to present a new approach for accurate modeling of absorption spectra of CDOM (a_cdom) and deriving information on its composition in global ocean waters. The modeling approach uses measurements (in situ) of the remote sensing reflectances at two wavelengths (denoted ₄₄₃⁵⁵⁵R_rs) to estimate a_cdom(350) and a_cdom(412), applies them to determine two spectral slopes of an exponential curve fit (S) and a hyperbolic curve fit (γ), derives an appropriate parameter (γ^o) for grading the CDOM compositional changes from a_cdom (350) and γ, and finally employs a_cdom(350), S, and γ^o in a modified exponential model to describe a_cdom(λ) as a function of wavelength. The robustness of this model was rigorously tested on three independent datasets, such as NOMAD in situ data, NOMAD SeaWiFS match-ups data and IOCCG simulated data (all of them contain a_cdom(λ) and R_rs(λ)), which represent a variety of waters within coastal and offshore regions around the world. Accuracy of the retrievals found with the new models was generally excellent, with MRE (mean relative error) and RMSE (root mean square error) of − 5.64-3.55% and 0.203-0.318 for the NOMAD in situ datasets, and − 5.63 to −0.98% and 0.136-0.241 for the NOMAD satellite datasets respectively (for λ₄₁₂ to λ₆₇₀). When used with SeaWiFS images collected over the regional and global waters, the new model showed the highest surface abundances of CDOM within the subpolar gyres and continental shelves dominated by terrestrial inputs (and perhaps local production) of colored dissolved materials, and the lowest surface abundances of CDOM in the central subtropical gyres and the open oceans presumably regulated by photobleaching phenomenon, bacterial activity and local processes. Significant interseasonal and interannual seasonal changes in the terrestrially-derived CDOM distributions were noticed from these new products that closely corresponded with the global mean runoff/river discharge induced by climate change/warming scenarios.     

A four-band semi-analytical model for estimating chlorophyll a in highly turbid lakes: The case of Taihu Lake, China

Accurate estimation of phytoplankton chlorophyll a (Chla) concentration from remotely sensed data is particularly challenging in turbid, productive waters. The objectives of this study are to validate the applicability of a semi-analytical three-band algorithm in estimating Chla concentration in the highly turbid, widely variable waters of Taihu Lake, China, and to improve the algorithm using a proposed four-band algorithm. The improved algorithm is expressed as [Rrs(λ₁)^− 1 − Rrs(λ₂)^− 1][Rrs(λ₄)^− 1 − Rrs(λ₃)^− 1]^− 1. The two semi-analytical algorithms are calibrated and evaluated against two independent datasets collected from 2007 and 2005 in Taihu Lake. Strong linear relationships were established between measured Chla concentration and that derived from the three-band algorithm of [Rrs^− 1(660) − Rrs^− 1(692)]Rrs(740) and the four-band algorithm of [Rrs^− 1(662) − Rrs^− 1(693)][Rrs^− 1(740) − Rrs^− 1(705)]^− 1. The first algorithm accounts for 87% and 80% variation in Chla concentration in the 2007 and 2005 datasets, respectively. The second algorithm accounts for 97% of variability in Chla concentration for the 2007 dataset and 87% of variation in the 2005 dataset. The three-band algorithm has a mean relative error (MRE) of 43.9% and 34.7% for the 2007 and 2005 datasets. The corresponding figures for the four-band algorithm are 26.7% and 28.4%. This study demonstrates the potential of the four-band model in estimating Chla even in highly turbid case 2 waters.     

Sensitivity of the Indian Ocean circulation to phytoplankton forcing using an ocean model

Most ocean general circulation models (OGCMs) do not take into account the effect of space- and time-varying phytoplankton on solar radiation penetration, or do it in a simplistic way using a constant attenuation depth, even though one-dimensional experiments have shown potential significant effect of phytoplankton on mixed-layer dynamics. Since some ocean basins are biologically active, it is necessary for an OGCM to take water turbidity into account, even if it is not coupled with a biological model. Sensitivity experiments carried out with the Massachusetts Institute of Technology (MIT) OGCM with spatially and temporally-varying pigment concentration from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data during 1998-2003 reveal the effect of ocean turbidity on tropical Indian Ocean circulation. Variations of light-absorbing phytoplankton pigments change the vertical distribution of solar heating in the mixed layer, thereby affecting upper-ocean circulation. A simulation was performed from 1948 to 2003 with a constant minimum pigment concentration of 0.02 mg m^− 3 while another simulation was performed from September 1997 to December 2003 with variable pigment concentration, and the differences between these two simulations allow us to quantify the effects of phytoplankton on solar radiation penetration in the ocean model. Model results from a period of 6 years (1998-2003) show large seasonal variability in the strength of the meridional overturning circulation (MOC), meridional heat transports (MHT), and equatorial under current (EUC). The MOC mass transport changes by 2 to 5 Sv (1 Sv = 10⁶ m³ s^− 1) between boreal winter (January) and boreal summer (July), with a corresponding change in the MHT of ∼ 0.05 PW (1 PW = 10¹⁵ W) in boreal winter, which is close to the expected change associated with a significant climate change [Shell, K., Frouin, R., Nakamoto, S., & Somerville, R.C.J. (2003): Atmospheric response to solar radiation absorbed by phytoplankton. Journal of Geophysical Research, 108(D15), 4445. doi:10.1029/2003JD003440.]. In addition, changes in phytoplankton pigments concentration are associated with a reduction in the EUC by ∼ 3 cm s^− 1. We discuss the possible physical mechanisms behind this variability, and the necessity of including phytoplankton forcing in the OGCM.     

Spatial coherence between remotely sensed ocean color data and vertical distribution of lidar backscattering in coastal stratified waters

Detection of sub-surface optical layers in marine waters has important applications in fisheries management, climate modeling, and decision-based systems related to military operations. Concurrent changes in the magnitude and spatial variability of remote sensing reflectance (R_rs) ratios and submerged scattering layers were investigated in coastal waters of the northern Gulf of Alaska during summer of 2002 based on high resolution and simultaneous passive (MicroSAS) and active (Fish Lidar Oceanic Experimental, FLOE) optical measurements. Principal Component Analysis revealed that the spatial variability of total lidar backscattering signal (S) between 2.1 and 20 m depth was weakly associated with changes in the inherent optical properties (IOPs) of surface waters. Also based on a 250-m footprint, the vertical attenuation of S was inversely related to the IOPs (Spearman Rank Correlation up to −0.43). Low (arithmetic average and standard deviation) and high (skewness and kurtosis) moments of R_rs(443)/R_rs(490) and R_rs(508)/R_rs(555) ratios were correlated with vertical changes in total lidar backscattering signal (S) at different locations. This suggests the use of sub-pixel ocean color statistics to infer the spatial distribution of sub-surface scattering layers in coastal waters characterized by stratified conditions, well defined S layers (i.e., magnitude of S maximum comparable to near surface values), and relatively high vertically integrated phytoplankton pigments in the euphotic zone (chlorophyll a concentration > 150 mg m^− 2).     

Assessing the potential of SeaWiFS and MODIS for estimating chlorophyll concentration in turbid productive waters using red and near-infrared bands

Bio-optical algorithms for remote estimation of chlorophyll-a concentration (Chl) in case-1 waters exploit the upwelling radiation in the blue and green spectral regions. In turbid productive waters other constituents, that vary independently of Chl, absorb and scatter light in these spectral regions. As a consequence, the accurate estimation of Chl in turbid productive waters has so far not been feasible from satellite sensors. The main purpose of this study was to evaluate the extent to which near-infrared (NIR) to red reflectance ratios could be applied to the Sea Wide Field-of-View Sensor (SeaWiFS) and the Moderate Imaging Spectrometer (MODIS) to estimate Chl in productive turbid waters. To achieve this objective, remote-sensing reflectance spectra and relevant water constituents were collected in 251 stations over lakes and reservoirs with a wide variability in optical parameters (i.e. 4 ≤ Chl ≤ 240 mg m^− 3; 18 ≤ Secchi disk depth ≤ 308 cm). SeaWiFS and MODIS NIR and red reflectances were simulated by using the in-situ hyperspectral data. The proposed algorithms predicted Chl with a relative random uncertainty of approximately 28% (average bias between − 1% and − 4%). The effects of reflectance uncertainties on the predicted Chl were also analyzed. It was found that, for realistic ranges of R_rs uncertainties, Chl could be estimated with a precision better than 40% and an accuracy better than ± 35%. These findings imply that, provided that an atmospheric correction scheme specific for the red-NIR spectral region is available, the extensive database of SeaWiFS and MODIS images could be used to quantitatively monitor Chl in turbid productive waters.     

Remote sensing of water clarity in Tampa Bay

We examined the spatial and temporal variability of the Secchi Disk Depth (SDD) within Tampa Bay, Florida, using the Sea-viewing Wide Field-of-View Sensor (SeaWiFS) satellite imagery collected from September 1997 to December 2005. SDD was computed using a two-step process, first estimating the diffuse light attenuation coefficient at 490 nm, K_d(490), using a semi-analytical algorithm and then SDD using an empirical relationship with K_d(490). The empirical SDD algorithm (SDD = 1.04 × K_d(490)^− 0.82, 0.9 < SDD < 8.0 m, r² = 0.67, n = 80) is based on historical SDD observations collected by the Environmental Protection Commission of Hillsborough County (EPCHC) in Tampa Bay. SeaWiFS derived SDD showed distinctive seasonal variability, attributed primarily to chlorophyll concentrations and color in the rainy season and to turbidity in the dry season, which are in turn controlled by river runoff and winds or wind-induced sediment resuspension, respectively. The Bay also experienced strong interannual variability, mainly related to river runoff variability. As compared to in situ single measurements, the SeaWiFS data provide improved estimates of the “mean” water clarity conditions in this estuary because of the robust, frequent, and synoptic coverage. Therefore we recommend incorporation of this technique for routine monitoring of water quality in coastal and large estuarine waters like Tampa Bay.     

Red tide detection and tracing using MODIS fluorescence data: A regional example in SW Florida coastal waters

Near real-time data from the MODIS satellite sensor was used to detect and trace a harmful algal bloom (HAB), or red tide, in SW Florida coastal waters from October to December 2004. MODIS fluorescence line height (FLH in W m^− 2 μm^− 1 sr^− 1) data showed the highest correlation with near-concurrent in situ chlorophyll-a concentration (Chl in mg m^− 3). For Chl ranging between 0.4 to 4 mg m^− 3 the ratio between MODIS FLH and in situ Chl is about 0.1 W m^− 2 μm^− 1 sr^− 1 per mg m^− 3 chlorophyll (Chl = 1.255 (FLH × 10)^0.86, r = 0.92, n = 77). In contrast, the band-ratio chlorophyll product of either MODIS or SeaWiFS in this complex coastal environment provided false information. Errors in the satellite Chl data can be both negative and positive (3-15 times higher than in situ Chl) and these data are often inconsistent either spatially or temporally, due to interferences of other water constituents. The red tide that formed from November to December 2004 off SW Florida was revealed by MODIS FLH imagery, and was confirmed by field sampling to contain medium (10⁴ to 10⁵ cells L^− 1) to high (> 10⁵ cells L^− 1) concentrations of the toxic dinoflagellate Karenia brevis. The FLH imagery also showed that the bloom started in mid-October south of Charlotte Harbor, and that it developed and moved to the south and southwest in the subsequent weeks. Despite some artifacts in the data and uncertainty caused by factors such as unknown fluorescence efficiency, our results show that the MODIS FLH data provide an unprecedented tool for research and managers to study and monitor algal blooms in coastal environments.     

The origin and global distribution of second order variability in satellite ocean color and its potential applications to algorithm development

Empirical algorithms based on first order relationships between ocean color and the chlorophyll concentration ([Chl]; mg m^? 3) are widely used, but cannot explain the statistical dispersion or “anomalies” around the mean trends. We use an empirical approach that removes the first order effects of [Chl] from satellite ocean color, thus allowing us to quantify the impact on the ocean color signal of optical anomalies that vary independently of the global mean trends with remotely sensed [Chl]. We then present statistical and modeling analyses to interpret the observed anomalies in terms of their optical sources (i.e. absorption and backscattering coefficients). We identify two main sources of second order variability for a given [Chl]: 1) the amount of non-algal absorption, especially due to colored dissolved organic matter; and 2) the amplitude of the backscattering coefficient of particles. The global distribution of the anomalies displays significant regional and seasonal trends, providing important information for characterizing the marine optical environment and for inferring biogeochemical influences. We subsequently use our empirically determined anomalies to estimate the backscattering coefficient of particles and the combined absorption coefficient for colored detrital and dissolved materials. This purely empirical approach provides an independent assessment of second order optical variability for comparison with existing methods that are generally based on semi-analytical models.     

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.     

An evaluation of MODIS and SeaWiFS bio-optical algorithms in the Baltic Sea

An extensive bio-optical data set from field measurements was used to evaluate the performance of standard Moderate Resolution Imaging Spectroradiometer (MODIS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) ocean color (in-water) algorithms in the Baltic Sea, which represents an example of optically complex Case 2 waters with high concentration of colored dissolved organic matter (CDOM). The data set includes coincident measurements of radiometric quantities, chlorophyll a concentration (Chl a), and absorption coefficient of CDOM, which were taken on 25 cruises between 1993 and 2001. The data cover a wide range of variability with Chl a in surface waters from about 0.3 to 100 mg m⁻³. All the MODIS pigment algorithms examined as well as the SeaWiFS OC4v4 algorithm showed a systematic and large overestimation in chlorophyll retrievals. The mean systematic and random errors based on our entire data set exceeded 150% or even 200% in some cases, making these standard algorithms inadequate for pigment determinations in the Baltic. Although new parameterization of the standard pigment algorithms based on our field measurements in the Baltic resulted in a significant reduction of errors, the overall performance of such regionally tuned algorithms remained unsatisfactory. For example, the mean normalized bias (MNB) for the regionally tuned MODIS chlor_a_2 algorithm was reduced to 26% (from over 200% for the standard algorithm), but the root mean square (RMS) error was still large (>100%). The MODIS K_490 algorithm for estimating the diffuse attenuation coefficient of downwelling irradiance showed the best performance among all the algorithms examined. With the new coefficients based on our field data, the regional version of this algorithm showed an acceptable level of errors, MNB=4% and RMS=30%. In addition to the apparent problems of the standard in-water bio-optical algorithms, we found that the atmospheric correction currently in use for MODIS and SeaWiFS imagery usually fails to retrieve upwelling radiances emerging from the Baltic Sea. The match-up comparisons of the coincident in situ and satellite determinations of normalized water-leaving radiances showed generally poor agreement, especially in the blue spectral region. It appears that new approaches for ocean color algorithms are required in the Baltic Sea.     

Characterization of MODIS-derived euphotic zone depth: Results for the China Sea

Euphotic zone depth (Z_eu) products from ocean color measurements are now produced from MODIS ocean color measurements, one of which is based on inherent optical properties (IOP-approach) and the other is based on chlorophyll-a concentration (Chl-approach). For the first time, the quality of these satellite Z_eu products is assessed with extensive field-measured Z_eu (in the China Sea), where 78% of the measurements were made on the continental shelf (≤ 200 m). For the data with matching location and time window, we have found that the overall average difference (ε) between satellite and in situ Z_eu is 21.8% (n = 218, Z_eu ranges from 4 to 93 m) with a root mean square error in log scale (RMSE) of 0.118 by the IOP-approach, while it is 49.9% (RMSE = 0.205) by the Chl-approach. These results suggest that 1) MODIS Z_eu products for waters in the China Sea are robust, even in shelf waters; and 2) Z_eu produced with IOPs are more reliable than those produced with empirically derived Chl. Spatial and seasonal variations of Z_eu in the China Sea are briefly described with Z_eu products generated by the IOP-approach. These results will facilitate further research on carbon cycling and environmental changes on both local and global scales.     

Bio-optical properties in waters influenced by the Mississippi River during low flow conditions

Spatial and temporal patterns of bio-optical properties were studied in the Northern Gulf of Mexico during cruises in April and October of 2000, a year during which the discharge volume from the Mississippi River was unusually low. Highly variable surface Chl a concentrations (0.1 to 17 mg m⁻³) and colored dissolved organic matter (CDOM) absorption (0.07 to 1.1 m⁻¹ at 412 nm) were observed in the study region that generally decreased with increasing salinity waters, being highest nearshore and decreasing at offshore stations. The optical properties of absorption, scattering, and diffuse attenuation coefficients reflected these distributions with phytoplankton particles and CDOM contributing to most of the spatial, vertical, and seasonal variability. The diffuse attenuation coefficient K_d(λ) and spectral remote sensing reflectance R_rs(λ) were linear functions of absorption and backscattering coefficients a(λ) and b_b(λ) through the downward average cosine μ_d and the ratio of variables f/Q at the SeaWiFS wavebands for waters with widely varying bio-optical conditions. Although various R_rs(λ) ratio combinations showed high correlation with surface Chl a concentrations and CDOM absorption at 412 nm, power law equations derived using the R_rs(490)/R_rs(555) and R_rs(510)/R_rs(555) ratios provided the best retrievals of Chl a concentrations and CDOM absorption from SeaWiFS reflectance data.