Satellite Ocean Color Data Research Articles

Submesoscale and Mesoscale Eddies in the Florida Straits: Observations from Satellite Ocean Color Measurements

AbstractDespite their well‐recognized importance in driving ocean physics and biology, submesoscale (diameter < Rossby radius of deformation) eddies have been extremely difficult to observe due to technical difficulties from both field and remote platforms. Here using novel satellite ocean color data products and modified algorithms, we address this challenge for the Florida Straits (22–28°N, 78–85°W). Between 2002 and 2018, while mesoscale eddies (radius >15 km) show strong seasonality with occurrence frequency decreasing from Lower Keys to Upper Keys, submesoscale eddies show little or no seasonality with high occurrence frequency restricted to 30–200‐m isobaths. The number of mesoscale eddies decreases exponentially in size, but submesoscale eddies show a normal distribution in size. These findings are significant in filling our knowledge gap in submesoscale eddies in this physically and ecologically important region as it encompasses world‐renowned coral reefs, seagrasses, and fisheries.

Global ocean primary production trends in the modern ocean color satellite record (1998–2015)

Ocean primary production (PP), representing the uptake of inorganic carbon through photosynthesis, supports marine life and affects carbon exchange with the atmosphere. It is difficult to ascertain its magnitude, variability, and trends due to our inability to measure it directly at large scales. Yet it is paramount for understanding changes in marine health, fisheries, and the global carbon cycle. Using assimilation of ocean color satellite data into an ocean biogeochemical model, we estimate that global net ocean PP has experienced a small but significant decline −0.8 PgC y−1 (−2.1%) decade−1 (P < 0.05) in the 18-year satellite record from 1998 to 2015. This decline is associated with shallowing surface mixed layer depth (−2.4% decade−1) and decreasing nitrate concentrations (−3.2% decade−1). Relative contributions to PP by various types of ocean phytoplankton have changed, with decreases in production by intermediate-sized phytoplankton represented by chlorophytes (−14.3% decade−1). This is partially compensated by increases from the unique, more nutrient-efficient, coccolithophores (8.4% decade−1). Geographically, the North and Equatorial Indian Oceans are responsible for much of the decline in PP, falling 0.16 and 0.69 PgC y−1 decade−1, respectively. Reduced production by large, fast-growing diatoms along with chlorophytes characterizes the decline here. In contrast, increases in PP are found in the North and North Central Pacific. The increases here are led by chlorophytes in the North Pacific and the small cyanobacteria in the North Central Pacific. These results suggest that the multi-decadal satellite observational record, coupled with an underlying representation of marine biodiversity in a model, can monitor the uptake of carbon by phytoplankton and that changes, although small, are occurring in the global oceans.

Spatial variability of fishing grounds in response to oceanic front changes detected by multiple satellite measurements in the East (Japan) sea

ABSTRACT In the East (Japan) Sea, the ocean fronts resulting from coastal upwelling and eddies affect the formation of fishing grounds by creating an environment with abundant food resources. The aim of this study was to examine the relationship between fishing activities and the locations of these ocean fronts. To do this, Day/Night Band (DNB) images were used, and ocean fronts were detected based on satellite ocean colour data. It was found that the illuminated pixels on the DNB images were related to the number of sailed out boats (coefficient of determination, R 2 = 0.55) and so may represent the number of fishing activities. Consequently, a new index was developed to assess the spatial correlation between the locations of fishing activities and ocean fronts, referred to as the ‘DNB score,’ which combined the scientific method of determining the locations of regional ocean fronts with the social method of observing the locations of fishing activities based on fishermen’s experiences. The DNB score was approximately 21% for the coastal upwelling front and 44% for the eddy front. Since most boats with lights in the East Sea are known to be fishing for Todarodes pacificus, the relationship between the DNB score and the catch of T. pacificus was also examined. This showed that the DNB score reflected the temporal catch variability and the catch per unit effort of T. pacificus, suggesting that it could be used as an index to evaluate the location of fishing grounds in association with fishing activities.

Spatial heterogeneity of seasonal phytoplankton blooms in a marginal sea: physical drivers and biological responses

Abstract Satellite and in situ observations are used in this study to examine spatial heterogeneity in the timing and magnitude of phytoplankton blooms in relation to local and remote physical processes in the Yellow Sea (YS), a marginal sea in the northwestern Pacific Ocean. Satellite ocean colour data reveal that annual chlorophyll maximums vary significantly in both timing and magnitude over different subregions of the YS. Strong summer blooms were found off estuary regions, and widespread spring blooms were found in the central trough. Localized autumn and winter peaks were found in small patches around Jeju Island and in nearshore regions. A statistical analysis of in situ measurements of the western YS suggests that variability in hydrographic properties could explain most of the spatial heterogeneity observed in both bloom timing and magnitude. The spatial heterogeneity of hydrographic properties, such as stratification and nutrient availability, are controlled by a suite of physical forcings, including the extent of the YS Cold Water Mass, river discharge, warm slope water intrusion, and seasonal warming/cooling. Our results imply that the spatial heterogeneity of marginal seas must be carefully considered when assessing phytoplankton responses in the context of climate change, because of the complexity of underlying mechanisms.

Comparison of Particulate Organic Carbon to Chlorophyll-a Ratio Based on the Ocean Color Satellite Data at the Ieodo and Socheongcho Ocean Research Stations

Lee, D.; Jeong, J.-Y.; Jang, H.K.; Min, J.-O.; Kim, M.J.; Youn, S.H.; Lee, T., and Lee, S.H., 2019. Comparison of particulate organic carbon to chlorophyll-a ratio based on the ocean color satellite data at the Ieodo and Socheongcho ocean research stations. In: Jung, H.-S.; Lee, S.; Ryu, J.-H., and Cui, T. (eds.), Advances in Remote Sensing and Geoscience Information Systems of Coastal Environments. Journal of Coastal Research, Special Issue No. 90, pp. 267-271. Coconut Creek (Florida), ISSN 0749-0208.The Ieodo ocean research station (IORS) and the Socheongcho ocean research station (SORS) have been operated in South Korea to carry out a research across multiple disciplines. The IORS and the SORS are affected by various water masses such as Tsushima Warm Current (TWC), Yellow Sea Warm Current (YSWC) and Changjiang Diluted Water (CDW). Therefore, the IORS and the SORS are suitable for the research on the physio-ecological response of phytoplankton to environmental changes. The particulate organic carbon to chlorophyll-a ratio (POC:Chl-a) has been widely used for an indicator of the ecological and physiological conditions of the phytoplankton. The purpose of this study is to investigate the POC:Chl-a ratio and its controlling factors at the IORS and the SORS by using satellite dataset. At the IORS, POC:Chl-a ratio ranged from 166.16 to 431.20, and the average was 322.14 ± 46.35. On the other hand, at the SORS, POC:Chl-a ratio ranged from 131.92 to 703.98, and the average was 385.05 ± 123.95. The POC:Chl-a ratio was higher at the SORS from autumn to winter. However, POC:Chl-a ratio in the IORS showed similar ranges in every month. The difference in POC:Chl-a ratio between the IORS and the SORS appear to be caused by differences of environmental conditions such as light intensity, temperature, and nutrients. However, to reveal the detailed relationship between environmental conditions and POC:Chl-a ratio, a further study on seasonal variations of the phytoplankton community structure and several environmental parameters would be warrant.

Red Tide Detection Based on High Spatial Resolution Broad Band Satellite Data: A Case Study of GF-1

Liu, R.-J.; Zhang, J.; Cui, B.-G.; Ma, Y.; Song, P.J., and An, J.-B., 2019. Red tide detection based on high spatial resolution broad band satellite data: A case study of GF-1. In: Jung, H.-S.; Lee, S.; Ryu, J.-H., and Cui, T. (eds.), Advances in Remote Sensing and Geoscience Information Systems of Coastal Environments. Journal of Coastal Research, Special Issue No. 90, pp. 120-128. Coconut Creek (Florida), ISSN 0749-0208.Traditional red tide remote sensing detection methods are based on ocean color satellite data with high spectral resolution (spectral band width < 20 nm), but low spatial resolution. Clearly, fine-scale remote-sensing monitoring of red tide requires high spatial resolution satellite data. Yet, satellite data with high spatial resolution often lack high spectral resolution, with spectral band width > 50 nm. Moreover, systematic research has yet to demonstrate effective detection of red tide using high spatial resolution, but low spectral resolution, satellite data. In this paper, high spatial resolution (16 m), but low spectral resolution, data from the satellite, GF-1, are analyzed to determine if effective fine-scale detection of red tide is possible. The spectral response characteristics of red tide in GF-1 data are analyzed using a 2014 red tide event that occurred in Guangdong Province, China. It was found that, despite broad spectral band widths, GF-1 WFV imaging spectrometer data still exhibits a clear tide detection algorithm for GF-1 WFV data based on this red tide spectral signal. The detection accuracy of red tide for this algorithm is better than 92 %, and the F1-Score value is better than 87 %. Spatial analysis of the Guangdong 2014 red-tide event based on this algorithm showed that the maximum red tide area extracted from GF-1 satellite data is 10 km2, and that the red tide area decreases greatly during the extinction phase. A comparative analysis of MODIS satellite data indicates that, despite the availability of multiple ocean color bands, no ocean color anomaly is detected because of coarse spatial resolution. The developed method was also successfully used to detect red tide occurred in Rizhao, Shandong Province.

UV-NIR approach with non-zero water-leaving radiance approximation for atmospheric correction of satellite imagery in inland and coastal zones.

In the atmospheric correction process of the satellite ocean color data, the removal of the aerosol scattering contribution over the coastal and inland water bodies has been a major challenge with the standard algorithms. In this work, a practical method is proposed based on a combination of NIR and ultraviolet (UV) bands (named as UVNIR-ex) for the succeeding generation of space borne multispectral and hyperspectral sensors. This scheme replaces the black-ocean assumption and accounts for non-zero water-leaving radiance contributions in the NIR and UV bands. The aerosol contributions are thus deduced for these two bands and used to select the appropriate aerosol models to retrieve aerosol optical properties and hence, water-leaving radiances in the UV, Visible and NIR bands. The performance of the UVNIR-ex algorithm was tested and evaluated based on match-ups between HICO and in-situ observations in optically complex coastal and inland waters and by comparison with three alternative aerosol correction methods based on UV-NIR, Spectral Shape Parameter (SSP) and iterative NIR (INIR) approaches. A preliminary comparison with in-situ aerosol optical thickness (AOT) measurements from AERONET-OC sites revealed that the UVNIR-ex algorithm significantly improved the AOT retrievals with a mean relative error (MRE) around 25%, while the UVNIR, SSP and INIR algorithms showed performance degradation with a MRE of 27%, 34%, and 42%, respectively. The comparison with AERONET-OC and regional in-situ measurements from turbid and productive waters further showed that the INIR algorithm underestimated the nLw retrievals in blue bands in turbid waters (MRE > 100%) and negligible nLw in red-NIR bands and high anomalous radiances in UV-Blue bands in productive waters (MRE 53%). The SSP and UVNIR algorithms performed better in retrieving the nLw in green-NIR bands but showed significant errors in UV-blue bands in both turbid and productive waters. Based on these match-up analyses, the UVNIR-ex algorithm yielded best nLw retrievals across all the UV-NIR bands in terms of accuracy and performance. The highest accuracy and consistency of the UVNIR-ex algorithm indicates that it is more suited for estimating the aerosol optical properties and water-leaving radiance and has a significant advantage over the requirement of shortwave infrared bands for turbid and productive waters.

The influence of geostrophic strain on oceanic ageostrophic motion and surface chlorophyll

Oceanic submesoscale ageostrophic processes have been progressively recognized as an important upwelling mechanism to close the nutrient budget and sustain the observed primary production of phytoplankton in the euphotic layer. Their relatively small spatio-temporal scales (of 1~10 km and a few days) have hindered a systematic observational quantification of the submesoscale ageostrophic flow variability and its impact on ocean biogeochemistry. By combining surface drifters, satellite altimetry and satellite ocean-color data, we detect that when the strain rate of mesoscale surface geostrophic flow is strong, it favors a higher ageostrophic kinetic energy level and an increase in surface chlorophyll concentration. The strain-induced frontal processes are characterized by a surface chlorophyll increase and secondary ageostrophic upwelling along the light side of the oceanic density front. Further analysis indicates that the balanced ageostrophic motions with longer time scales are more effective in inducing chlorophyll increase than the unbalanced shorter time-scale wave motions.

A blended inherent optical property algorithm for global satellite ocean color observations

AbstractWater inherent optical properties (IOPs) can be derived from satellite‐measured normalized water‐leaving radiance (nLw(λ)) spectra. In this study, we evaluate the performance of the quasi‐analytical algorithm (QAA) and the near‐infrared (NIR)‐based IOP algorithm using a Hydrolight simulation data set covering a wide range of water types that span from clear open ocean to turbid coastal/inland waters. The NIR‐based algorithm produces significantly improved IOP retrievals over turbid coastal and inland waters, while the QAA algorithm performs well in the open ocean and less turbid coastal waters. Based on the advantages of the NIR‐based and QAA‐based algorithms, a combination of the NIR‐ and QAA‐based algorithm has been proposed using satellite‐measured nLw(745) as the threshold in order to produce accurate IOP products for both the open ocean and turbid coastal/inland waters. The new combined IOP algorithm can produce reasonably accurate IOP data for all water types, and can be easily implemented into the satellite ocean color data processing. The La Plata River Estuary region is used as an example to show the difference in performance of IOP retrievals from the Visible Infrared Imaging Radiometer Suite (VIIRS) measurements between 2012 and 2017 with the NIR‐based, QAA‐based, and NIR‐QAA combined IOP algorithms. We also demonstrate that the NIR‐QAA combined algorithm can be applied to VIIRS global ocean color observations to derive good quality IOP products in China's east coastal region, the US east coastal region, and the region of Mississippi River Estuary and tributaries.

Deriving inherent optical properties from decomposition of hyperspectral non-water absorption

Semi-analytical algorithms (SAAs) developed for multispectral ocean color sensors have benefited from a variety of approaches for retrieving the magnitude and spectral shape of inherent optical properties (IOPs). SAAs generally follow two approaches: 1) simultaneous retrieval of all IOPs, resulting in pre-defined bio-optical models and spectral dependence between IOPs and 2) retrieval of bulk IOPs (absorption and backscattering) first followed by decomposition into separate components, allowing for independent retrievals of some components. Current algorithms used to decompose hyperspectral remotely-sensed reflectance into IOPs follow the first strategy. Here, a spectral deconvolution algorithm for incorporation into the second strategy is presented that decomposes at-w(λ) from in situ measurements and estimates absorption due to phytoplankton (aph(λ)) and colored detrital material (adg(λ)) free of explicit assumptions. The algorithm described here, Derivative Analysis and Iterative Spectral Evaluation of Absorption (DAISEA), provides estimates of aph(λ) and adg(λ) over a spectral range from 350 to 700 nm. Estimated aph(λ) and adg(λ) showed an average normalized root mean square difference of <30% and <20%, respectively, from 350 to 650 nm for the majority of optically distinct environments considered. Estimated Sdg median difference was <20% for all environments considered, while distribution of Sdg uncertainty suggests that biogeochemical variability represented by Sdg can be estimated free of bias. DAISEA results suggest that hyperspectral satellite ocean color data will improve our ability to track biogeochemical processes affiliated with variability in adg(λ) and Sdg free of explicit assumptions.

Simulation of Sedimentation in Lake Taihu with Geostationary Satellite Ocean Color Data

In this study, the goal is to estimate the sedimentation on the bottom bed of Lake Taihu using numerical simulation combined with geostationary satellite ocean color data. A two-dimensional (2D) model that couples the dynamics of shallow water and sediment transport is presented. The shallow water equations are solved using a semi-implicit finite difference method with an Alternating Direction Implicit (ADI) method. Suspended sediment transport is simulated by solving the general convection-diffusion equation with resuspension and deposition terms using a second-order explicit central difference method in space and two-step Adams–Bashforth method in time. Moreover, the total suspended particulate matter (TSM) is retrieved by the world’s first geostationary satellite ocean color sensor Geostationary Ocean Color Imager (GOCI) using atmospheric correction algorithm for turbid waters using ultraviolet wavelengths (UV-AC) and regional empirical TSM algorithm. The 2D model and GOCI-retrieved TSM are applied to study the sediment transport and sedimentation in Lake Taihu. Validation results show rationale TSM concentration retrieved by GOCI, and the simulated TSM concentrations are consistent with GOCI observations. In addition, simulated sedimentation results reveal the dangerous locations that must be observed and desilted.

Spatial variations of small phytoplankton contributions in the Northern Bering Sea and the Southern Chukchi Sea

Phytoplankton size classes (hereafter, PSCs) were derived from satellite ocean color data using a present phytoplankton abundance-based optical algorithm in the northern Bering and southern Chukchi Seas to characterize the spatial and seasonal variations of the different PSC and investigate the contributions of small phytoplankton to the total phytoplankton biomass. The comparison results showed that the phytoplankton abundance-based method approach could reasonably classify the three PSCs (pico-, nano-, and micro phytoplankton). The satellite maps of the dominant PSCs were derived using long-term satellite ocean color data. The general spatial distribution showed that the large (micro-) phytoplankton were dominant in the coastal waters and the west side of the Bering strait, while the small size (nano- or pico-) phytoplankton were dominant in the open ocean waters. Nano- and microphytoplankton were dominant in May and October in most of the study area, while pico-phytoplankton were dominant in the summer months in the open ocean waters. The annual variation in small phytoplankton dominance had a strong positive relationship with the annual mean sea surface temperature (SST), which is consistent with the increasing dominance of small phytoplankton biomass as water temperature increases. Microphytoplankton have an apparent increasing trend in the southeastern Chukchi Sea but slightly decreasing trends in Chirikov and St. Lawrence Island Polynya (SLIP). In contrast, there were increasing trends in picophytoplankton in Chirikov and SLIP, which seems to be related to increasing annual SST. It is crucial to monitor changes in dominant groups of phytoplankton community in the Bering and Chukchi Seas as important biological hotspots responding to the recent changes in environmental conditions.

Satellite monitoring of harmful algal blooms in the Western Basin of Lake Erie: A 20-year time-series

Blooms of harmful cyanobacteria (cyanoHABs) have occurred on an annual basis in western Lake Erie for more than a decade. Previously, we developed and validated an algorithm to map the extent of the submerged and surface scum components of cyanoHABs using MODIS ocean-color satellite data. The algorithm maps submerged cyanoHABs by identifying high chlorophyll concentrations (>18 mg/m3) combined with water temperature >20 °C, while cyanoHABs surface scums are mapped using near-infrared reflectance values. Here, we adapted this algorithm for the SeaWiFS sensor to map the annual areal extents of cyanoHABs in the Western Basin of Lake Erie for the 20-year period from 1998 to 2017. The resulting classified maps were validated by comparison with historical in situ measurements, exhibiting good agreement (81% accuracy). Trends in the annual mean and maximum total submerged and surface scum extents demonstrated significant positive increases from 1998 to 2017. There was also an apparent 76% increase in year-to-year variability of mean annual extent between the 1998–2010 and 2011–2017 periods. The 1998–2017 time-series was also compared with several different river discharge nutrient loading metrics to assess the ability to predict annual cyanoHAB extents. The prediction models displayed significant relationships between spring discharge and cyanoHAB area; however, substantial variance remained unexplained due in part to the presence of very large blooms occurring in 2013 and 2015. This new multi-sensor time-series and associated statistics extend the current understanding of the extent, location, duration, and temporal patterns of cyanoHABs in western Lake Erie.

Spatial and Temporal Variability of Coccolithophore Blooms in the Eastern Bering Sea

AbstractCoccolithophores are a widespread group of marine phytoplankton that produce plates of calcium carbonate that cover their cells. Large blooms of coccolithophores may significantly influence the biogeochemical properties of the ocean and atmosphere and trophic dynamics of the marine ecosystem. Because of the important implications of coccolithophore blooms, their timely monitoring and reporting is necessary for ecosystem management. To communicate with ecosystem management stakeholders, we developed an annual Coccolithophore Bloom Index (CBI) for the eastern Bering Sea shelf using satellite ocean color data. Comparisons between in situ and satellite data and the CBI (years 1997–2017) were used to examine the hypotheses regarding environmental influences on interannual bloom variability. A significant nonlinear relationship with summer stratification was found: the CBI was higher during years with either very low or very high stratification. In addition, while the blooms usually occurred over the middle shelf (50‐ to 100‐m depth), more of the bloom was located over the shallow (30–50 m) inner shelf when stratification was low. Spatial correspondence between nutrient concentrations (nitrate and ammonium) and the areal extent of the coccolithophore bloom provides tantalizing but nonconclusive evidence that nutrient availability plays a role in bloom formation and location.

Impact of spatiotemporal variability in phytoplankton size structure on benthic macrofaunal distribution in the Pacific Arctic

The size structure of the phytoplankton community strongly affects energy flow through food webs; hence, monitoring the spatial and temporal dynamics of phytoplankton size structure is crucial to evaluate variability in marine ecosystems. In this study, the spatiotemporal changes in phytoplankton size structure and their impact on benthic macrofaunal distribution were examined in the Pacific Arctic as part of the international Distributed Biological Observatory effort. The exponent of the chlorophyll-a (Chla) size distribution (hereafter, CSD slope), which is an index of synoptic size structure of a phytoplankton community, was estimated based on spectral shape of the phytoplankton absorption coefficient using satellite ocean color data. The CSD slope during the post-bloom period was significantly correlated with sediment Chla concentration, suggesting that the amount of organic carbon input to the seafloor was strongly related to surface phytoplankton size structure after the spring bloom. Average macrofaunal biomass in the Pacific Arctic was persistently high (>20 g C m−2) throughout 2000–2013 in the regional hotspots, and the biomass-based latitudinal centroid of macrofaunal habitat in the region shifted significantly (p < 0.05) northward. This northward shift is likely driven by a spatiotemporal change in phytoplankton size structure during the post-bloom period. Our results suggest that bottom-up forcing by the phytoplankton community affected the distribution of benthic macrofauna. We conclude that the remote estimate of phytoplankton size structure largely contributes to advancing our knowledge of ecosystem changes observed in the Pacific Arctic marine ecosystem.

Northward Expansion and Intensification of Phytoplankton Growth During the Early Ice‐Free Season in Arctic

AbstractIn the last decades, reduction of the ice cover has been documented to affect the structure and the functioning of Arctic marine ecosystems. One direct consequence is earlier phytoplankton spring blooms and larger annual primary production compared with previous decades. However, the impact of changes in the dynamics of sea ice specifically on phytoplankton spring blooms, a major contributor of the annual primary production in the Arctic Ocean, remains poorly known. Here we report on their temporal and spatial variabilities in open waters between 2003 and 2013 using satellite ocean color data. We observed a significant increase in primary productivity of phytoplankton spring blooms in different sectors of the Arctic Ocean, especially in the Barents and Kara Seas. Satellite observations also revealed a northward expansion of these blooms at a rate of 1° per decade driven by the Barents and the Kara regions.

Improved MODIS-Aqua Chlorophyll-a Retrievals in the Turbid Semi-Enclosed Ariake Bay, Japan

The accurate retrieval of chlorophyll-a concentration (Chl-a) from ocean color satellite data is extremely challenging in turbid, optically complex coastal waters. Ariake Bay in Japan is a turbid semi-enclosed bay of great socio-economic significance, but it suffers from serious water quality problems, particularly due to red tide events. Chl-a derived from the MODerate resolution Imaging Spectroradiometer (MODIS) sensor on satellite Aqua in Ariake Bay was investigated, and it was determined that the causes of the errors were from inaccurate atmospheric correction and inappropriate in-water algorithms. To improve the accuracy of MODIS remote sensing reflectance (Rrs) in the blue and green bands, a simple method was adopted using in situ Rrs data. This method assumes that the error in MODIS Rrs(547) is small, and MODIS Rrs(412) can be estimated from MODIS Rrs(547) using a linear relation between in situ Rrs(412) and Rrs(547). We also showed that the standard MODIS Chl-a algorithm, OC3M, underestimated Chl-a, which was mostly due to water column turbidity. A new empirical switching algorithm was generated based on the relationship between in situ Chl-a and the blue-to-green band ratio, max(Rrs(443), Rrs(448)/Rrs(547), which was the same as the OC3M algorithm. The criterion of Rrs(667) of 0.005 sr−1 was used to evaluate the extent of turbidity for the switching algorithm. The results showed that the switching algorithm performed better than OC3M, and the root mean square error (RMSE) of estimated Chl-a decreased from 0.414 to 0.326. The RMSE for MODIS Chl-a using the recalculated Rrs and the switching algorithm was 0.287, which was a significant improvement from the RMSE of 0.610, which was obtained using standard MODIS Chl-a. Finally, the accuracy of our method was tested with an independent dataset collected by the local Fisheries Research Institute, and the results revealed that the switching algorithm with the recalculated Rrs reduced the RMSE of MODIS Chl-a from 0.412 of the standard to 0.335.

Enduring Lagrangian coherence of a Loop Current ring assessed using independent observations

Ocean flows are routinely inferred from low-resolution satellite altimetry measurements of sea surface height assuming a geostrophic balance. Recent nonlinear dynamical systems techniques have revealed that surface currents derived from altimetry can support mesoscale eddies with material boundaries that do not filament for many months, thereby representing effective transport mechanisms. However, the long-range Lagrangian coherence assessed for mesoscale eddy boundaries detected from altimetry is constrained by the impossibility of current altimeters to resolve ageostrophic submesoscale motions. These may act to prevent Lagrangian coherence from manifesting in the rigorous form described by the nonlinear dynamical systems theories. Here we use a combination of satellite ocean color and surface drifter trajectory data, rarely available simultaneously over an extended period of time, to provide observational evidence for the enduring Lagrangian coherence of a Loop Current ring detected from altimetry. We also seek indications of this behavior in the flow produced by a data-assimilative system which demonstrated ability to reproduce observed relative dispersion statistics down into the marginally submesoscale range. However, the simulated flow, total surface and subsurface or subsampled emulating altimetry, is not found to support the long-lasting Lagrangian coherence that characterizes the observed ring. This highlights the importance of the Lagrangian metrics produced by the nonlinear dynamical systems tools employed here in assessing model performance.

Satellite ocean colour algorithm for Prochlorococcus, Synechococcus, and picoeukaryotes concentration retrieval in the South China Sea

An algorithm for retrieval of surface waters cell concentrations (in cell/ml) for three picophytoplankton components, Prochlorococcus (Pro), Synechococcus (Syn), and picoeukaryotes (Peuk) in the South China Sea (SCS), from ocean colour satellite data was developed and tested. Level 3 merged multisensor Ocean Colour Climate Change Initiative satellite data is used. Training is performed using in situ data on abundances of the three phytoplankton components. Several predictors derived from satellite reflectance data were tested. The regression form that assures the highest accuracy of the algorithm was chosen based on cross-validation (CV). According to the CV on test data subset, the algorithm performance is characterized by the r value 0.89, 0.72, and 0.73 and MAPD 38, 71 and 51% for Peuk, Pro, and Syn respectively. This is one of the few studies aimed at the Peuk, Pro, and Syn distribution research in the northern SCS using ocean colour satellite data. This is the only research providing algorithm with accuracy estimates of the Peuk, Pro, and Syn concentrations retrieval from the ocean colour data. Analysis of the developed algorithm allows us to conclude that both mechanisms (specific spectral features caused by pigments composition and spectrum features sensitive to general primary productivity, e.g. band ratios in 443–510 nm range and spectrum absolute values) are important for getting accurate information on the picophytoplankton composition.

Impact of decadal reversals of the north Ionian circulation on phytoplankton phenology

Abstract. In the north Ionian, water circulation is characterized by a decadal alternation of cyclonic and anticyclonic regime driven by the mechanism called BiOS (bimodal oscillating system). The circulation regimes affect both vertical dynamics and the nutrient distribution. The north Ionian is then a good study area to investigate how changes in circulation can affect phytoplankton dynamics in oligotrophic regions. From in situ observations, for each circulation regime the averaged distribution of isopycnals is provided, and a depth difference of about 80 m is estimated for the nitracline between the cyclonic and anticyclonic regime. Based on phytoplankton phenology metrics extracted from annual time series of satellite ocean color data for the period 1998–2012, the cyclonic and anticyclonic regimes are compared. Results show that the average chlorophyll in March, the date of bloom onset and the date of maximum chlorophyll were affected by circulation patterns in the north Ionian. In the center of the north Ionian gyre, the bloom started in December and chlorophyll was low in March when circulation was anticyclonic, whereas during the cyclonic circulation regime, a late chlorophyll peak, likely resulting from different phytoplankton dynamics, was commonly observed in March. An additional analysis shows that the winter buoyancy losses, which govern the mixed layer depth (MLD), also contribute to explaining the interannual variability in bloom onset and intensity. Two trophic regimes were then identified in the north Ionian gyre (NIG) and they could be explained with the relative position of the MLD and nitracline. The first one is characterized by an early winter bloom onset and the absence of a chlorophyll peak in March. It was observed when circulation was anticyclonic or when winter MLD was relatively shallow. Dominant regenerated production all year and an absence of significant nutrient supplies to surface waters are proposed to explain this trophic regime. Conversely, the second trophic regime is marked by a bloom onset in late winter (i.e., February) and a chlorophyll peak in March. The chlorophyll increase was interpreted as a direct response to the nutrient enrichment of surface waters. This winter–spring bloom was observed when circulation was cyclonic and when winter mixing was relatively strong.