Variability Of Chl-a Research Articles

Variabilidade Temporal das Concentrações de Clorofila -A e da Temperatura Superficial do Mar na Costa Central de Santa Catarina

O fenômeno das florações de algas é conhecido mundialmente devido aos impactos diretos na saúde dos ecossistemas aquáticos, nos recursos pesqueiros e aquícolas, nas atividades recreacionais e na saúde humana. O presente estudo avaliou o uso de sensores satelitais na quantificação dos parâmetros de temperatura superficial do mar (TSM) e concentração de clorofila-a na superfície do mar (Chl-a) na costa de Santa Catarina, durante o período entre 2002 e 2019, objetivando identificar a variabilidade temporal da TSM e da Chl-a a partir da decomposição das séries temporais em tendência, sazonalidade e resíduos. Para atingir este objetivo foram adquiridas estimativas de TSM e Chl-a oriundas dos sensores orbitais Moderate-Resolution Imaging Spectroradiometer (MODIS) a bordo dos satélites (Aqua e Terra) e Visible Infrared Imaging Radiometer Suite (VIIRS) a bordo dos satélites (SNPP e NOAA-20). Através da extração dos valores de TSM e Chl-a para um ponto ao largo da costa central de Santa Catarina foram geradas séries temporais para o período especificado e aplicada a metodologia de decomposição de séries temporais para identificar oscilações de baixa frequência. Foi possível identificar que os eventos com maior Chl-a estão relacionados com eventos com menores valores de TSM. As componentes encontradas poderão ser utilizadas para modelos preditivos auxiliando assim a minimizar os impactos associados às florações de algas.

Analysis of surface chlorophyll a associated with sea surface temperature and surface wind in the South China Sea

In this study, the spatial and temporal variability in surface chlorophyll a (Chl-a) in the whole South China Sea (SCS) was investigated in detail by using 8-day, 4-km, gap-free MODIS-A data (2003–2016). Monthly climatology and empirical-orthogonal-functions analysis of Chl-a were performed in association with sea surface temperature and surface wind to aid in better understanding the physical mechanisms responsible for the Chl-a variability. The results are as follows: (1) Chl-a has out-of-phase variability between the coastal and open-sea regions due to different major factors controlling phytoplankton growth in each region; (2) in particular, Chl-a increases in the northern SCS during winter and in the western and southwestern SCS during summer mainly due to the effects of monsoons and orography; and (3) wind-driven coastal upwelling is stronger in the western SCS than in the eastern SCS. A wind-induced coastal upwelling not reported in the literature was detected along Palawan Island (8–12∘N, 117–120∘E) during winter. In the SCS, the Chl-a variability is influenced by the El Nino–Southern Oscillation with a time lag of 4–9 months, depending on the variability scales.

The Influence of Seasonal and Interannual Variability on Surface Chlorophyll-a Off the Western Lesser Sunda Islands

Novel and long-term satellite data (2003–2017) are analyzed to investigate the variability of ocean surface chlorophyll-a (Chl-a) concentration off the Western Lesser Sunda Islands (WLSI) under the influence of the Indonesian Australian monsoon, the El Nino-Southern Oscillation, and the Indian Ocean Dipole (IOD). In this article, we first analyzed the seasonal variability of Chl-a, and then describe the relationship among the sea surface Chl-a, sea surface temperature (SST), and sea surface wind stress in the region. Our results demonstrate that prevailing southeasterly wind stress plays a pivotal role in generating the Chl-a maxima off the WLSI. Particularly on seasonal time scale, the strengthening of southeasterly wind stress (up to ∼0.01 N·m−2) during the southeast monsoon season produces enhanced Chl-a concentrations (0.59 mg·m−3) associated with sea surface cooling (∼28.8 °C) in the area of study. In contrast, the Chl-a maxima completely vanished during the northwest monsoon season. On interannual time scale, the largest positive Chl-a and wind stress anomalies and the coolest SST anomaly are observed in 2006 when El Nino and positive IOD events occur at the same time. Meanwhile, the greatest negative Chl-a anomaly is prevailed during the 2016 negative IOD event. This article demonstrates that wind variability is the essential factor in determining the magnitude of the Chl-a maxima off the WLSI.

VARIABILITY OF SEA SURFACE TEMPERATURE (SST) AND CHLOROPHYLL-A (CHL-A) CONCENTRATIONS IN THE EASTERN INDIAN OCEAN DURING THE PERIOD 2002–2017

We analysed the variability of sea surface temperature (SST) and chlorophyll-a concentration (Chl-a) in the eastern Indian Ocean (EIO). We used monthly mean Chl-a and SST data with a 4-km spatial resolution derived from Level-3 Aqua Moderate-resolution Imaging Spectroradiometer (MODIS) distributed by the Asia-Pacific Data-Research Center (APDRC) for the period 2002–2017. Wavelet analysis shows the annual and interannual variability of SST and Chl-a concentration in the EIO. The annual variability of SST and Chl-a is influenced by monsoon systems. During a southeast monsoon, SST falls while Chl-a increases due to upwelling. The annual variability of SST and Chl-a is also influenced by the Indian Ocean Dipole (IOD). During positive phases of the IOD (2006, 2012 and 2015), there was more intense upwelling in the EIO caused by the negative anomaly of SST and the positive anomaly of Chl-a concentration.

Estimation of Chlorophyll-a in Northern Coastal Bay of Bengal Using Landsat-8 OLI and Sentinel-2 MSI Sensors

Chlorophyll-a can be used as a proxy for phytoplankton and thus is an essential water quality parameter. The presence of phytoplankton in the ocean causes selective absorption of light by chlorophyll-a pigment resulting in change of the ocean color that can be identified by ocean colour remote sensing. The accuracy of chlorophyll-a concentration (Chl-a) estimated from remote sensing sensors depends on the bio-optical algorithm used for the retrieval in specific regional waters. In this work, it is attempted to estimate Chl-a from two currently active satellite sensors with relatively good spatial resolutions considering ocean applications. Suitability of two standard bio-optical Ocean Colour (OC) Chlorophyll algorithms, OC-2 (2-band) and OC-3 (3-band) in estimating Chl-a for turbid waters of the northern coastal Bay of Bengal is assessed. Validation with in-situ data showed that OC-2 algorithm gives an estimate of Chl-a with a better correlation of 0.795 and least bias of 0.35 mg/m3. Further, inter-comparison of Chl-a retrieved from the two sensors, Landsat-8 OLI and Sentinel-2 MSI was also carried out. The variability of Chl-a during winter, pre-monsoon and post-monsoon seasons over the study region were inter-compared. It is observed that during pre-monsoon and post-monsoon seasons, Chl-a from MSI is over estimated compared to OLI. This work is a preliminary step towards estimation of Chl-a in the coastal oceans utilizing available better spatially resolved sensors.

The variability of chlorophyll-a and its relationship with dynamic factors in the basin of the South China Sea

Abstract Satellite observations from 2002 to 2017 were used to investigate the spatial distribution and temporal variability of chlorophyll-a (Chl-a) in the South China Sea (SCS). High levels of Chl-a were mostly found near the coasts of China and Vietnam, with a significantly long-term increasing trend. Large seasonal variability was found in the northern SCS and southeast of Vietnam. The Chl-a levels reached the maximum in winter and minimum in summer for majority of the SCS, while the seasonal variability to the southeast of Vietnam was out of phase. The monsoon winds and sea surface temperatures were the most important determinants impacting the distribution and variability of Chl-a along with other associated and influential environmental drivers, e.g., wind stress curl, frontal activity, and sea level anomalies. High correlation coefficients for the seasonal variability between Chl-a and other factors were found in a majority of the SCS, especially in the northern and central parts. The coefficients to the southeast of Vietnam were not valid at seasonal scales, but Chl-a and other factors were significantly correlated at the monthly anomalous fields. This observation occurred because the nutrient supply was mainly determined by local dynamics, e.g., wind-induced coastal upwelling and offshore transport. The interannual variability indicated low levels of Chl-a southeast of Vietnam during El Nino years because of the weakened southwest monsoon. The study offered the first comprehensive description of Chl-a in the SCS at seasonal, anomalous, and interannual variability scales and an analysis of the potential contributing dynamical processes.

Atmospheric factors influencing biological productivity in the Antarctic polynyas, derived from satellite and reanalysis data

ABSTRACTAntarctic coastal polynyas are the most productive area in the Southern Ocean, playing a significant role in a polar ecosystem. Understanding polynya properties is important because changes in polynya’s environment can alter, or even disrupt, the polar food web. Nevertheless, there are still many unknown aspects of polynyas and its subsequent effects in the ecosystem. Based on satellite and atmospheric reanalysis data for 1998–2016, roles of atmospheric forcing on phytoplankton dynamics are examined. We find that chlorophyll-a (chl-a) has a noticeable year-to-year variability and its responses to atmospheric forcing differ regionally. That is, winds have a strong correlation with chl-a in the west Antarctic polynyas since strong winds tend to increase nutrient entrainment from subsurface water. A cloud cover is suggested to influence chl-a variability with a strong inverse correlation in the Weddell Sea and a moderate inverse correlation in the Amundsen Sea. We also find that chl-a decreases for 1998–2016 in the Amundsen Sea and Weddell Sea, which implies that a large amount of glacier meltwater is likely to decrease chl-a by enhancing oceanic stratification, whereas iron supply from recent higher ice melt would not directly affect such a long-term chl-a change.

Chlorophyll Concentration Response to the Typhoon Wind-Pump Induced Upper Ocean Processes Considering Air–Sea Heat Exchange

The typhoon Wind-Pump induced upwelling and cold eddy often promote the significant growth of phytoplankton after the typhoon. However, the importance of eddy-pumping and wind-driven upwelling on the sea surface chlorophyll a concentration (Chl-a) during the typhoon are still not clearly distinguished. In addition, the air–sea heat flux exchange is closely related to the upper ocean processes, but few studies have discussed its role in the sea surface Chl-a variations under typhoon conditions. Based on the cruise data, remote sensing data, and model data, this paper analyzes the contribution of the vertical motion caused by the eddy-pumping upwelling and Ekman pumping upwelling on the surface Chl-a, and quantitatively analyzes the influence of air–sea heat exchange on the surface Chl-a after the typhoon Linfa over the northeastern South China Sea (NSCS) in 2009. The results reveal the Wind Pump impacts on upper ocean processes: (1) The euphotic layer-integrated Chl-a increased after the typhoon, and the increasing of the surface Chl-a was not only the uplift of the deeper waters with high Chl-a but also the growth of the phytoplankton; (2) The Net Heat Flux (air–sea heat exchange) played a major role in controlling the upper ocean physical processes through cooling the SST and indirectly increased the surface Chl-a until two weeks after the typhoon; (3) the typhoon-induced cyclonic eddy was the most important physical process in increasing the surface Chl-a rather than the Ekman pumping and wind-stirring mixing after typhoon; (4) the spatial shift between the surface Chl-a blooms and the typhoon-induced cyclonic eddy could be due to the Ekman transport; (5) nutrients uplifting and adequate light were two major biochemical elements supplying for the growth of surface phytoplankton.

Spatio-temporal variability of surface chlorophyll-a in the Halmahera Sea and its relation to ENSO and the Indian Ocean Dipole

ABSTRACT Long-term satellite data are used to investigate the variability of ocean surface chlorophyll-a (chl-a) concentration in the Halmahera Sea (HS) under influence of the Australian-Indonesian Monsoon (AIM), the El Niño-Southern Oscillation (ENSO), and the Indian Ocean Dipole (IOD). In this study, we first analysed the seasonal variability of chl-a, and then examine the relationship between surface chl-a, sea surface temperature (SST), and sea surface wind stress in the area. Our results suggest that prevailing southeasterly winds play a fundamental role in generating chl-a blooms in the HS. Particularly on a seasonal timescale, through the mechanism of Ekman mass transport, strengthening of southeasterly wind stress during the Southeast Monsoon season (June – August) produces enhanced chl-a concentrations associated with ocean surface cooling in the area of study. On the other hand, the chl-a bloom completely diminishes during the Northwest Monsoon season (December – February) due to weakening of wind stress and Ekman transport. On an interannual timescale, sea level pressure and wind stress are coherent with ENSO and IOD phases. During El Niño and positive IOD events (La Niña and negative IOD events), both sea level pressure and wind stress greatly increase (decrease) over the HS. These conditions cause an anomaly in southerly (northerly) wind stress, which is favourable to an enhancement (reduction) of the chl-a concentration in the region. This study demonstrates that sea level pressure and wind stress are the critical factors in determining the magnitude of chl-a bloom in the HS.

Uncoupling of Seasonal Variations Between Phytoplankton Chlorophyll a and Production in the East China Sea

AbstractPhytoplankton chlorophyll a (Chla), primary production (PP), and nutrient uptake rates are fundamental and important parameters in marine biogeochemical studies. However, the relationships between them are associated with much uncertainty that reflects gaps in basic understanding of ecosystem dynamic. In this study, we simultaneously measured PP and nitrate assimilation (NA) along with estimated concentrations of nutrients, particulate organic carbon concentrations, phytoplankton Chla, pigments, and carbon biomass in the dynamic shelf ecosystems of the East China Sea (ECS) on four cruises during different seasons. There were large spatial gradients of these parameters, and seasonal patterns of phytoplankton Chla and PP varied between water masses. The results of this study and previous work indicated that seasonal variations of Chla and PP were similar in coastal waters but opposite in off‐shelf waters. During summer in off‐shelf waters, there were patches of high PP and NA associated with low Chla concentrations; this pattern was reversed in the winter. We suggest that there is a global tendency for PP and Chla patterns to be out of phase. This asynchrony is reflected mainly in the seasonal variations of C:Chla ratios driven by the combined influences of light, temperature, and nutrients. Stronger grazing pressure by microzooplankton in summer likely contributed to the high production but low biomass in the ECS. The significant correlation between PP and NA suggested that variations of PP in the ECS were driven largely by nitrate uptake, which may be inhibited by high ammonium concentrations in the Changjiang River plume.

Temporal and Vertical Relations between Various Environmental Factors in the Largest Lake of Łęczna-Włodawa Lake District (Eastern Poland)

Due to global warming and increasing water eutrophication, understanding in-lake relationships is paramount to prevent excessive pollution and further negative changes in lakes. The physico-chemical and biological parameters, as well as nutrient variabilities, both temporal and vertical (in the water column), were studied in the largest Łęczna-Włodawa lake. The study was conducted during two consecutive water years, from November 2015 to September 2017. The non-parametric Kruskal–Wallis ANOVA, test H was used to detect variability between years, and among seasons and lake depths in water temperature, electrical conductivity, pH, ORP, concentration of dissolved oxygen as well as concentration of NO3−, PO43−, TP and chlorophyll a. One-way analysis of variance (ANOVA) was used to detect any differences in Secchi depth (SD) and concentration of NH4+, NO2−, and TN. Ordination techniques: Detrended correspondence analysis (DCA), and Principal Components Analysis (PCA) were used to describe the relationships among 13 environmental variables and distribution of samples. Results showed significant differences (P < 0.05) between two years of the study for most variables except of water temperature, visibility, concentration of PO43−, TN and TP, which corresponded with highly different weather conditions in both years. All of the tested variables, except for nutrients, differed significantly among seasons. Most parameters showed fluctuation in depth, especially in summer and in winter, despite the fact that no hypolimnion or long-lasting thermocline was observed in the study period. However, variability of Chl-a was statistically significant only. The results emphasized complex and multi-directional relations between tested variables, dependent on both external (catchment) and internal (in-lake) processes.

Preliminary assessment of spatial and short-term variability of bio-optical properties in a tidal dominated estuary (Bahía Blanca, Argentina)

Estuarine environments are very complex systems whose productivity is defined by multiple biological and physicochemical interactions. Thus, monitoring the biophysical properties of estuarine waters becomes fundamental to our understanding of their ecosystem functions. Remote sensing retrieval of biochemical and biological variables appears as a complementary tool, providing information at a high spatial and temporal resolution and thus allowing us to study processes that cannot be comprehended based only on in situ data. However, the quality of remotely sensed data strongly depends on ground-truthing, using discrete in situ measurements. The aim of this study was to describe temporal (short term) and spatial (across short distances) variations of optically active water components in the Bahia Blanca Estuary (BBE, Argentina), and to characterize their relationship with bio-optical properties. Concentrations of suspended particulate matter (SPM) and chlorophyll-a (Chl-a), as well as the absorption by colored dissolved organic matter (acdom (443)), considered as a proxy for the concentration of colored dissolved organic matter, were tightly coupled to tidal forcing, causing significant short-term variations. Along the estuary, a steep gradient of these variables was observed with higher concentrations through the head of the channel. Considering bio-optical properties, absorption by non-algal particles (anap (443)) dominate the absorption budget of these optically complex waters, followed by absorption by phytoplankton (aph (443). aph (443) was closely related to variations in Chl-a, and anap (443) showed increased values under the influence of sewage discharge. Considering in situ measurements of water reflectance, a high short-term variability was observed in response to tidal forcing, as well as large differences across relatively short distances. For the first time in the BBE, bio-optical properties of seawater were quantified, and their variations described at different scales. These results revealed a highly variable environment from the optical perspective and have large implications for the validation of remote sensing products.

Evaluation of Weighting Average Functions as a Simplification of the Radiative Transfer Simulation in Vertically Inhomogeneous Eutrophic Waters

Current water color remote sensing algorithms typically do not consider the vertical variations of phytoplankton. Ecolight with a radiative transfer program was used to simulate the underwater light field of vertical inhomogeneous waters based on the optical properties of a eutrophic lake (i.e., Lake Chaohu, China). Results showed that the vertical distribution of chlorophyll-a (Chla(z)) can considerably affect spectrum shape and magnitude of apparent optical properties (AOPs), including subsurface remote sensing reflectance in water (rrs(λ, z)) and the diffuse attenuation coefficient (Kx(λ, z)). The vertical variations of Chla(z) changed the spectrum shapes of rrs(λ, z) at the green and red wavelengths with a maximum value at approximately 590 nm, and changed the Kx(λ, z) from blue to red wavelength range with no obvious spectral variation. The difference between rrs(λ, z) at depth z m and its asymptotic value (Δrrs(λ, z)) could reach to ~78% in highly stratified waters. Diffuse attenuation coefficient of downwelling plane irradiance (Kd(λ, z)) had larger vertical variations, especially near water surface, in highly stratified waters. Three weighting average functions performed well in less stratified waters, and the weighting average function proposed by Zaneveld et al., (2005) performed best in highly stratified waters. The total contribution of the first three layers to rrs(λ, 0−) was approximately 90%, but the contribution of each layer in the water column to rrs(λ, 0−) varied with wavelength, vertical distribution of Chla(z) profiles, concentration of suspended particulate inorganic matter (SPIM), and colored dissolved organic matter (CDOM). A simple stratified remote sensing reflectance model considering the vertical distribution of phytoplankton was built based on the contribution of each layer to rrs(λ, 0−).

Assessment of model-simulated upper ocean biogeochemical dynamics of the Bay of Bengal

The capability of a physical-biogeochemical model configured using Regional Ocean Modeling System (ROMS) in simulating upper ocean biogeochemical dynamics of the Bay of Bengal (BoB) is evaluated with available remote sensing and in situ observations. The accuracy of model-simulated and satellite (MODIS-Aqua) retrieved surface chlorophyll-a (chl-a) are individually assessed against in situ data, measured in surface waters of the western BoB, from March 2008 to November 2015. Model-simulated chl-a showed better correlation (R2 = 0.80) with the in situ observations as compared to that retrieved from satellite (R2 = 0.72). Although, the model underestimates chl-a (slope = 0.84), significant correlation proves its capability to reproduce the in situ trend. The root mean square error (RMSE) between model simulated and satellite retrieved chl-a against measured chl-a are 0.33 and 0.36, respectively. Additionally, a comparison with remote sensing time series data indicates that the model realistically simulates the seasonal variability of chl-a. Further, temperature, salinity, nitrate, chl-a and dissolved oxygen (DO) profiles obtained from two biogeochemical Argo floats deployed in the central BoB, are also compared with model-simulated profiles. In comparison, the model adequately simulates the observed subsurface variability of chl-a as well as persistent Deep Chlorophyll Maximum (DCM) at depths between 20 and 90 m having concentration 0.75–1.0 mg-m−3. The undulations in the subsurface spatial variability of chl-a are appreciably well captured by the model and comparable with the observations albeit the magnitude is overestimated in the model. It is noted that the temporal variability of the DCM and oxycline in the BoB is significantly influenced by the vertical movement of the thermocline.

Evaluating tropical phytoplankton phenology metrics using contemporary tools

The timing of phytoplankton growth (phenology) in tropical oceans is a crucial factor influencing the survival rates of higher trophic levels, food web structure and the functioning of coral reef ecosystems. Phytoplankton phenology is thus categorised as an ‘ecosystem indicator’, which can be utilised to assess ecosystem health in response to environmental and climatic perturbations. Ocean-colour remote sensing is currently the only technique providing global, long-term, synoptic estimates of phenology. However, due to limited available in situ datasets, studies dedicated to the validation of satellite-derived phenology metrics are sparse. The recent development of autonomous oceanographic observation platforms provides an opportunity to bridge this gap. Here, we use satellite-derived surface chlorophyll-a (Chl-a) observations, in conjunction with a Biogeochemical-Argo dataset, to assess the capability of remote sensing to estimate phytoplankton phenology metrics in the northern Red Sea – a typical tropical marine ecosystem. We find that phenology metrics derived from both contemporary platforms match with a high degree of precision (within the same 5-day period). The remotely-sensed surface signatures reflect the overall water column dynamics and successfully capture Chl-a variability related to convective mixing. Our findings offer important insights into the capability of remote sensing for monitoring food availability in tropical marine ecosystems, and support the use of satellite-derived phenology as an ecosystem indicator for marine management strategies in regions with limited data availability.

Investigation of physicochemical factors, chl-a and primary production in Mahshahr Creeks (Northwest Persian Gulf)

The study on physiochemical factors and primary production of the aquatic ecosystems is important to know the characteristic of environment and capacity of recharge. Mahshahr creeks are the most important creeks in Khuzestan, Iran. In this study, variations in physiochemical factors, chl-a and primary production in 3 regions (Mahshahr, Zangi, and Moussa entrance creeks) were evaluated in 2 months of every season of 2014 in different depths (1m and 8m). The following variable has been analyzed: nitrate, phosphate, nitrite, silicate, temperature, salinity, DO, pH, conductivity, turbidity, light, chl-a, primary production and phytoplankton abundance. The maximum amount of chl-a (1.6 mg m-3) was observed in the shallow region of Mahshahr creek in April while the minimum amount (0.08 mg m-3) was seen in the depth region of Zangi in July. The highest (1.59 gc m-2 day-1) and lowest (0.02gc m-2 day-1) amount of primary production were observed in the shallow region of Moussa entrance in April and the depth region of Zangi creek in Nov, respectively. The maximum abundance of shallow and depth phytoplankton was observed in April and the minimum was observed in July in all of the three creeks. The results of correlation test between the studied factors revealed that primary production has a significant relationship with nitrite, chl-a, phytoplankton abundance and light. Primary production in these creeks is relatively high in April, but in other months the production is low.

Adjusting Neural Network to a Particular Problem: Neural Network-Based Empirical Biological Model for Chlorophyll Concentration in the Upper Ocean

The versatility of the neural network (NN) technique allows it to be successfully applied in many fields of science and to a great variety of problems. For each problem or class of problems, a generic NN technique (e.g., multilayer perceptron (MLP)) usually requires some adjustments, which often are crucial for the development of a successful application. In this paper, we introduce a NN application that demonstrates the importance of such adjustments; moreover, in this case, the adjustments applied to a generic NN technique may be successfully used in many other NN applications. We introduce a NN technique, linking chlorophyll “a” (chl-a) variability—primarily driven by biological processes—with the physical processes of the upper ocean using a NN-based empirical biological model for chl-a. In this study, satellite-derived surface parameter fields, sea-surface temperature (SST) and sea-surface height (SSH), as well as gridded salinity and temperature profiles from 0 to 75m depth are employed as signatures of upper-ocean dynamics. Chlorophyll-a fields from NOAA’s operational Visible Imaging Infrared Radiometer Suite (VIIRS) are used, as well as Moderate Resolution Imaging Spectroradiometer (MODIS) and Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) chl-a concentrations. Different methods of optimizing the NN technique are investigated. Results are assessed using the root-mean-square error (RMSE) metric and cross-correlations between observed ocean color (OC) fields and NN output. To reduce the impact of noise in the data and to obtain a stable computation of the NN Jacobian, an ensemble of NN with different weights is constructed. This study demonstrates that the NN technique provides an accurate, computationally cheap method to generate long (up to 10 years) time series of consistent chl-a concentration that are in good agreement with chl-a data observed by different satellite sensors during the relevant period. The presented NN demonstrates a very good ability to generalize in terms of both space and time. Consequently, the NN-based empirical biological model for chl-a can be used in oceanic models, coupled climate prediction systems, and data assimilation systems to dynamically consider biological processes in the upper ocean.

Global patterns of change and variation in sea surface temperature and chlorophyll a

Changes over the scale of decades in oceanic environments present a range of challenges for management and utilisation of ocean resources. Here we investigate sources of global temporal variation in Sea Surface Temperature (SST) and Ocean Colour (Chl-a) and their co-variation, over a 14 year period using statistical methodologies that partition sources of variation into inter-annual and annual components and explicitly account for daily auto-correlation. The variation in SST shows bands of increasing variability with increasing latitude, while the analysis of annual variability in Chl-a shows mostly mid-latitude high variability bands. Covariation patterns of SST and Chl-a suggests several different mechanisms impacting Chl-a change and variance. Our high spatial resolution analysis indicates these are likely to be operating at relatively small spatial scales. There are large regions showing warming and rising of Chl-a, contrasting with regions that show warming and decreasing Chl-a. The covariation pattern in annual variation in SST and Chl-a reveals broad latitudinal bands. On smaller scales there are significant regional anomalies where upwellings are known to occur. Over decadal time scales both trend and variation in SST, Chl-a and their covariance is highly spatially heterogeneous, indicating that monitoring and resource management must be regionally appropriate.

Temporal Variation of Chlorophyll-a Concentrations in Highly Dynamic Waters from Unattended Sensors and Remote Sensing Observations.

Monitoring of water quality changes in highly dynamic inland lakes is frequently impeded by insufficient spatial and temporal coverage, for both field surveys and remote sensing methods. To track short-term variations of chlorophyll fluorescence and chlorophyll-a concentrations in Poyang Lake, the largest freshwater lake in China, high-frequency, in-situ, measurements were collected from two fixed stations. The K-mean clustering method was also applied to identify clusters with similar spatio-temporal variations, using remote sensing Chl-a data products from the MERIS satellite, taken from 2003 to 2012. Four lake area classes were obtained with distinct spatio-temporal patterns, two of which were selected for in situ measurement. Distinct daily periodic variations were observed, with peaks at approximately 3:00 PM and troughs at night or early morning. Short-term variations of chlorophyll fluorescence and Chl-a levels were revealed, with a maximum intra-diurnal ratio of 5.1 and inter-diurnal ratio of 7.4, respectively. Using geostatistical analysis, the temporal range of chlorophyll fluorescence and corresponding Chl-a variations was determined to be 9.6 h, which indicates that there is a temporal discrepancy between Chl-a variations and the sampling frequency of current satellite missions. An analysis of the optimal sampling strategies demonstrated that the influence of the sampling time on the mean Chl-a concentrations observed was higher than 25%, and the uncertainty of any single Terra/MODIS or Aqua/MODIS observation was approximately 15%. Therefore, sampling twice a day is essential to resolve Chl-a variations with a bias level of 10% or less. The results highlight short-term variations of critical water quality parameters in freshwater, and they help identify specific design requirements for geostationary earth observation missions, so that they can better address the challenges of monitoring complex coastal and inland environments around the world.

Remote sensing of water constituent concentrations using time series of in-situ hyperspectral measurements in the Wadden Sea

This study aimed to investigate the capability of the two-stream radiative transfer model 2SeaColor for the simultaneous retrieval of Chlorophyll-a (Chla), Suspended Particulate Matter (SPM) and Colored Dissolved Organic Matter (CDOM) concentrations from remote sensing measurements under various conditions (i.e., solar zenith angle values (SZAs) and water turbidity levels). For this evaluation, a time series of diurnal in-situ hyperspectral measurements of remote sensing reflectance (Rrs) concurrent with in-situ measured Chla and SPM concentrations between 2008 and 2010 by the NIOZ jetty station (the NJS), located in the Dutch part of the Wadden Sea, was used. Validation of the model retrievals against in-situ measurements showed an acceptable accuracy (Chla: R2 = 0.80 and RMSE = 2.98 [mg m−3]; SPM: R2 = 0.89 and RMSE = 2.53 [g m−3]) with good agreement between the temporal trends of measured and retrieved concentration values over multiple years. However, the model inversion results yielded less good estimates at SZA > 60° during winter. Furthermore, the effect of the tide on the variation of daily time series of Chla and SPM concentrations was analyzed. At the particular NJS location, the tidal effects on the concentrations of SPM and Chla were found to be small. The capability of the 2SeaColor model to retrieve reliable estimates, and the favorable location of the NJS, which is little influenced by tidal phase variations, contribute to a better understanding of the long-term variability of Chla and SPM concentrations. The results of this study may support the ongoing efforts on Sentinel-3 Ocean and Land Color Instrument (OLCI) calibration and validation at the Dutch Wadden Sea.