Remote Sensing Sea Surface Temperature Research Articles

Effect of topography on the cold water region in the east entrance area of Qiongzhou Strait

A cold water region will occur in the east entrance area of Qiongzhou Strait when upwelling develops off the northeast coast of Hainan Island. The effect of topography on this cold water region was investigated by combining satellite observations and numerical simulations. Multi-source high-resolution remote-sensed sea surface temperature images revealed that the western periphery of the cold water region frequently occurred at a quasi-fixed location with similar jagged structure. Compared with observations, the numerical model employed in this study could satisfactorily simulate the intense tidal currents in the strait, and reasonably reproduce the jagged western periphery of the cold water region. Under strong westward tidal flow, the cold upwelling water intruded deeply into the interior strait, whereas under sustained eastward tidal currents, much stronger tidal currents occurred where there were deeper waters connecting the inner strait, therefore the cold upwelling water faded towards east faster and formed the concave parts (looking in east-to-west direction) of the western periphery of the cold water region; conversely, convex parts would develop over the adjacent shallower shoals. The eastward movement of the cold water was dominated by topography-modified tidal currents, and only after sustained eastward tidal currents (usually in the second half or near the end of the eastward tidal current phase), the western periphery of the cold water region would occur at a quasi-fixed location with similar jagged shape. Moreover, the development of the upwelling off the northeast coast of Hainan Island, which was the precondition of the cold water region, was found to be mainly driven by sustained SE ~ S winds.

On the cross-shelf exchange driven by frontal eddies along a western boundary current during austral winter 2007

Western boundary currents are characterised by high mesoscale eddy activity including that of cyclonic frontal eddies (CFEs). These form frequently adjacent to the shelf-break, export coastal water and affect biological productivity. Here, we study the physical properties of eddies identified within the intensification zone of the East Australian Current (EAC) through the analysis of remotely sensed data, the application of an ocean circulation model and the evaluation of Lagrangian simulations during austral winter 2007. We examine the spatial and temporal evolution of identified eddies, investigate their formation mechanism, and quantify the contribution made to cross-shelf exchanges. The mesoscale eddies are tracked from generation to decay using an eddy detection and tracking method. In this case study, we identify two CFEs referred to as C1 and C2 with lifetimes of 11 and 38 days and radii of 45 and 70 km, respectively, and one anticyclonic eddy (ACE) with a lifetime of 62 days and a radius of 60 km. Both CFEs interact with the ACE leading to quasi-stationary dipole-eddies located in the vicinity of the shelf. This is the first time dipole-eddies are reported for the intensification zone of the EAC. The location of CFEs characterised by negative sea surface height anomaly (SSHA) and clockwise rotation coincides with remotely-sensed sea surface temperature (SST) and chlorophyll-a (Chl-a) anomalies. CFEs C1 and C2 appear to contribute in different ways to the cross-shelf transport along the shelf-break. CFE C1 drives a stronger onshore transport, while CFE C2 appears to enhance the offshore transport. The estimated export of shelf water associated with CFE C2 is estimated with about 1.23 Sv (~106 km3 day−1). It renews the regional shelf water in about 7 days. The lifetime of CFE C2 is about 38 days, thus the eddy had the potential to flush the shelf at least five times. The CFEs intensify the cross-shelf exchange that is due to the wind-driven cyclonic circulation of the Fraser Gyre. This seasonally occurring gyre dominates the local shelf during austral autumn and winter. The results from this study demonstrate the importance of CFEs in exporting cooler and Chl-a enriched shelf water into the warmer and oligotrophic waters of the southward-flowing EAC.

SST Anomalies in the Mozambique Channel Using Remote Sensing and Numerical Modeling Data

Based on both satellite remote sensing sea surface temperature (SST) data and numerical model results, SST warming differences in the Mozambique Channel (MC) west of the Madagascar Island (MI) were found with respect to the SST east of the MI along the same latitude. The mean SST west of the MI is up to about 3.0 °C warmer than that east of the MI. The SST differences exist all year round and the maximum value appears in October. The area of the highest SST is located in the northern part of the MC. Potential factors causing the SST anomalies could be sea surface wind, heat flux and oceanic flow advection. The presence of the MI results in weakening wind in the MC and in turn causes weakening of the mixing in the upper oceans, thus the surface mixed layer depth becomes shallower. There is more precipitation on the east of the MI than that inside the MC because of the orographic effects. Different precipitation patterns and types of clouds result in different solar radiant heat fluxes across both sides of the MI. Warm water advected from the equatorial area also contribute to the SST warm anomalies.

4DVAR Data Assimilation with the Regional Ocean Modeling System (ROMS): Impact on the Water Mass Distributions in the Yellow Sea

In this study, we evaluate the performance of the recently developed incremental strong constraint 4-dimensional variational (4DVAR) data assimilation applied to the Yellow Sea (YS) using the Regional Ocean Modeling System (ROMS). Two assimilation experiments are compared: assimilating remote-sensed sea surface temperature (SST) and both the SST and in-situ profiles measured by shipboard CTD casts into a regional ocean modeling from January to December of 2011. By comparing the two assimilation experiments against a free-run without data assimilation, we investigate how the assimilation affects the hydrographic structures in the YS. Results indicate that the SST assimilation notably improves the model behavior at the surface when compared to the non-assimilative free-run. The SST assimilation also has an impact on the subsurface water structure in the eastern YS; however, the improvement is seasonally dependent, that is, the correction becomes more effective in winter than in summer. This is due to a strong stratification in summer that prevents the assimilation of SST from affecting the subsurface temperature. A significant improvement to the subsurface temperature is made when the in-situ profiles of temperature and salinity are assimilated, forming a tongue-shaped YS bottom cold water from the YS toward the southwestern seas of Jeju Island.

Comparison of Remotely-Sensed Sea Surface Temperature and Salinity Products With in Situ Measurements From British Columbia, Canada

Sea surface temperature (SST) and salinity (SSS) are essential variables at the ocean and atmosphere interface when considering risk factors for disease in farmed and wild fish stocks. Ecological research has witnessed a recent trend in use of digital and satellite technologies, including remote-sensing tools. We explored spatial coverage of remotely-sensed SST and SSS data and compared them with in situ measurements of water temperatures and salinity, which led to suggested adjustments to the remotely-sensed data for its use in aquaculture research. The in situ data were from farms and wild surveillance sites in coastal British Columbia, Canada, from 2003 to 2016. Concurrent SST and SSS values were extracted from remotely-sensed products and compared with 20,513 and 20,038 in situ records for water temperature and salinity, respectively, from 232 different sites. Among nine SST products evaluated, the UKMO OSTIA SST (UK Meteorological Office) had the highest retrieval, and highest concordance correlation coefficient (0.86), highest index of agreement (0.93), fewest missing values, and smallest mean and SD values for bias, when compared to in situ measurements. A mixed linear regression model with UKMO OSTIA SST as the predictor for in situ measurements estimated an adjustment coefficient of 0.89 °C for UKMO OSTIA SST. None of the three SSS products evaluated provided appropriate corresponding values for in situ sites, suggesting that spatial coverage for the study area is currently lacking. This study demonstrates that, among SST products, UKMO OSTIA SST is currently best suited for aquaculture studies in coastal BC. The near real-time availability of these data with the estimated adjustment would allow their use in forecast models, surveillance of pathogens, and the creation of risk maps.

Seasonal phytoplankton blooms in the Gulf of Aden revealed by remote sensing

The Gulf of Aden, situated in the northwest Arabian Sea and linked to the Red Sea, is a relatively unexplored ecosystem. Understanding of large-scale biological dynamics is limited by the lack of adequate datasets. In this study, we analyse 15years of remotely-sensed chlorophyll-a data (Chl-a, an index of phytoplankton biomass) acquired from the Ocean Colour Climate Change Initiative (OC-CCI) of the European Space Agency (ESA). The improved spatial coverage of OC-CCI data in the Gulf of Aden allows, for the first time, an investigation into the full seasonal succession of phytoplankton biomass. Analysis of indices of phytoplankton phenology (bloom timing) reveals distinct phytoplankton growth periods in different parts of the gulf: a large peak during August (mid-summer) in the western part of the gulf, and a smaller peak during November (mid-autumn) in the lower central gulf and along the southern coastline. The summer bloom develops rapidly at the beginning of July, and its peak is approximately three times higher than that of the autumnal bloom. Remotely-sensed sea-surface temperature (SST), wind-stress curl, vertical nutrient profiles and geostrophic currents inferred from the sea-level anomaly, were analysed to examine the underlying physical mechanisms that control phytoplankton growth. During summer, the prevailing southwesterlies cause upwelling along the northern coastline of the gulf (Yemen), leading to an increase in nutrient availability and enhancing phytoplankton growth along the coastline and in the western part of the gulf. In contrast, in the central region of the gulf, lowest concentrations of Chl-a are observed during summer, due to strong downwelling caused by a mesoscale anticyclonic eddy. During autumn, the prevailing northeasterlies enable upwelling along the southern coastline (Somalia) causing local nutrient enrichment in the euphotic zone, leading to higher levels of phytoplankton biomass along the coastline and in the lower central gulf. The monsoon wind reversal is shown to play a key role in controlling phytoplankton growth in different regions of the Gulf of Aden.

A comparison of remote-sensing SST and in situ seawater temperature in near-shore habitats in the western Mediterranean Sea

Remote sensing of sea surface temperature (SST) is widely used in climate science because it provides a quasi-synoptic coverage of the ocean. However, the use of these data for near-shore habitats is hindered by the proximity of the coast, therefore further investigation is needed. We compared remote-sensing SST from the MODIS sensor (aboard the Aqua satellite) to near-shore seawater temperature (ST) recorded in situ with data loggers at 5 locations in the western Mediterranean Sea. In situ ST data were collected at 5 m depth over a ~6 yr period and at depths below 5 m at 3 of the locations. We evaluated the suitability of MODIS to represent the temperature at shallow subtidal depths relative to different modes of variability. MODIS reproduced seasonal variability with high correlations (r > 0.98) and biases (0.59 ± 0.03°C) only slightly higher than the accuracy of the loggers (0.50°C). MODIS also captured interannual variability with no systematic biases. When evaluated for intra-seasonal temperature variability, MODIS showed limited biases (up to 0.79°C) with a tendency to overestimate the variability (between 4 and 64%) in both cold and warm seasons. Finally, MODIS over-/underestimated only the most extreme unseasonably cold/warm events (by 1.51 and -0.79°C, respectively). The observed limited differences between the 2 methods can be explained by the particular hydrodynamics of the area and by methodological constraints. Overall, MODIS SST data proved to be a reliable proxy for near-shore ST in the western Mediterranean Sea, and are thus considered suitable for studies requiring temperature reconstruction in shallow near-shore environments.

Modelling the shelf circulation off eastern Tasmania

The marine waters across Tasmanian's eastern continental shelf are biologically productive and home to economically important fisheries and aquaculture industries. However, the marine climate there is poorly understood. We use a high-resolution (∼2km in the horizontal), three-dimensional ocean model for eastern Tasmania (ETAS) to examine the simulated mean state and seasonal cycle of temperature, salinity and three-dimensional flow field, and the evaluation of daily model outputs against in situ and remote observations for the 1993–2014 period. We also use the model to examine the roles of river input and tidal forcing. The model is evaluated against remotely-sensed sea surface temperature and in-situ observations of sea level and subsurface temperature, salinity, and currents. The mean state demonstrates the influence of two well-known boundary currents (the East Australian Current, EAC, and the Zeehan Current, ZC) as well as the effects of local freshwater input from river runoff. The EAC is dominant in summer and the ZC in winter; the influence of the EAC also increases northwards and in the offshore direction. In addition, the model indicates the presence of a semi-permanent subsurface (50–100m depth) northward flow trapped near the coast. Cool freshwater runoff from the Derwent and Huon Rivers directly impacts the temperature and salinity in their estuaries but has little influence further across the shelf. Tidal forcing impacts the mean state through tide-river interactions which flush Frederick Henry Bay and Norfolk Bay with freshwater. Tidal forcing also impacts the variability of temperature all along the coastline, most likely due to changes in the turbulent mixing near to the coast. The ETAS model output data are available as a high-resolution representation of the mean state, seasonal variations, and interannual variability of Tasmania's eastern continental shelf marine climate.

ROMS-NPZD 접합모델을 이용한 한반도 주변해역의 표층 영양염 및 클로로필의 계절변동성

Recently, there has been a growing interest in physical-biological ocean-modeling systems by communities in the fields of science and business. In this paper, we present preliminary results from a coupled physical-biological model for the Northwestern Pacific marginal seas. The ocean circulation component is an implementation of the Regional Ocean Modeling System (ROMS), and the lower trophic level ecosystem component is a Nutrient-Phytoplankton-Zooplankton-Detritus (NPZD) model. The ROMSNPZD coupled system, with a 25 km resolution, is forced by climatological atmospheric data and predicts the physical variables and concentrations of nitrate, phytoplankton, zooplankton, and detritus. Model results are compared with remote-sensed sea surface temperature and chlorophyll, and with climatological sea surface salinity and nitrate. Our model adequately reproduces the observed spatial distribution and seasonal variability of nitrate and chlorophyll concentrations as well as physical variables, showing a high correlation in the East Sea (ES) and Kuroshio/Oyashio Extension (KOE) region but relatively low correlation in the Yellow Sea (YS) and East China Sea (ECS). Although some deficiencies were found in the biological components, such as the over/underestimation of the intensity of phytoplankton blooms in the ES and KOE/ the YS and ECS, our system demonstrates the capability of the model to capture and record dominant seasonal variability in physical-biological processes and this holds out the promise of coming to a better understanding of such processes and making better predictions .

Verification of an operational ocean circulation-surface wave coupled forecasting system for the China’s seas

An operational ocean circulation-surface wave coupled forecasting system for the seas off China and adjacent areas (OCFS-C) is developed based on parallelized circulation and wave models. It has been in operation since November 1, 2007. In this paper we comprehensively present the simulation and verification of the system, whose distinguishing feature is that the wave-induced mixing is coupled in the circulation model. In particular, with nested technique the resolution in the China’s seas has been updated to (1/24)° from the global model with (1/2)° resolution. Besides, daily remote sensing sea surface temperature (SST) data have been assimilated into the model to generate a hot restart field for OCFS-C. Moreover, inter-comparisons between forecasting and independent observational data are performed to evaluate the effectiveness of OCFS-C in upper-ocean quantities predictions, including SST, mixed layer depth (MLD) and subsurface temperature. Except in conventional statistical metrics, non-dimensional skill scores (SS) is also used to evaluate forecast skill. Observations from buoys and Argo profiles are used for lead time and real time validations, which give a large SS value (more than 0.90). Besides, prediction skill for the seasonal variation of SST is confirmed. Comparisons of subsurface temperatures with Argo profiles data indicate that OCFS-C has low skill in predicting subsurface temperatures between 100 m and 150 m. Nevertheless, inter-comparisons of MLD reveal that the MLD from model is shallower than that from Argo profiles by about 12 m, i.e., OCFS-C is successful and steady in MLD predictions. Validation of 1-d, 2-d and 3-d forecasting SST shows that our operational ocean circulation-surface wave coupled forecasting model has reasonable accuracy in the upper ocean.

Sea ice cover in Isfjorden and Hornsund, Svalbard (2000–2014) from remote sensing data

Abstract. A satellite database including 16 555 satellite images and ice charts displaying the area of Isfjorden, Hornsund, and the Svalbard region has been established with focus on the time period 2000–2014. 3319 manual interpretations of sea ice conditions have been conducted, resulting in two time series dividing the area of Isfjorden and Hornsund into "fast ice" (sea ice attached to the coastline), "drift ice", and "open water". The maximum fast ice coverage of Isfjorden is > 40 % in the periods 2000–2005 and 2009–2011 and stays < 30 % in 2006–2008 and 2012–2014. Fast ice cover in Hornsund reaches > 40 % in all considered years, except for 2012 and 2014, where the maximum stays < 20 %. The mean seasonal cycles of fast ice in Isfjorden and Hornsund show monthly averaged values of less than 1 % between July and November and maxima in March (Isfjorden, 35.7 %) and April (Hornsund, 42.1 %), respectively. A significant reduction of the monthly averaged fast ice coverage is found when comparing the time periods 2000–2005 and 2006–2014. The seasonal maximum decreases from 57.5 to 23.2 % in Isfjorden and from 52.6 to 35.2 % in Hornsund. A new index, called "days of fast ice" (DFI), is introduced for quantification of the interannual variation of fast ice cover, allowing for comparison between different fjords and winter seasons. Considering the time period from 1 March until end of the sea ice season, the mean DFI values for 2000–2014 are 33.1 ± 18.2 DFI (Isfjorden) and 42.9 ± 18.2 DFI (Hornsund). A distinct shift to lower DFI values is observed in 2006. Calculating a mean before and after 2006 yields a decrease from 50 to 22 DFI for Isfjorden and from 56 to 34 DFI for Hornsund. Fast ice coverage generally correlates well with remote-sensing sea surface temperature and in situ air temperature. An increase of autumn ocean heat content is observed during the last few years when the DFI values decrease. The presented sea ice time series can be utilized for various climate effect studies linked to, e.g. glacier dynamics, ocean chemistry, and marine biology.

Suitability of remotely-sensed sea surface temperature for aquaculture research: comparison with in situ records from salmon farms in British Columbia (BC), Canada

Suitability of remotely-sensed sea surface temperature for aquaculture research: comparison with in situ records from salmon farms in British Columbia (BC), Canada

An ocean data assimilation system in the Indian Ocean and west Pacific Ocean

The development and application of a regional ocean data assimilation system are among the aims of the Global Ocean Data Assimilation Experiment. The ocean data assimilation system in the regions including the Indian and West Pacific oceans is an endeavor motivated by this goal. In this study, we describe the system in detail. Moreover, the reanalysis in the joint area of Asia, the Indian Ocean, and the western Pacific Ocean (hereafter AIPOcean) constructed using multi-year model integration with data assimilation is used to test the performance of this system. The ocean model is an eddy-resolving, hybrid coordinate ocean model. Various types of observations including in-situ temperature and salinity profiles (mechanical bathythermograph, expendable bathythermograph, Array for Real-time Geostrophic Oceanography, Tropical Atmosphere Ocean Array, conductivity–temperature–depth, station data), remotely-sensed sea surface temperature, and altimetry sea level anomalies, are assimilated into the reanalysis via the ensemble optimal interpolation method. An ensemble of model states sampled from a long-term integration is allowed to change with season, rather than remaining stationary. The estimated background error covariance matrix may reasonably reflect the seasonality and anisotropy. We evaluate the performance of AIPOcean during the period 1993–2006 by comparisons with independent observations, and some reanalysis products. We show that AIPOcean reduces the errors of subsurface temperature and salinity, and reproduces mesoscale eddies. In contrast to ECCO and SODA products, AIPOcean captures the interannual variability and linear trend of sea level anomalies very well. AIPOcean also shows a good consistency with tide gauges.

Assessment of Long Term Thermal Stress on Egyptian Coral Reefs Based on Remotely Sensed Sea Surface Temperature Data

Assessment of Long Term Thermal Stress on Egyptian Coral Reefs Based on Remotely Sensed Sea Surface Temperature Data

Influence of climate on Pelorus Sound mussel aquaculture yields: predictive models and underlying mechanisms

Multiple regression models were used to predict aquaculture production in Pelorus Sound, a 50 km long estuary supporting 68% of New Zealand's greenshell mussel Perna canali - culus aquaculture industry (worth NZ$ 204 million per annum). Mussel meat yield was modelled using both biological predictors, including seston (indexed by particulate nitrogen, PN), phyto- plankton and nutrients collected over 9 yr (July 1997 to November 2005) by the mussel industry, and physical, climatic predictors, including Southern Oscillation Index (SOI), along-shelf winds, sea surface temperature (SST) and Pelorus River flow, held in New Zealand national databases. Yield was best predicted using biological predictors collected locally at the farms inside the sound, but it was also predictable using only physical predictors collected distant from the farming region. Seston (mussel food) was also predictable using the physical predictors. Optimal predictor sets for yield and seston differed between summer and winter half-years. In summer, deep water (which enters the sound through the estuarine circulation) at the sound entrance was nitrate (NO3 � )-rich during upwelling conditions (negative SOI, NNW wind stress and cool SST). The increased NO3 � levels, in turn, triggered increased PN within the sound. In the winter half-year, PN was unrelated to upwelling and NO3 � effects at the entrance and was instead related to river flow. Remotely-sensed SST data showed that in summer, upwelling affected the entrance waters of the sound under negative SOI and upwelling-favourable wind stress, patterns which dissipated in winter. Overall, these results show that time series of physical drivers can be useful for explain- ing production variation of farmed bivalves and indicate the prospects for using data routinely col- lected in national databases for predicting mussel yield.

Remote Sensing the Phytoplankton Seasonal Succession of the Red Sea

The Red Sea holds one of the most diverse marine ecosystems, primarily due to coral reefs. However, knowledge on large-scale phytoplankton dynamics is limited. Analysis of a 10-year high resolution Chlorophyll-a (Chl-a) dataset, along with remotely-sensed sea surface temperature and wind, provided a detailed description of the spatiotemporal seasonal succession of phytoplankton biomass in the Red Sea. Based on MODIS (Moderate-resolution Imaging Spectroradiometer) data, four distinct Red Sea provinces and seasons are suggested, covering the major patterns of surface phytoplankton production. The Red Sea Chl-a depicts a distinct seasonality with maximum concentrations seen during the winter time (attributed to vertical mixing in the north and wind-induced horizontal intrusion of nutrient-rich water in the south), and minimum concentrations during the summer (associated with strong seasonal stratification). The initiation of the seasonal succession occurs in autumn and lasts until early spring. However, weekly Chl-a seasonal succession data revealed that during the month of June, consistent anti-cyclonic eddies transfer nutrients and/or Chl-a to the open waters of the central Red Sea. This phenomenon occurs during the stratified nutrient depleted season, and thus could provide an important source of nutrients to the open waters. Remotely-sensed synoptic observations highlight that Chl-a does not increase regularly from north to south as previously thought. The Northern part of the Central Red Sea province appears to be the most oligotrophic area (opposed to southern and northern domains). This is likely due to the absence of strong mixing, which is apparent at the northern end of the Red Sea, and low nutrient intrusion in comparison with the southern end. Although the Red Sea is considered an oligotrophic sea, sporadic blooms occur that reach mesotrophic levels. The water temperature and the prevailing winds control the nutrient concentrations within the euphotic zone and enable the horizontal transportation of nutrients.

Time Series Analysis of Cholera in Matlab, Bangladesh, during 1988-2001

The study examined the impact of in-situ climatic and marine environmental variability on cholera incidence in an endemic area of Bangladesh and developed a forecasting model for understanding the magnitude of incidence. Diarrhoea surveillance data collected between 1988 and 2001 were obtained from a field research site in Matlab, Bangladesh. Cholera cases were defined as Vibrio cholerae O1 isolated from faecal specimens of patients who sought care at treatment centres serving the Matlab population. Cholera incidence for 168 months was correlated with remotely-sensed sea-surface temperature (SST) and in-situ environmental data, including rainfall and ambient temperature. A seasonal autoregressive integrated moving average (SARIMA) model was used for determining the impact of climatic and environmental variability on cholera incidence and evaluating the ability of the model to forecast the magnitude of cholera. There were 4,157 cholera cases during the study period, with an average of 1.4 cases per 1,000 people. Since monthly cholera cases varied significantly by month, it was necessary to stabilize the variance of cholera incidence by computing the natural logarithm to conduct the analysis. The SARIMA model shows temporal clustering of cholera at one- and 12-month lags. There was a 6% increase in cholera incidence with a minimum temperature increase of one degree celsius in the current month. For increase of SST by one degree celsius, there was a 25% increase in the cholera incidence at currrent month and 18% increase in the cholera incidence at two months. Rainfall did not influenc to cause variation in cholera incidence during the study period. The model forecast the fluctuation of cholera incidence in Matlab reasonably well (Root mean square error, RMSE: 0.108). Thus, the ambient and sea-surface temperature-based model could be used in forecasting cholera outbreaks in Matlab.

High and Ultra-High resolution processing of satellite Sea Surface Temperature data over Southern European Seas in the framework of MyOcean project

In the framework of the GMES (Global Monitoring for Environment and Security) MyOcean projects, funded by the European Commission, different remotely-sensed Sea Surface Temperature (SST) supercollated (L3S) and interpolated (L4) data are produced and distributed in near-real time by the Consiglio Nazionale delle Ricerche – Istituto di Scienze dell'Atmosfera e del Clima – Gruppo di Oceanografia da Satellite (CNR). These SST products are based on the night-time images collected by the infrared sensors mounted on different satellite platforms and cover the whole Southern European Seas (i.e. the Mediterranean Sea, including the eastern Atlantic Ocean, and the Black Sea). The CNR processing chains include several modules, from the data extraction and preliminary quality control, to cloudy pixel removal and satellite images collating/merging up to L3S. A two-step algorithm finally allows to interpolate SST data at High (HR 1/16°) and Ultra-High (UHR 1/100°) spatial resolution. The basic design and the main algorithms used in MyOcean processing chains are described hereafter. A validation of the HR super-collating procedure developed during MyOcean is presented. The Mediterranean HR and UHR L3S and L4 operational products have then been validated vs in situ SST measurements from drifting buoys, covering two years of data (2010–2011). The validation includes a comparison between the UHR CNR L4 and the G1SST L4 developed by Chao et al. (2009).

Assessment of remotely-sensed sea-surface temperature and chlorophyll-a concentration in San Matías Gulf (Patagonia, Argentina)

Field measurements of surface temperature and chlorophyll-a concentration were used to evaluate for the first time the performance of the standard sea surface temperature and chlorophyll-a algorithms of the Moderate Resolution Imaging Spectroradiometer (MODIS) in San Matías Gulf, northern of the Argentine Patagonian Continental Shelf (between 40°47′S and 42°13′S). The fit of the temperature data to a Standard Major Axis (SMA) type II regression model indicated that a high proportion of the total variance (r2≥0.80) was explained by the model. For chlorophyll-a, the low correlation (r2=0.15) and high dispersion indicated a poor performance and a general overestimation of Chl-a by the OC3Mv5 algorithm as indicated by the Relative Percent Difference (RPD=113%). However, for stations located in the northern area of the gulf the result showed a higher correlation (r2=0.76) and less dispersion (RPD=31%). The feasible reasons and explanations for the performance of NLSST and OC3Mv5 algorithms are discussed. The results of the temporal variability analysis of SST and Chl-a in different areas of the gulf agreed with previous studies.

Declines in phytoplankton cell size in the subtropical oceans estimated from satellite remotely-sensed temperature and chlorophyll, 1998–2007

Satellite remotely-sensed sea surface temperature (SST) and surface chlorophyll were used to estimate median phytoplankton cell size at monthly and 11km2 resolution over the global ocean, 1998–2007. The temporal dynamics of median phytoplankton cell size were examined for the Pacific equatorial upwelling region and the subtropical oceans. For the equatorial upwelling region, cell size varied coherently with the El Niño Southern Oscillation with smaller (larger) median cell size during El Niños (La Niñas). Specifically, estimated median cell diameter increased by 34% between the 1998 El Nino and the 1999–2001 La Nina. In the subtropical oceans, over the period 1998–2007, median cell diameter exhibited statistically significant linear declines of about 2% in the North and South Pacific, and 4% in the North Atlantic. Pooling the data over all subtropical oceans, over the period 1998–2007, global median cell diameter declined by about 2%.These results suggest that phytoplankton cell size may vary on interannual and decadal scales resulting in changes in food chain length and hence energy transfer to higher trophic levels. Further, a shift to smaller sized phytoplankton has been hypothesized as a response to ocean warming. Thus, this approach, estimating phytoplankton cell size from remotely-sensed temperature and chlorophyll, has the potential to provide global monitoring of an aspect of phytoplankton community structure likely to be responsive to future climate change.