Satellite-derived Satellite-derived Sea Surface Temperature Research Articles

Modeling approaches in the investigation of upwelling along the east coast of Peninsular Malaysia: Its driven mechanisms

Numerous processes can cause upwelling, but the processes that cause upwelling along the east coast of Peninsular Malaysia (ECPM) are not well understood. Therefore, the dynamics of upwelling driving processes along the ECPM were investigated in this study. During the southwest monsoon, satellite-derived sea surface temperature (SST) and cruise surveys revealed the presence of upwelling signals, which were indicated by inshore cooler SST and onshore shoaling of the parameters isolines toward the coast and surface. In addition, the satellite-derived SST revealed a prominent feature of cooler water advection from the Java Sea. The Regional Ocean Modelling System (ROMS) was then used to simulate upwelling and the physical characteristics of adjacent waters. The simulation was generally agreed with the available datasets, showing the reliability of the simulated model. A series of simulation-based experiments were carried out to study the various contributions of physical processes to upwelling along the ECPM. The results revealed that wind-driven upwelling processes of Ekman transport were more essential in the generation of upwelling along the ECPM than wind stress curl. The elimination of tides from the model resulted in an intriguing feature in which the salinity along the ECPM decreased significantly, resulting in an increased in density (or salinity) gradient and the ensuing baroclinic pressure gradient force (PGF) in the upper inshore region, which significantly enhanced upwelling along the ECPM, and this is the new finding provided by this study. However, under the real oceanographic conditions, the effects of baroclinic PGF in causing upwelling was expected to be less substantial than the Ekman transport.

Assessment of Three-Dimensional Interpolation Method in Hydrologic Analysis in the East China Sea

The water mass in the East China Sea (ECS) shelf has a complicated three-dimensional (3D) hydrologic structure. However, previous studies mostly concentrated on the sea surface based on the sparse in situ and incomplete satellite-derived observations. Therefore, the 3D interpolation technology was introduced for the reconstruction of hydrologic structure in the ECS shelf using in situ temperature and salinity observations in the summer and autumn of 2010 to 2011. Considering the high accuracy and good fitness of the radial basis function (RBF) methods, we applied the RBF methods to the in situ observations to completely reconstruct the 3D hydrologic fields. Other 3D interpolation methods and 2D methods were also tested for a comparison. The cubic and thin plate spline RBFs were recommended because their mean absolute error (MAE) in the 10-fold cross-validation experiments maintained the order of ~10−2. The 3D RBF reconstructions showed a reasonable 3D hydrologic structure and extra details of the water masses in the ECS shelf. It also helps evaluate regional satellite-derived sea surface temperature (SST). Comparisons between the interpolated and satellite-derived SST indicates that the large bias of satellite-derived SST in the daytime corresponds to weak mixing during low-speed wind and shows seasonal variation.

Using Saildrones to Validate Satellite-Derived Sea Surface Salinity and Sea Surface Temperature along the California/Baja Coast

Traditional ways of validating satellite-derived sea surface temperature (SST) and sea surface salinity (SSS) products by comparing with buoy measurements, do not allow for evaluating the impact of mesoscale-to-submesoscale variability. We present the validation of remotely sensed SST and SSS data against the unmanned surface vehicle (USV)—called Saildrone—measurements from the 60 day 2018 Baja California campaign. More specifically, biases and root mean square differences (RMSDs) were calculated between USV-derived SST and SSS values, and six satellite-derived SST (MUR, OSTIA, CMC, K10, REMSS, and DMI) and three SSS (JPLSMAP, RSS40, RSS70) products. Biases between the USV SST and OSTIA/CMC/DMI were approximately zero, while MUR showed a bias of 0.3 °C. The OSTIA showed the smallest RMSD of 0.39 °C, while DMI had the largest RMSD of 0.5 °C. An RMSD of 0.4 °C between Saildrone SST and the satellite-derived products could be explained by the diurnal and sub-daily variability in USV SST, which currently cannot be resolved by remote sensing measurements. SSS showed fresh biases of 0.1 PSU for JPLSMAP and 0.2 PSU and 0.3 PSU for RMSS40 and RSS70 respectively. SST and SSS showed peaks in coherence at 100 km, most likely associated with the variability of the California Current System.

Evidence linking satellite-derived sea-surface temperature signals to changes in the Atlantic meridional overturning circulation

Abstract This study explores an application of satellite-derived Sea Surface Temperature (SST) to climate studies by focusing on a connection with the Atlantic Meridional Overturning Circulation (AMOC). Here we focus on SSTs from the advanced very high resolution radiometer and report a 99% significant correlation between the changes of in situ measured AMOC transport and the variation of 1-month leading SST anomalies in the subpolar North Atlantic region (45°N–70°N) based on analyses of an 85-month period. The leading mode of the singular value decomposition analysis of SST and Sea Level Pressure (SLP) for 31 years (1981/12–2012/12) shows an apparent North Atlantic Oscillation (NAO) forcing on the SST fields. Specifically, the SST and SLP one-month phase lag covariance is notable at temporal scales of 4 to 11 months. After removing the first order component of the NAO, the residual SST (RESST) provides better estimates of the AMOC on a shorter time scale than the SST. This is because that RESST is less likely to be affected by the local SLP on these time scales. The high correlation is primarily between the RESST and variations of the geostrophic Upper Mid-Ocean transport component of the AMOC. The 31-year RESST time series in the North Atlantic subpolar region is also significantly correlated with the Gulf Stream path SST anomalies with a one-month lead, implying a fast signal transport from the subpolar North Atlantic to the Gulf Stream. A similar fast adjustment signal is also found in 500-year control simulations of the GFDL model CM2.1. These results indicate a prospective capability of satellite-derived SSTs to predict AMOC variability.

A comparison of satellite-derived sea surface temperature fronts using two edge detection algorithms

Satellite-derived sea surface temperature (SST) fronts provide a valuable resource for the study of oceanic fronts. Two edge detection algorithms designed specifically to detect fronts in satellite-derived SST fields are compared: the histogram-based algorithm of Cayula and Cornillon (1992, 1995) and the entropy-based algorithm of Shimada et al. (2005). The algorithms were applied to 4 months (July and August for both 1995 and 1996) of SST fields and the results are compared with SST data taken by the M.V. Oleander, a container ship that makes weekly transits between New York and Bermuda. There is no significant difference in front pixels found with the Cayula-Cornillon algorithm and those found in the in situ (Oleander) data. Furthermore, for strong fronts, with gradients greater than 0.2K/km, the distribution of fronts found with the Shimada et al. algorithm is quite similar to that of fronts found with the Cayula-Cornillon algorithm. However, there are significant differences in the number of weak fronts found. This is seen clearly in waters south of the Gulf Stream where the gradient magnitude of fronts found is less than 0.1K/km. In this region, the probability that the Shimada et al. algorithm detects a front rarely falls below 4% while neither the Cayula-Cornillon algorithm applied to the satellite-derived SST fields nor the gradient-based algorithm applied to the Oleander temperature time series find fronts more than 1% of the time. These results raise the question of exactly what qualifies as an SST front, a classic problem in edge detection.

Reconstruction of Three-Dimensional Pacific Temperature with Argo and Satellite Observations

Combining Argo temperature and salinity profiles with satellite-derived sea surface temperature (SST), weekly three-dimensional temperature fields of the Pacific Ocean were reconstructed for the period January 2000 to December 2010. The data reconstruction methodology we used has three salient features: the first is a combined application of the Optimal Interpolation (OI) and the Multivariate Data Interpolating Empirical Orthogonal Function (MDINEOF) methods, the second is an emphasis on the multivariate nature of the vertical thermohaline structure, and the third is the inclusion of a continuous satellite-derived SST dataset to compensate for the discontinuities and the lack of surface observations in Argo data. Comparisons with other observations and data products indicate that our gridded temperature product is able to capture the main features of temperature distribution as well as its variability from intraseasonal to interannual time scales, thus providing a useful new dataset for ocean and climate studies. RÉSUMÉ [Traduit par la rédaction] En combinant les profils de température et de salinité Argo avec les températures de la surface de la mer dérivées des données satellitaires, nous avons reconstruit les champs tridimensionnels hebdomadaires de température de l'océan Pacifique pour la période de janvier 2000 à décembre 2010. La méthodologie de reconstruction des données que nous avons utilisée présente trois points saillants : le premier est une application combinée des méthodes de l'interpolation optimale et de la fonction orthogonale empirique d'interpolation de données multivariées (MDINEOF), le deuxième est une mise en évidence de la nature multivariée de la structure thermohaline verticale et le troisième est l'inclusion d'un ensemble continu de données de température de la surface de la mer dérivées des données satellitaires pour compenser les discontinuités et le manque d'observations de surface dans les données Argo. Les comparaisons avec d'autres observations et produits de données montrent que notre produit de températures à des points de grille est capable de discerner les caractéristiques principales de la distribution des températures de même que sa variabilité de l’échelle intrasaisonnière à l’échelle interannuelle, ce qui fournit un nouvel ensemble de données utile pour les études océaniques et climatiques.

The Kuroshio variations from satellite-derived sea surface temperature and Argos satellite-tracking Lagrangian drifters

This study aimed to identify the spatial and temporal variations of the Kuroshio using satellite-derived Sea Surface Temperature (SST) data and a total of 585 Argos satellite-tracking Lagrangian drifters during 1987–2006 in the northwestern Pacific Ocean. The threshold of high surface velocity, more than 75 cm s–1, was used to determine the location of the Kuroshio Current and found that its width ranged from 50 to 100 km. Moreover, this study first conducted a synoptic view for three predominant regions of the Kuroshio, including the area east of Taiwan, the area east of the East China Sea (ECS) and the area south of Japan. We found that the Kuroshio flows at a three-step increase in speed from upstream to downstream. The maximum mean surface velocity, 153 cm s–1, occurred to the south of Japan. Furthermore, the higher surface velocity of the Kuroshio was usually during the summertime (from April to September). In addition, the four-cruise CTD (Conductivity, Temperature, Depth)-transect data observed in January 2005 were collected to identify and validate the path of the Kuroshio axes. The results showed that the measure of 17.5°C at a depth of 200 m could be regarded as an indicator of the Kuroshio axis, corresponding with the maximum surface velocities of the Argos drifters. The monthly satellite-derived SST values of the Kuroshio were usually more than 10°C, so it was difficult to find a specific isotherm to express the location of the Kuroshio. However, extensive Kuroshio fronts derived from satellite SST data were found in this study. These Kuroshio fronts, associated with high SST gradients, were usually located on the boundary between the warm water of the Kuroshio and the colder water of the shelf, corresponding with the boundary of high surface velocity of the Argos drifters. Consequently, this study suggests that these Kuroshio fronts can be regarded as an effective indicator of the Kuroshio paths and its main axes.

Satellite-derived SST validation based on in-situ data during summer in the East China Sea and western North Pacific

Satellite-derived sea surface temperature (SST) is validated based on in-situ data from the East China Sea (ECS) and western North Pacific where most typhoons, which make landfall on the Korean peninsula, are formed and pass. While forecasting typhoons in terms of intensity and track, coupled ocean-typhoon models are significantly influenced by initial ocean condition. Potentially, satellite-derived SST is a very useful dataset to obtain initial ocean field because of its wide spatial coverage and high temporal resolution. In this study, satellite-derived SST from various sources such as Tropical Rainfall Measuring Mission Microwave Imager (TMI), Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and New Generation Sea Surface Temperature for Open Ocean (NGSST-O) datasets from merged SSTs were compared with in-situ observation data using an indirect method which is using near surface temperature for validation of satellite derived SST. In-situ observation data included shipboard measurements such as Expendable Bathythermograph (XBT), and Conductivity, Temperature, Depth (CTD), and Argo buoy data. This study shows that in-situ data can be used for microwave derived SST validation because homogeneous features of seawater prevail at water depths of 2 m to 10 m under favorable wind conditions during the summer season in the East China Sea. As a result of validation, root-mean-square errors (RMSEs) are shown to be 0.55 °C between microwave SST and XBT/CTD data mostly under weak wind conditions, and 0.7 °C between XBT/CTD measurement and NGSST-O data. Microwave SST RMSE of 0.55 °C is a potentially valuable data source for general application. Change of SST before and after typhoon passing may imply strength of ocean mixing due to upwelling and turbulent mixing driven by the typhoon. Based on SST change, ocean mixing, driven by Typhoon Nari, was examined. Satellite-derived SST reveals a significant SST drop around the track immediately following the passing of Typhoon Nari in October, 2007.

Shelf water entrainment by Gulf Stream warm-core rings between 75°W and 50°W during 1978–1999

Previous work concerning Gulf Stream warm-core rings (WCRs) and their associated shelf water entrainments have been based upon single surveys or time series from individual WCRs. To date, estimates of annual shelf water volume entrained into the Slope Sea by WCRs and its interannual variability have not been made. Using a long time series of satellite-derived sea surface temperature (SST) observations of Slope Sea WCRs, we have completed an analysis of 22 years of WCR data (1978–1999) between 75°W and 50°W to understand the interannual variability of WCRs and their role in entraining shelf water. Satellite-derived SST data digitized at Bedford Institute of Oceanography are analyzed using an ellipse-fitting feature model to determine key WCR characteristics including WCR center position, radius and orientation. Key characteristics are then used to compute WCR swirl velocity by finite-differencing WCR orientations ( θ) obtained from the feature model time series. Global mean WCR-edge swirl velocity calculated from all observations is 105.72±10.7 km day −1 (122.36±12.4 cm s −1), and global mean WCR radius is 64.8±6.2 km. Primary and derived WCR data are incorporated into a two-dimensional ring entrainment model (RM) using the quasi-geostrophic approximation of the potential vorticity equation. The RM defines ambient water as entrained by a WCR only if the gradient of relative vorticity term (horizontal shear) dominates the potential vorticity. Proximity of a WCR to the position of the shelf-slope front (SSF) is then used to determine whether the ambient water is entrained from the outer continental shelf. WCR-induced shelf entrainment derived from the RM displays considerable spatial variability, with maximum entrainment occurring offshore of Georges Bank, advecting a mean total annual shelf water volume of 7500 km 3 year −1 from the region. Estimates of shelf water fluxes display significant interannual variability, which may be in part due to the observed covariance between WCR occurrences and the state of the North Atlantic Oscillation (NAO). Increased (decreased) occurrences of WCRs are evidenced during positive (negative) phases of the NAO. The total mean annual shelf-wide WCR-induced shelf water transport is estimated to be 23,700 km 3 year −1 (0.75 Sv), accounting for nearly 25% of the total transport in the Slope Sea region neighboring the outer continental shelf.

On the heat budget of the Arabian Sea

This study analyzes the heat budget of the Arabian Sea using satellite-derived sea-surface temperature (SST) from 1985 to 1995 along with other data sets. For a better understanding of air–sea interaction, canonical average monthly fields representing the spatial and temporal structure of the various components of the heat balance of the Arabian Sea are constructed from up to 30 years of monthly atmospheric and oceanic data. The SST over the Arabian Sea is not uniform and continually evolves with time. Cooling occurs over most of the basin during November through January and May through July, with the greatest cooling in June and July. Warming occurs over most of the basin during the remainder of the year, with the greatest warming occurring in March and September. Results indicate that the sign of the net heat flux is strongly dependent on the location and month. The effects of net heat flux and penetrative solar radiation strongly influence the change in SST during February and are less important during August and September. Horizontal advection acts to cool the sea surface during the northeast monsoon months. During the southwest monsoon horizontal advection of surface waters warms the SST over approximately the southern half of the basin, while the advection of upwelled water from the Somalia and Oman coasts substantially cools the northern basin. The central Arabian Sea during the southwest monsoon is the only area where the change in SST is balanced by the entrainment and turbulent diffusion at the base of the mixed layer. Agreement between the temporal change in the satellite-derived SST and the change calculated from the conservation of heat equation is surprisingly good given the errors in the measured variables and the bulk formula parameters. Throughout the year, monthly results over half of the basin agree within 3°. Considering that the SST changes between 8° and 12° over the year, this means that our results explain from 62% to 75% of the change in SST over 56% of the Arabian Sea. Two major processes contribute to the discrepancy in the change in SST calculated according to the heat budget equation and the change in SST derived from satellite observations. The first is the effect of the horizontal advection term. The position of the major eddies and currents during the southwest monsoon greatly affects the change in SST due to the large gradient in temperature between the cold upwelled waters along the Somali coast to the warm waters in the interior of the basin. The second major process is the thermocline effect. In areas of shallow mixed-layer depth, high insolation and wind speeds of either less than 3 m/s or greater than 15 m/s, the bulk formulae parameterization of the surface heat fluxes is inappropriate.

A high-resolution satellite-derived sea surface temperature climatology for the western North Atlantic Ocean

Long-term and high-resolution (∼1.2 km) satellite-derived sea surface temperature (SST) fields of a monthly mean time series for the 1985–1999 period, and a daily climatology have been calculated for the North West Atlantic Ocean. The SST fields extend from 78°W to 41°W in longitude, and 30°N to 56°N in latitude, encompassing the region off Cape Hatteras, North Carolina, to the southern Labrador Sea. The monthly mean time series, consists of 180 cloud-masked monthly mean SST fields, derived from a full-resolution NOAA/NASA Pathfinder SST data set for the 1985–1999 period. The satellite-derived monthly mean SST fields, as compared with in situ monthly mean near-surface ocean temperatures from buoys located in the western North Atlantic, yield an overall RMS difference of 1.15 °C. The daily climatology, which consists of 365 fields, was derived by applying a least-squares harmonic regression technique on the monthly mean SST time series for the full study period. The monthly mean and daily climatological SST fields will be useful for studying inter-annual variability related to climate variability of SST over the study domain.

Detection method of the Kuroshio front using the satellite-derived chlorophyll-a images

Satellite-derived sea surface temperature (SST) has been providing high-resolution information of the oceanic front. However, in summer, increasing surface heating effects make SSTs uniform and the SST front disappears. The purpose of the present study is to examine applicability of satellite-derived surface chlorophyll-a (Chl-a) for detection of the Kuroshio front in the ocean south of Japan during the summer season. The Kuroshio surface front is formed between the Kuroshio water (KW) and the coastal water (CW) in the study area. Investigating accumulated in situ observations of SST and Chl-a, it is shown that the difference of Chl-a between KW and CW is increased in summer though that of SST becomes small. Using 76 pairs of cloud-free satellite-derived SST and Chl-a images with 0.01° spatial resolution, their seasonal variations are investigated through two-dimensional (2-D) histograms of Chl-a and SST. In summer, SST ranges from 25 to 30 °C and Chl-a ranges 0.03 to 0.4 mg/m 3. Two peaks in the summer 2-D histogram correspond to wider KW and CW areas with rather uniform Chl-a and SST distributions. The peak values are extracted from the 2-D histograms and used to determine a threshold value dividing the KW and CW surface Chl-a during summer. It is found that the Chl-a concentration of 0.17 mg/m 3 divides the extracted peaks into two groups, i.e., CW and KW except for a few peaks. The proposed Kuroshio-front detection method using the Chl-a images and the threshold value is examined using the satellite images and in situ data. The threshold contour superimposed in the summer Chl-a image distinctly separates the two representative waters in the ocean south of Japan. The front positions determined by the satellite-derived Chl-a, in situ SST, and in situ surface salinity transects along observation lines crossing the Kuroshio front agree with each other. Applying a traditional Kuroshio front index of temperature at 200 m depth, the capability of new Chl-a threshold in dividing two waters around the near-front area is quantitatively examined. Producing 74 match-ups of the satellite-derived Chl-a and 200-m temperature in the frontal zone, the dividing capability is evaluated quantitatively using the traditional Kuroshio-axis index. The detection capability of the proposed method is 82%, which can be considered high enough for practical applications.

Hydrographic and Satellite Observations of Summertime Upwelling in the Taiwan Strait: A Preliminary Description

Combination of the hydrographic and satellite-derived Sea Surface Temperature (SST) data provides Dew evidence for the existence of four Upwelling-related Low Temperature Zones (LTZs) in the Taiwan Strait in summer. These LTZs are located along the southwestern coast of the Taiwan Strait (SW-LTZ), along the northwestern coast of the Taiwan Strait (NW-LTZ), near the Taiwan Bank (TB-LTZ) and around the Penghu Islands (PH-LTZ), respectively. The hydrographic data from three August cruises during 1997-1999 show that these LTZs also possess relatively higher salinity (greater than 34) at the surface layer. Four years of higher resolution AVHRR satellite-derived SST data clearly indicate the summertime pattern of these upwelling-related LTZs and demonstrate their inter-annual and inter-monthly variability.

High-resolution satellite-derived sea-surface temperature variability over the Gulf of Maine and Georges Bank region, 1993–1996

Empirical orthogonal function (EOF) analyses were completed using 3 yr (fall 1993 through late-summer 1996) of 1.4-km resolution, satellite-derived sea-surface temperature (SST) imagery from a large domain that includes the Gulf of Maine, Georges Bank, southern New England and western Scotian shelves, and the adjacent slope water region located seaward of the 200-m isobath. Prior to analysis, raw satellite-derived SST images were carefully cloud masked using automated and manual cloud detection techniques and then interpolated to a 7-km resolution grid using optimal interpolation (OI). OI resulted in 218 cloud-free, five-day-averaged SST fields, produced at five-day intervals for the study period. After removal of the 3 yr temporal mean SST at each gridpoint, a covariance EOF analysis of OI SST shows three significant modes, accounting for a total of 96.5% of observed SST variance. A gradient EOF analysis also shows three significant modes, accounting for a total of 92.7% of observed SST variance after removal of the spatial mean SST from each OI SST field. Covariance EOF modes 1 and 3 represent 92.2 and 1.3% of observed SST variance, and depict rich spatial structure in the seasonal heating cycle and additional spatial variation in the seasonal heating cycle over the study domain, respectively. SST variability noted for covariance EOF mode 1 is largely related to local differences in the seasonal mixed-layer depth, with deeper mixed layers resulting from strong tidal mixing over offshore banks and shoals contrasting with more- shallow-mixed layers and seasonal density stratification caused by weaker tidal mixing over regions of greater bottom depth. Additional spatial differences in seasonal SST variability and noted in covariance EOF mode 3 are related to regional differences in seasonal thermohaline and density characteristics of surface waters across the Gulf of Maine. Regional surface water differences across the Gulf of Maine are caused by different phasing between annual cycles of vertical heat flux and inputs of low-salinity Scotian Shelf water in eastern Gulf of Maine during late winter and local freshwater runoff from rivers in western Gulf of Maine during late spring. Covariance EOF mode 2 represents 3.0% of observed SST variance and describes interannual SST variability manifested by a cooling trend within the slope water region caused by a decrease in Gulf Stream warm-core ring activity during the study period. The gradient EOF analysis shows results that support and supplement the covariance EOF analysis by depicting the year-round nature of the SST gradient associated with the shelf break front (mode 1, 86.4% of SST variance) and SST gradients arising from spatial variation in the seasonal heating cycle (modes 2 and 3, 4.3% and 2.0% of SST variance, respectively) and some degree of interannual variability as described for covariance EOF mode 2 (mode 3).