Sea Surface Temperature Analysis Research Articles

A new global daily sea‐surface temperature analysis system at Environment and Climate Change Canada

AbstractA new global daily sea‐surface temperature (SST) analysis system has been developed at Environment and Climate Change Canada (ECCC). All components of the new SST analysis system are implemented within the Modular and Integrated Data Assimilation System (MIDAS) software. MIDAS is already used for the data assimilation component of the main operational numerical weather prediction (NWP) systems at ECCC. The new SST analysis system, integrated together with the global sea‐ice analysis, will be part of the combined ocean surface analysis used for all operational prediction systems at ECCC. The data assimilation method used to compute the new SST analyses is two‐dimensional variational method with a diffusion operator for representing the horizontal background‐error correlations. A new algorithm for satellite data bias estimation has also been developed employing gridded bias estimates computed from a spatial averaging of the differences between collocated satellite and in‐situ data. New algorithms for quality control and thinning of satellite data have also been implemented, making each type of observational dataset more evenly distributed over the globe. The performance of the new SST system is examined relative to the current operational SST system by using independent data. The impact of using the new SST analysis within NWP and ocean prediction systems is also evaluated. When compared with the operational system currently in use, the experiments employing the new SST analysis system produce a nearly neutral impact on the NWP and ocean prediction systems. This validation of the new system is an important first step towards the ability to use MIDAS to perform ensemble‐based three‐dimensional ocean and coupled ocean‐ice–atmosphere data assimilation.

Satellite-based time-series of sea-surface temperature since 1980 for climate applications

A 42-year climate data record of global sea surface temperature (SST) covering 1980 to 2021 has been produced from satellite observations, with a high degree of independence from in situ measurements. Observations from twenty infrared and two microwave radiometers are used, and are adjusted for their differing times of day of measurement to avoid aliasing and ensure observational stability. A total of 1.5 × 1013 locations are processed, yielding 1.4 × 1012 SST observations deemed to be suitable for climate applications. The corresponding observation density varies from less than 1 km−2 yr−1 in 1980 to over 100 km−2 yr−1 after 2007. Data are provided at their native resolution, averaged on a global 0.05° latitude-longitude grid (single-sensor with gaps), and as a daily, merged, gap-free, SST analysis at 0.05°. The data include the satellite-based SSTs, the corresponding time-and-depth standardised estimates, their standard uncertainty and quality flags. Accuracy, spatial coverage and length of record are all improved relative to a previous version, and the timeseries is routinely extended in time using consistent methods.

Global Sea Surface Temperature Analysis Based on Domestic Ocean Satellite Data. Part II: Comparative Analysis of Multiple Sets of Global Sea Surface Temperature Products in 2022

With more and more global gap-free fusion products of the sea surface temperature, understanding the consistency and discrepancy of the different SST fusion products will not only help data providers to improve their algorithms, but also help them to select the one that may better suit their applications. In this article, we have compared and analysed 10 sets of global gap-free fusion products of sea surface temperature in 2022, with different fusion techniques and related configurations. It is found that each SST analysis product has the same spatial distribution, with the minimum NMEFC mean value (20.11) and the maximum MGDSST mean value (20.31). Compared with ARGO in-situ data, the RMSE ranges are from 0.3233 (OSTIA) to 0.5180 (MGDSST). The RMSE between NMEFC fusion products and Argo in-situ data is 0.3861, ranked fifth out of 10 sets of fusion products. Compared with GMPE analysis among 9 sets of fusion products, the RMSE ranges are from 0.1579 (CMC) to 0.3199 (K10), and the NMEFC fusion product has a RMSE of 0.3040, which is at the intermediate level, ranked sixth out of 9 fusion products.

Automated ocean front feature mapping using Sentinel-1 with examples from the Gulf Stream

ABSTRACT This study assessed the ability of Sentinel-1 radial velocity (RVL) products to mark the position of ocean current front features, using the Gulf Stream (GS) as a case study. RVL-derived front features were compared to fronts derived from Multi-scale Ultra-high Resolution Sea Surface Temperature Analysis (MURSST) data. A ridge filter was used to find fronts in both the Sea Surface Temperature (SST) and RVL data, and the similarity between each pair of fronts was measured using the discrete Hausdorff Distance (HD) and Mean Hausdorff Distance (MHD). Front features were correctly identified in concurrent SST and RVL data pairs in 65% of cases. The automatic front extraction sometimes failed by misclassifying an eddy or similar ocean feature as the ocean current in either the RVL or SST image, and sometimes failed to extract the entire length of the front visible within the image. SST and RVL fronts were classified manually to determine the success rate of the automatic front extraction, and to exclude front extraction errors from further analysis. The results demonstrated that RVL products were effective at determining the location of ocean fronts where the angle between the front’s normal vector and the sensor’s azimuthal heading is less than ~ 40°. A mean HD of 25.5 km and a mean MHD of 10.8 km was calculated for all front pairs in the study area.

Predictability of marine heatwaves: assessment based on the ECMWF seasonal forecast system

Abstract. Marine heatwaves (MHWs), defined as prolonged period of extremely warm sea surface temperature (SST), have been receiving a lot of attention in the past decade as their frequency and intensity increase in a warming climate. This paper investigates the extent to which the seasonal occurrence and duration of MHWs can be predicted with the European Centre for Medium-Range Weather Forecast (ECMWF) operational seasonal forecast system. The prediction of the occurrence of MHW events, the number of MHW days per season, and their intensity and spatial extent are derived from seasonal SST forecasts and evaluated against an observation-based SST analysis using both deterministic and probabilistic metrics over the 1982–2021 period. Forecast scores show useful skill in predicting the occurrence of MHWs globally for the two seasons following the starting date. The skill is the highest in the El Niño region, the Caribbean, the wider tropics, the north-eastern extra-tropical Pacific, and southwest of the extra-tropical basins. The skill is not as good for other midlatitude eastern basins nor for the Mediterranean, with the forecast system being able to represent the low-frequency modulation of MHWs but showing poor skill in predicting the interannual variability of the MHW characteristics. Linear trend analysis shows an increase in MHW occurrence at a global scale, which the forecasts capture well.

Modulations of ocean-atmosphere interactions on squid abundance over Southwest Atlantic

Anthropogenic shifts in seas are reshaping fishing trends, with significant implications for aquatic food sources throughout this century. Examining a 21-year abundance dataset of Argentine shortfin squids Illex argentinus paired with a regional oceanic analysis, we noted strong correlations between squid annual abundance and sea surface temperature (SST) in January and February and eddy kinetic energy (EKE) from March to May in the Southwest Atlantic. A deeper analysis revealed combined ocean-atmosphere interactions, pinpointed as the primary mode in a rotated empirical orthogonal function analysis of SST. This pattern produced colder SST and amplified EKE in the surrounding seas, factors crucial for the unique life stages of squids. Future projections from the CMIP6 archive indicated that this ocean-atmosphere pattern, referred to as the Atlantic symmetric pattern, would persist in its cold SST phase, promoting increased squid abundance. However, rising SSTs due to global warming might counteract the abundance gains. Our findings uncover a previously unrecognized link between squids and specific environmental conditions governed by broader ocean-atmosphere interactions in the Southwest Atlantic. Integrating these insights with seasonal and decadal projections can offer invaluable information to stakeholders in squid fisheries and marine conservation under a changing climate.

Intra-tidal upwelling variability off Zhoushan Islands, East China Sea

The coastal upwelling that takes place off the Zhoushan Islands is of great importance in the transport of nutrients, nourishing local fisheries and exerting a substantial environmental influence. While it is known that tides play a central role in triggering and controlling the Zhoushan upwelling, its short-term variability within the tidal cycle remains uncertain, thereby constituting the primary focus of this study, which relies on the analysis of high-resolution Sea Surface Temperature (SST) satellite images and in-situ data. In a tidal cycle, cold upwelling patches exhibit a westward shift during the flood tide and an eastward shift during the ebb tide. The extent of cold upwelling patches is greatest during maximum flood and ebb periods. At maximum ebb, the core temperature within the cold patches notably decreases, which indicates intensified upwelling. At the same time, a similar pattern of sudden increases is also observed throughout the entire water column in the upwelling region. The strong ebb current swiftly transports the upper water mass during maximum ebb, facilitating the compensation of lower water and augmenting the intensity of the upwelling. The calculated vertical velocity within the study area ranged from −9.04 × 10−4 m/s to 12.66 × 10−4 m/s during the observational period, when upwelling showed a significant congruence with low-temperature phenomena. Alternating upwelling and downwelling phases were discernible within a tidal cycle, with upwelling being prevalent. The influence of surface heat flux on seawater below the thermocline and night-time SST was negligible. Furthermore, compared to the vertical velocity, the calculated wind-induced upwelling velocity was much lower, reaching just 3.38 × 10−6 m/s during the observed tidal cycle, which suggests that wind does not exert a primary influence on upwelling within the tidal cycle. This study contributes to an enhanced understanding of upwelling variability under the influence of tides, a topic of paramount importance in the marine environment.

Analysis of Sea Surface Temperature and Chlorophyll-A and Its Relationship with Catch Results Flying Fish Eggs in the Waters of the Kei Islands

The Kei Islands water area is quite productive in fisheries management. Environmental characteristics and oceanographic factors in a body of water will determine the potential of fisheries resources in a water body, and influence fish movement patterns and the formation of fishing areas for flying fish eggs. This research aims to examine the distribution of sea surface temperature and chlorophyll-a concentrations and analyze the relationship between sea surface temperature and chlorophyll-a concentrations with catches of flying fish eggs. The research focused on the waters of the Kei Islands, Southeast Maluku, which is an area for catching flying fish eggs. The research data was studied in the period December 2014 – November 2017. SPL and Chlorophyll-a data were downloaded from Citra MODIS-Aqua, while data on flying fish egg production was obtained from PPN Tual. The research results show that the monthly average SST distribution is between 25.03-30.42ºC, and the monthly average of chlorophyll-a varies quite widely with a range of 0.05-3.09 mg/m3. The number of flying fish egg production fluctuates every year with a production range of 36.28-81.905 kg. The peak of catching flying fish eggs occurs in June-September (eastern season and transition season II). The results of the analysis show that the correlation between SST and chlorophyll-a variables has a very dominant influence on the abundance of flying fish eggs.

Inter-Comparison of Satellite-Based Sea Ice Concentration in the Amundsen Sea, Antarctica

We conducted a comparison of sea ice concentration (SIC) in the Amundsen Sea using three satellite datasets: Hadley Centre’s sea ice and sea surface temperature (HadISST1), Operational Sea Surface Temperature and Ice Analysis (OSTIA), and Advanced Microwave Scanning Radiometer 2 (AMSR2). HadISST1 has the longest time period, while AMSR2 has the shortest. In terms of grid resolution, HadISST1 has the coarsest resolution, while AMSR2 has the finest. The sea ice areas (SIAs) observed in HadISST1, OSTIA, and AMSR2 are similar. We studied the decadal variations in SICs by dividing the study period into four temporal segments. We investigated the differences between HadISST1 and OSTIA for each temporal segment. HadISST1 exhibited a more pronounced positive trend compared to OSTIA between 2005 and 2010. Additionally, we compared the interannual and seasonal variations in SICs between HadISST1 and OSTIA. Lastly, it should be noted that the Amundsen Sea polynya area varies across all three datasets.

Analysis of Marine Heatwaves in China’s Coastal Seas and Adjacent Offshore Waters

Marine heatwaves (MHWs) are changing global ecosystems and bearing profound socio-economic impacts, yet our understanding of the spatial features, temporal evolution characteristics, and regional differences in China’s marginal seas remains insufficient. In this study, the spatio-temporal variation characteristics of the frequency, mean intensity, maximum intensity, cumulative intensity, duration and total days of MHWs are systematically analyzed based on daily sea surface temperature data from Operational Sea Surface Temperature and Ice Analysis (OSTIA) for the period of 1983–2020. The results show the following: The annual mean frequency of MHWs in China’s coastal seas is 1.4–4.6 counts per year and increases gradually from north to south. The annual mean of mean intensity, maximum intensity and cumulative intensity are, respectively, in the ranges of 0.3–2.9 °C, 0.4–3.7 °C and 3.9–41.7 °C days, all of which show a significant decreasing trend from north to south. The annual mean of duration and total days of MHWs are in the respective ranges 8.7–19.7 and 18.9–69.1 days. The annual mean of frequency, cumulative intensity, duration and total days all show a clear increasing trend, with respective linear increases of 1.03 counts, 3.57 °C days, and 1.98 and 17.58 days per decade. The annual means of the mean intensity and maximum intensity have no obvious upward trend, with the exceptions of the Bohai and Yellow Seas. Finally, MHWs were divided into the four categories of moderate, strong, severe and extreme, with the results showing that moderate ones account for more than 70% of all heatwave events, while strong, severe and extreme ones, respectively, account for about 25%, 2% and 0.02%.

Likelihood-Free Parameter Estimation with Neural Bayes Estimators

Neural Bayes estimators are neural networks that approximate Bayes estimators. They are fast, likelihood-free, and amenable to rapid bootstrap-based uncertainty quantification. In this article, we aim to increase the awareness of statisticians to this relatively new inferential tool, and to facilitate its adoption by providing user-friendly open-source software. We also give attention to the ubiquitous problem of estimating parameters from replicated data, which we address using permutation-invariant neural networks. Through extensive simulation studies we demonstrate that neural Bayes estimators can be used to quickly estimate parameters in weakly identified and highly parameterized models with relative ease. We illustrate their applicability through an analysis of extreme sea-surface temperature in the Red Sea where, after training, we obtain parameter estimates and bootstrap-based confidence intervals from hundreds of spatial fields in a fraction of a second.

Analysis of Extreme Sea Surface Temperature along the Western Coastal area of Chungnam: Current Status and Future Projections

Analysis of Extreme Sea Surface Temperature along the Western Coastal area of Chungnam: Current Status and Future Projections

Sea surface temperature trends for Tampa Bay, West Florida Shelf and the deep Gulf of Mexico

Sea surface temperatures for Tampa Bay, the West Florida Continental Shelf (WFS) and the adjacent deep Gulf of Mexico are examined for trends. Data sets are from stations maintained by the Hillsborough County Environmental Protection Commission, buoys maintained by the University of South Florida Coastal Ocean Monitoring and Prediction System and the National Oceanic and Atmosphere Administration (NOAA) National Data Buoy Center, the Optimum Interpolation Sea Surface Temperature analyses by the NOAA National Centers for Environmental Information, and the Hadley Centre Sea Surface Temperature. These various data sets, each with different record lengths, require the consideration of trends both on the basis of record length and start time. Tampa Bay shows a warming trend, but with considerable inter-annual variability and start time bias resulting in a lack of statistical significance in more recent years. The WFS is also generally warming, and its inter-annual variability is largely controlled by the upwelling of cooler, deeper Gulf of Mexico water across the shelf break. The deep GOM shows statistically significant warming in most of the data except for the “gappy” records from buoys, both along the continental shelf and in the deep water. Trends in the Gulf of Mexico are mostly between 0.1 and 0.5 °C/decade, somewhat larger than the secular rise found globally, although within the range of the observed decadal variability.

A comparative study of satellite-based operational analyses and ship-based in-situ observations of sea surface temperatures over the eastern Canadian shelf

The satellite-based operational sea surface temperature (SST) was compared to the ship-based in-situ SSTs established by the Atlantic Zone Monitoring Program (AZMP) over the eastern Canadian shelf (ECS) for a 3-year anal-ysis period (2005–2007). Two sets of operational SST analyses were considered in this study, with one set produced by the Canadian Meteorological Centre (CMC) and the other produced by the National Centers for Environmental Predic-tion (NCEP). The comparative study indicated that there was no appreciable systematic difference between the CMC and NCEP SST analyses over the ECS. The root mean squared difference (RMSD) between the AZMP ship-based in-situ SSTs and the satellite-based STT analyses over the ECS was about 1.0°C, without any obvious seasonal or geo-graphic trend. The RMSDs were relatively larger over the outer flank of the Grand Banks than the other regions of the ECS, mainly due to dynamically complicated circulation and hydrographic conditions over this shelf break area associated with the Labrador Current.

A New Upwelling Index for the Moroccan Atlantic Coast for the Period between 1982–2021

Being a component of the Eastern Boundary Upwelling (EBU) ecosystem, Morocco’s Atlantic coast presents high biological production throughout the year, with seasonal variations in upwelling dynamics. This characterization reflects the inherent nature of EBU’s ecosystems. In this work, we develop a novel methodology to compute a new upwelling index based on the analysis of sea surface temperature (SST) images. Our new upwelling index is not only simple to calculate but also efficient. Indeed, it is limited only to the upwelling region, which has allowed the improvement of the quantification and analysis of the seasonal and interannual variability of the upwelling dynamics. The new proposed upwelling index is based on the application of a recent segmentation method that allows for the monitoring of upwelling dynamics using satellite observations. The proposed upwelling index is applied to a 40-year database of weekly SST images covering the period from 1982 to 2021, and the results are used to analyze seasonal and interannual variations of the upwelling in the region.

Imprint of Mesoscale Eddies on Air-Sea Interaction in the Tropical Atlantic Ocean

This study investigates the effect of mesoscale eddies on air–sea heat and fresh water exchange in the tropical Atlantic Ocean (TAO) using 8 years of satellite altimetry data, combined with sea surface temperature (SST), latent and sensible heat fluxes (LHF and SHF), infrared fluxes (IRF) and precipitation (PR) data. Results indicate that approximately ∼40% of cyclonic eddies contribute to warm SST anomalies, and ∼40% of anticyclonic eddies contribute to cold SST anomalies. Eddies were found to play a role in the variability in LHF, SHF and IRF, contributing 10–35% of their total variability, with the largest contributions observed beneath the intertropical convergence zone (ITCZ) and frontal SST areas. Composite analysis of SST and heat flux anomalies over eddies suggested that the anomalies created through horizontal advection processes may not significantly impact the overall LHF, SHF and IRF over eddies, contrary to vertical processes. Despite a lack of clear correlation between heat flux and PR anomalies over eddies in the TAO, significant correlations were found beneath the ITCZ, suggesting that eddies may impact both heat fluxes and PR in the ITCZ region. This study provides an original contribution to the understanding of the impact of ocean mesoscale eddies on the atmosphere in the TAO.

Anisotropic diffusion filters for flow-dependent variational data assimilation of sea surface temperature

It is well known that the background error covariance matrix in the data assimilation is anisotropic and varied with the flow field, that is, flow-dependent. However, it is generally assumed to be isotropic and static for ease of implementation. Therefore, to enhance the quality of the background error covariance, two easy-to-implement, flow-dependent three-dimensional variational analysis (3DVar) schemes, the advection–diffusion filter (ADF) and the Smagorinsky diffusion filter (SDF), are tentatively proposed. These serve as alternative schemes for the traditional methods that are based on the isotropic assumption. First, a correctness test of the gradient for the ADF is performed to verify the validity of the adjoint code. Then, the response analysis for the 1D advection–diffusion​ equation is investigated to validate the anisotropic characteristic of the ADF with various flow velocities. Second, the two flow-dependent 3DVar schemes are verified via single-observation assimilation experiments. Compared to the existing diffusion filter with a static diffusion coefficient, both new schemes show a flow-dependent capability in the assimilation experiment because they successfully spread the observational information anisotropically. Finally, a retroactive real-time forecast experiment framework based on a 3D baroclinic primitive equation ocean model is used to investigate the effects of the ADF/SDF on the analysis and forecast accuracy of sea surface temperature (SST). While the traditional variational assimilation method with an isotropic diffusion filter generally reduces initial field errors, both the ADF and SDF can further enhance the accuracy of the initial fields in strong current areas. In addition, better forecast skills can be obtained with the two flow-dependent schemes in the East China Sea.

Examining the Consistency of Sea Surface Temperature and Sea Ice Concentration in Arctic Satellite Products

Available observations and a theoretical simulation are used to explore the consistency and relationship between sea surface temperature (SST) and sea ice concentration (SIC) within open-ocean-sea ice mixed satellite pixels as a function of grid resolution. The maximum limiting SST value for a specified SIC and spatial resolution is first examined within collocated satellite-derived products contained within existing Level 4 SST analyses distributed using the data specification from the Group for High Resolution Sea Surface Temperature. The shape of the interdependence is further validated with manually quality-controlled buoy SST and SIC collocations. A parametric equation for the limiting SST value is derived from simulations of a mixed ocean/ice pixel with specified ice fraction and a linear SST gradient extending away from the ice edge. The exponential curve matching the observed interdependence suggests a maximum 5 km pixel-averaged SST at SIC values approaching zero between 6 and 8 °C. This maximum value is significantly greater than the previously assumed limiting values of ~3 °C and the corresponding SST gradient is larger than those typically observed with satellite SST products, but agrees well with recent Saildrone SST observations near ice. The curve provides a conservative limit with which inconsistent SST/SIC pairings can be identified, not only near the ice edge but at intermediate ice concentrations. Application of the filter improves the agreement between the SST/SIC relationship in satellite products and available Saildrone observations as well as the internal consistency of the different satellite products.

A new global coupled atmosphere-ocean wavenumber-4 pattern in Southern mid–latitudes during austral summer and its climate linkage

A new pattern referred to as the coupled ocean-atmosphere wavenumber-4 (COAW4) pattern has been identified in the Southern mid-latitudes during austral summer. This pattern consists of a wavenumber-4 pattern in the anomalous 200-hPa meridional wind and a wavenumber-4 pattern of the anomalous sea surface temperature (SST). The SST component of the COAW4 pattern, which includes the Indian Ocean Subtropical Dipole (IOSD), the South Atlantic Subtropical Dipole (SASD) and the South Pacific Subtropical Dipole (SPSD), develops through air-sea interactions involving surface turbulent heat flux, surface wind, and ocean mixed-layer depth. The atmospheric component displays a barotropic structure. The sources for COAW4 pattern include not only the wavenumber-4 pattern of the anomalous SST over Southern oceans, but also the anomalous convective activities over Southern land areas. The COAW4 pattern is associated with increased precipitation over land in southern mid-latitudes, particularly in central Australia. Furthermore, the COAW4 pattern is linked to Antarctic sea ice cover in the Weddell, Amundsen, and northern Ross Seas. Plain language summary In the southern mid-latitudes, there exists a wavenumber 4 pattern in the anomalous 200-hPa meridional wind and a wavenumber-4 pattern of the anomalous sea surface temperature (SST). Previous studies have examined the two wavenumber-4 patterns separately, but their potential linkage remains largely unknown. Through statistical analyses of SST and atmospheric global data, we demonstrated that the two wavenumber 4 patterns could be integrated into a coupled ocean-atmosphere wavenumber-4 (COAW4) pattern in Southern mid-latitudes in austral summer. Additionally, we have investigated the sources of this pattern as well as its effect on precipitation over southern lands and on Antarctic sea ice.

Co-occurrence of a marine heatwave and a reported tomato jellyfish (<i>Crambione mastigophora</i> Maas, 1903) bloom in March 2020 at El Nido, Palawan, Philippines

Globally, observations on marine species during marine heatwaves (MHWs) help outline the scope of the MHW’s possible biological effects. In line with this effort, this paper presents a 2020 MHW that coincided with a reported ‘tomato jellyfish’ (Crambione mastigophora Maas, 1903) bloom on 23 March 2020 in the Corong-Corong Bay of Palawan, Philippines. Detecting a moderate MHW from 21 March to 04 April 2020, the analysis of sea surface temperatures revealed that most areas surrounding the bloom site attained their peak positive anomalies on the same day as the reported bloom. Certain physical mechanisms present in the first quarter of 2020 may have played a role in the occurrence of both events: the presence of cyclonic eddies and parallel monsoonal winds alongshore can induce upwelling which promotes biological productivity in surface waters, while the observed weakening of winds have been associated with anomalous warming of the sea surface. Further studies are still highly recommended to determine the exact causes of the jellyfish bloom and what conditions make it more likely to happen during MHWs. However, if the C. mastigophora is hypothetically able to continually bloom amidst warming temperatures, the increasing trend of MHW frequency and intensity in the West Philippine Sea (where the reported bloom site is situated) may consequently yield more future co-occurrences. This paper aims to hopefully contribute to the existing knowledge of possible biological impacts associated with extreme marine events, especially in the Philippine context where both jellyfish blooms and MHWs are understudied.