Sea Surface Temperature Data Products Research Articles

Performance of high-resolution MUR satellite sea surface temperature data as a proxy for near-surface in situ temperatures on neotropical reefs

As ocean temperatures increase, so does the need for accurate, regular, and widespread temperature data. This is especially important for researchers studying corals, which can be pushed over their bleaching thresholds by small, sustained changes in water temperature. Satellite data products offer longitudinal estimates of sea surface temperature (SST) taken at regular intervals without the ongoing costs and geospatial limits associated with underwater temperature loggers. However, previous work indicates satellite data are sometimes characterized by significant temperature biases, particularly in stratified coastal waters. Here, we compared the foundation sea surface temperature (fSST) estimated from a highly processed, gridded satellite data set (GHRSST MUR L4 Global SST) to in situ temperature (IST) data collected from coral reef habitats in the top 20 m of the water column at 19 sites in Panama. Comparisons between Pacific and Caribbean coasts and between upwelling and non-upwelling seasons provide a robust test of the utility of this product to estimate subsurface temperatures. The mean differences between fSST and IST show that MUR fSST accurately reflects temperatures at shallow (<9 m) depths on the Caribbean coast (mean bias ≤0.55°C ± standard error (SE) 0.01°C) and during the non-upwelling season on the Pacific coast (mean bias ≤0.26°C ± SE 0.03°C). MUR fSST poorly reflects IST during the Pacific upwelling season, especially at sites 12 m and deeper. In such cases, 66% of satellite estimates deviated from ISTs by >1°C. Our findings underscore how highly processed SST data products should be ground-truthed before being used as a substitute for IST, especially in upwelling areas.

Evaluation of SST Data Products from Multi-Source Satellite Infrared Sensors in the Bohai-Yellow-East China Sea

The measurement of sea surface temperature (SST) is of utmost importance in the realm of oceanography. The increasing utilization of satellite data in SST research has highlighted the crucial need to compare and evaluate various satellite data sources. Using iQuam2 in situ SST data, this study aims to assess the accuracy of SST datasets obtained from three polar-orbiting satellites (AVHRR, Modis-Aqua, and Modis-Terra) and one geostationary satellite (Himawari-8) in the Bohai-Yellow-East China Sea (BYECS) throughout 2019. The results showed a strong correlation between satellite and in situ data, with R correlation coefficients exceeding 0.99. However, the accuracy of the satellite datasets exhibited some variability, with Himawari-8 showing the highest deviation error and MODIS-Aqua showing the least. Subsequently, the Modis-Aqua data were used as a benchmark to evaluate the SST data of the other three satellites over the previous six years (July 2015–June 2021). The results indicate that, in addition to intricate temporal variations, the deviations of the three satellites from Modis-Aqua also show significant spatial disparities due to the effect of seawater temperature. Compared to Modis-Aqua, the deviation of Himawari-8 generally displayed a negative trend in BYECS and showed pronounced seasonal variation. The deviation of AVHRR showed a negative trend across all regions except for a substantial positive value in the coastal region, with the time variation exhibiting intricate features. The SST values obtained from MODIS-Terra exhibited only marginal disparities from MODIS-Aqua, with positive values during the day and negative values at night. All three satellites showed significantly abnormal bias values after December 2020, indicating that the MODIS-Aqua-derived SST reference dataset may contain outliers beyond this period. In conclusion, the accuracy of the four satellite datasets varies across different regions and time periods. However, they could be effectively utilized and integrated with relevant fusion algorithms to synthesize high-precision datasets in the future.

Weak Mesoscale Variability in the Optimum Interpolation Sea Surface Temperature (OISST)-AVHRR-Only Version 2 Data before 2007

Mesoscale sea surface temperature (SST) variability triggers mesoscale air–sea interactions and is linked to ocean subsurface mesoscale dynamics. The National Oceanic and Atmospheric Administration (NOAA) daily Optimum Interpolation SST (OISST) products, based on various satellite and in situ SST data, are widely utilized in the investigation of multi-scale SST variabilities and reconstruction of subsurface and deep-ocean fields. The quality of OISST datasets is subjected to temporal inhomogeneity due to alterations in the merged data. Yet, whether this issue can significantly affect mesoscale SST variability is unknown. The analysis of this study detects an abrupt enhancement of mesoscale SST variability after 2007 in the OISST-AVHRR-only version 2 and version 2.1 datasets (hereafter OI.v2-AVHRR-only and OI.v2.1-AVHRR-only). The contrast is most stark in the subtropical western boundary current (WBC) regions, where the average mesoscale SST variance during 2007–2018 is twofold larger than that during 1993–2006. Further comparisons with other satellite SST datasets (TMI, AMSR-E, and WindSAT) suggest that the OISST-AVHRR-only datasets have severely underestimated mesoscale SST variability before 2007. An evaluation of related documents of the OISST data indicates that this bias is mainly caused by the change of satellite AVHRR instrument in 2007. There are no corresponding changes detected in the associated fields, such as the number and activity of mesoscale eddies or the background SST gradient in these regions, confirming that the underestimation of mesoscale SST variability before 2007 is an artifact. Another OISST product, OI.v2-AVHRR-AMSR, shows a similar abrupt enhancement of mesoscale SST variability in June 2002, when the AMSR-E instrument was incorporated. This issue leaves potential influences on scientific research that utilize the OISST datasets. The composite SST anomalies of mesoscale eddies based on the OI.v2-AVHRR-only data are underestimated by up to 37% before 2007 in the subtropical WBC regions. The underestimation of mesoscale variability also affects the total (full-scale) SST variability, particularly in winter. Other SST data products based on the OISST datasets were also influenced; we identify suspicious changes in J-OFURO3 and CFSR datasets; the reconstructed three-dimensional ocean products using OISST data as input may also be inevitably affected. This study reminds caution in the usage of the OISST and relevant data products in the investigation of mesoscale processes.

An enigmatic decoupling between heat stress and coral bleaching on the Great Barrier Reef.

Ocean warming threatens the functioning of coral reef ecosystems by inducing mass coral bleaching and mortality events. The link between temperature and coral bleaching is now well-established based on observations that mass bleaching events usually occur when seawater temperatures are anomalously high. However, times of high heat stress but without coral bleaching are equally important because they can inform an understanding of factors that regulate temperature-induced bleaching. Here, we investigate the absence of mass coral bleaching on the Great Barrier Reef (GBR) during austral summer 2004. Using four gridded sea surface temperature data products, validated with in situ temperature loggers, we demonstrate that the summer of 2004 was among the warmest summers of the satellite era (1982–2017) on the GBR. At least half of the GBR experienced temperatures that were high enough to initiate bleaching in other years, yet mass bleaching was not reported during 2004. The absence of bleaching is not fully explained by wind speed or cloud cover. Rather, 2004 is clearly differentiated from bleaching years by the slow speed of the East Australian Current (EAC) offshore of the GBR. An anomalously slow EAC during summer 2004 may have dampened the upwelling of nutrient-rich waters onto the GBR shelf, potentially mitigating bleaching due to the lower susceptibility of corals to heat stress in low-nutrient conditions. Although other factors such as irradiance or acclimatization may have played a role in the absence of mass bleaching, 2004 remains a key case study for demonstrating the dynamic nature of coral responses to marine heatwaves.

Meteorological impacts of sea-surface temperature associated with the humid airflow from Tropical Cyclone Talas (2011)

Abstract. This paper examines meteorological impacts of sea-surface temperature (SST) in the presence of the humid airflow from Tropical Cyclone Talas (2011). To investigate the influence of the SST on the severe weather in and around Japan, sensitivity simulations were conducted using six SST data products covering a period of 7 days. The upward sea-surface latent heat flux that accumulated over the 7-day period was high around the Kuroshio during the slow passage of the tropical cyclone. Large differences were found among the individual SST products around the southern coast of Japan. The coastal warm SST anomaly of ~ 1.5 °C enhanced the surface upward latent heat fluxes (by 60 to 80%), surface southeasterly winds (by 6 to 8%), and surface water mixing ratios (by 4%) over the coastal sea area. The enhanced latent heat flux resulting from the coastal SST anomaly contributed to the further enhancement of the latent heat flux itself via a positive feedback with the amplified surface horizontal wind. The SST anomalies produced an anomaly in 7-day precipitation (ca. 40 mm) along the mountainsides and over a coastal area where the surface wind anomaly was locally large. Thus, coastal SST error is important in the atmospheric simulation of accumulated evaporation and precipitation associated with tropical cyclones making landfall.

Multi-specimen and multi-site calibration of Aleutian coralline algal Mg/Ca to sea surface temperature

Higher latitude oceanic and climatic reconstructions are needed to distinguish natural climate variability from anthropogenic warming in regions projected to experience significant increases in temperature during this century. Clathromorphum nereostratum is a long-lived coralline alga abundant along the Aleutian archipelago that records seasonal to centennial fluctuations in seawater temperatures in its high-Mg calcite skeleton. Thus, C. nereostratum is an important proxy archive to reconstruct past seawater temperature variability in this data-poor subarctic region. Here, we measured magnesium to calcium ratios (Mg/Ca) by laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) along the growth axis in six live-collected specimens from three islands in the Aleutian archipelago to assess Mg/Ca reproducibility and to calibrate algal Mg/Ca against modern gridded sea surface temperature (SST) data products. The master Mg/Ca–SST transfer function, determined by averaging the algal Mg/Ca–SST from each island (n=6), resulted in a reconstruction error of ±0.45°C, a 31–46% reduction in error compared to the reconstruction error for a single alga. The master algal-SST record interpolated to monthly and annual resolution significantly varied with gridded SST data products (r2=0.98, p<0.0001, n=517 and r2=.27, p<0.0003, n=44, respectively) for the period from 1960 to 2003. Therefore, coralline algal Mg/Ca-derived SST reconstructions record absolute changes in past SST variability in the Aleutian archipelago. The transfer functions developed here can be applied to Mg/Ca records generated from long-lived specimens of C. nereostratum to reconstruct northern North Pacific and Bering Sea SST variability for the past several hundred years.

Long-term validation of AATSR SST data products using shipborne radiometry in the Bay of Biscay and English Channel

Radiometric measurements of the sea surface temperature (SST) made by the infrared SST autonomous radiometer (ISAR) deployed routinely between 2004 and 2009 from a passenger vessel traversing the English Channel and Bay of Biscay are used to validate satellite SST data products produced using the Advanced along-track scanning radiometer (AATSR) flown on Envisat. More than 1500 independent pairings between an ISAR record and an AATSR pixel, coincident within specified space–time matching windows, are analysed. These confirm good agreement between the in situ and the satellite derived SST estimates, based on the dual view AATSR algorithms, with a bias of less than 0.1K which is the accuracy limit of the ISAR. The standard deviation of the comparisons depends on the coincidence criteria: for a match-up window of 1km and 2h it is around 0.3K for the three channel (night only) algorithm and 0.4K for the 2 channel algorithm. Separate validation statistics are produced for the periods before and after 7 Dec 2005 when a change was made to the AATSR algorithms. It is shown that the error distribution was narrowed by introducing the new algorithm and further narrowed by using only the AATSR data that have the highest Confidence Value. This is the first systematic use of autonomous underway shipboard radiometry on a vessel of opportunity for validating satellite data. The methodology is carefully assessed and shown to provide an effective and reliable means of confirming the high quality and stability of the SST data products from AATSR.

The Global Ocean Data Assimilation Experiment High-resolution Sea Surface Temperature Pilot Project

A new generation of integrated sea surface temperature (SST) data products are being provided by the Global Ocean Data Assimilation Experiment (GODAE) High-Resolution SST Pilot Project (GHRSST-PP). These combine in near-real time various SST data products from several different satellite sensors and in situ observations and maintain the fine spatial and temporal resolution needed by SST inputs to operational models. The practical realization of such an approach is complicated by the characteristic differences that exist between measurements of SST obtained from subsurface in-water sensors, and satellite microwave and satellite infrared radiometer systems. Furthermore, diurnal variability of SST within a 24-h period, manifested as both warm-layer and cool-skin deviations, introduces additional uncertainty for direct intercomparison between data sources and the implementation of data-merging strategies. The GHRSST-PP has developed and now operates an internationally distributed system that provides operational feeds of regional and global coverage high-resolution SST data products (better than 10 km and ~6 h). A suite of online satellite SST diagnostic systems are also available within the project. All GHRSST-PP products have a standard format, include uncertainty estimates for each measurement, and are served to the international user community free of charge through a variety of data transport mechanisms and access points. They are being used for a number of operational applications. The approach will also be extended back to 1981 by a dedicated reanalysis project. This paper provides a summary overview of the GHRSST-PP structure, activities, and data products. For a complete discussion, and access to data products and services see the information online at www.ghrsst-pp.org.

Using sea surface temperature measurements from microwave and infrared satellite measurements

The Tropical Rainfall Mapping Mission Microwave Imager (TMI) instrument Sea Surface Temperature (SST) product (v1.0) is compared with in situ observations obtained in the Atlantic Ocean. The TMI SST has a mean warm bias of 0.25 K±0.7 K when compared to in situ SST at a depth of 7 m. When TMI SST are compared to in situ skin SST measurements, the bias is 0.6 K±0.5 K. A limited global comparison between TMI SST and co-incident ERS-2 Along-Track Scanning Radiometer (ATSR/2) skin SST demonstrates a bias of 0.6 K±0.6 K consistent with the result obtained using in situ observations. These results are consistent with the predicted accuracy of the TMI SST data products. Based on these results, a simple method to merge the TMI and ATSR data is proposed.

Global Measurement of Sea Surface Temperature from Space: Some New Perspectives

The measurement of global sea surface temperature (SST) from space is well established with 20 years of useful data already acquired, but the more stringent sampling requirements and the higher degree of accuracy now demanded for applications in both climate monitoring and operational oceanography are increasingly difficult to meet with the standard meteorological polar orbiting sensors that have been the basic sensors used for global SST mapping. The established methods and sensors for measuring SST, both in situ and in space, are reviewed, compared, and their major limitations are identified. Mention is made of phenomena which complicate an apparently simple measurement, including diurnal stratification, the presence of clouds and the contamination of the stratosphere by volcanic aerosols. Recent developments in remote sensing of SST are mentioned, noting the improved microwave sensors now becoming available, the calibrated infrared sensors planned for geostationary platforms, and weighing the benefits of merging these data. The conventional buoy-calibration of SST measurements from space is complicated by the variable thermal structure of the upper few metres of the ocean. The recent improvement of radiometers for ship deployment has led to better understanding of the thermal skin of the ocean which suggests a new approach for the validation of SST algorithms based on radiation transfer models. Finally, a future strategy is outlined for combining measurements from many types of sensor in order to achieve the required accuracy and sampling rate of SST data products, and to identify some of the remaining scientific challenges in this field.