Spatial Sea Surface Temperature Research Articles

First Analyses of the TIMELINE AVHRR SST Product: Long-Term Trends of Sea Surface Temperature at 1 km Resolution across European Coastal Zones

Coastal areas are among the most productive areas in the world, ecologically as well as economically. Sea Surface Temperature (SST) has evolved as the major essential climate variable (ECV) and ocean variable (EOV) to monitor land–ocean interactions and oceanic warming trends. SST monitoring can be achieved by means of remote sensing. The current relatively coarse spatial resolution of established SST products limits their potential in small-scale, coastal zones. This study presents the first analysis of the TIMELINE 1 km SST product from AVHRR in four key European regions: The Northern and Baltic Sea, the Adriatic Sea, the Aegean Sea, and the Balearic Sea. The analysis of monthly anomaly trends showed high positive SST trends in all study areas, exceeding the global average SST warming. Seasonal variations reveal peak warming during the spring, early summer, and early autumn, suggesting a potential seasonal shift. The spatial analysis of the monthly anomaly trends revealed significantly higher trends at near-coast areas, which were especially distinct in the Mediterranean study areas. The clearest pattern was visible in the Adriatic Sea in March and May, where the SST trends at the coast were twice as high as that observed at a 40 km distance to the coast. To validate our findings, we compared the TIMELINE monthly anomaly time series with monthly anomalies derived from the Level 4 CCI SST anomaly product. The comparison showed an overall good accordance with correlation coefficients of R > 0.82 for the Mediterranean study areas and R = 0.77 for the North and Baltic Seas. This study highlights the potential of AVHRR Local Area Coverage (LAC) data with 1 km spatial resolution for mapping long-term SST trends in areas with high spatial SST variability, such as coastal regions.

Exploring temporal and spatial SST patterns and their impact in the Arabian Sea: Insights from the regional ocean modeling system

The Regional Ocean Modeling System (ROMS) is integrated across the Arabian Sea (AS) from 1992 to 2021 and covers 33°E to 80°E and 5°N to 32°N at high horizontal resolutions of 1/4°(∼25 km). The study demonstrates that the variability is controlled by a seasonal high-resolution setup, with superior performance for various seasons during the months of December-January-February (DJF), March-April-May (MAM), June-July-August-September (JJAS) and October–November (ON). The Sea Surface Temperature (SST) anomalies in the JJAS season werestudied. SST dominates the seasonal variability of the Indian summer monsoon (ISM). Our results show that the ROMS can simulate seasonal variability and its effects on the upper ocean properties over the AS. In addition, the impact of monthly variation is controlled. In recreating the spatio-temporal distribution of surface as well as subsurface hydrographic parameters such as surface and subsurface temperature, the simulation results are reasonable like observation and reanalysis.

Mean reef fish body size decreases towards warmer waters

AbstractAquatic ectotherms often attain smaller body sizes at higher temperatures. By analysing ~15,000 coastal‐reef fish surveys across a 15°C spatial sea surface temperature (SST) gradient, we found that the mean length of fish in communities decreased by ~5% for each 1°C temperature increase across space, or 50% decrease in mean length from 14 to 29°C mean annual SST. Community mean body size change was driven by differential temperature responses within trophic groups and temperature‐driven change in their relative abundance. Herbivores, invertivores and planktivores became smaller on average in warmer temperatures, but no trend was found in piscivores. Nearly 25% of the temperature‐related community mean size trend was attributable to trophic composition at the warmest sites, but at colder temperatures, this was <1% due to trophic groups being similarly sized. Our findings suggest that small changes in temperature are associated with large changes in fish community composition and body sizes, with important ecological implications.

Statistical relationships between the Interdecadal Pacific Oscillation and El Niño–Southern Oscillation

AbstractThe climate of the Pacific Ocean varies on interannual, decadal, and longer timescales. This variability is dominated by the El Niño–Southern Oscillation (ENSO) and the Interdecadal Pacific Oscillation (IPO), both of which have profound impacts on countries within and well beyond the Pacific. To date, previous studies have only examined a small subset of the possible links between ENSO, its diversity, and the IPO. Here we focus on the statistical relationship between decadal variability in ENSO properties and the IPO, testing the null hypothesis that the IPO arises from random decadal changes in ENSO activity, including ENSO diversity. We use observed sea surface temperature (SST) records since 1920 to investigate how the timing, structure, frequency, duration, and magnitude of El Niño and La Niña events differ between IPO phases. We find that using the relative frequency of El Niño and La Niña events and either the mean event duration or SST magnitude can reproduce up to 60% of the IPO Tripole Index timeseries. While the spatial SST patterns that represent the IPO and ENSO are similar, the IPO is meridionally broader in the central to eastern Pacific, which may be caused by a lagged relationship with low-frequency SST variability in the equatorial Pacific. In addition, North Pacific SST anomalies of opposite sign to the tropical Pacific SST anomalies is a unique feature of the IPO that cannot be explained by decadal ENSO variability. This suggests a clear IPO and ENSO relationship, but also independence in some of the IPO’s characteristics.

Seasonal cycle of sea surface temperature in the tropical Angolan Upwelling System

Abstract. The Angolan shelf system represents a highly productive ecosystem. Throughout the year the sea surface is cooler near the coast than further offshore. The lowest sea surface temperature (SST), strongest cross-shore temperature gradient, and maximum productivity occur in austral winter when seasonally prevailing upwelling-favourable winds are weakest. Here, we investigate the seasonal mixed layer heat budget to identify atmospheric and oceanic causes for heat content variability. By using different satellite and in situ data, we derive monthly estimates of surface heat fluxes, mean horizontal advection, and local heat content change. We calculate the heat budgets for the near-coastal and offshore regions separately to explore processes that lead to the observed SST differences. The results show that the net surface heat flux warms the coastal ocean stronger than further offshore, thus acting to damp spatial SST differences. Mean horizontal heat advection is dominated by meridional advection of warm water along the Angolan coast. However, its contribution to the heat budget is small. Ocean turbulence data suggest that the heat flux, due to turbulent mixing across the base of the mixed layer, is an important cooling term. This turbulent cooling, being strongest in shallow shelf regions, is capable of explaining the observed negative cross-shore temperature gradient. The residuum of the mixed layer heat budget and uncertainties of budget terms are discussed.

Weakening seasonality of Indo-Pacific warm pool size in a warming world since 1950

Seasonal variation of the Indo-Pacific warm pool (IPWP) plays an important role in oceanographic and climatological processes. While expansion of the IPWP under greenhouse warming has been widely discussed, the response of IPWP seasonality to climate change has received limited attention. In this study, we found an obvious seasonal diversity in expansion of the IPWP from 1950 to 2020, with a maximum (minimum) expansion trend of 0.28 107 km2/decade in winter (0.17 107 km2/decade in spring), which consequently reduces the seasonality amplitude of the variation in IPWP size. This is primarily attributed to the seasonal difference in the climatological spatial sea surface temperature (SST) pattern over the Indo-Pacific Ocean, especially that over the tropical Indian Ocean, which determines the capacity for IPWP expansion. Heat budget analyses show that the seasonal shortwave radiation and latent heat fluxes are the major factors controlling the capacity for change in IPWP size across seasons. The presented analyses emphasize the significant weakening of the seasonality of IPWP size, which may have great impacts on the ecological environment of the IPWP and the tropical climate system, and remind us that the intrinsic properties of the climate background of Indo-Pacific SST hold important clues about IPWP expansion under climate change.

Satellite-Observed Spatial and Temporal Sea Surface Temperature Trends of the Baltic Sea between 1982 and 2021

The Baltic Sea is one of the fastest-warming marginal seas globally, and its temperature rise has adversely affected its physical and biochemical characteristics. In this study, forty years (1982–2021) of sea surface temperature (SST) data from the advanced very high resolution radiometer (AVHRR) were used to investigate spatial and temporal SST variability of the Baltic Sea. To this end, annual maximum and minimum SST stacked series, i.e., time series of stacked layers of satellite data, were generated using high-quality observations acquired at night and were fed to an automatic algorithm to detect linear and non-linear trend patterns. The linear trend pattern was the dominant trend type in both stacked series, while more pixels with non-linear trend patterns were detected when using the annual minimum SST. However, both stacked series showed increases in SST across the Baltic Sea. Annual maximum SST increased by an average of 0.062 ± 0.041 °C per year between 1982 and 2021, while annual minimum SST increased by an average of 0.035 ± 0.017 °C per year over the same period. Averaging annual maximum and minimum trends produces a spatial average of 0.048 ± 0.022 °C rise in SST per year over the last four decades.

Colpophyllia natans From Tobago, a Novel Paleoclimate Archive for Reconstructing Sea Surface Temperature in the Tropical Atlantic

AbstractMassive, long‐lived Siderastrea and Diploria corals are species commonly used for sea surface temperature (SST) reconstructions in the North Atlantic. However, they are rarely found to exceed 200 years in age. Thus, it is imperative to continuously develop alternative taxa for paleoreconstructions. Colpophyllia natans, a highly populous tropical North Atlantic coral, are known to grow large colonies, potentially containing environmental records spanning several hundreds of years. However, its low density and complicated architecture poses a challenge in extracting climate signals from this coral. This study presents the first monthly‐resolved climate calibration of Colpophyllia natans and validates its utility as a new paleoarchive, relative to Siderastrea siderea. Linear regressions of monthly and interannual coral Sr/Ca with instrumental SST reveal robust, significant relationships (p < 0.05), indicating that microsampling along a single thecal wall of C. natans allowed for robust climate reconstructions. Additionally, both corals capture similar SST variations (t‐test, p ≥ 0.05), which allowed for the generation of a single, composite interspecies SST record that correlates with instrumental SST even more strongly (p < 0.0001) than the individual corals. Mean annual and boreal summer interspecies SST correlate significantly with North Atlantic SST indices (p < 0.05), demonstrating the ability to capture regional, long‐term SST trends in the North Atlantic. Spatial correlation maps of boreal winter interspecies SST to instrumental SST and geopotential height anomalies reveal coherent spatial patterns linked to the North Atlantic Oscillation. Our findings suggest that Colpophyllia natans has enormous potential as a new paleoclimate archive for reconstructing temporal and spatial SST variability in the tropical Atlantic.

Assessing the ability of satellite sea surface temperature analyses to resolve spatial variability – The northwest tropical Atlantic ATOMIC region

Direct measurements of the sea surface temperature (SST) from multiple platforms deployed during the Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC) field campaign are used to evaluate the ability of satellite SST products to accurately represent spatial gradients within the region. The results further provide insight into the suitability of different satellite SST products for application to ATOMIC and other northwest tropical Atlantic scientific analyses. In situ SST measurements from the Research Vessel Ronald H. Brown, Saildrones, and Surface Velocity Program – Salinity (SVPS) drifters were collocated with five daily Level 4 satellite SST analyses and two Level 3 single-sensor satellite SST products during the period from January 1 to February 24, 2020. The absolute accuracy of the satellite products was generally good with random errors on the order of 0.2 K or less, though most exhibited a small cool bias of ∼0.1 K. The biases were not representative of a consistent offset, but rather larger cool biases of a subset of observations influenced the overall statistics. Sub-grid SST variability in the ATOMIC region was small (< 0.03 K) in relationship both to other regions and to uncertainties in the satellite products. Despite their absolute accuracy, the L4 analyses accurately reproduced the spatial SST variability within the ATOMIC domain only on scales of 0.5–1° or more. At the scale of their respective grid resolutions, correlations between satellite-derived and Saildrone-inferred grid-scale SST gradients were low, as the satellite–Saildrone SST differences dominated over small cell-to-cell variability in the region. One reason was the coarser feature resolution of the analyses compared to their grid resolution. Correlations increased with the distance over which the SST values were averaged. Simulations demonstrated that a satellite product precision near 0.05 K was needed to successfully reproduce the observed SST spatial variability at the grid cell level. Comparison with Saildrone observations from the Arctic showed sub-grid SST variability six-times larger and a relaxed satellite accuracy requirement of near 0.5 K in that region, but the satellite product accuracy was also degraded, again hindering the accurate sampling of SST gradients at the scale of the L4 analyses.

Detection of surface temperature anomaly of the Sea of Marmara

Monitoring sea surface temperature (SST) over a long-term and detecting the anomalies highly contribute to understanding the prevailing water quality of the sea. Earth observation satellite images are the key data sources that offer the long-term SST detection in a cost and time effective way. Since the Sea of Marmara in Türkiye is surrounded by the highly populated provinces, the water quality of the sea has gained importance for scientific and public communities over the years. This article emphasizes on the significance of detecting SST trend and corresponding anomalies of the Sea of Marmara over the past 32 years. To address the SST variations of the Sea of Marmara in time, a comprehensive set of both field and satellite data regarding SSTs were obtained within the context of this study. The SST trend and its anomalies between the years 1990 and 2021 were detected by applying Seasonal-Trend decomposition procedure based on LOESS (STL) method to NOAA OISST V2 data. On the other hand, spatial SST distribution was detected with Landsat-8, Sentinel-3 and NOAA OISST V2 satellite data. SST results were verified with the in-situ data within the scope of accuracy assessment. The results showed that SST time-series data performed an increasing trend and had anomalies mostly during the spring months in the recent years.

Sea Surface Temperature Changes Over the Twentieth and Twenty-First Centuries in East Vietnam Sea Simulated by Multi CMIP5 Models

The East ​​Vietnam Sea plays important roles in the Pacific Northwest region. The projection of changes in sea surface temperature (SST) in these regions is an important research topic in marine science. However, this is a very difficult problem due to the lack of available long-term projection data. Recently, with the development of numerical modeling technology, it has become an important way to help us understand climate change. This paper focuses on studying the SST changes in the East Vietnam Sea during the history of the 20th century and the change under 3 emission scenarios in the 21st century based on a combination of 20 global models (GCM) from Phase 5 of the the Climate Model Intercomparison Project (CMIP5) and together with the observed data set. Compared with the observed data, most of the global GCMs models can simulate well the spatial and seasonal changes of the SST over the East Vietnam Sea regions. The spatial and annual SST trends over the the 20th century based on both observations and multimodel ensemble averages show that the warming trend of SST over most of the East Vietnam Sea with the largest warming trend occurred in the center and southern regions of the East Vietnam Sea. However, compared with the observation, CMIP5 underestimated SST trends over most regions of East Vietnam Sea. In addition, there is a consistency between the CMIP5 and the spatial and seasonal observations of the SST trend in the East Vietnam Sea areas. The future SST projections for East Vietnam Sea indicate that RCP 4.5 and RCP 8.5 exhibit a gradual increase in annual SST during the 21st century at a rate of 0.1 °C and 0.3 °C per 10 years respectively. The lowest emission mitigation scenario, RCP 2.6, produces the lowest rate of warming. By the end of the 21st century, the annual SST is projected to increase by 0.5-2.0 °C in 3 emission scenarios of typical representative concentration pathways (RCP) 8.5, 4.5 and 2.6.&#x0D;

Weakly Nonlinear Ekman Pumping in the Sri Lanka Dome and Southwest Monsoon Current

Abstract The Sri Lanka Dome is a cyclonic recirculation feature in the Southwest Monsoon Current system in the southern Bay of Bengal. Cooler sea surface temperature (SST) in the vicinity of this system is often denoted as the Bay of Bengal “Cold Pool.” Although the wind shadow of Sri Lanka creates a region of strong positive wind stress curl, both sea level height dynamics and the distribution of cool SST cannot be explained by wind stress curl alone via traditional Ekman pumping. Moreover, the Cold Pool region is often aligned with the eastern portion of the Sri Lanka Dome, as defined by sea surface height. Previous work has attributed the spatial SST pattern to lateral advection. In this analysis, we explore whether low-latitude weakly nonlinear “vorticity” Ekman pumping could be an explanation for both cooling and observed changes in sea level height in the southwest Bay of Bengal. We show that weakly nonlinear upwelling, calculated from ERA5 and AVISO geostrophic currents, collocates with changes in sea level height (and presumably isopycnals). While the SST signal is sensitive to several factors including the net surface flux, regional upwelling explains changes in AVISO sea level height if the nonlinear terms are included, in both the Sri Lanka Dome and the region of the Southwest Monsoon Current.

Sea Surface Temperature Variability and Marine Heatwaves in the Black Sea

Marine heatwaves (MHWs) have recently been at the forefront of climate research due to their devastating impacts on the marine environment. In this study, we have evaluated the spatiotemporal variability and trends of sea surface temperature (SST) and MHWs in the Black Sea. Furthermore, we investigated the relationship between the El Niño–Southern Oscillation (ENSO) and MHW frequency. This is the first attempt to investigate MHWs and their characteristics in the Black Sea using high-resolution remote-sensing daily satellite SST data (0.05° × 0.05°) from 1982 to 2020. The results showed that the spatial average of the SST warming rate over the entire basin was about 0.65 ± 0.07 °C/decade. Empirical orthogonal function (EOF) analysis revealed that SST in the Black Sea exhibited inter-annual spatiotemporal coherent variability. The maximum spatial SST variability was discovered in the central Black Sea, whereas the lowest variability was in the Batumi and Caucasus anti-cyclonic eddies in the eastern Black Sea. The highest SST temporal variability was found in 1994. More than two-thirds of all MHW events were recorded in the last decade (2010–2020). The highest annual MHW durations were reported in 1994 and 2020. The highest MHW frequency was detected in 2018 (7 waves). Over the whole study period (1982–2020), a statistically significant increase in annual MHW frequency and duration was detected, with trends of 1.4 ± 0.3 waves/decade and 2.8 ± 1.3 days/decade, respectively. A high number of MHW events coincided with El Niño (e.g., 1996, 1999, 2007, 2010, 2018, and 2020). A strong correlation (R = 0.90) was observed between the annual mean SST and the annual MHW frequency, indicating that more MHWs can be expected in the Black Sea, with serious consequences for the marine ecosystem.

Sea Surface Temperature Variability and Marine Heat Waves over the Aegean, Ionian, and Cretan Seas from 2008–2021

The sea surface temperature (SST) is an important factor and indicator of the sea water quality, with various ecological and anthropogenic implications. We used high-resolution satellite-derived SST data, in tandem with field observations and long-term meteorological data, to investigate the spatial and interannual SST variability over the Aegean, Ionian, and Cretan (AIC) Seas during the recent 14-year period (2008–2021). Increasing trends were identified for most of the sub-basins of the AIC Seas. The numbers and durations (days) of the marine heat waves (MHWs) have significantly increased, especially during the last quadrennial period (2018–2021). Changes have been detected in both the maximum and minimum values; however, the trend of the mean annual values is mainly associated with the interannual increases in the lowest values (weaker minima during the cold seasons). The interannual variability and the increasing positive trends of the air temperature are very similar to the SST variations, showing a 5-to-10-day lag between the seasonal time series of the two parameters for all regions; however, extreme atmospheric events (e.g., cold fronts or heat waves) have a more direct impact on the SST variability (zero lag). MHWs were more frequent over the northern Aegean Sea, especially in Thermaikos Gulf, which is characterized as a “hot spot” for MHWs. MHWs were rarer over the southern regions, especially over the southeastern Aegean and Cretan Seas. A stratified upper ocean, controlled by buoyant brackish plumes, such as the Black Sea Waters (BSW) in the northern Aegean, may increase the heat storage capacity of the surface water masses, contributing to the further warming of the ocean. This was the case in the summer of 2021, which was a unique year for the AIC Seas, and especially for the northern Aegean, which revealed the highest SST values among all the study years. The satellite-derived observations of the 2008–2021 period showed increasing trends for all coastal waters, strong trend slopes for most of the coasts of the northern Aegean and central Ionian Seas, and milder trend slopes in the eastern Aegean.

Ocean Response to Tropical Cyclone Seroja at East Nusa Tenggara Waters

Tropical Cyclone (TC) Seroja is a unique tropical cyclone that has significant impacts along its path, such as floods in East Nusa Tenggara and high waves along the southern coast of Indonesia. Research related to ocean responses to tropical cyclones in Indonesia is still limited due to its rarely occurence in Indonesian waters. The responses of the upper ocean to TC Seroja were investigated using multi-satellite remote sensing of sea surface wind (SSW), sea surface temperature (SST), sea surface height anomaly (SSHA), and numerical model of mixed layer depth (MLD) and chlorophyll-a (Chl-a). The SST cooling occurred around the TC Seroja track at 0.5 – 3°C after the storm had passed. During April 3 – 7, 2021, in addition to spatial SST cooling, changes in chlorophyll-a, SSHA, and MLD were also detected. The chlorophyll-a increase to 2.57 mg/m3 and SSHA reached -10 cm. Thus, the MLD was deeper around the eye of the storm during the cyclone and became uniform after the storm passed. These characteristics indicate the upwelling phenomenon induced by the cyclone.

Ocean-atmosphere interactions over the western South Atlantic during Heinrich stadials

Abstract Slowdowns of the Atlantic meridional overturning circulation during Heinrich stadials (HS) caused reductions in cross-equatorial heat transport, southward shifts of the Intertropical Convergence Zone and intensification of precipitation over eastern tropical South America. While these changes are well described, the associated spatial sea surface temperature (SST) patterns are still unclear. Here, we analyze proxy data to assess changes in ocean-atmosphere interactions during HS over the western South Atlantic. Our SST proxy records show contrasting patterns between the tropical (warming) and the subtropical (no change) western South Atlantic during HS. We propose that the distinct SST behavior in the subtropics was associated with the cloud cover effect of the South Atlantic Convergence Zone over the upper ocean.

Forced and Unforced Decadal Behavior of the Interhemispheric SST Contrast during the Instrumental Period (1881–2012): Contextualizing the Late 1960s–Early 1970s Shift

AbstractThe sea surface temperature (SST) contrast between the Northern Hemisphere (NH) and Southern Hemisphere (SH) influences the location of the intertropical convergence zone (ITCZ) and the intensity of the monsoon systems. This study examines the contributions of external forcing and unforced internal variability to the interhemispheric SST contrast in HadSST3 and ERSSTv5 observations, and 10 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) from 1881 to 2012. Using multimodel mean fingerprints, a significant influence of anthropogenic, but not natural, forcing is detected in the interhemispheric SST contrast, with the observed response larger than that of the model mean in ERSSTv5. The forced response consists of asymmetric NH–SH SST cooling from the mid-twentieth century to around 1980, followed by opposite NH–SH SST warming. The remaining best-estimate residual or unforced component is marked by NH–SH SST maxima in the 1930s and mid-1960s, and a rapid NH–SH SST decrease around 1970. Examination of decadal shifts in the observed interhemispheric SST contrast highlights the shift around 1970 as the most prominent from 1881 to 2012. Both NH and SH SST variability contributed to the shift, which appears not to be attributable to external forcings. Most models examined fail to capture such large-magnitude shifts in their control simulations, although some models with high interhemispheric SST variability are able to produce them. Large-magnitude shifts produced by the control simulations feature disparate spatial SST patterns, some of which are consistent with changes typically associated with the Atlantic meridional overturning circulation (AMOC).

Temporal Variation and Spatial Structure of the Kuroshio-Induced Submesoscale Island Vortices Observed from GCOM-C and Himawari-8 Data

Dynamics of ocean current-induced island wake has been an important issue in global oceanography. Green Island, a small island located off southeast of Taiwan on the Kuroshio path was selected as the study area to more understand the spatial structure and temporal variation of well-organized vortices formed by the interaction between the Kuroshio and the island. Sea surface temperature (SST) and chlorophyll-a (Chl-a) concentration data derived from the Himawari-8 satellite and the second generation global imager (SGLI) of global change observation mission (GCOM-C) were used in this study. The spatial SST and Chl-a variations in designed observation lines and the cooling zone transitions on the left and right sides of the vortices were investigated using 250 m spatial resolution GCOM-C data. The Massachusetts Institute of Technology general circulation model (MITgcm) simulation confirmed that the positive and negative vortices were sequentially detached from each other in a few hours. In addition, totals of 101 vortexes from July 2015 to December 2019 were calculated from the 1-h temporal resolution Himawari-8 imagery. The average vortex propagation speed was 0.95 m/s. Totals of 38 cases of two continuous vortices suggested that the average vortex shedding period is 14.8 h with 1.15 m/s of the average incoming surface current speed of Green Island, and the results agreed to the ideal Strouhal-Reynolds number fitting curve relation. Combined with the satellite observation and numerical model simulation, this study demonstrates the structure of the wake area could change quickly, and the water may mix in different vorticity states for each observation station.

Subpixel variability and quality assessment of satellite sea surface temperature data using a novel High Resolution Multistage Spectral Interpolation (HRMSI) technique

A novel interpolation technique is applied to assessment of the quality of sea surface temperature (SST) observations and quantitative analysis of the subpixel variability within satellite footprints of different size. Using retrieved satellite data as input, the new, global, multistage interpolation technique generates a trigonometric polynomial, providing a representation of the underlying physical SST field in functional form. The resulting interpolating function can be efficiently and accurately evaluated anywhere within the domain over which it was derived and its moments calculated to estimate the mean and variance of the field over desired sub-regions. Application of the technique is demonstrated for SST retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS), Spinning Enhanced Visible and Infrared Imager (SEVIRI), and Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) sensors. Comparison of the functional form with the data from which it was derived demonstrates how the technique can potentially help to identify small observational artifacts such as MODIS scan striping and residual cloud contamination. Integrals of the interpolating functions over successively larger spatial scales successfully emulate the retrieved SST at the different effective spatial resolutions and the second moments are consistent with the direct sample variances, and hence representative of the spatial SST variability of the available finer-resolution observations over the coarser scales. Using the approach, the variability of 1-km-resolution SST observations on open ocean grids of both 5- and 25-km resolution is found to be ~0.07 K. In regions of sharper gradients such as associated with strong localized diurnal warming, the variability within 25-km-resolution grids increases to as much as 0.4 K for sampling at 1-km resolution. The variability of 1-km observations on a 25-km-resolution grid is about 2.4 times greater than that on a 5-km-resolution grid. Broader application of the technique globally could help better quantify regional variations in the spatial variability, which would subsequently improve uncertainty estimates for existing satellite-based SST products.

A spatiotemporal reconstruction of sea-surface temperatures in the North Atlantic during Dansgaard–Oeschger events 5–8

Abstract. Here, we establish a spatiotemporal evolution of the sea-surface temperatures in the North Atlantic over Dansgaard–Oeschger (DO) events 5–8 (approximately 30–40 kyr) using the proxy surrogate reconstruction method. Proxy data suggest a large variability in North Atlantic sea-surface temperatures during the DO events of the last glacial period. However, proxy data availability is limited and cannot provide a full spatial picture of the oceanic changes. Therefore, we combine fully coupled, general circulation model simulations with planktic foraminifera based sea-surface temperature reconstructions to obtain a broader spatial picture of the ocean state during DO events 5–8. The resulting spatial sea-surface temperature patterns agree over a number of different general circulation models and simulations. We find that sea-surface temperature variability over the DO events is characterized by colder conditions in the subpolar North Atlantic during stadials than during interstadials, and the variability is linked to changes in the Atlantic Meridional Overturning circulation and in the sea-ice cover. Forced simulations are needed to capture the strength of the temperature variability and to reconstruct the variability in other climatic records not directly linked to the sea-surface temperature reconstructions. This is the first time the proxy surrogate reconstruction method has been applied to oceanic variability during MIS3. Our results remain robust, even when age uncertainties of proxy data, the number of available temperature reconstructions, and different climate models are considered. However, we also highlight shortcomings of the methodology that should be addressed in future implementations.