What Is Sea Surface Temperature (SST) Data?

Sea surface temperature (SST) is the measure of thermal energy at the top layer of the ocean. It is a primary variable for understanding Earth’s weather and climate because it influences the exchange of heat and moisture between the ocean and the atmosphere. Since the ocean covers approximately 71% of the planet’s surface, its temperature is a significant driver of global weather systems. The continuous collection of SST data allows scientists to track large-scale climate phenomena, forecast weather, and monitor the health of marine ecosystems.

Defining Sea Surface Temperature

The term “sea surface temperature” refers to several distinct measurements depending on the depth where the temperature is taken. These definitions are important because the ocean’s top layer has a complex thermal structure that varies with depth. Each measurement type provides a unique insight into the ocean’s thermal state and is relevant for different scientific analyses, especially when high accuracy is required.

The shallowest measurement is the ‘skin’ SST, representing the temperature at a depth of only 10 to 20 micrometers, which is measured by infrared radiometers on satellites. Just below this is the ‘sub-skin’ SST, the temperature at the base of the skin layer, which is measured by microwave radiometers.

A more common measurement is the ‘bulk’ SST, taken by thermometers on ships and buoys at depths from a few centimeters to several meters. Under strong winds and at night, the ocean’s upper layer is well-mixed, making the skin, sub-skin, and bulk temperatures similar. During calm, sunny days, however, solar radiation can create a stratified layer where temperature changes with depth, known as the diurnal thermocline. A ‘foundation’ SST measurement is taken just below this variable layer to provide a more stable reference.

Techniques for Measuring SST

SST is measured using two primary methods: in-situ techniques involving direct contact with water, and remote sensing from satellites. Historically, measurements were taken from ships, first with buckets and later with automated sensors measuring water from engine intake ports. While providing a long historical record, these ship-based measurements are concentrated along major shipping routes.

Today, much of the in-situ data comes from a global network of moored and drifting buoys. Drifting buoys move with ocean currents and measure temperature at a specific depth, while moored buoys are anchored to provide continuous data at fixed locations. The Global Drifter Program maintains a network of over 1,250 such buoys, providing broad coverage of the world’s oceans.

Since the 1980s, satellites have become the primary source for global SST data due to their extensive coverage. Satellites carry infrared (IR) radiometers that measure the ‘skin’ temperature at a high spatial resolution of 1 to 4 kilometers. A major limitation of IR sensors is that they cannot see through clouds, which absorb the infrared radiation from the ocean.

To overcome cloud cover, scientists also use microwave radiometers, which measure the ‘sub-skin’ temperature and can penetrate clouds in all weather conditions. Microwave sensors have a coarser spatial resolution, around 25 kilometers. By combining data from both infrared and microwave instruments, scientists create high-resolution, all-weather SST products.

Processing Raw Measurements into Data Products

Raw measurements from satellites and in-situ instruments require processing to become useful data products. A primary step is calibration, where raw sensor readings are converted into accurate temperature values. For satellite data, this involves comparing its measurements with highly accurate in-situ data from buoys and ships to correct for any biases.

After calibration, the data undergoes quality control to flag or remove erroneous measurements. For satellite infrared data, this includes using algorithms to detect and mask pixels contaminated by clouds. Since data comes from different locations and times, it is often interpolated to create a gridded dataset, which is a spatially complete map of SST on a regular grid.

From these gridded datasets, scientists produce various data products. A common product is the SST anomaly, which is the difference between the current temperature and a long-term average for that location and time of year, highlighting unusual warming or cooling. Another is a climatology, the long-term average SST for a particular period, used as a baseline for calculating anomalies. These processed products are then made available for a wide range of applications.

Applications of SST Data in Forecasting and Monitoring

SST data is a foundational component of modern weather forecasting. Numerical weather prediction models rely on accurate SST data as a boundary condition, as the ocean surface temperature influences the transfer of heat and moisture to the atmosphere. For example, the formation and intensification of tropical cyclones like hurricanes depend on warm ocean waters for energy.

SST data is also used to monitor large-scale phenomena that influence regional weather patterns. The El Niño-Southern Oscillation (ENSO) is a prime example, characterized by periodic warming (El Niño) and cooling (La Niña) of the equatorial Pacific. Scientists monitor SST anomalies in specific Pacific regions to track ENSO and predict its global impacts. Frontal activity, the boundary between warm and cool water masses, is another feature tracked with this data.

Beyond weather, SST data has applications in marine biology and resource management. The distribution and migration of many marine species are linked to water temperature, so fisheries managers use SST data to identify habitats for commercial species like tuna. This data is also used to monitor marine ecosystem health by identifying areas at risk of coral bleaching, which occurs when water temperatures become too high.

Observing Climate Change with SST Data

Long-term records of sea surface temperature provide clear evidence of global climate change. By analyzing historical data from ships, buoys, and satellites, scientists identify multi-decadal trends in ocean warming. These records, dating back to the 1850s, show a clear warming trend that has continued to the present day.

The rate of ocean warming has not been constant, and data shows the increase in SST has accelerated in recent decades. Between 1901 and 2023, the average global sea surface temperature rose at a rate of 0.14°F per decade. More recent data indicates that between 2019 and 2023, the rate increased to 0.27°C per decade. The Intergovernmental Panel on Climate Change (IPCC) concluded that the ocean has absorbed over 90% of the excess heat from greenhouse gas emissions since the 1970s.

This warming is not uniform across the globe, as some regions are warming faster than others. The waters around Europe, for instance, have warmed considerably, with the Black Sea seeing an increase of around 0.5°C per decade between 1991 and 2024. Analyzing SST anomalies over long periods allows scientists to distinguish the long-term climate signal from short-term natural variations.