Climate Shift Index: Ocean
The Climate Shift Index: Ocean quantifies the influence of climate change on sea surface temperatures. It’s grounded in peer-reviewed attribution science and was launched by Climate Central in 2024.
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Looking for information about the influence of climate change on other types of weather? Head to the Climate Shift Index (air temperatures) or Climate Shift Index: Tropical Cyclones.
How the Climate Shift Index: Ocean works
The Climate Shift Index: Ocean (Ocean CSI) is a system that computes the climate change fingerprint on daily ocean temperatures. More specifically, it indicates how human-caused climate change (from humans burning fossil fuels) has influenced the likelihood of daily sea surface temperatures occurring at nearly any location around the world’s oceans.
The Ocean CSI scale ranges from -1000 to +1000, where positive numbers indicate sea surface temperatures that are more likely due to climate change (negative scores indicate temperatures that are less likely). Zero indicates there is no robust climate change influence on the likelihood of the temperature. For example, a value of 800 means that climate change made the observed sea surface temperature at least 800 times more likely in today’s climate.
Warming ocean temperatures impact people, weather, and ecosystems in many different ways. As a result, the Ocean CSI can help connect climate change-driven ocean warming to environmental consequences such as tropical cyclone (hurricane) intensities and rapid intensification, coral bleaching, and impacts on fisheries, wildlife migration patterns, ecosystem health, and biodiversity.
How to use the Ocean CSI
The Ocean CSI data is available for anyone to use, including but not limited to meteorologists, journalists, scientists, and policymakers. Here’s how you can see it:
Use the Ocean CSI map tool (csi.climatecentral.org/ocean) to visually identify climate fingerprints anywhere in the global ocean.
Download custom graphics directly from the map tool for TV, social media, presentations, reports, and more.
Download a KML file from the map tool that you can add directly into a Max/Baron Lynx weather system. (Learn more here.)
In addition to the Ocean CSI data, the online tool also provides maps for sea surface temperatures and temperature anomalies, and tropical cyclone storm tracks that show the influence of climate change on tropical cyclone intensities.
How Climate Central uses the Ocean CSI
We use the Ocean CSI to analyze the climate change influence on ocean warming in relation to weather events and impacts. We’ve covered how these warm ocean waters impact marine heat waves, bomb cyclones, atmospheric rivers resulting in heavy rainfall and floods, and tropical storms including cyclones and hurricanes.
Additionally, our tropical cyclone attribution system, launched in 2025, uses the Ocean CSI and new peer-reviewed methods to quantify how much stronger a storm’s winds became due to climate change-warmed waters.
How the science works
The methods underpinning the Ocean CSI are detailed in “Attributing daily ocean temperatures to anthropogenic climate change” (Giguere et al., May 2024).
To compute the Climate Shift Index: Ocean, we average the results from two complementary methods estimating how climate change has altered the frequency of a given sea surface temperature (SST).
The model-based method uses 13 climate models, each run with and without historical carbon pollution and other human emissions (including other greenhouse gasses, non-greenhouse gasses, and aerosols). At each location, we calculate the likelihood of daily sea surface temperatures across the 13 pairs of simulated climates. We then take the ratio of the SST likelihoods in model simulations with observed carbon pollution and simulations without any carbon pollution.
The observation-based method begins by calculating the likelihood of daily SST from the past 30 years of observed SST data. We then calculate how much daily SSTs at a particular location have changed in response to an increase in global mean temperature. This relationship allows us to remove the contribution of human-caused climate change, yielding an estimate of the daily SST likelihood in a climate without carbon pollution. We then take the ratio of the SST likelihoods in the observed current climate with carbon pollution and the estimated climate without any carbon pollution.
Final Climate Shift Index: Ocean estimates are derived by averaging together observation-based and model-based estimates.
Values on the scale should be interpreted as “at least that many times more likely” (or less likely, when the Index is negative). For example, an Ocean CSI value of 100 means “at least 100 times more likely.”
In order to help contextualize these values, we conservatively rounded down the raw estimated likelihoods. Ocean CSI values between 1 and 9 are rounded down to the nearest whole number. Values between 10 and 100 are rounded down to the nearest ten. Values between 100 and 1024 are rounded down to the nearest hundred. For example, if the raw value was calculated to be 536, it would show on the map as 500, meaning that temperature was made at least 500 times more likely because of climate change.
Note: The largest number labeled on the map scale is 800 (meaning "at least 800 times more likely") but values of 900 and 1000 are possible.
FAQ #
The Climate Shift Index: Ocean (also, “Ocean Climate Shift Index” or “Ocean CSI”) is based on the same scientific framework as the Climate Shift Index (Gilford, et al. (2022), but applied to sea surface temperatures rather than air temperatures.
In the Ocean CSI system, there are often levels of climate change signals that far exceed what the CSI typically measures. As a result, our scientists greatly extended the range for the Ocean CSI to be -1000 to +1000.
This is because, on a whole, the climate change-driven warming of ocean surface temperatures is more confidently identifiable than the climate change-driven warming of air temperatures over land. This is due to the following:
- The oceans absorb the vast majority of the Earth’s excess warming (more than 90%).
- There is comparatively lower variability of ocean surface temperatures day to day and year to year. This makes the signal of climate change easier to isolate.
Because the ocean surface temperatures don’t change much day to day, the warming that does appear can be strongly attributed to the long-term global warming trend.
Yes!
No, it only analyzes temperatures at the ocean’s surface.
No. It can only analyze past observed temperatures.
The sea surface temperature source data comes from OISST (Optimum Interpolation Sea Surface Temperature), and is downloaded daily at approximately 13:30 UTC. The data is typically available after a one-day delay. Additionally, the data is typically updated 14 days after initial publication when OISST data become final. Disruptions in data availability from OISST will lead to corresponding disruptions in the availability of Ocean CSI values.
Model data comes from 13 CMIP6 models. For all models that included daily sea surface temperature data, see Table 1 of Giguere et al. (2024). Analyses are based on the peer-reviewed research of Giguere et al. (2024) and Gilford et al. (2022).
Yes! Our new hurricane attribution system, the Climate Shift Index: Tropical Cyclones, uses the Ocean CSI to calculate the increase (or decrease) in a hurricane’s wind speeds because of climate change-warmed ocean waters and tropical climate warming.
We show the National Hurricane Center (NHC) observed storm tracks overlaid on the map to visualize the influence of climate change on sea surface temperatures that fuel hurricanes along their track. These tracks show the location of observation points, but do not show the size of the storm or reflect the range of its impacts.
Note that the map does not show forecast tracks. If you’re looking for forecast tracks, please rely on information from the NHC and other appropriate agencies. Because day-to-day sea surface temperature changes are frequently small, the Ocean CSI map tool may show reasonably accurate recent temperatures under forecast tracks, but forecasters should exercise judgment when combining observed data with forecast tracks.
Ahead of a landfalling tropical system: The Ocean CSI map tool can illustrate the influence of climate change on sea surface temperatures in the direct path of a storm. For example, it could be used to show that the warm water that fueled a period of rapid intensification was made much more likely by climate change.
Looking retrospectively at tropical systems: After landfall or dissipation, or on the anniversary of a tropical cyclone of note, this map tool can show the influence of climate change on sea surface temperatures along the storm track.
Investigating ocean ecosystem impacts: This system can connect the ecosystem impacts of ocean warming to climate change. For example, coral bleaching occurs when water gets too hot, and the Ocean CSI directly links unusually warm water to climate change.
Investigating above-average or extreme sea surface temperatures: The Ocean CSI can add context to temperature observations or extreme events like marine heat waves, highlighting the consequences of carbon pollution.
Ocean surface data for polar regions often includes both ice and water temperatures. Climate Central has chosen not to show data in the polar regions because it is difficult to accurately compare the temperatures of ice and water for this type of scientific calculation.
Certain areas along the coasts appear as a slate-blue color. These are regions where Climate Central does not compute an Ocean CSI value; this is because there’s a lack of alignment between the climate model data and observed ocean temperature data. Specifically, the climate models (CMIP6) used for Ocean CSI have a low resolution, meaning they provide less detailed information. In contrast, the ocean temperature data is more detailed. In areas where the detailed ocean data can't be accurately combined with the less detailed climate model data, it's not possible to provide a reliable Ocean CSI value, so the tool does not show a value.
To make sure we are accurately measuring the impact of climate change on sea surface temperatures, we use 40 years of observed OISST data to help us understand how each specific ocean location behaves on a daily basis. This helps to account for short-term randomness and natural variations, as well as longer-term trends like El Niño-Southern Oscillation (ENSO).
For more details, you can refer to Giguere et al. (2024), which explains how these steps help us confidently attribute higher sea surface temperatures to climate change instead of other causes.