How Long-Term Averages Can Distort Our View of Sea Surface Temperatures
Introduction
Climate data often relies on long-term averages — known as "climatological baselines" — to compare current conditions against historical norms. While this is useful for spotting trends, it can also cause confusion or even unintentionally distort our understanding of real-time data. This article explores how that happens, with a focus on sea surface temperatures (SSTs) and hurricane season predictions.
What Are Long-Term Averages?
- Usually based on 30-year periods (e.g., 1981–2010 or 1991–2020)
- Used to calculate “normal” temperatures for any given region or month
- Any current reading is compared to that baseline to determine whether it’s above or below average
Why They Can Cause Confusion
Long-term averages are not static. As the climate warms, these baselines are updated — and that’s where confusion can creep in:
- Shifting baselines make past years look more extreme — If we switch to a warmer baseline, past warm years (like 2017) can appear even hotter in contrast.
- Cooler current conditions may seem normal — When compared to a newer, warmer baseline, cooler actual temperatures can look “normal” even if they are warmer than historical values.
- Two different baselines = two different stories — Depending on which climatology period is used, the same current temperature can be framed as “above normal” or “near normal.”
Example: Atlantic Hurricane Seasons in 2017 vs. 2025
Let’s look at how real sea surface temperatures can be interpreted differently depending on the long-term average used.
| Year | Actual SST | Compared to 1981–2010 | Compared to 1991–2020 |
|---|---|---|---|
| 2017 | ~26.9°C | +0.8°C above normal | +0.4°C above normal |
| 2025 | ~26.5°C | +0.4°C above normal | ~0.0°C (near normal) |
In this example:
- Using the **1981–2010 baseline**, 2025 appears warm and above average
- Using the **1991–2020 baseline**, 2025 appears normal or even slightly cool
How This Can Distort Reality
Here are some real-world impacts of using long-term averages without context:
- Underestimating short-term threats — If SSTs are "near normal" on a warm baseline, the public might not realize how favorable conditions still are for hurricanes.
- Overhyping differences — If a colder year is compared to a warmer baseline, it may be seen as cooling — even when it’s historically hot.
- Misleading graphs and reports — Some visual data representations omit which climatology is used, making it difficult to interpret true changes over time.
What Should Be Done?
To avoid confusion, climate reports and weather forecasts should:
- Always state which climatological period is used
- Include actual temperatures alongside anomalies
- Provide context when comparing years with different baselines
Conclusion and Opinion
Long-term averages are a critical tool for understanding climate trends — but they must be used carefully. Without clearly stating the baseline, it's easy to draw misleading conclusions about what’s "normal" or "extreme." Our recent comparison of 2017 and 2025 sea surface temperatures shows how two different baselines can paint very different pictures — even when the actual temperatures are only 0.4°C apart.
My take: When discussing ocean temperatures, hurricanes, or climate data in general, showing the real temperatures alongside anomalies — and being transparent about the reference baseline — is essential. It creates clarity, builds public trust, and helps avoid misinterpretations that can affect preparedness and policy.
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