Signal and noise
If you watch the temperature at one place, you see big swings: day and night, summer and winter, warm years and cool years. A gradual shift can be hidden inside that variation. Climate scientists face this problem at a planetary scale. They want to detect long-term trends, but the climate system also fluctuates on its own, in cycles of different lengths. Telling the two apart is one of the central tasks of climate research.
Climate variability means natural fluctuations in the climate system from one year, season or decade to the next. Climate change refers to longer-term shifts in the average state, including those driven by human activity. The two overlap in any dataset, and both appear in satellite records.
The best-known cycle: El Nino and La Nina
In the tropical Pacific Ocean, surface waters sometimes become warmer than average (El Nino) and sometimes cooler (La Nina), alternating irregularly every few years. The shifts affect winds and rainfall patterns and can influence weather in distant regions, such as wetter conditions in some places and drier conditions in others. Together, the cycle is often called the El Nino-Southern Oscillation.
Satellites contribute much of the observational picture. Sea surface temperature maps show the warm and cool patches. Altimeters show how sea surface height changes as warm water sloshes eastward or westward. Instruments measure rainfall, cloudiness and winds. Researchers use these to monitor each event as it develops and compare it with past events.
Effects often appear in satellite data of global quantities, too. Global average temperature tends to be a bit higher during and just after a strong El Nino and a bit lower during La Nina. Sea level changes temporarily as water is redistributed and as rainfall shifts between land and ocean. Vegetation growth in some regions rises or falls with rainfall patterns.
Other natural influences
El Nino is not the only source of variability. Others include:
- Volcanic eruptions, which can inject particles into the upper atmosphere that reflect sunlight and may cool the surface for a year or two.
- The solar cycle, an approximately eleven-year variation in solar activity, which has a small effect on the energy reaching Earth.
- Slower ocean patterns, which shift over years to decades in the Atlantic and Pacific, and may modulate regional climate.
Satellites that monitor atmospheric particles, solar output and ocean conditions help to quantify these influences.
How scientists tell trends from cycles
Several practical approaches are used.
- Long records. A cycle with a period of a few years tends to average out over several decades, while a steady drift persists. This is why continuity of observation matters.
- Statistical methods. Analysts can estimate and remove the influence of known cycles, such as El Nino, to see what remains. This is imperfect, since cycles overlap and their effects are not identical each time.
- Physical understanding and models. Climate models can be run with and without particular influences, to see what patterns each would produce.
- Multiple lines of evidence. A change seen in many independent variables, such as temperature, ice and sea level, is harder to explain by one cycle.
Why short periods can mislead
Beginning or ending a trend line on a strong El Nino or La Nina year can make a short-term trend look steeper or flatter than the underlying long-term one. Scientists therefore avoid reading much into a few years of data. For the same reason, a single cold winter or hot summer does not settle questions about long-term change, in either direction.
Why it matters
Understanding natural variability improves seasonal forecasts, which can help farmers, water managers and disaster planners prepare for a likely wet or dry season. It also keeps expectations realistic, because the path of long-term change will include pauses, bursts and regional differences. Satellite data, supported by other observations and models, remains a main tool for sorting out which changes are temporary and which are lasting.