Climate data is usually presented as anomalies — differences from a long-term average — rather than absolute temperatures. Understanding why is half the skill.
1. Why plot the difference from an average instead of the temperature itself?
Answer
Because absolute temperatures vary hugely by place — a station in Iqaluit and one in Windsor cannot be averaged meaningfully. Their changes can be. Using anomalies lets thousands of stations be combined, and makes a trend of a degree visible where it would vanish inside a 60-degree range.
2. A graph of global temperature rises overall but falls in several individual years. Does a falling year contradict the trend?
Answer
No. Climate is the statistics of weather over decades. Individual years vary for reasons that have nothing to do with the long-term trend — El Niño, a volcanic eruption, ordinary noise. A trend is a statement about the shape of the whole record, and no single year can refute it.
3. Two graphs of the same data, one with a vertical axis from to and one from to , look completely different. Is either dishonest?
Answer
Neither is dishonest by itself — but the second is misleading in effect, because it compresses a real change into a flat line. The reader’s job is to check the axis before reacting to the shape. A graph’s slope means nothing until you know its scale.
4. A graph starting in 1998 — an unusually warm year — shows a flatter trend than one starting in 1970. Name the technique.
Answer
Cherry-picking the start date. Beginning at an unusually high point makes the following years look flat or falling. The test is simple: does the claim survive if you move the start date a few years either way? If not, the claim is about the choice of start date, not about the climate.
5. Which indicator from Indicators of Climate Change would be hardest to misrepresent this way?
Answer
Sea level and ice mass are strong answers: both change slowly and in one direction, so a cherry-picked window still shows the trend. Year-to-year temperature is the easiest to distort, because it is the noisiest.
The skill being practised
Not “is this graph true?” but “what is this graph for, and what has it left out?” That question is the whole of the scientific literacy expectation.