Climate Variable

A climate variable is a physical quantity used to describe the state of the climate system: temperature, precipitation, humidity, wind, pressure, radiation, and the derived quantities built from them.

Stated that way it sounds trivial. The part that matters in practice is that a variable name is never a complete specification. “Temperature” is not a variable — 2 m air temperature, skin temperature, and mid-tropospheric temperature are different physical quantities that share a word, and confusing them is a routine source of error in comparisons between datasets.

What a full specification requires

• What is measured. Air temperature at 2 m is not surface skin temperature. The two can differ by more than 10 K over a dry surface at midday.
• Where. Height or depth, and whether it is a point, a layer, or a column integral.
• Over what interval, and how reduced. An hourly mean, a daily mean from hourly values, and a daily mean from a max-min pair are three quantities. Long station records typically use the third; models produce the second; they are compared as though equivalent more often than they should be.
• Over what area. A station measures a point; a model reports a grid-cell average. Area averages have systematically lower variance and weaker extremes, which means an apparent model bias in extremes may be entirely a scale artefact.
• Units, unambiguously. Precipitation as a rate, an accumulation, or an accumulation over an unstated interval are distinguishable only from metadata.

This is exactly the ambiguity CF conventions exist to remove. A CF standard name such as air_temperature carries a formal definition including the quantity and its context, so that two files claiming the same standard name really do hold the same thing. Community profiles like ATMODAT and the UC2 data standard extend this with domain requirements.

Essential Climate Variables

The Global Climate Observing System defines a set of Essential Climate Variables — those judged both feasible to observe globally and necessary for characterising the climate system. The list is worth knowing because it shapes what gets funded and sustained in observing systems, and therefore what long records exist to analyse decades later. It is a statement about observational priorities as much as about physics.

See also: climate for the concept these describe, climate data for how they are distributed, metadata for what has to accompany them, and precipitation for the variable with the most definitional traps.