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Temperature anomaly

Temperature anomaly is a earth science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Temperature anomaly rather than just read about it. In short: Temperature anomaly is the difference, positive or negative, of a temperature from a base or reference value, normally chosen as an average of temperatures over a certain reference or base period. In atmospheric sciences, the average temperature is commonly calculated over a period of at least 30 years over a homogeneous geographic region, or globally over the entire planet.

Temperature anomaly — main illustration
Temperature anomaly — illustration

Key takeaways

  • Temperature anomaly belongs to earth science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Temperature anomaly to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Temperature anomaly from memory before moving on to harder problems.

Reference excerpt

Temperature anomaly is the difference, positive or negative, of a temperature from a base or reference value, normally chosen as an average of temperatures over a certain reference or base period. In atmospheric sciences, the average temperature is commonly calculated over a period of at least 30 years over a homogeneous geographic region, or globally over the entire planet. Temperatures are obtained from surface and offshore weather stations or inferred from meteorological satellite data. Temperature anomalies can be calculated based on datasets of near-surface and upper-air atmospheric temperatures or sea surface temperatures.

Description Temperature anomalies are a measure of temperature compared to a reference temperature, which is often calculated as an average of temperatures over a reference period, often called a base period. Records of global average surface temperature are usually presented as anomalies rather than as absolute temperatures. Using reference values computed for distinct areas over the same time period establishes a baseline from which anomalies are calculated, so that normalized data is used to more accurately compare temperature patterns to what is normal. For example, sub-global datasets may be for land-only, ocean-only, and hemispheric time series. Anomalies provide a frame of reference that allows more meaningful comparisons between locations and more accurate calculations of temperature trends. Using different base periods does not change the shape of time series charts or affect portrayal of the trends within them. For example, World Meteorological Organization (WMO) policy motivates use of a 30 year base period, whereas for conceptual simplicity a century-long base period is sometimes used to track the big-picture evolution of temperatures across the entire global surface. Different meteorological organizations have used respective base periods for global mean surface temperature datasets, such as 1951–1980 (NASA GISS and Berkeley Earth), 1961–1990 (HadCRUT U.K.), 1901–2000 (NCDC/NOAA), and 1991–2020 (Japan Met).

Standard deviation

Anomalies alone are not sufficient to characterize exceptionality of temperature values. The standard deviation—symbolized by a lower case sigma, σ—quantifies the degree of variation of a dataset's values (see coloured bands in chart at right). For example, a variation of +2 °C can be more significant over a region with normally stable temperatures than another of +3 °C from a region with normally large variability. For this purpose, anomalies are often shown as 'standardized anomalies' namely the anomaly divided by the standard deviation. To summarize: choice of reference period determines vertical placement of a trace on a graph, and deviation determines how much the trace is "stretched" in the vertical direction on the graph.

Forecasting Numerical weather prediction provides the temperature forecast for the next few days or weeks. This can be used to calculate anomalies during these forecast periods. There are two types of forecasts, deterministic and probabilistic, which will give different results. Deterministic data are values obtained by running the forecast model with initial conditions determined by the initial conditions from data assimilation. Probabilistic data comes from predicting sets where the model (or different models) is run several times with a slight variations in the initial conditions each time. Deterministic anomalies have a standard deviation which depends only on the bias of the forecast. The deviation and the probabilistic anomalies, being calculated from several model solutions, are themselves probabilities that they will occur.

See also Extreme weather Heat wave Marine heatwave

References

Illustrations

Temperature anomaly: Various global surface temperature datasets originally had different reference periods, but for meaningful comparison have been adjusted to have the same "0 °C" reference temperature. Without such an adjustment, the traces would be vertically offset from each other. Here, the "0 °C" value is determined based the average for 1850-1900—considered to be the "pre-industrial" temperature—and does not indicate an absolute measured temperature of "0 °C".
Various global surface temperature datasets originally had different reference periods, but for meaningful comparison have been adjusted to have the same "0 °C" reference temperature. Without such an adjustment, the traces would be vertically offset from each other. Here, the "0 °C" value is determined based the average for 1850-1900—considered to be the "pre-industrial" temperature—and does not indicate an absolute measured temperature of "0 °C".
Temperature anomaly: Though northern America has warmed more than its tropics, the tropics have more clearly departed from normal historical variability (coloured bands: 1σ, 2σ standard deviations).[7] The two charts have the same reference period.
Though northern America has warmed more than its tropics, the tropics have more clearly departed from normal historical variability (coloured bands: 1σ, 2σ standard deviations).[7] The two charts have the same reference period.

Worked examples

Example 1 — a first encounter with Temperature anomaly

Start with the simplest possible case. Write down what Temperature anomaly claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In earth science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Temperature anomaly before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Temperature anomaly ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Temperature anomaly

In research
Temperature anomaly appears in earth science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Temperature anomaly in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Temperature anomaly is common in secondary-school and first-year university syllabi. It links to neighbouring topics Climate history, Meteorological concepts, Temperature, so understanding it makes those chapters shorter.
In everyday life
Look for Temperature anomaly outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Temperature anomaly in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Temperature anomaly means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Temperature anomaly out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Temperature anomaly in simple terms?

Temperature anomaly is the difference, positive or negative, of a temperature from a base or reference value, normally chosen as an average of temperatures over a certain reference or base period. In atmospheric sciences, the average temperature is commonly calculated over a period of at least 30 y…

Why does Temperature anomaly matter?

Because it connects several earth science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Temperature anomaly?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Temperature anomaly.

Tags

  • Climate history
  • Meteorological concepts
  • Temperature

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