Yearly Temperature Anomaly Distribution

What is the Yearly Temperature Anomaly Distribution?

This is the geographical breakdown of regional temperature anomalies around the Earth per year. Each temperature anomaly is the difference between the average yearly surface temperature and its pre-industrial baseline for that area. The pre-industrial baseline is calculated as the average temperature from 1850 to 1900.

Yearly Average Temperature Anomaly

The regional temperature anomalies on a yearly average are a result of many underlying factors:

  • Global warming: This is due to the reduction in the Earth’s outgoing energy because of the increase in crucial greenhouse gas concentrations, like carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O) and others.
  • Climate and weather patterns: These include El Niño, La Niña, currents, jet streams and more.
  • Direct solar reflection: For example, aerosols and sulfur dioxide from volcanic eruptions and pollution cool the planet by directly reflecting sunlight back into space. Similar or opposite effects can come from Earth surface changes and other phenomena.
  • Feedback loops: For instance, global warming can melt the reflective ice cover, creating an energy-absorbing ocean that reduces direct solar reflection. Many more feedback loops exist and they can be very complex.

The Yearly Temperature Anomaly Distribution is important because not all areas of the Earth are warming equally, and not all areas respond the same to the warming. For example, the polar regions are warming faster than the global average, which accelerates the ice melt. Understanding regional temperature increases will be one of many crucial factors for humanity’s ability to deal with regional and global climate change disasters.


Wikipedia: Climate change
Wikipedia: Climate
Wikipedia: Weather
Wikipedia: Instrumental temperature record

Units and measures

Degree Celsius (°C) or degree Fahrenheit (°F) per year per area. Each dot represents an area of approximately 180 km by 180 km, which is around 32,000 km².

Wikipedia: Degree Celsius

Insights from this chart

Poles

The poles are warming faster due to polar amplification. In 2012, the warming at the North Pole was extreme. In almost all years since 2000, the effect has been clearly visible.

Wikipedia: Polar amplification

Northern hemisphere

The northern hemisphere warms faster than the southern hemisphere. Different types of land cover, like ocean, land and ice, cause differences in regional warming. For example, the southern hemisphere is dominated by oceans and is warming more slowly than the northern hemisphere, which has a lot of land mass.

Greenhouse gases and global warming

Greenhouse gases cause global warming, but regional emissions do not specifically warm those regions because greenhouse gases spread quickly around the world.

Wikipedia: Greenhouse gas emissions
Earth's Energy Imbalance

Technological and scientific advancements

The year 1864 offers a good example of a year with many blank, dark areas with not enough data or confidence to calculate average temperatures. After 1950, you can see almost no blank areas, which means that the scientific confidence and technological benefits of observing our planet significantly improved.

Warm years

In 2016 and 2020, you can see some of the highest anomalies so far. These are the warmest years since the pre-industrial era and have the highest global and regional anomalies. They are full of orange, red and violet areas, representing anomalies up to 8 °C (14.4 °F). Such high levels can only be observed in the last few decades.

Cold years

The year 1904 is an example of a cold year, where the majority of the globe is colored blue.

In 1964 you can explore a rather cool year, which occurred during a period of global dimming.

Wikipedia: Global dimming

About the data

We use Berkeley Earth data, which is taken from a huge number of weather stations on land, ships, buoys and more. As explained in the insights above, the data from the earlier years have many regions with unknown values.


The value for the current year is actually the average for the last available 12 months. For example, in March we include values since the previous April. This approach allows us to include the latest data for a full year and avoids showing possibly misleading values for shorter time periods.

Data sources

Temperature Data Berkeley Earth
Credits: Rohde, R. A. and Hausfather, Z.: The Berkeley Earth Land/Ocean Temperature Record, Earth Syst. Sci. Data, 12, 3469–3479, https://doi.org/10.5194/essd-12-3469-2020, 2020.Update cycle: monthlyDelay: ~ 1 month

Elevation maps, land and water mask, earth surface textures, cloud textures Shaded Relief
Credits: Shaded Relief, Tom Patterson

Surface textures, cloud textures NASA Visible Earth
Credits: NASA