What is the Yearly Average Observed Temperature Anomaly?

It is the difference between the average yearly global surface temperature and its pre-industrial baseline. The pre-industrial baseline is calculated as the average temperature from 1850 to 1900. It is also referred to as the observed warming.

The average temperature anomaly is a crucial metric because the change in the Earth’s average temperature is causing major transformations to our planet. It puts the existence of many species - including humans – at risk. Efforts to adapt to the impacts of global warming should consider the impacts with respect to this observed warming.

Please note that human-induced warming is the indicator that should be used to track our progress against the Paris Agreement goal of limiting global temperature increase to well below 2 °C (3.6 °F), while pursuing efforts to limit the increase to 1.5 °C (2.7 °F). For now you can find that in our Indicators for Policy Makers dashboard.

Many scientific global average temperature anomalies use a 1951 to 1980 baseline, showing anomaly values roughly 0.3 °C (0.54 °F) lower. While it is scientifically valid to choose any baseline, the global community, governments and other organizations are setting targets to limit global warming at 1.5 °C (2.7 °F) with respect to the pre-industrial baseline from 1850 to 1900.

Units and measures

Degree Celsius (°C) or degree Fahrenheit (°F) per year

Insights from this chart

Since 1850

The overall increase in the average temperature anomaly since the pre-industrial baseline is driven by human emissions of several greenhouse gases, like carbon dioxide (CO₂), methane (CH₄), nitrous oxide (N₂O) and others, which cause an increased greenhouse effect. We, i.e. humans, are still emitting more greenhouse gases and are causing more warming.

The period from 1850-1900, with relatively small blue and orange fluctuations in the chart, sets the baseline and is widely known as the pre-industrial era baseline.

Global warming already started in the 1920s. During the 1945 to 1975 period, heavy atmospheric pollution caused by humans cooled the Earth by reflecting sunlight, a process known as global dimming. The cooling effect from global dimming was reduced significantly by several global efforts to reduce air pollution.

Since the late 1970s, there has been a steady and very rapid increase in the global average temperature anomaly, with peaks in 2016 and 2020. By the end of 2023 it is likely that it will be the hottest year on record.

Last ~ 2000 Years

For a large part of the last 2000 years the global average temperature anomaly was about 0.2 °C (0.36 °F) above the 1850 to 1900 baseline. The warming of the last 100 years is very large and extremely fast compared to the long period before.

The global temperature anomaly does change over time due to natural causes, but human greenhouse gas emissions caused changes that disrupt our planet. If we, humanity, reduce our greenhouse gas emissions we can halt global warming.

About the data

For values since 1850 we primarily use data from the IGCC, which is an average of four sources: HadCRUT5, NOAAGlobalTemp, Berkeley Earth and Kadow et al.. The IGCC data updates yearly, to estimate warming for the current year the latest updates from sources are used directly. This data is gathered using a huge number of weather stations on land, ships, buoys and more.

For the years leading up to 1850 we use PAGES2k Consortium reconstruction data. It is based on models where temperatures are reconstructed from proxies. Proxy analysis has higher uncertainty, and we display the smoothed set to highlight the longer-term fluctuations.

The value for the current year is actually the average for the last 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 when using shorter time periods.

Data sources

IGCC Indicators of Global Climate Change 2022
Credits: Chris Smith, Tristram Walsh, Alex Borger, Piers Forster, Nathan Gillett, Mathias Hauser, Willam Lamb, Robin Lamboll, Matthew Palmer, Aurélien Ribes, Dominik Schumacher, Sonia Seneviratne, Blair Trewin, & Karina von Schuckmann. (2023). Indicators of Global Climate Change 2022 (v2023.06.02). Zenodo. https://doi.org/10.5281/zenodo.8000192Update cycle: yearlyDelay: up to a year

HadCRUT5 Met Office Hadley Centre
Credits: Morice, C.P., J.J. Kennedy, N.A. Rayner, J.P. Winn, E. Hogan, R.E. Killick, R.J.H. Dunn, T.J. Osborn, P.D. Jones and I.R. Simpson (in press) An updated assessment of near-surface temperature change from 1850: the HadCRUT5 dataset. Journal of Geophysical Research (Atmospheres) doi:10.1029/2019JD032361Update cycle: monthlyDelay: Less than 1 month

NOAA Global Temp. v5.1 NOAA's National Centers for Environmental Information
Credits: R. S. Vose, B. Huang, X. Yin, D. Arndt, D. R. Easterling, J. H. Lawrimore, M. J. Menne, A. Sanchez-Lugo, and H. M. Zhang (2022): NOAA Global Surface Temperature Dataset (NOAAGlobalTemp), Version 5.1 Gridded. NOAA National Centers for Environmental Information. doi.org/10.25921/2tj4-0e21.Update cycle: monthlyDelay: Less than 1 month

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 to 4 month

Kadow et al. Kadow et al.
Credits: Kadow, C., Hall, D.M. & Ulbrich, U. Artificial intelligence reconstructs missing climate information. Nat. Geosci. 13, 408–413 (2020). https://doi.org/10.1038/s41561-020-0582-5

PAGES2k Common Era Surface Temperature Reconstructions NCEI NOAA
Credits: PAGES2k Consortium: Raphael Neukom, Luis A. Barboza, Michael P. Erb, Feng Shi, Julien Emile-Geay, Michael N. Evans, Jörg Franke, Darrell S. Kaufman, Lucie Lücke, Kira Rehfeld, Andrew Schurer,Feng Zhu,Stefan Brönnimann, Gregory J. Hakim, Benjamin J. Henley, Fredrik Charpentier Ljungqvist, Nicholas McKay, Veronika Valler, Lucien von Gunten. 2019. Consistent multidecadal variability in global temperature reconstructions and simulations over the Common Era. Nature Geoscience, 12. doi: 10.1038/s41561-019-0400-0. Data accessed on May 4. 2022