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Rising temperatures are causing phenomena such as loss of sea ice and ice sheet mass, sea level rise, longer and more intense heat waves, and shifts in plant and animal habitats. Understanding such long-term climate trends is essential for the safety and quality of human life, allowing humans to adapt to the changing environment in ways such as planting different crops, managing our water resources and preparing for extreme weather events.

A separate, independent analysis by the National Oceanic and Atmospheric Administration (NOAA) concluded that 2020 was the second-warmest year in their record, behind 2016. NOAA scientists use much of the same raw temperature data in their analysis, but have a different baseline period (1901-2000) and methodology. Unlike NASA, NOAA also does not infer temperatures in polar regions lacking observations, which accounts for much of the difference between NASA and NOAA records.

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The largest source of year-to-year variability in global temperatures typically comes from the El Nino-Southern Oscillation (ENSO), a naturally occurring cycle of heat exchange between the ocean and atmosphere. While the year has ended in a negative (cool) phase of ENSO, it started in a slightly positive (warm) phase, which marginally increased the average overall temperature. The cooling influence from the negative phase is expected to have a larger influence on 2021 than 2020.

The 2020 GISS values represent surface temperatures averaged over both the whole globe and the entire year. Local weather plays a role in regional temperature variations, so not every region on Earth experiences similar amounts of warming even in a record year. According to NOAA, parts of the continental United States experienced record high temperatures in 2020, while others did not.

The GISS analysis incorporates surface temperature measurements from 6,300 weather stations, ship- and buoy-based observations of sea surface temperatures, and temperature measurements from Antarctic research stations. This raw data is analyzed using an algorithm that takes into account the varied spacing of temperature stations around the globe and urban heating effects that could skew the calculation. The result is an estimate of the global average temperature difference from a baseline period of 1951 to 1980. 17dc91bb1f