Daytime Land Temperature Anomaly
Land-surface temperature is how hot the surface of the Earth would feel to touch. From a satellite’s perspective, the “surface” is whatever it sees when it looks through the atmosphere to the ground. It could be snow and ice, the grass, a rooftop, or the treetops in a forest. An anomaly is when something is different from normal, or average. These maps show monthly daytime land-surface-temperature anomalies from March 2000 to the present, compared to the average monthly temperatures from 2001-2010 as derived using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard NASA’s Terra satellite. Places that are warmer than average are red, places that are near-normal are white, and places that are cooler than average are blue. Black means there is no data. Some land-surface-temperature anomalies are simply transient weather phenomena, not part of a specific pattern or trend. Others anomalies are more meaningful. Widespread cold anomalies may be an indication of a harsh winter with lots of snow on the ground. Isolated warm (daytime) anomalies that appear in forests or other natural ecosystems may indicate deforestation or insect damage. Many urban areas also show up as hot spots in these maps because developed areas are often warmer in the daytime than surrounding natural ecosystem or farmland.
Monthly land-surface-temperature anomaly maps, March 2000 to the present.
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Credits
Based on images by Jesse Allen, NASA’s Earth Observatory using data courtesy of the MODIS Land Group.
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Visualizers
- Marit Jentoft-Nilsen
- Jesse Allen (Sigma Space Corporation)
Release date
This page was originally published on Thursday, October 24, 2013.
This page was last updated on Monday, July 15, 2024 at 12:15 AM EDT.
Missions
This page is related to the following missions:Series
This page can be found in the following series:Datasets used
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Land Surface Temperature [Terra: MODIS]
ID: 696
Note: While we identify the data sets used on this page, we do not store any further details, nor the data sets themselves on our site.