JRC scientists have developed a global dataset of air temperature derived from satellites and weather stations. Their work contributes to better understanding climate monitoring and land-climate interactions.
Monitoring the status of air temperature at 2 metres above the land surface is essential for scientists to tackle climate change issues, because air temperature is a key element of all processes that guarantee life on Earth.
While weather stations regularly detect and collect air temperature records, their number is limited and their distribution scattered over the Earth surface, with a stronger concentration in developed countries, mainly USA and EU.
The resulting records are often patchy in both space and time. For this reason, scientists constantly test new methods to collect better and more complete global air temperature data.
JRC researchers recently developed an innovative method to enhance the quality of global air temperature information. By analysing the land surface temperature records collected by weather stations and detected by satellites, they developed a statistical model that can improve monthly predictions of global air temperature.
One of the novelties of this new method is how data recorded by weather stations is paired with data derived from satellite observations, based on geographic and climatic similarities. A second novelty concerns the geographical coverage of the analysis: satellites can access remote areas of the planet - such as the boreal region in the Arctic, or the Siberian plateau – whose evolution in terms of air temperature is crucial to understand trends in global temperatures. There are few weather stations in those remote areas, and those that exist generally report scarce or poor-quality information.
"Overall, our research combines the relative strengths of surface and satellite temperature records to derive a new, more complete dataset of air temperature observations" explains Gregory Duveiller, one of the co-authors of the study.
The model developed at the JRC makes use of monthly land temperature observations collected by satellites over a period of more than 15 years, from 2003 to 2016.
"The resulting dataset has the potential to improve climate monitoring and land climate interactions through a variety of applications", explains Duveiller. "We are currently using it to develop a prototype tool that can quantify the biophysical impacts of land cover change that could be useful for policymakers."
- Fecha de publicación
- 6 de noviembre de 2018