Can you outline some of the benefits of using CCI datasets?


Satellite data aren’t always optimally processed and may contain jumps (discontinuities), erroneous data or have other issues. CMUG is re-processing the data to produce datasets useful for climate studies.

CMUG is evaluating a set of essential climate variables (ECVs; defined by GCOS) which were identified by climate scientists as key for climate research. They are as follows (in bold = ECVs introduced in phase 3 of the project).

  • Marine
    • Sea ice, sea level, sea state, sea surface temperature, sea surface salinity, ocean colour
  • Terrestrial
    • Land cover, high-resolution land cover, lakes, land surface temperature, soil moisture, fire, biomass, permafrost, snow, glaciers, ice sheets (Greenland and Antarctica)
  • Atmosphere
    • Cloud, aerosol, ozone, greenhouse gases, water vapour

Examples of their use include ozone climate data record, profiles and total column, which are being used in a reanalysis models by ECMWF and other numerical weather prediction modelling centres. This is the most accurate record we have of global ozone.

Another example is the glacier dataset. The glacier team is using CCI data to map changes in the area, thickness and extent of glaciers over time, providing a clear record of changes over the last 15 years compared with the pre-satellite record.

Sea level data provides a very clear indication of sea level rise over the last two decades associated with climate change.

Artificial image of the Earth surrounded by the symbols of the essential climate variables
Some of the CMUG essential climate variables: glaciers, land cover, soil moisture, fire, ice sheets, sea ice, sea surface temperature, ocean colour, sea level, ozone, greenhouse gases, cloud, aerosols.