Yearly Archives: 2017

Map of the correlation between CCI SST and CCI cloud cover in the Pacific Ocean
The El Niño Southern Oscillation (ENSO) is the most important coupled ocean-atmosphere phenomenon affecting global climate variability on seasonal to inter-annual time scales. It is an irregularly periodical variation in winds and sea surface temperatures (SST) over the tropical eastern Pacific Ocean, affecting much of the tropics and subtropics: The […]

Using CCI SST and clouds for studying ENSO

 in Cloud / Sea surface temperature
Matrix of root-mean-square deviation values
An enhanced version of the Earth System Model evaluation tool (ESMValTool, Eyring et al., 2016) has been developed that exploits a subset of Essential Climate Variables (ECVs) from the European Space Agency’s Climate Change Initiative (ESA CCI) Phase 2. This version of the ESMValTool has been used to demonstrate the […]

Benchmarking CMIP models with ESA CCI data using the ESMValTool

 in Aerosols / Cloud / Greenhouse gases / Land cover / Ozone / Sea ice / Sea surface temperature / Soil moisture (updated on )
Yes please! We welcome contributions from modellers, scientists and anyone else. The CMUG data forum is a community space dedicated to users of CCI data, set up to showcase use of CCI data and to facilitate/encourage collaboration and participation by scientists and data users. To send us your ideas or suggestions, to feed […]

Can I feed back my experience using CCI data?

 in FAQ (updated on )
The data are freely available to scientists and newer versions are becoming available as they are improved over time. A key benefit is the addition of uncertainty information associated with the data which is not available elsewhere.

Do I have to pay for the data?

 in FAQ (updated on )
CMUG provides scientifically evaluated datasets and uncertainty estimates so that they can be used with confidence by the climate modelling community and other user groups. The datasets have been assessed by CMUG partners for the validation of essential climate variables (ECV) in climate models. The evaluation provides quality information to data […]

What is CMUG’s added value?

 in FAQ (updated on )
CMUG is providing an independent assessment of the CCI datasets and providing quality flags where issues are identified. This provides quantitative information on data quality, and improves confidence in their use. The data are promoted to the modelling community to encourage their use and reduce the lead time, sometimes 10-15 […]

How can scientists access and make best use of the ...

 in FAQ (updated on )
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 […]

Can you outline some of the benefits of using CCI ...

 in FAQ (updated on )