CCI Toolbox = scientific data processing algorithms
The importance of climate change has been recognized in several reports from the IPCC. To respond to this need ESA (the European Space Agency) initiated a program called the Climate Change Initiative (CCI) to provide an adequate, comprehensive, and timely response to the extremely challenging set of requirements for (highly stable) long-term satellite-based products for climate, that have been addressed to Space Agencies via the Global Climate Observing System (GCOS) and the Committee on Earth Observation Satellites (CEOS). The program consists of 14 parallel projects, each delivering climate variables (ECVs, Essential Climate Variables) derived from satellite data sets.
Simultaneously a need arose to be able to analyze and compare climate time series across different types of ECVs, as well as perform inter-comparisons with non-ESA ECV data types. Advanced users would furthermore like to apply novel processing algorithms and research methodologies consistently across different ECV types.
To address the user need for having a toolset to enable cross-comparison of multiple data sets and time series across ECV parameter types, the CCI Toolbox has been developed. The toolbox consists of a set of software tools to simplify handling, inspection, conversion, statistical processing and analysis of CCI data products, including means to combine, interrogate and exploit information across ECVs. The toolbox is developed using open source technologies, and taking advantage of already existing toolboxes within the EO (Earth Observation) and climate research community, and will be distributed openly to all users of CCI data. Furthermore, the toolbox will enable advanced users to introduce their own functionality in the form of plugins (APIs and extension points). The toolbox is open for several programming languages (Python, R, C, Java).
The various data sets are ingested into a common data model, where algorithms can be computed homogenously across data types.
The CCI Toolbox equips climate users with a means to operate across multiple ECV data sets, enabling cross-comparisons and combinations of time series. The development of the toolbox has been strongly user driven, in an iterative approach with fast release cycles beta-tested with champion users representative of the different climate communities linked with the various ECVs.