APIs

Toolbox

Welcome to the CCI Toolbox!

The Toolbox is a python package that provides access and operations to CCI data.

It is available on GitHub and can be installed with Conda and PyPi.

Accessing CCI Data

The CCI Toolbox provides access to the datasets from the various CCI projects. It provides functionality to search for specific datasets, to describe its metadata, and to load it into an appropriate data representation, defined by Python packages xarray and geopandas.

The CCI Data is provided in three different formats which are handled by three different data stores, based on the xcube store framework:

- The CCI Open Data Portal Store(esa-cci) provides the most comprehensive access

- The CCI Zarr Data Store (esa-cci-zarr) accesses datasets that have been converted to the Zarr format for faster access. Applicable to selected datasets.

- The CCI Kerchunk Data Store (esa-cci-kc) provides Zarr views on datasets provided as collections of datasets, thereby establishing a very good compromise on the completeness of the ODP Store and the Zarr Store

Operations

The CCI Toolbox provides climate analyses operations geared to CCI data for coregistration, resampling, spatial and temporal subsetting, time series extraction, outlier detection, merging, normalising, spatial adjustment, temporal adjustment, and providing the means for operation registration. In addition, the Python packages xarray, pandas, and geopandas provide a rich and powerful low-level data processing interface for datasets opened through the CCI Toolbox. See the API reference for details.

Quick Start

The Toolbox documentation has a dedicated quick start section which provides Jupyter Notebooks on listing and searching CCI data, subsetting CCI data, accessing Zarr format CCI data, listing the operations of the CCI Toolbox, and general operations on CCI data.

If you don't want to install the Toolbox on your local machine for now, we invite you to try the ESA CCI Jupyter Lab, where you will find the latest and maintained versions of the Toolbox, notebooks, and required software. Just register for free with your email or github account.

If you'd like to explore a specific ECV project, we've made it easy for you! We've put together helpful notebooks that give you direct access to prticular datasets.

You'll find these conveniently organised in the Examples Explorer within Jupyter Lab, ready for you to dive in and explore.

Quick looks are available on this website for:

• Aerosol
• Biomass
• Cloud
• Fire
• Greenhouse Gases
• Ice Sheets
• Lakes
• Land Cover
• Land Surface Temperature
• Ocean Colour
• Ozone
• Permafrost
• Sea Ice
• Sea Level
• Sea Surface Salinity
• Sea Surface Temperature
• Snow
• Soil Moisture
• Vegetation
• Water Vapour

Of course, you can also install the Toolbox on your local machine following the steps in the next section.

Installation

Method 1 - Install Conda and then run the following

$ conda create --name ect --channel conda-forge esa-climate-toolbox
$ conda activate ect

Method 2 - Or, if you already have an existing Conda environment then just run the following with the environment activated

$ conda install --channel conda-forge esa-climate-toolbox

Method 3 - Install directly from the GitHub repository as follows

$ git clone https://github.com/esa-cci/esa-climate-toolbox.git
$ cd esa-climate-toolbox
$ conda env create
$ conda activate ect
$ pip install -e .

Method 4 - Install using pip
$ pip install esa-climate-toolbox

Getting Started

Try our Jupyter Notebooks on listing and searching CCI data, subsetting CCI data, accessing Zarr format CCI data, listing the operations of the CCI Toolbox, and general operations on CCI data.

Helpdesk

For support with the CCI Toolbox, please visit our Helpdesk.

Policy & Standards

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