Climate and earth observation data is distributed across dozens of providers — each with different APIs, formats, and access mechanisms. Open Climate Service is an open-source platform that cuts through this complexity to deliver tailored data for climate-smart decision-making.
Open Climate Service brings together data about our climate, environment, and society from many different sources — to help you make informed decisions, manage risks, and adapt to climate change.
Data
Open Climate Service
Decision-making tools
Open Climate Service handles the complexity of sourcing, processing, and serving climate data — so you can focus on using it.
Data is kept current automatically. When a new day, week, or month of data is released upstream, Open Climate Service retrieves only what is missing and updates your local copy — no manual intervention required.
Deploy on your own servers, national cloud, or any infrastructure you control. No dependency on proprietary platforms. Countries retain full ownership of their data and can operate the service independently.
Climate data is aggregated to org unit boundaries and pushed directly into DHIS2, where it becomes available to the Maps App, Climate App, and the CHAP modelling platform — no manual data handling needed.
Data is published through open geospatial standards, so it is accessible to QGIS, Python, R, and any other analysis tool without custom integration. If a tool understands standard geospatial formats, it works with Open Climate Service.
Data is processed and aggregated at the temporal and spatial resolution that matters for your programme — daily, weekly, or monthly; national, district, or facility level. Derived variables and custom data sources can be added without modifying the core service.
Developed in close collaboration with HISP groups and country teams across Africa and Asia — the people who understand local data landscapes, institutional constraints, and what it takes to run a sustainable climate service in practice.
Set up Open Climate Service for your country, configure your spatial extent, and start ingesting climate data. Works via Docker or direct installation.
Setup guide →Discover and access climate datasets from a running instance. Visualise in QGIS, analyse in Python or R.
User guide →Add custom data sources, build processing workflows, or use Open Climate Service as a data backend in your own application or modelling platform.
Instance guide →