ClimateTriage - Impactful open source contributions

A software framework for supporting the efficient development, construction, execution, and scientific interpretation of atmospheric, oceanic, and climate system models.

An energy system modelling framework for investment (expansion) and dispatch (operations) optimisations using mixed-integer linear programming (MILP) - primarily for informing policy-maker & stakeholder decisions in the energy transition. Focuses on generalized & compact formulations (peer-reviewed publications) and efficient code implementation to handle large-scale problems (i.e. European) while maintaining sufficient granularity.

A framework for realistic ocean-only and coupled ocean + sea-ice simulations driven by prescribed atmospheres and based on Oceananigans and ClimaSeaIce.

Building an extensible, reproducible, test-driven, harmonised, open-source, versioned, ensemble model for air quality.

A website dedicated to organizing groups of people to clean up the world we live in. Users create cleanup events, publicize them, and recruit people to join up, as well as ask for assistance from communities and partners.

Build the world's best near-term forecasting system for solar electricity generation.

Calculates the energy consumption of Python scripts by sampling usage statistics from your hardware components.

Create and run land models in integrated or standalone modes.

An extension of xarray for climate data analysis on structured grids.

Measures, tracks, and rewards the impact on gardens with a simple Progressive Web App.

A Python package for identifiying, tracking and analysing of clouds and other meteorological phenomena in different types of gridded datasets.

Atool for running simulations of energy systems. It is written in Rust and its purpose is to provide users with a framework to simulate pathways of energy system transition. These transitions are usually in the context of climate change mitigation.

The Biorefinery Simulation and Techno-Economic Analysis Modules.

Aims to providhttps://github.com/open-energy-transition/solver-benchmarke a unified standard for understanding, quantifying, and reducing carbon emissions from an organisation's technology landscape.

Download and process GOES-16 and GOES-17 data from NOAA's archive on AWS using Python.