Sponsored by
Sort By
The aim of the project is to build an open source PV forecast that is free and easy to use.
lang: Jupyter Notebook
stars: 154
last activity:
A Python library for computing Finite-Amplitude Local Wave Activity from climate data.
lang: Jupyter Notebook
stars: 49
last activity:
A versatile, dynamic systems-optimization modeling framework developed by the IIASA Energy, Climate, and Environment (ECE) Program since the 1980s.
lang: Jupyter Notebook
stars: 150
last activity:
Large-eddy-simulation software for urban flow, dispersion and microclimate modelling.
lang: Jupyter Notebook
stars: 85
last activity:
This Cookbook is learning-oriented to support scientific researchers using NASA Earthdata from Distributed Active Archive Centers as they migrate their workflows to the cloud.
lang: Jupyter Notebook
stars: 113
last activity:
A comprehensive benchmark dataset designed to enhance the development of machine learning models for instance segmentation of agricultural field boundaries.
lang: Jupyter Notebook
stars: 160
last activity:
Analysis framework and collection of process-oriented diagnostics for weather and climate simulations.
lang: Jupyter Notebook
stars: 80
last activity:
A collection of Python libraries for simulating the irradiation of any point on earth by the sun. It includes code for extremely precise ephemeris calculations.
lang: Jupyter Notebook
stars: 405
last activity:
Data analysis tools for working with historical PV solar time-series data sets.
lang: Jupyter Notebook
stars: 99
last activity:
A collection of scripted tools developed to inform risk analytics for the World Bank's Country Climate and Development Report risk screening activities.
lang: Jupyter Notebook
stars: 33
last activity:
An open source project and Python package that makes working with labelled multi-dimensional arrays simple, efficient, and fun.
lang: Jupyter Notebook
stars: 204
last activity:
Stands for CLIMate ADAptation and is a probabilistic natural catastrophe impact model, that also calculates averted damage (benefit) thanks to adaptation measures of any kind (from grey to green infrastructure, behavioural, etc.).
lang: Jupyter Notebook
stars: 473
last activity:
A Bayesian inference approach for using terrestrial ecosystem observations to optimize terrestrial carbon cycle model states and processes parameters.
lang: Jupyter Notebook
stars: 13
last activity:
A Python package that provides a simple way to use nighttime lights data from NASA's Black Marble project that provides a product suite of daily, monthly and yearly global nighttime lights.
lang: Jupyter Notebook
stars: 65
last activity: