nicolasfauchereau
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UCL / UK-climate-by-mp
Forked from geowillits/ucfagl1hex maps
Xarray backend to map an ECMWF style request to a service onto an XArray Dataset
A comprehensive collection of Jupyter Notebook templates for data science tasks, developed to improve workflow efficiency and cover a wide range of topics, including exploratory data analysis, hypo…
A powerful data & AI notebook templates catalog: prompts, plugins, models, workflow automation, analytics, code snippets - following the IMO framework to be searchable and reusable in any context.
A script to calculate heatwaves from AWAP
Course files for "Ocean/Atmosphere Time Series Analysis"
Sketchbook Earth: Illustrated Climate Chronicles
Repository containing the notebooks used for the forecast-based attribution analysis of the 2019 European winter heatwave.
material for ATS 655 - Objective Analysis
A Python package of algorithms and metrics used to characterise and identify jet streams, based on xarray.
Supplementary files and scripts for Nowack et al., Causal networks for climate model evaluation and constrained projections, Nature Communications (2020), https://doi.org/10.1038/s41467-020-15195-y
A collection of scripts to download ECMWF family data through the Meteorological Archival and Retrieval System (MARS) and Copernicus Climate Data Store (CDS).
Make it easy to work with the Climate Data Store api (Copernicus)
Tool for parallel retrieve of ECMWF ERA5 from the Climate Data Store
Code for paper "A Robust Generative Adversarial Network Approach for Climate Downscaling"
The Super-Resolution for Renewable Resource Data (sup3r) software uses generative adversarial networks to create synthetic high-resolution wind and solar spatiotemporal data from coarse low-resolut…
A Large-Scale Climate Model Dataset for Machine Learning
Python API to access the Copernicus Climate Data Store (CDS)
Single source of truth with requirements for pip and conda
organize data visualization output, automatically picking meaningful names based on semantic plotting variables
Code for data processing and making figures for Simpson et al (2023) A global discrepancy in atmospheric water vapor trends between models and observations.
A reactive notebook for Python — run reproducible experiments, execute as a script, deploy as an app, and version with git.