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climetlab-s2s-ai-challenge

climetlab plugin to access subseasonal to seasonal (S2S) forecasts for the s2s-ai-challenge

climlab

Python package for process-oriented climate modeling

climpred

:earth_americas: Verification of weather and climate forecasts :earth_africa:

coursera_capstone-1

Repository for Coursera's IBM Applied Data Science Capstone

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

dianna

Deep Insight And Neural Network Analysis

esmvaltool

ESMValTool: A community diagnostic and performance metrics tool for routine evaluation of Earth system models in CMIP

forecast_predictability

from-0-to-research-scientist-resources-guide

Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.

github-example

Demonstration of how to create a repository and set it up

hagelslag

Hagelslag is an object-based severe storm hazard forecasting system.

innvestigate

A toolbox to iNNvestigate neural networks' predictions!

latexify_py

Generates LaTeX math description from Python functions.

lorentz_workshop

ml_tutorial_csu

material for the CSU-led machine learning tutorial for earth science research

mplotutils

helper functions for cartopy and matplotlib

nn-svg

Publication-ready NN-architecture schematics.

python-practical-application-on-climate-variability-studies

This tutorial is a companion volume of Matlab versionm but add more. Main objective is the transference of know-how in practical applications and management of statistical tools commonly used to explore meteorological time series, focusing on applications to study issues related with the climate variability and climate change. This tutorial starts with some basic statistic for time series analysis as estimation of means, anomalies, standard deviation, correlations, arriving the estimation of particular climate indexes (Niño 3), detrending single time series and decomposition of time series, filtering, interpolation of climate variables on regular or irregular grids, leading modes of climate variability (EOF or HHT), signal processing in the climate system (spectral and wavelet analysis). In addition, this tutorial also deals with different data formats such as CSV, NetCDF, Binary, and matlab'mat, etc. It is assumed that you have basic knowledge and understanding of statistics and Python.

pythonhpc_cscs

PythonHPC

r-metric

Code to calculate R-metric

rossby-wave-packets-driving-concurrent-and-non-concurrent-heatwaves-in-the-nh-and-sh

In this repository we provide the code for the plots presented in the paper: Pyrina et al., 2023

s2spy

A high-level python package integrating expert knowledge and artificial intelligence to boost (sub) seasonal forecasting

speedyweather.jl

The little sister of a big weather forecast model

tigramite

Tigramite is a time series analysis python module for causal discovery. The Tigramite documentation is at

wind-rose-diagrams

plot some win-rose diagrams using python package

xeofs

Collection of EOF analysis and related variants for climate science