maartaud Goto Github PK

awesome-open-climate-science

Awesome Open Atmospheric, Ocean, and Climate Science

climate_data_science

Python for Climate Data Science

climatemodeling_courseware

A collection of interactive lecture notes and assignments in Jupyter notebook format.

climlab

Python package for process-oriented climate modeling

fortran-csv-module

Read and Write CSV Files Using Modern Fortran

gempak

Analysis and product generation for meteorological data.

hurricane-forecasting

Deep Learning for Hurricane Forecasting

intro_programming

A set of IPython notebooks and learning resources for an Introduction to Programming class, focusing on Python.

intro_to_physical_oceanography

Course materials for Introduction to Introduction to Physical Oceanography (EESC4925)

jupyter

Jupyter metapackage for installation, docs and chat

maartaud.github.io

metlib

Various meterologically relevant calculations, as well as additional utilities for visualizing data.

metpy

MetPy is a collection of tools in Python for reading, visualizing and performing calculations with weather data.

notebooks

All my notebooks.

nwp-python-jul-2021

Python scripts for the "NWP Data Acquisition, Processing and Visualization With Python" training course (INPE / CPTEC) - Jul / 2021

pangeo

Pangeo website + discussion of general issues related to the project.

pangeo-example-notebooks

Pangeo Example Notebooks

pcc

Resources for Python Crash Course, from No Starch Press.

pydata-book

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

pymt

A Python toolkit for running and coupling Earth surface models.

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.

python-workshop

A series of Jupyter Notebooks on exploring Unidata technology with Python. See website for more information.

python4oceanographers

Python lectures with oceanography examples.