nicolasfauchereau
Climate Scientist working on scale interactions in the climate system, predictability and Machine Learning. Pythonista, Data Geek, Solarpunk.
NIWAHamilton, Aotearoa (New Zealand)
Pinned Repositories
ACRE_workshop
Climate indices and synoptic types in Python
Auckland_Cycling
An analysis of cycling counts in Auckland in relation to the weather
Auckland_Python_Workshop
Python for Climate and Meteorological Data Analysis and Visualisation
climate_data_analytics
Material (Jupyter Notebooks) for the University of Otago Climate Data and Analytics Workshop (26 May 2022)
ICU_Water_Watch
Repository for the code, notebooks and scripts for the ICU "Water Watch" (Drought monitoring and forecasting for the Southwest Pacific)
metocean
Python for ocean - atmosphere science and engineering
NIWA_Python_seminars
A series of IPython notebooks on Python for data analysis geared towards environmental sciences
Pacific_RCC
Code for the Pacific RCC ENSO tracker and other products
paleopy
implements bases classes, methods and functions for PICT (Past Interpretation of Climate Tool)
Python-for-data-analysis-and-visualisation
NIWA Scientific Python tutorial, April 2015, Wellington, New Zealand
nicolasfauchereau's Repositories
nicolasfauchereau/NIWA_Python_seminars
A series of IPython notebooks on Python for data analysis geared towards environmental sciences
nicolasfauchereau/metocean
Python for ocean - atmosphere science and engineering
nicolasfauchereau/clidesc
CLIDESC: CLImate Data for the Environment Service Client
nicolasfauchereau/wavelets
Python implementation of the wavelet analysis found in Torrence and Compo (1998)
nicolasfauchereau/cams_opi
some Python scripts and IPython notebooks to process and map CAMS / OPI precipitation data
nicolasfauchereau/eofs
EOF analysis in Python
nicolasfauchereau/FPL2015
Extra-tropical impacts of the Madden-Julian-Oscillation over New Zealand from an atmospheric circulation regime perspective
nicolasfauchereau/Kiwi_pycon
Repository for the tutorial: "Python and the pydata ecosystem for data analysis"
nicolasfauchereau/matplotlib_for_papers
Handout for the tutorial "Creating publication-quality figures with matplotlib"
nicolasfauchereau/met_data_rep
Met Data Processing
nicolasfauchereau/mjo_nz
Repository for the code (IPython notebooks and python scripts) for the paper "The impact of the MJO on New Zealand climate and circulation regimes and relationships with the Southern Annular Mode", by Nicolas Fauchereau, Benjamin Pohl and Andrew Lorrey
nicolasfauchereau/Python_NIWA_Wellington
Python tutorial, NIWA Wellington, November 2014
nicolasfauchereau/UoA_Workshop_14082014
Material for the workshop on "Using open-source software for Engineering and Science research", 14 August 2014, University of Auckland. Please scroll down to see README.
nicolasfauchereau/windspharm
A Python library for spherical harmonic computations on vector winds.
nicolasfauchereau/BasemapTutorial
A Basemap tutorial for ReadTheDocs
nicolasfauchereau/cloud-craft-python
Python demo app for 'Cloud Craft for Spatial Cadets' presentation
nicolasfauchereau/conda-recipes-scitools
Conda recipes for the SciTools binstar channel.
nicolasfauchereau/DeBaCl
Density Based Clustering (DeBaCl) Toolbox
nicolasfauchereau/fit_rain_levels
fit a function to some data relating rain to arbitrary levels
nicolasfauchereau/MeanShift_py
nicolasfauchereau/msla_data
process the MSLA data
nicolasfauchereau/notejam
The easy way to learn web frameworks
nicolasfauchereau/parallel_ml_tutorial
Tutorial on scikit-learn and IPython for parallel machine learning
nicolasfauchereau/PatternRecog
Global recognition and analysis of coastline associated rainfall using objective pattern recognition
nicolasfauchereau/pyws-BE-15-2-26
Scientific Programming in Python for Atmospheric Sciences and Climatology
nicolasfauchereau/runipy
Run IPython notebooks as command-line scripts, generate HTML reports
nicolasfauchereau/scipy2014
some demo material for the interesting libraries exposed during scipy2014
nicolasfauchereau/statsintro
Introduction to Statistics
nicolasfauchereau/supersmoother
Efficient pure Python implementation of Friedman's Supersmoother
nicolasfauchereau/waipy
This guide includes a Continuous Wavelet Transform (CWT), significance tests from based on Torrence and Compo (1998) and Cross Wavelet Analysis (CWA) based on Maraun and Kurths(2004).