Python notebooks I use for research and teaching. Please feel free to get in touch if you have any comments — even if just to say you found them useful.
Getting Started
Using BASpy to read in climate model data (CMIP5) into Xarray
Load and explore CMIP5 climate model data using BASpy, then process and visualise it with Xarray and Cartopy — including polar stereographic maps.
View notebook →Get monthly average weather station data (Global)
Extract monthly averaged temperature and precipitation records for countries of interest from the Global Historical Climatology Network – Monthly (GHCNM v3).
View notebook →Get daily average weather station data (Global)
Python tools to extract daily weather station data (temperature, precipitation) from the Global Historical Climatology Network – Daily (GHCND).
View notebook →Research
Seasonal sea ice prediction using IceNet
Deep learning for seasonal Arctic sea ice forecasting. An Environmental Data Science Book chapter demonstrating IceNet end-to-end.
Open in EDS Book ↗Creating an Amundsen Sea Low (ASL) index
Automatic detection of the Amundsen Sea Low from ERA-Interim sea-level pressure fields using a minima-finding algorithm.
View notebook →Working with the RACMO regional climate model
Analyse simulated Antarctic precipitation from the RACMO2 regional climate model using Xarray. Written jointly with Tony Phillips (BAS).
View notebook →Reading and plotting WRF data using wrf-python and Xarray
Read output from the Weather Research and Forecasting (WRF) regional climate model into Xarray for further analysis and visualisation.
View notebook →