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geoffreyogutu's Projects

atlas icon atlas

Repository supporting the implementation of FAIR principles in the IPCC-WGI Atlas

calibrator icon calibrator

An R package for statistical calibration of seasonal climate forecasts

chapter-7 icon chapter-7

Figure and data generation for Chapter 7 of the IPCC's Sixth Assessment Report, Working Group 1 (plus assorted other contributions)

chapter-9 icon chapter-9

Repository with the code and data for all figures from Chapter 9 of the IPCC AR6

chapter-x icon chapter-x

Repository for allocating code used in Chapter X

chirps-stars icon chirps-stars

Exploration of CHIRPS data using R and the stars package for handling NetCDF files

climate-analysis icon climate-analysis

Code used for the analysis and visualisation of climate data during my PhD

climate_indices icon climate_indices

Climate indices for drought monitoring, community reference implementations in Python

course_files icon course_files

Course files for my textbook "A Hands-On Introduction to Using Python in the Atmospheric and Oceanic Sciences" (2012, First Edition)

ggplot2 icon ggplot2

An implementation of the Grammar of Graphics in R

gscript icon gscript

Script and script function libraries for GrADS

hyfo icon hyfo

Hydrology and Climate Forecasting R package

latexcv icon latexcv

:necktie: A collection of cv and resume templates written in LaTeX. Leave an issue if your language is not supported!

malawi-historical-climate-modelling-assessment icon malawi-historical-climate-modelling-assessment

Python scripts to evaluate the ability of various RCM (CORDEX) and GCM models to hindcast climatic variables in Malawi. Specifically Temperature (mean, max and min) and Precipitation. These scripts were created as part of a NERC funded PhD project. Erika Warnatzsch was funded by a NERC doctoral training partnership grant (NE/L002558/1).

notebooks icon notebooks

Notebooks of papers from the SantanderMetGroup

openair icon openair

Tools for air quality data analysis

pyaprp icon pyaprp

Python implementation of the Approximate Partial Radiation Perturbation method (Taylor et al., J. Climate, 2007)

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