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archer2-docs

Repository for draft ARCHER2 documentation

cmip_spreads

Code to calculate across-model spreads in CMIP fields

ecco-v4-configurations

This repository contains documentation (doc/) and model configuration files (code/, namelist/) for official releases of the ECCO version 4 ocean and sea-ice state estimates. Model configuration files allow users to reproduce the state estimate or conduct new simulation experiments.

ecco-v4-python-tutorial

This repository contains a several tutorials for using the ECCO Central Production Version 4 ocean and sea-ice state estimate. Individiual lessons are provided as both Juypter notebooks (Tutorials_as_Jupyter_Notebooks/ ) and Python file (Tutorials_as_Python_Files/).

ecco_convolve

Example notebooks to convolve ecco sensitivities with other fields

eccov4-py

A Python library with routines that support the loading, analysis, and plotting fields of the ECCO Version 4 Ocean and Sea-Ice State Estimate. The ecco_v4_py library builds on several valuable tools such as xmitgcm, gcm, xarray, and dask.

eccov4_fw_budget

gcmfaces

gcmfaces is a Matlab / Octave toolbox that handles gridded earth variables in generic fashion. Read more at:

mitgcm

mitgcm-fork

M.I.T General Circulation Model master code and documentation repository

oceanclustering

oceanclusteringmethods

Code and data to reproduce figures and classification models from Boland et al (2023) A heuristic method for detecting overfit in unsupervised classification of climate model data

python-intermediate-inflammation

A template software project for use in Intermediate Research Software Development Skills In Python course. Contact: @jag1g13

smurphs_ohc

Notebooks to reproduce figures from "Ocean Heat Content responses to changing Anthropogenic Aerosol Forcing Strength: regional and multi-decadal variability" Boland et al 2022

write-gcmfaces-adjoint

Matlab code to write MITgcm adjoint experiments on LLC grid to either nctiles or 1/2 degree interpolated netcdfs

xadjoint

Python scripts for reading and analysing adjoint sensitivities from MITgcm

xmip

Analysis ready CMIP6 data in python the easy way with pangeo tools.