XinZhou-1

3D_Plumb_flux

a500_notebooks

aostools

Helper functions for postprocessing and analysis of netCDF data. Also includes I/O routines to seamlessly work with pv_atmos.

Astus

Atmospheric_General_Circulation

Various notebooks about the Atmosheric General Circulation (radiative budget, meridional transport, zonal and transient anomalies, meridional eddy heat and momentum fluxes)

CAN2017_pyrocb_stratovortex

Cardinale-et-al-2021-JCLI

This repository hosts the python code used for Cardinale et al. (2021).

GRL-Data-Archive

notes-python

中文 Python 笔记

S2S-reforcast-retrieve

Efficiently download all the past 20 hindcast for ECMWF

XinZhou-1/S2S-reforcast-retrieve

Efficiently download all the past 20 hindcast for ECMWF

XinZhou-1/3D_Plumb_flux

XinZhou-1/Astus

XinZhou-1/Atmospheric_General_Circulation

Various notebooks about the Atmosheric General Circulation (radiative budget, meridional transport, zonal and transient anomalies, meridional eddy heat and momentum fluxes)

XinZhou-1/CAN2017_pyrocb_stratovortex

XinZhou-1/Cardinale-et-al-2021-JCLI

This repository hosts the python code used for Cardinale et al. (2021).

XinZhou-1/GRL-Data-Archive

XinZhou-1/cmip6_downloader

Simple tool written in Python to download cmip6 and (maybe) cmip5 files

XinZhou-1/ENSO_metrics

CMIP ENSO metrics python code

XinZhou-1/foto

The FOTO (Fourier Transform Textural Ordination) R package.

XinZhou-1/github-slideshow

A robot powered training repository :robot:

XinZhou-1/GJR_hist_climate_data

This is data and code used in the paper 'How well does CMIP6 capture the dynamics of Euro-Atlantic weather regimes, and why?' by Josh Dorrington, Kristian Strommen and Federico Fabiano.

XinZhou-1/glens

XinZhou-1/iv_impacts

Code and data links for Schwarzwald and Lenssen, in press at PNAS

XinZhou-1/jasmin-workshop

Materials and code for JASMIN workshops

XinZhou-1/MDTF-diagnostics

Analysis framework and collection of process-oriented diagnostics for weather and climate simulations

XinZhou-1/MEMD-Python-

Python version of the Multivariate Empirical Mode Decomposition algorithm

XinZhou-1/MHW_Drivers

Code to support publication: Holbrook et al., Nature Communications, A global assessment of marine heatwaves and their drivers.

XinZhou-1/MJO_ML

Reconstruction of historical (1905-2015) MJO indices using machine learning

XinZhou-1/ml_tutorial_csu

material for the CSU-led machine learning tutorial for earth science research

XinZhou-1/movis

Python library for video editing, presentation video generation, motion graphics, shader art coding, and other video production tasks

XinZhou-1/PyEMD

Python implementation of Empirical Mode Decompoisition (EMD) method

XinZhou-1/pySAGE

Basic python reader for SAGE II data files

XinZhou-1/pyvortex

Equivalent Latitude and polar vortex edge calculation using Nash criteria

XinZhou-1/Sentinel5P

XinZhou-1/STC

Manipulating geostationary netcdf satellite images and grib data from ECMWF

XinZhou-1/STC-CAN

Software for the processing of the data related to the 2017 British Columbia wildfire

XinZhou-1/time-series

Course files for "Ocean/Atmosphere Time Series Analysis"

XinZhou-1/WLMC_climate_time_series

This material is used in the paper: Polanco-Martínez, J.M., Fernández-Macho, J. & Medina-Elizalde, M. Dynamic wavelet correlation analysis for multivariate climate time series. Sci Rep 10, 21277 (2020). https://doi.org/10.1038/s41598-020-77767-8

XinZhou-1/XinZhou-1.github.io

XinZhou's personal websit