Pinned Repositories
baiquniyu.github.io
Hey Yo Dude Bismillah
dask-labextension
JupyterLab extension for Dask
ipython_ferretmagic
IPython notebook extension for ferret
Komitmen-Software-Training
Python-Practical-Application-on-Climate-Variability-Studies
This tutorial is a companion volume of Matlab versionm but add more. Main objective is the transference of know-how in practical applications and management of statistical tools commonly used to explore meteorological time series, focusing on applications to study issues related with the climate variability and climate change. This tutorial starts with some basic statistic for time series analysis as estimation of means, anomalies, standard deviation, correlations, arriving the estimation of particular climate indexes (Niño 3), detrending single time series and decomposition of time series, filtering, interpolation of climate variables on regular or irregular grids, leading modes of climate variability (EOF or HHT), signal processing in the climate system (spectral and wavelet analysis). In addition, this tutorial also deals with different data formats such as CSV, NetCDF, Binary, and matlab'mat, etc. It is assumed that you have basic knowledge and understanding of statistics and Python.
warmpool-mjo
MJO events and the code for estimating the phase duration and warm pool area as in Roxy et al. 2019, Nature, "Twofold expansion of Indo-Pacific warm pool warps MJO lifecycle"
xeofs
Collection of EOF analysis and related variants for climate science
yakh
Climate enthusiast
baiquniyu's Repositories
baiquniyu/baiquniyu.github.io
Hey Yo Dude Bismillah
baiquniyu/dask-labextension
JupyterLab extension for Dask
baiquniyu/ipython_ferretmagic
IPython notebook extension for ferret
baiquniyu/Komitmen-Software-Training
baiquniyu/Python-Practical-Application-on-Climate-Variability-Studies
This tutorial is a companion volume of Matlab versionm but add more. Main objective is the transference of know-how in practical applications and management of statistical tools commonly used to explore meteorological time series, focusing on applications to study issues related with the climate variability and climate change. This tutorial starts with some basic statistic for time series analysis as estimation of means, anomalies, standard deviation, correlations, arriving the estimation of particular climate indexes (Niño 3), detrending single time series and decomposition of time series, filtering, interpolation of climate variables on regular or irregular grids, leading modes of climate variability (EOF or HHT), signal processing in the climate system (spectral and wavelet analysis). In addition, this tutorial also deals with different data formats such as CSV, NetCDF, Binary, and matlab'mat, etc. It is assumed that you have basic knowledge and understanding of statistics and Python.
baiquniyu/warmpool-mjo
MJO events and the code for estimating the phase duration and warm pool area as in Roxy et al. 2019, Nature, "Twofold expansion of Indo-Pacific warm pool warps MJO lifecycle"
baiquniyu/xeofs
Collection of EOF analysis and related variants for climate science
baiquniyu/yakh
Climate enthusiast