Unidata provides data and software tools for use in geoscience education and research. NetCDF was developed and is maintained at Unidata. NetCDF is a set of software libraries and self-describing, machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data. The default for reading and writing netCDF files is netCDF4 (the capability to read and write text files, including. four dimensional latitude/longitude/altitude/time data arrays) is numpy, while the netCDF data format is commonly used in Atmospheric science and Oceanography as it is convinient to store various variables of many dimensions. The default Python library for dealing with large arrays of numeric data (e.g. Generic libraries for scientific analysis It is assumed that you have basic knowledge and understanding of statistics and Python. In addition, this tutorial also deals with different data formats such as CSV, NetCDF, Binary, and matlab'mat, etc. 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 (NiƱo 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). Main objective of this tutorial 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. Python & Practical Application on Climate Variability Studies 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. GitHub - royalosyin/Python-Practical-Application-on-Climate-Variability-Studies: This tutorial is a companion volume of Matlab versionm but add more.
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