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nmc_verification

提供气象产品检验相关程序

proplot

🎨 A comprehensive matplotlib wrapper for making beautiful, publication-quality graphics

py3grads

Python 3 Interface to GrADS

pycinrad

CINRAD radar data reading and plotting

pynmic

用Python处理国家气象信息中心（NMIC）的数据

python-chinamap

使用 PyNGL 库绘制**地图

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.

python-small-examples

告别枯燥，致力于打造 Python 实用小例子

python_ncl

qiuzeng296.github.io

scikit-downscale

Statistical climate downscaling in Python

scikit-downscale-feedstock

A conda-smithy repository for scikit-downscale.

skewt

Python 3 compliant SkewT

skillmetrics

A Python library for calculating and displaying the skill of model predictions against observations.

t-n_wave-activity-flux

Python scripts for caculating the Wave-Activity Flux derived by Takaya and Nakamura (JAS,2001)

test

weather-data-clustering-using-k-means

In this notebook, I will learn how to perform k-means lustering using scikit-learn in Python. I will use cluster analysis to generate a big picture model of the weather at a local station using a minute-graunlarity data. In this dataset, I have in the order of millions records. How do I create 12 clusters out of them? NOTE: The dataset that I will use is in a large CSV file called minute_weather.csv downloaded from: https://drive.google.com/open?id=0B8iiZ7pSaSFZb3ItQ1l4LWRMTjg

website

flet.dev project website

xgrads

Parse and read ctl file commonly used by GrADS

xmca

Maximum Covariance Analysis in xarray for Climate Science