A curated list of awesome Python libraries, software and resources in Atmosphere, Environment and Machine Learning

Inspired by awesome-python

• Awesome Atmosphere
  • Numerical Model
  • Data Assimilation
  • Radar
  • Satellite
  • Calculating Index
  • Data Processing/Analysis
  • Machine Learning
  • Visualization
  • Resources

• wrf-python: WRF results postprocessing
• CAMxtools: CAMx and CMAQ results postprocessing
• salem: Model results post-processing, including WRF pre/post processing
• geos2cmaq: Map GEOS-Chem results to CMAQ boundary condition
• ingest_cm1: A Fortran library to read CM1 output files
• CESM_postprocessing: Project repository for the CESM python based post-processing code, documentation and issues tracking.
• SuPy: a Python-enhanced urban climate model with SUEWS as its computation core.

• DAPPER: Data Assimilation with Python: a Package for Experimental Research (DAPPER). DAPPER enables the numerical investigation of DA methods through a variety of typical test cases and statistics.
• pyWRFDART: A collection of Python scripts for running WRF with the DART data assimilation system
• PSU_WRF_EnKF: PSU WRF Ensemble-Variational Data Assimilation System

• PyART: A data model driven interactive toolkit for working with weather radar data.
• wradlib: An open source library for weather radar data processing.
• DualPol: Python Interface to Dual-Pol Radar Algorithms.
• SingleDop: Single Doppler Retrieval Toolkit.
• ARTView: Interactive radar viewing browser.
• PyCINRAD:Decode CINRAD radar data and visualize.

• satpy: For Multiple sattlelite data product
• PyCAMA: For TROPOMI Sentinel-5P Level2 product
• pys5p: For TROPOMI Sentinel-5P Level1B product
• pyresample: resample sattlelite image

• Metpy: To calculate many of atmos index
• Sharppy: Sounding/Hodograph Analysis and Research Program
• atmos: An atmospheric sciences library for Python

• siphon: Siphon is a collection of Python utilities for downloading data from remote data services
• cfgrib: processing grib format file
• h5netcdf: Pythonic interface to netCDF4 via h5py
• PseudoNetcdf: PseudoNetCDF like NetCDF except for many scientific format backends
• netcdf4-python: python/numpy interface to the netCDF C library
• xarray: N-D labeled arrays and datasets in Python
• iris: in- memory manipulation of labeled arrays supported by the UK Met office
• PyNio: PyNIO is a multi-format data I/O package with a NetCDF-style interface
• xESMF: Universal Regridder for Geospatial Data
• esmlab-regrid: a lightweight library for regridding in Python.
• geopandas: Python tools for geographic data
• Pandas:Data structures and computational tools for working with tabular datasets
• PySAL: Python spatial analysis library
• cdat: Community Data Analysis Tools
• aospy: Python package for automated analysis and management of gridded climate data
• climlab:Process-oriented climate modeling
• CDMS:Python Object-oriented data management system for multidimensional, gridded data used in climate analysis and simulation
• eof2:EOF analysis in Python
• statsmodels:statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models
• Pysteps:an open-source Python library for probabilistic precipitation nowcasting
• QGIS:C++ GIS platform to visualize, manage, edit, analyse data, and compose printable maps

• hageleslag: Hagelslag is an object-based severe storm hazard forecasting system
• IDEA Lab: Research in data science and applied artificial intelligence/machine learning with a focus on high-impact real-world applications
• EarthML: Tools for working with machine learning in earth science
• sklearn: A Python module for machine learning built on top of SciPy.
• keras - High-level neural networks frontend for TensorFlow, CNTK and Theano.
• TensorFlow - Open source software library for numerical computation using data flow graphs.
• PyTorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
• MXNet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Go, Javascript and more.
• XGBoost - A parallelized optimized general purpose gradient boosting library.
• CatBoost - General purpose gradient boosting on decision trees library with categorical features support out of the box for R.
• LightGBM - Microsoft's fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
• hur-detect: Deep Semi-Supervised Object Detection for Extreme Weather Events.

• matplotlib: plotting with Python
• PyNGL: PyNGL ("pingle") is a Python module built on top of NCL's graphics library.
• Seaborn: Statistical data visualization using matplotlib
• Basemap: Plot on map projections (with coastlines and political boundaries) using matplotlib.
• Cartopy: Cartopy is a Python package designed to make drawing maps for data analysis and visualisation easy.
• cmaps:Make it easier to use user defined colormaps in matplotlib.Default colormaps are from NCL website.
• holoviews: make data analysis and visualization seamless and simple

• pangeo: A community platform for Big Data geoscience
• ECCO: global ocean and sea-ice state estimate tutorial.
• NMC-WFT: The R & D Center for Weather Forecasting Technology in NMC, CMA
• Python & Practical Application on Climate Variability Studies: 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 for Climate and Meteorological Data Analysis and Visualisation: Python for Climate and Meteorological Data Analysis and Visualisation.
• Example notebooks showing how to work with ECMWF services and data