An Open-Source Python Package to Integrate and Analyze Precipitation Datasets

Python is rapidly evolving as the primary programming language for data analysis and visualization in atmospheric science. With NASA’s Transformation to Open Science (TOPS) initiative, led NASA’s Global Precipitation Measurement (GPM) Ground Validation (GV) program to develop a python package to integrate precipitation datasets from a variety of sensors into a combined data product. The System for Integrating Multiplatform Data to Build the Atmospheric Column (SIMBA; https://gpm-gv.gsfc.nasa.gov/SIMBA) software package was developed in the Interactive Data Language (IDL), aligned with the TOPS principle. However, the license restriction to run code drawback facilitated the program to develop pySIMBA. Code is adapted from IDL to python using well-established scientific libraries Numpy, Scipy, netCDF, Xarray, Matplotlib, and Py-ART. SIMBA’s purpose is to integrate precipitation datasets from ground- and space-based radars, rain gauges, and disdrometers onto a 3-dimensional Cartesian grid. Each sensor-specific method is written to read, process, and interpolate (when applicable) native data onto a user-defined grid. The code can be readily adapted to incorporate additional instruments. In addition, plotting routines are included to visualize precipitation comparisons among the different sensors. This package allows researchers to explore myriad science applications, including collocated instrument comparisons for determining biases, evaluating precipitation processes, and validating space-based retrieval algorithms. The pySIMBA source code will be available soon on GitHub to download: https://github.com/GPM-GV.