Development of a Display Tool to Quality Control Weather Balloon Data for Space Launch Vehicles Using Python

The Marshall Space Flight Center (MSFC) Natural Environments Branch (EV44) performs analysis on a wide range of data from different instruments, primarily existing at NASA’s Kennedy Space Center (KSC) and the US Air Force’s Eastern Range (ER). These instruments include several types of weather balloons and Doppler Radar Wind Profiler (DRWP) systems. One application that these instruments support entails providing wind and atmospheric data for NASA’s Space Launch System (SLS) day-of-launch loads and trajectory analysis. However, data from these instruments are sometimes suspect and/or erroneous, and thus need to undergo quality control (QC) checks prior to use. EV44 has determined these methodologies to autonomously flag potentially erroneous data as part of the QC process, but the subsequent manual process of implementing said methodologies could be time-prohibitive if an efficient mechanism for examining the data is not in place. EV44 has created a tool to streamline the process of performing QC on the existing database, which enables future analyses to utilize balloon data that have undergone a standardized QC process and mitigates the need to QC data with each analysis, thus enabling one to perform analyses more efficiently. This tool was developed in Python 3.6 utilizing Pandas for its data analysis and manipulation abilities, and Tkinter for the creation of the graphical user interface. This paper describes the tool’s capabilities to visualize data and to implement various QC checks, as well as the Python code used to provide said capabilities.