The Weather Analysis Display (WAND) Tool: Developing a Meteorological Data Display Tool for Situational Awareness During Day-Of-Launch of Space Launch Vehicles Using Python

Abstract

Atmospheric conditions are an important driver in the design and operation of space launch vehicles. The Profile Envision and Splicing Tool (PRESTO) was developed by NASA’s Marshall Space Flight Center (MSFC) Natural Environments Branch (NE) to generate vertically complete atmospheric profiles from various data sources at NASA’s Kennedy Space Center (KSC), co-located on the United States Air Force (USAF) Eastern Range (ER), for NASA’s Space Launch System (SLS) day-of-launch (DOL) loads and trajectory analysis. PRESTO was designed solely to generate a vertically complete atmospheric profile (Orcutt et al., 2017). However, NE has also been tasked to provide a quality assessment of meteorological data examined on DOL, which goes beyond PRESTO’s utility. Thus, NE developed the Weather Analysis Display (WAND) to visualize data from all available observation systems in conjunction with climatological databases. WAND can display data from various sources in multiple ways, including Skew-T Log-P plots, time-height cross sections, and time series. WAND was developed in Python 3 taking advantage of common packages, such as NumPy for data handling, SciPy for mathematical functions, Matplotlib for data visualization, and Tkinter for the execution of the Graphical User Interface (GUI).