January 2020 Meteorological Support Interface Control Working Group (MSICWG) Instrumentation, Data Format, and Networks Document
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James C Brenton↗
Engineering topics
James C Brenton
Publications and source records attributed to James C Brenton.
Development of a Display Tool to Quality Control Weather Balloon Data for Space Launch Vehicles Using Python
Continuous atmospheric data analysis is an important factor for space launch vehicle design and operations. The balloon quality control tool was developed by NASA’s Marshall Space Flight Center (MSFC) Natural Environments Branch (NEB) for monitoring quality control processes and verifying the automated flags created on the balloon data sets analyzed. The data sets currently analyzed are comprised of high-resolution and low-resolution balloon data from NASA Kennedy Space Center (KSC), co-located on the United States Air Force’s Eastern range (ER) at the Cape Canaveral Air Force Station. The NEB was tasked to perform a quality assessment of these data sets and needed a tool to confirm the quality control (QC) flags produced from an automated process and add additional QC flags if necessary. This Graphical User Interface (GUI) was developed to visualize all of the data from these balloon sets, display any flags from the automated QC process, and add additional flags to variables if necessary. The GUI was developed in Python 3.6 utilizing different packages available such as pandas for data analysis and manipulation, NumPy for high-performance multidimensional array and tools to compute with and manipulate arrays, Matplotlib for plotting data and Tkinter to build the GUI.
Jessica K Headley↗
Development of a Display Tool to Quality Control Weather Balloon Data for Space Launch Vehicles
Continuous atmospheric data analysis is an important factor for space launch vehicle design and operations. The balloon quality control tool was developed by NASA’s Marshall Space Flight Center (MSFC) Natural Environments Branch (NEB) for monitoring quality control processes and verifying the automated flags created on the balloon data sets analyzed. The data sets currently analyzed are comprised of high-resolution and low-resolution balloon data from NASA Kennedy Space Center (KSC), co-located on the United States Air Force’s Eastern range (ER) at the Cape Canaveral Air Force Station. The NEB was tasked to perform a quality assessment of these data sets and needed a tool to confirm the quality control (QC) flags produced from an automated process and add additional QC flags if necessary. This Graphical User Interface (GUI) was developed to visualize all of the data from these balloon sets, display any flags from the automated QC process, and add additional flags to variables if necessary. The GUI was developed in Python 3.6 utilizing different packages available such as pandas for data analysis and manipulation, NumPy for high-performance multidimensional array and tools to compute with and manipulate arrays, Matplotlib for plotting data and Tkinter to build the GUI.
Jessica K Headley↗
Quality Control Methods of Tower Data at Kennedy Space Center’s Launch Complex 39-B and the USAF Cape Canaveral 500 Foot Tower
The National Aeronautics and Space Administration (NASA) has long used meteorological data from weather towers located at Kennedy Space Center (KSC) and the United States Air Force’s Eastern Range(ER) in support of their various launch vehicles and climate studies. Some of the most valuable data is gathered at the Launch Complex 39-B (LC39-B) and the 500 foot tower located approximately two miles west of LC39-B and three miles north of the Vehicle Assembly Building (VAB). The data from LC39-B gives NASA Space Launch System (SLS) engineers valuable insight into the weather the vehicle can expect at the pad, while the 500 foot tower has a longer period of record and has been used by the Shuttle and SLS programs. However, numerous data quality (DQ) control issues have arisen when utilizing this data for analysis. In addition, instrumentation tends to deteriorate faster than normal due to the corrosive nature of the high salt content in the air. NASA’s Natural Environments branch has developed several QC databases of these towers, but these studies were for fixed periods of records. EV44 identified a need for a continually updated and QC’ed database of tower data not only to provide along term QC’ed database for vehicle and climate analyses, but also to provide the capability to investigate recent weather events such as downbursts and other high wind events. This study follows the methods developed in prior Natural Environment QC tower databases, which includes variable specific QC thresholds and checks used to generate QC flags. However, this study developed new techniques such as the development and design of the graphical user interface (GUI) for manual verification, and the creation of the final monthly QC files.
Quality Control↗
MSFC Natural Environments Tower QC, Verification GUI, and Future Work
Natural Environments (EV44) has developed a new methodology for performing quality control (QC) of tower data. The latest step reached in developing these methods is the creation of a Graphic User Interface to manually verify automated QC flags. This presentation outlines how the GUI is used to investigate QC flags and data, as well future plans for developing new QC tower databases.
James C Brenton↗