Streamlining the Data Management Plan for the Miniaturized Laser Heterodyne Radiometer (mini-LHR)

Abstract

The objective of this project is to streamline the data management plan for the Miniaturized Laser Heterodyne Radiometer (mini-LHR) using the coding program Python to identify spectra containing methane CH4 and carbon dioxide CO2 concentrations from Earth’s atmospheric column that can be sufficiently uploaded to NASA’s Planetary Spectrum Generator (PSG). By collecting worldwide greenhouse gas emission data with the mini-LHR, scientists and citizens alike can achieve a deeper understanding of the effects of climate change and how it might vary with location and local environment. This thesis focuses in particular on a mini-LHR data set from Cabauw, Netherlands, taken in September 2021. The Cabauw data set serves as an input for the design framework of the proposed data management plan to show how this plan generates the intended output, which is a data set that is prepared to undergo further analysis in the PSG. Previously, a spectrum’s journey from extraction to the PSG was tedious and involved considerable user input. With the implementation of the following Python files, "Usable_data.py," "Outliers.py," and "Baseline.py," which serve as the foundation of this thesis, this process becomes more efficient and involves significantly less user input. Thousands of .csv files containing CH4 and CO2 concentration data from anywhere in the world can be uploaded, sorted, and polished within seconds. These three Python files successfully sorted usable and unusable data, removed outliers, and corrected the baseline of the spectra in the Cabauw data set so that 93.75% of spectra that were analyzed by the proposed data management plan were prepared to enter NASA’s PSG. In other words, out of the 592 spectra identified by the proposed data management plan, 37 were not usable. The PSG corrects for air mass, extracts mole fractions, converts the voltage reading from the raw data into wavelength, and calibrates the resulting wavelength. While it is outside the scope of this thesis, it is important to note that the data must be cross validated with the Total Carbon Column Observing Network (TCCON) before it is considered publishable.