This dataset contains data generated during the measurement campaign inside the karst cave. The CO2 sensors in the cave air will continue to measure (as of Feb. 2023). For details on the site etc. see https://doi.org/10.3390/geosciences13020051 To create the graphs in the Class et al. 2023 Download cave-data.tar.xz, make sure you have the dependencies shown in requirements_paper_2022.txt. Then one can recreate the graphs by running the jupyter-notebook in that directory.

Structure of the dataset:

cave-data.tar.xz: contains the data produced during the measurement campaign. Additionally, all the figures of (todo: add paper doi) are created here. grid_const.tar.gz: contains the data generated by the grid study with constant CO2 concentration at the top. grid_data.tar.gz: contains the data generated by the grid study with measured CO2 concentration at the top 3D.tar.gz: contains data generated by the 2D and 3D comparison cave_sims.tar.gz: contains details on the simulation of the whole column. Specifically, figures and a video on the development of vortex cascades. requirements_paper_2022.txt: contains python modules for the post-processing.

The main focus of this dataset lies on the data generated in the cave. Items in cave-data.tar.xz are:

Raw_data contains the CO2(g) and pressure measurements in csv files. DWD_data contains the pressure,temperature and precipitation data from the DWD ('Deutscher Wetterdienst'). Pressure/temperature is measured in Stötten (30km apart) and precipitation is measured in Westerheim (5km apart). Control_data_temperature contains the temperature data from additional temperature sensors. This data is used for comparison only. Control_data_CO2 contains the CO2(g) data from additional CO2(g) sensors. This data is used for comparison only. Sim_data contains results from various simulations. The script Cave_measures_sim_plot.ipynb contains the code to process and visualize the data. Furthermore, the titration results are directly written into the script.

Python, 3.9