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- Title:
Lunar Hydrogen Exosphere Predictions
- Document type:
- Forschungsdaten
- Publication date:
- 15.09.2022
- Responsible:
- Smolka, Alexander
- Authors:
- Smolka, Alexander ; Nikolic, Dragan ; Gscheidle, Christian ; Reiss, Philipp
- Author affiliation:
- TUM
- Publisher:
- TUM
- Identifier:
- doi:10.14459/2022mp1686124
- End date of data production:
- 22.08.2022
- Subject area:
- DAT Datenverarbeitung, Informatik; MAT Mathematik; NAT Naturwissenschaften (allgemein)
- Other subject areas:
- Space Science
- Resource type:
- Simulationen / simulations
- Data type:
- Tabellen / tables
- Description:
- "Smolka2022 - Lunar Hydrogen Exosphere Predictions" The dataset contains the three subfolders "mean_loss", "mean_surface_number_density", and "raw_julia". The first two folders contain eight CSV files, one for each of the eight performed studies, which list the empirical mean value over all (4000) Monte-Carlo steps for the losses and the surface number densities, respectively. The losses are given as globally lost particles per second, sorted by the loss mechanism (rows) and the elements H, H2, OH, and H2O (columns). The surface number densities are given as particles per cubic centimeters at the numerical grid points, which are supplied in the form of local time (first column) and subsolar latitude (second column). The used numerical grid is a structured grid with 180 points along the local time and 45 points along the latitude, which discretizes the upper hemisphere, assuming equatorial symmetry. The last folder "raw_julia" contains the compressed Julia data of all Monte-Carlo steps, in ".jld2" format. These can be extracted using the "JLD2" package with the command "jldopen( < path > .jld2)".
- Method of data assessment:
- Data generated by the Julia based Monte-Carlo simulation model.
- Links:
- This dataset relates to the publication: https://www.sciencedirect.com/science/article/abs/pii/S0019103523000854?dgcid=author
- Key words:
- Moon, Exosphere, Simulation, Density, Hydrogen, Water
- Technical remarks:
- View and download (7,5 GB total, 33 Files)
The data server also offers downloads with FTP
The data server also offers downloads with rsync (password m1686124):
rsync rsync://m1686124@dataserv.ub.tum.de/m1686124/ - Language:
- en
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