Browse
Choose a species to see its shapes, sizes, structures and data files.
Browse the species one by one: open a species to download its files one at a time and to look at the structure of each aggregate. To download many files at once, a whole species or the entire database, use the Downloads section.
FilesWhat the files contain: formats, columns and units
Every curve is the cross section of one species, one shape and one size (the volume-equivalent radius of the whole grain), computed at 241 wavelengths from 1 to 25 µm in steps of 0.1 µm. Each curve is a separate file, in the formats below.
ASCII table .csv
A text file: a few header lines that start with #, then four columns separated by commas, one row per wavelength (241 rows). All values are in SI units.
| Column | Quantity | Unit |
|---|---|---|
| 1 | Wavelength | m |
| 2 | Scattering cross section | m² |
| 3 | Absorption cross section | m² |
| 4 | Extinction cross section | m² |
Mind the order: scattering comes before absorption, and extinction is last. Extinction = scattering + absorption.
# Condensate: Forsterite # Mode: compact # Number of spheres: 16 # Target Equivalent Radius: 1.0um, Monomer Sphere Radius: 0.40 um # Calculation: nptm-code np_cluster # Data format: Wavelength [m], Scattering Cross Sec[m2], Absorption Cross Sec[m2], Extinction Cross Sec [m2] 1.0000000E-06,1.2387046E-11,1.4463832E-14,1.2401509E-11 1.1000000E-06,1.3601055E-11,1.1769628E-14,1.3612825E-11
The header says which species and shape it is, how many monomers the grain has (1 for a single sphere), the equivalent radius, the radius of one monomer and the code used.
In Python: numpy.loadtxt(file, delimiter=",") gives an array of 241 rows × 4 columns (the # lines are skipped).
JSON .json
The same curve, ready for plotting, in other units: wavelength in µm and cross sections in cm² (1 m² = 10⁴ cm²).
{"label": "Mg2SiO4 compact aggregate r=1 um (16 monomers)",
"lambda_um": [1.0, 1.1, ...], // 241 values, µm
"ext": [...], "abs": [...], "sca": [...] // 241 values each, cm²
}
Structure of the grain .geo.json
Only for aggregates: where the monomers are, so that you can draw the grain.
{"monomer_um": 0.4, // radius of one monomer, µm
"radius_um": 1.0, // equivalent radius of the whole grain, µm
"positions_um": [[x, y, z], ...] // one centre per monomer, µm
}
Binary file .npz
The whole database in one file, for Python: curves as NumPy arrays grouped by species and shape, in µm and m². Its layout and the functions to read it are described inside csdb.py.
How a zip is organised
Folders species/shape/ with one file per size and format, named like forsterite_compact_r1um.csv (the number after r is the radius in µm).
Next to them: manifest.csv, one line per curve with its species, shape, radius, number of monomers, wavelength range, refractive-index source and release, and README.txt with these units.
Please cite the papers listed in Cite, the refractive-index source of each species and the release you used.