Smoothing and inter/extrapolating gps coordinates #253
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+ some renaming + moving some necessary steps (like directional wind speed calculation to the L1toL2 step
- `calcHumid` renamed to `calcSpHumid` for clarity - `cleanHeatFlux` and `cleanSpHumid` were just removing NaNs, so it is now done at the end of `calcHeatFlux` and `calcSpHumid` - `rho_atm`, `nu` were only used in `calcSpHumid` so they are calculated inside the function rather than outside
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Jun 4, 2024
BaptisteVandecrux
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This PR builds on top of #251. It:
toL3on that L2 file within which the GPS latitude, longitude and altitude are post-processed into smooth, gapg-free seriesThis is done by:
finding breaks in the available GPS coordinates which correspond to station maintenance. The smoothing and interpolation will be done separately for each interval between maintenance so that station relocation is not smoothed.
For each interval, we apply 1) a LOWESS (Locally Weighted Scatterplot Smoothing) to the each coordinate; 2) an internal linear interpolation between the available smoothed coordinates and 3) a linear extrapolation of the result to the next maintenance, to the latest timestamp or backward in time if necessary.
For stations where no GPS data is available, the static value contained as an attribute in the aws-l2 data file is given to each timestamp
The result are six variables:
lat,lon,altthe smoothed and gapless time-dependent coordinates for each stationslat_avg,lon_avg,alt_avgthe mean value of the previous three variables that can be given as attribute in thre netcdf files and potentially in theAWS_metadata.csvfile distributed with the dataset.