We save here all the hindcast data that is used in this wave height calibration project. The initial files, just downloaded from the csiro website and pre-processed with the preprocess_csiro_datset.py file available here, have a name similar to csiro_dataframe_location.pkl, although it can be also saved as a netcdf file, as the transformation from a pandas dataframe to a xarray dataset is very straightforward (link). Below, the structure of this pandas dataframe is shown:
where the name of the variables has been modified from the ones that csiro gives to all the oceanographic data, but here, we preferred these new, more representative names:
| CalValWaves | CSIRO | Desciption | Download |
|---|---|---|---|
| Hs | hs | Significant height of wind and swell waves | Yes |
| Tm_01 | t01 | Mean period T01 | Optional |
| Tm_02 | t02 | Mean period T02 | Optional |
| Tp | 1 / fp | Wave peak frequency | Yes |
| DirM | dir | Wave mean direction | Yes |
| DirP | dp | Peak direction | Yes |
| Spr | spr | Wave directional spread | Yes |
| Nwp | pnr | Number of wave partitions | Optional |
| U10 | uwnd | Eastward wind component | Optional |
| V10 | vwnd | Northward wind component | Optional |
| Hsea | phs0 | Wave significant height partition 0 | Yes |
| Tpsea | ptp0 | Peak direction partition 0 | Yes |
| ... | ... | ... | ... |
| Hs_cal | None | This is the total Hs calculated from partitions | None |
where not all the variables are going to be used, and some variables such us the wind and its velocity (W, DirW), are calculated in the preprocess_csiro_datset.py file. Although not all the variables are used in the CalValWaves project, we recommend the download of all these variables, as they can be used in other related projects such as the DeliWaves project, where all the data used in this repository, plus the corrected hindcast, here named csiro_dataframe_location_sat_corr.pkl, which is the main goal of the work, will be used.
Moreover, two time series plots are shown, so the continuos aspect of the data can be easily seen:
