ERA-5 reanalysis results interpolated onto the five-minute average cruise track of the Antarctic Circumnavigation Expedition (ACE) during the austral summer of 2016/2017.

***** Dataset abstract *****

ERA-5 fields at 1-hour temporal and grid size of  0.25° x 0.25° (0.5° x 0.5° for wave variables) have been downloaded from https://cds.climate.copernicus.eu/api/v2/resources/reanalysis-era5-single-levels
The data are interpolated using two methods:
'nearest': the value of the nearest ERA-5 grid cell is use
'linear': the values from the nearest grid cells in space and time are linearly interpolated to the [date_time, latitude, longitude] coordinate of the ship 
providing a number of atmospheric, land and oceanic climate variables interpolated along the five-minute cruise track. 

Data files: era5-on-cruise-track-5min-legs0-4-nearest.csv, era5-on-cruise-track-5min-legs0-4-linear.csv

***** Original data collection *****

The intermediate processing steps and files which take us from the input dataset (10.5281/zenodo.3772377) and the ERA-5 reanalysis to this final set of output files can be seen in the dataset presented here. This dataset is a direct output of these intermediate processing steps.

***** Data processing *****

To produce this dataset run `src/interpolate-to-shiptrack.py` after downloading the ECMWF ERA5 data using `notebooks/download-ecmwf.ipynb` and importing the ship cruise dataset at 10.5281/zenodo.3772377.

The data repository can be checked out at: https://renkulab.io/gitlab/ACE-ASAID/ecmwf-interpolation-to-cruise-track 

***** Quality checking *****

No quality measures were applied to the data.

***** Standards *****
 
This dataset does not conform to any data formats or standards. 

***** Further information for interpreting the data and using the dataset *****

Timescales: The ERA-5 reanalysis data output is provided at 1-hour temporal resolution and grid size of  0.25° x 0.25° (0.5° x 0.5° for wave variables) but may not resolve fine scale features. Here provided 5-minute resolution represents a heavy oversampling of the data.

Interpolation: Interpolation to finer resolution does not make any sense.

Aggregation to lower temporal resolution: No problem but correct vector averaging should be done.

***** Dataset contents *****

- era5-on-cruise-track-5min-legs0-4-linear.csv, data file, comma-separated values
- era5-on-cruise-track-5min-legs0-4-nearest.csv, data file, comma-separated values
- interpolate-to-shiptrack.py, processing script, text/x-python
- download-ecmwf.ipynb, processing script, application/x-ipynb+json 
- ecwmf_interpolate.zip, processing scripts, zip file
- data_file_header, metadata, text format
- README.txt, metadata, text format

***** Dataset contact *****

Michele Volpi, Swiss Data Science Center, ETH Zurich. ORCID: 0000-0003-2771-0750. Email: michele.volpi@datascience.ch

***** Dataset license *****

This interpolation of the ERA-5 reanalysis output to the five-minute averaged cruise track and velocity dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/

***** Dataset citation *****

Please cite this dataset as:
M. Volpi, S. Landwehr, J. Thomas and J. Schmale. (2020). ERA-5 reanalysis results interpolated onto the five-minute average cruise track of the Antarctic Circumnavigation Expedition (ACE) during the austral summer of 2016/2017. (Version 1.0) [Data set]. Zenodo.