10-day backward trajectories from ECMWF analysis data along the ship track of the Antarctic Circumnavigation Expedition in austral summer 2016/2017.

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

This dataset contains 10-day backward trajectories along the ship track of the Antarctic Circumnavigation Expedition from Nov 2016 – April 2017 calculated with the Lagrangian analysis tool LAGRANTO using the 3D-wind fields from the European Centre for Medium Range Weather Forecasts (ECMWF) operational analyses. The trajectories were started from up to 56 vertical levels between 0 and 500 hPa above sea level and various variables were interpolated along the trajectories.

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

The trajectories were calculated using the Lagrangian analysis tool LAGRANTO (Wernli and Davies, 1997; Sprenger and Wernli, 2015) using the three-dimensional wind fields from the six-hourly global operational analyses of the European Centre for Medium Range Weather Forecasts (ECMWF) and short-term forecasts in between the analysis time steps, i.e. at 03, 09, 15, 21 UTC. The ECMWF fields used for the trajectory calculations were interpolated on a regular horizontal grid of 0.5° horizontal spacing on 137 vertical levels. Up to 56 trajectories were launched every hour between the surface and 500 hPa above sea level in steps of 10 hPa, and with increased vertical resolution in the lowest 20 hPa above sea level, starting trajectories at 1, 2, 3, 4, 5, 10, 15 and 20 hPa above sea level. If the calculated pressure along the trajectories rose above the sea level pressure, the pressure was set equal to the sea level pressure such that the trajectories stayed above ground level. Various variables were interpolated along the trajectories (see data_file_header for details).

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

Timescales: Phenomena, which affect the air properties during transport, and which last at least 3 hours up to several days, can be studied with these trajectories. Furthermore, the changes in air properties and origin can be studied along the ACE track in a 1-hourly resolution.

Interpolation: It is not recommended to increase the resolution of the data.

Aggregation to lower temporal resolution: The data can be averaged to lower temporal resolution of a few days. Examples of the usage of these trajectories can, for example, be found in Schmale et al. (2019) and Thurnherr et al. (2020).

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

trajs_ACE.zip: lsl_${year}${month}${day}_${hour}, trajectory files (containing all trajectories starting at ${year}${month}${day} ${hour}UTC at the ACE track from different vertical levels), ASCII text

fig_map.zip: map_long10_${year}${month}${day}_${hour}.png, map plots of all trajectories starting at ${year}${month}${day} ${hour}UTC coloured by pressure, portable network graphics

fig_cross.zip: cross10_q_${year}${month}${day}_${hour}.png, cross-section plots of all trajectories starting at ${year}${month}${day} ${hour}UTC coloured by specific humidity, portable network graphics

data_file_header.txt, metadata for lsl-files, text

README.txt, metadata, text

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

Iris Thurnherr, Institute for Atmospheric and Climate Science, ETH Zurich, Switzerland. ORCID: 0000-0003-3647-0373. Email: iris.thurnherr@env.ethz.ch Telephone: +41 44 632 82 66
Heini Wernli, Institute for Atmospheric and Climate Science, ETH Zurich, Switzerland. ORCID: 0000-0001-9674-4837
Franziska Aemisegger, Institute for Atmospheric and Climate Science, ETH Zurich, Switzerland. ORCID: 0000-0002-4022-9825

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

This 10-day backward trajectory dataset from ACE 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 *****

Thurnherr, I., Wernli, H. and Aemisegger, F. (2020). 10-day backward trajectories from ECMWF analysis data along the ship track of the Antarctic Circumnavigation Expedition in austral summer 2016/2017. (Version 1.0) [Data set]. Zenodo. DOI: 10.5281/zenodo.4031705