The NEWA Ferry Lidar Benchmark
A benchmark for mesoscale models — compare your model with a unique dataset of wind profiles along a ship track
Status
The benchmark is open for participation.
Update 6 February 2019: You can still submit results. The preliminary evaluation will be done in late February, all results received until then will be included.
Update 18 December 2018: A python script and a .csv file with the ship path is now available which can be used to or serve as a guideline how to extract the model output along the ship path: https://cloudstorage.uni-oldenburg.de/s/inzzrXqo5RW9WSi (see also section “Input data”). Furthermore we added an upload link (see section “Output data”).
Background: The NEWA Ferry Lidar Experiment
The Ferry Lidar Experiment is one of the experiments conducted as part of the New European Wind Atlas (NEWA) project.
A vertically scanning Doppler lidar was placed on a ferryboat travelling on a regular route through the Southern Baltic Sea between Kiel (Germany) and Klaipeda (Lithuania). One trip took approximately 20 hours followed by a 4 hours stopover in the harbour. During four months between February and June 2017, the Ferry Lidar continuously measured wind profiles between 65 m and 275 m above sea level along the ship track. The obtained wind profile data were corrected for ship motions (i.e. ship velocity and heading). To our knowledge this is the first dataset of wind profile measurements with lidar along such a long track.
Details about the employed ship lidar system, developed by Fraunhofer IWES, and the correction algorithm can be found in Wolken-Möhlmann et al. (2014). Further details about the NEWA Ferry Lidar Experiment can be found in the recently published article by Gottschall et al. (2018).
Motivation of the benchmark
It is common practice to evaluate mesoscale meteorological models against in-situ mast measurements of one or several met masts. With the Ferry Lidar Experiment we further develop the concept of spatially distributed wind profile measurements. The lidar moves with the ship and covers a distance that is comparable to a typical mesoscale model domain. Hence, this dataset is very suitable to be compared against meteorological mesoscale model data.
Benchmark objectives
The Ferry Lidar Benchmark is intended for mesoscale meteorological models (meso-α, meso-β scale). The objectives of the benchmark are:
- To assess how well today’s mesoscale models can reproduce the wind conditions offshore and, in particular, in the Southern Baltic Sea where quite often coastal effects are present.
- To compare different models as well as different model setups of the same model against the measurements.
- To gain experience with this unique kind of data (moving wind profiles) and explore its strengths and weaknesses.
Benchmark specifications
We plan a two-stage approach. In this first stage the participant is completely free in choosing the model setup. Use your best practice setup(s) and feel free to run more than one setup.
In a possible second stage we would prescribe part of the setup, i.e. the forcing data. This would however be announced as a separate benchmark.
The only specifications given for this first round are:
- The model domain should at least cover the full path of the ferry lidar experiment:
South-North: 54.1°N — 56.0°N
East-West: 9.8°E — 21.6°E - The time period to be simulated is at least:
6 February — 8 June 2017
Input data
As the amount of data you will generate is too large to be uploaded somewhere, you will have to extract only the data along the ship path. We provide a python script that can be used at least as guideline how to do that. The following link leads to a cloud storage folder including the python script interpolateWRF2ship.py and the text file shippath_out.csv with the ship track during the whole campaign (time, latitude, longitude): https://cloudstorage.uni-oldenburg.de/s/inzzrXqo5RW9WSi
Please note that the script is designed to work with WRF output data in a specific format. You will have to modify the script so that it can work with your output. Further remarks are given in the header of the script. If you have any questions, please write to bjoern.witha@uol.de or write a comment.
Output data
- Time series of wind speed, wind direction and temperature (optional) along the ship path (from the closest model grid point) for the duration of the campaign
- Time resolution of the output should be 30 min, all times in UTC
- Output in netCDF format including metadata (the extraction script requires it). To be submitted is then a csv file with the model output along the ship path (one location at a time) including the time variable (please indicate the time format!)
- Height levels: at least 100 m, if possible also: 65 m, 150 m, 200 m, 250 m.
- Information about the model and the setup (model evaluation questionnaire)
The output is to be uploaded to the following folder on our cloud storage server: https://cloudstorage.uni-oldenburg.de/s/kEgADfW5oCKRzmL
Please upload one zip or tar archive containing all your data and include your name and organisation in the file name.
Note that the link above is for dropping files only — you cannot see other participants’ data and they cannot see your data!
Further steps
If you want to participate but have not yet indicated that, please write an e-mail to the benchmark managers (see contact information below). It is still possible to participate.
The results have to be submitted by 24 February 2019.
We will compare the model time series with the measured time series in different heights. Furthermore vertical profiles at specific locations and/or times will be evaluated.
Preliminary results will be discussed with the participants in a dedicated webinar.
We plan to present the results of this benchmark at the Wind Energy Science Conference in Cork/Ireland in June 2019.
Contact
If you have any questions or comments, please comment below this blog post.
You might also write an e-mail to:
Björn Witha, bjoern.witha@uol.de (benchmark manager)
Martin Dörenkämper, martin.doerenkaemper@iwes.fraunhofer.de (benchmark co-manager)
Julia Gottschall, julia.gottschall@iwes.fraunhofer.de (specific questions about the experimental data)
References
Mann, J., Angelou, N., Arnqvist, J., Callies, D., Cantero, E., Chávez Arroyo, R., Courtney, M., Cuxart, J., Dellwik, E., Gottschall, J. et al. (2017): Complex terrain experiments in the New European Wind Atlas, Philos. Trans. A Math. Phys. Eng. Sci., 375, 20160101, doi: http://dx.doi.org/10.1098/rsta.2016.0101
Wolken-Möhlmann, G., Gottschall, J., Lange, B. (2014): First verification test and wake measurement results using a Ship-LIDAR System, Energy Procedia, 53, 146–155, doi: https://doi.org/10.1016/j.egypro.2014.07.223
Gottschall, J., Catalano, E., Dörenkämper, M., Witha, B. (2018): The NEWA Ferry Lidar Experiment: Measuring Mesoscale Winds in the Southern Baltic Sea, Remote Sens. 2018, 10, 1620, doi: https://doi.org/10.3390/rs10101620
