Vertical profiles and integrated time series of bird density and flight speed vector (19.09.2016-10.10.2016)

Description

This dataset contains the vertical profiles and integrated time series of bird density and flight speed (NS and EW) used in Nussbaumer (2019) [open access: https://www.mdpi.com/2072-4292/11/19/2233]. Data are stored in a JavaScript Object Notation (JSON) file for each radar, with the following structure:

{
   "name"     : "bejab", //code name of the radar (http://eumetnet.eu/wp-content/themes/aeron-child/observations-programme/current-activities/opera/database/OPERA_Database/index.html)
   "lat"      : 51.1917, //Latitude
   "lon"      : 3.0642, //Longitude
   "height"   : 50, //Height of the radar antenna [m] a.s.l.
   "maxrange" : 25, //Maximum range [km] used for profile
   "alt"      : [100, 300,...],
   "time"     : ["19-Sep-2016 00:00:00", "19-Sep-2016 00:05:00",...],
   "dens"     : [[...],...], //Vertical profile of bird density [1/km3]
   "u"        : [[...],...], //Vertical profile of bird flight speed in East(+)/West(-) [m/s]
   "v"        : [[...],...], //Vertical profile of bird flight speed in North(+)/South(-) [m/s]
   "denss"    : [...], //Integrated profile of bird density [1/km2]
   "us"       : [...], //Integrated profile of bird flight speed in East(+)/West(-) [m/s]
   "vs"       : [...], //Integrated profile of bird flight speed in North(+)/South(-) [m/s]
}

Procedure

The raw data are downloaded on the ENRAM repository,( see Dokter (2011) and (2019) for more details) and processed according to the procedure described below.

1. Of the 84 radars contributing data during the study period, 11 radars are discarded because of their poor quality due to S-band radar type, poor processing or large gaps (temporal or altitude cut). The same radars were removed in Nilsson et al. (2019).In addition, the 4 radars from Bulgaria and Portugal were excluded because of their geographic isolation.
2. The full vertical profile was discarded when rain was present at any altitude bin. A dedicated MATLAB GUI was used to visualise the data and manually set bird densities to “not-a-number” in such cases. 
3. Zones of high bird densities can sometimes be incorrectly eliminated in the raw data. To address this, Nilsson et al. (2019) excluded problematic time or height ranges from the data. Here, in order to keep as much data as possible, the data was manually edited to replace erroneous data either with “not-a-number”, or by cubic interpolation using the dedicated MATLAB GUI.
4. Due to ground scattering,the lower altitude layers are sometimes contaminated by errors or excluded in the raw data. We vertically interpolated bird density by copying the first layer without error into to the lower ones. This approach is relatively conservative as bird migration intensity usually decreases with height in the absence of obstacles, and more so in autumn (Bruderer, 2018)
5. The vertical profiles are vertically integrated from the radar altitude and up to 5000 m asl.
6. The data recorded during daytime are excluded. Daytime is defined at each radar by the civil dawn and dusk (6° below horizon).
7. Finally, the data of 10 radars with high temporal resolution (5-10minutes) was down-sampled to 15 minutes to preserve a balanced representation of each radar.

The resulting cleaned vertical-integrated time series of nocturnal bird density can be viewed in vp_corrected.zip.

More details and illustrations are available in Nussbaumer (2019) [open access: https://www.mdpi.com/2072-4292/11/19/2233], 

Acknowledgement

We acknowledge the European Operational Program for Exchange of Weather Radar Information (EUMETNET/OPERA) for providing access to European radar data, faciliated through a research-only license agreement between EUMETNET/OPERA members and ENRAM.

References

Bruderer, B.; Liechti, F. Variation in density and height distribution of nocturnal migration in the south of israel. Israel Journal of Zoology 1995, 41, 477–487. doi:10.1080/00212210.1995.10688815.

Dokter A. M. , F. Liechti, H. Stark, L. Delobbe, P. Tabary, and I. Holleman, “Bird migration flight altitudes studied by a network of operational weather radars,” J. R. Soc. Interface, vol. 8, no. 54, pp. 30–43, Jan. 2011. doi:10.1098/rsif.2010.0116

Dokter A. M. , P. Desmet, J. H. Spaaks, S. van Hoey, L. Veen, L. Verlinden, C. Nilsson, G. Haase, H. Leijnse, A. Farnsworth, W. Bouten, and J. Shamoun‐Baranes, “bioRad: biological analysis and visualization of weather radar data,” Ecography (Cop.)., vol. 42, no. 5, pp. 852–860, May 2019. doi: 10.1111/ecog.04028

Nilsson, C.; Dokter, A.M.; Verlinden, L.; Shamoun-Baranes, J.; Schmid, B.; Desmet, P.; Bauer, S.; Chapman, J.; Alves, J.A.; Stepanian, P.M.; Sapir, N.;Wainwright, C.; Boos, M.; Górska, A.; Menz, M.H.M.; Rodrigues, P.; Leijnse, H.; Zehtindjiev, P.; Brabant, R.; Haase, G.; Weisshaupt, N.; Ciach, M.; Liechti, F. Revealing patterns of nocturnal migration using the European weather radar network. Ecography 2019, 42, 876–886. doi:10.1111/ecog.04003.

Nussbaumer R., L. Benoit, G. Mariethoz, F. Liechti, S. Bauer, and B. Schmid, “A Geostatistical Approach to Estimate High Resolution Nocturnal Bird Migration Densities from a Weather Radar Network,” Remote Sens., vol. 11, no. 19, p. 2233, Sep. 2019. doi: 10.3390/rs11192233