As with all countries in the agreement, PVOL data (if available) are processed by BALTRAD to VPTS data. Those VPTS data are subsequently synchronized to the Aloft data portal. See Desmet et al. (2025) for more information on the process. Note that the presence and quality of biological signals has not been evaluated. Data became available on 2025-12-09 for most of the new countries.

Additional countries

You can explore the new data in CROW. We also enabled access to new radars from existing countries (dksam, ptflr, ptsmg, sevax) (aloftdata/crow#21).

Radar metadata update

As part of this update, we synchronized radar metadata from the source files maintained by OPERA (aloftdata/aloftdata.eu#22). Five radar stations have changed codes:

See Table 2 in Desmet et al. (2025) for previous code changes.

Data access

Use the getRad R package to access the new data and metadata. As always, beware of the caveats.

library(getRad)
library(dplyr, warn.conflicts = FALSE)

# Get VPTS data
get_vpts(radar = "robar", datetime = "2026-02-01", source = "baltrad")
#>                    Irregular time series of vertical profiles (class vpts)
#> 
#>            radar:  robar 
#>       # profiles:  263 
#> time range (UTC):  2026-02-01 00:00:00 - 2026-02-01 21:45:00 
#>    time step (s):  min: 0     max:  900

# Get radar metadata
wr <- get_weather_radars()
wr |> filter(country == "Romania") |> select(radar, location)
#> # A tibble: 8 × 3
#>   radar location             geometry
#>   <chr> <chr>             <POINT [°]>
#> 1 robar Barnova   (27.58255 47.01184)
#> 2 romed Medgidia  (28.25059 44.24336)
#> 3 robob Bobohalma (24.22523 46.36022)
#> 4 rotim Timisoara (21.25773 45.77174)
#> 5 roora Oradea    (21.94289 47.09218)
#> 6 robuc Bucuresti (26.07735 44.51267)
#> 7 rocra Craiova   (23.86743 44.31029)
#> 8 roopa Oradea          (21.94 47.09)

Insect flights observed by the Finnish weather radar network on 21 July 2025.

The weather-radar based monitoring products use the polarimetric echo classification developed by FMI to extract insect and bird signals from the radar data pool. Data products include densities and flight directions of insects and birds, as well as bird migration traffic rates and migration calendars for 114 bird species derived from citizen science observations.

An example of the bird migration forecast on 3 July 2025 on the ILMU website.

The bird migration model is directly linked with operational numerical weather forecasts and predicts bird migration of 114 species two day ahead in a 10-km grid. Migration phenology is derived from bird observations from the Finnish bird portal Tiira maintained by BirdLife Finland. Bird migration dynamics are shaped by a number of meteorological and behavioural factors.

The website implements work from the Biodiversa projects GloBAM and HiRAD and it received further support by the Nessling foundation and the Finnish Ecosystem Observatory.

Visit the ILMU website

Researchers from the University of Amsterdam animal movement ecology group presented the “Grote Amsterdamse Vogel Spel” (the Big Amsterdam Bird Game): five interactive games about birds. In these games hunderds of participants learned about bird migration, foraging strategies, and how radars are used to study the responses of birds to wind turbines and fireworks.

birdscanR

For the birdscanR R package, a website and readme were created, and continuous testing was implemented. Furthermore, a function to construct a vertical profile time series was implemented, and numerous other improvements were made.

getRad

In the getRad R package, functionality to download polar volume data was extended to the United States. Seven countries are now supported. Vertical profile time series data can be loaded directly from the Aloft bucket and the RMI. In addition, the behaviour of the get_pvol() and get_vpts() functions is synchronized, and documentation was improved. These updates will be released to CRAN soon.

Other

Smaller updates were made to the bioRad and birdR R packages, and the NAAVRE environment was explored to create a pipeline for processing radar data. The sprint allowed us to communicate directly, so many questions and discussions could be resolved efficiently.

Billions of flying animals move through the air, day and night. Due to the scale, volume and high altitudes, the scope of these movements are hard to study through observations or biologgers. Weather radars however continuously monitor the sky across large areas, registering not only weather, but also the movements of animals in the air. Archives of weather radar data are therefore goldmines for biological monitoring, providing an overview of the year-round activity of animals in the air in a way no other method can. Even though weather radar networks exist in many countries, they are usually operated on a national basis so combining biological data from several such networks across Europe has been a decade-long challenge.

We have now processed and published the first large-scale datasets of biological activity in the air, derived from weather radars across a large part of Europe. The radar data were obtained from the Operational Programme for the Exchange of Weather Radar Information (OPERA) at EUMETNET and three national meteorological services. The resulting datasets are a major milestone for the aeroecology community and the result of long-term interdisciplinary collaborations in the projects ENRAM, GloBAM and HiRAD.

Visualization of biological activity in the air, derived from radar SEANG in Ängelholm, Sweden (see blue dot on map). The charts show data from October 14 to 16, 2024. The top chart depicts the number of birds flying over the location per hour. The bottom chart shows at what altitudes the birds are flying (yellow = high density). Explore the data yourself at crow.aloftdata.eu.

The data consist of measures of all biological activity in the air surrounding the radar stations, stored as vertical profiles that describe the amount, speed and directions of animals at different altitudes. These were obtained by processing weather radar data with dedicated and validated methods for detecting birds and especially bird migration, but the data in itself do not offer any distinction between birds, insects or bats, so it must be interpreted through biological knowledge of what species groups are expected to be moving during different periods and places. Likewise, careful consideration of the variation in data coverage and quality is necessary. For more information on the intricacies of this exciting new datasets, we have provided usage notes in our paper.

The paper describes two public datasets that collectively contain biological data from 141 radar stations in 18 European countries, from the years 2008 to 2023. You can download these data from Zenodo or explore and visualize them in our Aloft data portal at aloftdata.eu. The portal is also updated daily with new data.

Weather radar data gives us a glimpse into life in the air, shedding light on the movements that take place above our heads. It has great potential to be used for conservation efforts, such as mapping where and how high birds fly in relation to anthropogenic threats, mapping diseases that spread along flyways, and highlighting periods of high bird activity for flight safety applications. These new datasets offer tremendous value for researchers studying flying animal movements and for enthusiasts simply witnessing these aerial spectacles. We look forward to seeing the creative, important and urgent applications that emerge as these biological data reach the wider scientific and conservation community in the coming years.