**7. Conclusions**

In this paper, the extension of an approach controller support system for diversions around severe weather areas is presented that can use different meteorological nowcast models to automatically calculate approach routes and target times for arrival sequencing.

For this purpose, an AMAN was used in the H2020 project SINOPTICA as a planning system considering polygons enclosing severe weather areas as no-fly zones and the calculation of 4D trajectories based on aircraft type-specific parameters to avoid these areas. In the project, the AMAN considered not only standard approach routes, but also the constraints of waypoints; thus, realistic approach profiles were calculated that can be used for approach and touchdown sequencing. After a user requirements analysis with nine ATCOs, new functions were implemented so that approach controllers could receive guidance instructions from the AMAN for clearances in order to guide weather-affected aircraft along planned trajectories, and visual presentations were also provided on the primary display to help quickly and clearly identify aircraft concerned by a diversion. The AMAN and the newly developed diversion functionalities were tested with different extreme weather events that occurred in 2019 in northern Italy, which were modeled and reproduced with the PhaSt, WRF-RUC, and RaNDeVIL weather models.

During the first phase of the project, a user requirement survey was conducted in which different severe weather display types and support functionalities were evaluated by an international ATCO team with nine participants. As a result of the survey, two dynamic presentation variants were developed for the display of the current meteorological situation in the airspace, as well as its predicted development, and these variants are presented in detail in this paper. The first one is based on a linear extrapolation of the last meteorological measurements. It can be used if no dedicated weather forecasts are available. The second variant is based on a method similar to morphing in computer graphics. Here, the shapes of the actual and the predicted weather areas are decomposed into polygons and then merged in a flowing animation. In this way, an ATCO can track the development of severe weather areas at any time and can even adjust the organization of the airspace independent of planning support provided by a decision support system.

An evaluation with an international team of five active controllers showed that an AMAN is very helpful if there is a possibility of large-scale fly-around routing for the avoidance of severe weather areas. For this purpose, longer-term and highly precise forecasts that are precisely tailored to air traffic control requirements are essential. Additionally, the forecast model must correspond to the safety perception of ATCOs and pilots on site so that they can manage the traffic as efficiently and safely as possible. In summary, with the help of sophisticated nowcast models and an extended AMAN, SINOPTICA was able to show that it is possible to support ATCOs and pilots to guide air traffic safely and efficiently around severe weather areas in challenging meteorological situations, thus making planning more reliable and predictable for all stakeholders on the ground and in the air.

**Author Contributions:** Conceptualization, M.-M.T. and O.G.; methodology, M.-M.T., O.G., L.N., M.K. (Markus Kerschbaum) and O.O.; software, L.N., M.K. (Matthias Kleinert), O.O., K.M., H.E., N.G., V.M., M.M., M.L., E.R., L.E., T.R. and A.T.; validation, K.M., M.-M.T. and O.G.; formal analysis, O.G.; investigation, M.-M.T., O.G., M.K. (Matthias Kleinert), L.N. and O.O.; resources, H.E.; data curation, O.G. and A.T.; writing—original draft preparation, M.-M.T. and O.G.; writing—review and editing, A.P., R.B., O.G., V.M., M.M., M.L., S.F., R.C.T., L.E., M.C.L., R.B. and M.-M.T.; visualization, O.G., L.N., N.G. and M.-M.T.; supervision, A.P.; project administration, A.P.; funding acquisition, E.R., A.P., R.B., M.K. (Markus Kerschbaum) and M.-M.T. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by H2020 SESAR, grant number No 892362.

**Data Availability Statement:** Restrictions apply to the availability of these data. Data was obtained from FlightRadar24.com and are available https://www.flightradar24.com/commercial-services/ data-services. Further reports are available under "http://sinoptica-project.eu/index.php/articles/".

**Conflicts of Interest:** The authors declare no conflict of interest. The founding sponsor had no role in the design of the study, in the collection, analyses, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results.

#### **References**


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