## 1 Introduction  
The Air Traffic Management (ATM) system organises a large network of airports and a large volume of airspace to help thousands of flights operate safely and efficiently day to day [1]. But the ATM system is currently facing certain difficulties. The ever-increasing traffic demand is saturating the ATM system [2]. EUROCONTROL predicts that the demand for flights in 2035 will be 14.4 million movements, which is 1.5 times the number of operations documented in 2012 [3]. This increase causes the existing balance between ATM service capacity and demand for operations to break down, as there is not sufficient capacity to handle all operations. This traffic growth will have negative consequences, such as airspace congestion, delays, or increased fuel consumption [4], and this situation will worsen in the coming years. This increase in complexity will also lead to an increase in the workload of Air Traffic Controllers (ATCOs) [5] because of their direct relationship. For these reasons, complexity is critical for operational safety and will limit Air Traffic Control (ATC) system capacity [6]. Because of these negative consequences, the assessment of and reduction in air traffic complexity is a topic that is attracting a great deal of interest from researchers around the world [7, 8]. It follows that early identification of traffic complexity can help to increase ATC system capacity [9]. For this reason, studies on this topic are based on the definition of a complexity indicator [10] or to assess the complexity in the airspace [11]. Therefore, knowledge of the complexity of air traffic will be associated with better management of both human and technological resources by the ATC system [12]. Despite much work on the study of complexity, no consensus has been reached on the definition of complexity [13]. Measuring complexity is very challenging due to, among other reasons, the selection of factors that affect complexity. Since these factors are very varied but highly correlated with each other, their selection is very difficult [14]. Therefore, arriving at a single indicator of complexity is very challenging. At present, air navigation service providers remain reliant on the subjective assessment of ATCOs as the most prominent technique for measuring air traffic complexity, despite the fact that many studies have focused on the research of new complexity indicators based on objective parameters [15]. However, there is also a tendency to create indicators that objectively measure the workload of air traffic controllers, taking into account air traffic parameters [15]. Complexity describes air traffic situations. For this reason, the knowledge of complexity can give much information to the air traffic controllers. By knowing complexity, they will have information about the structure of air traffic, which could help in providing separation to aircraft, helping efficiency and safety in air traffic management. Complexity is a variable that depends on many parameters. These parameters can be airspace structure, weather conditions, space weather conditions, wars, and technological factors, among others. From the operational point of view, an analysis of the operational variables that influence complexity is shown in [16]. These variables include the number of aircraft in the airspace, the number of aircraft per flight level, and daily occupancy. Regarding the structure of airspace, the number of flows is also a parameter taken into account in this analysis. In addition, war conflicts also affect complexity by affecting air traffic. In [17], it is analysed how the airspace bans resulting from the Russo-Ukrainian war affect traffic. Specifically, by modifying trajectories, areas of complexity are generated for ATCOs as they have a traffic structure with which they are not familiar. One factor that is widely related to complexity is weather. Uncertainty in weather, and the effects on air traffic structuring (regulations, delays, economic costs [18],...), make adverse weather conditions related to complexity.