# Real-Time Contrail Monitoring and Mitigation Using CubeSat Constellations
## 3 Mitigation Strategies Through Real-Time Monitoring  
### Advancements in Contrail Monitoring Technologies  
The challenge of monitoring contrails has long been a topic of interest within the atmospheric science and aviation communities. Traditional methods, such as ground-based radar systems, pilot observations, and imagery from large satellites, have provided the foundational data necessary to understand contrail formation [30; 31; 32]. However, these methods often fall short in several key areas, particularly in their ability to offer the high temporal and spatial resolution needed for real-time monitoring and predictive modeling.  
Ground-based radar, while effective at capturing large-scale cloud formations and precipitation, lacks the vertical resolution necessary to accurately monitor contrails, which form at altitudes of approximately 26,000 to 40,000 feet. These radar systems are also limited by their fixed locations, which means they can only monitor specific areas and cannot provide the global coverage required for comprehensive contrail tracking.  
Satellite imagery has been a valuable tool in observing contrail formations and their evolution over time. Large satellites, such as those in the Geostationary Operational Environmental Satellite (GOES) series [33], offer broad coverage and have been used extensively to monitor weather patterns and cloud formations, including contrails. However, these satellites are often designed for multiple purposes, and their sensors may not be optimized specifically for detecting the fine-scale ice crystals that characterize contrails. Additionally, the temporal resolution of these satellites and how frequently they pass over the same point on Earth can be too low to capture the dynamic processes involved in contrail formation and dissipation.  
Pilot reports and visual observations have also contributed to our understanding of contrails, particularly in identifying areas where contrails are frequently observed. However, these methods are inherently subjective and limited by the pilot's ability to observe and report contrails while managing the complexities of flight operations [34; 35].  
In contrast to these traditional methods, the advent of CubeSat technology represents a significant leap forward in contrail monitoring. CubeSats are miniaturized satellites, typically measuring as small as 10 \(\times\) 10 \(\times\) 10 cm per unit, which can be deployed in smaller to larger constellations to provide high-resolution data on atmospheric conditions. These satellites are particularly well suited to the task of monitoring contrails due to their ability to carry specialized sensors designed to detect the specific environmental conditions that lead to contrail formation. CubeSats offer several key advantages over traditional monitoring methods. First, they can be deployed in constellations, meaning multiple CubeSats can work together to provide continuous, global coverage. This capability is particularly valuable for monitoring high-traffic air routes, where the frequency and persistence of contrails are of greatest concern. Second, CubeSats can be equipped with state-of-the-art sensors, including infrared and hyperspectral imagers, that are specifically tuned to detect the presence of ice crystals and water vapor in the upper atmosphere [36]. In particular, the use of high-resolution sensors in the thermal infrared band to detect contrail formation has been demonstrated [37], with different bands used to differentiate contrails from water and ice clouds.  
The small size and relatively low cost of CubeSats also allow for more flexible and frequent deployments compared to larger satellites. This means that new CubeSats can be launched regularly to replace or supplement existing constellations, ensuring that the monitoring network remains up to date with the latest technological advancements. Moreover, CubeSats can be deployed in low Earth orbit (LEO), providing them with the proximity to the atmosphere necessary to capture detailed, high-resolution data.