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Keerthi B Thimmegowda Keerthi B Thimmegowda Written by Keerthi B Thimmegowda, Head Corporate Ventures and Aero, Rail Growth
on 03 May 2023

Urban air mobility (UAM), a complex and technologically advanced system that enables on-demand, highly automated, passenger- or cargo-carrying air transportation services, ensures seamless transportation of people and goods, mitigating current and future challenges in urban areas. It has the potential to revolutionize the way people and goods are transported within and between cities, providing a faster and more efficient alternative to traditional ground-based transportation. Urban air mobility adoption comes down to five key drivers:

  • Growing demand for alternative modes of transportation in urban mobility
  • Need for convenient, efficient, and last-mile delivery
  • Zero emission and noise-free mandates
  • Advancement in technologies (energy storage, autonomous, connected, power electronics)
  • Security

Impact of weather conditions on UAM

As UAM gains traction as a potential solution for the future of transportation in urban areas, understanding the impact of weather on and its interactions with UAM operations becomes crucial. From electric vertical takeoff and landing (eVTOL) aircraft to autonomous drones, the weather can significantly influence the safety, efficiency, and feasibility of UAM operations in terms of business and technical viability.

Unlike traditional weather forecasting, which typically provides forecasts for a larger region and for longer timeframes, UAM operations need a weather forecasting technique that provides highly detailed and accurate short-term weather predictions for a specific location. Nowcasting is a technique suited for UAM that uses a combination of data from ground-based weather sensors, satellite imagery, and numerical weather prediction models to provide up-to-the-minute weather information. Nowcasting technology can provide detailed information on a range of weather phenomena, including thunderstorms, heavy rain, and fog, for flight path planning.

Similarly, we can leverage short-term and micro-scale wind forecasts for UAM operations. Short-term wind forecasts typically cover a time frame of a few hours up to a day or two, and can be used to predict wind speed, direction, and gusts. Micro-scale wind forecasts, on the other hand, provide even more detailed wind information, covering a smaller geographic area and shorter time frame. These forecasts are particularly useful for UAM operators as they can predict highly variable and unpredictable wind patterns in and around urban environments. This helps operators plan flight paths and adjust their operations in real time based on changing wind conditions.

In addition, there are unmet weather requirements such as real-time data on wind gusts, lightning detection and prediction, precipitation intensity and type, visibility information, turbulence detection and prediction, icing conditions, and severe weather alerts and warnings that need to be addressed using appropriate monitoring and measurement technologies. These are addressed by combining data from multiple sensors and sources like weather radar, satellite imagery, LiDAR, infrared sensors, ground-based weather stations, and onboard weather sensors. UAM operators can thus improve weather forecasting accuracy and make informed decisions about flight path planning and operation.

Most prospective UAM operators envision a scenario of thousands of simultaneous flight operations occurring over a large metropolitan area within an altitude block stretching from the surface to 5,000 feet, with nominal cruising altitudes of 1,000 – 2,000 feet above ground level (AGL). Consequently, flight conditions can change frequently and dramatically across very short temporal and spatial scales. Unfortunately, the lower mass and moment of inertia, and limited thrust and speed of UAM vehicles, increase their sensitivity to these ambient atmospheric conditions. Meteorological hazards of concern (refer to the table below), which include wind and turbulence, temperature, ceiling and visibility, precipitation and icing along with interactions of wind shear or tunnel effect from skyscrapers could result in safety or unnecessary grounding of the aircraft, delaying the delivery of goods and services, ultimately impacting operational efficiency, revenue, and liability.

 Impact score defined by Meteorological airdrome

Suggested interventions to manage and minimize risks

In addition to ensuring the safety and comfort of passenger-carrying aerial vehicles and the performance of cargo delivery aircraft, reliable weather information is required for flight planning, flight authorizations, real-time adaptive trajectory planning, and managing dynamic airspace boundaries, along with contingency planning. Consequently, appropriate real-time weather data from multiple sources and its fusion to plan and manage low-altitude urban airspace is needed and will be particularly critical for unlocking the full potential of UAM.

  1. Robust communication and coordination: Establishing robust communication and coordination channels between UAM operators, pilots, and relevant weather authorities is crucial. This can facilitate the exchange of real-time weather information, updates on changing weather conditions, and timely decision-making based on weather forecasts. Clear and effective communication can help operators and pilots stay informed and adapt their operations accordingly.
  2. Robust weather monitoring and sensor technology: In the future, equipping automated vehicles, unmanned aircraft systems (i.e., drones), and eVTOLs with meteorological sensors plus sensors within urban environments such as vertiports, buildings, ground stations, and ATC, connected through a 5G network, could provide improved real-time weather data. This improved real-time weather data, coupled with artificial intelligence and machine learning, could enhance weather forecasting and predictive capabilities leading to reduced flight cancellations and delays for travelers. Advanced aircraft technology, such as fly-by-wire systems, can also help improve aircraft stability and performance during adverse weather conditions.
  3. Advanced aircraft and forecasting: UAM service providers may consider mixed fleets of aircraft with different performance capabilities that can maximize operational capability in different weather conditions. Alternatively, they can also roll out mixed fleets that optimize flight performance for different regions to gather timely and actionable weather guidance using techniques like nowcasting and short-term and micro-scale wind forecasts that will support eVTOL flight operations in urban environments.
  4. Contingency planning: Leveraging weather forecasting and preparing contingency plans to pre-emptively route travelers to non-aerial modes of urban transportation prior to commencing their journey could reduce traveler disruptions associated with flight delays and cancellations. This may include having alternative routes, backup landing sites, or contingency measures in place to deal with unexpected weather changes. Contingency planning can help minimize the impact of adverse weather conditions on UAM operations and ensure continued operations with minimal disruptions.
  5. Robust technology for accurate prediction: Meteorological observation and prediction will have to be upgraded to support eVTOLs and UAM to operate in most weather conditions reliably.

Proactive approach

Mitigating weather-related issues in UAM operations requires a proactive and comprehensive approach that includes robust weather monitoring, weather-responsive operations, advanced technology such as sensors, data fusion, and artificial intelligence, training and education, communication and coordination, and contingency planning. By implementing these measures, UAM operators can enhance the safety, efficiency, and reliability of their operations, making UAM a more viable mode of transportation in urban areas. Furthermore, the ability to accurately forecast UAM weather and provide a dependable consumer experience will be a key enabler for the UAM sector. Additionally, big data and a robust predicative weather analytics mechanism would present opportunities for UAM service providers to manage demand, reduce delays, and enhance traveler safety and experience.

 

About the Author

Keerthi brings in significant expertise in the engineering business, having led initiatives involving growth and diversification across global markets, industries, and technology. Furthermore, he has worked with leading companies in the aerospace, automotive, industrial, healthcare, and hi-tech industries and established global engineering centers such as Bombardier Aerospace, GE Consumer Products among others.

With 27+ years of experience across Tech Mahindra, Boeing, Mahindra and Mahindra, Force Motor, and NAL/HAL, Keerthi is a certified project management professional (PMP), reliability practitioner, and master black belt in six sigma. He holds a mechanical engineering degree from the Bangalore Institute of Technology and has done the Executive Management Program in International Business from IIFT, New Delhi.

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