By: Clint Harper, Autonomy Global Ambassador – AAM
The advanced air mobility (AAM) industry has made remarkable strides. Vehicles navigating the certification process, vertiport networks are being contemplated, and regulatory frameworks are taking shape. But at the LIFT Summit in Monterey, California, a panel of operators, air traffic professionals, atmospheric scientists, and policy specialists gathered to confront the inconvenient truth that much of that progress will stall at scale if we can’t tell a drone or an eVTOL what the wind is doing 200 feet above a downtown rooftop.
The Invisible Bottleneck
Weather has always governed aviation. Any air traffic controller (ATC) will tell you that the first thing they do when they walk onto the floor is check the weather. It shapes every decision, from which runway is active and how much separation to apply to when to hold, when to vector and when to wave off. Ray Adams, a retired air traffic controller who worked in the Newark airspace,, explained, “Weather is one of the most absolutely important things that you have to get your head wrapped around when you step into an air traffic control position.” He’s right. And he’s equally right that the problem gets harder, not easier, when you remove the pilot from the cockpit.
Unmanned and autonomous systems can’t look out the window. They can’t feel the aircraft buffet and decide to climb above a gust front. The heuristics we’ve spent decades building into trained pilots do not naturally exist in an autonomous system unless they are deliberately built into the data and decision architecture.. As Don Berchoff, CEO of TruWeather Solutions, noted, a meaningful share of aviation delays and cancellations attributed to weather stem from uncertainty rather than clearly unsafe conditions.. He described that uncertainty as an invisible weather-related penalty built into the economics of flight. For an industry built on thin margins and electric powertrains with finite energy reserves, that tax is existential.
Below 5,000 Feet: A Measurement Desert
One of the least appreciated gaps in the National Airspace System (NAS) is how sparse weather observation remains in the low-altitude environment away from airports. The FAA has acknowledged this explicitly in its Part 108 Notice of Proposed Rulemaking, noting that weather observations at an airport may not be relevant to conditions just miles away. For a commercial air carrier flying at FL350, that’s a minor inconvenience. For an eVTOL threading between downtown skyscrapers or a drone delivering cargo across a coastal valley, it can create a serious operational and safety issue..
I saw this problem firsthand while supporting urban air mobility planning in Los Angeles. Flying into Burbank one evening, the airport ASOS reported clear skies, and the skies above Burbank were, in fact, clear. But heading into downtown, a low cloud layer sat just above the rooftops. If an operator had been using the Burbank ASOS to plan an urban air mobility flight to a downtown vertiport, they would have launched into conditions their instruments never saw coming. This could have resulted in an aborted mission, a diversion or a degraded passenger experience.
This is the operational reality of the low-altitude environment. It is also why digital weather infrastructure must be treated as foundational for the emerging low-altitude economy.
The Wind Cone Problem
I’ve spent considerable time cataloguing hospital and private heliports, the physical precursors to the vertiports we’re now designing, and what I find again and again is a wind cone that hasn’t been meaningfully attended to in decades. Sometimes it’s just a rusted metal ring. The data it provides, when it provides any at all, is purely visual and purely local. Nobody downstream (think: dispatcher, route planner, autonomous flight management system) knows what that wind cone is reading.
That image represents the infrastructure gap nicely. On one end, a $50 wind cone that provides no digital output. On the other, a $300,000 ASOS that most operators can’t afford and that still fails to capture winds aloft. There is almost nothing in between. That gap is precisely where the entire AAM industry will try to operate. Moving from a rusted ring to a networked, validated, machine-readable weather picture will require a categorical leap that has to happen before autonomous aircraft begin at scale.
From Sensors to Networked Intelligence
The good news is that new standards are beginning to close that gap. During the panel, Don Berchoff described an emerging ASTM-based framework that supports a minimum viable product approach to low-altitude weather infrastructure. Instead of forcing every site into an all-or-nothing model, that approach would allow operators to deploy a curated sensor stack covering visibility, ceiling, and wind conditions for roughly $60,000. Add a vertical wind lidar, and the total can rise to around $180,000 while providing a far better picture of winds aloft than most sites have today.
Just as importantly, that framework opens the door to validated IoT weather inputs and AI-enhanced observational tools as part of a broader weather picture. That includes camera-based systems and other digital inputs that can help interpret visibility, cloud boundaries, and localized conditions, provided they meet reliability and validation requirements. The direction is clear: expand the range of usable data without sacrificing trust in the observation.
But individual sensors remain insufficient on their own. What the low-altitude NAS requires is networked weather intelligence: distributed sensing platforms that feed machine learning models capable of producing hyperlocal, real-time atmospheric forecasts.
The Monterey region offers a compelling demonstration case, with vertical wind profilers deployed across multiple airports building a mesh of data points that collectively characterize microclimatic behavior across the peninsula. The vision is a regional sensing network feeding a predictive analytics layer, which in turn feeds go/no-go decision systems for operators, dispatchers and eventually autonomous flight management platforms. Every reduction in uncertainty translates directly to more flights, more revenue and safer operations.
The eIPP as Accelerant
The FAA’s March 2026 announcement of the eVTOL Integration Pilot Program (eIPP) creates a meaningful forcing function. The eIPP is designed to bring operations into the regulatory conversation rather than waiting for every question to be settled in theory. For weather data infrastructure, that creates an opportunity to bring real operational requirements to the table before low-altitude operations begin scaling.
Some eIPP participants are already using the program to focus on foundational infrastructure, including weather data. That means thinking now about how weather observations will be collected, validated, shared, and integrated into operational decision-making. These are not side issues. They are part of the enabling infrastructure that will shape whether low-altitude operations are reliable, scalable, and economically viable.
If you are part of an eIPP team, bring your actual operational requirements to the table. The FAA wants to understand what you’re trying to do. Weather data infrastructure belongs at the center of every airspace integration conversation.
Building the Foundation Now
The low-altitude economy will require a data-rich, interoperable, cyber-resilient digital backbone. And weather sensing is a critical layer of that backbone. We cannot fly autonomous systems safely, efficiently or economically through airspace we cannot characterize.
The technology exists andstandards are maturing. The policy frameworks are beginning to align. The industry needs to commit to investing in distributed sensor networks, in validated third-party data services and in machine learning pipelines that turn raw observations into actionable intelligence.
For the communities, airports and operators that move first, the payoff will be both operational and competitive. The regions that build robust low-altitude weather infrastructure now will be the regions that attract the first commercial routes, the first certified operators and the first returns on what promises to be a transformative sector of the national economy.
The data gap is real. So is the opportunity to close it.