On May 31, 2013, four storm chasers died pursuing a gigantic tornado barreling across Oklahoma. Many more hurricane hunters have lost their lives attempting to collect data during some of the biggest storms of the past several decades.
Not only are storm chasing missions dangerous, they’re expensive. Aside from the personnel, aerial weather reconnaissance planes cost tens of millions of dollars. Even studying non-extreme atmospheric phenomenon (such as air pollution) is expensive when using regular aircraft. But using unmanned aerial vehicles (UAVs) could perform many of the same functions for a fraction of the cost. Another advantage to using sophisticated UAVs is that they can stay in the air three times longer than conventional storm-chasing planes.
Satellite-mounted remote sensing technology has been used for decades to study hurricanes and other extreme weather events, and UAVs have been utilized for about ten years. The National Oceanic and Atmospheric Administration (NOAA) states that “drones have played a critical role in data collection, enabling unprecedented access to vital information…in a region of the atmosphere [that] has historically been difficult to sample.” In addition to enhancing our ability to produce climate models that can accurately predict extreme weather events, NOAA and NASA have used UAVs to track the metrics of dangerous storms themselves as well as the damage caused in their wake. In the aftermath of devastating hurricanes in Texas and Florida in 2017, dozens of UAVs were deployed to monitor flooding and assess damage to roads and bridges. Additionally, UAVs have proved useful in the rescue response; they can spot survivors more quickly than traditional rescue teams can find them. According to NOAA, UAVs are of particular benefit to rural areas where storm damage is often underreported and disaster response slow.
Not only do these technologies save money and lives in tracking extreme weather events, they show promise in minimizing losses from disasters or even preventing them altogether. According to Swiss Re, a leading global provider of risk assessment and insurance, natural disasters cost the United States 136 billion dollars in 2019, and six of the most extreme and costliest wildfire seasons have occurred in the past 15 years. Fires in Australia in recent years have resulted in billions of dollars in damage. Remote-sensing technology could be an early detection game-changer for wildfire prevention; fleets of drones equipped with machine-learning algorithms could spot and track small fires before they get out of control. Engineers in Spain are working on prototype for wildfire detection: rather than relying on traditional fire towers by staffed by lonely humans, towers equipped with thermal cameras and sensors could detect wildfires and subsequently automatically deploy drones to gather precise information about the fire.
From their efficacy in preventing or minimizing climatic catastrophes, to improving our predictive models, to saving lives, it’s clear why remote sensing technologies are on track to become the next generation of storm chasers.
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