Analysts at the National Oceanic and Atmospheric Administration predicted a busier-than-average hurricane season in 2017, and they certainly hit the mark, according to the Los Angeles Times. These heavy-hitting storms left communities reeling in their wake and prompted important questions regarding hurricane predictions.
2018 may bring another active Atlantic hurricane season, according to New Scientist. Combined with ongoing impact from global climate change, weather prediction technology is more critical than ever — improved outcomes demand input from current tools and real-time data from tech advancements combined with expert interpretation.
What GOES Around Comes Around
Hurricanes Harvey, Irma and Maria caused devastating, long-term damage. As noted by The Balance, Harvey caused around $180 billion worth of damage, Irma cost the economy at least $100 billion and the storm in Puerto Rico left $85 billion of insurance claims in its wake. Can hurricane prediction tools prevent this from happening again?
- NOAA’s National Hurricane Center — Provides tropical storm and hurricane forecasts and warnings to help mitigate the impact of large storms. Recent technological advances have also helped the cause, like the GOES-16 satellite. CNBC said GOES-16 makes it possible to see hurricanes and other storms in their formative stages, which helps weather forecasters stay up-to-date. “From its constant perch over the Western Hemisphere, GOES-16 is already helping meteorologists issue more accurate and earlier warnings for severe thunderstorms, tornadoes, flooding and hurricanes because of its greater resolution and faster refresh than previous GOES satellites,” said The Washington Post.
- Super Computing — As noted by CNBC, the National Weather Service has invested substantially in supercomputing to gain three-fold processing power, in turn reducing storm tracking and location error rates. According to Phys.org, NOAA tracked hurricane Harvey to within 100 nautical miles (185,200 m) — an impressive feat considering the scope of the hurricane.
- Eyes in the Sky — With the capability to fly over severe weather and achieve high altitudes for up to 30 hours straight, intelligence gathered by Northrop Grumman’s Global Hawk UAV has helped civilian authorities assess storm strength and direction and plan next steps for warnings and disaster relief. In partnership with NASA and NOAA, the Global Hawk UAV has been used to track hurricane intensification for the Eastern Pacific Origins and Characteristics of Hurricanes Program.
- IoT Sensors — As noted by Recode, wind farms in Norway have already started using sensors to monitor the status of 400-foot-high (122 m) wind turbines for damage or performance degradation. Similarly, sensors could be attached to physical structures or on-site machinery to measure the impact of hurricane-force winds or rain. There’s a double benefit here: Companies gain continual assessment of risk, and employees aren’t put in danger checking the integrity of outside structures.
While technology remains a critical aspect of weather prediction, The Washington Post points out that a tech-first approach only takes forecasting so far. Better outcomes mean taking a “mission-first” approach where end-user needs drive the development of new technology. For example, civil authorities want more time to warn residents they may need to evacuate, while homeowners want some kind of quantifiable data about risk to their property. Mission-driven goals can help set the stage for new technology development.
Forecasters are also still critical to weather prediction, as noted by David Novak, director of the NWS’s Weather Prediction Center. “‘Models and observations are the base infrastructure that allows human forecasters to do better forecasts,'” he said. This follows a similar trend in business: internet of things tools, analytics and automation are essential elements to improve ROI, but can’t deliver ideal outcomes without human oversight.
The same is true of hurricane predictions — improved weather prediction technology can refine modeling and evaluation processes, but the experience and expertise of weather scientists remains critical to translate hard data into actionable outcomes.