As Hurricane Florence bears down on the East Coast, its intensity is coming into sharp relief. The Category 2 hurricane had sustained winds of 105 miles per hour at the time of writing, with tropical storm-force winds stretching more than 335 square miles in all directions. Rainfall was predicted to reach 40 inches in regions of coastal Carolina, and Wilmington — which just had its rainiest year to date — might get eight months worth of rain in three days. One firm closely tracking Florences progress is The Weather Company, the weather forecasting division of IBM whose consumer-facing brands include the weather.com, intellicast.com, and Weather Underground. Its systems analyze more than 100 terabytes of third-party data and generate 25 billion customized regional models daily. Our models provide a forecast evolution of what the atmosphere is going to look like in the coming days, Dr. James Belanger, a senior meteorological scientist for The Weather Company, told VentureBeat in an interview. The system keeps in memory what the forecasts are all across the globe. One of the predictive technologies its data scientists tap is Deep Thunder, an IBM research project spun out of the companys Deep Computing initiative. Leveraging public satellite imagery, proprietary datasets, and sensors — including more than 250,000 personal weather stations and smartphone barometer readings — its able to produce short-term, hyperlocal weather forecasts for local governments and corporate clients alike. In a pilot in Rio de Janeiro, Deep Thunder predicted floods and anticipated where storms might trigger mudslides. And in the U.S., it enabled a utility company to pinpoint where storms were likely to bring down power lines. Its capable of even greater precision, Belanger explained. Using historical weather data, it can create probability distributions by modeling synthetic storms (think a computer-generated tropical cyclone.) And later this year, itll be used to issue probabilistic snowfall reports seven days in advance. Another tool in The Weather Companys arsenal are forecast runs from government agencies like the National Weather Service, which are typically released 10-15 days in advance of shifting weather patterns. Theyre ingested and run through adaptive regression models — statistical models that automatically plot interactions between variables — that apply weight and bias corrections for any given target location. Its a really scalable system, Belanger said. The calibration information is continually updated … Were able to distribute temperature and precipitation forecasts for anywhere in the globe. So hows The Weather Data use that backend to track high-profile storms like Florence? While it defers to the National Weather Service on forecasted storm impacts — going so far as to impose what Belanger calls guardrails and adjustments that ensure its messaging remains in alignment — its consumer team employs analytics to identify the best times to issue alerts. They look at the times of day when consumers are most actively engaging our content, Belanger said, and make sure to keep people informed of rainfall and flood threats. Its an important way we deliver messages and communications to people who are the most vulnerable.
Simple analysis suggests global warming boosts Florences rain by 50 percent. In the last few years, teams of scientists have developed a consistent protocol for rapidly analyzing the influence of climate change on extreme weather events. Within a week of the disaster, reports have been available to inform the conversation about whether we can expect more events like it in the future. But on Wednesday, we saw the first example of something new—an analysis published before the event even happened. A group led by Stony Brook Universitys Kevin Reed ran a very simple computer model experiment on Hurricane Florence—which isnt due to make landfall until Friday—and quickly released the top-line results. The rapid studies weve been seeing are done by examining the historical weather record to estimate how rare and extreme a given storm or heat event would be in that area of the globe. From there, climate model simulations are used to see if climate change is expected to change the frequency of that type of event. In this case, theres obviously no data available for a thing that hasnt happened yet. Instead, the researchers focused on a much more limited question that is faster to answer: how does a warmer world change this storm? In the counterfactual world where global warming never happened, its impossible to say if Hurricane Florence would even have been born. Even small changes can have complex consequences on the atmosphere, such that events would play out completely differently. But thats not the point. Since Hurricane Florence is occurring in this warmer world, we can simply examine the effect of warmer temperatures. To do this, the researchers took the current state of the world on Tuesday, dropped that into their model as a starting point, and pressed play to simulate ahead to Sunday. For a comparison simulation, they took those starting conditions and essentially subtracted out global warming. In this counterfactual world, the storm looks significantly different. Hurricanes are fueled by energy from the evaporation of warm seawater, so its no surprise that warmer sea surface temperatures should give the storm a boost. The size of the boost in this case is pretty remarkable, though. The model analysis showed the real-world Florence dumping 50 percent more rain near the coast than it would in a world without human-caused warming. The modeled hurricane clearly stays stronger when simulated under current-day conditions, but its also larger. The diameter of the storm is about 80 kilometers (50 miles) greater than in the cooler simulation, which would translate into higher storm surge flooding on the coast. Team member Michael Wehner told Ars that the team is working to repeat this analysis with updated observations as the storm barrels down on the Carolinas, so we'll get to see how similar the results are for each iteration. The researchers also plan to repeat their work after the storm and carefully compare with the forecast analyses. That will help show how useful this trial run of pre-storm analysis was. For their part, the group behind the within-one-week studies explained Thursday that they wont be providing an analysis of Hurricane Florence in the near future (for reasons ranging from complex historical data to swamped workloads). But they did comment on these pre-storm results, writing, More analyses are needed to assess the robustness of this quick analysis, although the basic result that global warming increases the precipitation is a very robust one supported by observations and modelling studies.