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Supercomputer predicts cyclones 5 days ahead

A NASA supercomputer has enabled researchers to predict the birth of a cyclone five days in advance, a first for storm-modeling that might improve forecasting and emergency preparedness.
Cyclone Nargis
Cyclone NargisNASA
/ Source: TechNewsDaily

A NASA supercomputer has enabled researchers to predict the birth of a cyclone five days in advance, a first for storm-modeling that might improve forecasting and emergency preparedness.

At the heart of the research is an advanced computer model that ran millions of numbers — atmospheric conditions like wind speed, temperature, and moisture — through a series of equations.

"To do hurricane forecasting, what's really needed is a model that can represent the initial weather conditions — air movements and temperatures, and precipitation — and simulate how they evolve and interact globally and locally to set a cyclone in motion," said Bo-wen Shen, a research scientist at the University of Maryland-College Park, whose study appeared online last week in the Journal of Geophysical Research–Atmospheres.

Shen and his colleagues used such atmospheric data to retrospectively simulate tropical cyclone Nargis, which devastated Myanmar in 2008 and stands as one of the 10 deadliest cyclones on record. The scientists were able to anticipate the formation of the storm five days in advance of its actual generation, which could provide a critical forewarning in a region where the meteorology and monitoring of cyclones is hampered by a lack of data.

Knowing is half the battle
Tropical cyclones are major storms that are called hurricanes in the Atlantic Ocean and typhoons in the western Pacific Ocean. To save lives from the high winds, flooding, and storm surges of these meteorological monsters, forecasters need to give as much advance warning as possible and the greatest degree of accuracy about a brewing storm.

Scientists study the maps and data from computer models of hurricanes and compare them against real observations of a past storm (like Nargis) to evaluate the models' accuracy. The more a model reflects the actual storm results, the greater confidence researchers have that a particular model can be used to paint a picture of what the future might look like.

"We know what's happening across very large areas. So, we need really good, high-resolution simulations with the ability to detail conditions across the smallest possible areas," said Shen. "We've marked several forecasting milestones since 2004, and we can now compute a storm's fine-scale details to 10 times the level of detail than we could with traditional climate models."

Supercomputing power
It is this level of detail that made cyclone birth prediction possible on the Pleiades supercomputer at NASA's Ames Research Center in Moffett Field, Calif. This floor-filling machine can process atmospheric data for global and regional conditions, as well as the fine-scale measurements like those around the eye of a storm.

NASA built the Pleiades supercomputer in 2008, incrementally boosting its processing "brain power" since to the capacity of 81,920 desktop central processing units (CPUs). The upgrades laid the groundwork for Shen and others to gradually improve simulations of varying aspects of a storm – from simulations of the path, then intensity, and now the actual genesis of a storm.

The improved simulations can translate into greater accuracy and less guesswork in assessing when a storm is forming and where it's heading.

"There is a tendency to over-warn beyond the actual impact area of a storm, leading people to lose confidence in the warning system and to ignore warnings that can save their lives," said study co-author Robert Atlas, director of the National Oceanic and Atmospheric Administration's (NOAA) Atlantic Oceanographic and Meteorological Laboratory in Miami, Fla., and former chief meteorologist at NASA's Goddard Space Flight Center in Greenbelt, Md.

"Although we've seen tremendous forecasting advances in the past 10 years – with potential to improve predictions of a cyclone's path and intensity — they're still not good enough for all of the life-and-death decisions that forecasters have to make," Atlas continued. "Tropical cyclones have killed nearly two million people in the last 200 years, so this remaining 'cone of uncertainty' in our predictions is unacceptable."

Forecasting forecasts
As promising as the new model may be, Atlas cautioned that "Shen's model worked for one cyclone, but it doesn't mean it'll work in real-time for future storms. The research model Shen and predecessors at NASA have developed sets the stage for NOAA's researchers to hone and test the new capability with their own models."

The new model also yields insights into the dynamics of weather conditions over time and across different areas that generate such storms.

"In the last few years, high-resolution global modeling has evolved our understanding of the physics behind storms and its interaction with atmospheric conditions more rapidly than in the past several decades combined," explained Shen, who presented the study last month before peers at the American Geophysical Union's Western Pacific Geophysics Meeting in Taipei, Taiwan.

As a teen in his native Taiwan, Shen observed helplessly as typhoon after typhoon pummeled the small island country. Without advanced forecasting systems, the storms left a trail of human loss and property destruction in their wake.

Determined to find ways to stem the devastation, Shen chose a career studying tropical weather and atmospheric science. In the end, his new cyclone model might just provide the predicting power to mitigate such future calamities.

"We can 'see' a storm's physical processes with this advanced global model — like both the release of heat associated with rainfall and changes in environmental atmospheric flow, which was very difficult until now," Shen said.

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