Atmosphere And Weather

How Math Helped Forecast Hurricane Sandy



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Forecasting hurricanes is a complicated process, but one that holds out hope that many lives could possibly be saved. Like any dangerous situation, the more warning that can be given, the more likely that those in potential harm can reach places of safety in time. Various methods have been considered over time in an attempt to predict when and where a hurricane will occur. One method that is gaining interest is math-based forecasting, and, in at least one instance, it has proven remarkably helpful. Hurricane Sandy was forecast with astonishing accuracy due to the use of math. How did this occur and what lessons does this instance provide for the future?

While hurricane warning systems go back into the late 19th century, hurricane research intensified in the 1950s. Attempts to forecast the presence and intensity of hurricanes increased in response to the development of new technologies. Advances in the capability of aircraft enabled those tracking these storm systems to more accurately identify the current position of the hurricane and the potential threat which it presented. As computer technology advanced rapidly through the 1960s and 1970s, statistical models became more and more complex as researchers attempted to mimic the large number of factors that must be considered in determining where a hurricane was headed and the degree of threat which it represented. The National Hurricane Center was founded in 1965 to incorporate the latest models and technology in order to create better systems for warning those in danger from the approach of a hurricane. While more and better models have continued to be developed over the years and the ability to determine the direction of a hurricane has improved steadily, the ability of models to determine the intensity of a hurricane continues to be a significant challenge.

Hurricanes yearly do astonishing damage and affect the lives of a great number of people. Hurricanes that hit landfall can result in upwards of billions of dollars in damage and can lead to the deaths of many people who find themselves in a hurricane’s path. Improved forecasting holds out hope that at least some of these deaths can be prevented and that at least some of the damage can be prevented or reduced. From time to time a hurricane hits land with such force that it is remembered for many years afterward and its impact is felt long after it has ceased. Hurricane Sandy was one such hurricane. In October of 2012, this intense storm struck New York and New Jersey and eventually damaged parts of 12 states in all. The property damage inflicted by the storm was estimated at over $18 billion in insured losses. The impact of such a storm system is felt not only in the loss of individual lives and property, but in the economic, social and psychological scars that linger long after the event.

Mathematics has more and more become a key factor in the forecasting of a variety of weather systems of which hurricanes are one. The use of mathematical models in order to anticipate hurricanes before they inflict damage to physical property and individual life requires integrating a wide range of meteorological variables. Such modeling differs greatly from standard weather forecasting because of the time and the variables involved. Weather forecasting is generally only reliable over a six- or seven-day time period, but hurricane forecasting requires the ability to be accurate over a much longer time frame if the necessary actions can be taken to prevent loss of life and to limit property damage as much as possible.

Mathematical modeling takes into consideration the historical data on past storm systems in order to determine the likelihood that current systems will develop into hurricanes, the intensity with which the hurricane will hit land and the most likely trajectory it will take. Mathematical forecasting must also take into consideration how various changes in climate affect current hurricane development. As mathematical modeling improves, relief agencies will be better prepared to provide the appropriate measures to help those impacted by hurricanes that hit landfall.

Mathematical modeling played an important role with regard to Hurricane Sandy. The advancements in these models targeted the area of New Jersey where the hurricane first made landfall. This specific and timely information enabled authorities to direct people to higher ground, thereby saving many lives. The complexity of the storm was brought under some semblance of control by use of advanced mathematical modeling.

The mathematical models used with regard to Hurricane Sandy were particularly effective because they were able to take into consideration the mixture of two significant weather systems and to gauge the consequences of that interaction. As a result, the trajectory and intensity of the system was identified well before previous systems, thus providing time to notify those in the affected area and allow them to take the necessary action to protect property and save lives. Though the impact of Hurricane Sandy was horrific, it could have been much worse if not for the advancements in mathematical forecasting.

Hurricanes are a constant threat to life and property. Many individuals have dedicated themselves to the attempt to forecast the trajectory and intensity of these devastating storms. The significance of this effort was demonstrated when Hurricane Sandy threatened the eastern seaboard of the United States. Advanced mathematical modeling provided the authorities and the public with the information and time necessary to direct people to safer areas. As these models continue to be enhanced, more lives will be saved and the negative impact of these storms will be lessened. Mathematical models are an essential tool in keeping people safe from the variety of factors that threaten coastal areas on a yearly basis, and they provide hope for better things to come.

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ARTICLE SOURCES AND CITATIONS
  • InfoBoxCallToAction ActionArrowhttp://www.hurricanescience.org/science/forecast/models/modelshistory/
  • InfoBoxCallToAction ActionArrowhttp://en.wikipedia.org/wiki/Hurricanes.gov
  • InfoBoxCallToAction ActionArrowhttp://www.iii.org/facts_statistics/hurricanes.html
  • InfoBoxCallToAction ActionArrowhttp://coastal.news14.com/content/hurricane_season/610048/hurricane-predictions-more-math-than-science
  • InfoBoxCallToAction ActionArrowhttp://www.scientificamerican.com/article.cfm?id=how-math-helped-forecast-superstorm-sandy