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Lessons From El Niño: New Modeling Techniques Improve Prediction And Tracking Of Extreme Weather Events

Date:
January 27, 1999
Source:
Harvard Medical School
Summary:
The past year's extreme weather events and the subsequent outbreaks of infectious diseases have provided a wealth of evidence that suggests a significant causal relationship between El Niño, extreme weather events, and a decline in human health. Noting this correlation, scientists and public health experts are utilizing an array of tools, including satellite remote sensing and mathematical modeling, to improve their ability to predict and track climate variability and change and related infectious disease outbreaks.
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ANAHEIM, Calif. -- January 24, 1999 -- The past year's extreme weather events and the subsequent outbreaks of infectious diseases have provided a wealth of evidence that suggests a significant causal relationship between El Niño, extreme weather events, and a decline in human health.

Noting this correlation, scientists and public health experts are utilizing an array of tools, including satellite remote sensing and mathematical modeling, to improve their ability to predict and track climate variability and change and related infectious disease outbreaks.

"If the primary manifestation of climate change is more severe and unstable weather, then we have begun to see firsthand how a changing climate impacts our health and the international economy," says Paul R. Epstein, MD, MPH, associate director of the Harvard Medical School Center for Health and the Global Environment. "By recognizing this phenomenon and by improving our ability to predict extreme weather events, we can implement proactive programs to prevent or minimize some of the weather-related health problems."

Epstein will outline current efforts to enhance forecasting models at a press briefing on Sunday, January 24, 1:00 pm at the annual meeting of the American Association for the Advancement of Science in Anaheim, Calif.

El Niño/Southern Oscillation (ENSO) is characterized by a disruption of normal wind and ocean current patterns in the South Pacific. This causes warm western Pacific waters to move toward South America, displacing the normally cold, nutrient rich Humboldt Current. ENSO can cause global climate change, from droughts in Southeast Asia to flooding in arid regions of Africa and South America.

Extreme weather events in 1998 caused significant outbreaks of disease and economic losses throughout the world. Extensive flooding in East Africa resulted in large increases in incidence of malaria, Rift Valley fever and cholera. In Southeast Asia, delayed monsoons-compounded by local farming practices-led to prolonged fires, which caused widespread respiratory illnesses and extensive wildlife losses. Central America, in the wake of Hurricane Mitch, experienced an increase of cholera, dengue fever, and malaria. Most recently, a four-day deep freeze in California's Central Valley last month devastated the state's citrus crops.

According to a Worldwatch Institute study, weather-related disasters during the first 11 months of 1998 caused more than $89 billion in economic losses (by comparison, weather-attributed economic losses total $55 billion during the 1980s), resulted in 32,000 deaths, and displaced more than 300 million people from their homes.

While improved modeling techniques will help organizations to minimize extreme weather-related disease outbreaks, Epstein notes that future climate changes could bring even greater problems. "There is growing evidence of heat accumulation in the deep ocean and around the North and South Poles," Epstein says. "This raises a few questions. First, are the oceans the repository for this country's global warming? Second, is this increase in ocean temperature altering El Niño/Southern Oscillation, thus leading us to even more severe and volatile weather in the future?"


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The above post is reprinted from materials provided by Harvard Medical School. Note: Materials may be edited for content and length.


Cite This Page:

Harvard Medical School. "Lessons From El Niño: New Modeling Techniques Improve Prediction And Tracking Of Extreme Weather Events." ScienceDaily. ScienceDaily, 27 January 1999. <www.sciencedaily.com/releases/1999/01/990127081007.htm>.
Harvard Medical School. (1999, January 27). Lessons From El Niño: New Modeling Techniques Improve Prediction And Tracking Of Extreme Weather Events. ScienceDaily. Retrieved August 29, 2015 from www.sciencedaily.com/releases/1999/01/990127081007.htm
Harvard Medical School. "Lessons From El Niño: New Modeling Techniques Improve Prediction And Tracking Of Extreme Weather Events." ScienceDaily. www.sciencedaily.com/releases/1999/01/990127081007.htm (accessed August 29, 2015).

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