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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.

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.


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The above story is based on 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 April 24, 2014 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 April 24, 2014).

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