El Niño 2015- a graph that says it all: be prepared.
*The Oceanic Niño Index (ONI) is based on current year three month running mean of Sea Surface Temperature (SST) departures from average in the Niño 3.4 region, and is a principal measure for monitoring patterns in order to predict El Niño/Southern Oscillation (ENSO).
As the graph clearly shows, this year’s El Niño looks like it will be just as bad as its predecessors – if not worse. Let’s take a look at the past big El Niño phenomena:
- 1997-98: Severe weather events included flooding in the southeast, an ice storm in the northeast, flooding in California, and tornadoes in Florida- resulting in a total U.S./Canada death toll of 56. Flooding in California alone is estimated to have resulted in $550 million in damage for the state along with 17 storm-related deaths; 35 counties were declared federal disaster areas.
- 1982: Droughts and fires in Australia, Southern Africa, Central America, Indonesia, the Philippines, South America and India along with floods in the U.S., Gulf of Mexico, Peru, Ecuador, Bolivia and Cuba and more hurricanes than usual in Hawaii and Tahiti resulted in the loss of nearly 2,000 lives and displacement of hundreds of thousands from their homes.
- 1972: The ocean warming caused a serious drop in the cold-water fish catch which took years to recover- the Peruvian fishing industry experienced the worst crisis since the early 1950’s as the anchovy stocks declined sharply. Only 2.5 million tons were harvested while normal catch was 9.5 million tons, for a virtual collapse of the Peruvian fishing industry. Fishmeal was a major source of feed for livestock and poultry around the world. With this collapse, nations had to find other, more expensive sources of feed, causing world meat prices to rise.
The scientists and forecasters have spoken and the data is clear, a severe storm is coming. Emergency managers and public safety officials are gearing up to ensure that they are ready to respond to the storms, flooding, and droughts that El Niño 2015 augurs.
**Data is from