Salty Oceans Can Forecast Rain On Land

2016-12-20T17:07:34+00:00 December 20, 2016|
Scientists used ocean salinity to predict terrestrial rainfall. (Credit: Darren Barefoot/Flickr)

(Click to enlarge) Scientists used ocean salinity to predict terrestrial rainfall. (Credit: Darren Barefoot/Flickr)

At this week’s American Geophysical Union meeting, a team of researchers from the Woods Hole Oceanographic Institution (WHOI) presented their latest research findings on the long-range predictions of rainfall on land. Their method is based on ocean salinity rather than sea surface temperatures, which has been the standard for decades.

(From– Using this method, a research team led by Ray Schmitt, a physical oceanographer at WHOI, was able to successfully predict the extreme event that flooded states throughout the Midwest in the summer of 2015. The results of the study will be published in a paper currently in review.

Researchers analyzed more than 60 years of global and terrestrial rainfall data and found that year-to-year variations in salinity, or saltiness, in certain parts of the ocean can be used to make accurate predictions of seasonal rainfall on land, often thousand of miles away.

“When we started analyzing the records, we found these ‘teleconnections’ between regions of ocean salinity and certain regions of higher precipitation on land,” he explains.

Schmitt and his colleagues first found evidence of a clear link between higher levels in the North Atlantic Ocean and increased rainfall on land in the African Sahel—the area between the Sahara Desert and the savannah across Central Africa. The results were published in the May 6, 2016 issue of Science Advances

Schmitt and his colleagues also found that high springtime salinity in the western North Atlantic correlates with high summer rainfall in the U.S. Midwest. Those results were published in the May 1, 2016 issue of the Journal of Climate.

“We can use patterns of salinity variations to predict rain a season in advance because there is about a three-month delay between the high patterns and the resulting rainfall on land. Also, low springtime salinity is a good predictor of summer drought in the Midwest.” Schmitt says. Their analysis uses sophisticated “machine learning” techniques to identify and rank the best climate variables for rainfall predictions and salinity proves to be the most reliable for many areas. 

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