Predicting extreme rain events months in advance is difficult for farmers and city managers in the Midwest. Heavy summer rains are good indicators of saltier ocean surface, according to a new study.
The weather in the Midwest is connected to the Pacific and Atlantic oceans, with wind patterns delivering heat and humidity to the region at different times. Sea surface temperatures have been used by scientists to predict how wind patterns will behave and what the weather will be thousands of kilometers away from the ocean.
Farmers looking to time their planting with the rains aren't helped by the fact that the sea surface temperature is very variable and can be hit or miss. Adding data about how much water is in the atmosphere improves predictions for the season.
The ocean gets a little bit saltier when water leaves it. Saltiness is an indicator for the amount of water carried by the atmosphere and the weather patterns in where it will rain out.
"For these seasonal weather patterns, we look at the oceans because they store far more heat and water than the atmosphere, and therefore drive large-scale atmospheric patterns," said Raymond Schmitt, a coauthor of the new study.
Schmitt and colleagues have been able to draw connections between weather patterns and the amount of salt in the ocean with the help of remote sensors.
"For extreme precipitation years, patterns of sea surface temperature are just really diverse, with different patterns every year," said Li, a climate scientist at Pennsylvania State University. She said that salinity is more reliable with more consistency in patterns.
The new study builds on previous work. Schmitt is working with agricultural suppliers to use salinity-based predictions, which he says they have found helpful for advising farmers.
Summer rains.
The study improves predictions of magnitude for summer extreme rainfall events in the Midwest, which are more difficult to predict than overall rainfall for a season. Li compared the sea surface temperature and salinity records in different parts of the Pacific and Atlantic oceans during the same time period.
By incorporating springtime sea surface salinity in the tropical Pacific and subtropical North Atlantic into their models, they found that their predictions for summertime extreme rain events were more accurate than their sea surface temperature based predictions. Their models using salt captured more variability in the amount of extreme rains than their models using sea surface temperature.
It can be difficult to understand the relationship between sea surface temperatures and tropical precipitation. Nathaniel Johnson, a research meteorologist with the National Oceanographic and Atmospheric Administration, was not involved in the study. I like the idea of sea surface salt as a proxy for atmospheric processes in the tropics, and it's a very provocative idea.
Billions of dollars in damage and economic losses can be caused by heavy rains in the Midwest. The "Great Flood" of 1993, which flooded the Mississippi and Missouri Rivers, caused about fifteen billion dollars in damages. If the predictors were put in place, the losses would be less than half. Accurately predicting extreme rains could help energy managers estimate demand for summer heating, as dry summers are more likely to be hot, and manage water in hydroelectric systems.
More information: Laifang Li et al, Skillful Long‐Lead Prediction of Summertime Heavy Rainfall in the US Midwest From Sea Surface Salinity, Geophysical Research Letters (2022). DOI: 10.1029/2022GL098554 Journal information: Geophysical Research Letters
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