A climate model can now reliably predict the Asian summer monsoon – and tropical cyclone activity associated with it – more than one year ahead of time, which could enable government agencies to make preparations for damaging weather events.
Yuhei Takaya at the Japan Meteorological Agency and his colleagues have developed a climate prediction system that takes into account both historical and up-to-date meteorological measurements to simulate atmospheric changes and temperatures on land and in the ocean. The key to its long-range forecasting is the ability to predict when an El Niño-Southern Oscillation will occur.
“When an El Niño occurs, the Indian Ocean warms during the fall to winter and this persists in the next summer,” says Takaya. The resulting warm conditions in the Indian Ocean have a significant effect on the Asian summer monsoon, he says.
The team’s model was tested using oceanic and climate data gathered between 1980 and 2016. Given meteorological data for a particular year, the model predicts what will happen the following summer, including the sea surface temperature, regional rainfall, and a weather pattern known as the western North Pacific monsoon.
“In summer we have droughts or floods associated with this variability,” he says.
The climate model predicted the strength of the monsoon a year ahead, measuring how linear the correlation is between real and predicted weather patterns with an value of 0.5, where a score of 1 indicates a perfect correlation. It was more accurate at predicting temperatures over southeast Asia than predicting monsoon strength, with a score of 0.75.
Existing climate models used by meteorological centres are usually able to predict weather patterns six months in advance, says Takaya.
Extreme weather events such as heat waves or flooding have significant socio-economic impacts, particularly given that Asia is the world’s most populous continent, says Takaya. “If we can predict the temperature or the precipitation, we can better prepare for these extreme events,” he says.
Journal reference: Nature Communications, DOI: 10.1038/s41467-021-22299-6
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