Interaction of ‘Saola’ & ‘Haikui’ cyclones to determine weather: SMG

2023-08-30 03:41
BY Ginnie Liang
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The Meteorological and Geophysical Bureau (SMG) said in a statement yesterday that the distance between tropical cyclones “Saola” and “Haikui” will shorten in the coming two to three days, causing them to interact with each other, making the paths of both even more difficult to predict.

The local observatory predicted that “Saola” would move towards the area south of Taiwan in the next few days, and was expected to come within 800 km of Macau tonight at the earliest.

The Hong Kong Observatory (HKO) said last night’s distance between the two tropical cyclones was about 1,500 km, and was expected to shorten to 1,000 km, which might trigger the so-called “Fujiwhara effect”, i.e., if one tropical cyclone is a lot stronger than the other, the smaller one will orbit it and eventually come crashing into its vortex to be absorbed.

However, the HKO pointed out that whether the two tropical cyclones will combine into one will depend on their intensity, as the two tropical cyclones are constantly changing their paths and speeds; and that if the distance between the two tropical cyclones is over 1,200 km, the opportunity of the two merging into one is low.

Macau’s weather station said that if “Haikui” develops fast, “Saola” will be on an easterly path, close to the coast of Fujian, or even pull back close to Taiwan, and if “Haikui” develops slowly, the path of “Saola” will be westward, close to the eastern part of Guangdong, and even close to the Pearl River Estuary, which would have a greater impact on Macau causing flooding in low-lying areas.

The bureau also said that due to the influence of the downdraft outside “Saola” and the drier northeast wind in the inland, it was expected that the temperature will rise, and there might be a few thunderstorms until the weekend. 


This weather map provided by the Meteorological and Geophysical Bureau (SMG) yesterday shows the possible routes of Tropical Cyclones “Saola” and “Haikui” under different prediction models from different countries.


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