A recent analysis by ForecastWatch found that the extreme heat wave in the Pacific Northwest and southwest Canada was forecast by computer models further in advance than nearly every human developed forecast. Recent technological advances are making it possible to forecast the potential for extreme weather events such as this up to 2-4 weeks in advance, according to a recent paper published in the Bulletin of the American Meteorological Society. This increased ability for subseasonal forecasting is very beneficial to industries such as the energy sector, where preparation for upcoming extreme events that can challenge power grids will make the difference between a large-scale power grid failure and energy stability during the event when demand becomes considerable.
The study found that heat waves show some predictability up to 3-4 weeks in advance, cold spells up to 2-3 weeks in advance, and tropical cyclones up to 3 weeks in advance, with shorter advance predictability for precipitation and extratropical cyclone extremes.
These longer predictions are often made by examining processes that move much more slowly than day-to-day weather, such as ocean temperatures. For example, seasonal forecasts made by the Climate Prediction Center are based partly on ocean temperature patterns and atmosphere-ocean interactions (also called teleconnection indices) such as La Niña, El Niño, the Pacific Decadal Oscillation, and the Arctic Oscillation. The large negative Pacific Decadal Oscillation helped play some part in a wetter than normal spring for the Pacific Northwest in 2022, with cooler ocean temperatures west of the Pacific Northwest coast that helped support more upper-air troughs than in an average spring.
Energy companies, particularly those in the renewable sector, have been slow to make use of these long-term forecasts. Understandably, it can be difficult to trust forecasts of wind or sunshine in the long range. Additional studies have shown that teleconnection indices and ensemble predictions of geopotential height can lead to predictions of wind and solar energy up to 2-3 weeks in advance that are at least slightly better than climatological forecasts of these variables – findings that can increase energy companies’ confidence in these long-term forecasts and potentially lead to increased cost savings. For example, the February 2021 Texas cold snap and June 2021 Pacific Northwest heat wave both had some long-range indications before the magnitude of each event became more apparent as the events neared. Increased preparation for these events in the long range may have led to increased anticipation in energy demand further in advance before each event.
For a more comprehensive summary of the research into subseasonal forecast impacts to the energy sector, see this news release from The Washington Post.
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