Imagine an orchestra playing without a conductor. Each section takes its turn: first the winds introduce the theme, then the strings join in, and sometimes an unexpected percussionist solos. So it is with weather over North America: the atmosphere, ocean, and land take turns in the lead role when it comes to predicting large-scale weather regimes on timescales from a week to two months.
Weather regimes are persistent patterns of atmospheric circulation that determine whether a winter will be unusually warm or a summer dry. There are four of them: the Pacific Trough, the Pacific Ridge, the Greenland Maximum, and the Alaskan Ridge. Plus, there are days when no regime is expressed, which they call "No Regime." To understand which "musician" matters most at different forecast lead times, the scientists trained hundreds of machine learning models, each receiving only one variable as input, for example, sea surface temperature or soil moisture.
Season shifts the balance of power. In winter and summer, predictability is higher than in spring and autumn, because the atmosphere more often gets stuck in one regime. For the Pacific Trough in autumn and winter, the ocean makes a key contribution, especially signals from El Niño, the warm phase of the Pacific sea surface temperature oscillation. For the Pacific Ridge in winter, stratospheric winds and sea ice are important. And the Greenland Maximum in winter depends on tropical convection and soil conditions.
The analysis showed that accurate forecasts are linked to specific anomalies. For example, enhanced convection over the central tropical Pacific precedes the Pacific Trough, while zonal wind anomalies in the southern tropical stratosphere precede the Pacific Ridge. This means that to improve forecasts, we need not just add more data, but understand which component of the Earth system matters in a given situation.
An orchestra without a conductor plays harmoniously if you know who comes in next. So it is with subseasonal forecasting: the atmosphere sets the tone in the first two weeks, then the ocean and land pick up the melody. And if meteorologists learn to hear each instrument individually, warnings about weather anomalies will become more accurate.
The frequency of the 'No Regime' class varies from 18% in winter to 44% in summer, making summer forecasts particularly difficult: the atmosphere is more often in a transitional state without a pronounced large-scale structure.
In Kim Stanley Robinson's novel 'Forty Signs of Rain', scientists attempt to predict abrupt changes in weather regimes due to a shutdown of the Gulf Stream. This study resonates with that idea: it shows which slow components of the Earth system might serve as early indicators of circulation regime shifts.