Extratropical Prediction Skill of the Subseasonal‐to‐Seasonal (S2S) Prediction Models

Abstract

The deterministic prediction skill of the 10 operational models participating in the subseasonal‐to‐seasonal (S2S) prediction project is assessed for both the extratropical stratosphere and troposphere. Based on the mean squared skill score of 50‐ and 500‐hPa geopotential height forecasts, the overall prediction skill is on average 16 days in the stratosphere and 9 days in the troposphere. The high‐top models with a fully resolved stratosphere typically have a higher prediction skill than the low‐top models. Among them, the European Centre for Medium‐Range Weather Forecasts model shows the best performance in both hemispheres. The decomposition of model errors reveals that eddy errors are more important than zonal‐mean errors in both the stratosphere and troposphere. While the errors in the stratosphere are dominated by planetary‐scale eddies, those in the troposphere are equally influenced by planetary‐ and synoptic‐scale eddies. This result indicates that subseasonal‐to‐seasonal prediction could be improved by better representing planetary‐scale wave activities in the model.

Stratospheric drivers of extreme events at the Earth’s surface

“…For example, many climate models either cannot intrinsically simulate a QBO or simulate a degraded version 76 , and forecast models initialized with QBO winds lose information about the amplitude and even sign of tropical winds within 1-2 weeks 118 . The full spectrum and amplitude of wave coupling linking the troposphere and the stratosphere is also not well represented or poorly parameterized 119,120 . Other stratospheric processes that are not yet well captured by many numerical models, such as interactive ozone chemistry or radiative effects of aerosols, may influence extremes in ways that remain to be determined.…”

Long Range Prediction and the Stratosphere

“…The climate system contains significant unpredictable variance and -for daily weather fluctuations at least -it is thought to have a deterministic predictability horizon of around two weeks due to the sensitivity of the evolution of the atmospheric state to small errors in initial conditions (Lorenz 1969)the so-called 'butterfly effect'. Recent estimates (Leung et al, 2020;Domeisen et al, 2018) as well as tests of the predictability of midlatitude daily weather using the latest global prediction models (Zhang et al, 2019;Son et al, 2020) produce similar estimates for this predictability limit. However, this does not preclude skilful forecasts of the statistics (most notably the average) of conditions at long range beyond this timescale (e.g.…”

“…These fluctuations also show a tendency to vacillate between strong westerly and weak (SSW) states on subseasonal timescales (Kuroda and Kodera 2001;Hardiman et al, 2020a). The changes in the troposphere persist roughly as long as those in the lower stratosphere, and last for around two months (Baldwin and Dunkerton 2001;Baldwin et al, 2003;Hitchcock et al, 2013;Son et al, 2020;Domeisen 2019). The impacts on surface climate also affect the frequency of extremes of temperature and rainfall King et al, 2019;Cai et al, 2016;Domeisen et al, 2020b).…”

Representation of the Scandinavia–Greenland pattern and its relationship with the polar vortex in S2S forecast models

“…Weak or disrupted SPV states are driven by the vertical propagation and subsequent breaking of large-scale (planetary wavenumbers 1-3) Rossby waves from the troposphere to the stratosphere (Charney and Drazin, 1961;Matsuno, 1971;McIntyre and Palmer, 1983), although the tropospheric wave activity need not be anomalously large, with preconditioning of the SPV playing an important role (Birner and Albers, 2017;De La Cámara et al, 2019;Lawrence and Manney, 2020). Despite substantially longer predictability and persistence timescales in the stratosphere than in the troposphere (e.g., Baldwin et al, 2003;Son et al, 2020), predicting the onset of significant SPV circulation anomalies on S2S timescales remains challenging and is likely to be a contributing factor to poor skill in wintertime NH subseasonal forecasts. Several recent studies have analysed the performance of prediction systems contributing to the World Climate Research Program and World Weather Research Program S2S Prediction Project database (Vitart et al, 2017), comprising operational forecasts and hindcasts from various modelling centres around the world.…”

“…Despite substantially longer predictability and persistence timescales in the stratosphere than in the troposphere (e.g., Baldwin et al ., 2003; Son et al ., 2020), predicting the onset of significant SPV circulation anomalies on S2S timescales remains challenging and is likely to be a contributing factor to poor skill in wintertime NH subseasonal forecasts. Several recent studies have analysed the performance of prediction systems contributing to the World Climate Research Program and World Weather Research Program S2S Prediction Project database (Vitart et al ., 2017), comprising operational forecasts and hindcasts from various modelling centres around the world.…”