Subseasonal forecast barrier of the North Atlantic oscillation in S2S models during the extreme mei-yu rainfall event in 2020

Abstract

Enhanced predictability of high-impact weather events is a Subseasonal to Seasonal Prediction Project (S2S) priority. In early summer 2020, a record-breaking heavy rainfall event occurred over the Yangtze River valley during the mei-yu season (June and July). Here we evaluate the S2S model forecast performance concerning the summer 2020 extreme mei-yu event over the Yangtze River valley. Our results show all operational S2S models exhibit fluctuating high-low-high forecast skill patterns during this three-stage mei-yu event, determined by different dominant circulations. In particular, the poor midlatitude circulation forecast (low trough over northern China) in the North Atlantic Oscillation (NAO) negative phase, with relative more contribution than that of the low-latitude circulation (western North Pacific subtropical high and South Asian high), decreases the model forecast skill for mei-yu rainfall in early-mid July. The prediction barrier of the NAO pattern and its downstream response, via the eastward-propagating wave train, jointly decrease the rainfall forecast skill during the NAO active negative period. Therefore, the skillful model prediction of the active summer NAO could help predict mei-yu events in the East Asian summer monsoon, suggesting further model improvements to the S2S forecasting of summertime mid-latitude variations are urgently needed.

Glo3DHydroClimEventSet(v1.0): A global‐scale event set of hydroclimatic extremes detected with the 3D DBSCAN‐based workflow (1951–2022)

“…Associated detection results and intercomparisons are displayed in the time‐longitude diagrams (Figure 5) and spatial distributions (Figure 6). As reported previously, the record‐breaking Meiyu‐related extreme precipitation events occurred over MLRYR in June and July 2020 (Yan et al, 2022; Zheng & Wang, 2021; Zhou et al, 2021), characterized by an advanced onset, long‐term persistence and delated retreat (Ding et al, 2021; Qiao et al, 2021). Regarding process evolutions, the 2020 MLRYR extreme precipitations are caused by two‐stage front‐related heavy rainfalls.…”

Subseasonal Predictability of the July 2021 Extreme Rainfall Event Over Henan China in S2S Operational Models

“…Tropical variability provides the major source of subseasonal predictability. Our previous studies have revealed that the subseasonal predictability of the East Asia summer monsoon in S2S models is driven by tropical variability but largely constrained by the poor skill of mid‐high latitude atmospheric variations (Liu et al., 2020; Yan et al., 2022). Generally, the S2S model forecast skills for weekly accumulated precipitation were low when the lead time was beyond 2 weeks in extratropical continental areas (de Andrade et al., 2019; Li & Robertson, 2015).…”

“…Recently, Domeisen et al (2022) analyzed the advances in S2S probabilistic forecasts of several extreme rainfall events and illustrated the potential for event-dependent advance warnings. However, the S2S models show distinct forecast skills and effective lead times for individual heavy rainfall events, depending on the broad-scale atmospheric conditions and oceanic signals (e.g., Cowan et al, 2019;Doss-Gollin et al, 2018;Yan et al, 2022).…”

Orographic mechanical and surface thermal effects of the Tibetan–Iranian Plateau on extratropical intraseasonal waves in boreal summer: numerical experiments

“…Numerous studies have identified the importance of extratropical intraseasonal oscillations along the SJ (EISO-SJ) on causing regional subseasonal variations and frequently triggering extreme meteorological events, such as heatwaves (Schubert et al 2011, Gao et al 2018 and flooding (Dugam et al 2009, Li et al 2021. Meanwhile, EISO-SJ has been proven to significantly affect the local subseasonal prediction skills (Qi and Yang 2019, Liu et al 2020, Yan et al 2021, 2022 and even provides a window of opportunity for East Asian subseasonal prediction (Zhu et al 2023). Therefore, understanding the factors affecting the variations and features of EISO-SJ is crucial for the subseasonal community.…”