Key Multi-scale Factors Determining Convection Initiation and Forecast Skill on the Rear Side of the Northeast China Cold Vortex

The Northeast China Cold Vortex (NCCV) is the primary synoptic system causing severe weather in North China and more than 70% of convective events associated with the NCCV occur in its southeast and southwest sides; however, forecasting first convection initiation (first CI) in its rear side remains highly challenging. This study investigates the underlying CI triggering mechanisms and the causes of low forecast skill in this regime. Using 2016–2021 mosaic reflectivity from seven operational Doppler radars and a modified convective tracking algorithm, we map first-CI distributions and evaluate Numerical Weather Prediction model (NWP) simulations to pinpoint low-forecasting-skill regions (the plain region between Beijing and Tianjin). A representative case (8 June 2019) is then diagnosed using a high-resolution rapid-update (3-km, 12-min) analysis assimilating radar and dense-surface-network observations.

Results show that CI is driven by complex interactions among a cold, dry northerly flow, a warm, moist southerly flow, and a modified sea-breeze front (SBF). Near 850 hPa, the converging northerly and southerly flows generate localized weak convergence and high humidity. Simultaneously, the topographically deflected, inland-propagating SBF forces intense near-surface convergence with the prevailing southerly flow. This combined dynamic forcing establishes a deep updraft channel that successfully initiates convection.

Diagnostics reveal that NWP forecast failures primarily stem from inaccuracies in simulating nocturnal boundary layer wind fields. Although the model similarly captures synoptic-scale forcing and the moisture environment, it produces an anomalously strong low-layer northerly flow. This overestimation blocks the inland penetration of the SBF, thereby eliminating the critical near-surface convergence zone. Absent this essential dynamic trigger, accumulated convective instability cannot be released, resulting in missed CI forecasts. This study addresses the critical challenge of forecasting CI events associated with the R-NCCV, which are notoriously difficult to predict due to their weak synoptic forcing. We have identified the key multiscale factors of a representative event and elucidated how their misrepresentation compromises prediction accuracy.