Evaluating Wave‐Train and Blocking Type Cold Surges in Reanalysis and CMIP6 Simulations Using an Index‐Based Approach

ABSTRACT

East Asian winter cold surges are classified into two major types based on their dynamical pathways: the wave‐train type (WT), driven by upstream Rossby waves, and the blocking type (BT), linked to quasi‐stationary high‐latitude anomalies. The wave‐train index (WI) and blocking index (BI) have been used to classify cold surge events that were first identified using surface temperature and Siberian High criteria, but their utility for detecting cold surge candidates directly from index time series has not been fully evaluated. Here, we evaluate the WI and BI as an index‐based detection framework for WT and BT cold surge candidates and apply it to ERA5 and to historical and four SSP scenario simulations from seven CMIP6 models. In ERA5, the detected candidates reproduce characteristic cold surge signatures, including surface cooling, Siberian High intensification and distinct upper‐tropospheric structures. The CMIP6 historical multi‐model simulations reproduce similar spatial patterns and lag evolution, supporting the framework's applicability to model simulations. Across the SSP projection period (2015/16–2099/2100), candidate frequencies defined relative to the fixed 1979/80–2014/15 climatology show relatively small changes under SSP1‐2.6 and SSP2‐4.5, whereas SSP3‐7.0 and SSP5‐8.5 exhibit increasing WT and decreasing BT candidate frequencies, with broad model agreement in the direction of change. Overall, WI and BI provide a compact framework for index‐based detection of cold surge candidates from upper‐tropospheric circulation alone, with applications in climate projection and potential relevance for subseasonal prediction.