Distinct Roles of Key Driving Factors in Compound Heat‐Drought Days Over Eastern China’s Hotspots

ABSTRACT

Compound heat‐drought days (CHDDs) are frequent in eastern China's summer, peaking in June–July over North China (NC) and July–August in the middle and lower reaches of the Yangtze River (YR), threatening crops, human health and energy supplies. This study compares their thermodynamic mechanisms driving CHDDs in the two regions. Both experience lower‐tropospheric anticyclonic anomalies with enhanced subsidence, with land–atmosphere processes varying between the two regions. In NC, limited soil moisture suppresses evapotranspiration, converting energy to sensible heat and reinforcing hotter–drier conditions. In YR, abundant moisture sustains evapotranspiration, prolonging heat while intensifying drought through moisture loss. The formation of these anomalous anticyclones is further modulated by preceding sea surface temperature (SST) and sea ice concentration (SIC). In NC, the cold‐phase North Atlantic tripole SST and increased Greenland‐Barents Seas SIC act together to excite high‐latitude Rossby wave trains under a weakened, southward‐shifted subtropical jet, producing a British‐Baikal Corridor‐like teleconnection that anchors a Mongolian high. Concurrently, a mega‐El Niño‐like SST anomaly induces a western North Pacific low through the Gill Matsuno response and Pacific‐Japan pattern, reinforcing the Mongolian‐NC high‐Pacific low dipole. In YR, the warm‐phase tripole SST and enhanced Barents‐Kara Seas SIC interact with a strengthened, northward‐shifted jet to generate a high‐latitude British‐Okhotsk Corridor‐like teleconnection and the mid‐latitude circumglobal‐like teleconnection. Meanwhile, a La Niña‐like SST pattern excites northwestward‐propagating Rossby waves and Pacific‐Japan pattern, helping maintain the anticyclonic system over the YR. These findings emphasise the synergistic influence of preceding surface factors in shaping CHDDs across eastern China and provide a physical basis for improving their prediction and early warning.