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Abstract
Increases in day-to-day temperature variation (DTDV) elevate the risk of weather extremes and impose significant health, ecological, and economic burdens, yet few studies specifically investigated their anthropogenic drivers at regional hotspotsespecially in spring, when rapid warming may trigger earlier heat events. Here, we identified the Yangtze River Valley (YRV) as a hotspot exhibiting the strongest springtime DTDV increases and quantified anthropogenic contributions on mean DTDV and its extremes-DTDX (largest warming) and DTDN (largest cooling).CMIP6 models captured the DTDV upward trend but underestimated its magnitude.Optimal fingerprinting identified anthropogenic signals dominated by greenhouse gases (GHGs) in mean DTDV and DTDX, with GHGs explaining ~35-69% of the observed changes, while DTDN was largely affected by internal variability. Projections suggested continued intensification of DTDV by up to 7.14% in this hotspot. Given model underestimation, actual DTDV changes may be more frequent and severe but could be reduced by emission mitigation.
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Citation
Heyang Song, Ying Sun. 2026: Yangtze River Valley as a Hotspot of Human-induced Increases in Day-to-day Temperature Variation. Journal of Meteorological Research. DOI: 10.1007/s13351-026-5292-5
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Heyang Song, Ying Sun. 2026: Yangtze River Valley as a Hotspot of Human-induced Increases in Day-to-day Temperature Variation. Journal of Meteorological Research. DOI: 10.1007/s13351-026-5292-5
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Heyang Song, Ying Sun. 2026: Yangtze River Valley as a Hotspot of Human-induced Increases in Day-to-day Temperature Variation. Journal of Meteorological Research. DOI: 10.1007/s13351-026-5292-5
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Heyang Song, Ying Sun. 2026: Yangtze River Valley as a Hotspot of Human-induced Increases in Day-to-day Temperature Variation. Journal of Meteorological Research. DOI: 10.1007/s13351-026-5292-5
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