From Radiative Saturation to Temperature–Wind Synergy: Driving Mechanisms of Extreme Potential Evapotranspiration in the Wei River Basin

Abstract

Potential evapotranspiration (PET) is a core indicator of atmospheric evaporative demand and plays a critical role in drought dynamics. Yet the characteristics of extreme PET events and their governing mechanisms remain poorly understood. Unlike previous studies that have mainly focused on mean-state PET, this study provides the first systematic identification and attribution of extreme PET events in a representative semi-humid to semi-arid climatic transition zone. This study investigates the spatiotemporal evolution and driving mechanisms of extreme PET in the Wei River Basin, using daily meteorological data from 1975 to 2019, the FAO-56 Penman–Monteith equation, and an adapted thirstwaves identification framework. A three-dimensional indicator system comprising magnitude intensity (MI, severity), temporal intensity (TI, mean duration), and frequency intensity (QI, occurrence frequency) is constructed, and integrated methods including the variance-corrected Mann–Kendall test, wavelet analysis, conditional sensitivity analysis, and cross-wavelet transform are employed. Results reveal that extreme PET exhibits pronounced spatial heterogeneity, with higher intensity in drier northwest and longer duration and higher frequency in the southeast. Trend directions vary substantially across stations, while multi-scale periodic oscillations of 5–15 years are identified. Conditional sensitivity analysis indicates that PET is most sensitive to sunshine duration overall, but its relative sensitivity decreases under extreme conditions, indicating a radiative saturation effect. In contrast, the synergistic enhancement of maximum temperature and wind speed becomes the primary driver pushing PET beyond extreme thresholds, with the strongest synergy in the semi-arid northwestern WRB. PET is more sensitive to relative humidity in the southeastern Guanzhong Plain, while atmospheric pressure has only a weak influence across the basin. Cross-wavelet analysis further shows that ENSO and PDO significantly modulate the cyclic variations of extreme PET, yet their teleconnection signals are attenuated compared to those for average PET. In sharp contrast, the Arctic Oscillation (AO) exhibits negligible influence on the basin’s extreme PET, highlighting the seasonal decoupling of high-latitude atmospheric signals from regional evaporative demand during the growing season. Notably, annual mean PET shows a significant upward trend, whereas extreme PET exhibits no significant trend, indicating that the “evaporation variability increase” hypothesis does not hold in the WRB. This implies that SPEI-based drought monitoring relying on mean PET may not fully capture changes in extreme evapotranspiration. These findings advance the mechanistic understanding of extreme evapotranspiration, highlight the regime shift in relative importance from radiation to temperature-wind synergy under extreme conditions, and provide scientific support for drought adaptation and water resource management in climatically sensitive regions.