Extreme environmental events have become a major interest of ecologists. Commonly, extreme climatic events are identified based on “changes in the mean conditions” over a discrete period with respect to the longer-term climatology. In this study we aim to: 1) define a different type of extreme event, i.e. weather extreme events: an event with extreme deviation from an expected value (calculated based on past weather conditions) and 2) quantify ecosystem resistance, recovery, and resilience in response to these shock events based on changes in net ecosystem productivity (NEP) measured over 16 years (2004 – 2019), in a montane mixed forest in Switzerland (CH-LAE, Lägeren). In addition to the identification of the physiological extreme events, we test the hypothesis that extremes associated with continuously varying environmental conditions can modify the physiological functionality of a forest ecosystem. We calculated weather extreme;based on half-hourly measurements of atmospheric water demand (i.e. vapor pressure deficit, VPD) measured alongside eddy covariance flux measurements. Between 2004 and 2019, we found 185 such physiological extreme events (VPD-extreme), ranging from one to seven days, that occurred about 27 % in spring and 68 % in summer. On average NEP decreased by 25% during these VPD-extreme days compared to the normal-VPD day before, resulting in mean resistance (NEPextreme/NEPpre-extreme) of 0.75. Mean recovery (NEPpost-extreme/NEEextreme) was about 0.85, indicating about a 15% decrease in NEP on days after the extreme events compared to before. There was no significant trend in resistance, recovery, and resilience over the 16 years. Finally, decreased functionality during these VPD-extreme days events confirms our hypothesis. Our approach of looking at the forest response to extreme events is independent of “changes of mean conditions from long-term climatology” and focuses on the ability of the ecosystem to maintain functionality within the realm of “continuous environmental variability”. Identification of physiologically-relevant climatic extremes and testing the legacy effect from those events is a crucial requirement for understanding the future response of forests to climate change.