Abstract:

Extreme temperature events pose serious risks to society and ecosystems. While mean warming is well established, changes in the variance of surface temperature are equally critical for understanding future extremes. In my PhD work, focusing on synoptic surface air temperature variance over ocean, we developed an energy-based scaling framework derived from the moist static energy (MSE) variance budget, connecting horizontal advection to energetic damping at the surface. The variance is expressed as a balance between generation by horizontal moist energy transport and dissipation by radiation and turbulent fluxes. Linearization separates the damping into dry processes (longwave radiation and sensible heat) and moist processes (evaporative cooling following Clausius–Clapeyron scaling). This leads to a scaling estimate in terms of diffusivity, dry static energy (DSE) and MSE gradients, and a CC factor tied to mean temperature.

In idealized aquaplanet simulations, variance decreases under CO₂ forcing, primarily due to weakened eddy heat flux from reduced equator-to-pole gradients. Changes in evaporative cooling and strengthened MSE gradients exert secondary but opposing effects, highlighting the dual role of moisture processes.

In the Southern Hemisphere ocean within CESM2 Large Ensemble (LENS2), surface temperature variance intensifies and shifts poleward under SSP370. These patterns arise from enhanced DSE and MSE gradients that amplify variance, counteracted by reduced diffusivity and stronger evaporative CC damping.

Together, these studies establish the framework as a physically grounded tool for diagnosing and constraining synoptic surface air temperature variability over ocean in a warming climate.