GPS Seminars & Events

Regional hydroclimate projections are often viewed as deeply uncertain due to differences in simulated atmospheric circulation responses, yet many key features of projected change in the Western United States, including extreme precipitation intensification, snowpack loss, and shifts in runoff timing, are remarkably robust across models and downscaling approaches. In this talk, I argue that this robustness arises because the forced response of the regional hydroclimate system is primarily thermodynamically controlled. Using dynamical downscaling experiments that isolate thermodynamic and dynamical contributions, along with moisture budget diagnostics, I show that much of the regional response can be reproduced from thermodynamic forcing alone, with circulation changes playing a secondary, modulating role. I then synthesize results across multiple components of the water cycle to show how this framework explains both robust signals and key uncertainties. I suggest that similar thermodynamic constraints may govern hydroclimate responses in other regions, even where evidence remains more limited. Finally, I discuss implications of this framework for water resources and wildfire, where thermodynamically driven changes in moisture availability and variability propagate through the system to shape risks.

Regional hydroclimate projections are often viewed as deeply uncertain due to differences in simulated atmospheric circulation responses, yet many key features of projected change in the Western United States, including extreme precipitation intensification, snowpack loss, and shifts in runoff timing, are remarkably robust across models and downscaling approaches. In this talk, I argue that this robustness arises because the forced response of the regional hydroclimate system is primarily thermodynamically controlled. Using dynamical downscaling experiments that isolate thermodynamic and dynamical contributions, along with moisture budget diagnostics, I show that much of the regional response can be reproduced from thermodynamic forcing alone, with circulation changes playing a secondary, modulating role. I then synthesize results across multiple components of the water cycle to show how this framework explains both robust signals and key uncertainties. I suggest that similar thermodynamic constraints may govern hydroclimate responses in other regions, even where evidence remains more limited. Finally, I discuss implications of this framework for water resources and wildfire, where thermodynamically driven changes in moisture availability and variability propagate through the system to shape risks.

Methane (CH4) is the second most important anthropogenic greenhouse gas after carbon dioxide, yet its variability and long-term increase remain poorly understood, in part because of large uncertainties in atmospheric removal processes. Stratospheric CH4 oxidation represents an important sink in the global methane budget and a major source of stratospheric water vapor, while methane–chlorine reactions further modulate catalytic ozone chemistry. Until now, estimates of stratospheric CH4 chemical loss have relied exclusively on chemistry–climate models (CCMs), resulting in substantial uncertainty. Here, I present an observationally based estimate of stratospheric methane loss (LSTR), derived from the CH4 diabatic flux across an isentropic surface fitted to the tropical tropopause using satellite observations of CH4 concentrations, temperature, and radiative heating rates. It is shown that both reanalysis and CCMs systematically underestimate stratospheric methane loss. Incorporating our observational estimate of LSTR into the bottom-up global methane budget reduces the reported imbalance for the 2000s, bringing it into close agreement with the imbalance inferred from top-down estimates. These results demonstrate the critical role of observational constraints on stratospheric methane loss in reconciling the global CH4 budget and carry important implications for understanding stratospheric water vapor and ozone chemistry.