Influence of ENSO on entry stratospheric water vapor in coupled chemistry-ocean CCMI and CMIP6 models

Abstract

<p>The connection between the dominant mode of interannual variability in the tropical troposphere, El Ni&#241;o Southern<br>Oscillation (ENSO), and entry of stratospheric water vapor, is analyzed in a set of the model simulations archived for the<br>Chemistry-Climate Model Initiative (CCMI) project and for phase 6 of the Coupled Model Intercomparison Project. While the<br>models agree on the temperature response to ENSO in the tropical troposphere and lower stratosphere, and all models also agree<br>&#160;on the zonal structure of the response in the tropical tropopause layer, the only aspect of the entry water vapor with consensus<br>is that La Ni&#241;a leads to moistening in winter relative to neutral ENSO. For El Ni&#241;o and for other seasons there are significant<br>differences among the models. For example, some models find that the enhanced water vapor for La Ni&#241;a in the winter of the<br>event reverses in spring and summer, other models find that this moistening persists, while some show a nonlinear response<br>with both El Ni&#241;o and La Ni&#241;a leading to enhanced water vapor in both winter, spring, and summer. A moistening in the spring<br>&#160;following El Ni&#241;o events, perhaps the strongest signal in observations, is simulated by only half of the models. Focusing on<br>Central Pacific ENSO versus East Pacific ENSO, or temperatures in the mid-troposphere as compared to temperatures near the<br>surface, does not narrow the inter-model discrepancies. Despite this diversity in response, the temperature response near the<br>cold point can explain the response of water vapor when each model is considered separately. While the observational record is<br>too short to fully constrain the response to ENSO, it is clear that most models suffer from biases in the magnitude of interannual<br>variability of entry water vapor. This bias could be due to biased cold point temperatures in some models, but others appear to<br>be missing forcing processes that contribute to observed variability near the cold point</p>