Contribution of different processes to changes in tropical lower-stratospheric water vapor in chemistry–climate models
Kevin M. Smalley1,Andrew E. Dessler1,Slimane Bekki2,Makoto Deushi3,Marion Marchand2,Olaf Morgenstern4,David A. Plummer5,Kiyotaka Shibata6,Yousuke Yamashita7,a,and Guang Zeng4Kevin M. Smalley et al.Kevin M. Smalley1,Andrew E. Dessler1,Slimane Bekki2,Makoto Deushi3,Marion Marchand2,Olaf Morgenstern4,David A. Plummer5,Kiyotaka Shibata6,Yousuke Yamashita7,a,and Guang Zeng4
Received: 28 Oct 2016 – Discussion started: 08 Nov 2016 – Revised: 15 May 2017 – Accepted: 29 May 2017 – Published: 04 Jul 2017
Abstract. Variations in tropical lower-stratospheric humidity influence both the chemistry and climate of the atmosphere. We analyze tropical lower-stratospheric water vapor in 21st century simulations from 12 state-of-the-art chemistry–climate models (CCMs), using a linear regression model to determine the factors driving the trends and variability. Within CCMs, warming of the troposphere primarily drives the long-term trend in stratospheric humidity. This is partially offset in most CCMs by an increase in the strength of the Brewer–Dobson circulation, which tends to cool the tropical tropopause layer (TTL). We also apply the regression model to individual decades from the 21st century CCM runs and compare them to a regression of a decade of observations. Many of the CCMs, but not all, compare well with these observations, lending credibility to their predictions. One notable deficiency is that most CCMs underestimate the impact of the quasi-biennial oscillation on lower-stratospheric water vapor. Our analysis provides a new and potentially superior way to evaluate model trends in lower-stratospheric humidity.
This paper explains a new way to evaluate simulated lower-stratospheric water vapor. We use a multivariate linear regression to predict 21st century lower stratospheric water vapor within 12 chemistry climate models using tropospheric warming, the Brewer–Dobson circulation, and the quasi-biennial oscillation as predictors. This methodology produce strong fits to simulated water vapor, and potentially represents a superior method to evaluate model trends in lower-stratospheric water vapor.
This paper explains a new way to evaluate simulated lower-stratospheric water vapor. We use a...