Tropical cyclone sensitivities to CO2 doubling: roles of atmospheric resolution, synoptic variability and background climate changes

Gabriel A Vecchi,Jane W Baldwin,James A Smith,Ching Ho Justin Ng,William Cooke,V Balaji,Keith W Dixon,Nathaniel C Johnson,S J Lin ,Karin Van Der Wiel,Fanrong Zeng,T L Delworth ,Gabriele Villarini,Jie He,Andrew T Wittenberg,Wei Zhang,Jan–Huey –H Chen ,W Anderson ,Kieran T Bhatia,Thomas R Knutson,Maofeng Liu,Hiroyuki Murakami,R Gudgel ,Sarah B Kapnick,Lucas Harris ,Seth Underwood ,Anthony Rosati,Liwei Jia,Xiaosong Yang

doi:10.1007/s00382-019-04913-y

Abstract

Responses of tropical cyclones (TCs) to CO2 doubling are explored using coupled global climate models (GCMs) with increasingly refined atmospheric/land horizontal grids (~ 200 km, ~ 50 km and ~ 25 km). The three models exhibit similar changes in background climate fields thought to regulate TC activity, such as relative sea surface temperature (SST), potential intensity, and wind shear. However, global TC frequency decreases substantially in the 50 km model, while the 25 km model shows no significant change. The ~ 25 km model also has a substantial and spatially-ubiquitous increase of Category 3–4–5 hurricanes. Idealized perturbation experiments are performed to understand the TC response. Each model’s transient fully-coupled 2 × CO2 TC activity response is largely recovered by “time-slice” experiments using time-invariant SST perturbations added to each model’s own SST climatology. The TC response to SST forcing depends on each model’s background climatological SST biases: removing these biases leads to a global TC intensity increase in the ~ 50 km model, and a global TC frequency increase in the ~ 25 km model, in response to CO2-induced warming patterns and CO2 doubling. Isolated CO2 doubling leads to a significant TC frequency decrease, while isolated uniform SST warming leads to a significant global TC frequency increase; the ~ 25 km model has a greater tendency for frequency increase. Global TC frequency responds to both (1) changes in TC “seeds”, which increase due to warming (more so in the ~ 25 km model) and decrease due to higher CO2 concentrations, and (2) less efficient development of these“seeds” into TCs, largely due to the nonlinear relation between temperature and saturation specific humidity.

Highlights

Understanding the response of the climate system to increasing greenhouse gases is a topic of substantial scientific interest, reflecting in large part the societal concern for potential future climatic changes, and the need to better understand the controls on past climates (e.g., Knutson et al 2010; Walsh et al 2016)
In response to the top of atmosphere (TOA) imbalance, there is a warming of the global surface (Fig. 1a), tropical ocean surface (Fig. 1c) and full ocean (Fig. 1d) in all the models, which continues after the C O2 levels are stabilized in year 171
We explore the response to CO2 doubling in three global coupled Global climate models (GCMs) (LOAR, FLOR, and HiFLOR) with identical oceans and sea ice components, and atmospheric and land components that differ only in their resolution

Summary

Introduction

Understanding the response of the climate system to increasing greenhouse gases is a topic of substantial scientific interest, reflecting in large part the societal concern for potential future climatic changes, and the need to better understand the controls on past climates (e.g., Knutson et al 2010; Walsh et al 2016). GCMs have advanced our understanding of spatial and temporal variability of TC genesis and landfall (Sugi and Yoshimura 2012; Zarzycki and Jablonowski 2014; Roberts et al 2015; Camargo 2013; Camargo and Wing 2016; Murakami et al 2017a, b, 2018; Baldwin et al 2019), the association between climate oscillations and TCs (Bell et al 2014; Chand et al 2016; Vecchi et al 2014; Krishnamurthy et al 2016; Murakami et al 2016a, b; Zhang et al 2016), the responses of TCs to anthropogenic forcing, and provided projections for possible changes in the future (Yoshimura and Sugi 2005; Yoshimura et al 2006; Gualdi et al 2008; Zhao et al 2009; Murakami and Sugi 2010; Held and Zhao 2011; Mendelsohn et al 2012; Zhao and Held 2012; Knutson et al 2013, 2015; Kim et al 2014; Scoccimarro et al 2014; Villarini et al 2014b; Wehner et al 2015; Yamada et al 2017; Yoshida et al 2017; Bhatia et al 2018). In an effort to overcome the coarse resolution of most current climate models, statistical, dynamical and hybrid downscaling methods have been used to estimate the response of TCs to climate change and variability (e.g., Emanuel and Nolan 2004; Emanuel et al 2008; Knutson et al 2008; Bender et al 2010; Vecchi et al 2011, 2013; Emanuel 2013; Knutson et al 2013; Villarini et al 2012; Villarini and Vecchi 2012, 2013; Camargo and Wing 2016; Lee et al 2018)

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