Response of Tropical Cyclones to Idealized Climate Change Experiments in a Global High-Resolution Coupled General Circulation Model

Abstract

The authors present an assessment of how tropical cyclone activity might change owing to the influence of increased atmospheric carbon dioxide concentrations, using the U.K. High-Resolution Global Environment Model (HiGEM) with N144 resolution (;90 km in the atmosphere and ;40 km in the ocean). Tropical cyclones are identified using a feature-tracking algorithm applied to model output. Tropical cyclones from idealized 30-yr 23CO 2 (2CO2) and 43CO 2 (4CO2) simulations are compared to those identified in a 150-yr present-day simulation that is separated into a five-member ensemble of 30-yr integrations. Tropical cyclones are shown to decrease in frequency globally by 9% in the 2CO2 and 26% in the 4CO2. Tropical cyclones only become more intense in the 4CO2; however, uncoupled time slice experiments reveal an increase in intensity in the 2CO2. An investigation into the large-scale environmental conditions, known to influence tropical cyclone activity in the main development regions, is used to determine the response of tropical cyclone activity to increased atmospheric CO 2 . A weaker Walker circulation and a reduction in zonally averaged regions of updrafts lead to a shift in the location of tropical cyclones in the Northern Hemisphere. A decrease in mean ascent at 500 hPa contributes to the reduction of tropical cyclones in the 2CO2 in most basins. The larger reduction of tropical cyclones in the 4CO2 arises from further reduction of the mean ascent at 500 hPa and a large enhancement of vertical wind shear, especially in the Southern Hemisphere, North Atlantic, and northeast Pacific.

Past and Projected Changes in Western North Pacific Tropical Cyclone Exposure

“…A number of previous studies have explored relationships between WNP TC track characteristics and anthropogenic climate change and have identified systematic shifts in TC genesis location and steering flow that combine to cause TC track shifts (Wu and Wang 2004;Li et al 2010;Wang et al 2011;Murakami et al 2011Murakami et al , 2012Yokoi et al 2013;Bell et al 2013;Mori et al 2013;Manganello et al 2014;Wu et al 2014;Colbert et al 2015;Mei et al 2014Mei et al , 2015Roberts et al 2015;Wang and Wu 2015). There is, however, some divergence among the model projections in some of these studies.…”

Projected changes in medicanes in the HadGEM3 N512 high-resolution global climate model

“…SSTs and ice for the future simulations were determined by adding to the OSTIA SSTs, the change in SSTs from the RCP8.5 HadGEM2-ES coupled climate simulations performed for IPCC AR5. This study uses 26 The influence of the large scale environment on TC has initally been studied by Strachan et al (2013) and Bell et al (2013Bell et al ( , 2014 for the HadGEM1 model, then by Roberts et al (2015) for the HadGEM3 model. More generally, the HadGEM3 TC simulation skill has been tested in a large GCM intercomparison carried out by the CLIVAR Hurricane Working Group (Shaevitz et al 2014) including the response to natural and forced variability (Walsh et al 2014;Daloz et al 2015).…”

High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6

“…High horizontal resolution in the atmosphere has a positive impact in representing the non-Gaussian probability distribution associated with the climatology of quasi-persistent low-frequency variability weather regimes (Dawson et al, 2012). In addition, the increased resolution enables a more realistic simulation of small-scale phenomena with potentially severe impacts such as tropical cyclones (Shaevitz et al, 2015;Zhao et al, 2009;Bengtsson et al, 2007;Murakami et al, 2015;Walsh et al, 2012;Ohfuchi et al, 2004;Bell et al, 2013;Strachan et al, 2013;Walsh et al, 2015), tropical-extratropical interactions (Baatsen et al, 2015;Haarsma et al, 2013), and polar lows (Zappa et al, 2014). Other phenomena that are sensitive to increasing resolution are ocean mixing, sea-ice dynamics, the diurnal precipitation cycle (Sato et al, 2009;Birch et al, 2014;Vellinga et al, 2016), quasi biennial oscillation (QBO) (Hertwig et al, 2015), the Madden-Julian oscillation (MJO) representation (Peatman et al, 2015), atmospheric low-level coastal jets and their impact on sea surface temperature (SST) bias along eastern boundary upwelling regions Zuidema et al, 2016), and monsoons (Sperber et al, 1994;Lal et al, 1997;Martin, 1999).…”

“…Vellinga et al, 2016). A wide variety of processes will be assessed, from global and regional drivers of climate variability, down to mesoscale eddies in atmosphere and ocean -in the atmosphere these include tropical cyclones (Zhao et al, 2009;Bell et al, 2013;Rathmann et al, 2014;Roberts et al, 2015;Walsh et al, 2015) and eddy-mean flow interactions (Novak et al, 2015;Schiemann et al, 2016), while for the ocean they are an important mechanism for mesoscale airsea interactions (Chelton and Xie, 2010;Bryan et al, 2010;Frenger et al, 2013;Ma et al, 2015Ma et al, , 2016, trans-basin heat transport (e.g. Agulhas leakage) (Sein et al, 2016), convection, and oceanic fronts.…”