Application of the Pseudo‐Global Warming Approach in a Kilometer‐Resolution Climate Simulation of the Tropics

Abstract

Clouds over tropical oceans are among the most uncertain factors controlling Earth's temperature response to anthropogenic greenhouse gas emissions (Forster et al., 2021). They form along the branches of the Hadley circulation (HC, e.g., Held & Hou, 1980), for instance, in the form of deep convection at the intertropical convergence zone (ITCZ) (Waliser & Gautier, 1993) and shallow convection in the marine boundary layer (MBL) in the Trades (e.g., Stevens, 2007;Vial et al., 2017;Wood, 2012). Tropical clouds have the potential for a strong radiative feedback in a warming climate (Bony & Dufresne, 2005;Zelinka et al., 2016). Yet, their evolution with climate change is uncertain (e.g., Bretherton, 2015), making them a prime focus of current climate change research.Model intercomparison projects of global climate models (GCMs) such as the fifth or sixth phase of the Coupled Model Intercomparison Project (CMIP5, CMIP6, Eyring et al., 2016;Taylor et al., 2012) allow for an assessment of the magnitude and inter-model variability of cloud changes in a large ensemble of state-of-the-art GCMs. With respect to tropical deep convection at the ITCZ, many GCMs project that the upper part of the clouds (i.e., the anvils) will rise in a warming atmosphere and remain at approximately the same temperature, according to the fixed anvil temperature (FAT) hypothesis (Hartmann & Larson, 2002). As the anvils rise, they find themselves in

Climate Change Response of Tropical Atlantic Clouds in a Kilometer-Resolution Model

“…This study uses the same simulation output as the study by Heim et al (2023). Two 4-year-long simulations are conducted using the limited-area model COSMO (see Section 2.3).…”

“…Thanks to their comparably high resolution and explicit representation of deep convective circulations, KRMs have been found to improve the representation of tropical deep and shallow convection (e.g. Klocke et al, 2017;Stevens et al, 2020;Heim et al, 2023;?, ? ) and humidity profiles (Lang et al, 2021) (Heim et al, 2021).…”

“…In this regard, one may argue that KRMs resemble LES more than they resemble GCMs, even though their grid spacing lies roughly in the middle of GCMs and LES. KRMs were also found to give an improved representation of the diurnal (Stevens et al, 2020) and annual (Heim et al, 2023) cycle of shallow cumulus compared to coarser models, and a realistic cloud-water profile (Caldwell et al, 2021). A particularly promising aspect about KRMs is that they were found to enable organization of the low-cloud field into mesoscale structures (Klocke et al, 2017;Heim et al, 2021Heim et al, , 2023Caldwell et al, 2021).…”

“…KRMs were also found to give an improved representation of the diurnal (Stevens et al, 2020) and annual (Heim et al, 2023) cycle of shallow cumulus compared to coarser models, and a realistic cloud-water profile (Caldwell et al, 2021). A particularly promising aspect about KRMs is that they were found to enable organization of the low-cloud field into mesoscale structures (Klocke et al, 2017;Heim et al, 2021Heim et al, , 2023Caldwell et al, 2021). Mesoscale structures are considered an important property of the shallow cumulus cloud field since they may affect the cloud feedback in the Trades (Stevens et al, 2019;Bony et al, 2020;Schulz et al, 2021).…”

“…In a previous study (Heim et al, 2023), a limited-area KRM climate simulation based on the PGW approach was run over the tropical Atlantic. They evaluated the simulation under current climate conditions and compared the PGW climate change signal to the GCMs of the sixth phase of the Coupled Model Intercomparison Project (CMIP6, Eyring et al, 2016).…”