Clouds in Convection‐Resolving Climate Simulations Over Europe

Abstract

Although crucial for the Earth's climate, clouds are poorly represented in current climate models, which operate at too coarse grid resolutions and rely on convection parameterizations. Thanks to advances in high‐performance computing, it is becoming feasible to perform high‐resolution climate simulations with explicitly resolved deep convection. The added value of such convection‐resolving simulations for the representation of precipitation has already been demonstrated in a number of studies, but assessments about clouds are still rare. In the present study, we analyze the representation of clouds in decade‐long convection‐resolving climate simulations (2.2‐km horizontal grid spacing) over a computational domain with 1,536 × 1,536 × 60 grid points covering Europe and compare it against coarser‐resolution convection‐parameterizing simulations (12‐km horizontal spacing). The simulations have been performed with a version of the COSMO model that runs entirely on graphics processing units. The European Centre for Medium‐Range Weather Forecasts Re‐Analysis‐Interim reanalysis‐driven present climate simulations (1999–2008) show that biases in mean summertime cloudiness and top‐of‐the‐atmosphere radiation budget are reduced when convection is resolved instead of parameterized. Especially, the typically underestimated midtropospheric cloud layer is enhanced, thanks to stronger vertical exchange. Future climate simulations (2079–2088) conducted using pseudo global warming experiments for a Representative Concentration Pathway 8.5 scenario show a predominating reduction in low‐level and midlevel cloud cover fraction and an increase in cloud top height, implying positive cloud‐amount and cloud‐height feedbacks. These positive feedbacks are only partly compensated by the negative cloud‐thickness feedback. Although the simulations exhibit substantial differences in terms of clouds in the present climate, the simulated cloud feedbacks are similar between the 2.2‐ and 12‐km models.

Kilometer-Scale Climate Models: Prospects and Challenges

“…The 12 km model produces widespread low-intensity precipitation (a long-standing problem of convective parameterizations), while a more realistic representation of intense summer precipitation is obtained in the 2 km model. Furthermore, kilometer-scale resolution is needed for resolving local-scale wind systems, like sea breeze and orographic circulations (e.g., Belušić et al 2018), and for a better representation of clouds and their vertical profiles (e.g., Hentgen et al 2019).…”

“…In addition to a better representation of the present-day climate, convection-resolving climate models provide modified climate change signals. Although changes in mean seasonal precipitation are generally robust between convection-resolving and convectionparameterizing models, significant differences occur for projections of heavy hourly precipitation events (Ban et al 2015;Kendon et al 2017) and for changes in the vertical structure of clouds (Hentgen et al 2019).…”

Subhourly rainfall in a convection-permitting model

“…CPMs also reduce the 'drizzle problem' found in coarser models [7], whereby light rainfall is too persistent, and tend to more realistically represent the frequency of short intense events [3,8]. In addition to a better representation of vertical mixing [14], the added value of CPMs may extend to future changes in precipitation extremes: CPMs have shown enhanced intensification of extremes in response to warming [15][16][17] and diurnal differences in future scaling [18] for certain regions.…”

Causes of future Mediterranean precipitation decline depend on the season

“…The smoothed annual cycle is imposed onto the boundary fields of the historical simulation, retaining the full historical variability, meaning that the historical sequence of weather systems at the lateral boundaries is unchanged. The CO 2 concentrations are increased in all experiments.The employed simulation strategy, quantifying different drivers by modifying the boundary conditions, is often referred to as the pseudo-global warming (PGW) approach(Yoshikane et al 2012, Lackmann 2013, Prein et al 2017, Brogli et al 2019, Hentgen et al 2019 . In this study, TDLR, SSTE, and MEA are assessed for the first time in a PGW-framework.…”