SNIC SUPR
Deep convective cloud precipitation extremes and climate feedbacks
Dnr:

SNIC 2019/3-288

Type:

SNIC Medium Compute

Principal Investigator:

Thorsten Mauritsen

Affiliation:

Stockholms universitet

Start Date:

2019-06-01

End Date:

2019-12-01

Primary Classification:

10501: Climate Research

Secondary Classification:

10508: Meteorology and Atmospheric Sciences

Webpage:

Allocation

Abstract

Deep convective clouds are central to the atmospheric energy balance, the circulation and they provide most of the precipitation in the tropics. They typically reach from the surface up 10-15 km height, and can be 10s to 100s km wide, and cause strong and localised precipitation. Regular global climate models cannot resolve these, and so instead resort to parametrisation, which is an empirical description of the mixing, precipitation and heating caused by these clouds. However, with the growing computing power it is now possible to begin to resolve these clouds, even in global models. It is still very challenging today, but in the next 5-10 years studies based on such simulations will be common. In this study we will first conduct simulations regarding extreme precipitation in the tropics that will complement computations done previously in Germany at DKRZ. Precipitation extremes are expected to increase with the increasing amount of water vapour in the lower atmosphere of about 7 percent per degree warming following Clausius-Clapeyron. However, both certain observations - and our simulations - show a strong increase of nearly double that predicted by simple theory. This so-called super-CC scaling is thought to be due to dynamic enhancement of the largest precipitating storms in a warmer climate. The new simulations will use a more advanced cloud microphysics scheme which is better applicable to deep convective clouds. We target simulations in the 5-20 km resolution range. Whereas these new planned simulations are important for an ongoing study, we do have much greater plans for the future. Here we wish to study the climate change cloud feedbacks associated with deep convective clouds. These simulations are expected to go beyond what can be done within the medium project in terms of resolution and simulation times. We therefore see this proposal as a stepping-stone to gain the necessary experience with the machine towards a large proposal. We furthermore look forward to PDCs replacement for Beskow since the ICON model is now being adapted to take advantage of GPUs.