Parameterized orographic gravity wave drag in CMIP6 models, distribution, variability, trends and intermodel spread

Internal gravity waves (GWs) are a naturally occurring and intermittent phenomenon in the atmosphere. GWs can propagate horizontally and vertically and are important for atmospheric dynamics, influencing the atmospheric thermal and dynamical structure. Research on GWs is connected with some of the most challenging issues of Earth climate and atmospheric science. Consideration of GW-related processes is necessary for a proper description and modelling of the middle and upper atmosphere. However, as GWs exist on scales from a few to thousands of kilometers, they cannot be fully resolved by general circulation models (GCMs) and hence have to be parameterized. Although recently satellite and reanalysis datasets with improved resolution and novel analysis methods together with high-resolution atmospheric models have been tightening the constraints for GW parameterizations in GCMs, the parameterized GW effects still bear a significant margin of uncertainty.

To quantify this uncertainty, we analyze the three-dimensional distribution and interannual variability of orographic gravity wave drag (OGWD) in chemistry-climate model simulations. For this, we use a set of AMIP simulations produced within the CMIP6 activity. In particular, we focus on the intermodel spread in the vertical and horizontal OGWD distribution. The different models generaly agree on the areas of the OGWD hotspots. However, in all these regions we find considerable intermodel differences in OGWD magnitude as well as in the altitude of the strongest GW dissipation. In this presentation, we show our findings and discuss possible explanations for the intermodel differences, like different parametrization schemes and choices of tunable parameters.