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Abstract. Polar stratospheric clouds (PSCs) play a key role in the polar chemistry of the stratosphere. Nitric acid trihydrate (NAT) particles have been shown to lead to denitrification of the lower stratosphere. While the existence of large NAT particles (NAT “rocks”) has been verified by many measurements, especially in the Northern Hemisphere (NH), most current chemistry–climate models use simplified parameterizations, often based on evaluations in the Southern Hemisphere where the polar vortex is stable enough that accounting for NAT rocks is not as important as in the NH. Here, we evaluate the probability density functions of various gaseous species in the polar vortex using one such model, the Whole Atmosphere Community Climate Model (WACCM), and compare these with measurements by the Michelson Interferometer for Passive Atmospheric Sounding onboard the Environmental Satellite (MIPAS/Envisat) and two ozonesonde stations for a range of years and in both hemispheres. Using the maximum difference between the distributions of MIPAS and WACCM as a measure of coherence, we find better agreement for HNO3 when reducing the NAT number density from the standard value of 10−2 used in this model to 5×10-4 cm−3 for almost all spring seasons during the MIPAS period in both hemispheres. The distributions of ClONO2 and O3 are not greatly affected by the NAT density. The average difference between WACCM and ozonesondes supports the need to reduce the NAT number density in the model. Therefore, this study suggests using a NAT number density of 5×10-4 cm−3 for future simulations with WACCM. 

The climate model hierarchy encompasses models of varying complexity along different axes, ranging from idealized models that elegantly describe isolated mechanisms to fully coupled Earth system models that aspire to provide useable climate projections. Based on the second Model Hierarchies Workshop, which took place in 2022, we present perspectives on how this field has evolved since the first Model Hierarchies Workshop in 2016. In this period, we have witnessed a dramatic increase in the use of (a) machine learning in climate modeling and (b) climate models to estimate risks and influence decision making under climate change. Here, we discuss the implications of these growing areas of research and how we expect them to become integrated into the model hierarchies framework.

 

Abstract Matsuno–Gill circulations have been widely studied in tropical meteorology, but their impact on stratospheric chemistry has seldom been explicitly evaluated. This study demonstrates that, in a model nudged to reanalysis, anticyclonic Rossby wave gyres that form near the tropopause as a result of equatorially symmetric heating in the troposphere provide a dynamical mechanism to influence tropical and subtropical atmospheric chemistry during near-equinox months. The anticyclonic flow entrains extratropical air from higher latitudes into the deep tropics of both hemispheres and induces cooling in the already cold upper-troposphere/lower-stratosphere (UTLS) region. Both of these aspects of the circulation allow heterogeneous chlorine activation on sulfuric acid aerosols to proceed rapidly, primarily via the HCl + ClONO 2 reaction. Precipitation rates and heating rates from reanalysis are shown to be consistent with these heating and circulation response patterns in the months of interest. This study analyzes specified dynamics simulations from the Whole Atmosphere Community Climate Model (SD-WACCM) with and without tropical heterogeneous chemistry to demonstrate that these circulations influence substantially the distributions of, for example, NO 2 and ClO in the UTLS tropics and subtropics of both hemispheres. This provides a previously unrecognized dynamical influence on the spatial structures of atmospheric composition changes in the UTLS during near-equinox months.