GREenhouse gases, Aerosols and lower atmospheric Turbulence

How do gases and particles affect turbulence in the lower atmosphere? It is a well-established fact that an increase in atmospheric concentrations of CO2 and other greenhouse gases leads to higher surface temperatures on Earth. However, increasing concentrations of greenhouse gases, and particles (e.g., soot), has many other impacts on the Earth's climate. There is a particularly large knowledge gap in the literature regarding how greenhouse gases and particles affect atmospheric turbulence near the Earth's surface. GREAT will substantially increase our scientific understanding on this issue. Turbulence is a topic of high societal relevance, entangled as it is with human health, physical damage to infrastructure, and the carbon cycle. Soot particles are hazardous air pollutants and key contributors to climate change. Observations have now shown that soot particles can reduce turbulence in the lower atmosphere. These new findings could have implications for cloud formation and human health through air pollution. A driving question for the GREAT project is whether global climate models, our best tools for understanding and projecting air quality and climate change, are able to represent these processes adequately? Do elevated concentrations of sulphate particles and CO2 concentrations show similar connections with turbulence? GREAT seeks to answer these questions by using high-quality observations from several sites and sources in combination with atmospheric modelling tools ranging from global to microscale. Results from a range of global climate models show that soot particles strongly influence the stability of the lower atmosphere (Myhre et al., 2018, Nat. Comm.), and this could be an important indicator of changes in turbulence. In contrast to other climate drivers (e.g., CO2), soot particles strongly increase the stability of the lower atmosphere and this leads to reduction of the sensible heat flux. Sensible heat is the transfer of heat from the surface to the atmosphere (without phase changes) and is one of the most uncertain factors in the global energy budget. Model results further show that soot particles lead to a general reduction in surface winds, a finding that is in line with the observed reduction in lower atmospheric turbulence due to soot. The effect of increased CO2 concentrations in the atmosphere has been studied using the regional model Weather Research and Forecasting (WRF) with different horizontal resolutions (50 km and 10 km). The results show that for important indicators of turbulence (e.g., vertical velocity and boundary layer height), changes due to CO2 increase could be highly dependent on model resolution (Hodnebrog et al., 2021, Clim. Dyn.). In regions dominated by convection, which largely governs the boundary layer height and influences turbulence, results even show different sign of change between 50 and 10 km resolution. This is due to the improved representation of convection in the model simulation with high resolution. These findings indicate that global climate models, and even regional models with coarse resolution (~50 km), do not represent the effect of climate change on turbulence adequately. Numerical model experiments with the global Community Earth System Model (CESM) show clear differences in how individual climate drivers influence stability and turbulence in the lower part of the atmosphere (Stjern et al., 2023, Nat. Comm.). Results from the latest generation global climate models (CMIP6) further show that future scenarios with increasing CO2 and reduced aerosol emissions lead to a reduction in intense pollution events due to strong increases in turbulence and boundary layer height. Regions with high level of air pollution are being investigated in more detail using the models WRF and WRF-Chem. For a polluted region in Asia, effects of soot and CO2 on turbulence and boundary layer meteorology are simulated at horizontal scales ranging from that typical of global climate models (50-100 km) and down to 100 m grid spacing using WRF-LES. These simulations will help answer the question of how well coarse-resolution global climate models are able to represent fine-resolution meteorological processes. Through a large regional multi-model initiative, the added value of high resolution (~3 km) simulations, compared to coarser regional and global model simulations, is quantified. E.g., a correct representation of surface temperature is important for turbulence through sensible heat fluxes. Results indicate that higher resolution leads to only modest improvements in simulating surface temperature (Soares et al., 2022), with warmer heatwave temperatures when using high resolution (Sangelantoni et al., 2023). There is added value of using high resolution when simulating near-surface winds, especially in complex coastal terrain (Belusic et al., 2023), and model resolution has a strong impact on simulating precipitation frequency over land (Ha et al., 2022).

The GREAT project investigates turbulence in the lower parts of the atmosphere. Turbulence is a topic of high societal relevance, with connections to human health, physical damage to infrastructure, and the carbon cycle. Yet, little is known of how the various anthropogenic climate drivers, such as greenhouse gases and aerosols, affect atmospheric turbulence near the Earth's surface. GREAT aims to substantially increase our understanding on this issue. Soot particles are hazardous air pollutants and important contributors to climate change. Observations have now shown that soot particles can reduce turbulence in the lower atmosphere. These new findings could have implications for cloud formation and human health through air pollution. Are global models, our best tools for understanding and projecting air quality and climate change, able to represent these processes adequately? Do elevated concentrations of sulphate particles and CO2 concentrations show similar connections with turbulence? GREAT seeks to answer these questions by using high-quality observations from several sites and sources in combination with atmospheric modelling tools ranging from global to microscale. GREAT represents the next step towards a more fundamental understanding of the broad climate impact of anthropogenic emissions. The project leader will build on his own experience, and the expertise of the project group, to become an international expert in a key field of atmospheric research.