Small shallow cumulus clouds (< 1 km) over the tropical oceans appear to possess the ability to self-organise into mesoscale (10-100 km) patterns. To better understand the processes leading to such self-organized convection, we present Cloud Botany, an ensemble of 103 large-eddy simulations on domains of 150 km, produced by the Dutch Large Eddy Simulation (DALES) model on supercomputer Fugaku. Each simulation is run in an idealized, fixed, larger-scale environment, controlled by six free parameters. We vary these over characteristic ranges for the winter trades, including parameter combinations observed during the EUREC4A (Elucidating the role of clouds–circulation coupling in climate) field campaign. In contrast to simulation setups striving for maximum realism, Cloud Botany provides a platform for studying idealized, and therefore more clearly interpretable causal relationships between conditions in the larger-scale environment and patterns in mesoscale, self-organized shallow convection. We find that any simulation that supports cumulus clouds eventually develops mesoscale patterns in their cloud fields. We also find a rich variety in these patterns as our control parameters change, including cold pools lined by cloudy arcs, bands of cross-wind clouds and aggregated patches, sometimes topped by thin anvils. Many of these features are similar to cloud patterns found in nature. The published data set consists of raw simulation output on full 3D grids and 2D cross-sections, as well as post-processed quantities aggregated over the vertical (2D), horizontal (1D) and all spatial dimensions (time-series). The data set is directly accessible from Python through the use of the EUREC4A intake catalog.

Understanding the mechanism underlying the formation of bimodal raindrop size distribution (RDSD) requires quantification of the cloud microphysical and dynamic behavior of precipitation particles within the precipitation system. Although the microphysical equilibrium state associated with collision-coalescence and breakup is considered the main mechanism for the formation of bimodal RDSD, the importance of dynamical advection effects associated with the influence of background wind fields has also been pointed out in recent years. Here, we investigated the formation of bimodal RDSD by quantifying the microphysical and dynamical processes that cause RDSD variability in a two-dimensional idealized simulation with an explicit representation of RDSD using a spectral-bin cloud microphysics scheme. Within the simulated precipitation system, bimodal RDSDs formed by horizontal and vertical advection and collision-coalescence breakups were present in similar proportions. The coalescence breakup-type bimodal RDSD appeared when the updrafts in the background field were strong. In contrast, the vertical advection-type bimodal RDSD was formed when the particles at the secondary peak selectively fell out by size sorting. Furthermore, the horizontal advection type of the bimodal RDSD was formed under the influence of particle size sorting associated with horizontal wind. The bimodal RDSD formed by these processes can be classified according to the particle size of the secondary peak. This study proposes a novel comprehensive picture of the bimodal RDSD formation mechanism caused by different microphysical and dynamical processes.

The NASA/AERONET field campaign DRAGON/J-ALPS (Distributed Regional Aerosol Gridded Observation Networks/Joint work to the AerosoL Properties and Process Simulations) was conducted from March 2020 to May 2021 in Nagano, Japan. Twelve sun photometers were installed around Nagano prefecture. The effects of topography on aerosols were studied using observations and simulations. In this study, a regional chemical transport model (SCALE-Chem) was employed. Three numerical experiments were conducted: E1 (control experiment), E2 (E1 without topography), and E3 (E1 with removal of all anthropogenic emissions over Nagano prefecture). In E2, the terrain effect was not considered; the difference between E1 and E2 indicated the influence of mountains. The differences between E1 and E3 evaluate the local emission effect. In some cases, the mountainous terrain seemed to have suppressed aerosol inflow (i.e., reduced aerosol concentration), while in other cases, the mountains contributed to aerosol retention on days when aerosols tended to accumulate in mountain basins due to local emissions. Thus, while mountains prevent the inflow of aerosols from outside, they also contribute to increased aerosol concentration in the basin. Naturally, more significant effects are produced by meteorological conditions and the presence or absence of transboundary pollution from the outside. From observations and model simulations, we found that the aerosol concentration was not high around the J-ALPS site because of the mountain effect that prevents advection from the outside, even when transboundary pollution was observed in Japan in March 2020.

Aerosols interact with radiation and clouds. Substantial progress made over the past 40 years in observing, understanding, and modeling these processes helped quantify the imbalance in the Earth’s radiation budget caused by anthropogenic aerosols, called aerosol radiative forcing, but uncertainties remain large. This poster presents the outcome of an international workshop and subsequent review paper, which quantify the likely range of aerosol radiative forcing over the industrial era based on multiple lines of evidence, including modelling approaches, theoretical considerations, and observations. Improved understanding of aerosol absorption and the causes of trends in surface radiative fluxes narrow the range of the forcing from aerosol-radiation interactions compared to the latest assessment by the Intergovernmental Panel on Climate Change (IPCC). A robust theoretical foundation and convincing evidence constrain the forcing caused by aerosol-driven increases in liquid cloud droplet number concentration. However, the influence of anthropogenic aerosols on cloud liquid water content and cloud fraction and on mixed-phase and ice clouds remains poorly constrained. Observed changes in surface temperature and radiative fluxes provide additional constraints. These multiple lines of evidence lead to total aerosol radiative forcing ranges that are of similar width to the last IPCC assessment but more clearly based on physical arguments.