Abstract. Clouds and cloud feedbacks represent one of the largest uncertainties in climate projections. As the ice phase influences many key cloud properties and their lifetime, its formation needs to be better understood in order to improve climate and weather prediction models. Ice crystals sedimenting out of a cloud do not sublimate immediately but can survive certain distances and eventually fall into a cloud below. This natural cloud seeding can trigger glaciation and has been shown to enhance precipitation formation. However, to date, an estimate of its occurrence frequency is lacking. In this study, we estimate the occurrence frequency of natural cloud seeding over Switzerland from satellite data and sublimation calculations. We use the DARDAR (radar lidar) satellite product between April 2006 and October 2017 to estimate the occurrence frequency of multi-layer cloud situations, where a cirrus cloud at T < −35 ∘C can provide seeds to a lower-lying feeder cloud. These situations are found to occur in 31 % of the observations. Of these, 42 % have a cirrus cloud above another cloud, separated, while in 58 % the cirrus is part of a thicker cloud, with a potential for in-cloud seeding. Vertical distances between the cirrus and the lower-lying cloud are distributed uniformly between 100 m and 10 km. They are found to not vary with topography. Seasonally, winter nights have the most multi-layer cloud occurrences, in 38 % of the measurements. Additionally, in situ and liquid origin cirrus cloud size modes can be identified according to the ice crystal mean effective radius in the DARDAR data. Using sublimation calculations, we show that in a significant number of cases the seeding ice crystals do not sublimate before reaching the lower-lying feeder cloud. Depending on whether bullet rosette, plate-like or spherical crystals were assumed, 10 %, 11 % or 20 % of the crystals, respectively, could provide seeds after sedimenting 2 km. The high occurrence frequency of seeding situations and the survival of the ice crystals indicate that the seeder–feeder process and natural cloud seeding are widespread phenomena over Switzerland. This hints at a large potential for natural cloud seeding to influence cloud properties and thereby the Earth's radiative budget and water cycle, which should be studied globally. Further investigations of the magnitude of the seeding ice crystals' effect on lower-lying clouds are necessary to estimate the contribution of natural cloud seeding to precipitation.

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Abstract. The discrepancy between the observed concentration of ice nucleating particles (INPs) and the ice crystal number concentration (ICNC) remains unresolved and limits our understanding of ice formation and, hence, precipitation amount, location and intensity. Enhanced ice formation through secondary ice production (SIP) could account for this discrepancy. Here, in a region over the eastern Swiss Alps, we perform sensitivity studies of additional simulated SIP processes on precipitation formation and surface precipitation intensity. The SIP processes considered include rime splintering, droplet shattering during freezing and breakup through ice–graupel collisions. We simulated the passage of a cold front at Gotschnagrat, a peak at 2281 m a.s.l. (above sea level), on 7 March 2019 with the Consortium for Small-scale Modeling (COSMO), at a 1 km horizontal grid spacing, as part of the RACLETS (Role of Aerosols and CLouds Enhanced by Topography and Snow) field campaign in the Davos region in Switzerland. The largest simulated difference in the ICNC at the surface originated from the breakup simulations. Indeed, breakup caused a 1 to 3 orders of magnitude increase in the ICNC compared to SIP from rime splintering or without SIP processes in the control simulation. The ICNCs from the collisional breakup simulations at Gotschnagrat were in best agreement with the ICNCs measured on a gondola near the surface. However, these simulations were not able to reproduce the ice crystal habits near the surface. Enhanced ICNCs from collisional breakup reduced localized regions of higher precipitation and, thereby, improved the model performance in terms of surface precipitation over the domain.

Rainfall simulations over southern and tropical Africa in the form of low-resolution Atmospheric Model Intercomparison Project (AMIP) simulations and higher resolution National Centre for Environmental Prediction (NCEP) reanalysis downscalings are presented and evaluated in this paper. The model used is the conformal-cubic atmospheric model (CCAM), a variable-resolution global atmospheric model. The simulations are evaluated with regards to rainfall totals, spatial distribution, seasonality and inter-annual variability. Since both Global Circulation Models (GCMs) and Regional Climate Models (RCMs) are known to have relatively large biases and shortcomings in simulating rainfall over the steep eastern escarpment of southern Africa and in particular Lesotho, the paper has a focus on evaluating model performance over these regions. It is shown that in the reanalysis simulations the model realistically represents the seasonal cycle in rainfall. However, the AMIP simulations are prone to the model overestimating rainfall totals in spring. The spatial distribution of rainfall is simulated realistically; however rainfall totals are significantly overestimated over the escarpment areas of both southern Africa and East Africa. When nudged within the observed circulation patterns of the reanalysis data, the model is capable of realistically simulating inter-annual rainfall variability over the eastern parts of southern Africa.

Abstract. The sensitivity of climate models to the characterization of African aerosol particles is poorly understood. Africa is a major source of dust and biomass burning aerosols and this represents an important research gap in understanding the impact of aerosols on radiative forcing of the climate system. Here we evaluate the current representation of aerosol particles in the Conformal Cubic Atmospheric Model (CCAM) with ground-based remote retrievals across Africa, and additionally provide an analysis of observed aerosol optical depth at 550 nm (AOD 550 nm ) and Ångström exponent data from 34 Aerosol Robotic Network (AERONET) sites. Analysis of the 34 long-term AERONET sites confirms the importance of dust and biomass burning emissions to the seasonal cycle and magnitude of AOD 550 nm across the continent and the transport of these emissions to regions outside of the continent. In general, CCAM captures the seasonality of the AERONET data across the continent. The magnitude of modeled and observed multiyear monthly average AOD 550 nm overlap within ±1 standard deviation of each other for at least 7 months at all sites except the Réunion St Denis Island site (Réunion St. Denis). The timing of modeled peak AOD 550 nm in southern Africa occurs 1 month prior to the observed peak, which does not align with the timing of maximum fire counts in the region. For the western and northern African sites, it is evident that CCAM currently overestimates dust in some regions while others (e.g., the Arabian Peninsula) are better characterized. This may be due to overestimated dust lifetime, or that the characterization of the soil for these areas needs to be updated with local information. The CCAM simulated AOD 550 nm for the global domain is within the spread of previously published results from CMIP5 and AeroCom experiments for black carbon, organic carbon, and sulfate aerosols. The model's performance provides confidence for using the model to estimate largescale regional impacts of African aerosols on radiative forcing, but local feedbacks between dust aerosols and climate over northern Africa and the Mediterranean may be overestimated.