Abstract. We document model updates and present and discuss modeling and validation results from a further developed production-tagged aerosol module, OsloAero5.3, for use in Earth system models. The aerosol module has in this study been implemented and applied in CAM5.3-Oslo. This model is based on CAM5.3–CESM1.2 and its own predecessor model version CAM4-Oslo. OsloAero5.3 has improved treatment of emissions, aerosol chemistry, particle life cycle, and aerosol–cloud interactions compared to its predecessor OsloAero4.0 in CAM4-Oslo. The main new features consist of improved aerosol sources; the module now explicitly accounts for aerosol particle nucleation and secondary organic aerosol production, with new emissions schemes also for sea salt, dimethyl sulfide (DMS), and marine primary organics. Mineral dust emissions are updated as well, adopting the formulation of CESM1.2. The improved model representation of aerosol–cloud interactions now resolves heterogeneous ice nucleation based on black carbon (BC) and mineral dust calculated by the model and treats the activation of cloud condensation nuclei (CCN) as in CAM5.3. Compared to OsloAero4.0 in CAM4-Oslo, the black carbon (BC) mass concentrations are less excessive aloft, with a better fit to observations. Near-surface mass concentrations of BC and sea salt aerosols are also less biased, while sulfate and mineral dust are slightly more biased. Although appearing quite similar for CAM5.3-Oslo and CAM4-Oslo, the validation results for organic matter (OM) are inconclusive, since both of the respective versions of OsloAero are equipped with a limited number of OM tracers for the sake of computational efficiency. Any information about the assumed mass ratios of OM to organic carbon (OC) for different types of OM sources is lost in the transport module. Assuming that observed OC concentrations scaled by 1.4 are representative for the modeled OM concentrations, CAM5.3-Oslo with OsloAero5.3 is slightly inferior for the very sparsely available observation data. Comparing clear-sky column-integrated optical properties with data from ground-based remote sensing, we find a negative bias in optical depth globally; however, it is not as strong as in CAM4-Oslo, but has positive biases in some areas typically dominated by mineral dust emissions. Aerosol absorption has a larger negative bias than the optical depth globally. This is reflected in a lower positive bias in areas where mineral dust is the main contributor to absorption. Globally, the low bias in absorption is smaller than in CAM4-Oslo. The Ångström parameter exhibits small biases both globally and regionally, suggesting that the aerosol particle sizes are reasonably well represented. Cloud-top droplet number concentrations over oceans are generally underestimated compared to satellite retrievals, but seem to be overestimated downwind of major emissions of dust and biomass burning sources. Finally, we find small changes in direct radiative forcing at the top of the atmosphere, while the cloud radiative forcing due to anthropogenic aerosols is now more negative than in CAM4-Oslo, being on the strong side compared to the multi-model estimate in IPCC AR5. Although not all validation results in this study show improvement for the present CAM5.3-Oslo version, the extended and updated aerosol module OsloAero5.3 is more advanced and applicable than its predecessor OsloAero4.0, as it includes new parameterizations that more readily facilitate sensitivity and process studies and use in climate and Earth system model studies in general.

Abstract. Fungal spores as a prominent type of primary biological aerosol particles (PBAP) have been incorporated into the COSMO-ART (Consortium for Small-scale ModellingAerosols and Reactive Trace gases) regional atmospheric model. Two literature-based emission rates for fungal spores derived from fungal spore colony counts and chemical tracer measurements were used as a parameterization baseline for this study. A third, new emission parameterization for fluorescent biological aerosol particles (FBAP) was adapted to field measurements from four locations across Europe. FBAP concentrations can be regarded as a lower estimate of total PBAP concentrations. Size distributions of FBAP often show a distinct mode at approx. 3 µm, corresponding to a diameter range characteristic for many fungal spores. Previous studies for several locations have suggested that FBAP are in many cases dominated by fungal spores. Thus, we suggest that simulated FBAP and fungal spore concentrations obtained from the three different emission parameterizations can be compared to FBAP measurements. The comparison reveals that simulated fungal spore concentrations based on literature emission parameterizations are lower than measured FBAP concentrations. In agreement with the measurements, the model results show a diurnal cycle in simulated fungal spore concentrations, which may develop partially as a consequence of a varying boundary layer height between day and night. Temperature and specific humidity, together with leaf area index (LAI), were chosen to drive the new emission parameterization which is fitted to the FBAP observations. The new parameterization results in similar root mean square errors (RMSEs) and correlation coefficients compared to the FBAP observations as the previously existing fungal spore emission parameterizations, with some improvements in the bias. Using the new emission parameterization on a model domain covering western Europe, FBAP in the lowest model layer comprise a fraction of 15 % of the total aerosol mass over land and reach average number concentrations of 26 L −1 . The results confirm that fungal spores and biological particles may account for a major fraction of supermicron aerosol particle number and mass concentration over vegetated continental regions and should thus be explicitly considered in air quality and climate studies.

Abstract. Primary ice formation, which is an important process for mixed-phase clouds with an impact on their lifetime, radiative balance, and hence the climate, strongly depends on the availability of ice-nucleating particles (INPs). Supercooled droplets within these clouds remain liquid until an INP immersed in or colliding with the droplet reaches its activation temperature. Only a few aerosol particles are acting as INPs and the freezing efficiency varies among them. Thus, the fraction of supercooled water in the cloud depends on the specific properties and concentrations of the INPs. Primary biological aerosol particles (PBAPs) have been identified as very efficient INPs at high subzero temperatures, but their very low atmospheric concentrations make it difficult to quantify their impact on clouds. Here we use the regional atmospheric model COSMO–ART to simulate the heterogeneous ice nucleation by PBAPs during a 1-week case study on a domain covering Europe. We focus on three highly ice-nucleation-active PBAP species, Pseudomonas syringae bacteria cells and spores from the fungi Cladosporium sp. and Mortierella alpina. PBAP emissions are parameterized in order to represent the entirety of bacteria and fungal spores in the atmosphere. Thus, only parts of the simulated PBAPs are assumed to act as INPs. The ice nucleation parameterizations are specific for the three selected species and are based on a deterministic approach. The PBAP concentrations simulated in this study are within the range of previously reported results from other modeling studies and atmospheric measurements. Two regimes of PBAP INP concentrations are identified: a temperature-limited and a PBAP-limited regime, which occur at temperatures above and below a maximal concentration at around −10 ∘C, respectively. In an ensemble of control and disturbed simulations, the change in the average ice crystal concentration by biological INPs is not statistically significant, suggesting that PBAPs have no significant influence on the average state of the cloud ice phase. However, if the cloud top temperature is below −15 ∘C, PBAP can influence the cloud ice phase and produce ice crystals in the absence of other INPs. Nevertheless, the number of produced ice crystals is very low and it has no influence on the modeled number of cloud droplets and hence the cloud structure.

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