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Aerosol effects on convective clouds in global km-scale models – from idealised aerosol perturbations to explicit aerosol modelling

(2024)

Authors:

Philip Stier, Philipp Weiss, Ross Herbert, Maor Sela

Abstract:

Aerosol effects on convective clouds and climate mediated via radiative and microphysical perturbations remain highly uncertain. Microphysical perturbations are generally not included in current climate models due to the simplified representation of convective clouds in existing parameterisations. Progress has been made through regional cloud resolving modelling, however such simulations often neglect energy and water budget constraints and the coupling to larger scales. The emergence of global km-scale climate models provides a significant opportunity to advance our understanding of aerosol-convection interactions. Here we present results from a hierarchy of global km-scale atmospheric model simulations using ICON, investigating aerosol effects on convective clouds. Idealised model simulations, in which aerosols are prescribed as fixed plumes of radiative properties, with an optional associated semi-empirical scaling of droplet number perturbations, provide fascinating insights into the physical processes underlying aerosol effects on convection and into the interaction of local perturbations with the larger scale dynamics – but neglect key aerosol-convection interactions. These simulations highlight the importance of the radiatively mediated pathway for tropical convective clouds, with significant impacts on the diurnal cycle of cloud properties and precipitation over the Amazon and the Congo basin – and interactions with the large-scale dynamics for perturbations over the Pacific warm pool region. We contrast our results from idealised simulations with simulations including explicit aerosols, enabled by a novel reduced complexity aerosol scheme suitable for global km-scale models, HAM-Lite. Comparison of the idealised simulations with prescribed aerosol perturbations and the simulations with explicit aerosols, provides new insights into the complexity of aerosol-convection interactions. This study provides a testbed for a future global km-scale model intercomparison project focusing on aerosol effects as part of the GEWEX Aerosol Precipitation (GAP) initiative.
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Cloud condensation nuclei concentrations derived from the CAMS reanalysis

(2024)

Authors:

Karoline Block, Mahnoosh Haghighatnasab, Daniel G Partridge, Philip Stier, Johannes Quaas

Abstract:

Determining number concentrations of cloud condensation nuclei (CCN) is one of the first steps in the chain in analysis of cloud droplet formation, the direct microphysical link between aerosols and cloud droplets, and a process key for aerosol-cloud interactions (ACI).  Here, we present a new CCN dataset (https://doi.org/10.26050/WDCC/QUAERERE_CCNCAMS_v1) which combines aerosol modeling with observations to better explore magnitude, source, temporal and spatial distribution of CCN numbers. The dataset features 3-D CCN number concentrations of global coverage for various supersaturations and aerosol species covering the years from 2003 to 2021 with daily frequency. CCN are derived based on aerosol mass mixing ratios from the latest Copernicus Atmosphere Monitoring Service reanalysis (CAMSRA) in a diagnostic model that uses CAMSRA aerosol properties and a simplified kappa-Köhler framework which are suitable for global models. The emitted aerosols in CAMSRA are not only based on input from emission inventories using aerosol observations, they also have a strong tie to satellite-retrieved aerosol optical depth (AOD) as this is assimilated as a constraining factor in the reanalysis. Thus, this dataset is one of its kind as it offers lots of opportunities to be used for evaluation in models and in ACI studies. We will illustrate the distribution and variability of such derived CCN, evaluate them with observations and have a look at some specific features this dataset provides. Data description paper (preprint): https://essd.copernicus.org/preprints/essd-2023-172/
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Investigating the role of air mass history of Arctic black carbon in GCMs

(2024)

Authors:

Roxana S Cremer, Paul Kim, Sara M Blichner, Emanuele Tovazzi, Ben Johnson, Zak Kipling, Thomas Kühn, Duncan Watson-Parris, David Neubauer, Phillip Stier, Alistair Sellar, Eemeli Holopainen, Ilona Riipinen, Daniel G Partridge

Abstract:

Black Carbon (BC) aerosols are known to be important for the Earth’s climate, yet their exact role to the changing of the Earth’s climate and Arctic amplification remains unclear. An accurate description of the BC life cycle in general circulation models (GCMs) can help reduce the uncertainties due to BC aerosols and specify BC's role in the Arctic.In this study, several GCMs (ECHAM6.3-HAM2.3, ECHAM6.3-HAM2.3-P3, ECHAM6.3-HAM2.3-SALSA2 and UKESM1.0) are compared in terms of their representation of BC mass in the Arctic within the AeroCom project GCM Trajectory. A novel Lagrangian framework is employed to examine the history of air masses reaching the observational station Zeppelin, Svalbard. Therfore the removal processes were analysed along the trajectory and the GCMs compared with each other. The analysis emphasises the impact of remote emissions on local BC concentrations in the Arctic, indicating a longer BC lifetime compared to the global average. This underlines the importance of dry and wet scavenging parametrisations in the GCMs.   
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Multifractal analysis for evaluating the representation of clouds in global km-scale models

(2024)

Authors:

Lilli Freischem, Philipp Weiss, Hannah Christensen, Philip Stier

Abstract:

Clouds are one of the largest sources of uncertainty in climate predictions. Emerging next-generation km-scale climate models need to simulate clouds and precipitation accurately to reliably predict future climates. To isolate issues in their representation of clouds, and thereby facilitate their improvement, km-scale models need to be thoroughly evaluated via comparisons with observations. Traditionally, climate models are evaluated using spatio-temporally averaged observations. However, aggregated evaluation loses crucial information about underlying physical processes, such as convective updrafts, and the resulting cloud macrophysical structures. We postulate that a novel spatio-temporal evaluation strategy using satellite observations provides direct constraints on physical processes. Here, we introduce multifractal analysis as a method for evaluating km-scale simulations. We apply it to top-of-atmosphere outgoing longwave radiation (OLR) fields to investigate structural differences between observed and simulated clouds in the tropics. For this purpose, we compute structure functions from OLR fields to which we fit scaling exponents. We then parameterise the scaling exponents to compute scaling parameters. The parameters compactly characterise OLR variability and can be compared across simulations and observations. We use this method to evaluate the ICON-Sapphire and IFS-FESOM simulations run for cycle 3 of the nextGEMS project via comparison with data from the geostationary satellite GOES-16. We find that clouds in both models exhibit multifractal scaling from 50 to 1000km. However, the scaling parameters are significantly different between ICON and IFS, and neither match observations. In the ICON model, multifractal scaling exponents are lower than in observations whereas in IFS, they are larger. The observed differences indicate how the modelling approaches in ICON and IFS impact the organisation of clouds. More specifically, the deep convection scheme in ICON is switched off completely whereas it is still active in IFS, which could explain the difference in scaling behaviour we observed. Our results show that spatio-temporal analysis is a promising new way to constrain global km-scale models. It can provide key insights into model performance and shed light on issues in the representation of clouds.
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The sensitivity of cloud micro- and macrophysical properties to cloud microphysics parameterisations and simulation setup

(2024)

Authors:

Maor Sela, Philipp Weiss, Philip Stier

Abstract:

The climate impact and radiative effect of clouds and aerosols are significant. Both are among the most considerable sources of uncertainties in the climate system and in modelling the climate system. This arises not only from the fundamental uncertainty in cloud microphysics processes but also from their representation in models, and in particular in Cloud-Resolving Models (CRMs). CRMs are powerful tools for weather prediction, climate study, and investigating aerosol-cloud interactions at regional and global scales. However, they introduce a substantial degree of uncertainty due to model construction and parameterisation. To further investigate the sources of uncertainty in CRMs, we isolate two key aspects: the model's configuration (global and regional) and the employed cloud microphysics scheme (single- and double-moment schemes). Then, for each key aspect, we compare the simulated data to identify any discrepancies.We present results from regional simulation with ICON-Sapphire in limited area mode. The region we focused on in this study is the Amazon basin, using a horizontal resolution of about 1.2 km and a time period of 8 days. First, we compare results obtained using both single- and double-moment bulk microphysics schemes, maintaining consistency in other simulation parameters. Then, we compare results obtained from both regional and global simulations utilising the single-moment bulk microphysics scheme, again maintaining consistency in other simulation parameters. We find that the double-moment cloud microphysics scheme yields increased ice levels and reduced precipitation rates compared to the single-moment cloud microphysics scheme. We also find that the Amazonian diurnal cycle of precipitation rate, ice, and liquid water paths is more pronounced in the global runs compared to the regional runs. These results and other results that we will present may have implications on global radiation balance in global km-scale climate models.
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