| 1. |
- Bergman, Tommi, et al.
(author)
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Description and evaluation of a secondary organic aerosol and new particle formation scheme within TM5-MP v1.2
- 2022
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In: Geoscientific Model Development. - : Copernicus GmbH. - 1991-959X .- 1991-9603. ; 15:2, s. 683-713
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Journal article (peer-reviewed)abstract
- We have implemented and evaluated a secondary organic aerosol scheme within the chemistry transport model TM5-MP in this work. In earlier versions of TM5-MP the secondary organic aerosol (SOA) was emitted as Aitken-sized particle mass emulating the condensation. In the current scheme we simulate the formation of secondary organic aerosol from oxidation of isoprene and monoterpenes by ozone and hydroxyl radicals, which produce semi-volatile organic compounds (SVOCs) and extremely low-volatility compounds (EVOCs). Subsequently, SVOCs and ELVOCs can condense on particles. Furthermore, we have introduced a new particle formation mechanism depending on the concentration of ELVOCs. For evaluation purposes, we have simulated the year 2010 with the old and new scheme; we see an increase in simulated production of SOA from 39.9ĝ€¯Tgĝ€¯yr-1 with the old scheme to 52.5ĝ€¯Tgĝ€¯yr-1 with the new scheme. For more detailed analysis, the particle mass and number concentrations and their influence on the simulated aerosol optical depth are compared to observations. Phenomenologically, the new particle formation scheme implemented here is able to reproduce the occurrence of observed particle formation events. However, the modelled concentrations of formed particles are clearly lower than in observations, as is the subsequent growth to larger sizes. Compared to the old scheme, the new scheme increases the number concentrations across the observation stations while still underestimating the observations. The organic aerosol mass concentrations in the US show a much better seasonal cycle and no clear overestimation of mass concentrations anymore. In Europe the mass concentrations are lowered, leading to a larger underestimation of observations. Aerosol optical depth (AOD) is generally slightly increased except in the northern high latitudes. This brings the simulated annual global mean AOD closer to the observational estimate. However, as the increase is rather uniform, biases tend to be reduced only in regions where the model underestimates the AOD. Furthermore, the correlations with satellite retrievals and ground-based sun-photometer observations of AOD are improved. Although the process-based approach to SOA formation causes a reduction in model performance in some areas, overall the new scheme improves the simulated aerosol fields.
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| 2. |
- Döscher, Ralf, et al.
(author)
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The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6
- 2022
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In: Geoscientific Model Development. - : Copernicus GmbH. - 1991-959X .- 1991-9603. ; 15:7, s. 2973-3020
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Journal article (peer-reviewed)abstract
- The Earth system model EC-Earth3 for contributions to CMIP6 is documented here, with its flexible coupling framework, major model configurations, a methodology for ensuring the simulations are comparable across different high-performance computing (HPC) systems, and with the physical performance of base configurations over the historical period. The variety of possible configurations and sub-models reflects the broad interests in the EC-Earth community. EC-Earth3 key performance metrics demonstrate physical behavior and biases well within the frame known from recent CMIP models. With improved physical and dynamic features, new Earth system model (ESM) components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.
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| 3. |
- Fanourgakis, George S., et al.
(author)
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Evaluation of global simulations of aerosol particle and cloud condensation nuclei number, with implications for cloud droplet formation
- 2019
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In: Atmospheric Chemistry and Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 19:13, s. 8591-8617
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Journal article (peer-reviewed)abstract
- A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011-2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of -24% and -35% for particles with dry diameters >50 and >120nm, as well as -36% and -34% for CCN at supersaturations of 0.2% and 1.0%, respectively. However, they seem to behave differently for particles activating at very low supersaturations (<0.1%) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2% (CCN0.2) compared to that for N3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40% during winter and 20% in summer. In contrast to the large spread in simulated aerosol particle and CCN number concentrations, the CDNC derived from simulated CCN spectra is less diverse and in better agreement with CDNC estimates consistently derived from the observations (average NMB -13% and -22% for updraft velocities 0.3 and 0.6ms-1, respectively). In addition, simulated CDNC is in slightly better agreement with observationally derived values at lower than at higher updraft velocities (index of agreement 0.64 vs. 0.65). The reduced spread of CDNC compared to that of CCN is attributed to the sublinear response of CDNC to aerosol particle number variations and the negative correlation between the sensitivities of CDNC to aerosol particle number concentration (Nd=Na) and to updraft velocity (Nd=w). Overall, we find that while CCN is controlled by both aerosol particle number and composition, CDNC is sensitive to CCN at low and moderate CCN concentrations and to the updraft velocity when CCN levels are high. Discrepancies are found in sensitivities Nd=Na and Nd=w; models may be predisposed to be too "aerosol sensitive" or "aerosol insensitive" in aerosol-cloud-climate interaction studies, even if they may capture average droplet numbers well. This is a subtle but profound finding that only the sensitivities can clearly reveal and may explain intermodel biases on the aerosol indirect effect.
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| 4. |
- Quaas, Johannes, et al.
(author)
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Constraining the Twomey effect from satellite observations : issues and perspectives
- 2020
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In: Atmospheric Chemistry And Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 20:23, s. 15079-15099
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Journal article (peer-reviewed)abstract
- The Twomey effect describes the radiative forcing associated with a change in cloud albedo due to an increase in anthropogenic aerosol emissions. It is driven by the perturbation in cloud droplet number concentration (Delta N-d, (ant)) in liquid-water clouds and is currently understood to exert a cooling effect on climate. The Twomey effect is the key driver in the effective radiative forcing due to aerosol-cloud interactions, but rapid adjustments also contribute. These adjustments are essentially the responses of cloud fraction and liquid water path to Delta N-d, (ant) ant and thus scale approximately with it. While the fundamental physics of the influence of added aerosol particles on the droplet concentration (N-d) is well described by established theory at the particle scale (micrometres), how this relationship is expressed at the large-scale (hundreds of kilometres) perturbation, Delta N-d, (ant), remains uncertain. The discrepancy between process under-standing at particle scale and insufficient quantification at the climate-relevant large scale is caused by co-variability of aerosol particles and updraught velocity and by droplet sink processes. These operate at scales on the order of tens of metres at which only localised observations are available and at which no approach yet exists to quantify the anthropogenic perturbation. Different atmospheric models suggest diverse magnitudes of the Twomey effect even when applying the same anthropogenic aerosol emission perturbation. Thus, observational data are needed to quantify and constrain the Twomey effect. At the global scale, this means satellite data. There are four key uncertainties in determining Delta N-d, (ant) namely the quantification of (i) the cloud-active aerosol - the cloud condensation nuclei (CCN) concentrations at or above cloud base, (ii) N-d, (iii) the statistical approach for inferring the sensitivity of N-d to aerosol particles from the satellite data and (iv) uncertainty in the anthropogenic perturbation to CCN concentrations, which is not easily accessible from observational data. This review discusses deficiencies of current approaches for the different aspects of the problem and proposes several ways forward: in terms of CCN, retrievals of optical quantities such as aerosol optical depth suffer from a lack of vertical resolution, size and hygroscopicity information, non-direct relation to the concentration of aerosols, difficulty to quantify it within or below clouds, and the problem of insufficient sensitivity at low concentrations, in addition to retrieval errors. A future path forward can include utilising co-located polarimeter and lidar instruments, ideally including high-spectral-resolution lidar capability at two wavelengths to maximise vertically resolved size distribution information content. In terms of N-d, a key problem is the lack of operational retrievals of this quantity and the inaccuracy of the retrieval especially in broken-cloud regimes. As for the N-d-to-CCN sensitivity, key issues are the updraught distributions and the role of N-d sink processes, for which empirical assessments for specific cloud regimes are currently the best solutions. These considerations point to the conclusion that past studies using existing approaches have likely underestimated the true sensitivity and, thus, the radiative forcing due to the Twomey effect.
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| 5. |
- Schrödner, Roland, et al.
(author)
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Modelling multiphase aerosol-cloud processing with the 3-D CTM COSMO-MUSCAT : application for cloud events during HCCT-2010
- 2017
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In: Springer Proceedings in Complexity. - Cham : Springer International Publishing. ; , s. 587-592
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Book chapter (peer-reviewed)abstract
- The online-coupled 3-D chemistry transport model COSMO-MUSCAT was enhanced by a detailed description of aqueous phase chemical processes. The aqueous phase chemistry is represented by the detailed chemical mechanism CAPRAM 3.0i reduced (C3.0RED). In addition, the deposition schemes were improved in order to account for the deposition of matter incorporated in cloud droplets of ground layer clouds and fogs. The extended model system was applied for real 3‑D case studies connected to the field experiment HCCT-2010 (Hill Cap Cloud Thuringia, 2010). Process and sensitivity studies were conducted and the results were compared to the available measurements during HCCT-2010. The studies indicate the requirement to consider chemical cloud effects in regional CTMs because of their key impacts on e.g., oxidation capacity in the gas and aqueous phase, formation of organic and inorganic particulate matter, and droplet acidity.
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| 6. |
- Van Noije, Twan, et al.
(author)
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EC-Earth3-AerChem : A global climate model with interactive aerosols and atmospheric chemistry participating in CMIP6
- 2021
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In: Geoscientific Model Development. - : Copernicus GmbH. - 1991-959X .- 1991-9603. ; 14:9, s. 5637-5668
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Journal article (peer-reviewed)abstract
- This paper documents the global climate model EC-Earth3-AerChem, one of the members of the EC-Earth3 family of models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6). EC-Earth3-AerChem has interactive aerosols and atmospheric chemistry and contributes to the Aerosols and Chemistry Model Intercomparison Project (AerChemMIP). In this paper, we give an overview of the model, describe in detail how it differs from the other EC-Earth3 configurations, and outline the new features compared with the previously documented version of the model (EC-Earth 2.4). We explain how the model was tuned and spun up under preindustrial conditions and characterize the model's general performance on the basis of a selection of coupled simulations conducted for CMIP6. The net energy imbalance at the top of the atmosphere in the preindustrial control simulation is on average -0.09 W m-2 with a standard deviation due to interannual variability of 0.25 W m-2, showing no significant drift. The global surface air temperature in the simulation is on average 14.08 ∼ C with an interannual standard deviation of 0.17 ∼ C, exhibiting a small drift of 0.015 ± 0.005 ∼ C per century. The model's effective equilibrium climate sensitivity is estimated at 3.9 ∼ C, and its transient climate response is estimated at 2.1 ∼ C. The CMIP6 historical simulation displays spurious interdecadal variability in Northern Hemisphere temperatures, resulting in a large spread across ensemble members and a tendency to underestimate observed annual surface temperature anomalies from the early 20th century onwards. The observed warming of the Southern Hemisphere is well reproduced by the model. Compared with the ECMWF (European Centre for Medium-Range Weather Forecasts) Reanalysis version 5 (ERA5), the surface air temperature climatology for 1995-2014 has an average bias of -0.86 ± 0.05 ∼ C with a standard deviation across ensemble members of 0.35 ∼ C in the Northern Hemisphere and 1.29 ± 0.02 ∼ C with a corresponding standard deviation of 0.05 ∼ C in the Southern Hemisphere. The Southern Hemisphere warm bias is largely caused by errors in shortwave cloud radiative effects over the Southern Ocean, a deficiency of many climate models. Changes in the emissions of near-term climate forcers (NTCFs) have significant effects on the global climate from the second half of the 20th century onwards. For the SSP3-7.0 Shared Socioeconomic Pathway, the model gives a global warming at the end of the 21st century (2091-2100) of 4.9 ∼ C above the preindustrial mean. A 0.5 ∼ C stronger warming is obtained for the AerChemMIP scenario with reduced emissions of NTCFs. With concurrent reductions of future methane concentrations, the warming is projected to be reduced by 0.5 ∼ C.
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