Quantification of marine aerosol subgrid variability and its correlation with clouds based on high‐resolution regional modeling

Lin, Guang; Qian, Yun; Yan, Huiping; Zhao, Chun; Ghan, Steven J.; Easter, Richard C.; Zhang, Kai

doi:10.1002/2017jd026567

Cited by 6 publications

(9 citation statements)

References 47 publications

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“…These discrepancies do not stop at physical observations. Current global climate models operate over spatial grids that can span hundreds of kilometres per grid box and sub-grid variability within these boxes can significantly limit the accuracy of the model, particularly for aerosol parameters such as CCN (Lin et al, 2017;Weigum et al, 2016). Given the highly dynamic conditions within the Southern Ocean and the limited and sometimes conflicting observations reported to date, further investigation is required to identify the main factors contributing to aerosol variability.…”

Section: Introductionmentioning

confidence: 99%

Marine productivity and synoptic meteorology drive summer-time variability in Southern Ocean aerosols

et al. 2020

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Abstract. Cloud–radiation interactions over the Southern Ocean are not well constrained in climate models, in part due to uncertainties in the sources, concentrations, and cloud-forming potential of aerosol in this region. To date, most studies in this region have reported measurements from fixed terrestrial stations or a limited set of instrumentation and often present findings as broad seasonal or latitudinal trends. Here, we present an extensive set of aerosol and meteorological observations obtained during an austral summer cruise across the full width of the Southern Ocean south of Australia. Three episodes of continental-influenced air masses were identified, including an apparent transition between the Ferrel atmospheric cell and the polar cell at approximately 64∘ S, and accompanied by the highest median cloud condensation nuclei (CCN) concentrations, at 252 cm−3. During the other two episodes, synoptic-scale weather patterns diverted air masses across distances greater than 1000 km from the Australian and Antarctic coastlines, respectively, indicating that a large proportion of the Southern Ocean may be periodically influenced by continental air masses. In all three cases, a highly cloud-active accumulation mode dominated the size distribution, with up to 93 % of the total number concentration activating as CCN. Frequent cyclonic weather conditions were observed at high latitudes and the associated strong wind speeds led to predictions of high concentrations of sea spray aerosol. However, these modelled concentrations were not achieved due to increased aerosol scavenging rates from precipitation and convective transport into the free troposphere, which decoupled the air mass from the sea spray flux at the ocean surface. CCN concentrations were more strongly impacted by high concentrations of large-diameter Aitken mode aerosol in air masses which passed over regions of elevated marine biological productivity, potentially contributing up to 56 % of the cloud condensation nuclei concentration. Weather systems were vital for aerosol growth in biologically influenced air masses and in their absence ultrafine aerosol diameters were less than 30 nm. These results demonstrate that air mass meteorological history must be considered when modelling sea spray concentrations and highlight the potential importance of sub-grid-scale variability when modelling atmospheric conditions in the remote Southern Ocean.

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Section: Introductionmentioning

confidence: 99%

Marine productivity and synoptic meteorology drive summer-time variability in Southern Ocean aerosols

et al. 2020

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“…The global and annual averages of the ratio for the AOT are calculated to be 28.5% (HRM) and 16.6% (LRM). The value obtained from only the HRM ranges between the two values obtained by Lin et al (2017). For the CCN at a height of 2 km, the values are relatively small (7.6% for the HRM and 4.1% for the LRM),…”

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confidence: 48%

“…In addition to the impact of the model grid size on the monthly averages of the aerosol concentrations at the relevant sites, the temporal variations in the aerosol concentrations are also investigated. Such comparisons were carried out by Lin et al (2017), who investigated the marine aerosol subgrid variability using a regional HRM over the southern Pacific Ocean. Lin et al (2017) estimated variabilities in the aerosol mass concentrations of 15% near the surface and 50% in the free troposphere in a 180-km×180-km domain using 3-hourly 3-km×3-km original grids for October 2008.…”

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confidence: 99%

Global aerosol simulations using NICAM.16 on a 14-km grid spacing for a climate study: Improved and remaining issues relative to a lower-resolution model

Goto¹,

Sato²,

Yashiro³

et al. 2020

Preprint

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Abstract. High-performance computing resources allow us to conduct numerical simulations with a horizontal grid spacing that is sufficiently high to resolve cloud systems on a global scale, and high-resolution models (HRMs) generally provide better simulation performances than low-resolution models (LRMs). In this study, we execute a next-generation model that is capable of simulating global aerosols on a nonhydrostatic icosahedral atmospheric model version 16 (NICAM.16). The simulated aerosol distributions are obtained for 3 years with a HRM in a global 14-km grid spacing, an unprecedentedly high horizontal resolution and long integration period. For comparison, a NICAM with a 56-km grid spacing is also run as an LRM, although this horizontal resolution is still high among current global climate models. The comparison elucidated that the differences in the various variables of meteorological fields, including the wind speed, precipitation, clouds, radiation fluxes and total aerosols, are generally within 10 % of their annual averages, but most of the variables related to aerosols simulated by the HRM are slightly closer to the observations than are those simulated by the LRM. Upon investigating the aerosol components, the differences in the water-insoluble black carbon (WIBC) and sulfate concentrations between the HRM and LRM are large (up to 32 %), even in the annual averages. This finding is attributed to the differences in the column burden of the aerosol wet deposition, which is determined by a conversion rate of precipitation to cloud and the difference between the HRM and LRM is approximately 20 %. Additionally, the differences in the simulated aerosol concentrations at polluted sites during polluted months between the HRM and LRM are estimated with medians of −23 % (−63 % to −2.5 %) for BC, −4 % (−91 % to +18 %) for sulfate and −1 % (−49 % to +223 %) for the aerosol optical thickness (AOT). These findings indicate that the differences in the secondary and tertiary products, such as the AOT, between the different horizontal grid spacings are not explained simply by the grid size. On a global scale, the subgrid variabilities in the simulated AOT and COT in the 1°×1° domain using 6-hourly data are estimated to be 28.5 % and 80.0 %, respectively, in the HRM, whereas the corresponding differences are 16.6 % and 22.9 % in the LRM. Over the Arctic, both the HRM and the LRM generally reproduce the observed aerosols, but the largest difference in the surface BC mass concentrations between the HRM and LRM reaches 30 % in spring (the HRM-simulated results are closer to the observations). The vertical distributions of the HRM- and LRM-simulated aerosols are generally close to the measurements, but the differences between the HRM and LRM results are large above a height of approximately 3 km, mainly due to differences in the wet deposition of the aerosols. The global annual averages of the direct and indirect aerosol radiative forcings (ARFs) attributed to anthropogenic aerosols in the HRM are estimated to be −0.29 Wm−2 and −0.93 Wm−2, respectively, whereas those in the LRM are −0.24 Wm−2 and −1.10 Wm−2. The differences in the direct ARF between the HRM and LRM are primarily caused by those in the aerosol burden, whereas the differences in the indirect ARF are primarily caused by those in the cloud expression and performance, which are attributed to the grid spacing. Because one-tenth of the computer resources are required for the LRM (56-km grid) compared to the HRM (14-km grid), we recommend that the various tuning parameters associated with the aerosol distributions using the LRM can be applicable to those using the HRM under the limitation of the available computational resources or before the HRM integration.

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“…Aerosol subgrid cloud‐scale vertical transport and wet removal are closely related to clouds and usually take place on scales smaller than the traditional global climate model (GCM) grid size (typically about 100 km). Previous studies have shown the existence of large variability for aerosol processes on scales smaller the GCM grid box (Lin et al, ; Qian et al, ). This poses a significant challenge to representing aerosol lifecycles in traditional GCMs.…”

Section: Introductionmentioning

confidence: 99%

“…We found that (1) the MMF with aerosol processes explicitly represented in CRM grid cells can improve aerosol simulations in many aspects.(2) the MMF with aerosols parameterized in GCM grid cells can cause great biases in modelled aerosol distributions.Aerosol subgrid cloud-scale vertical transport and wet removal are closely related to clouds and usually take place on scales smaller than the traditional global climate model (GCM) grid size (typically about 100 km). Previous studies have shown the existence of large variability for aerosol processes on scales smaller the GCM grid box (Lin et al, 2017;Qian et al, 2010). This poses a significant challenge to representing aerosol lifecycles in traditional GCMs.…”

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confidence: 99%

Development and Evaluation of an Explicit Treatment of Aerosol Processes at Cloud Scale Within a Multi‐Scale Modeling Framework (MMF)

Lin

Ghan

Wang

et al. 2018

J Adv Model Earth Syst

Self Cite

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Modeling the aerosol lifecycle in traditional global climate models (GCM) is challenging for a variety of reasons, not the least of which is the coarse grid. The multiscale modeling framework (MMF), in which a cloud resolving model replaces conventional parameterizations of cloud processes within each GCM grid column, provides a promising framework to address this challenge. Here we develop a new version of MMF that for the first time treats aerosol processes at cloud scale to improve the aerosol-cloud interaction representation in the model. We demonstrate that the model with the explicit aerosol treatments shows significant improvements of many aspects of the simulated aerosols compared to the previous version of MMF with aerosols parameterized at the GCM grid scale. The explicit aerosol treatments produce a significant increase of the column burdens of black carbon (BC), primary organic aerosol, and sulfate by up to 40% in many remote regions, a decrease of the sea-salt aerosol burdens by 40% in remote regions. These differences are caused by the differences in aerosol convective transport and wet removal between these two models. The new model also shows reduced bias of BC surface concentration in North America and BC vertical profiles in the high latitudes. However, the biased-high BC concentrations in the upper troposphere over the remote Pacific regions remain, requiring further improvements on other process representations (e.g., secondary activation neglected in the model). Plain Language SummaryMost global climate models (GCMs) cannot resolve the important aerosol processes that are related to clouds and occur at cloud scale. This makes it difficult to predict the aerosol change and aerosol effects on climate. In contrast, the multi-scale modeling framework (MMF), which embeds a cloud resolving model (CRM) into each GCM grid column to resolve the cloud formation, provides a promising tool to handle this challenge. In this study, we develop a first global model explicitly representing aerosol processes at cloud scale (in each CRM grid cell) within a MMF. We found that (1) the MMF with aerosol processes explicitly represented in CRM grid cells can improve aerosol simulations in many aspects. (2) the MMF with aerosols parameterized in GCM grid cells can cause great biases in modelled aerosol distributions.

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Quantification of marine aerosol subgrid variability and its correlation with clouds based on high‐resolution regional modeling

Cited by 6 publications

References 47 publications

Marine productivity and synoptic meteorology drive summer-time variability in Southern Ocean aerosols

Marine productivity and synoptic meteorology drive summer-time variability in Southern Ocean aerosols

Global aerosol simulations using NICAM.16 on a 14-km grid spacing for a climate study: Improved and remaining issues relative to a lower-resolution model

Development and Evaluation of an Explicit Treatment of Aerosol Processes at Cloud Scale Within a Multi‐Scale Modeling Framework (MMF)

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