Aerosols at the poles: an AeroCom Phase II multi-model evaluation

Sand, Maria; Samset, B. H.; Balkanski, Yves; Bauer, Susanne E.; Bellouin, Nicolas; Berntsen, Terje; Bian, Huisheng; Chin, Mian; Diehl, Thomas; Easter, Richard C.; Ghan, S. J.; Iversen, Trond; Kirkevåg, Alf; Lamarque, Jean‐François; Lin, Gufa; Liu, Xiaohong; Luo, Gan; Myhre, Gunnar; Noije, Twan van; Penner, Joyce E.; Schulz, Mıchael; Seland, Øyvind; Skeie, Ragnhild Bieltvedt; Stier, Philip; Takemura, Toshihiko; Tsigaridis, Kostas; Yu, Fangqun; Zhang, Kai; Zhang, Hua

doi:10.5194/acp-17-12197-2017

Cited by 75 publications

(108 citation statements)

References 91 publications

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“…S4a). The zonal transported dust may mix with ice nuclei at high latitudes through microphysical nucleation processes and result in cloud formation Yu et al, 2012;Sand et al, 2017). Our simulations showed by the time the dust had been transported across the Pacific Ocean that > 4 Tg of fine dust aerosols remained in suspension in the atmosphere (Fig.…”

Section: Influence On Asia-pacific Regionmentioning

confidence: 89%

“…This suspended dust likely influenced the atmospheric chemical composition as well as optical proper-ties. These anomalies of fast-rising atmospheric aerosol concentration could directly or indirectly influence the climate of temperature-sensitive regions like the Arctic (Di Pierro et al, 2011;Carslaw et al, 2013;Sand et al, 2017).…”

Section: Influence On Asia-pacific Regionmentioning

confidence: 99%

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East Asian dust storm in May 2017: observations, modelling, and its influence on the Asia-Pacific region

et al. 2018

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Abstract. A severe dust storm event originated from the Gobi Desert in Central and East Asia during 2–7 May 2017. Based on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite products, hourly environmental monitoring measurements from Chinese cities and East Asian meteorological observation stations, and numerical simulations, we analysed the spatial and temporal characteristics of this dust event as well as its associated impact on the Asia-Pacific region. The maximum observed hourly PM10 (particulate matter with an aerodynamic diameter ≤ 10 µm) concentration was above 1000 µg m−3 in Beijing, Tianjin, Shijiazhuang, Baoding, and Langfang and above 2000 µg m−3 in Erdos, Hohhot, Baotou, and Alxa in northern China. This dust event affected over 8.35 million km2, or 87 % of the Chinese mainland, and significantly deteriorated air quality in 316 cities of the 367 cities examined across China. The maximum surface wind speed during the dust storm was 23–24 m s−1 in the Mongolian Gobi Desert and 20–22 m s−1 in central Inner Mongolia, indicating the potential source regions of this dust event. Lidar-derived vertical dust profiles in Beijing, Seoul, and Tokyo indicated dust aerosols were uplifted to an altitude of 1.5–3.5 km, whereas simulations by the Weather Research and Forecasting with Chemistry (WRF-Chem) model indicated 20.4 and 5.3 Tg of aeolian dust being deposited respectively across continental Asia and the North Pacific Ocean. According to forward trajectory analysis by the FLEXible PARTicle dispersion (FLEXPART) model, the East Asian dust plume moved across the North Pacific within a week. Dust concentrations decreased from the East Asian continent across the Pacific Ocean from a magnitude of 103 to 10−5 µg m−3, while dust deposition intensity ranged from 104 to 10−1 mg m−2. This dust event was unusual due to its impact on continental China, the Korean Peninsula, Japan, and the North Pacific Ocean. Asian dust storms such as those observed in early May 2017 may lead to wider climate forcing on a global scale.

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Section: Influence On Asia-pacific Regionmentioning

confidence: 89%

Section: Influence On Asia-pacific Regionmentioning

confidence: 99%

East Asian dust storm in May 2017: observations, modelling, and its influence on the Asia-Pacific region

et al. 2018

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“…They showed a tendency to underestimate peak near-surface BC concentrations in late winter and/or early spring (Shindell et al, 2008). Although more recent studies show an improvement in the representation of the high late winter and/or early spring concentrations (e.g., Eckhardt et al, 2015;Sand et al, 2017), the modelto-model variability in simulated BC concentration remains considerable (Eckhardt et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

The importance of the representation of air pollution emissions for the modeled distribution and radiative effects of black carbon in the Arctic

et al. 2019

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Aerosol particles can contribute to the Arctic amplification (AA) by direct and indirect radiative effects. Specifically, black carbon (BC) in the atmosphere, and when deposited on snow and sea ice, has a positive warming effect on the top-of-atmosphere (TOA) radiation balance during the polar day. Current climate models, however, are still struggling to reproduce Arctic aerosol conditions. We present an evaluation study with the global aerosol-climate model ECHAM6.3-HAM2.3 to examine emission-related uncertainties in the BC distribution and the direct radiative effect of BC. The model results are comprehensively compared against the latest ground and airborne aerosol observations for the period 2005-2017, with a focus on BC. Four different setups of air pollution emissions are tested. The simulations in general match well with the observed amount and temporal variability in near-surface BC in the Arctic. Using actual daily instead of fixed biomass burning emissions is crucial for reproducing individual pollution events but has only a small influence on the seasonal cycle of BC. Compared with commonly used fixed anthropogenic emissions for the year 2000, an up-to-date inventory with transient air pollution emissions results in up to a 30 % higher annual BC burden locally. This causes a higher annual mean all-sky net direct radiative effect of BC of over 0.1 W m −2 at the top of the atmosphere over the Arctic region (60-90 • N), being locally more than 0.2 W m −2 over the eastern Arctic Ocean. We estimate BC in the Arctic as leading to an annual net gain of 0.5 W m −2 averaged over the Arctic region but to a local gain of up to 0.8 W m −2 by the direct radiative effect of atmospheric BC plus the effect by the BC-in-snow albedo reduction. Long-range transport is identified as one of the main sources of uncertainties for ECHAM6.3-HAM2.3, leading to an overestimation of BC in atmospheric layers above 500 hPa, especially in summer. This is related to a misrepresentation in wet removal in one identified case at least, which was observed during the ARCTAS (Arctic Research of the Composition of the Troposphere from Aircraft and Satellites) summer aircraft campaign. Overall, the current model version has significantly improved since previous intercomparison studies and now performs better than the multi-model average in the Aerosol Comparisons between Observation and Models (AEROCOM) initiative in terms of the spatial and temporal distribution of Arctic BC.

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“…In both aerosol categories, dust and the rest, the majority of the cases fall under the low AOD conditions. Such result is expected in the Arctic since the mean AOD over the region fluctuates around 0.07 at 500 nm (Sand et al, 2017) with occasional pollution episodes from lower latitudes. Nevertheless, there is a rather equal fraction of mineral dust and PD cases over the dust category regardless the aerosol load.…”

Section: Aerosol Load Effectmentioning

confidence: 73%

“…Aerosol layers with AOD < 0.10 were considered as low concentration and those with AOD > 0.25 as high. The low AOD threshold is typical for Arctic aerosol conditions (Sand et al, 2017), while the high AOD limit is a compromise between the higher AODs, which were observed in this region and the amount of data points in our data set. Figure 6a delivers the same information as Figure 5 but with the AOD constraint, and Figure 6b shows the number of cases per aerosol type for each temperature bin for each aerosol category and load.…”

Section: Aerosol Load Effectmentioning

confidence: 82%

Aerosol Effect on the Cloud Phase of Low‐Level Clouds Over the Arctic

et al. 2019

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Three years of nighttime Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation data was used in synergy with CloudSat measurements to quantify how strongly aerosol type and aerosol load affect the cloud phase in low‐level clouds over the Arctic. Supercooled liquid layers were present in the majority of observed low‐level clouds (0.75 ≤ z ≤ 3.5 km) between −10 and −25 °C. Furthermore, based on the subset (6%) of data with high quality assurance for aerosol typing, ice formation is more common in the presence of dust or continental aerosols as opposed to marine or elevated smoke aerosols. With the first aerosol group, glaciated clouds were found at cloud top temperatures of 2 to 4 °C warmer than with the latter aerosol types. Further association of the aerosol concentration with the cloud phase showed that the aerosol concentration outweighs the aerosol type effect. Depending on the aerosol load, the temperature at which a cloud completely glaciates can vary by up to 6–10 °C. However, this behavior was most pronounced in stable atmospheric conditions and absent over open ocean with lower tropospheric stability values and probably less stratified clouds. Finally, more mixed‐phase clouds were associated with high aerosol load, suggesting that mixed‐phase clouds have an extended lifetime in the Arctic under high cloud condensation nuclei concentrations. This implies that in a pristine environment, with few or no local aerosol sources, and under the investigated conditions the amount of aerosol particles affects the cloud phase more than the aerosol type does.

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Aerosols at the poles: an AeroCom Phase II multi-model evaluation

Cited by 75 publications

References 91 publications

East Asian dust storm in May 2017: observations, modelling, and its influence on the Asia-Pacific region

East Asian dust storm in May 2017: observations, modelling, and its influence on the Asia-Pacific region

The importance of the representation of air pollution emissions for the modeled distribution and radiative effects of black carbon in the Arctic

Aerosol Effect on the Cloud Phase of Low‐Level Clouds Over the Arctic

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