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| 001 | 890965 | ||
| 005 | 20240712100834.0 | ||
| 024 | 7 | _ | |a 10.5194/acp-21-3255-2021 |2 doi |
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| 037 | _ | _ | |a FZJ-2021-01281 |
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| 100 | 1 | _ | |a Lee, Keun-Ok |0 P:(DE-HGF)0 |b 0 |e Corresponding author |
| 245 | _ | _ | |a Convective uplift of pollution from the Sichuan Basin into the Asian monsoon anticyclone during the StratoClim aircraft campaign |
| 260 | _ | _ | |a Katlenburg-Lindau |c 2021 |b EGU |
| 336 | 7 | _ | |a article |2 DRIVER |
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| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a The StratoClim airborne campaign took place in Nepal from 27 July to 10 August 2017 to document the physical and chemical properties of the South Asian upper troposphere–lower stratosphere (UTLS) during the Asian summer monsoon (ASM). In the present paper, simulations with the Meso-NH cloud-chemistry model at a horizontal resolution of 15 km are performed over the Asian region to characterize the impact of monsoon deep convection on the composition of Asian monsoon anticyclone (AMA) and on the formation of the Asian tropopause aerosol layer (ATAL) during the StratoClim campaign. StratoClim took place during a break phase of the monsoon with intense convective activity over South China and Sichuan. Comparisons between brightness temperatures (BTs) at 10.8 µm observed by satellite sensors and simulated by Meso-NH highlight the ability of the model to correctly reproduce the life cycle of deep convective clouds. A comparison between CO and O3 concentrations from Meso-NH and airborne observations (StratoClim and IAGOS (In-service Aircraft for a Global Observing System)) demonstrates that the model captures most of the observed variabilities. Nevertheless, for both gases, the model tends to overestimate the concentrations and misses some thin CO plumes related to local convective events probably because the resolution is too coarse, but the convective uplift of pollution is very well captured by the model. We have therefore focused on the impact of Sichuan convection on the AMA composition. A dedicated sensitivity simulation showed that the 7 August convective event brought large amounts of CO deep into the AMA and even across the 380 K isentropic level located at 17.8 km. This Sichuan contribution enhanced the CO concentration by ∼15 % to reach more than 180 ppbv over a large area around 15 km height. It is noteworthy that Meso-NH captures the impact of the diluted Sichuan plume on the CO concentration during a StratoClim flight south of Kathmandu, highlighting its ability to reproduce the transport pathway of Sichuan pollution. According to the model, primary organic aerosol and black carbon particles originating from Sichuan are transported following the same pathway as CO. The large particles are heavily scavenged within the precipitating part of the convective clouds but remain the most important contributor to the particle mass in the AMA. Over the whole AMA region, the 7 August convective event resulted in a 0.5 % increase in CO concentration over the 10–20 km range that lasted about 2 d. The impact of pollution uplift from three regions (India, China, and Sichuan) averaged over the first 10 d of August has also been evaluated with sensitivity simulations. Even during this monsoon break phase, the results confirm the predominant role of India relative to China with respective contributions of 11 % and 7 % to CO concentration in the 10–15 km layer. Moreover, during this period a large part (35 %) of the Chinese contribution comes from the Sichuan Basin alone. |
| 536 | _ | _ | |a 211 - Die Atmosphäre im globalen Wandel (POF4-211) |0 G:(DE-HGF)POF4-211 |c POF4-211 |x 0 |f POF IV |
| 536 | _ | _ | |a STRATOCLIM - Stratospheric and upper tropospheric processes for better climate predictions (603557) |0 G:(EU-Grant)603557 |c 603557 |x 1 |f FP7-ENV-2013-two-stage |
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| 700 | 1 | _ | |a Barret, Brice |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Flochmoën, Eric L. |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Tulet, Pierre |0 P:(DE-HGF)0 |b 3 |
| 700 | 1 | _ | |a Bucci, Silvia |0 P:(DE-Juel1)180723 |b 4 |
| 700 | 1 | _ | |a von Hobe, Marc |0 P:(DE-Juel1)129170 |b 5 |
| 700 | 1 | _ | |a Kloss, Corinna |0 P:(DE-Juel1)161426 |b 6 |
| 700 | 1 | _ | |a Legras, Bernard |0 0000-0002-3756-7794 |b 7 |
| 700 | 1 | _ | |a Leriche, Maud |0 P:(DE-HGF)0 |b 8 |
| 700 | 1 | _ | |a Sauvage, Bastien |0 0000-0003-3410-2139 |b 9 |
| 700 | 1 | _ | |a Ravegnani, Fabrizio |0 P:(DE-HGF)0 |b 10 |
| 700 | 1 | _ | |a Ulanovsky, Alexey |0 P:(DE-HGF)0 |b 11 |
| 770 | _ | _ | |a StratoClim stratospheric and upper tropospheric processes for better climate predictions |
| 773 | _ | _ | |a 10.5194/acp-21-3255-2021 |g Vol. 21, no. 5, p. 3255 - 3274 |0 PERI:(DE-600)2069847-1 |n 5 |p 3255 - 3274 |t Atmospheric chemistry and physics |v 21 |y 2021 |x 1680-7324 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/890965/files/acp-21-3255-2021.pdf |y OpenAccess |
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