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• W4386871664 abstract "<strong class=journal-contentHeaderColor>Abstract.</strong> Water vapour and ozone are important for the thermal and radiative balance of the upper troposphere (UT) and lowermost stratosphere (LMS). Both species are modulated by transport processes. Chemical and microphysical processes affect them differently. Thus, representing the different processes and their interactions is a challenging task for dynamical cores, chemical modules and microphysical parameterisations of state-of-the-art atmospheric model components. To test and improve the models, high-resolution measurements of the UT–LMS are required. Here, we use measurements taken in a flight of the GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere) instrument on HALO (High Altitude and LOng Range Research Aircraft). The German research aircraft HALO performed a research flight on 26 February 2016 that covered deeply subsided air masses of the aged 2015/16 Arctic vortex, high-latitude LMS air masses, a highly textured region affected by troposphere-to-stratosphere exchange and high-altitude cirrus clouds. Therefore, it provides a challenging multifaceted case study for comparing GLORIA observations with state-of-the-art atmospheric model simulations in a complex UT–LMS region at a late stage of the Arctic winter 2015/16. Using GLORIA observations in this manifold scenario, we test the ability of the numerical weather prediction (NWP) model ICON (ICOsahedral Nonhydrostatic) with the extension ART (Aerosols and Reactive Trace gases) and the chemistry–climate model (CCM) EMAC (ECHAM5/MESSy Atmospheric Chemistry – fifth-generation European Centre Hamburg general circulation model/Modular Earth Submodel System) to model the UT–LMS composition of water vapour (H<span class=inline-formula>₂</span>O), ozone (O<span class=inline-formula>₃</span>), nitric acid (HNO<span class=inline-formula>₃</span>) and clouds. Within the scales resolved by the respective model, we find good overall agreement of both models with GLORIA. The applied high-resolution ICON-ART set-up involving an R2B7 nest (local grid refinement with a horizontal resolution of about 20 km), covering the HALO flight region, reproduces mesoscale dynamical structures well. Narrow moist filaments in the LMS observed by GLORIA at tropopause gradients in the context of a Rossby wave breaking event and in the vicinity of an occluded Icelandic low are clearly reproduced by the model. Using ICON-ART, we show that a larger filament in the west was transported horizontally into the Arctic LMS in connection with a jet stream split associated with poleward breaking of a cyclonically sheared Rossby wave. Further weaker filaments are associated with an older tropopause fold in the east. Given the lower resolution (T106) of the nudged simulation of the EMAC model, we find that this model also reproduces these features well. Overall, trace gas mixing ratios simulated by both models are in a realistic range, and major cloud systems observed by GLORIA are mostly reproduced. However, we find both models to be affected by a well-known systematic moist bias in the LMS. Further biases are diagnosed in the ICON-ART O<span class=inline-formula>₃</span>, EMAC H<span class=inline-formula>₂</span>O and EMAC HNO<span class=inline-formula>₃</span> distributions. Finally, we use sensitivity simulations to investigate (i) short-term cirrus cloud impacts on the H<span class=inline-formula>₂</span>O distribution (ICON-ART), (ii) the overall impact of polar winter chemistry and microphysical processing on O<span class=inline-formula>₃</span> and HNO<span class=inline-formula>₃</span> (ICON-ART and EMAC), (iii) the impact of the model resolution on simulated parameters (EMAC), and (iv) consequences of scavenging processes by cloud particles (EMAC). We find that changing the horizontal model resolution results in notable systematic changes for all species in the LMS, while scavenging processes play a role only in the case of HNO<span class=inline-formula>₃</span>. We discuss the model biases and deficits found in this case study that potentially affect forecasts and projections (adversely) and provide suggestions for further model improvements." @default.
• W4386871664 created "2023-09-20" @default.
• W4386871664 creator A5056460069 @default.
• W4386871664 date "2021-10-20" @default.
• W4386871664 modified "2023-09-27" @default.
• W4386871664 title "Comment on acp-2021-574" @default.
• W4386871664 doi "https://doi.org/10.5194/acp-2021-574-rc2" @default.
• W4386871664 hasPublicationYear "2021" @default.
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