Hectometric-scale modelling of the mixed layer in an urban region evaluated with a dense LiDAR-ceilometer network

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Abstract

With development in recent years of hectometric (O(100 m); hm) scale numerical weather prediction (NWP) models, there is a need for their evaluation with high spatio-Temporal scale observations. Here we assess UK Met Office Unified Model (UM) simulations with grid-spacing down to 100 m using a dense network of observations obtained during the urbisphere-Berlin campaign. A network of 25 automatic lidars-ceilometers (ALCs) provide aerosol attenuated backscatter observations from which mixed-layer height (MLH) is determined. UM simulated aerosol on 2 d (18 April and 4 August 2022) is used to determine model MLH with a novel algorithm (MMLH). Evaluation of MMLH with ALCs is focused on the MLH (1) urban-rural variability, and (2) urban plume. MMLH is consistently able to reproduce the vertical extent of the mixed layer during late afternoon despite the 2 case-study days having different maxima. MMLH performance is better in the 100 m model domain compared to a 300 m configuration, which may be explained by the higher vertical resolution in the 100 m configuration. During the August case in which an extreme heat event occurred, a delayed MLH growth is seen in the morning and afternoon over the city compared to the rural surroundings in both the model and ALCs. Both days show a distinct influence of the city through the mixed layer, including a plume extending downwind of the city that is detectable in both the observations and model. The modelled urban plume has a deeper mixed layer compared to the rural surroundings (4 August: g1/4 500 m; 18 April: g1/4 200 m) for up to 15 km downwind of the city. Copyright:

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Glazer, R. H., Grimmond, S., Blunn, L., Fenner, D., Lean, H., Christen, A., … Shonk, J. K. P. (2025). Hectometric-scale modelling of the mixed layer in an urban region evaluated with a dense LiDAR-ceilometer network. Weather and Climate Dynamics, 6(4), 1723–1742. https://doi.org/10.5194/wcd-6-1723-2025

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