The vertical Structure and spatial Variability of lower tropospheric Water Vapor and Clouds in the Trades

Abstract

<p><strong>Abstract.</strong> Horizontal and vertical variability of water vapor is omnipresent in the tropics but its interaction with cloudiness poses challenges for weather and climate models. In this study we compare airborne lidar measurements from a summer and a winter field campaign in the tropical Atlantic with high-resolution simulations to analyse the water vapor distributions in the trade wind regime, its covariation with cloudiness and their representation in simulations. Across model grid spacing from 300 m to 2.5 km, the simulations show good skill in reproducing the water vapor distribution in the trades as measured by the lidar. An exception to this is a pronounced moist model bias at the top of the shallow cumulus layer in the dry winter season which is accompanied by a too weak humidity inversion at the cloud top. The model's underestimation of water vapor variability in the cloud and subcloud layer occurs in both seasons but is less pronounced. Despite the model's insensitivity to resolution from hecto- to kilometer scale for the distribution of water vapor, cloud fraction decreases strongly with increasing model resolution and is not converged at hectometer grid spacing. The observed cloud deepening with increasing water vapor path is captured well across model resolution but the concurrent transition from cloud-free to low cloud fraction is better represented at hectometer resolution. In particular, in the wet summer season the simulations with kilometer-scale resolution overestimate the observed cloud fraction near the inversion but lack condensate near the observed cloud base. This illustrates how a model's ability to properly capture the water vapor distribution does not need to translate into an adequate representation of shallow cumulus clouds that live at the tail of the water vapor distribution.</p>

The role of shallow convection in the momentum budget of the trades from large‐eddy‐simulation hindcasts

“…The inner domains have been run with different resolutions, which allows us to infer the importance of eddies of different scales. The dataset has already offered a wealth of new insights, for example on the diurnal cycle of marine shallow convection (Vial et al ., 2019), the shallow‐convective mass flux (Vogel et al ., 2020), the vertical distribution of lower‐tropospheric water vapour (Naumann and Kiemle, 2020) and counter‐gradient momentum transport (which we also briefly discuss below; Dixit et al ., 2021).…”

The role of shallow convection in the momentum budget of the trades from large-eddy-simulation hindcasts

“…The inner domains have been run with different resolutions, which allows us to infer the importance of eddies of different scales. The dataset has already offered a wealth of new insights, for example on the diurnal cycle of marine shallow convection (Vial et al, 2019), the shallow-convective mass flux (Vogel et al, 2020), the vertical distribution of lower-tropospheric water vapour (Naumann and Kiemle, 2020) and counter-gradient momentum transport (which we also briefly discuss below; Dixit et al, 2021).…”

Multi-layer Cloud Conditions in Trade Wind Shallow Cumulus – Confronting Models with Airborne Observations

“…As shallow cumulus convection is not expected to trigger at the same time and place in a model and reality, a statistical approach is adopted here, in which the airborne observations are compared to their model counterpart for different LWP regimes. The analysis in 80 LWP space is similar to the studies in moisture space that first have been published by Schulz and Stevens (2018) for groundbased observations and by Naumann and Kiemle (2019) for airborne observations. In the LWP space it is possible to study microphysical cloud processes like the transition from non-precipitating to precipitating clouds.…”