Abstract. The characterization of systematic forecast errors in lower-tropospheric winds over the ocean is a primary need for reforming models. Winds are among the drivers of convection, thus an accurate representation of winds is essential for better convective parameterizations. We focus on the temporal variability and vertical distribution of lower-tropospheric wind biases in operational medium-range weather forecasts and ERA5 reanalyses produced with the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). Thanks to several sensitivity experiments and an unprecedented wealth of measurements from the 2020 EUREC4A field campaign, we show that the wind bias varies greatly from day to day, resulting in RSME's up to 2.5 m s−1, with a mean wind speed bias up to −1 m s−1 near and above the trade-inversion in the forecasts and up to −0.5 m s−1 in reanalyses. The modeled zonal and meridional wind exhibit a too strong diurnal cycle, leading to a weak wind speed bias everywhere up to 5 km during daytime, turning into a too strong wind speed bias below 2 km at nighttime. The biases are fairly insensitive to the assimilation of sondes and likely related to remote convection and large scale pressure gradients. Convective momentum transport acts to distribute biases throughout the lowest 1.5 km, whereas at higher levels, other unresolved or dynamical tendencies play a role in setting the bias. Below 1 km, modelled friction due to unresolved physical processes appears too strong, but is (partially) compensated by dynamical tendencies, making this a challenging coupled problem.

Abstract. The characterization of systematic forecast errors in lower-tropospheric winds is an essential component of model improvement. This paper is motivated by a global, long-standing surface bias in the operational medium-range weather forecasts produced with the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). Over the tropical oceans, excessive easterly flow is found. A similar bias is found in the western North Atlantic trades, where the EUREC4A field campaign provides an unprecedented wealth of measurements. We analyze the wind bias in the IFS and ERA5 reanalysis throughout the entire lower troposphere during EUREC4A. The wind bias varies greatly from day to day, resulting in root mean square errors (RMSEs) up to 2.5 m s−1, with a mean wind speed bias up to −1 m s−1 near and above the trade inversion in the forecasts and up to −0.5 m s−1 in reanalyses. These biases are insensitive to the assimilation of sondes. The modeled zonal and meridional winds exhibit a diurnal cycle that is too strong, leading to a weak wind speed bias everywhere up to 5 km during daytime but a wind speed bias below 2 km at nighttime that is too strong. Removing momentum transport by shallow convection reduces the wind bias near the surface but leads to stronger easterly near cloud base. The update in moist physics in the newest IFS cycle (cycle 47r3) reduces the meridional wind bias, especially during daytime. Below 1 km, modeled friction due to unresolved physical processes appears to be too strong but is (partially) compensated for by the dynamics, making this a challenging coupled problem.

It has long been recognized that deep convective systems play a key role in regulating the large-scale circulations and thermal structure of the atmosphere in the tropics (de

<p>The transport of horizontal momentum takes place at various spatial and temporal scales: from small-scale turbulence to cloud- and meso-scale circulations. This study focuses on the role of convective momentum transport (CMT) in the momentum budget in trade-wind cloud regimes with different patterns of cloud organization. Observations of the momentum budget during EUREC4A suggest that in early February, deeper convection and larger cloud structures are associated with a different profile of eddy momentum flux divergence than days with shallower cumulus humilis. Using large eddy simulation hindcasts and a mesoscale weather model, we study the profiles of eddy momentum flux associated with turbulence, convection and mesoscale flows in different cloud scenes during EUREC4A. Are turbulent, convective or mesoscale circulations responsible for a deceleration or acceleration of the mean flow? Are along-wind or cross-wind circulations more pronounced? Do the models show evidence of countergradient flux  production in the cloud layer?</p><p> </p><p>We select a ten-day period for which the Dutch Atmospheric Large-Eddy Simulation (DALES) model is run on a 150 km x 150 km domain with a resolution of 100 m. Its boundaries are forced hourly with dynamical tendencies from the mesoscale weather model (HARMONIE), which is initialized every 24 hours from ERA5. HARMONIE is also run in a climatological mode on a 3200 km x 2000 km domain with 2.5 km resolution, in runs with shallow convective momentum transport on and off.</p><p> </p><p>In this presentation, we first evaluate the models’ ability to reproduce the mean and evolution of the wind profiles and the momentum fluxes during the ten days, as well as the cloud organization. Second, we present and discuss the eddy momentum flux divergence that is carried by flows on different scales and evaluate its role in the momentum budget. Third, we discuss the relationship between shallow convective momentum transport and cloud organization.</p>

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