Abstract. The effect of parameterized deep convection on warm conveyor belt (WCB) activity and the jet stream is investigated by performing simulations of an explosively developing large-scale cyclone that occurred during the North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX) field campaign using the Météo-France global atmospheric model ARPEGE. Three simulations differing only from their deep convection representation are analysed. The first one was performed with the Bougeault (1985) scheme (B85), the second one with the Prognostic Condensates Microphysics and Transport (PCMT) scheme of Piriou et al. (2007), and the third one without any parameterized deep convection. In the latter simulation, the release of convective instability at the resolved scales of the model generates localized cells marked by strong heating with few degrees extent in longitude and latitude along the fronts. In runs with active parameterized deep convection (B85, PCMT), the heating rate is more homogeneously distributed along fronts as the instability release happens at subgrid scales. This difference leads to more rapid and abrupt ascents in the WCB without parameterized deep convection and more moderate but more sustained ascents with parameterized deep convection. While the number of WCB trajectories does not differ much between the three simulations, the averaged heating rates over the WCB trajectories exhibits distinct behaviour. After 1 d of simulations, the upper-level heating rate is on average larger, with the B85 scheme leading to stronger potential vorticity (PV) destruction. The difference comes from the resolved sensible and latent heating and not the parameterized one. A comparison with (re)analyses and a large variety of airborne observations from the NAWDEX field campaign (Doppler radar, Doppler lidar, dropsondes) made during the coordinated flights of two aircraft in the WCB outflow region shows that B85 performs better in the representation of the double jet structure at 1 d lead time than the other two simulations. That can be attributed to the more active WCB at upper levels. However, this effect is too strong and that simulation becomes less realistic than the other ones at forecast ranges beyond 1.5 d. The simulation with the PCMT scheme has an intermediate behaviour between the one with the B85 scheme and without parameterized deep convection, but its impact on the jet stream is closer to the latter one. Finally, additional numerical experiments show that main differences in the impact on the jet between PCMT and B85 largely come from the chosen closure, with the former being based on CAPE and the latter on moisture convergence.

Abstract. The effect of parameterized deep convection on warm conveyor belt (WCB) activity and jet stream is investigated by performing simulations of an explosively-developing large-scale cyclone that occurred during the North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX) field campaign using the Météo-France global atmospheric model ARPEGE. Three simulations differing only from their deep convection representation are analysed. The first one was performed with the Bougeault et al. (1985) scheme (B85), the second one with the Prognostic Condensates Microphysics and Transport (PCMT) scheme of Piriou et al. (2007), and the third one without any parameterized deep convection. In the latter simulation, the release of convective instability at the resolved scales of the model generates localized cells marked by strong heating with few degrees extent in longitude and latitude along the fronts. In runs with active parameterized deep convection (B85, PCMT), the heating rate is more homogeneously distributed along fronts as the instability release happens at sub-grid scales. This difference leads to more rapid and abrupt ascents in the WCB without parameterized deep convection, and more moderate but more sustained ascents with parameterized deep convection. While the number of WCB trajectories does not differ much between the three simulations, the averaged heating rates over the WCB trajectories exhibits distinct behavior. After one day of simulations, the upper-level heating rate is in average larger with B85 scheme leading to stronger potential vorticity (PV) destruction. The difference comes from the large-scale heating and not the parameterized heating.A comparison with (re)analyses and a large variety of airborne observations from the NAWDEX field campaign (Doppler radar, Doppler lidar, dropsondes) made during the coordinated flights of two aircraft in the WCB outflow region shows that B85 performs better in the representation of the double jet structure at 1-day lead time than the other two simulations. That can be attributed to the more active WCB at upper levels. However this effect is too strong and that simulation becomes less realistic at longer forecast range (1.5 to 2 days) than the other ones. The simulation with PCMT scheme has an intermediate behavior between the one with B85 scheme and without parameterized deep convection but its impact on the jet stream is closer to the latter one. Finally, additional numerical experiments show that main differences in the impact on the jet between PCMT and B85 largely come from the chosen closure, the former being based on CAPE and the latter on moisture convergence.

A global sensitivity analysis of the convective-scale Application of Research to Operations at Mesoscale (AROME) model is performed in order to determine the most influential parameters on the forecast of different near-surface variables.For that purpose, the Morris method is applied to 21 parameters from six different physical and dynamical parametrization schemes, over different seasons. Results highlight a set of eight parameters with a noticeable influence on most variables, in particular 10 m wind speed and precipitation forecasts. The sensitivity of parameter uncertainties is also examined on different spatio-temporal scales. A clear diurnal cycle of parameters influence is observed in summer, in close connection with the convective activity. In addition, the spatial distribution of parameters influence is mostly consistent with the underlying distribution of weather forecasts. A Sobol' sensitivity analysis, based on surrogate models, mostly confirms Morris conclusions and highlights some interactions between parameters.