Convective self-aggregation is an atmospheric phenomenon seen in numerical simulations in a radiative convective equilibrium framework thought to be informative of some aspects of the behavior of real-world convection in the deep tropics. We impose a background mean wind flow on convection-permitting simulations through the surface flux calculation in an effort to understand how the asymmetry imposed by a mean wind influences the propagation of aggregated structures in convection. The simulations show that, with imposing mean flow, the organized convective system propagates in the direction of the flow but slows down compared to what pure advection would suggest, and it eventually becomes stationary relative to the surface after 15 simulation days. The termination of the propagation arises from momentum flux, which acts as a drag on the near-surface horizontal wind. In contrast, the thermodynamic response through the wind-induced surface heat exchange feedback is a relatively small effect, which slightly retards the propagation of the convection relative to the mean wind.

In this article, we explore the simplest possible configuration that allows for the interaction of a convective cluster with a mean flow. This is motivated by a desire to better understand processes influencing the propagation of organized deep convection in the tropics. In simulations of radiative convective equilibrium (RCE), a single aggregated cluster can develop from randomly distributed convective fields despite homogeneous initial conditions, boundary conditions, and forcing

This line of thinking leads us to attempt to study a much simpler problem, which is how convective self-aggregation responds to the imposition of a background mean flow. As a first step, we focus on how asymmetries in the surface flux, in response to a mean flow, affect the propagation of a convective cluster in RCE. We impose a large-scale mean flow in simulations of RCE in the form of a shear-free wind, a setup that has not been investigated in previous simulations of RCE. We hypothesize that, on the upwind side of a convective cluster, the mean flow adds constructively to the near-surface component of the convective-scale circulation, enhancing the surface enthalpy flux, and vice versa on the downwind side. The asymmetry in the thermodynamic response to the mean wind leads to a slow upwind propagation of the deep convective system. In addition to the thermodynamic response, we also investigate the dynamic response to the mean flow, and that is how the modified surface wind field affects the surface momentum fluxes. The simulations show that the thermodynamic response to asymmetry in the mean winds is strongly coupled to changes in the momentum budget, which equilibrates the near-surface winds, due to a mean wind contribution to the surface drag in ways that damps and eventually eliminates asymmetries in the surface heat and moisture fluxes. We perform a mechanism denial experiment to suppress the dynamic response and quantify to what extent the propagation can be attributed to the thermodynamic response.

In Sect.

We conduct numerical simulations using the University of California Los Angeles Large-Eddy Simulation (UCLA-LES) model. The UCLA-LES solves the anelastic equations with a third-order Runge–Kutta method for the temporal discretization and with centered difference in space for momentum

A

We consider two types of simulations. In a first set of experiments we conduct numerical simulations with different background wind speeds. In an effort to isolate the thermodynamic effects of the convective circulation on the evolution of the self-aggregated convective cluster, we subject the flow to mean wind whose presence is encoded through the surface fluxes. This is equivalent to simulating a situation subject to a large-scale mean wind using a Galilean transform to avoid numerical artifacts of advection

The surface fluxes, including the momentum flux (

The modification makes the model see the

The aggregated state in simulations of RCE reveals hysteresis; it hardly returns to the random occurrence of convection once an aggregated state is established

UB0, UB2, and UB4 indicate that the dynamic feedback significantly modulates the propagation of the convective system, as the surface momentum flux

In UB0 convection begins to be organized into a single cluster at around day 22, so we restart a simulation with an uncoupled

For the remainder of the study, we refer to the simulation day, where we begin to impose the background wind, as day 0 (day 26 above). For example, the time when we restart the denial experiment without mean wind (day 22) would be equivalent to day

Daily average precipitable water on day 19. Black contours indicate where precipitable water is equal to 58

Figure

Temporal evolution of

We estimate the propagation speed of a convective cluster by tracking the cluster in the simulation domain. We find all grid columns where the precipitable water (PW) is greater than 62

When

Figure

In the following sections we examine if the tendency towards stationarity is a consequence of WISHE-like asymmetries by means of an upstream and downstream difference.

The temporal evolution of the propagation speed demonstrates that the spin-down of the propagation speed occurs over a week whose timescale is longer than the convective adjustment timescale, which is on the order of hours, and the convective cluster settles around 2 weeks after it begins to propagate. We focus on two simulation periods: the transient phase for the first 5 d (day 0–4) when

The surface enthalpy flux is larger on the upwind side of a convective cluster than on the downwind side through WISHE, i.e., the modulation of

Figure

Radial distributions of the azimuthally averaged

In the model, the surface enthalpy flux is determined by the difference between the wind speed near the surface and the velocity of the surface, which is equal to 0

Without Coriolis force, the tendency of the horizontal wind is obtained as follows:

As in Fig.

As seen in

Hovmöller diagram of the cloud-top height averaged over the

To isolate the role of a sustained thermodynamic feedback, we perform an additional simulation where

As the surface momentum flux is uncoupled from the near-surface wind field, the displacement of the convective cluster with time can be considered to be a result of the pure thermodynamic process. Assuming that the change of the lateral transport of the moisture flux is negligible, the spatial distribution of PW due to the pure thermodynamic process at a certain time

This simple thermodynamic argument gives us a displacement of PW

This study uses a highly simplified framework to understand how the imposition of a mean flow may influence the propagation of organized deep convection.
For the simulations, we applied an RCE framework with a horizontal grid spacing of 3 km, with no rotation and with a prescribed SST of

Sketch of the convective cluster, the surface wind field, the imposed mean wind (

While the problem we study is probably too simple to meaningfully inform our understanding of much more complex and larger-scale processes like the MJO, it does highlight how a consideration of surface thermodynamic fluxes alone has only a small influence on the propagation of the convective cluster as well as how considering these fluxes in isolation of the associated fluxes of momentum distorts our understanding of the response to the asymmetry imposed by the mean winds. The periodic boundary conditions are limitations of our study, as they cause the effect of anomalously small fluxes to affect the inflow of the region with anomalously large fluxes in ways that damp the effect of the large fluxes. To the extent that WISHE is important for the propagation of convective self-aggregated systems, it would favor large-scale, or solitary systems, so that the moistening that leads the disturbed phase does more than simply offset the drying that lags.

A Galilean transformation can have the advantage of avoiding numerical artifacts of advection. The benefit of the approach, however, ends up being true only to a limited extent, as the convective system starts to propagate through the model grid in our study. Nevertheless, the simulations show that the convective system maintains its thermodynamic structure until the end of the simulation period when

The simplicity of our framework and the difficulties encountered in the setup of the simulations prevent direct inferences from our study for real-world propagating deep convection, let alone the MJO. Compared to typical wind speeds in the tropics, the prescribed large-scale wind speed of up to 4

The UCLA-LES model is published in the peer-reviewed paper by

BS and AKN developed the idea, designed the experimental setups, and performed initial experiments. HJ analyzed the outputs, performed further experiments, designed and carried out the denial experiment, and interpreted the results together with AKN and BS. HJ prepared the article with contributions from AKN and BS.

The authors declare that they have no conflict of interest.

We thank Cathy Hohenegger and Julia Windmiller for helpful discussions of the study. We thank Martin Singh for suggesting the analogy of the conveyor belt and Tobias Becker and Caroline Muller for fruitful comments on an early version of the article. We would like to thank two anonymous reviewers and the editor for insightful comments and suggestions on the article. Ann Kristin Naumann was supported by the Hans-Ertel Centre for Weather Research. This research network of universities, research institutes, and the Deutscher Wetterdienst is funded by the Federal Ministry of Transport and Digital Infrastructure (BMVI). Primary data and scripts used in the analysis and other supplementary information that may be useful in reproducing the author's work are archived by the Max Planck Institute for Meteorology and can be obtained by contacting publications@mpimet.mpg.de.

The article processing charges for this open-access publication were covered by the Max Planck Society.

This paper was edited by Peter Haynes and reviewed by two anonymous referees.