No Arabic abstract
We describe and illustrate a mechanism whereby convective aggregation and eastward propagating equatorial disturbances, similar in some respects to the Madden--Julian oscillation, arise. We construct a simple, explicit system consisting only of the shallow water equations plus a humidity variable; moisture enters via evaporation from a wet surface, is transported by the flow and removed by condensation, so providing a mass source to the height field. For a broad range of parameters the system is excitable and self-sustaining, even if linearly stable, with condensation producing convergence and gravity waves that, acting together, trigger more condensation. On the equatorial beta-plane the convection first aggregates near the equator, generating patterns related to those in the Matsuno--Gill problem. However, the pattern is unsteady and more convection is triggered on its eastern edge, leading to a precipitating disturbance that progresses eastward. The effect is enhanced by westward prevailing winds that increase the evaporation east of the disturbance. The pattern is confined to a region within a few deformation radii of equator because here the convection can best create the convergence needed to organize into a self-sustaining pattern. Formation of the disturbance preferentially occurs where the surface is warmer and sufficient time (a few tens of days) must pass before conditions arise that enable the disturbance to reform, as is characteristic both of excitable systems and the MJO itself. The speed of the disturbance depends on the efficiency of evaporation and the heat released by condensation, and is typically a few meters per second, much less than the Kelvin wave speed.
We present results derived from the analysis of spectropolarimetric measurements of active region AR12546, which represents one of the largest sunspots to have emerged onto the solar surface over the last $20$ years. The region was observed with full-Stokes scans of the Fe I 617.3 nm and Ca II 854.2 nm lines with the Interferometric BIdimensional Spectrometer (IBIS) instrument at the Dunn Solar Telescope over an uncommon, extremely long time interval exceeding three hours. Clear circular polarization (CP) oscillations localized at the umbra-penumbra boundary of the observed region were detected. Furthermore, the multi-height data allowed us to detect the downward propagation of both CP and intensity disturbances at $2.5-3$~mHz, which was identified by a phase delay between these two quantities. These results are interpreted as a propagating magneto-hydrodynamic surface mode in the observed sunspot.
Raylaigh-Benard convection is one of the most well-studied models in fluid mechanics. Atmospheric convection, one of the most important components of the climate system, is by comparison complicated and poorly understood. A key attribute of atmospheric convection is the buoyancy source provided by the condensation of water vapour, but the presence of radiation, compressibility, liquid water and ice further complicate the system and our understanding of it. In this paper we present an idealized model of moist convection by taking the Boussinesq limit of the ideal gas equations and adding a condensate that obeys a simplified Clausius--Clapeyron relation. The system allows moist convection to be explored at a fundamental level and reduces to the classical Rayleigh-Benard model if the latent heat of condensation is taken to be zero. The model has an exact, Rayleigh-number independent `drizzle solution in which the diffusion of water vapour from a saturated lower surface is balanced by condensation, with the temperature field (and so the saturation value of the moisture) determined self-consistently by the heat released in the condensation. This state is the moist analogue of the conductive solution in the classical problem. We numerically determine the linear stability properties of this solution as a function of Rayleigh number and a nondimensional latent-heat parameter. We also present a number of turbulent solutions.
Convective self-aggregation refers to a phenomenon that random convection can self-organize into large-scale clusters over an ocean surface with uniform temperature in cloud-resolving models. Understanding its physics provides insights into the development of tropical cyclones and the Madden-Julian Oscillation. Here we present a vertically resolved moist static energy (VR-MSE) framework to study convective self-aggregation. We find that the development of self-aggregation is associated with an increase of MSE variance in the boundary layer (BL). We further show that radiation dominates the generation of MSE variance, which is further enhanced by atmospheric circulations. Surface fluxes, on the other side, consume MSE variance and then inhibits self-aggregation. These results support that the BL plays a key role in the development of self-aggregation, which agrees with recent numerical simulation results and the available potential energy analyses. Moreover, we find that the adiabatic production of MSE variance due to circulation mainly comes from the near-surface layer rather than the low-level circulation emphasized by previous literature. This new analysis framework complements the previous MSE framework that does not resolve the vertical dimension.
This paper demonstrates the efficacy of data-driven localization mappings for assimilating satellite-like observations in a dynamical system of intermediate complexity. In particular, a sparse network of synthetic brightness temperature measurements is simulated using an idealized radiative transfer model and assimilated to the monsoon-Hadley multicloud model, a nonlinear stochastic model containing several thousands of model coordinates. A serial ensemble Kalman filter is implemented in which the empirical correlation statistics are improved using localization maps obtained from a supervised learning algorithm. The impact of the localization mappings is assessed in perfect model observing system simulation experiments (OSSEs) as well as in the presence of model errors resulting from the misspecification of key convective closure parameters. In perfect model OSSEs, the localization mappings that use adjacent correlations to improve the correlation estimated from small ensemble sizes produce robust accurate analysis estimates. In the presence of model error, the filter skills of the localization maps trained on perfect and imperfect model data are comparable.
Turbulence is ever produced in the low-viscosity/large-scale fluid flows by the velocity shears and, in unstable stratification, by buoyancy forces. It is commonly believed that both mechanisms produce the same type of chaotic motions, namely, the eddies breaking down into smaller ones and producing direct cascade of turbulent kinetic energy and other properties from large to small scales towards viscous dissipation. The conventional theory based on this vision yields a plausible picture of vertical mixing and remains in use since the middle of the 20th century in spite of increasing evidence of the fallacy of almost all other predictions. This paper reveals that in fact buoyancy produces chaotic vertical plumes, merging into larger ones and producing an inverse cascade towards their conversion into the self-organized regular motions. Herein, the velocity shears produce usual eddies spreading in all directions and making the direct cascade. This new paradigm is demonstrated and proved empirically; so, the paper launches a comprehensive revision of the theory of unstably stratified turbulence and its numerous geophysical or astrophysical applications.