The formation of the stable layer below about 2 × 10⁶ Pa pressure level (about 20 km altitude) of the atmosphere of Venus detected by in situ observations is investigated by the use of a radiative-convective equilibrium model. We demonstrate that, assuming mixing ratio profiles of absorbers to be at the upper limits of the observed ranges for H₂O and SO₂ and the lower limit for CO, a stable layer forms as a radiative-convective equilibrium state, but its stability is lower than the observed one. Also, increasing the continuum absorption coefficient of CO₂ and/or H₂O, which are not well constrained observationally or experimentally, results in the formation of a stable layer whose stability is comparable to the observed one. These results suggest a practical method to form the stable layer in the dynamical models of the Venus atmosphere. Further, these results indicate that the important targets of future observations and laboratory measurements are to obtain more precise profiles of the mixing ratios of H₂O, CO, and SO₂ in the Venus atmosphere, and to determine the continuum absorption coefficients of those.

The effect of vertical discretization methods and vertical resolution on Quasi-Biennial Oscillation (QBO)-like oscillations that can occur in mechanistic General Circulation Models (dry GCMs) is investigated. Two models are compared. One model uses the spectral method in the horizontal direction but the finite difference method in the vertical direction (VFD model), while the other is a three-dimensional spectral model that uses the spectral method for discretization in both the horizontal and vertical directions (3DS model). Both models include horizontal hyperdiffusion, simple Newtonian cooling and Rayleigh friction, but as they are dry models, they do not include the effects of moist convection, and no explicit vertical diffusion is used, following a previous study. Long-term numerical integrations of these models show that the 3DS model does not generate QBO-like oscillations at the vertical resolution settings used. On the other hand, the VFD model generates QBO-like oscillations at low vertical resolution, but no QBO-like oscillations at higher vertical resolution. Wavenumber-frequency spectral analyses of wave disturbances show that, in the VFD model, the amplitude of the waves at the sigma-level near the central altitude of the QBO-like oscillations is highly dependent on the vertical resolution of the model. Analyses of the wave contribution to the vertical momentum fluxes and additional numerical experiments show that in the higher vertical resolution setting, steady eastward zonal winds form above the altitude corresponding to the tropopause, and these zonal winds suppress the upward propagation of eastward moving waves. Transformed Eulerian mean analyses are also done for the results of the VFD models to investigate the contribution of the residual circulation and the wave-mean-flow interaction to the QBO-like oscillation.

Research on particle filters has been progressing with the aim of applying them to high-dimensional systems, but alleviation of problems with ensemble Kalman filters (EnKFs) in nonlinear or non-Gaussian data assimilation is also an important issue. It is known that the deterministic EnKF is less robust than the stochastic EnKF in strongly nonlinear regimes. We prove that if the observation operator is linear the analysis ensemble perturbations of the local ensemble transform Kalman filter (LETKF) are uniform contractions of the forecast ensemble perturbations in observation space in each direction of the eigenvectors of a forecast error covariance matrix. This property approximately holds for a weakly nonlinear observation operator. These results imply that if the forecast ensemble is strongly non-Gaussian the analysis ensemble of the LETKF is also strongly non-Gaussian, and that strong non-Gaussianity therefore tends to persist in high-frequency assimilation cycles, leading to the degradation of analysis accuracy in nonlinear data assimilation. A hybrid EnKF that combines the LETKF and the stochastic EnKF is proposed to mitigate non-Gaussianity in nonlinear data assimilation with small additional computational cost. The performance of the hybrid EnKF is investigated through data assimilation experiments using a 40-variable Lorenz-96 model. Results indicate that the hybrid EnKF significantly improves analysis accuracy in high-frequency data assimilation with a nonlinear observation operator. The positive impact of the hybrid EnKF increases with the increase of the ensemble size.

What controls the variability of daily precipitation averaged over the tropics? Are these the most numerous precipitation rates or the most intense ones? And do they relate to a specific cloud type? This work addresses these questions using precipitation from the one-year simulation of the global-coupled storm-resolving ICOsahedral Non-hydrostatic model run in its Sapphire configuration (ICON-Sapphire) and observations. Moreover, we develop a framework to analyze the precipitation variability based on the area covered by and the mean intensity of different groups of precipitation rates. Our framework shows that 60 % of the precipitation variability is explained by precipitation rates between 20 mm d⁻¹ and 70 mm d⁻¹, but those precipitation rates only explain 46 % of the mean precipitation in the tropics. The decomposition of the precipitation variability into the area fraction and mean intensity of a set of precipitation rates shows that this variability is explained by changes in the area fraction covered by precipitation rates between 20 mm d⁻¹ and 70 mm d⁻¹, not by changes in the mean intensity. These changes in the area fraction result from changes in the area covered by congestus clouds, not by cumulonimbus or shallow clouds, even though congesti and cumulonimbi contribute equally to the mean tropical precipitation.

Overall, ICON-Sapphire reproduces the probability density function of precipitation rates and the control of specific precipitation rates on the tropical mean precipitation and variability compared to observations.