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Enoch Jo and Sonia Lasher-Trapp

Abstract

Supercell thunderstorms can produce heavy precipitation, and an improved understanding of entrainment may help to explain why. In Part I of this series, various mechanisms of entrainment were identified in the rotating stage of a single simulated supercell thunderstorm. The current study examines the strength and effectiveness of these mechanisms as a function of the environmental vertical wind shear in eight different supercell simulations. Entrainment is calculated directly as fluxes of air over the surface of the storm core; tracers are used to assess the resulting dilution of the moistest air ingested by the storm. Model microphysical rates are used to compare the impacts of entrainment on the efficiency of condensation/deposition of water vapor on hydrometeors within the core, and ultimately, upon precipitation production. Results show that the ascending “ribbons” of horizontal vorticity wrapping around the updraft contribute more to entrainment with increasing vertical wind shear, while turbulent eddies on the opposite side of the updraft contribute less. The storm-relative airstream introduces more low-level air into the storm core with increasing vertical wind shear. Thus, the total entrainment increases with increasing vertical wind shear, but the fractional entrainment decreases, yielding an increase in undiluted air within the storm core. As a result, the condensation efficiency within the storm core also increases with increasing vertical wind shear. Due to the increase in hydrometeors detrained aloft and the resulting enhanced evaporation as they fall, the precipitation efficiency evaluated using surface rainfall decreases with increasing vertical wind shear, as found in past studies.

Open access
Free access
Vladimir M. Gryanik and Jörg Hartmann

Abstract

We consider the closure problem of representing the higher-order moments (HOMs) in terms of lower-order moments, a central feature in turbulence modeling based on the Reynolds-averaged Navier–Stokes (RANS) approach. Our focus is on models suited for the description of asymmetric, nonlocal, and semiorganized turbulence in the dry atmospheric convective boundary layer (CBL). We establish a multivariate probability density function (PDF) describing populations of plumes that are embedded in a sea of weaker randomly spaced eddies, and apply an assumed delta-PDF approximation. The main content of this approach consists of capturing the bulk properties of the PDF. We solve the closure problem analytically for all relevant HOMs involving velocity components and temperature and establish a hierarchy of new non-Gaussian turbulence closure models of different content and complexity ranging from analytical to semianalytical. All HOMs in the hierarchy have a universal and simple functional form. They refine the widely used Millionshchikov closure hypothesis and generalize the famous quadratic skewness–kurtosis relationship to higher order. We examine the performance of the new closures by comparison with measurement, LES, and DNS data and derive empirical constants for semianalytical models, which are best for practical applications. We show that the new models have a good skill in predicting the HOMs for atmospheric CBL. Our closures can be implemented in second-, third-, and fourth-order RANS turbulence closure models of bi-, tri-, and four-variate levels of complexity. Finally, several possible generalizations of our approach are discussed.

Open access
Paul E. Roundy

Abstract

A robust linear regression algorithm is applied to estimate 95% confidence intervals on the background wind associated with Madden Julian oscillation (MJO) upper tropospheric atmospheric circulation signals characterized by different phase speeds. Data reconstructed from the ERA5 reanalysis to represent advection by the upper tropospheric background flow and MJO-associated zonal wind anomalies, together with satellite outgoing longwave radiation anomalies, all in the equatorial plane, are regressed against advection data filtered for zonal wavenumber 2 and phase speeds of 3, 4, 5, and 7 ms−1. The regressed advection by the background flow is then divided by the negative of the zonal gradient of regressed zonal wind across the central Indian Ocean base longitude at 80°E, to estimate the associated background wind that leads to the given advection. The median estimates of background wind associated with these phase speeds are 13.4, 11.2, 10.5, and 10.3 ms−1 easterly. The differences between estimated values at neighboring speeds suggests that advection acts most strongly in slow MJO events, indicating that the slowest events happen to be slow because they experience stronger easterly advection by the upper tropospheric background wind.

Open access
Free access
Masashi Minamide and Derek J. Posselt

Abstract

Atmospheric deep moist convection has emerged as one of the most challenging topics for numerical weather prediction, due to its chaotic process of development and multiscale physical interactions. This study examines the dynamics and predictability of a weakly organized linear convective system using convection permitting EnKF analysis and forecasts with assimilating all-sky satellite radiances from a water vapor sensitive band of the Advanced Baseline Imager on GOES-16. The case chosen occurred over the Gulf of Mexico on 11 June 2017 during the NASA Convective Processes Experiment (CPEX) field campaign. Analysis of the water vapor and dynamic ensemble covariance structures revealed that meso-α-scale (2000–200 km) and meso-β-scale (200–20 km) initial features helped to constrain the general location of convection with a few hours of lead time, contributing to enhancing convective activity, but meso-γ-scale (20–2 km) or even-smaller-scale features with less than 30-min lead time were identified to be essential for capturing individual convective storms. The impacts of meso-α-scale initial features on the prediction of particular individual convective cells were found to be classified into two regimes; in a relatively dry regime, the meso-α-scale environment needs to be moist enough to support the development of the convection of interest, but in a relatively wet regime, a drier meso-α-scale environment is preferable to suppress the surrounding convective activity. This study highlights the importance of high-resolution initialization of moisture fields for the prediction of a quasi-linear tropical convective system, as well as demonstrating the accuracy that may be necessary to predict convection exactly when and where it occurs.

Open access
Chiung-Yin Chang and Isaac M. Held

Abstract

Diffusive theories for the meridional atmospheric energy transport can summarize our understanding of this central aspect of the general circulation. They can also be utilized in simple models of the Earth’s energy balance to help interpret the response of the system to perturbations. A theory for this diffusivity of eddy heat transport is described based on Rhines scaling and the global entropy budget, each of which provides a constraint between the kinetic energy dissipation and the diffusivity. An expression for the diffusivity is then obtained by eliminating the dissipation from this set of two constraints. The theory can be thought of as a generalization of the theories of Held-Larichev and Barry-Craig-Thuburn. The theory is compared to simulations of the Held-Suarez idealized dry atmospheric model. Limitations of the theory are emphasized. The form of the theory allows it to be readily generalized to a moist atmosphere.

Open access
Soichiro Hirano, Kosuke Ito, Hiroyuki Yamada, Satoki Tsujino, Kazuhisa Tsuboki, and Chun-Chieh Wu

Abstract

The sporadic formation of short-lived convective clouds in the eye of Tropical Cyclone (TC) Trami (2018) is investigated using dropsonde data and simulation results from a coupled atmosphere–ocean model. According to the satellite data, top height of the convective clouds exceeds 9 km above mean sea level, considerably taller than that of typical hub clouds (2–3 km). These clouds are located 10–30 km away from the TC center. Hence, these convective clouds are called deep eye clouds (DECs) in this study. The dropsonde data reveal an increase in relative humidity in the eye region during the formation of DECs. Short-lived convective clouds are simulated up to the middle troposphere in the eye region in the coupled model. Investigation of thermodynamic conditions shows a weakened low-level warm core and associated favorable conditions for convection in the eye region during the formation of DECs. DECs are formed after the weakening and outward displacement of convective heating within the eyewall. To elucidate the influence of the changes in convective heating within the eyewall on the formation of DECs, we calculate secondary circulation and associated adiabatic warming induced by convective heating within the eyewall using the Sawyer–Eliassen equation. In the eye region, weakening of subsidence and associated vertical potential temperature advection is observed as DECs are formed. This suggests that the weakening and outward displacement of convective heating within the eyewall create favorable conditions for the sporadic formation of DECs.

Open access
Jun-Ichi Yano and Agostino Manzato

Abstract

It is typically interpreted that more moisture in the atmosphere leads to more intense rains. This notion may be supported, for example, by taking a scatterplot between rain and column precipitable water. The present paper suggests, however, that the main consequence of intense rains with more moisture in the atmosphere is that there is a higher chance of occurrence rather than an increase in the expected magnitude. This tendency equally applies to any rains above 1 mm (6 h)−1 to a lesser extent. The result is derived from an analysis of 33 local rain gauge station data and a shared sounding over Friuli Venezia Giulia, northeast Italy.

Significance Statement

Moisture is the source of clouds. Clouds, in turn, are source of rain. So we may expect that more moisture in the atmosphere causes more intense rains. We may further speculate that with more moisture in the atmosphere as a consequence of the global warning, we must face more catastrophic rain events and floods. However, this paper, by analyzing data over Friuli Venezia Giulia, northeast Italy, suggests otherwise: more moisture indeed increases frequencies of intense rains, but not their magnitudes as much.

Open access
Katelyn A. Barber, Casey D. Burleyson, Zhe Feng, and Samson M. Hagos

Abstract

In this study, a pair of convection-permitting (2-km grid spacing), month-long, wet-season Weather Research and Forecasting (WRF) Model simulations with and without the eddy-diffusivity mass-flux (EDMF) scheme are performed for a portion of the Green Ocean Amazon (GoAmazon) 2014/15 field campaign period. EDMF produces an ensemble of subgrid-scale convective plumes that evolve in response to the boundary layer meteorological conditions and can develop into shallow clouds. The objective of this study is to determine how different treatments of shallow cumulus clouds (i.e., with and without EDMF) impact the total cloud population and precipitation across the Amazonian rain forest, with emphasis on impacts on the likelihood of shallow-to-deep convection transitions. Results indicate that the large-scale synoptic conditions in the EDMF and control simulations are nearly identical; however, on the local scale their rainfall patterns diverge drastically and the biases decrease in EDMF. The EDMF scheme significantly increases the frequency of shallow clouds, but the frequencies of deep clouds are similar between the simulations. Deep convective clouds are tracked using a cloud-tracking algorithm to examine the impact of shallow cumulus on the surrounding ambient environment where deep convective clouds initiate. Results suggest that a rapid increase of low-level cloudiness acts to cool and moisten the low to midtroposphere during the day, favoring the transition to deep convection.

Open access