Abstract

Which processes control the mean amounts of precipitation received by tropical land and ocean? Do large-scale constraints exist on the ratio between the two? We address these questions using a conceptual box model based on water balance equations. With empirical but physically motivated parameterizations of the water balance components, we construct a set of coupled differential equations that describe the dynamical behavior of the water vapor content over land and ocean as well as the land’s soil moisture content. For a closed model configuration with one ocean and one land box, we compute equilibrium solutions across the parameter space and analyze their sensitivity to parameter choices. The precipitation ratio χ, defined as the ratio between mean land and ocean precipitation rates, quantifies the land–sea precipitation contrast. We find that χ is bounded between zero and one as long as the presence of land does not affect the relationship between water vapor path and precipitation. However, for the tested parameter values, 95% of the obtained χ values are even larger than 0.75. The sensitivity analysis reveals that χ is primarily controlled by the efficiency of atmospheric moisture transport rather than by land surface parameters. We further investigate under which conditions precipitation enhancement over land (χ > 1) would be possible. An open model configuration with an island between two ocean boxes and nonzero external advection into the domain can yield χ values larger than one, but only for a small subset of parameter choices, characterized by small land fractions and a sufficiently large moisture influx through the windward boundary.

Abstract

A determination of the sign and magnitude of the soil moisture–precipitation feedback relies either on observations, where synoptic variability is difficult to isolate, or on model simulations, which suffer from biases mainly related to poorly resolved convection. In this study, a large-eddy simulation model with a resolution of 250 m is coupled to a land surface model and several idealized experiments mimicking the full diurnal cycle of convection are performed, starting from different spatially homogeneous soil moisture conditions. The goal is to determine under which conditions drier soils may produce more precipitation than wetter ones. The methodology of previous conceptual studies that have quantified the likelihood of convection to be triggered over wet or dry soils is followed but includes the production of precipitation. Although convection can be triggered earlier over dry soils than over wet soils under certain atmospheric conditions, total precipitation is found to always decrease over dry soils. By splitting the total precipitation into its magnitude and duration component, it is found that the magnitude strongly correlates with surface latent heat flux, hence implying a wet soil advantage. Because of this strong scaling, changes in precipitation duration caused by differences in convection triggering are not able to overcompensate for the lack of evaporation over dry soils. These results are further validated using two additional atmospheric soundings and a series of perturbed experiments that consider cloud radiative effects, as well as the effect of large-scale forcing, winds, and plants on the soil moisture–precipitation coupling.

Abstract

This study investigates how precipitation-driven cold pools aid the formation of wider clouds that are essential for a transition from shallow to deep convection. In connection with a temperature depression and a depletion of moisture inside developing cold pools, an accumulation of moisture in moist patches around the cold pools is observed. Convective clouds are formed on top of these moist patches. Larger moist patches form with time supporting more and larger clouds. Moreover, enhanced vertical lifting along the leading edges of the gravity current triggered by the cold pool is found. The interplay of moisture aggregation and lifting eventually promotes the formation of wider clouds that are less affected by entrainment and become deeper. These mechanisms are corroborated in a series of cloud-resolving model simulations representing different atmospheric environments. A positive feedback is observed in that, in an atmosphere in which cloud and rain formation is facilitated, stronger downdrafts will form. These stronger downdrafts lead to a stronger modification of the moisture field, which in turn favors further cloud development. This effect is not only observed in the transition phase but also active in prolonging the peak time of precipitation in the later stages of the diurnal cycle. These findings are used to propose a simple way for incorporating the effect of cold pools on cloud sizes and thereby entrainment rate into parameterization schemes for convection. Comparison of this parameterization to the cloud-resolving modeling output gives promising results.

Abstract

In his comment, D. M. Schultz asked for clarification concerning (i) the validity of the results of C. Hohenegger and B. Stevens for the development of convection over the midlatitudes and (ii) the exact meaning and computation of the term “moisture convergence.” This reply aims at clarifying these two aspects.

Abstract

Recent studies have pushed forward the idea that congestus clouds, through their moistening of the atmosphere, could promote deep convection. On the other hand, older studies have tended to relate convective initiation to the large-scale forcing. These two views are here contrasted by performing a time-scale analysis. The analysis combines ship observations, large-eddy simulations, and 1 month of brightness temperature measurements with a focus on the tropical Atlantic and adjacent land areas.

The time-scale analysis suggests that previous work may have overstated the importance of congestus moistening in the preconditioning of deep convection. It is found that cumuli congestus transition very rapidly to deep convection, in 2 h over land and 4 h over ocean. This is much faster than the time needed (10 h and longer) by congestus clouds to sufficiently moisten the atmosphere. Moreover, the majority of congestus clouds seem unable to grow into cumulonimbus and the probability of transition does not increase with increasing congestus lifetime (i.e., more moistening). Finally, the presence of cumuli congestus over a given region generally does not enhance the likelihood for deep convection development, either with respect to other regions or to clear-sky conditions. Hence, the results do not support the view of an atmosphere slowly deepening by local moistening, but rather, they may be interpreted as reminiscent of an atmosphere marked by violent and sudden outbursts of convection forced by dynamical effects. This also implies that moisture convergence is more important than local surface fluxes to trigger deep convection over a certain region.

Abstract

While the benefits of ensemble techniques over deterministic numerical weather predictions (NWP) are now widely recognized, the prospects of ensemble prediction systems (EPS) at high computational resolution are still largely unclear. Difficulties arise due to the poor knowledge of the mechanisms promoting rapid perturbation growth and propagation, as well as the role of nonlinearities. In this study, the dynamics associated with the growth and propagation of initial uncertainties is investigated by means of real-case high-resolution (cloud resolving) NWP integrations. The considered case is taken from the Mesoscale Alpine Programme intensive observing period 3 (MAP IOP3) and involves convection of intermediate intensity. To assess the underlying mechanisms and the degree of linearity upon the predictability of the flow, vastly different initial perturbation methodologies are compared, while all simulations use identical lateral boundary conditions to mimic a perfectly predictable synoptic-scale flow.

Comparison of the perturbation methodologies indicates that the ensuing patterns of ensemble spread converge within 11 h, irrespective of the initial perturbations employed. All methodologies pinpoint the same meso-beta-scale regions of the flow as suffering from predictability limitations. This result reveals the important role of nonlinearities. Analysis also shows that hot spots of error growth can quickly (1–2 h after initialization) develop far away from the initial perturbations. This rapid radiation of the initial uncertainties throughout the computational domain is due to both sound and gravity waves, followed by the triggering and/or growth of perturbations over regions of convective instability. The growth of the uncertainties is then limited by saturation effects, which in turn are controlled by the larger-scale atmospheric environment.

From a practical point of view, it is suggested that the combined effects of rapid propagation, sizeable amplification, and inherent nonlinearities may pose severe difficulties for the design of EPS or data assimilation techniques related to high-resolution quantitative precipitation forecasting.

Abstract

The distribution of cloud-base mass flux is studied using large-eddy simulations (LESs) of two reference cases: one representing conditions over the tropical ocean and another one representing midlatitude conditions over land. To examine what sets the difference between the two distributions, nine additional LES cases are set up as variations of the two reference cases. It is found that the total surface heat flux and its changes over the diurnal cycle do not influence the distribution shape. The latter is also not determined by the level of organization in the cloud field. It is instead determined by the ratio of the surface sensible heat flux to the latent heat flux, that is, the Bowen ratio B. This ratio sets the thermodynamic efficiency of the moist convective heat cycle, which determines the portion of the total surface heat flux that can be transformed into mechanical work of convection against mechanical dissipation. The thermodynamic moist heat cycle sets the average mass flux per cloud 〈m〉, and through 〈m〉 it also controls the shape of the distribution. An expression for 〈m〉 is derived based on the moist convective heat cycle and is evaluated against LES. This expression can be used in shallow cumulus parameterizations as a physical constraint on the mass flux distribution. The similarity between the mass flux and the cloud area distributions indicates that B also has a role in shaping the cloud area distribution, which could explain its different shapes and slopes observed in previous studies.

The limited atmospheric predictability has been addressed by the development of ensemble prediction systems (EPS) that are now routinely applied for medium-range synoptic-scale numerical weather prediction (NWP). With the increase of computational power, interest is growing in the design of high-resolution (cloud resolving) NWP models and their associated short-range EPS. This development raises a series of fundamental questions, especially concerning the type of error growth and the validity of the tangent-linear approximation. To address these issues, a comparison between perturbed medium-range (10 day) synoptic-scale integrations (taken from the operational ECMWF EPS with a horizontal resolution of about 80 km) and short-range (1 day) high-resolution simulations (based on the Lokal Modell of the Consortium for Small-Scale Modeling with a grid spacing of 2.2 km) is conducted. The differences between the two systems are interpreted in a nondimensional sense and illustrated with the help of the Lorenz attractor.

Typical asymptotic perturbation-doubling times of cloud-resolving and synoptic-scale simulations amount to about 4 and 40 h, respectively, and are primarily related to convective and baroclinic instability. Thus, in terms of growth rates, integrating a 1-day cloud-resolving forecast may be seen as equivalent to performing a 10-day synoptic-scale simulation. However, analysis of the prevailing linearity reveals that the two systems are fundamentally different in the following sense: the tangent-linear approximation breaks down at 1.5 h for cloud resolving against 54 h for synoptic-scale forecasts. In terms of nonlinearity, a 10-day synoptic-scale integration thus corresponds to a very short cloud-resolving simulation of merely about 7 h. The higher degree of nonlinearity raises questions concerning the direct application of standard synoptic-scale forecasting methodologies (e.g., optimal perturbations, 4D variational data assimilation, or targeted observations) to 1-day cloud-resolving forecasting.

Abstract

The influence of surface conditions in the form of changing surface temperatures on fully developed mesoscale convective systems (MCSs) is investigated using a cloud-system-resolving setup of the Icosahedral Nonhydrostatic (ICON) model (1-km grid spacing). The simulated MCSs take the form of squall lines with trailing stratiform precipitation. After the squall lines have reached a quasi-steady state, secondary convection is triggered ahead of the squall line, resulting in an increase of squall-line propagation speed, also known as discrete propagation. The higher propagation speed is then maintained for the remainder of the simulations because secondary convection ahead of the squall line acts to reduce the environmental wind shear over the depth of the squall line’s cold pool. The surface conditions have only a marginal effect on the squall lines themselves. This is so because the surface fluxes cannot significantly affect the cold pool, which is continuously replenished by midtropospheric air. The midtroposphere remains similar given the use of identical initial profiles. The only effect of the surface fluxes consists in an earlier acceleration of the squall line due to earlier initiation of secondary convection with higher surface temperature. Finally, a conceptual model to estimate the change in surface temperature needed to achieve a change in onset time of prefrontal secondary convection and the associated discrete propagation events given the environmental conditions is presented.

Abstract

In this study, we estimate bulk entrainment rates for deep convection in convection-permitting simulations, conducted over the tropical Atlantic Ocean, encompassing parts of Africa and South America. We find that, even though entrainment rates decrease with height in all regions, they are, when averaging between 600 and 800 hPa, generally higher over land than over ocean. This is so because, over Amazonia, shallow convection causes an increase of bulk entrainment rates at lower levels and because, over West Africa, where entrainment rates are highest, convection is organized in squall lines. These squall lines are associated with strong mesoscale convergence, causing more intense updrafts and stronger turbulence generation in the vicinity of updrafts, increasing the entrainment rates. With the exception of West Africa, entrainment rates differ less across regions than across different environments within the regions. In contrast to what is usually assumed in convective parameterizations, entrainment rates increase with environmental humidity. Furthermore, over ocean, they increase with static stability, while over land, they decrease. In addition, confirming the results of a recent idealized study, entrainment rates increase with convective aggregation, except in regions dominated by squall lines, like over West Africa.