The diurnal and seasonal water cycles in the Amazon remain poorly simulated in general circulation models, exhibiting peak evapotranspiration in the wrong season and rain too early in the day. We show that those biases are not present in cloud-resolving simulations with parameterized large-scale circulation. The difference is attributed to the representation of the morning fog layer, and to more accurate characterization of convection and its coupling with large-scale circulation. The morning fog layer, present in the wet season but absent in the dry season, dramatically increases cloud albedo, which reduces evapotranspiration through its modulation of the surface energy budget. These results highlight the importance of the coupling between the energy and hydrological cycles and the key role of cloud albedo feedback for climates over tropical continents.cloud-resolving models T ropical forests, and the Amazon in particular, are the biggest terrestrial CO 2 sinks on the planet, accounting for about 30% of the total net primary productivity in terrestrial ecosystems. Hence, the climate of the Amazon is of particular importance for the fate of global CO 2 concentration in the atmosphere (1). Besides the difficulty of estimating carbon pools (1-3), our incapacity to correctly predict CO 2 fluxes in the continental tropics largely results from inaccurate simulation of the tropical climate (1, 2, 4, 5). More frequent and more intense droughts in particular are expected to affect the future health of the Amazon and its capacity to act as a major carbon sink (6-8). The land surface is not isolated, however, but interacts with the weather and climate through a series of land−atmosphere feedback loops, which couple the energy, carbon, and water cycles through stomata regulation and boundary layer mediation (9).Current General Circulation Models (GCMs) fail to correctly represent some of the key features of the Amazon climate. In particular, they (i) underestimate the precipitation in the region (10, 11), (ii) do not reproduce the seasonality of either precipitation (10, 11) or surface fluxes such as evapotranspiration (12), and (iii) produce errors in the diurnal cycle and intensity of precipitation, with a tendency to rain too little and too early in the day (13,14). In the more humid Western part of the basin, surface incoming radiation, evapotranspiration, and photosynthesis all tend to peak in the dry season (15-17), whereas GCMs simulate peaks of those fluxes in the wet season (10, 11). Those issues might be related to the representation of convection (1,2,4,5,13,14) and vegetation water stress (6)(7)(8)(15)(16)(17) in GCMs.We here show that we can represent the Amazonian climate using a strategy opposite to GCMs in which we resolve convection and parameterize the large-scale circulation (Methods). The simulations lack many of the biases observed in GCMs and more accurately capture the differences between the dry and wet season of the Amazon in surface heat fluxes and precipitation. Besides top-of-the-atmosphere inso...

It is well known that vertical wind shear can organize deep convective systems and greatly extend their lifetimes. Much less is known about the influence of shear on the bulk properties of tropical convection in statistical equilibrium. To address the latter question, the authors present a series of cloud-resolving simulations on a doubly periodic domain with parameterized large-scale dynamics based on the weak temperature gradient (WTG) approximation. The horizontal-mean horizontal wind is relaxed strongly in these simulations toward a simple unidirectional linear vertical shear profile in the troposphere. The strength and depth of the shear layer are varied as control parameters. Surface enthalpy fluxes are prescribed. The results fall in two distinct regimes. For weak wind shear, time-averaged rainfall decreases with shear and convection remains disorganized. For larger wind shear, rainfall increases with shear, as convection becomes organized into linear mesoscale systems. This nonmonotonic dependence of rainfall on shear is observed when the imposed surface fluxes are moderate. For larger surface fluxes, convection in the unsheared basic state is already strongly organized, but increasing wind shear still leads to increasing rainfall. In addition to surface rainfall, the impacts of shear on the parameterized large-scale vertical velocity, convective mass fluxes, cloud fraction, and momentum transport are also discussed.

The authors investigate the effects of cloud–radiation interaction and vertical wind shear on convective ensembles interacting with large-scale dynamics in cloud-resolving model simulations, with the large-scale circulation parameterized using the weak temperature gradient approximation. Numerical experiments with interactive radiation are conducted with imposed surface heat fluxes constant in space and time, an idealized lower boundary condition that prevents wind–evaporation feedback. Each simulation with interactive radiation is compared to a simulation in which the radiative heating profile is held constant in the horizontal and in time and is equal to the horizontal-mean profile from the interactive-radiation simulation with the same vertical shear profile and surface fluxes. Interactive radiation is found to reduce mean precipitation in all cases. The magnitude of the reduction is nearly independent of the vertical wind shear but increases with surface fluxes. Deep shear also reduces precipitation, though by approximately the same amount with or without interactive radiation. The reductions in precipitation due to either interactive radiation or deep shear are associated with strong large-scale ascent in the upper troposphere, which more strongly exports moist static energy and is quantified by a larger normalized gross moist stability.

The effects of turbulent surface fluxes and radiative heating on tropical deep convection are compared in a series of idealized cloud-system-resolving simulations with parameterized large-scale dynamics. Two methods of parameterizing the large-scale dynamics are used: the weak temperature gradient (WTG) approximation and the damped gravity wave (DGW) method. Both surface fluxes and radiative heating are specified, with radiative heating taken as constant in the vertical in the troposphere. All simulations are run to statistical equilibrium. In the precipitating equilibria, which result from sufficiently moist initial conditions, an increment in surface fluxes produces more precipitation than an equal increment of column-integrated radiative heating. This is straightforwardly understood in terms of the column-integrated moist static energy budget with constant normalized gross moist stability. Under both large-scale parameterizations, the gross moist stability does in fact remain close to constant over a wide range of forcings, and the small variations that occur are similar for equal increments of surface flux and radiative heating. With completely dry initial conditions, the WTG simulations exhibit hysteresis, maintaining a dry state with no precipitation for a wide range of net energy inputs to the atmospheric column. The same boundary conditions and forcings admit a rainy state also (for moist initial conditions), and thus multiple equilibria exist under WTG. When the net forcing (surface fluxes minus radiative heating) is increased enough that simulations that begin dry eventually develop precipitation, the dry state persists longer after initialization when the surface fluxes are increased than when radiative heating is increased. The DGW method, however, shows no multiple equilibria in any of the simulations.

Using a nonhydrostatic model based on a version of Geophysical Fluid Dynamics Laboratory's FV3 dynamical core at a cloud‐resolving resolution in radiative‐convective equilibrium (RCE) configuration, the sensitivity of the mean RCE climate to the magnitude and scale‐selectivity of the divergence damping is explored. Divergence damping is used to reduce small‐scale noise in more realistic configurations of this model. This sensitivity is tied to the strength (and width) of the convective updrafts, which decreases (increases) with increased damping and acts to organize the convection, dramatically drying out the troposphere and increasing the outgoing longwave radiation. Increased damping also results in a much‐broadened precipitation probability distribution and larger extreme values, as well as reduction in cloud fraction, which correspondingly decreases the magnitude of shortwave and longwave cloud radiative effects. Solutions exhibit a monotonic dependence on the strength of the damping and asymptotically converge to the inviscid limit. While the potential dependence of RCE simulations on resolution and microphysical assumptions are generally appreciated, these results highlight the potential significance of the choice of subgrid numerical diffusion in the dynamical core.

A framework is introduced to investigate the indirect effect of aerosol loading on tropical deep convection using three-dimensional limited-domain idealized cloud-system-resolving model simulations coupled with large-scale dynamics over fixed sea surface temperature. The large-scale circulation is parameterized using the spectral weak temperature gradient (WTG) approximation that utilizes the dominant balance between adiabatic cooling and diabatic heating in the tropics. The aerosol loading effect is examined by varying the number of cloud condensation nuclei (CCN) available to form cloud droplets in the two-moment bulk microphysics scheme over a wide range of environments from 30 to 5000 cm−3. The radiative heating is held at a constant prescribed rate in order to isolate the microphysical effects. Analyses are performed over the period after equilibrium is achieved between convection and the large-scale environment. Mean precipitation is found to decrease modestly and monotonically when the aerosol number concentration increases as convection gets weaker, despite the increase in cloud liquid water in the warm-rain region and ice crystals aloft. This reduction is traced down to the reduction in surface enthalpy fluxes as an energy source to the atmospheric column induced by the coupling of the large-scale motion, though the gross moist stability remains constant. Increasing CCN concentration leads to 1) a cooler free troposphere because of a reduction in the diabatic heating and 2) a warmer boundary layer because of suppressed evaporative cooling. This dipole temperature structure is associated with anomalously descending large-scale vertical motion above the boundary layer and ascending motion at lower levels. Sensitivity tests suggest that changes in convection and mean precipitation are unlikely to be caused by the impact of aerosols on cloud droplets and microphysical properties but rather by accounting for the feedback from convective adjustment with the large-scale dynamics. Furthermore, a simple scaling argument is derived based on the vertically integrated moist static energy budget, which enables estimation of changes in precipitation given known changes in surfaces enthalpy fluxes and the constant gross moist stability. The impact on cloud hydrometeors and microphysical properties is also examined, and it is consistent with the macrophysical picture.

Mixing of environmental air into clouds, or entrainment, has been identified as a major contributor to erroneous climate predictions made by modern comprehensive climate and numerical weather prediction models. Despite receiving extensive attention, the ad hoc treatment of this convective-scale process in global models remains poor. On the other hand, while limited-area high-resolution nonhydrostatic models can directly resolve entrainment, their sensitivity to model resolution, especially with the lack of benchmark mass flux observations, limits their applicability. Here, the dataset from the Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) campaign focusing on radar retrievals of convective updraft vertical velocities is used with the aid of cloud-resolving model simulations of four deep convective events over the Amazon to provide insights into entrainment. Entrainment and detrainment are diagnosed from the model simulations by applying the mass continuity equation over cloud volumes, in which grid cells are identified by some thresholds of updraft vertical velocity and cloud condensates, and accounting for the sources and sinks of the air mass. Entrainment is then defined as the environmental air intruding into convective cores causing cloud volume to shrink, while detrainment is defined as cloudy grid cells departing the convective core and causing cloud volume to expand. It is found that the diagnosed entrainment from the simulated convective events is strongly correlated to the inverse of the updraft vertical velocities in convective cores, which enables a more robust estimation of the mixing time scale. This highlights the need for improved observational capabilities for sampling updraft velocities across diverse geographic and cloud conditions. Evaluation of a number of assumptions used to represent entrainment in parameterization schemes is also presented, as contrasted against the diagnosed one.

The effect of coupling a slab ocean mixed layer to atmospheric convection is examined in cloud‐resolving model (CRM) simulations in vertically sheared and unsheared environments without Coriolis force, with the large‐scale circulation parameterized using the Weak Temperature Gradient (WTG) approximation. Surface fluxes of heat and moisture as well as radiative fluxes are fully interactive, and the vertical profile of domain‐averaged horizontal wind is strongly relaxed toward specified profiles with vertical shear that varies from one simulation to the next. Vertical wind shear is found to play a critical role in the simulated behavior. There exists a threshold value of the shear strength above which the coupled system develops regular oscillations between deep convection and dry nonprecipitating states, similar to those found earlier in a much more idealized model which did not consider wind shear. The threshold value of the vertical shear found here varies with the depth of the ocean mixed layer. The time scale of the spontaneously generated oscillations also varies with mixed layer depth, from 10 days with a 1 m deep mixed layer to 50 days with a 10 m deep mixed layer. The results suggest the importance of the interplay between convection organized by vertical wind shear, radiative feedbacks, large‐scale dynamics, and ocean mixed layer heat storage in real intraseasonal oscillations.