Kay Suselj

A Unified Model for Moist Convective Boundary Layers Based on a Stochastic Eddy-Diffusivity/Mass-Flux Parameterization

AbstractA single-column model (SCM) is developed for representing moist convective boundary layers. The key component of the SCM is the parameterization of subgrid-scale vertical mixing, which is based on a stochastic eddy-diffusivity/mass-flux (EDMF) approach. In the EDMF framework, turbulent fluxes are calculated as a sum of the turbulent kinetic energy–based eddy-diffusivity component and a mass-flux component. The mass flux is modeled as a fixed number of steady-state plumes. The main challenge of the mass-flux model is to properly represent cumulus clouds, which are modeled as moist plumes. The solutions have to account for a realistic representation of condensation within the plumes and of lateral entrainment into the plumes. At the level of mean condensation within the updraft, the joint pdf of moist conserved variables and vertical velocity is used to estimate the proportion of dry and moist plumes and is sampled in a Monte Carlo way creating a predefined number of plumes. The lateral entrainment ...

Eddy Diffusivity/Mass Flux and Shallow Cumulus Boundary Layer: An Updraft PDF Multiple Mass Flux Scheme

AbstractIn this study, the eddy diffusivity/mass flux (EDMF) approach is used to combine parameterizations of nonprecipitating moist convection and boundary layer turbulence. The novel aspect of this EDMF version is the use of a probability density function (PDF) to describe the moist updraft characteristics. A single bulk dry updraft is initialized at the surface and integrated vertically. At each model level, the possibility of condensation within the updraft is considered based on the PDF of updraft moist conserved variables. If the updraft partially condenses, it is split into moist and dry updrafts, which are henceforth integrated separately. The procedure is repeated at each of the model levels above. The single bulk updraft ends up branching into numerous moist and dry updrafts. With this new approach, the need to define a cloud-base closure is circumvented. This new version of EDMF is implemented in a single-column model (SCM) and evaluated using large-eddy simulation (LES) results for the Barbado...

Implementation of a Stochastic Eddy-Diffusivity/Mass-Flux Parameterization into the Navy Global Environmental Model

AbstractA unified boundary layer and shallow convection parameterization based on a stochastic eddy-diffusivity/mass-flux (EDMF) approach is implemented and tested in the Navy Global Environmental Model (NAVGEM). The primary goals of this work are to improve the representation of convectively driven boundary layers and the coupling between the boundary layer and cumulus regions. Within the EDMF framework the subgrid vertical fluxes are calculated as a sum of an eddy-diffusivity part, which in the current implementation is based on the approach developed by Louis in the late 1970s, and a stochastic mass-flux parameterization. The mass-flux parameterization is a model for both dry and moist convective thermals. Dry thermals, which represent surface-forced coherent structures in a flow, provide countergradient mixing in the boundary layer and, if conditions permit, are the roots for moist thermals. Moist thermals represent shallow convective clouds. The new parameterization implemented in a single-column mod...

On the Dependence of Cloud Feedbacks on Physical Parameterizations in WRF Aquaplanet Simulations

We investigate the effects of physical parameterizations on cloud feedback uncertainty in response to climate change. For this purpose, we construct an ensemble of eight aquaplanet simulations using the Weather Research and Forecasting (WRF) model. In each WRF-derived simulation, we replace only one parameterization at a time while all other parameters remain identical. By doing so, we aim to (i) reproduce cloud feedback uncertainty from state-of-the-art climate models and (ii) understand how parametrizations impact cloud feedbacks. Our results demonstrate that this ensemble of WRF simulations, which differ only in physical parameterizations, replicates the range of cloud feedback uncertainty found in state-of-the-art climate models. We show that microphysics and convective parameterizations govern the magnitude and sign of cloud feedbacks, mostly due to tropical low-level clouds in subsidence regimes. Finally, this study highlights the advantages of using WRF to analyze cloud feedback mechanisms owing to its plug-and-play parameterization capability.

Analyses of Shallow Convection over the Amazon Coastal Region Using Satellite Images, Data Observations and Modeling

The Belem region of the state of Para, which is located in northern of Brazil and part of the Amazon biome is characterized by high temperatures, strong convection, unstable air conditions and high humidity favoring the formation of convective clouds. Shallow convection and deep convection are among the main components of the local energy balance. Typically a deep convection over the continents is preceded by a shallow convection. An analysis of the performance of the Jet Propulsion Laboratory / National Aeronautics and Space Administration (JPL/NASA) model of shallow convection parameterization in a framework of the single column model (SCM), in relation to the cluster of cumulus clouds formed in the coastal region of the Amazon forest due to squall lines, is provided. To achieve this purpose enhanced satellite images and infrared images from channels 2 and 4 from the GOES-12 satellite, and data obtained by the “Cloud processes of tHe main precipitation systems in Brazil: A contribUtion to cloud resolVing modeling and to the GPM (GlobAl Precipitation Measurement)” CHUVA campaign, during the month of June of 2011, were used. During that period, clusters of cumulus clouds penetrated the interior of the Amazon, causing heavy rains. Results demonstrated that the parameterizations performed well in the case where only a core of clouds was observed, such as at 18:00h on 14 June. This period of the day also presents the smallest bias and root mean square error (rmse) values for the relative humidity. For the potential temperature the smallest value of bias is at 12:00h on June 7 (0.18 K), the largest one is on June 11 (-2.32 K) and the rmse ranges from 0.59 to 2.99 K.

Parameterization Interactions in Global Aquaplanet Simulations: PARAMETERIZATION INTERACTIONS

Global climate simulations rely on parameterizations of physical processes that have scales smaller than the resolved ones. In the atmosphere, these parameterizations represent moist convection, boundary layer turbulence and convection, cloud microphysics, longwave and shortwave radiation, and the interaction with the land and ocean surface. These parameterizations can generate different climates involving a wide range of interactions among parameterizations and between the parameterizations and the resolved dynamics. To gain a simplified understanding of a subset of these interactions, we perform aquaplanet simulations with the global version of the Weather Research and Forecasting (WRF) model employing a range (in terms of properties) of moist convection and boundary layer (BL) parameterizations. Significant differences are noted in the simulated precipitation amounts, its partitioning between convective and large-scale precipitation, as well as in the radiative impacts. These differences arise from the way the subcloud physics interacts with convection, both directly and through various pathways involving the large-scale dynamics and the boundary layer, convection, and clouds. A detailed analysis of the profiles of the different tendencies (from the different physical processes) for both potential temperature and water vapor is performed. While different combinations of convection and boundary layer parameterizations can lead to different climates, a key conclusion of this study is that similar climates can be simulated with model versions that are different in terms of the partitioning of the tendencies: the vertically distributed energy and water balances in the tropics can be obtained with significantly different profiles of large-scale, convection, and cloud microphysics tendencies.