CJ
Christian Jakob
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An open boundary setup is presented in which a high-resolution (high-res) large eddy simulation (LES) is one-way nested in a low-resolution (low-res) LES. The high-res nested LES is compared to the periodic LES from Savazzi et al. (2023, https://doi.org/10.1175/jas-d-23-0098.1). Both simulations are forced by the regional weather model HARMONIE-AROME: the periodic LES via domain-averaged tendencies, and the open boundary setup via the boundaries of the low-res nested LES. The open boundary simulations inherit the full atmospheric state from the larger domains through frequent boundary updates, including developed cloud structures and their environmental states. Cloud structures are refined as they transition to higher-resolution simulations, with clouds breaking into smaller fragments while retaining their large-scale distribution. This results in larger, more organized clouds in the high-res nested LES compared to the periodic LES when cloud fractions are similar. The periodic LES has a stronger daily cycle in cloudiness, with days starting very cloudy and ending with clear skies, producing deeper and more intermittent clouds accompanied by more intense rainfall. This leads to greater variation in cloud structures, ranging from large clouds during cloudy periods to fewer, smaller clouds during low cloud cover. In contrast, the high-res nested LES maintains more constant cloud cover, with cloud top and size varying more gradually. The intermittent behavior of the periodic LES is explained by the applied horizontally averaged tendencies, which drive the domain toward stable or unstable conditions. Inheritance of the full atmospheric state allows the high-res nested LES to maintain larger, more organized clouds.
Plain Language Summary
In this study, we compare two types of computer simulations that model clouds in detail. One simulation (high-res nested large eddy simulation [LES]) is part of a series of models, where each smaller model gets its cloud patterns and atmospheric state from a larger model that covers a bigger area but with less detail. The other simulation (periodic LES) uses atmospheric background conditions from a larger weather model, but does not receive any clouds. The results show that the periodic LES creates clouds that change quickly, shifting between cloudy periods with large clouds and times with only a few small, scattered clouds. On the other hand, the high-res nested LES has more gradual changes in cloud patterns. In the setup consisting of a series of models, clouds tend to break into smaller fragments as they transition from larger models with less detail to smaller ones with more detail. The inheritance of clouds in the high-res nested LES results in larger, more clustered clouds during periods of similar cloud cover, compared to the periodic LES.
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Plain Language Summary
In this study, we compare two types of computer simulations that model clouds in detail. One simulation (high-res nested large eddy simulation [LES]) is part of a series of models, where each smaller model gets its cloud patterns and atmospheric state from a larger model that covers a bigger area but with less detail. The other simulation (periodic LES) uses atmospheric background conditions from a larger weather model, but does not receive any clouds. The results show that the periodic LES creates clouds that change quickly, shifting between cloudy periods with large clouds and times with only a few small, scattered clouds. On the other hand, the high-res nested LES has more gradual changes in cloud patterns. In the setup consisting of a series of models, clouds tend to break into smaller fragments as they transition from larger models with less detail to smaller ones with more detail. The inheritance of clouds in the high-res nested LES results in larger, more clustered clouds during periods of similar cloud cover, compared to the periodic LES.
...
An open boundary setup is presented in which a high-resolution (high-res) large eddy simulation (LES) is one-way nested in a low-resolution (low-res) LES. The high-res nested LES is compared to the periodic LES from Savazzi et al. (2023, https://doi.org/10.1175/jas-d-23-0098.1). Both simulations are forced by the regional weather model HARMONIE-AROME: the periodic LES via domain-averaged tendencies, and the open boundary setup via the boundaries of the low-res nested LES. The open boundary simulations inherit the full atmospheric state from the larger domains through frequent boundary updates, including developed cloud structures and their environmental states. Cloud structures are refined as they transition to higher-resolution simulations, with clouds breaking into smaller fragments while retaining their large-scale distribution. This results in larger, more organized clouds in the high-res nested LES compared to the periodic LES when cloud fractions are similar. The periodic LES has a stronger daily cycle in cloudiness, with days starting very cloudy and ending with clear skies, producing deeper and more intermittent clouds accompanied by more intense rainfall. This leads to greater variation in cloud structures, ranging from large clouds during cloudy periods to fewer, smaller clouds during low cloud cover. In contrast, the high-res nested LES maintains more constant cloud cover, with cloud top and size varying more gradually. The intermittent behavior of the periodic LES is explained by the applied horizontally averaged tendencies, which drive the domain toward stable or unstable conditions. Inheritance of the full atmospheric state allows the high-res nested LES to maintain larger, more organized clouds.
Plain Language Summary
In this study, we compare two types of computer simulations that model clouds in detail. One simulation (high-res nested large eddy simulation [LES]) is part of a series of models, where each smaller model gets its cloud patterns and atmospheric state from a larger model that covers a bigger area but with less detail. The other simulation (periodic LES) uses atmospheric background conditions from a larger weather model, but does not receive any clouds. The results show that the periodic LES creates clouds that change quickly, shifting between cloudy periods with large clouds and times with only a few small, scattered clouds. On the other hand, the high-res nested LES has more gradual changes in cloud patterns. In the setup consisting of a series of models, clouds tend to break into smaller fragments as they transition from larger models with less detail to smaller ones with more detail. The inheritance of clouds in the high-res nested LES results in larger, more clustered clouds during periods of similar cloud cover, compared to the periodic LES.
Plain Language Summary
In this study, we compare two types of computer simulations that model clouds in detail. One simulation (high-res nested large eddy simulation [LES]) is part of a series of models, where each smaller model gets its cloud patterns and atmospheric state from a larger model that covers a bigger area but with less detail. The other simulation (periodic LES) uses atmospheric background conditions from a larger weather model, but does not receive any clouds. The results show that the periodic LES creates clouds that change quickly, shifting between cloudy periods with large clouds and times with only a few small, scattered clouds. On the other hand, the high-res nested LES has more gradual changes in cloud patterns. In the setup consisting of a series of models, clouds tend to break into smaller fragments as they transition from larger models with less detail to smaller ones with more detail. The inheritance of clouds in the high-res nested LES results in larger, more clustered clouds during periods of similar cloud cover, compared to the periodic LES.
Open boundary conditions were developed for atmospheric large-eddy simulation (LES) models and implemented into the Dutch Atmospheric Large-Eddy Simulation model. The implementation was tested in a “Big Brother”-like setup, in which the simulation with open boundary conditions was forced by an identical control simulation with periodic boundary conditions. The results show that the open boundary implementation has minimal influence on the solution. Both the mean state and the turbulent structures are close to the control simulation, and disturbances at the in- and outflow boundaries are negligible. To emulate a setup in which the LES is coupled to a coarser model, the influence of coarse boundary input was tested by smoothing the output of the periodic control simulation both temporally and spatially before feeding it as input to the simulation with open boundary conditions. When smoothing is applied over larger spatial and longer temporal scales, disturbances start to form at the inflow boundary and an area exists where turbulence needs to develop. Adding synthetic turbulence to the smoothed input reduces the size of this area and the magnitude of the disturbances.
...
Open boundary conditions were developed for atmospheric large-eddy simulation (LES) models and implemented into the Dutch Atmospheric Large-Eddy Simulation model. The implementation was tested in a “Big Brother”-like setup, in which the simulation with open boundary conditions was forced by an identical control simulation with periodic boundary conditions. The results show that the open boundary implementation has minimal influence on the solution. Both the mean state and the turbulent structures are close to the control simulation, and disturbances at the in- and outflow boundaries are negligible. To emulate a setup in which the LES is coupled to a coarser model, the influence of coarse boundary input was tested by smoothing the output of the periodic control simulation both temporally and spatially before feeding it as input to the simulation with open boundary conditions. When smoothing is applied over larger spatial and longer temporal scales, disturbances start to form at the inflow boundary and an area exists where turbulence needs to develop. Adding synthetic turbulence to the smoothed input reduces the size of this area and the magnitude of the disturbances.
Most cumulus parametrizations today make use of a simple conceptual model of convection, called the mass-flux approach. This approach depicts convection as an ensemble of updrafts and downdrafts occurring within a model grid-box. The aim of this study is to determine convective mass-fluxes and their constituents on the scale of a 100 km GCM grid-box from a C-band polarimetric radar and thereafter investigate the relative role of area fraction and vertical velocity in determining the shape and magnitude of bulk mass-flux profiles. We make use of observational estimates of these quantities spanning 13 wet seasons in the tropical region of Darwin. Following a bulk approach, the results show that the distribution of mass-flux is positively skewed and its mean profile peaks at 4 km. This is the result of constant area fractions and increasing vertical velocities below that level. Above 4 km, in-cloud vertical velocity plays a marginal role compared to the convective area fraction in controlling mass-flux profiles.
...
Most cumulus parametrizations today make use of a simple conceptual model of convection, called the mass-flux approach. This approach depicts convection as an ensemble of updrafts and downdrafts occurring within a model grid-box. The aim of this study is to determine convective mass-fluxes and their constituents on the scale of a 100 km GCM grid-box from a C-band polarimetric radar and thereafter investigate the relative role of area fraction and vertical velocity in determining the shape and magnitude of bulk mass-flux profiles. We make use of observational estimates of these quantities spanning 13 wet seasons in the tropical region of Darwin. Following a bulk approach, the results show that the distribution of mass-flux is positively skewed and its mean profile peaks at 4 km. This is the result of constant area fractions and increasing vertical velocities below that level. Above 4 km, in-cloud vertical velocity plays a marginal role compared to the convective area fraction in controlling mass-flux profiles.
Abstract
(2019)
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Christian Jakob, Valentin Louf, Alessandro Savazzi, Alain Protat, Pier Siebesma, Louise Nuijens