Convectively driven wind variability in connection to wind biases in the ECMWF operational weather model

2020 ◽  
Author(s):  
Louise Nuijens ◽  
Irina Sandu ◽  
Beatrice Saggiorato ◽  
Hauke Schulz ◽  
Mariska Koning ◽  
...  
Keyword(s):  
Model Development ◽  
Meridional Overturning Circulation ◽  
Momentum Transport ◽  
Cloud Base ◽  
Moist Convection ◽  
Shallow Convection ◽  
Wind Speeds ◽  
Wind Variability ◽  
Large Eddy

<p>Despite playing a key role in the atmospheric circulation, the representation of momentum transport by moist convection (cumulus clouds) has been largely overlooked by the model development community over the past decade, at least compared with diabatic and radiative effects of clouds. In particular, how shallow convection may influence surface and boundary layer winds is not thoroughly investigated. In this talk, we discuss the role of convective momentum transport (CMT) in setting low-level wind speed and its variability and evaluate its role in long-standing wind biases in the ECMWF IFS model.</p><p>We use high-frequency wind profiling measurements and high-resolution large-eddy simulations to inform our understanding of convectively driven wind variability. We do this at two locations: in the trades, using wind lidar and radiosonde measurements from the Barbados Cloud Observatory and the intensive EUREC4A field campaign, and over the Netherlands, using an observationally constrained reanalysis wind dataset and large-eddy simulation hindcasts.</p><p>At both locations we use the data and model output to investigate whether CMT can be responsible for a missing drag near the surface in the IFS model. Namely, at short leadtimes, the model produces stronger than observed easterly/westerly flow near the surface, while “a missing drag” produces weaker than observed wind turning. Consequently, the meridional overturning circulation in both the tropics and midlatitudes is weaker in the IFS and in ERA-Interim and ERA5 reanalysis products.</p><p>Comparing simulated and IFS wind tendencies at selected grid points at the above locations, and by turning off the process of CMT by shallow convection in the model, we gain insight in the role of CMT in explaining wind biases. We find that CMT alone does not explain a missing drag near the surface. CMT often acts to accelerate winds near the surface. But CMT plays a role in communicating biases in cloud base wind speeds towards the surface. In the trades, a strong jet near cloud base is determined by thermal wind and a strong flux of zonal momentum through cloud base, where “cumulus friction” minimizes. Near this jet, the presence of (counter-gradient) turbulent momentum fluxes produces most of the drag. Implications of these findings for CMT parameterization are discussed.</p>

scholarly journals On the Role of Entrainment in the Fate of Cumulus Thermals

2018 ◽  
Vol 75 (11) ◽  
pp. 3911-3924 ◽  
Author(s):  
Daniel Hernandez-Deckers ◽  
Steven C. Sherwood
Keyword(s):  
Initial Conditions ◽  
Cloud Base ◽  
Entrainment Rate ◽  
Moist Convection ◽  
Key Factors ◽  
Global Circulation ◽  
Ascent Rate ◽  
Global Circulation Models ◽  
Large Eddy

Abstract Mixing is one of the most important processes associated with atmospheric moist convection. It determines the two-way interaction between clouds and their environment, thus having a direct impact on the time evolution of convection. The fractional entrainment rate ε—the main parameter related to mixing—is often parameterized in global circulation models as a function of updraft properties, and at the same time has a strong influence on how convection evolves. Within the framework of cumulus thermal vortices in large-eddy simulations of convection, here we first investigate the validity of some of the most common parameterizations of ε, and then investigate how relevant ε is for the fate of these thermals. We find that 1/R, where R is a measure of the thermal’s radius, best parameterizes ε, but it explains only about 20% of the total variance. On the other hand, we find that both ε and favorable initial conditions—including high initial saturated fraction of the thermals—are key factors that affect the thermals’ ascent rate, mean buoyancy, and distance traveled. The lifetimes of thermals, however, seem not to be affected significantly by either ε or initial conditions, which supports the view of cumulus convection as a succession of many short-lived thermals. Finally, our results suggest that for the majority of in-cloud cumulus thermals the important role of environmental moisture in the deepening of convection results mainly from providing the initial moisture for the short-lived thermals as they initiate at different altitudes above cloud base, rather than favoring their buoyancy as they rise through it.

The role of convection in the momentum budget of ICON-LEM hindcasts over the North Atlantic

2020 ◽  
Author(s):  
Kevin Helfer ◽  
Louise Nuijens ◽  
Vishal Dixit ◽  
Pier Siebesma
Keyword(s):  
North Atlantic ◽  
Cloud Layer ◽  
Momentum Transport ◽  
Cloud Base ◽  
Relative Role ◽  
Shallow Convection ◽  
Near Surface ◽  
Momentum Budget ◽  
The Impact

<p>Motivated by the uncertain role of convective momentum transport from low clouds in setting patterns of wind in the trades, we discuss the impact of shallow convection on boundary-layer winds and its role in the overall momentum budget in the trades from large-domain large-eddy simulations. To this end, we analyse ICON-LEM hindcast simulations over the (sub)tropical North Atlantic during the NARVAL1 and NARVAL2 flight campaigns.</p><p>We describe that the character of the momentum flux profile differs significantly in regimes of shallow and deep convection and thus its influence on cloud-layer and near-surface winds. In particular, we establish that the momentum transport tendency is of similar importance as other terms in the momentum budget, and though the shape of the profile is remarkably insensitive to the horizontal resolution of the simulation, the relative role of subgrid and resolved fluxes changes with resolution. Furthermore, we find that counter-gradient transport occurs even in the absence of organisation, namely in the lower cloud layer, where cloudy updrafts carry slow momentum air upwards, which locally accelerates winds and may play a role at maintaining the cloud-base wind maximum.</p>

scholarly journals Nature versus Nurture in Shallow Convection

2010 ◽  
Vol 67 (5) ◽  
pp. 1655-1666 ◽  
Author(s):  
David M. Romps ◽  
Zhiming Kuang
Keyword(s):  
Standard Deviation ◽  
The Other ◽  
Cloud Base ◽  
Shallow Convection ◽  
Eddy Simulation ◽  
Cloud Properties ◽  
Nature Versus Nurture ◽  
Large Eddy ◽  
The Mean ◽  
Single Set

Abstract Tracers are used in a large-eddy simulation of shallow convection to show that stochastic entrainment (and not cloud-base properties) determines the fate of convecting parcels. The tracers are used to diagnose the correlations between a parcel’s state above the cloud base and both the parcel’s state at the cloud base and its entrainment history. The correlation with the cloud-base state goes to zero a few hundred meters above the cloud base. On the other hand, correlations between a parcel’s state and its net entrainment are large. Evidence is found that the entrainment events may be described as a stochastic Poisson process. A parcel model is constructed with stochastic entrainment that is able to replicate the mean and standard deviation of cloud properties. Turning off cloud-base variability has little effect on the results, which suggests that stochastic mass-flux models may be initialized with a single set of properties. The success of the stochastic parcel model suggests that it holds promise as the framework for a convective parameterization.

A Stochastic Unified Convection Scheme (UNICON). Part I: Formulation and Single-Column Simulation for Shallow Convection

2020 ◽  
Vol 77 (2) ◽  
pp. 583-610 ◽  
Author(s):  
Jihoon Shin ◽  
Sungsu Park
Keyword(s):  
Similarity Theory ◽  
Domain Size ◽  
Cloud Base ◽  
Moist Convection ◽  
Shallow Convection ◽  
Power Law Distribution ◽  
Convection Scheme ◽  
Multivariate Gaussian Distribution ◽  
Single Column ◽  
Mean And Variance

Abstract By extending the previously developed unified convection scheme (UNICON), we develop a stochastic UNICON with convective updraft plumes at the surface randomly sampled from the correlated multivariate Gaussian distribution for updraft vertical velocity w^ and thermodynamic scalars ϕ^, of which standard deviations and intervariable correlations are derived from the surface-layer similarity theory. The updraft plume radius R^ at the surface follows a power-law distribution with a specified scale break radius. To enhance computational efficiency, we also develop a hybrid stochastic UNICON consisting of n bin plumes and a single stochastic plume, each of which mainly controls the ensemble mean and variance of grid-mean convective tendency, respectively. We evaluated the stochastic UNICON using the large-eddy simulation (LES) of the Barbados Oceanographic and Meteorological Experiment (BOMEX) shallow convection case in a single-column mode. Consistent with the assumptions in the stochastic UNICON, the LES w^ and ϕ^ at the surface follow approximately the half- and full-Gaussian distributions, respectively. LES showed that a substantial portion of the variability in ϕ^ at the cloud base stems from the surface, which also supports the concept of stochastic UNICON that simulates various types of moist convection based on the dry stochastic convection launched from the surface. Overall, stochastic UNICON adequately reproduces the LES grid-mean thermodynamic states as well as the mean and variance of ϕ^, including their dependency on the domain size and R^. A sensitivity test showed that the perturbations of ϕ^ as well as R^ at the surface are important for the correct simulation of the grid-mean thermodynamic states.

scholarly journals Idealized Large-Eddy and Convection-Resolving Simulations of Moist Convection over Mountainous Terrain

2016 ◽  
Vol 73 (10) ◽  
pp. 4021-4041 ◽  
Author(s):  
Davide Panosetti ◽  
Steven Böing ◽  
Linda Schlemmer ◽  
Jürg Schmidli
Keyword(s):  
Deep Convection ◽  
Convective Precipitation ◽  
Scale Model ◽  
Mountainous Terrain ◽  
Moist Convection ◽  
Shallow Convection ◽  
Large Eddy ◽  
Thermally Driven ◽  
Convection Initiation ◽  
Horizontal Grid

Abstract On summertime fair-weather days, thermally driven wind systems play an important role in determining the initiation of convection and the occurrence of localized precipitation episodes over mountainous terrain. This study compares the mechanisms of convection initiation and precipitation development within a thermally driven flow over an idealized double-ridge system in large-eddy (LESs) and convection-resolving (CRM) simulations. First, LES at a horizontal grid spacing of 200 m is employed to analyze the developing circulations and associated clouds and precipitation. Second, CRM simulations at horizontal grid length of 1 km are conducted to evaluate the performance of a kilometer-scale model in reproducing the discussed mechanisms. Mass convergence and a weaker inhibition over the two ridges flanking the valley combine with water vapor advection by upslope winds to initiate deep convection. In the CRM simulations, the spatial distribution of clouds and precipitation is generally well captured. However, if the mountains are high enough to force the thermally driven flow into an elevated mixed layer, the transition to deep convection occurs faster, precipitation is generated earlier, and surface rainfall rates are higher compared to the LES. Vertical turbulent fluxes remain largely unresolved in the CRM simulations and are underestimated by the model, leading to stronger upslope winds and increased horizontal moisture advection toward the mountain summits. The choice of the turbulence scheme and the employment of a shallow convection parameterization in the CRM simulations change the strength of the upslope winds, thereby influencing the simulated timing and intensity of convective precipitation.

scholarly journals On the Mass-Flux Representation of Vertical Transport in Moist Convection

2015 ◽  
Vol 72 (12) ◽  
pp. 4445-4468 ◽  
Author(s):  
Ping Zhu
Keyword(s):  
Vertical Velocity ◽  
Mass Flux ◽  
Cloud Layer ◽  
Momentum Transport ◽  
Moist Convection ◽  
Shallow Convection ◽  
Horizontal Momentum ◽  
Thermodynamic Variables ◽  
Convective Fluxes ◽  
2D Fft

Abstract This study investigates to what extent the convective fluxes formulated within the mass-flux framework can represent the total vertical transport of heat and moisture in the cloud layer and whether the same approach can be extended to represent the vertical momentum transport using large-eddy simulations (LESs) of six well-documented cloud cases, including both deep and shallow convection. Two methods are used to decompose the LES-resolved vertical fluxes: decompositions based on the coherent convective features using the mass-flux top-hat profile and by two-dimensional fast Fourier transform (2D-FFT) in terms of wavenumbers. The analyses show that the convective fluxes computed using the mass-flux formula can account for most of the total fluxes of conservative thermodynamic variables in the cloud layer of both deep and shallow convection for an appropriately defined convective updraft fraction, a result consistent with the mass-flux dynamic view of moist convection and previous studies. However, the mass-flux approach fails to represent the vertical momentum transport in the cloud layer of both deep and shallow convection. The 2D-FFT and other analyses suggest that such a failure results from a number of reasons: 1) the complicated momentum distribution in the cloud layer cannot be well described by the simple top-hat profile; 2) shear-driven small-scale eddies are more efficient momentum carriers than coherent convective plumes; 3) the phase relationship between vertical velocity and horizontal momentum components is substantially different from that between vertical velocity and conservative thermodynamic variables; and 4) the structure of horizontal momentum can change substantially from case to case even in the same climate regime.

A Large-Eddy Simulation Study of Moist Convection Initiation over Heterogeneous Surface Fluxes

2011 ◽  
Vol 139 (9) ◽  
pp. 2901-2917 ◽  
Author(s):  
Song-Lak Kang ◽  
George H. Bryan
Keyword(s):  
Surface Flux ◽  
Surface Fluxes ◽  
Heterogeneous Surface ◽  
Cloud Base ◽  
Convergence Zone ◽  
Phase Lag ◽  
Moist Convection ◽  
Surface Moisture ◽  
Large Eddy ◽  
Convection Initiation

This study uses large-eddy simulations to investigate processes of moist convection initiation (CI) over heterogeneous surface fluxes. Surface energy balance is imposed via a 180° phase lag of the surface moisture flux (relative to the sensible heat flux), such that the relatively warm surface is relatively dry (and the relatively cool surface is relatively wet). As shown in previous simulations, a mesoscale circulation forms in the presence of surface-flux heterogeneity, which coexists with turbulent fluctuations. The mesoscale convergence zone of this circulation develops over the relatively warm surface, and this is where clouds first form. Convection initiation occurs sooner as the amplitude of the heterogeneity increases, and as the surface moisture increases (i.e., Bowen ratio decreases). Shallow clouds initiate when boundary layer heights (zi) become greater than the lifting condensation level (LCL). Deep precipitating clouds initiate when the LCL and level of free convection (LFC) are roughly the same when averaged over the relatively warm surface, which is equivalent to the mean convective inhibition (CIN) becoming nearly zero. From the perspective of the entire (mesoscale) domain, cases with strongly heterogeneous surfaces have a wider distribution of both zi and LCL. Thus, a comparison of zi with LCL over a mesoscale area (i.e., within one mesoscale model grid box) may lead to misleading conclusions about CI and cloud-base height. It is also shown that as the amplitude of the surface-flux heterogeneity increases the mesoscale convergence zone becomes narrower and stronger. Furthermore, CI occurs earlier over relatively wet surfaces partly because turbulent eddies are more vigorous owing to slightly greater buoyancy.

scholarly journals Triggering Deep Convection with a Probabilistic Plume Model

2014 ◽  
Vol 71 (11) ◽  
pp. 3881-3901 ◽  
Author(s):  
Fabio D’Andrea ◽  
Pierre Gentine ◽  
Alan K. Betts ◽  
Benjamin R. Lintner
Keyword(s):  
Climate Models ◽  
Proper Time ◽  
Deep Convection ◽  
Potential Temperature ◽  
Specific Humidity ◽  
Cloud Base ◽  
Moist Convection ◽  
Density Currents ◽  
Shallow Convection ◽  
Plume Model

Abstract A model unifying the representation of the planetary boundary layer and dry, shallow, and deep convection, the probabilistic plume model (PPM), is presented. Its capacity to reproduce the triggering of deep convection over land is analyzed in detail. The model accurately reproduces the timing of shallow convection and of deep convection onset over land, which is a major issue in many current general climate models. PPM is based on a distribution of plumes with varying thermodynamic states (potential temperature and specific humidity) induced by surface-layer turbulence. Precipitation is computed by a simple ice microphysics, and with the onset of precipitation, downdrafts are initiated and lateral entrainment of environmental air into updrafts is reduced. The most buoyant updrafts are responsible for the triggering of moist convection, causing the rapid growth of clouds and precipitation. Organization of turbulence in the subcloud layer is induced by unsaturated downdrafts, and the effect of density currents is modeled through a reduction of the lateral entrainment. The reduction of entrainment induces further development from the precipitating congestus phase to full deep cumulonimbus. Model validation is performed by comparing cloud base, cloud-top heights, timing of precipitation, and environmental profiles against cloud-resolving models and large-eddy simulations for two test cases. These comparisons demonstrate that PPM triggers deep convection at the proper time in the diurnal cycle and produces reasonable precipitation. On the other hand, PPM underestimates cloud-top height.

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