Marat Khairoutdinov

Cloud resolving modeling of the ARM summer 1997 IOP: Model formulation, results, uncertainties, and sensitivities

Abstract A new three-dimensional cloud resolving model (CRM) has been developed to study the statistical properties of cumulus convection. The model was applied to simulate a 28-day evolution of clouds over the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains site during the summer 1997 Intensive Observation Period. The model was forced by the large-scale advective tendencies and surface fluxes derived from the observations. The sensitivity of the results to the domain dimensionality and size, horizontal grid resolution, and parameterization of microphysics has been tested. In addition, the sensitivity to perturbed initial conditions has also been tested using a 20-member ensemble of runs. The model captures rather well the observed temporal evolution of the precipitable water and precipitation rate, although it severely underestimates the shaded cloud fraction possibly because of an inability to account for the lateral advection of clouds over the ARM site. The ensemble runs reveal t...

Breaking the Cloud Parameterization Deadlock

A key factor limiting the reliability of simulations of anthropogenic climate change is the inability to accurately represent the various effects of clouds on climate. Despite the best efforts of t...

A New Cloud Physics Parameterization in a Large-Eddy Simulation Model of Marine Stratocumulus

Abstract A new bulk microphysical parameterization for large-eddy simulation (LES) models of the stratocumulus-topped boundary layer has been developed using an explicit (drop spectrum resolving) microphysical model as a data source and benchmark for comparison. The liquid water is divided into two categories, nonprecipitable cloud water and drizzle, similar to traditional Kessler-type parameterizations. The cloud condensation nucleus (CCN) count, cloud/drizzle water mixing ratios, cloud/drizzle drop concentrations, and the cloud drop integral radius are predicted in the new scheme. The source/sink terms such as autoconversion/accretion of cloud water into/by drizzle are regressed using the cloud drop size spectra predicted by an explicit microphysical model. The results from the explicit and the new bulk microphysics schemes are compared for two cases: nondrizzling and heavily drizzling stratocumulus-topped boundary layers (STBLs). The evolution of the STBL (characterized by such parameters as turbulence...

Evaluation of Large-Eddy Simulations via Observations of Nocturnal Marine Stratocumulus

Data from the first research flight (RF01) of the second Dynamics and Chemistry of Marine Stratocumulus (DYCOMS-II) field study are used to evaluate the fidelity with which large-eddy simulations (LESs) can represent the turbulent structure of stratocumulus-topped boundary layers. The initial data and forcings for this case placed it in an interesting part of parameter space, near the boundary where cloud-top mixing is thought to render the cloud layer unstable on the one hand, or tending toward a decoupled structure on the other hand. The basis of this evaluation consists of sixteen 4-h simulations from 10 modeling centers over grids whose vertical spacing wa s5ma t thecloud-top interface and whose horizontal spacing was 35 m. Extensive sensitivity studies of both the configuration of the case and the numerical setup also enhanced the analysis. Overall it was found that (i) if efforts are made to reduce spurious mixing at cloud top, either by refining the vertical grid or limiting the effects of the subgrid model in this region, then the observed turbulent and thermodynamic structure of the layer can be reproduced with some fidelity; (ii) the base, or native configuration of most simulations greatly overestimated mixing at cloud top, tending toward a decoupled layer in which cloud liquid water path and turbulent intensities were grossly underestimated; (iii) the sensitivity of the simulations to the representation of mixing at cloud top is, to a certain extent, amplified by particulars of this case. Overall the results suggest that the use of LESs to map out the behavior of the stratocumulus-topped boundary layer in this interesting region of parameter space requires a more compelling representation of processes at cloud top. In the absence of significant leaps in the understanding of subgrid-scale (SGS) physics, such a representation can only be achieved by a significant refinement in resolution—a refinement that, while conceivable given existing resources, is probably still beyond the reach of most centers.

A cloud resolving model as a cloud parameterization in the NCAR Community Climate System Model: Preliminary results

Preliminary results of a short climate simulation with a 2-D cloud resolving model (CRM) installed into each grid column of an NCAR Community Climate System Model (CCSM) are presented. The CRM replaces the conventional convective and stratiform cloud parameterizations, and allows for explicit computation of the global cloud fraction distribution for radiation computations. The extreme computational cost of the combined CCSM/CRM model has thus far limited us to a two-month long climate simulation (December-January) using 2.8° × 2.8° resolution. The simulated geographical distributions of the total rainfall, precipitable water, cloud cover, and Earth radiation budget, for the month of January, look very reasonable.

Simulations of the Atmospheric General Circulation Using a Cloud-Resolving Model as a Superparameterization of Physical Processes

Traditionally, the effects of clouds in GCMs have been represented by semiempirical parameterizations. Recently, a cloud-resolving model (CRM) was embedded into each grid column of a realistic GCM, the NCAR Community Atmosphere Model (CAM), to serve as a superparameterization (SP) of clouds. Results of the standard CAM and the SP-CAM are contrasted, both using T42 resolution (2.8° 2.8° grid), 26 vertical levels, and up to a 500-day-long simulation. The SP was based on a two-dimensional (2D) CRM with 64 grid columns and 24 levels collocated with the 24 lowest levels of CAM. In terms of the mean state, the SP-CAM produces quite reasonable geographical distributions of precipitation, precipitable water, top-ofthe-atmosphere radiative fluxes, cloud radiative forcing, and high-cloud fraction for both December– January–February and June–July–August. The most notable and persistent precipitation bias in the western Pacific, during the Northern Hemisphere summer of all the SP-CAM runs with 2D SP, seems to go away through the use of a small-domain three-dimensional (3D) SP with the same number of grid columns as the 2D SP, but arranged in an 8 8 square with identical horizontal resolution of 4 km. Two runs with the 3D SP have been carried out, with and without explicit large-scale momentum transport by convection. Interestingly, the double ITCZ feature seems to go away in the run that includes momentum transport. The SP improves the diurnal variability of nondrizzle precipitation frequency over the standard model by precipitating most frequently during late afternoon hours over the land, as observed, while the standard model maximizes its precipitation frequency around local solar noon. Over the ocean, both models precipitate most frequently in the early morning hours as observed. The SP model also reproduces the observed global distribution of the percentage of days with nondrizzle precipitation rather well. In contrast, the standard model tends to precipitate more frequently, on average by about 20%–30%. The SP model seems to improve the convective intraseasonal variability over the standard model. Preliminary results suggest that the SP produces more realistic variability of such fields as 200-mb wind and OLR, relative to the control, including the often poorly simulated Madden–Julian oscillation (MJO).

Application of MJO Simulation Diagnostics to Climate Models

The ability of eight climate models to simulate the Madden‐Julian oscillation (MJO) is examined using diagnostics developed by the U.S. Climate Variability and Predictability (CLIVAR) MJO Working Group. Although the MJO signal has been extracted throughout the annual cycle, this study focuses on the boreal winter (November‐April) behavior. Initially, maps of the mean state and variance and equatorial space‐time spectra of 850-hPa zonal wind and precipitation are compared with observations. Models best represent the intraseasonal space‐time spectral peak in the zonal wind compared to that of precipitation. Using the phase‐ space representation of the multivariate principal components (PCs), the life cycle properties of the simulated MJOs are extracted, including the ability to represent how the MJO evolves from a given subphase and the associated decay time scales. On average, the MJO decay (e-folding) time scale for all models is shorter (;20‐ 29 days) than observations (;31 days). All models are able to produce a leading pair of multivariate principal components that represents eastward propagation of intraseasonal wind and precipitation anomalies, although the fraction of the variance is smaller than observed for all models. In some cases, the dominant time scale of these PCs is outside of the 30‐80-day band. Several key variables associated with the model’s MJO are investigated, including the surface latent heat flux, boundary layer (925 hPa) moisture convergence, and the vertical structure of moisture. Low-level moisture convergence ahead (east) of convection is associated with eastward propagation in most of the models. A few models are also able to simulate the gradual moistening of the lower troposphere that precedes observed MJO convection, as well as the observed geographical difference in the vertical structure of moisture associated with the MJO. The dependence of rainfall on lower tropospheric relative humidity and the fraction of rainfall that is stratiform are also discussed, including implications these diagnostics have for MJO simulation. Based on having the most realistic intraseasonal multivariate empirical orthogonal functions, principal component power spectra, equatorial eastward propagating outgoing longwave radiation (OLR), latent heat flux, low-level moisture convergence signals, and vertical structure of moisture over the Eastern Hemisphere, the superparameterized Community Atmosphere Model (SPCAM) and the ECHAM4/ Ocean Isopycnal Model (OPYC) show the best skill at representing the MJO.

An Energy-Balance Analysis of Deep Convective Self-Aggregation above Uniform SST

Abstract The spatial organization of deep moist convection in radiative–convective equilibrium over a constant sea surface temperature is studied. A 100-day simulation is performed with a three-dimensional cloud-resolving model over a (576 km)2 domain with no ambient rotation and no mean wind. The convection self-aggregates within 10 days into quasi-stationary mesoscale patches of dry, subsiding and moist, rainy air columns. The patches ultimately merge into a single intensely convecting moist patch surrounded by a broad region of very dry subsiding air. The self-aggregation is analyzed as an instability of a horizontally homogeneous convecting atmosphere driven by convection–water vapor–radiation feedbacks that systematically dry the drier air columns and moisten the moister air columns. Column-integrated heat, water, and moist static energy budgets over (72 km)2 horizontal blocks show that this instability is primarily initiated by the reduced radiative cooling of air columns in which there is extensive...

High-Resolution Simulation of Shallow-to-Deep Convection Transition over Land

Results are presented from a high-resolution three-dimensional simulation of shallow-to-deep convection transition based on idealization of observations made during the Large-Scale Biosphere–Atmosphere (LBA) experiment in Amazonia, Brazil, during the Tropical Rainfall Measuring Mission (TRMM)-LBA mission on 23 February. The doubly periodic grid has 1536 1536 256 grid cells with horizontal grid spacing of 100 m, thus covering an area of 154 154 km 2 . The vertical resolution varies from 50 m in the boundary layer to 100 m in the free troposphere and gradually coarsens to 250 m near the domain top at 25.4 km. The length of the simulation is 6 h, starting from an early morning sounding corresponding to 0730 local time. Convection is forced by prescribed surface latent and sensible heat fluxes and prescribed horizontally uniform radiative heating Despite a considerable amount of convective available potential energy (CAPE) in the range of 1600– 2400 J kg 1 , and despite virtually no convective inhibition (CIN) in the mean sounding throughout the simulation, the cumulus convection starts as shallow, gradually developing into congestus, and becomes deep only toward the end of simulation. Analysis shows that the reason is that the shallow clouds generated by the boundary layer turbulence are too small to penetrate deep into the troposphere, as they are quickly diluted by mixing with the environment. Precipitation and the associated cold pools are needed to generate thermals big enough to support the growth of deep clouds. This positive feedback involving precipitation is supported by a sensitivity experiment in which the cold pools are effectively eliminated by artificially switching off the evaporation of precipitation; in the experiment, the convection remains shallow throughout the entire simulation, with a few congestus but no deep clouds. The probability distribution function (PDF) of cloud size during the shallow, congestus, and deep phases is analyzed using a new method. During each of the three phases, the shallow clouds dominate the mode of the PDFs at about 1-km diameter. During the deep phase, the PDFs show cloud bases as wide as 4 km. Analysis of the joint PDFs of cloud size and in-cloud variables demonstrates that, as expected, the bigger clouds are far less diluted above their bases than their smaller counterparts. Also, thermodynamic properties at cloud bases are found to be nearly identical for all cloud sizes, with the moist static energy exceeding the mean value by as much as 4 kJ kg 1 . The width of the moist static energy distribution in the boundary layer is mostly due to variability of water vapor; therefore, clouds appear to grow from the air with the highest water vapor content available. No undiluted cloudy parcels are found near the level of neutral buoyancy. It appears that a simple entraining-plume model explains the entrainment rates rather well. The least diluted plumes in the simulation correspond to an entrainment parameter of about 0.1 km 1 .

Large‐eddy simulation of the diurnal cycle of shallow cumulus convection over land

SUMMARY Large-eddy simulations of the development of shallow cumulus convection over land are presented. Many characteristics of the cumulus layer previously found in simulations of quasi-steady convection over the sea are found to be reproduced in this more strongly forced, unsteady case. Furthermore, the results are shown to be encouragingly robust, with similar results obtained with eight independent models, and also across a range of numerical resolutions. The datasets produced are already being used in the development and evaluation of parametrizations used in numerical weather-prediction and climate models.