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Marat Khairoutdinov and Yefim Kogan

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 intensity, drizzle rates, CCN depletion rates, fractional cloud cover, and drizzle effects on internal stratification) simulated by the bulk microphysical model was in good agreement with the explicit microphysical model.

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Marat Khairoutdinov and David Randall

Abstract

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 km2. 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.

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Xin Zhou and Marat F. Khairoutdinov

Abstract

Subdaily temperature and precipitation extremes in response to warmer SSTs are investigated on a global scale using the superparameterized (SP) Community Atmosphere Model (CAM), in which a cloud-resolving model is embedded in each CAM grid column to simulate convection explicitly. Two 10-yr simulations have been performed using present climatological sea surface temperature (SST) and perturbed SST climatology derived from the representative concentration pathway 8.5 (RCP8.5) scenario. Compared with the conventional CAM, SP-CAM simulates colder temperatures and more realistic intensity distribution of precipitation, especially for heavy precipitation. The temperature and precipitation extremes have been defined by the 99th percentile of the 3-hourly data. For temperature, the changes in the warm and cold extremes are generally consistent between CAM and SP-CAM, with larger changes in warm extremes at low latitudes and larger changes in cold extremes at mid-to-high latitudes. For precipitation, CAM predicts a uniform increase of frequency of precipitation extremes regardless of the rain rate, while SP-CAM predicts a monotonic increase of frequency with increasing rain rate and larger change of intensity for heavier precipitation. The changes in 3-hourly and daily temperature extremes are found to be similar; however, the 3-hourly precipitation extremes have a significantly larger change than daily extremes. The Clausius–Clapeyron scaling is found to be a relatively good predictor of zonally averaged changes in precipitation extremes over midlatitudes but not as good over the tropics and subtropics. The changes in precipitable water and large-scale vertical velocity are equally important to explain the changes in precipitation extremes.

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Diego A. Alfaro and Marat Khairoutdinov

Abstract

This study examines how environmental thermodynamics constrain the morphology of simulated idealized midlatitude squall lines (SLs). The thermodynamic soundings used for simulating various SLs are specified primarily by prescribed vertical profiles of the convective available potential energy (CAPE) and the level of free convection. This framework, which contemplates the latent instability properties of both low- and midtropospheric air, is considered to be convenient for investigating layer-lifting convective phenomena.

Results show that frequently used CAPE indices are unsuitable for diagnosing SL characteristics, while integrated CAPE (ICAPE) discriminates the amplitude of the storm-induced heating for a given value of environmental shear. The skill of ICAPE follows from its relation to the buoyancy attained by low- and midtropospheric parcels as they ascend over the cold pool under layer-lifting convection. Environmental kinematics also affect the storm-induced heating, with stronger low-level shear leading to a greater proportion of inflowing latent unstable air among total storm-relative inflow, thus producing higher temperatures aloft. The precipitable water accounts for much of the precipitation-rate variation for a given value of shear. The precipitation efficiency is lower in environments with weaker shear and dryer midtropospheric conditions.

Cold pool temperatures are slightly affected by environmental variations beneath the layer of minimum moist static energy, with drier midtropospheric conditions and weaker shear leading to warmer cold pools. SLs with a small vertical gradient of cold pool buoyancy propagate less rapidly and produce small surface wind speeds. Cold pool properties could be affected by a descending branch of the front-to-rear flow, which crosses over with the rear inflow jet.

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Marat F. Khairoutdinov and Kerry Emanuel

Abstract

Recent studies have suggested that the Madden–Julian oscillation is a result of an instability driven mainly by cloud–radiation feedbacks, similar in character to self-aggregation of convection in nonrotating, cloud-permitting simulations of radiative–convective equilibrium (RCE). Here we bolster that inference by simulating radiative–convective equilibrium states on a rotating sphere with constant sea surface temperature, using the cloud-permitting System for Atmospheric Modeling (SAM) with 20-km grid spacing and extending to walls at 46° latitude in each hemisphere. Mechanism-denial experiments reveal that cloud–radiation interaction is the quintessential driving mechanism of the simulated MJO-like disturbances, but wind-induced surface heat exchange (WISHE) feedbacks are the primary driver of its eastward propagation. WISHE may also explain the faster Kelvin-like modes in the simulations. These conclusions are supported by a linear stability analysis of RCE states on an equatorial beta plane.

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Marat F. Khairoutdinov and David A. Randall

Abstract

A three-dimensional cloud-resolving simulation of midlatitude continental convection during the Atmospheric Radiation Measurement (ARM) program summer 1997 intensive observation period (IOP) is used to study the similarity of several second and third statistical moments, and second-moment budgets among five episodes of deep convection. Several parameter scales relevant to deep convection similarity are introduced. The dimensionless vertical profiles of the vertical velocity variance and its third moment, cumulus kinetic energy, the prognostic variables' variances and fluxes, their budgets, as well as several triple correlations cluster together, confirming the dynamical similarity of the simulated convective events.

The dimensionless budgets of several second-order moments, such as convective kinetic energy (CKE), its vertical and horizontal components, variance, and vertical fluxes of the prognostic thermodynamic variables, as well as the momentum flux, are also presented. The most interesting aspect of the simulated CKE budget is that, in contrast to the boundary layer and shallow trade wind cumulus convection, the dissipation term is relatively small compared to the dominant buoyancy production, transport, and pressure correlation terms. The prognostic equation for the bulk CKE, defined as the vertically integrated mean CKE per unit area, is also discussed. It is found that the so-called bulk CKE dissipation timescale ranges in the simulation from 4 to 8 h. Therefore, the bulk CKE, mostly contained in the horizontal branches of mesoscale circulations associated with the deep convective systems, can persist much longer than the lifetime of an individual convective cloud. It is also found that the fraction of the bulk CKE associated with the vertical motions is about the same for all of the events considered, suggesting a strong correlation between the bulk CKE and the strength of the convective updrafts. It is shown that the bulk CKE dissipation timescale is inversely proportional to the square root of the bulk CKE itself. It is also found that the convective velocity scale is closely related to the convective available potential energy (CAPE) of the thermodynamic sounding taken immediately before a particular convective event.

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Marat F. Khairoutdinov and Yefim L. Kogan

Abstract

A new dynamical framework for the Cooperative Institute for Mesoscale Meteorological Studies large eddy simulation model (CIMMS LES) with an explicit microphysics scheme is developed. It is shown that simulation results are very sensitive to the drop spectrum remapping technique used in condensation calculations; however, the results are almost insensitive to doubling of the spectrum resolution used in the CIMMS LES model. It is also shown that the drop coagulation procedure conserves the liquid water content as long as the predominant radius of the drop size spectrum, defined as the cube root of the ratio of the drop radar reflectivity to the liquid water content, is below a threshold value of 250 μm. Finally, it is demonstrated that for typical maritime conditions this threshold radius is exceeded only in 0.1% of all cloudy points.

Realism of the model is evaluated by a direct comparison of its predictions with the aircraft observations of a stratocumulus-topped boundary layer. The first simulation is based on the U.K. Meteorological Research Flight flight 526 measurements collected over the North Sea on 22 July 1982; the second simulation corresponds to the Atlantic Stratocumulus Transition Experiment flight A209 on 12–13 June 1992. The model is able to reproduce reasonably well most of the observed boundary layer parameters, including turbulent fluxes and variances of various fields, the intensity and vertical distribution of the turbulent kinetic energy, the upward and downward radiative fluxes, and the cloud drop spectra. It is speculated that the most noticeable discrepancy, which is an underestimation of the concentration of drops smaller than 6 μm near the cloud top, may be an indicator of the need to refine theoretical formulation of small-scale turbulent mixing.

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Marat F. Khairoutdinov and David A. Randall

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 that the uncertainty of the simulated precipitable water due to the fundamental uncertainty of the initial conditions can be as large as 25% of the mean values. Even though the precipitation rates averaged over the whole simulation period were virtually identical among the ensemble members, the timing uncertainty of the onset and reaching the precipitation maximum can be as long as one full day. Despite the predictability limitations, the mean simulation statistics are found to be almost insensitive to the uncertainty of the initial conditions.

The overall effects of the third spatial dimension are found to be minor for simulated mean fields and scalar fluxes but are quite considerable for velocity and scalar variances. Neither changes in a rather wide range of the domain size nor the horizontal grid resolution have any significant impact on the simulations. Although a rather strong sensitivity of the mean hydrometeor profiles and, consequently, cloud fraction to the microphysics parameters is found, the effects on the predicted mean temperature and humidity profiles are shown to be modest. It is found that the spread among the time series of the simulated cloud fraction, precipitable water, and surface precipitation rate due to changes in the microphysics parameters is within the uncertainty of the ensemble runs. This suggests that correlation of the CRM simulations to the observed long time series of the aforementioned parameters cannot be generally used to validate the microphysics scheme.

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Marat Khairoutdinov, Charlotte DeMott, and David Randall

Abstract

The Colorado State University (CSU) Multiscale Modeling Framework (MMF) is a new type of general circulation model (GCM) that replaces the conventional parameterizations of convection, clouds, and boundary layer with a cloud-resolving model (CRM) embedded into each grid column. The MMF has been used to perform a 19-yr-long Atmospheric Model Intercomparison Project–style simulation using the 1985–2004 sea surface temperature (SST) and sea ice distributions as prescribed boundary conditions. Particular focus has been given to the simulation of the interannual and subseasonal variability.

The annual mean climatology is generally well simulated. Prominent biases include excessive precipitation associated with the Indian and Asian monsoon seasons, precipitation deficits west of the Maritime Continent and over Amazonia, shortwave cloud effect biases west of the subtropical continents due to insufficient stratocumulus clouds, and longwave cloud effect biases due to overestimation of high cloud amounts, especially in the tropics. The geographical pattern of the seasonal cycle of precipitation is well reproduced, although the seasonal variance is considerably overestimated mostly because of the excessive monsoon precipitation mentioned above. The MMF does a good job of reproducing the interannual variability in terms of the spatial structure and magnitude of major anomalies associated with El Niño–Southern Oscillation (ENSO).

The subseasonal variability of tropical climate associated with the Madden–Julian oscillation (MJO) and equatorially trapped waves are particular strengths of the simulation. The wavenumber–frequency power spectra of the simulated outgoing longwave radiation (OLR), precipitation rate, and zonal wind at 200 and 850 mb for time scales in the range of 2–96 days compare very well to the spectra derived from observations, and show a robust MJO and Kelvin and Rossby waves with phase speeds similar to those observed. The geographical patterns of the MJO and Kelvin wave–filtered OLR variance for summer and winter seasons are well simulated; however, the variances tend to be overestimated by as much as 50%. The observed seasonal and interannual variations of the strength of the MJO are also well reproduced.

The physical realism of the simulated marine stratocumulus clouds is demonstrated by an analysis of the composite diurnal cycle of cloud water content, longwave (IR) cooling, vertical velocity variance, rainfall, and subcloud vertical velocity skewness. The relationships between vertical velocity variance, IR cooling, and negative skewness all suggest that, despite the coarse numerical grid of the CRM, the simulated clouds behave in a manner consistent with the understanding of the stratocumulus dynamics. In the stratocumulus-to-cumulus transition zone, the diurnal cycle of the inversion layer as simulated by the MMF also bears a remarkable resemblance to in situ observations. It is demonstrated that in spite of the coarse spacing of the CRM grid used in the current version of MMF, the bulk of vertical transport of water in the MMF is carried out by the circulations explicitly represented on the CRM grid rather than by the CRM’s subgrid-scale parameterization.

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Marat Khairoutdinov, David Randall, and Charlotte DeMott

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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-of-the-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).

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