Papers by Marat Khairoutdinov
Journal of Climate, 2015
An analysis of a 5-yr (from 1 January 2009 to 31 December 2013) free run of the superparameterize... more An analysis of a 5-yr (from 1 January 2009 to 31 December 2013) free run of the superparameterized (SP) Climate Forecast System (CFS) version 2 (CFSv2) (SP-CFS), implemented for the first time at a spectral triangular truncation at wavenumber 62 (T62) atmospheric horizontal resolution, is presented. The SP-CFS simulations are evaluated against observations and traditional convection parameterized CFSv2 simulations at T62 resolution as well as at some higher resolutions. The metrics for evaluating the model performance are chosen in order to mainly address the improvement in systematic biases observed in the CFSv2 documented in earlier studies. While the primary focus of this work is on evaluating the improvement of the simulation of the Indian summer monsoon (ISM) by the SP-CFS model, some results are also presented within the context of the global climate. The SP-CFS significantly reduces the dry bias of precipitation over the Indian subcontinent and better captures the monsoon int...
Journal of the Atmospheric Sciences, 2005
Traditionally, the effects of clouds in GCMs have been represented by semiempirical parameterizat... more 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 wit...
Journal of Advances in Modeling Earth Systems
Systematic biases in the representation of boundary layer (BL) clouds are a leading source of unc... more Systematic biases in the representation of boundary layer (BL) clouds are a leading source of uncertainty in climate projections. A variation on superparameterization (SP) called ''ultraparameterization'' (UP) is developed, in which the grid spacing of the cloud-resolving models (CRMs) is fine enough (250 3 20 m) to explicitly capture the BL turbulence, associated clouds, and entrainment in a global climate model capable of multiyear simulations. UP is implemented within the Community Atmosphere Model using 28 resolution (14,000 embedded CRMs) with one-moment microphysics. By using a small domain and mean-state acceleration, UP is computationally feasible today and promising for exascale computers. Short-duration global UP hindcasts are compared with SP and satellite observations of top-of-atmosphere radiation and cloud vertical structure. The most encouraging improvement is a deeper BL and more realistic vertical structure of subtropical stratocumulus (Sc) clouds, due to stronger vertical eddy motions that promote entrainment. Results from 90 day integrations show climatological errors that are competitive with SP, with a significant improvement in the diurnal cycle of offshore Sc liquid water. Ongoing concerns with the current UP implementation include a dim bias for near-coastal Sc that also occurs less prominently in SP and a bright bias over tropical continental deep convection zones. Nevertheless, UP makes global eddy-permitting simulation a feasible and interesting alternative to conventionally parameterized GCMs or SP-GCMs with turbulence parameterizations for studying BL cloud-climate and cloud-aerosol feedback.
Journal of Advances in Modeling Earth Systems
The intrinsic small spatial scales and low reflectivity structure of oceanic warm precipitating c... more The intrinsic small spatial scales and low reflectivity structure of oceanic warm precipitating clouds suggest that millimeter spaceborne radars are best suited to provide quantitative estimates of cloud and rain liquid water path (LWP). This assertion is based on their smaller horizontal footprint, high sensitivities, and a wide dynamic range of path integrated attenuations associated to warm rain cells across the millimeter wavelength spectrum, with diverse spectral responses to rain and cloud partitioning. State-of-the-art single-frequency radar profiling algorithms of warm rain seem to be inadequate because of their dependence on uncertain assumptions on the rain/cloud partitioning and of the rain microphysics. Here, high resolution cloud resolving model simulations for the Rain in Cumulus over the Ocean field study and a spaceborne forward radar simulator are exploited to assess the potential of existing and future spaceborne radar system for quantitative warm rain microphysical retrievals. Specifically, the detrimental effects of non-uniform beam filling on path integrated attenuation (PIA) estimates, the added value of brightness temperatures (T B s) derived adopting radiometric radar modes, and the performances of multi-frequency PIA and/or T B combinations when retrieving liquid water path partitioning into cloud (c-LWP) and rain (r-LWP) are assessed. Results show that 1) Ka and W-band T B s add useful constraints and are effective at lower LWPs than the same frequency PIAs; 2) matched-beam combined T B s and PIAs from single/multi-frequency radars can significantly narrow down uncertainties in retrieved cloud and rain liquid water paths; 3) the configuration including PIAs, T B s and near surface reflectivities for the Ka-W band pairs in our synthetic retrieval can achieve rmse better than 30% for c-LWPs and r-LWPs exceeding 100 g/m 2. 1 Introduction Warm rain is precipitation that originates from non ice-phase processes usually in clouds whose tops lie below the atmospheric freezing level. Warm rain is the dominant mechanism for precipitation formation over the tropical oceans outside the Inter Tropical Convergence Zone, accounting for slightly more than 30% of the total rain amount and 70% of the total rain area in 1
<p>... more <p>The global version of the cloud-resolving System for Atmospheric Modeling (SAM) is used to simulate the global evolution of clouds and precipitation during the SOCRATES field campaign In Feb 2018 with particular focus on the Southern Ocean storm track region. The model has nonuniform horizontal resolution, which ranges from 4-km horizontal grid spacing over the Tropics up to 2-3 km isotropic grid-spacing over mid-latitudes. It includes a realistic topography and comprehensive land-surface model. The sea-surface temperature and sea ice are prescribed from observations. The results of two types of simulations are presented, weather-forecasting and observed-weather-nudged over 24-hour time scale; for the latter, hourly ERA5 reanalysis dataset is used. The cloud properties are compared to the SOCRATES observations. The sensitivity of the results to the choice of cloud microphysics, from simple single-moment to double-moment, is also discussed.</p>
Progress in Earth and Planetary Science
A review of the experimental protocol and motivation for DYAMOND, the first intercomparison proje... more A review of the experimental protocol and motivation for DYAMOND, the first intercomparison project of global storm-resolving models, is presented. Nine models submitted simulation output for a 40-day (1 August–10 September 2016) intercomparison period. Eight of these employed a tiling of the sphere that was uniformly less than 5 km. By resolving the transient dynamics of convective storms in the tropics, global storm-resolving models remove the need to parameterize tropical deep convection, providing a fundamentally more sound representation of the climate system and a more natural link to commensurately high-resolution data from satellite-borne sensors. The models and some basic characteristics of their output are described in more detail, as is the availability and planned use of this output for future scientific study. Tropically and zonally averaged energy budgets, precipitable water distributions, and precipitation from the model ensemble are evaluated, as is their representat...
Current Climate Change Reports
Purpose of Review Global cloud-resolving models (GCRMs) are a new type of atmospheric model which... more Purpose of Review Global cloud-resolving models (GCRMs) are a new type of atmospheric model which resolve nonhydrostatic accelerations globally with kilometer-scale resolution. This review explains what distinguishes GCRMs from other types of models, the problems they solve, and the questions their more commonplace use is raising. Recent Findings GCRMs require high-resolution discretization over the sphere but can differ in many other respects. They are beginning to be used as a main stream research tool. The first GCRM intercomparison studies are being coordinated, raising new questions as to how best to exploit their advantages. Summary GCRMs are designed to resolve the multiscale nature of moist convection in the global dynamics context, without using cumulus parameterization. Clouds are simulated with cloud microphysical schemes in ways more comparable to observations. Because they do not suffer from ambiguity arising from cumulus parameterization, as computational resources increase, GCRMs are the promise of a new generation of global weather and climate simulations.
Journal of Advances in Modeling Earth Systems
This article has been accepted for publication and undergone full peer review but has not been th... more This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as
Aerosols influence clouds across a wide range of spatial scales, and clouds influence aerosols ac... more Aerosols influence clouds across a wide range of spatial scales, and clouds influence aerosols across those same scales. Nearly all previous attempts to simulate cloud-aerosol interactions have either neglected or relied on crude parameterizations of the interactions involving deep convective clouds and subgrid variability in stratiform clouds. To address this challenge, a cloud-resolving model that explicitly resolves aerosol effects on
This paper reports an intercomparison study of midlatitude continental cumulus convection simulat... more This paper reports an intercomparison study of midlatitude continental cumulus convection simulated by eight 2-D and two 3-D cloud resolving models (CRMs), driven by observed large-scale advective temperature and moisture tendencies, surface turbulent fluxes, and radiative heating profiles during three subperiods of the Summer 1997 Intensive Observation Period (IOP) of the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) program. Each subperiod includes two or three precipitation events of various intensities over a span of 4 or 5 days. The results can be summarized as follows. CRMs can reasonably simulate midlatitude continental summer convection observed at the ARM Cloud and Radiation Testbed (CART) site in terms of the intensity of convective activity, and the temperature and specific humidity evolution. Delayed occurrences of the initial precipitation events are a common feature for all three subcases among the models. Cloud mass fluxes, condensate mixing ratios and hydrometeor fractions produced by all CRMs are similar. Some of the simulated cloud properties such as cloud liquid water path and hydrometeor fraction are rather similar to available observations. All CRMs produce large downdraft mass fluxes with magnitudes similar to those of updrafts, in contrast with CRM results for tropical convection. Some intermodel differences in cloud properties are likely to be related to those in the parameterizations of microphysical processes. There is generally a good agreement between the CRMs and observations with CRMs being significantly better than single-column models (SCMs), suggesting that current results are suitable for use in improving parameterizations in SCMs. However, improvements can still be made in the CRM simulations; those include the proper initialization of the CRMs and a more proper method of diagnosing cloud boundaries in model outputs for comparison with satellite and cloud radar observations.
Global climate models tend to have a bias in the phase of the diurnal cycle of precipitation over... more Global climate models tend to have a bias in the phase of the diurnal cycle of precipitation over land producing bulk of convective precipitation around local noon, which is several hours earlier than the observed pick at about 15h local time or even later. In this study, the issue of diurnal cycle over land is addressed using the System for
Aaar 28th Annual Conference, Oct 26, 2009
Remote Sensing and Modeling of the Atmosphere, Oceans, and Interactions VI, 2016
Agu Fall Meeting Abstracts, Dec 1, 2009
Agu Fall Meeting Abstracts, Dec 1, 2008
The goal of the MMF (Multiscale Modeling Framework) is to improve the representation of cloud pro... more The goal of the MMF (Multiscale Modeling Framework) is to improve the representation of cloud processes in climate models by using a novel approach that embeds a cloud-resolving model in each grid column of a global climate model. The current version of the MMF used by CMMAP (Center for Multiscale Modeling Modeling of Atmospheric Processes) is composed of a 2D cloud-resolving model (a 2D version of SAM [System for Atmospheric Modeling, Khairoutdinov and Randall 2003]) that is embedded in the CAM (Community Atmospheric Model). The 2D SAM has a horizontal grid size of 4 km and a domain size of either 128 km or 256 km (32 or 64 columns). Currently, SAM in MMF (SAM-MMF) uses a simple diagnostic SGS (subgrid-scale) model for the turbulent fluxes, and assumes no SGS variability, so there is no SGS cloud fraction: a grid box is entirely clear or entirely cloudy. This clearly limits the MMF's ability to simulate shallow cumulus and stratocumulus clouds. This has been verified by comparing the MMF's cloud type frequencies with those from satellite observations. Several approaches have been suggested to improve SAM-MMF's representation of SGS clouds and turbulence. The approach we are exploring is the assumed-PDF (probability density function) method. In this approach, the general form of a joint PDF for the SGS fluctuations of vertical velocity, liquid water potential temperature and total water is assumed. The actual PDF is determined by several moments. The moments are estimated by prognostic and/or diagnostic moment equations. Larson et al. (2002) and Golaz et al. (2002a,b) described and tested a 1D cloudy boundary layer model based on the assumed-PDF approach that uses a double Gaussian joint PDF that requires six second moments (variances and covariances) and one third moment (the skewness of the vertical velocity fluctuations) for its specification. We are testing their approach for possible use in the MMF (and in any coarse-grid cloud-resovling model). Is their approach suitable for coarse-grid simulations of deep moist convection? Larson and Golaz developed and tested their approach for boundary layer clouds using large-eddy simulations with domain sizes of 6 km by 6 km. For deep moist convection, a much larger domain is necessary in order to simulate the mesoscale cloud clusters, while at the same time, the horizontal grid size must still be appropriate (about 100 m) for LES (large-eddy simulation), and the simulation must be 3D (Bryan et al. 2003). We used SAM to conduct a 12-h LES of deep moist convection using a large domain (204.8 km x 204.8 km x 25.6 km) and a 100-m grid size. This simulation is equivalent to 1024 6.4-km x 6.4-km LESs. We collected statistics during the simulation for calculating the moments needed to specify assumed PDFs for grid sizes of 800 m x 800 m x 100 m and multiples thereof. The statistics also include cloud fraction, liquid water mixing ratio, and its vertical flux, that can be compared to those obtained from the PDF. This approach was also used by Larson et al. (2002) to evaluate various assumed PDFs. The results from the comparisons described above will be used to select an optimum configuration of horizontal grid size and SGS model complexity for SAM-MMF, and will also demonstrate the capabilities of the assumed PDF method for horizontal grid sizes up to 200 km. class="ab'>
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Papers by Marat Khairoutdinov