High-resolution Multiscale Modeling Framework Simulation Of Low . - NASA
High-resolution Multiscale Modeling FrameworkSimulation of Low CloudsKuan-Man Xu1 and Anning Cheng21. NASA Langley Research Center, Hampton, VA2. Science Systems and Applications, Inc., Hampton, VA
Multiscale Modeling Framework(Grabowski 2001; Khairoutdinov and Randall 2001) A CRM is embedded at each gridcolumn ( 100s km) of the host GCM torepresent cloud physical processes The CRM explicitly simulates cloudscale dynamics ( 1s km) andprocesses Periodic lateral boundary condition forCRM (not extend to the edges)Upgraded CRM with a third-order turbulence closure (IPHOC):G(qt) Double-Gaussian distribution of liquid-water potential temperature, total water mixingratio and vertical velocity Skewnesses, i.e., the three third-order moments, predicted All first-, second-, third- and fourth-order moments, subgrid-scale condensation andbuoyancy based on the same PDFqsqt
Objectives for MMF climate simulation to improve the simulation of low-level clouds in an MMF to evaluate and compare the performance of model simulationsagainst state-of-the-art observationsModels and observational data Standard SPCAM, at T21 resolution, 2-yr run (semi-Lagrangian) Upgraded SPCAM, called SPCAM-IPHOC, at T21 resolution (withsemi-Lagrangian dynamic core); 2-yr run SPCAM-IPHOC-hires: SPCAM-IPHOC with finite-volume dynamiccore (1.9 x2.5 ); doubling the number of levels below 700 hPa (6to 12); 10-yr run C3M (CloudSat, CALIPSO, CERES, MODIS) observations.
Highlights of results Improved low cloud simulation from the upgraded CRM and thehigher-resolution finite-volume dynamic core-based SPCAM-IPHOCmodel, compared to the standard SPCAM and the lower-resolutionSPCAM-IPHOC with semi-Lagrangian dynamic core, respectively Improved surface precipitation distributions, esp., in the tropics Radiative energy balance, compared to CERES observations Overall performance from the higher-resolution SPCAM-IPHOC isbetter than SPCAM and SPCAM-IPHOCCheng, A. and K.-M. Xu, 2011: Improved low-cloud simulation from a multiscalemodeling framework with a third-order turbulence closure in its cloud-resolving modelcomponent. J. Geophys. Res., 116, D14101, doi:10.1029/2010JD015362.Xu, K.-M., and A. Cheng, 2011: Further improvement of low-cloud simulation from amultiscale modeling framework with a third-order turbulence closure in its cloudresolving model component (in preparation).
Off-line sensitivity test to vertical resolutionATEX CumulusASTEX Stratocumulus
Low-level (sfc - 700 hPa) cloud amount (%)
Annual mean cloud fraction (color) and cloud liquid water(contour) west of South America (15 S)
Annual-mean surface precipitation rate
Summer precipitation in China
Oceanic surface latent heat flux
TOA albedo
TOA outgoing LW flux
Shortwave cloud radiative effect
LW cloud radiative effect
TOA and surface energy MIPHOC-hires240.10240.070.03SW-sfc LW-sfcLHSHImbalanceSPCAMIPHOC161.34 55.16 81.65 23.03-1.50SPCAMIPHOC-hires161.47 57.21 88.97 23.067.77
Summary of results: the Taylor diagram
Summary of results: the Taylor diagram
Summary of results: the Taylor diagram
Summary of results: the Taylor diagram
Summary of results: the Taylor diagram
Summary and conclusions Both upgraded SPCAM-IPHOC simulations showimproved representation of the global distributions of low-level clouds the amounts of low-level clouds in the subtropics surface precipitation (for higher-resolution one) The comparison against C3M observations showsfurther improved results in the higher-resolutionMMF, for example, near-coast thin stratus cloudsand deep convection in the tropics The TOA radiative energy balance is nearly perfectin the higher-resolution simulation There are rooms for further improvements
Summary of results: the Taylor diagramSPCAM-IPHOC vs. SPCAMSignificant improvementLow-level cloudSW CRFLW CRFSmall/no improvmentSurface pressureMiddle-level cloudHigh-level cloudSurface precipitationLatent heat fluxDegradedSurface sensible flux
Summary of results: the Taylor diagramSPCAM-IPHOC-hires vs. SPCAM-IPHOCSignificant improvementSurface pressureSurface precipitationMid-level cloudHigh-level cloudLatent heat fluxSW CRFSmall/no improvementLow-level cloudLW CRFSensible heat flux
A CRM is embedded at each grid column ( 100s km) of the host GCM to . A. and K.-M. Xu, 2011: Improved low-cloud simulation from a multiscale modeling framework with a third-order turbulence closure in its cloud-resolving model . Off-line sensitivity test to vertical resolution ATEX Cumulus ASTEX Stratocumulus . Low-level (sfc - 700 hPa .
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