Multi-scale Organization of Convection in a Global Numerical Simulation of the December 2006 MJO Event Using Explicit Moist Processes

Nasuno, Tomoe; Miura, Hiroaki; Satoh, Masaki; Noda, Akira; Oouchi, Kazuyoshi

doi:10.2151/jmsj.87.335

Cited by 35 publications

(30 citation statements)

References 33 publications

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“…Figure 7 shows the time-longitude cross-section from December 16, 2006, to January 16, 2007, which corresponds to MJO phases P2 through P6, because the experiment was conducted at the onset of MJO convection over the Indian Ocean. In the observations and numerical simulation, significant convective clouds of MJO passed through the island of Sumatra around January 1-2, 2007, (Miura et al 2007;Nasuno et al 2009). Liu et al (2009) determined the MJO characteristics using the same NICAM output.…”

Section: Simulated Diurnal Variation By Nicammentioning

confidence: 99%

Diurnal Convection Peaks over the Eastern Indian Ocean off Sumatra during Different MJO Phases

Fujita

Yoneyama

Mori

et al. 2011

Journal of the Meteorological Society of Japan

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The authors investigated diurnal convection peak characteristics over the eastern Indian Ocean o¤ the island of Sumatra during di¤erent phases of the Madden-Julian oscillation (MJO). During MJO phases 2 to 3 (P2 and P3) defined by Wheeler and Hendon (2004), prominent diurnal variation in convection was observed by satellites when moderate low-level westerly winds were dominant over the eastern Indian Ocean. The diurnal convection peaks were prominent over the island of Sumatra in the evening, while migrations of the convection toward the Indian Ocean were observed in the early morning. By using the Global Positioning System around the western region o¤shore of Sumatra, a significant reduction in water vapor was observed from evening until midnight, compensating for the upward motion over the island. During midnight to early morning, the water vapor increased in the western o¤shore region as the convections migrated from the island. This prominent diurnal variation confirmed the result from a numerical experiment by Miura et al. (2007) using the Nonhydrostatic ICosahedral Atmospheric Model (NICAM).During P2 to P3, the atmosphere over the eastern Indian Ocean contains abundant water vapor, while the Maritime Continent is fairly well heated by solar radiation under calm conditions. This situation should be favorable for the development of two diurnal convection peaks: the evening convection over the land induced by solar radiative heating and the midnight convection over the ocean triggered by convergence of the low-level westerly wind and the land breeze.

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Section: Simulated Diurnal Variation By Nicammentioning

confidence: 99%

Diurnal Convection Peaks over the Eastern Indian Ocean off Sumatra during Different MJO Phases

Fujita

Yoneyama

Mori

et al. 2011

Journal of the Meteorological Society of Japan

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“…Using the 7 km grid mesh NICAM, Miura et al [2007] reproduced the realistic structure of an MJO event that occurred during December 2006. They also integrated a 3.5 km grid mesh NICAM globally for a week with an initial condition from the National Centers for Environmental Prediction (NCEP) Global Tropospheric Analyses at 0000 UTC on 25 December 2006 [Nasuno et al, 2009]. Some aspects of deep convective clouds in this NICAM experiment have already been analyzed by Inoue et al [2008] and Masunaga et al [2008].…”

Section: Global Cloud-resolving Modelmentioning

confidence: 99%

Comparison of high‐level clouds represented in a global cloud system–resolving model with CALIPSO/CloudSat and geostationary satellite observations

Inoue¹,

Satoh²,

Hagihara³

et al. 2010

J. Geophys. Res.

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[1] Vertical and horizontal distributions of high-level clouds (ice and snow) simulated in high-resolution global cloud system-resolving simulations by the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) are compared with satellite observations. Ice and snow data in a 1 week experiment by the NICAM 3.5 km grid mesh global simulation initiated at 0000 UTC 25 December 2006 are used in this study. The vertical structure of ice and snow represented by NICAM was compared with Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and CloudSat observations. High-level clouds (cumulonimbus and cirrus type clouds) classified by the split window (11 and 12 mm) data on board geostationary meteorological satellites (GMSs) were used for comparison of the horizontal distributions of ice and snow in NICAM. The vertical distributions of ice and snow simulated by NICAM qualitatively agree well with those of cloud signals observed by CALIPSO and CloudSat. We computed corresponding cloud lidar backscatter coefficients and cloud radar reflectivity signals from ice and snow data of NICAM using Cloud Feedback Model Intercomparison Project (CFMIP) observational simulator packages. The contoured frequency by altitude diagram for the cloud lidar backscatter coefficients shows lower frequency at higher altitude of 8-14 km by NICAM than CALIOP observations. This suggests that the amount of ice is not well represented in NICAM. The simulated cloud radar reflectivity signals by NICAM indicated higher frequency at 8-10 km altitude than CloudSat observations, although there were some differences between over oceans and continents. This implies that the amount of snow is larger in NICAM simulations. The horizontal pattern of ice clouds (column-integrated ice and snow of greater than 0.01 kg/m 2 ) in NICAM shows good agreement with that of high-level clouds identified by the split window analysis. During this 1 week simulation, 48-59% of ice clouds in NICAM matches with observed high-level clouds. The cross correlation between the spatial distributions of simulated ice clouds and satellite-observed high-level clouds is 0.40-0.51, and the equitable threat score is 0.31-0.45. Furthermore, temporal variations of column-integrated ice clouds in NICAM are compared with high-level clouds classified by the split window at the decaying stage of deep convection over the tropics. The results indicate that the mean decaying speed of ice clouds of NICAM and high-level clouds by satellite observations agrees well for this analysis area and period, although the variances are larger in NICAM. This implies that the fall speed of snow in this NICAM experiment is appropriate to depict the decay of anvil clouds by compensating for the excess of snow in NICAM simulations, when we assume that the decay of anvil clouds is largely controlled by the evaporation of ice and snow.

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“…However, the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) has produced fairly realistic simulations of a few MJO cases in terms of cloud, precipitation, and zonal wind using a global model with explicit convection at grid spacings of 14, 7, and 3.5 km (Miura et al 2007;Nasuno et al 2009;Liu et al 2009;Oouchi et al 2009;Taniguchi et al 2010;Miyakawa et al 2012). Another approach has been the multiscale modeling framework (MMF, or superparameterization) in which a GCM with a coarse large-scale grid uses 2D cloud-system resolving models (CSRMs) embedded in each grid cell to explicitly simulate local convection based on the large-scale prognostic variables and then outputs the large-scale mean properties back to the coarse grid (Grabowski and Smolarkiewicz 1999;Khairoutdinov and Randall 2001).…”

Section: Introductionmentioning

confidence: 99%

The Effects of Explicit versus Parameterized Convection on the MJO in a Large-Domain High-Resolution Tropical Case Study. Part I: Characterization of Large-Scale Organization and Propagation*

Holloway

Woolnough

Lister

2013

Journal of the Atmospheric Sciences

100

114

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High-resolution simulations over a large tropical domain (;208S-208N, 428E-1808) using both explicit and parameterized convection are analyzed and compared to observations during a 10-day case study of an active Madden-Julian oscillation (MJO) event. The parameterized convection model simulations at both 40-and 12-km grid spacing have a very weak MJO signal and little eastward propagation. A 4-km explicit convection simulation using Smagorinsky subgrid mixing in the vertical and horizontal dimensions exhibits the best MJO strength and propagation speed. Explicit convection simulations at 12 km also perform much better than the 12-km parameterized convection run, suggesting that the convection scheme, rather than horizontal resolution, is key for these MJO simulations. Interestingly, a 4-km explicit convection simulation using the conventional boundary layer scheme for vertical subgrid mixing (but still using Smagorinsky horizontal mixing) completely loses the large-scale MJO organization, showing that relatively high resolution with explicit convection does not guarantee a good MJO simulation. Models with a good MJO representation have a more realistic relationship between lower-free-tropospheric moisture and precipitation, supporting the idea that the moisture-convection feedback is a key process for MJO propagation. There is also increased generation of available potential energy and conversion of that energy into kinetic energy in models with a more realistic MJO, which is related to larger zonal variance in convective heating and vertical velocity, larger zonal temperature variance around 200 hPa, and larger correlations between temperature and ascent (and between temperature and diabatic heating) between 500 and 400 hPa.

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Multi-scale Organization of Convection in a Global Numerical Simulation of the December 2006 MJO Event Using Explicit Moist Processes

Cited by 35 publications

References 33 publications

Diurnal Convection Peaks over the Eastern Indian Ocean off Sumatra during Different MJO Phases

Diurnal Convection Peaks over the Eastern Indian Ocean off Sumatra during Different MJO Phases

Comparison of high‐level clouds represented in a global cloud system–resolving model with CALIPSO/CloudSat and geostationary satellite observations

The Effects of Explicit versus Parameterized Convection on the MJO in a Large-Domain High-Resolution Tropical Case Study. Part I: Characterization of Large-Scale Organization and Propagation*

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