Editorial Type:
Article
Article Type:
Research Article

Improvement of a Cloud Microphysics Scheme for a Global Nonhydrostatic Model Using TRMM and a Satellite Simulator

Woosub Roh Atmosphere and Ocean Research Institute, University of Tokyo, Tokyo, Japan

Search for other papers by Woosub Roh in
Current site
Google Scholar
PubMed Close
,
Masaki Satoh Atmosphere and Ocean Research Institute, University of Tokyo, Tokyo, and Japan Agency for Marine-Earth Science and Technology, Yokosuka, Japan

Search for other papers by Masaki Satoh in
Current site
Google Scholar
PubMed Close
, and
Tomoe Nasuno Japan Agency for Marine-Earth Science and Technology, Yokosuka, Japan

Search for other papers by Tomoe Nasuno in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Jan 2017
DOI:
https://doi.org/10.1175/JAS-D-16-0027.1
Page(s):
167–184
Restricted access

Abstract

The cloud and precipitation simulated by a global nonhydrostatic model with a 3.5-km horizontal resolution, the Nonhydrostatic Icosahedral Atmospheric Model (NICAM), are evaluated using the Tropical Rainfall Measuring Mission (TRMM) and a satellite simulator. A previous study by Roh and Satoh evaluated the single-moment bulk microphysics and established the modified microphysics scheme for the specific tropical open ocean using a regional version of NICAM. In this study, the authors expanded the evaluation over the entire tropics and parts of the midlatitude areas (20°–36°S, 20°–36°N) using a joint histogram of the cloud-top temperature and precipitation echo-top heights and contoured frequency by altitude diagrams of the deep convective systems. The modified microphysics simulation improves the joint probability density functions of the cloud-top temperatures and precipitation cloud-top heights over not only the tropical ocean but also the land and midlatitude areas. Compared with the default microphysics simulation, the modified microphysics simulation shows a clearer distinction between the land and ocean in the tropics, which is related to the contrast between the shallow and the deep clouds. In addition, the two microphysics simulation methods were also compared over the tropics using joint histograms of the cloud-top and precipitation cloud-top heights on the basis of CloudSat measurements. It was found that the microphysics scheme that was modified for the tropical ocean displayed general cloud and precipitation improvements in the global domain over the tropics.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Denotes content that is immediately available upon publication as open access.

Corresponding author address: Woosub Roh, Atmosphere and Ocean Research Institute, University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa-shi, Chiba 277-8568, Japan. E-mail: ws-roh@aori.u-tokyo.ac.jp

Abstract

The cloud and precipitation simulated by a global nonhydrostatic model with a 3.5-km horizontal resolution, the Nonhydrostatic Icosahedral Atmospheric Model (NICAM), are evaluated using the Tropical Rainfall Measuring Mission (TRMM) and a satellite simulator. A previous study by Roh and Satoh evaluated the single-moment bulk microphysics and established the modified microphysics scheme for the specific tropical open ocean using a regional version of NICAM. In this study, the authors expanded the evaluation over the entire tropics and parts of the midlatitude areas (20°–36°S, 20°–36°N) using a joint histogram of the cloud-top temperature and precipitation echo-top heights and contoured frequency by altitude diagrams of the deep convective systems. The modified microphysics simulation improves the joint probability density functions of the cloud-top temperatures and precipitation cloud-top heights over not only the tropical ocean but also the land and midlatitude areas. Compared with the default microphysics simulation, the modified microphysics simulation shows a clearer distinction between the land and ocean in the tropics, which is related to the contrast between the shallow and the deep clouds. In addition, the two microphysics simulation methods were also compared over the tropics using joint histograms of the cloud-top and precipitation cloud-top heights on the basis of CloudSat measurements. It was found that the microphysics scheme that was modified for the tropical ocean displayed general cloud and precipitation improvements in the global domain over the tropics.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Denotes content that is immediately available upon publication as open access.

Corresponding author address: Woosub Roh, Atmosphere and Ocean Research Institute, University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa-shi, Chiba 277-8568, Japan. E-mail: ws-roh@aori.u-tokyo.ac.jp
Save
Cover Journal of the Atmospheric Sciences
Journal of the Atmospheric Sciences

  • Bodas-Salcedo, A., and Coauthors, 2011: COSP satellite simulation software for model assessment. Bull. Amer. Meteor. Soc., 92, 1023–1043, doi:10.1175/2011BAMS2856.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Fabry, F., and W. Szyrmer, 1999: Modeling of the melting layer. Part II: Electromagnetic. J. Atmos. Sci., 56, 3593–3600, doi:10.1175/1520-0469(1999)056<3593:MOTMLP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Field, P. R., R. J. Hogan, P. R. A. Brown, A. J. Illingworth, T. W. Choularton, and R. J. Cotton, 2005: Parametrization of ice-particle size distributions for mid-latitude stratiform cloud. Quart. J. Roy. Meteor. Soc., 131, 1997–2017, doi:10.1256/qj.04.134.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Gilmore, M. S., J. M. Straka, and E. N. Rasmussen, 2004: Precipitation uncertainty due to variations in precipitation particle parameters within a simple microphysics scheme. Mon. Wea. Rev., 132, 2610–2627, doi:10.1175/MWR2810.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Grabowski, W. W., 1998: Toward cloud resolving modeling of large-scale tropical circulations: A simple cloud microphysics parameterization. J. Atmos. Sci., 55, 3283–3298, doi:10.1175/1520-0469(1998)055<3283:TCRMOL>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hagihara, Y., H. Okamoto, and R. Yoshida, 2010: Development of a combined CloudSat-CALIPSO cloud mask to show global cloud distribution. J. Geophys. Res., 115, D00H33, doi:10.1029/2009JD012344.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hashino, T., M. Satoh, Y. Hagihara, T. Kubota, T. Matsui, T. Nasuno, and H. Okamoto, 2013: Evaluating cloud microphysics from NICAM against CloudSat and CALIPSO. J. Geophys. Res. Atmos., 118, 7273–7292, doi:10.1002/jgrd.50564.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Heymsfield, A. J., and L. J. Donner, 1990: A scheme for parameterizing ice-cloud water content in general circulation models. J. Atmos. Sci., 47, 1865–1877, doi:10.1175/1520-0469(1990)047<1865:ASFPIC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hong, S.-Y., J. Dudhia, and S.-H. Chen, 2004: A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon. Wea. Rev., 132, 103–120, doi:10.1175/1520-0493(2004)132<0103:ARATIM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Iga, S. I., H. Tomita, Y. Tsushima, and M. Satoh, 2011: Sensitivity of Hadley circulation to physical parameters and resolution through changing upper-tropospheric ice clouds using a global cloud-system resolving model. J. Climate, 24, 2666–2679, doi:10.1175/2010JCLI3472.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Inoue, T., M. Satoh, Y. Hagihara, H. Miura, and J. Schmetz, 2010: Comparison of high-level clouds represented in a global cloud system–resolving model with CALIPSO/CloudSat and geostationary satellite observations. J. Geophys. Res., 115, D00H22, doi:10.1029/2009JD012371.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Janowiak, J. E., R. J. Joyce, and Y. Yarosh, 2001: A real-time global half-hourly pixel-resolution infrared dataset and its applications. Bull. Amer. Meteor. Soc., 82, 205–217, doi:10.1175/1520-0477(2001)082<0205:ARTGHH>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kodama, C., A. T. Noda, and M. Satoh, 2012: An assessment of the cloud signals simulated by NICAM using ISCCP, CALIPSO, and CloudSat satellite simulators. J. Geophys. Res., 117, D12210, doi:10.1029/2011JD017317.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Lang, S. E., W.-K. Tao, R. Cifelli, W. Olson, J. Halverson, S. Rutledge, and J. Simpson, 2007: Improving simulations of convective systems from TRMM LBA: Easterly and westerly regimes. J. Atmos. Sci., 64, 1141–1164, doi:10.1175/JAS3879.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Lang, S. E., W.-K. Tao, X. Zeng, and Y. Li, 2011: Reducing the biases in simulated radar reflectivities from a bulk microphysics scheme: Tropical convective systems. J. Atmos. Sci., 68, 2306–2320, doi:10.1175/JAS-D-10-05000.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Lang, S. E., W. K. Tao, J. D. Chern, D. Wu, and X. W. Li, 2014: Benefits of a fourth ice class in the simulated radar reflectivities of convective systems using a bulk microphysics scheme. J. Atmos. Sci., 71, 3583–3612, doi:10.1175/JAS-D-13-0330.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Lim, K.-S. S., and S.-Y. Hong, 2010: Development of an effective double-moment cloud microphysics scheme with prognostic cloud condensation nuclei (CCN) for weather and climate models. Mon. Wea. Rev., 138, 1587–1612, doi:10.1175/2009MWR2968.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Lin, Y., and B. A. Colle, 2011: A new bulk microphysical scheme that includes riming intensity and temperature-dependent ice characteristics. Mon. Wea. Rev., 139, 1013–1035, doi:10.1175/2010MWR3293.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Lin, Y.-L., R. D. Farley, and H. D. Orville, 1983: Bulk parameterization of the snow field in a cloud model. J. Climate Appl. Meteor., 22, 1065–1092, doi:10.1175/1520-0450(1983)022<1065:BPOTSF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Masunaga, H., and C. D. Kummerow, 2006: Observations of tropical precipitating clouds ranging from shallow to deep convective systems. Geophys. Res. Lett., 33, L16805, doi:10.1029/2006GL026547.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Masunaga, H., T. S. L’Ecuyer, and C. D. Kummerow, 2005: Variability in the characteristics of precipitation systems in the tropical Pacific. Part I: Spatial structure. J. Climate, 18, 823–840, doi:10.1175/JCLI-3304.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Masunaga, H., M. Satoh, and H. Miura, 2008: A joint satellite and global cloud-resolving model analysis of a Madden-Julian Oscillation event: Model diagnosis. J. Geophys. Res., 113, D17210, doi:10.1029/2008JD009986.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Masunaga, H., and Coauthors, 2010: Satellite data simulator unit: A multisensor, multispectral satellite simulator package. Bull. Amer. Meteor. Soc., 91, 1625–1632, doi:10.1175/2010BAMS2809.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Matsui, T., X. Zeng, W.-K. Tao, H. Masunaga, W. S. Olson, and S. Lang, 2009: Evaluation of long-term cloud-resolving model simulations using satellite radiance observations and multifrequency satellite simulators. J. Atmos. Oceanic Technol., 26, 1261–1274, doi:10.1175/2008JTECHA1168.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Miyamoto, Y., Y. Kajikawa, R. Yoshida, T. Yamaura, H. Yashiro, and H. Tomita, 2013: Deep moist atmospheric convection in a subkilometer global simulation. Geophys. Res. Lett., 40, 4922–4926, doi:10.1002/grl.50944.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Miyamoto, Y., R. Yoshida, T. Yamaura, H. Yashiro, H. Tomita, and Y. Kajikawa, 2015: Does convection vary in different cloud disturbances? Atmos. Sci. Lett., 16, 305–309, doi:10.1002/asl2.558.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Morrison, H., J. A. Curry, and V. I. Khvorostyanov, 2005: A new double-moment microphysics parameterization for application in cloud and climate models. Part I: Description. J. Atmos. Sci., 62, 1665–1677, doi:10.1175/JAS3446.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Miura, H., M. Satoh, T. Nasuno, A. T. Noda, and K. Oouchi, 2007: A Madden-Julian Oscillation event realistically simulated by a global cloud-resolving model. Science, 318, 1763–1765, doi:10.1126/science.1148443.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Nasuno, T., and M. Satoh, 2011: Properties of precipitation and in-cloud vertical motion in a global nonhydrostatic aquaplanet experiment. J. Meteor. Soc. Japan, 89, 413–439, doi:10.2151/jmsj.2011-502.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Roh, W., and M. Satoh, 2014: Evaluation of precipitating hydrometeor parameterizations in a single-moment bulk microphysics scheme for deep convective systems over the tropical central Pacific. J. Atmos. Sci., 71, 2654–2673, doi:10.1175/JAS-D-13-0252.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Rutledge, S. A., and P. V. Hobbs, 1984: The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. XII: A diagnostic modeling study of precipitation development in narrow cold-frontal rainbands. J. Atmos. Sci., 41, 2949–2972, doi:10.1175/1520-0469(1984)041<2949:TMAMSA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Sato, T., T. Yoshikane, M. Satoh, H. Miltra, and H. Fujinami, 2008: Resolution dependency of the diurnal cycle of convective clouds over the Tibetan Plateau in a mesoscale model. J. Meteor. Soc. Japan, 86A, 17–31, doi:10.2151/jmsj.86A.17.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Satoh, M., T. Matsuno, H. Tomita, H. Miura, T. Nasuno, and S. Iga, 2008: Nonhydrostatic icosahedral atmospheric model (NICAM) for global cloud resolving simulations. J. Comput. Phys., 227, 3486–3514, doi:10.1016/j.jcp.2007.02.006.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Satoh, M., T. Inoue, and H. Miura, 2010: Evaluations of cloud properties of global and local cloud system resolving models using CALIPSO and CloudSat simulators. J. Geophys. Res., 115, D00H14, doi:10.1029/2009JD012247.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Satoh, M., and Coauthors, 2014: The Non-hydrostatic Icosahedral Atmospheric Model: Description and development. Prog. Earth Planet. Sci., 1, 18, doi:10.1186/s40645-014-0018-1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Seifert, A., and K. D. Beheng, 2006: A two-moment cloud microphysics parameterization for mixed-phase clouds. Part 1: Model description. Meteor. Atmos. Phys., 92, 45–66, doi:10.1007/s00703-005-0112-4.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Seiki, T., and T. Nakajima, 2014: Aerosol effects of the condensation process on a convective cloud simulation. J. Atmos. Sci., 71, 833–853, doi:10.1175/JAS-D-12-0195.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Stephens, G. L., and N. B. Wood, 2007: Properties of tropical convection observed by millimeter-wave radar systems. Mon. Wea. Rev., 135, 821–842, doi:10.1175/MWR3321.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Tomita, H., 2008a: New microphysical schemes with five and six categories by diagnostic generation of cloud ice. J. Meteor. Soc. Japan, 86A, 121–142, doi:10.2151/jmsj.86A.121.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Tomita, H., 2008b: A stretched icosahedral grid by a new grid transformation. J. Meteor. Soc. Japan, 86A, 107–119, doi:10.2151/jmsj.86A.107.

  • Tomita, H., and M. Satoh, 2004: A new dynamical framework of nonhydrostatic global model using the icosahedral grid. Fluid Dyn. Res., 34, 357–400, doi:10.1016/j.fluiddyn.2004.03.003.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Van Weverberg, K., N. P. M. van Lipzig, and L. Delobbe, 2011: The impact of size distribution assumptions in a bulk one-moment microphysics scheme on simulated surface precipitation and storm dynamics during a low-topped supercell case in Belgium. Mon. Wea. Rev., 139, 1131–1147, doi:10.1175/2010MWR3481.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Van Weverberg, K., and Coauthors, 2013: The role of cloud microphysics parameterization in the simulation of mesoscale convective system clouds and precipitation in the tropical western Pacific. J. Atmos. Sci., 70, 1104–1128, doi:10.1175/JAS-D-12-0104.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Voors, R., and Coauthors, 2007: ECSIM: The simulator framework for EarthCARE. Sensors, Systems, and Next-Generation Satellites XI, R. Meynart et al., Eds., International Society for Optical Engineering (SPIE Proceedings, Vol. 6744), 67441Y, doi:10.1117/12.737738.

    • Crossref
    • Export Citation

  • Wielicki, B. A., B. R. Barkstrom, E. F. Harrison, R. B. Lee, G. L. Smith, and J. E. Cooper, 1996: Clouds and the Earth’s Radiant Energy System (CERES): An Earth Observing System experiment. Bull. Amer. Meteor. Soc., 77, 853–868, doi:10.1175/1520-0477(1996)077<0853:CATERE>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Zhang, G., M. Xue, Q. Cao, and D. Dawson, 2008: Diagnosing the intercept parameter for exponential raindrop size distribution based on video disdrometer observations: Model development. J. Appl. Meteor. Climatol., 47, 2983–2992, doi:10.1175/2008JAMC1876.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 505 138 11
PDF Downloads 407 79 6