Mesoscale Convective Systems Simulated by a High‐Resolution Global Nonhydrostatic Model Over the United States and China

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  • Ying Na
    Beijing Municipal Climate Center Beijing China
  • Qiang Fu
    Department of Atmospheric Sciences University of Washington Seattle WA USA
  • L. Ruby Leung
    Atmospheric Sciences and Global Change Division Pacific Northwest National Laboratory Richland WA USA
  • Chihiro Kodama
    Japan Agency for Marine‐Earth Science and Technology Yokohama Japan
  • Riyu Lu
    State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China

書誌事項

公開日
2022-04-04
資源種別
journal article
権利情報
  • http://onlinelibrary.wiley.com/termsAndConditions#vor
DOI
  • 10.1029/2021jd035916
公開者
American Geophysical Union (AGU)

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説明

<jats:title>Abstract</jats:title><jats:p>Mesoscale convective systems (MCSs) contribute a large fraction of warm‐season precipitation and generate hazardous weather with substantial socioeconomic impacts. Uncertainties in convection parameterizations in climate models limit our understanding of MCS characteristics and reliability of future projection. We examine MCSs simulated by the global 14 km Nonhydrostatic ICosahedral Atmospheric Model (NICAM) without cumulus parameterization against satellite observation from Global Precipitation Measurement during 2001–2008. We focus on MCSs over the central United States and eastern China where MCSs are prevalent from March to August. A process‐oriented tracking method incorporating both cloud and precipitation criteria is used to identify and track MCSs. About 140/100 MCSs initiate in the central United States/eastern China per warm season and most of them initiate in the east of high mountains and in coastal regions. The frequency distribution of MCS lifetime is well captured by NICAM. However, the simulated MCSs have stronger precipitation, smaller precipitation area, and larger cold cloud system than that observed in both regions, which may be caused by weak entrainment as it is not well resolved at 14 km resolution. The simulated MCS number is also underestimated in summer. By examining the climatological and MCS large‐scale environments, the significant underestimation of MCS number in summer over the central United States may be attributed to the large climatological dry bias in the atmosphere. For China, mean moisture in summer is well simulated but deficiency in capturing the dynamic condition related to the coastal topography for triggering convection may have contributed to underestimation of MCS even in a sufficiently moist environment.</jats:p>

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