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The GAMIL3: Model Description and Evaluation

  • Lijuan Li
  • , Li Dong
  • , Jinbo Xie
  • , Yanli Tang
  • , Feng Xie
  • , Zhun Guo
  • , Hongbo Liu
  • , Tao Feng
  • , Lu Wang
  • , Ye Pu
  • , Wenqi Sun
  • , Kun Xia
  • , Li Liu
  • , Zhenghui Xie
  • , Yan Wang
  • , Longhuan Wang
  • , Xiangjun Shi
  • , Binghao Jia
  • , Juanjuan Liu
  • , Bin Wang

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

The Grid-point Atmospheric Model of the IAP LASG version 3 (GAMIL3) has been developed by upgrading the horizontal resolution, methods of parallel computation, boundary layer scheme, aerosol parameterization, convective parameterization, stratocumulus cloud fraction scheme, land component, and coupler, as well as tuning some moist physical parameters with large uncertainties. Its performance is evaluated, and the results show significant improvements compared with the previous version, GAMIL2. The simulated performance of mean states is notably enhanced, including the energy budget terms at the top of the atmosphere (TOA) and surface, shortwave/longwave cloud radiative forcing (SWCF/LWCF), precipitation, zonal wind, low-level temperature, 500-hPa geopotential height, and snow cover fraction in the Northern Hemisphere. The characteristics of internal variability are captured well, such as the frequency band and active areas of quasi-biweekly (QBW) oscillation, spectral power of convectively coupled equatorial waves (CCEWs), Madden-Julian Oscillation (MJO) eastward propagation, and heat flux response to El Niño-Southern Oscillation (ENSO), and these variabilities are generally strengthened in GAMIL3. In addition, the anthropogenic aerosol climate effects are weakened when using the forcings recommended by CMIP6.

Original languageEnglish
Article numbere2020JD032574
JournalJournal of Geophysical Research: Atmospheres
Volume125
Issue number15
DOIs
StatePublished - Aug 16 2020
Externally publishedYes

Funding

This research was jointly funded by the National Natural Science Foundation of China (Grants 41622503 and 41775101), Strategic Priority Research Program of Chinese Academy of Sciences (Grant XDB42010404), and National Key Research Project (Grant 2016YFB0200805).

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