Submitted as: model evaluation paper
05 Oct 2023
Submitted as: model evaluation paper |  | 05 Oct 2023
Status: this preprint is currently under review for the journal GMD.

Global variable-resolution simulations of extreme precipitation over Henan, China in 2021

Zijun Liu, Li Dong, Huiling Yuan, Xingrong Li, Dongmei Meng, Xiaobin Qiu, Dingyuan Liang, and Yafei Wang

Abstract. A historic rainstorm occurred over Henan, China in July 2021 ("7.20" extreme precipitation event), resulting in significant human casualties and socio-economic losses. A global variable-resolution model (MPAS-Atmosphere v7.3) was employed to simulate this extreme precipitation event, by bridging the hydrostatic and non-hydrostatic scales together. A series of simulations have been done at both quasi-uniform (60 km and 15 km) and variable-resolution meshes (60–15 km and 60–3 km). For the 48-hour peak precipitation duration (07/20–07/22), the 60–3 km variable-resolution simulation coupled with the scale-aware convection-permitting parameterization scheme suite stands out predominately among other simulation experiments as it reproduces this extreme precipitation event most accurately, in terms of both the intensity and location of the peak precipitation. At 15-km resolution, the 60–15 km variable-resolution simulation achieves comparable forecasting skills as the 15-km quasi-uniform simulation, but at a much reduced computing cost. In addition, at 15-km resolution, we found that the default mesoscale suite generally outperforms the convection-permitting suite at 15-km resolution as simulations coupled with convection-permitting suite missed the 3rd peak of this extreme precipitation event while the mesoscale suite did not. This implies that, when the resolution of the refined region is coarser than the cloud-resolving scale, the convection-permitting parameterization scheme suite does not necessarily work better than the default mesoscale suite, but once the refined mesh is close to the cloud-resolving scale, the convection-permitting suite becomes scale aware such that it can intelligently distinguish the convective precipitation and grid-scale precipitation, respectively. Finally, it is found that the large-scale wind field plays a vital role in affecting extreme precipitation simulations since it primarily influences the transport of the water vapor flux thereby altering the prediction of the precise peak precipitation location.

Zijun Liu et al.

Status: open (extended)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'Executive Editor comment on gmd-2023-193', Astrid Kerkweg, 23 Oct 2023 reply
    • CC1: 'Reply on CEC1', Zijun Liu, 26 Oct 2023 reply
  • RC1: 'Comment on gmd-2023-193', Anonymous Referee #1, 05 Nov 2023 reply
    • AC1: 'Reply on RC1', Zijun Liu, 06 Nov 2023 reply
      • RC2: 'Reply on AC1', Anonymous Referee #1, 06 Nov 2023 reply

Zijun Liu et al.

Zijun Liu et al.


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Short summary
In this study, we completed a series of simulations with the MPAS-Atmosphere (version 7.3) to study the extreme precipitation event of Henan, China, during July 20–22, 2021. We found the different performances of two built-in parameterization scheme suites (mesoscale and convection-permitting suites) with global quasi-uniform and variable-resolution meshes. This study holds significant implications for advancing the understanding of scale-aware capability of the MPAS-Atmosphere.