Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 4.252 IF 4.252
  • IF 5-year value: 4.890 IF 5-year
    4.890
  • CiteScore value: 4.49 CiteScore
    4.49
  • SNIP value: 1.539 SNIP 1.539
  • SJR value: 2.404 SJR 2.404
  • IPP value: 4.28 IPP 4.28
  • h5-index value: 40 h5-index 40
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 51 Scimago H
    index 51
Discussion papers
https://doi.org/10.5194/gmd-2019-1
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2019-1
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Model evaluation paper 28 Jan 2019

Model evaluation paper | 28 Jan 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).

CAM6 simulation of mean and extreme precipitation over Asia: Sensitivity to upgraded physical parameterizations and higher horizontal resolution

Lei Lin1, Andrew Gettelman2, Yangyang Xu3, Chenglai Wu4, Zhili Wang5, and Wenjie Dong1 Lei Lin et al.
  • 1School of Atmospheric Sciences and Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Zhuhai, Guangdong, China
  • 2National Center for Atmospheric Research, Boulder, Colorado, USA
  • 3Department of Atmospheric Sciences, College of Geosciences, Texas A&M University, College Station, Texas, USA
  • 4International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
  • 5State Key Laboratory of Severe Weather and Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, China

Abstract. The Community Atmosphere Model version 6 (CAM6) released in 2018, as part of the Community Earth System Model version 2 (CESM2) modeling framework, is a major upgrade over the previous CAM5 that has been used in numerous global and regional climate studies in the past six years. Since CESM2/CAM6 will participate in the upcoming Coupled Model Intercomparison Project phase 6 (CMIP6) and is likely to be adopted in many future studies, its simulation fidelity needs to be thoroughly examined. Here we evaluate the performance of a developmental version of the Community Atmosphere Model with parameterizations that will be used in CMIP6 (CAM6α) with the default 1º horizontal resolution (0.9º × 1.25º, CAM6α-1º) and a higher resolution simulation (approximately 0.25º, CAM6α-0.25º), against various precipitation observational datasets over Asia. The CAM6α performance is also compared with CAM5 with the default 1º horizontal resolution (CAM5-1º). With the prognostic treatment of precipitation processes (which is missing in CAM5) and the new microphysics module, CAM6 is able to better simulate climatological mean and extreme precipitation over Asia, to better capture the heaviest precipitation events, to reproduce the diurnal cycle of precipitation rates over most of Asia, and to better simulate the probability density distributions of daily precipitation over Tibet, Korea, Japan and Northern China. Higher horizontal resolution in CAM6α improves simulations of mean and extreme precipitation over mountainous Sichuan and Northern China, but the performance degrades over the Maritime continent. Further diagnosis on moisture budget suggests that the physical processes leading to model improvement are different over different regions. Both upgraded physical parameterizations and higher horizontal resolution affect the precipitation response to internal variability of ocean and atmosphere (e.g. Asian monsoon index, ENSO, PDO), but the effects vary across different regions. Higher horizontal resolution degrades the model performance in simulating precipitation variability associated with the East Asian summer monsoon in the middle and lower reaches of the Yangtze River in China. The precipitation variability associated with ENSO gets better with upgraded physical parameterizations and higher horizontal resolution. Higher horizontal resolution, however, induces an opposite response to PDO in CAM6 over Southern China.

Lei Lin et al.
Interactive discussion
Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Login for Authors/Topical Editors] [Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement
Lei Lin et al.
Data sets

CAM6 simulation of mean and extreme precipitation over Asia L. Lin, A. Gettelman, Y. Xu, C. Wu, Z. Wang, and W. Dong https://doi.org/10.5281/zenodo.2548255

Lei Lin et al.
Viewed  
Total article views: 291 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
218 67 6 291 6 6
  • HTML: 218
  • PDF: 67
  • XML: 6
  • Total: 291
  • BibTeX: 6
  • EndNote: 6
Views and downloads (calculated since 28 Jan 2019)
Cumulative views and downloads (calculated since 28 Jan 2019)
Viewed (geographical distribution)  
Total article views: 139 (including HTML, PDF, and XML) Thereof 139 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Cited  
Saved  
No saved metrics found.
Discussed  
No discussed metrics found.
Latest update: 17 Apr 2019
Publications Copernicus
Download
Short summary
Here we evaluate the performance of the Community Atmosphere Model version 6 (CAM6) released in 2018 with the default 1º horizontal resolution and a higher resolution simulation (approximately 0.25º), against various precipitation observational datasets over Asia. With the prognostic treatment of precipitation processes (which is missing in CAM5) and the new microphysics module, CAM6 is able to better simulate climatological mean and extreme precipitation over Asia.
Here we evaluate the performance of the Community Atmosphere Model version 6 (CAM6) released in...
Citation