The global dust cycle and uncertainty in CMIP5 (Coupled Model Intercomparison Project phase 5) models

Wu, Chenglai; Lin, Zhaohui; Liu, Xiaohong

doi:https://doi.org/10.5194/acp-20-10401-2020

Articles | Volume 20, issue 17

https://doi.org/10.5194/acp-20-10401-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-20-10401-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 20, issue 17

Research article

|

08 Sep 2020

Research article |

| 08 Sep 2020

The global dust cycle and uncertainty in CMIP5 (Coupled Model Intercomparison Project phase 5) models

Chenglai Wu, Zhaohui Lin, and Xiaohong Liu

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Final revised paper (published on 08 Sep 2020)
Preprint (discussion started on 03 Apr 2020)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Review of “Global dust cycle and uncertainty in CMIP5 models” by Chenglai Wu, Zhaohui Lin, and Xiaohong Liu', Anonymous Referee #1, 29 Apr 2020
- AC1: 'Respones to Referee #1 comments', Chenglai Wu, 26 Jun 2020
RC2: 'RC', Yaping Shao, 01 May 2020
- AC2: 'Respones to Referee #2 comments', Chenglai Wu, 26 Jun 2020

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Chenglai Wu on behalf of the Authors (26 Jun 2020) Author's response Manuscript

ED: Publish as is (02 Jul 2020) by Ashu Dastoor

Post-review adjustments

AA: Author's adjustment | EA: Editor approval

AA by Chenglai Wu on behalf of the Authors (18 Aug 2020) Author's adjustment Manuscript

EA: Adjustments approved (23 Aug 2020) by Ashu Dastoor

Short summary

This study provides a comprehensive evaluation of the global dust cycle in 15 models participating in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). We assess the global budget and associated uncertainties. We also quantify the discrepancies in each model. The results highlight the large uncertainties in both the locations and intensities of dust emission. Our study will serve as a useful reference for model communities and help further model improvements.