Evaluation of modeled surface ozone biases as a function of cloud cover fraction

Kim, H. C.; Lee, P.; Ngan, F.; Tang, Y.; Yoo, H. L.; Pan, L.

doi:https://doi.org/10.5194/gmd-8-2959-2015

Articles | Volume 8, issue 9

https://doi.org/10.5194/gmd-8-2959-2015

© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/gmd-8-2959-2015

© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 8, issue 9

Development and technical paper

|

25 Sep 2015

Development and technical paper |

| 25 Sep 2015

Evaluation of modeled surface ozone biases as a function of cloud cover fraction

H. C. Kim, P. Lee, F. Ngan, Y. Tang, H. L. Yoo, and L. Pan

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Final revised paper (published on 25 Sep 2015)
Preprint (discussion started on 14 Apr 2015)

Interactive discussion

Status: closed

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

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RC C1047: 'Referee comment', Anonymous Referee #1, 09 Jun 2015
- AC C1468: 'Response to review #1', hyuncheol kim, 23 Jul 2015
RC C1070: 'Review of "Evaluation of modeled surface ozone biases as a function of cloud cover fraction"', Anonymous Referee #2, 10 Jun 2015
- AC C1469: 'Response to review #2', hyuncheol kim, 23 Jul 2015

Peer-review completion

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

AR by hyuncheol kim on behalf of the Authors (17 Aug 2015) Manuscript

ED: Publish as is (25 Aug 2015) by Gerd A. Folberth

AR by hyuncheol kim on behalf of the Authors (31 Aug 2015) Manuscript

Short summary

This study focuses on the evaluation of regional air quality model's performance based on the cloud information from satellites. While cloud information is crucial in photochemistry model, the definitions of cloud fraction from model and satellite are not physically consistent. We demonstrate that improper modeling of cloud fraction is correlated with surface ozone bias, and we also show that current model cloud field might be too bright, causing an overestimation of surface ozone level.