Characteristics of surface energy balance and atmospheric circulation during hot-and-polluted episodes and their synergistic relationships with urban heat islands over the Pearl River Delta region

Nduka, Ifeanyichukwu C.; Tam, Chi-Yung; Guo, Jianping; Yim, Steve Hung Lam

doi:https://doi.org/10.5194/acp-21-13443-2021

Articles | Volume 21, issue 17

https://doi.org/10.5194/acp-21-13443-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-21-13443-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 21, issue 17

Research article

|

10 Sep 2021

Research article |

| 10 Sep 2021

Characteristics of surface energy balance and atmospheric circulation during hot-and-polluted episodes and their synergistic relationships with urban heat islands over the Pearl River Delta region

Ifeanyichukwu C. Nduka, Chi-Yung Tam, Jianping Guo, and Steve Hung Lam Yim

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Final revised paper (published on 10 Sep 2021)
Supplement to the final revised paper
Preprint (discussion started on 08 Dec 2020)
Supplement to the preprint

Interactive discussion

Status: closed

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

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- Supplement

AC1: 'Manuscript: corrected figure 1', Steve Hung Lam Yim, 29 Dec 2020
RC1: 'review', Anonymous Referee #3, 02 Jan 2021
RC2: 'Review comments', Anonymous Referee #2, 02 Jan 2021

Peer-review completion

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

AR by Steve Hung Lam Yim on behalf of the Authors (24 Feb 2021) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (27 Feb 2021) by Zhanqing Li

RR by Anonymous Referee #3 (19 Mar 2021)

Suggestions for revision or reasons for rejection

The authors prepared a new version of the manuscript including corrections and clarifications on a number of issues, as suggested.
Despite their efforts my main concern regarding the robustness and clarity of HPE identification remains. The criteria and methodology for HPE identification are described and presented in a somewhat messy and patchy way in the manuscript. Some information is included in the main text. Another short paragraph is included in Supplement, but without much information. It was difficult to reach and combine all this information. The thresholds for O3 are not included, although O3 has been included in the criteria for HPEs. The annual threshold value of 20μg/m3 is used for PM10, although the authors assume daily values (50th percentiles ) for at least 3 consecutive days and the daily threshold of WHO is 50 μg/m3. I suggest the authors to gather and include all information and criteria for HPE identification in a section and describe them in a precise way giving also quantitative information when needed. For instance
An HPE was identified when the following criteria were simultaneously fulfilled:
1. Daily Tmax at HK observatory was above 50th percentile of Tmax distribution from June-October over the study period 2009-2011 for at least 3 consecutive days. (which is this value? And comment that it is at the same time above the health risk values found by Chen et al, or Wang et al
2. 50th of daily PM10 concentration was above (provide threshold) for 3 consecutive days at 50% of the 11 air quality stations at Hong Kong (?)
3. 50th of daily O3 was above (xxxx…provide a threshold) for 3 consecutive days at 50% of the 11 air quality stations at Hong Kong (?)
If the criteria for air pollution are not strict please comment on this and provide an explanation for this decision. Also, a short period was selected for this study (2009-2011) due to lack of available data for a longer period and more recent period. But even in this short period, several assumptions were made due to lack of data in some stations. The limitations of the study should be discussed.
Additional comments
Although in their response to my question, the authors clarify that relative humidity and wind speed are used only for model simulations and not for HPE identification, in section 2.2 in Supplement entitled ‘Observational Data for HPE Identification’ wind speed and relative humidity are also included.
In their answer of comment No 20, the authors insist that the model results of RH are lower than the observations and thus Mean Bias is negative . But Table S2a shows the opposite. If indeed model value is lower than the observed value, then Table S2a must be corrected.
Line 247: …’ because they exhibit the characteristics of an air parcel over time’.. I do not understand , this is really strange. Please explain or provide a complete sentence that makes sense regarding the suitability of potential temperature as indicator in this case.

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ED: Publish subject to technical corrections (20 Mar 2021) by Zhanqing Li

AR by Steve Hung Lam Yim on behalf of the Authors (31 Mar 2021) Author's response Manuscript

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Short summary

This study analyzed the nature, mechanisms and drivers for hot-and-polluted episodes (HPEs) in the Pearl River Delta, China. A total of eight HPEs were identified and can be grouped into three clusters of HPEs that were respectively driven (1) by weak subsidence and convection induced by approaching tropical cyclones, (2) by calm conditions with low wind speed in the lower atmosphere and (3) by the combination of both aforementioned conditions.