the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 22 Aug 2024
Gridded surface O3, NOx, and CO abundances for model metrics from the South Korean ground station network
Abstract. We present gridded surface air quality datasets over South Korea for three key species – ozone (O3), carbon monoxide (CO), and nitrogen oxides (NOx) during the timeframe of the Korea–US Air Quality (KORUS–AQ) mission (May–June 2016). The tenth degree hourly averaged abundances are constructed from the 300+ air quality network sites using inverse distance weighting with simple declustering. Cross–comparing the interpolated fields against the site data that was used to create them reveals high prediction skill for O3 (80 %) throughout South Korea, and moderate skill (60 %) for CO and NOx on average in densely observed regions after individual mean bias corrections. The gridded O3 and CO interpolations predict the NASA DC–8 observations in the planetary boundary layer (PBL) with high skill (80 %) in the Seoul Metropolitan Area (SMA) after subtracting the mean bias. DC–8 NOx observations were much less predictable on account of consistently negative vertical gradients within the PBL. Our gridded products capture the mean and variability of O3 throughout South Korea, and of CO and surface NOx in most site–dense urban centres (SMA, Cheongju, Gwangju, Daegu, Changwon, and Busan).
- Preprint
(1718 KB) - Metadata XML
- BibTeX
- EndNote
Status: open (extended)
-
RC1: 'Comment on egusphere-2024-1173', Anonymous Referee #1, 13 Oct 2024
reply
This manuscript presented an IDW-based spatial interpolation method and an hourly gridded (0.1 x 0.1 deg) dataset for O3, CO, NOx. The gridded dataset was derived from the interpolated ground site observations in South Korea during the period of KORUS-AQ field campaign. The authors used this approach to mitigate the bias due to uneven density of the ground sites. The interpolation method and the gridded dataset were rigorously tested and analyzed in terms of bias and variability. The gridded dataset described in the manuscript will be useful to assess and improve models. The IDW-based interpolation approach is relatively straightforward and can also be used by researchers to better use the ground network observations. At the same time, it should be recognized that the IDW-based approach may not fully address the effect of microscale meteorological and local emissions, which both can be important under certain conditions. This reviewer believes it would benefit the readers if the authors can add more detailed discussions on the advantages and limitations the IDW-based approach, specifically discussing the statistical test results in the context of microscale meteorological conditions (e.g., wind speed and direction) and local emissions. Another important issue is the need to highlight the difference between weighted average and arithmetic average approaches in three grid cases with low, mid, and high Q values. This can be done by contrasting O3, CO, and NOx values between the gridded data presented in this manuscript and those computed from simple averages.
Specific comments:
- Line 90 – 91: The authors should clarify how the correlation was computed between different sites and discuss if different sites have similar temporal variation patterns with a phase shift.
- Section 3.2: This reviewer would like to raise a question if the better results obtained for O3 is partially attributed to that O3 abundance is not directly influenced by local emissions while the CO and NOx at a given site can be substantially affected by local emissions. It is possible that certain emission events are seen only in a few sites and the IDW interpolation would not be able to predict these observations in the leave-one-out tests. In this context, it would be helpful if the authors can state the limitation of the IDW interpolation under certain conditions.
- Section 4.2: It should be stated in this section that the DC-8 sampling may not be representative of the grids due to limitation of the flight patterns.
- The conclusion section should highlight the advantages and limitations of the IDW interpolation approach.
- The authors should consider adding global attributes and variable attributes (e.g., units) to the gridded netCDF file and make the file more CF compliant, e.g., using CF variable names, like time, lat, and lon. This will enhance the (re)usability and interoperability of the hourly gridded dataset.
Citation: https://doi.org/10.5194/egusphere-2024-1173-RC1 -
AC1: 'Reply on RC1', Calum Wilson, 21 Oct 2024
reply
We thank the reviewer once again for investing their time into our manuscript, and we detail how we addressed the comments in the upcoming manuscript version.
This manuscript presented an IDW-based spatial interpolation method and an hourly gridded (0.1 x 0.1 deg) dataset for O3, CO, NOx. The gridded dataset was derived from the interpolated ground site observations in South Korea during the period of KORUS-AQ field campaign. The authors used this approach to mitigate the bias due to uneven density of the ground sites. The interpolation method and the gridded dataset were rigorously tested and analyzed in terms of bias and variability. The gridded dataset described in the manuscript will be useful to assess and improve models. The IDW-based interpolation approach is relatively straightforward and can also be used by researchers to better use the ground network observations. At the same time, it should be recognized that the IDW-based approach may not fully address the effect of microscale meteorological and local emissions, which both can be important under certain conditions. This reviewer believes it would benefit the readers if the authors can add more detailed discussions on the advantages and limitations the IDW-based approach, specifically discussing the statistical test results in the context of microscale meteorological conditions (e.g., wind speed and direction) and local emissions. Another important issue is the need to highlight the difference between weighted average and arithmetic average approaches in three grid cases with low, mid, and high Q values. This can be done by contrasting O3, CO, and NOx values between the gridded data presented in this manuscript and those computed from simple averages.
We have added a discussion of the IDW vs. Arithmetic Mean techniques, noting significant differences in e.g. the Seoul Metropolitan Area, where IDW was previously shown to achieve good predictability.
Line 90 – 91: The authors should clarify how the correlation was computed between different sites and discuss if different sites have similar temporal variation patterns with a phase shift.We have clarified how the correlation was computed and added further analysis of the site autocorrelations.
Section 3.2: This reviewer would like to raise a question if the better results obtained for O3 is partially attributed to that O3 abundance is not directly influenced by local emissions while the CO and NOx at a given site can be substantially affected by local emissions. It is possible that certain emission events are seen only in a few sites and the IDW interpolation would not be able to predict these observations in the leave-one-out tests. In this context, it would be helpful if the authors can state the limitation of the IDW interpolation under certain conditions.
We agree with the reviewer in our arguments on lines 164 to 165, but have added the clarification that O3 is not directly emitted, unlike the other species. We added a description of the IDW limitations in the conclusion.
Section 4.2: It should be stated in this section that the DC-8 sampling may not be representative of the grids due to limitation of the flight patterns.
We updated our manuscript to acknowledge this fact.
The conclusion section should highlight the advantages and limitations of the IDW interpolation approach.
We have added a discussion of IDW vs. arithmetic mean technique in the conclusion and described the limitations of IDW, noting how some alternative techniques could address these limitations.
The authors should consider adding global attributes and variable attributes (e.g., units) to the gridded netCDF file and make the file more CF compliant, e.g., using CF variable names, like time, lat, and lon. This will enhance the (re)usability and interoperability of the hourly gridded dataset.
Great idea, thanks. We have updated our datasets to better comply with the CF standard. We use more conventional variable and dimension aliases (e.g. lat, lon, time) along with units, long_name, and description attributes. We have added global attributes that specify where found the data and how we processed it.
Citation: https://doi.org/10.5194/egusphere-2024-1173-AC1
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 158 | 62 | 11 | 231 | 2 | 4 |
- HTML: 158
- PDF: 62
- XML: 11
- Total: 231
- BibTeX: 2
- EndNote: 4
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1