the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 17 Mar 2023
Variability of coastal downwelling circulation in response to high-resolution regional atmospheric forcing off the Pearl River Estuary
Abstract. We investigated the variabilities of coastal circulation and dynamics in response to spatiotemporally variable high-resolution atmospheric forcing off the Pearl River Estuary during the downwelling wind. Our investigation focused on the processes and dynamics of coastal downwelling circulation in response to variable atmospheric forcing of (1) single station observation, (2) global reanalysis data, and (3) a high-resolution regional atmospheric model. We found that the high-resolution atmospheric model significantly improved the representations of the near-surface wind and air temperature, and the ocean model driven by the high-resolution and spatially variable atmospheric forcing improved the circulation and associated hydrographic properties in the coastal ocean. Momentum and vorticity analyses further revealed that the cross-isobath water exchange was primarily governed by the along-isobath pressure gradient force (PGF), which was influenced by different components of the atmospheric forcing. The spatial-temporal variability of high-resolution wind forcing determined the strength and structure of coastal circulation, and improved estimates of cross-isobath transport and the associated PGF by refining the net stress curl and nonlinear advection of relative vorticity in the simulation. The high-resolution heat forcing can greatly improve the sea surface temperature simulation and adjust the nonlinear advection of relative vorticity, resulting in changes in cross-isobath transport.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-318', Anonymous Referee #1, 19 Apr 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-318/egusphere-2023-318-RC1-supplement.pdf
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AC1: 'Reply on RC1', Wenfeng Lai, 29 Apr 2023
Review of “Variability of coastal downwelling circulation in response to high-resolution regional atmospheric forcing off the Pearl River Estuary”
This paper by Lai and Gan investigated the variabilities of coastal circulation and dynamics in response to spatiotemporally variable high-resolution atmospheric forcing off the Pearl River Estuary during the downwelling wind. The authors conducted three numerical experiments based on (1) single station observation, (2) global reanalysis data and (3) high-resolution regional atmospheric model. Results show that the model with high-resolution atmospheric forcing significantly improved the temperature-salinity profiles and ocean current simulation. In addition, the model with high atmo-forcing improved the estimation of cross-isobath transport. This paper is well-written and organized, and the results are beneficial for ocean modeler to improve their model results and associated studies. I would suggest a minor revision for this paper before publishing it.
Reply: Thank you for your constructive comments. We appreciate the positive feedback and are pleased to know that our work is beneficial for ocean modelers. We hope that our revisions have adequately addressed the reviewer’s concerns.Major Comments:
(1) One of the comment problems in ocean model is the over-heating in the surface layer. Usually the ocean model needs surface temperature nudging to the reanalysis or climatology SST data, such as GHRSST and MODIS, to avoid over-heating in the surface layer. In this paper, the author mentioned that ROMS were forced by high-resolution wind stress and heat fluxes. I wonder whether ROMS model in this paper only driven by high-resolution heat fluxes without SST nudging, or only driven by high-resolution SST. Please clarify it in the discussion.Reply: We understand that the surface temperature nudging to reanalysis or climatology SST data in the ocean model is important. However, in this study, we did not apply additional surface temperature nudging to the reanalysis or climatology SST data to avoid response of the model to artificial forcing which could twist internal physical response of the model and smear our analysis. We conducted a short-term simulation, with the main driving forces being wind stress and bulk heat fluxes. Applying high-frequency SST nudging could potentially affect the physical dynamics.
Furthermore, in this coastal region, the accuracy of GHRSST and MODIS SST is highly questionable, and the variability of SST in this region is large, making it difficult to find high-quality SST data for the coastal area.(2) The author used the ERA data with 75 km resolution as the “coarse” resolution product to compared with the WRF 1 km production. Actually, in nowadays, the 12-15 km resolution and 0.2 degree (approximately 22 km) resolution products are quite common, and provided by ECWMF and CFSV2 (from NECP), respectively. Ocean model driven by this 10-20 km resolution products may be closed to that driven by WRF 1 km product. The author may give some comment on this.
Reply: We acknowledge that other relatively high-resolution datasets are available, such as the latest ERA5 data from ECMWF with a 0.25-degree resolution and the 0.2-degree products from CFSv2 from NCEP. However, different reanalysis datasets can have differences in spatial and temporal resolution, as well as in the way they assimilate observations and model data, leading to different influences on ocean model performance. Thankaswamy et al. (2022) investigated the sensitivity of different reanalysis data (ERA-Interim and NCEP-CFSv2) on WRF dynamic downscaling for the South China Sea and found that the model forced with ERA-Interim data provides the best simulation of surface wind speed characteristics in the region.
In this study, we also used the latest ECMWF ERA5 data to drive the ocean model and found comparable results to those driven by the ERA-Interim data. This could be because they use similar physics schemes.
The primary focus of this study was to compare the response of the high-resolution coastal ocean model (less than 1 km horizontal resolution) results driven by the high-resolution WRF forcing with that driven by the widely used global reanalysis data, to demonstrate the benefits of using high-resolution atmospheric forcing. Therefore, we chose to compare the ocean response forced by our ultra-high-resolution (1 km horizontal resolution) WRF forcing with that by the relatively coarser ERA-Interim data.Reference:
Thankaswamy, A.; Xian, T.; Ma, Y.-F.; Wang, L.-P. Sensitivity to Different Reanalysis Data on WRF Dynamic Downscaling for South China Sea Wind Resource Estimations. Atmosphere 2022, 13, 771. https://doi.org/10.3390/atmos13050771Citation: https://doi.org/10.5194/egusphere-2023-318-AC1 - AC3: 'Reply on RC1', Wenfeng Lai, 09 Jun 2023
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AC5: 'Reply on RC1', Wenfeng Lai, 09 Jun 2023
Please check this link: https://editor.copernicus.org/index.php?_mdl=msover_md&_jrl=778&_lcm=oc108lcm109w&_acm=get_comm_sup_file&_ms=109814&c=245596&salt=13365367471420842352
Citation: https://doi.org/10.5194/egusphere-2023-318-AC5
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AC1: 'Reply on RC1', Wenfeng Lai, 29 Apr 2023
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RC2: 'Comment on egusphere-2023-318', Anonymous Referee #2, 09 May 2023
Lai and Gan 2023 analyse the variability of coastal circulation and dynamics in response to different atmospheric forcing during a period of downwelling-favorable winds. The analysis is similar to the one by the same authors (i.e. Lai and Gan 2022, cited) for upwelling winds (10-28th July 2015), while in this case they analyse a period of downwelling-favorable winds (5-23 July 2017). They analyse the sensitivity of the results to different spatio-temporal variable atmospheric forcing, namely 1) single station observation (WL-OBS), 2) global reanalysis data (LR-ERAI) and 3) high resolution regional atmospheric forcing (HR-WRFW with heatflux from ERAI and WRFA with heatflux from WRF) while in Lai and Gan 2022 they used 1) global reanalysis data, 2) high resolution regional atmospheric forcing and 3) air-sea coupled model. The results show that the model with high resolution forcing (and hence better representation of near-surface wind and air temperature) improved the simulation of coastal ocean currents, water temperature and salinity, and estimates of the across-isobath transport. The paper is well written and logically organized. The results are probably of interest for the community. I would suggest publication after minor revison.
Minor comments
It is not clear from the text whether heat flux is used in the simulations forced with observational data. In The methods it only mentions the wind, however on L324 it states ”…the heat flux forcing being the same in the WL-OBS, LR-ERAI, and HR-WRFW experiments…”
The authors used ERAI that has ~75km resolution and 6h resolution as forcing for the LR-ERAI case and as boundary and initial conditions for the production of the WRF 1km that is then used as forcing for the high-resolution cases. ERA5 is available at ECMWF for the period of interest and has higher temporal and spatial resolution (~30km and hourly resolution). A model forced with this higher resolution dataset (ERA5) may provide more accurate results.
Please rephrase L338 “A positive (negative) value represented an onshore (offshore) transport of the shelf water perpendicular to the isobaths”. Parenthesis are used to add extra information. The way the authors use them in the sentence can save a little of space but is confusing.
Please revise the colour schemes you use. The ones in figures 7, 8, 9 and 11 are not colour-blind friendly.
Citation: https://doi.org/10.5194/egusphere-2023-318-RC2 - AC2: 'Reply on RC2', Wenfeng Lai, 09 Jun 2023
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AC4: 'Reply on RC2', Wenfeng Lai, 09 Jun 2023
Please check this link: https://editor.copernicus.org/index.php?_mdl=msover_md&_jrl=778&_lcm=oc108lcm109w&_acm=get_comm_sup_file&_ms=109814&c=245594&salt=267814852887592822
Citation: https://doi.org/10.5194/egusphere-2023-318-AC4
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-318', Anonymous Referee #1, 19 Apr 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-318/egusphere-2023-318-RC1-supplement.pdf
-
AC1: 'Reply on RC1', Wenfeng Lai, 29 Apr 2023
Review of “Variability of coastal downwelling circulation in response to high-resolution regional atmospheric forcing off the Pearl River Estuary”
This paper by Lai and Gan investigated the variabilities of coastal circulation and dynamics in response to spatiotemporally variable high-resolution atmospheric forcing off the Pearl River Estuary during the downwelling wind. The authors conducted three numerical experiments based on (1) single station observation, (2) global reanalysis data and (3) high-resolution regional atmospheric model. Results show that the model with high-resolution atmospheric forcing significantly improved the temperature-salinity profiles and ocean current simulation. In addition, the model with high atmo-forcing improved the estimation of cross-isobath transport. This paper is well-written and organized, and the results are beneficial for ocean modeler to improve their model results and associated studies. I would suggest a minor revision for this paper before publishing it.
Reply: Thank you for your constructive comments. We appreciate the positive feedback and are pleased to know that our work is beneficial for ocean modelers. We hope that our revisions have adequately addressed the reviewer’s concerns.Major Comments:
(1) One of the comment problems in ocean model is the over-heating in the surface layer. Usually the ocean model needs surface temperature nudging to the reanalysis or climatology SST data, such as GHRSST and MODIS, to avoid over-heating in the surface layer. In this paper, the author mentioned that ROMS were forced by high-resolution wind stress and heat fluxes. I wonder whether ROMS model in this paper only driven by high-resolution heat fluxes without SST nudging, or only driven by high-resolution SST. Please clarify it in the discussion.Reply: We understand that the surface temperature nudging to reanalysis or climatology SST data in the ocean model is important. However, in this study, we did not apply additional surface temperature nudging to the reanalysis or climatology SST data to avoid response of the model to artificial forcing which could twist internal physical response of the model and smear our analysis. We conducted a short-term simulation, with the main driving forces being wind stress and bulk heat fluxes. Applying high-frequency SST nudging could potentially affect the physical dynamics.
Furthermore, in this coastal region, the accuracy of GHRSST and MODIS SST is highly questionable, and the variability of SST in this region is large, making it difficult to find high-quality SST data for the coastal area.(2) The author used the ERA data with 75 km resolution as the “coarse” resolution product to compared with the WRF 1 km production. Actually, in nowadays, the 12-15 km resolution and 0.2 degree (approximately 22 km) resolution products are quite common, and provided by ECWMF and CFSV2 (from NECP), respectively. Ocean model driven by this 10-20 km resolution products may be closed to that driven by WRF 1 km product. The author may give some comment on this.
Reply: We acknowledge that other relatively high-resolution datasets are available, such as the latest ERA5 data from ECMWF with a 0.25-degree resolution and the 0.2-degree products from CFSv2 from NCEP. However, different reanalysis datasets can have differences in spatial and temporal resolution, as well as in the way they assimilate observations and model data, leading to different influences on ocean model performance. Thankaswamy et al. (2022) investigated the sensitivity of different reanalysis data (ERA-Interim and NCEP-CFSv2) on WRF dynamic downscaling for the South China Sea and found that the model forced with ERA-Interim data provides the best simulation of surface wind speed characteristics in the region.
In this study, we also used the latest ECMWF ERA5 data to drive the ocean model and found comparable results to those driven by the ERA-Interim data. This could be because they use similar physics schemes.
The primary focus of this study was to compare the response of the high-resolution coastal ocean model (less than 1 km horizontal resolution) results driven by the high-resolution WRF forcing with that driven by the widely used global reanalysis data, to demonstrate the benefits of using high-resolution atmospheric forcing. Therefore, we chose to compare the ocean response forced by our ultra-high-resolution (1 km horizontal resolution) WRF forcing with that by the relatively coarser ERA-Interim data.Reference:
Thankaswamy, A.; Xian, T.; Ma, Y.-F.; Wang, L.-P. Sensitivity to Different Reanalysis Data on WRF Dynamic Downscaling for South China Sea Wind Resource Estimations. Atmosphere 2022, 13, 771. https://doi.org/10.3390/atmos13050771Citation: https://doi.org/10.5194/egusphere-2023-318-AC1 - AC3: 'Reply on RC1', Wenfeng Lai, 09 Jun 2023
-
AC5: 'Reply on RC1', Wenfeng Lai, 09 Jun 2023
Please check this link: https://editor.copernicus.org/index.php?_mdl=msover_md&_jrl=778&_lcm=oc108lcm109w&_acm=get_comm_sup_file&_ms=109814&c=245596&salt=13365367471420842352
Citation: https://doi.org/10.5194/egusphere-2023-318-AC5
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AC1: 'Reply on RC1', Wenfeng Lai, 29 Apr 2023
-
RC2: 'Comment on egusphere-2023-318', Anonymous Referee #2, 09 May 2023
Lai and Gan 2023 analyse the variability of coastal circulation and dynamics in response to different atmospheric forcing during a period of downwelling-favorable winds. The analysis is similar to the one by the same authors (i.e. Lai and Gan 2022, cited) for upwelling winds (10-28th July 2015), while in this case they analyse a period of downwelling-favorable winds (5-23 July 2017). They analyse the sensitivity of the results to different spatio-temporal variable atmospheric forcing, namely 1) single station observation (WL-OBS), 2) global reanalysis data (LR-ERAI) and 3) high resolution regional atmospheric forcing (HR-WRFW with heatflux from ERAI and WRFA with heatflux from WRF) while in Lai and Gan 2022 they used 1) global reanalysis data, 2) high resolution regional atmospheric forcing and 3) air-sea coupled model. The results show that the model with high resolution forcing (and hence better representation of near-surface wind and air temperature) improved the simulation of coastal ocean currents, water temperature and salinity, and estimates of the across-isobath transport. The paper is well written and logically organized. The results are probably of interest for the community. I would suggest publication after minor revison.
Minor comments
It is not clear from the text whether heat flux is used in the simulations forced with observational data. In The methods it only mentions the wind, however on L324 it states ”…the heat flux forcing being the same in the WL-OBS, LR-ERAI, and HR-WRFW experiments…”
The authors used ERAI that has ~75km resolution and 6h resolution as forcing for the LR-ERAI case and as boundary and initial conditions for the production of the WRF 1km that is then used as forcing for the high-resolution cases. ERA5 is available at ECMWF for the period of interest and has higher temporal and spatial resolution (~30km and hourly resolution). A model forced with this higher resolution dataset (ERA5) may provide more accurate results.
Please rephrase L338 “A positive (negative) value represented an onshore (offshore) transport of the shelf water perpendicular to the isobaths”. Parenthesis are used to add extra information. The way the authors use them in the sentence can save a little of space but is confusing.
Please revise the colour schemes you use. The ones in figures 7, 8, 9 and 11 are not colour-blind friendly.
Citation: https://doi.org/10.5194/egusphere-2023-318-RC2 - AC2: 'Reply on RC2', Wenfeng Lai, 09 Jun 2023
-
AC4: 'Reply on RC2', Wenfeng Lai, 09 Jun 2023
Please check this link: https://editor.copernicus.org/index.php?_mdl=msover_md&_jrl=778&_lcm=oc108lcm109w&_acm=get_comm_sup_file&_ms=109814&c=245594&salt=267814852887592822
Citation: https://doi.org/10.5194/egusphere-2023-318-AC4
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Wenfeng Lai
Jianping Gan
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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