Skip to main content
Log in

Surface wind gust prediction over Incheon international airport using the unified model

  • Original Paper
  • Published:
Natural Hazards Aims and scope Submit manuscript

Abstract

The unified model (Version: UM10.4) wind gust prediction system using rose nesting suite at 300 m resolution over the Incheon international airport (IIA) is carried out, and the prediction results of multiple domain nesting with input initial and lateral boundary conditions from the Korea meteorological administration (KMA) operational global data assimilation and prediction system (GDAPS) are compared with the operational local data assimilation and prediction system and the observed automated weather stations (AWS) dataset. The 300 m nested prediction system over the IIA is built from the 17 km GDAPS output in KMA; it is downscaled with a multiple nesting domains to 300 m resolution from the GDAPS, here after called as IIA-300 m. The model results are validated against the AWS to see the accuracy of the IIA-300 m model’s skill in predicting the wind gust over the IIA. The nesting suite is run with the default ancillary files created by the central ancillary program 9.0 (CAP 9.0) as well as modified ancillary files created by modifying the land points over IIA region using an ancillary editor. The UM model wind prediction is done with both ancillary files to see the improvements achieved by adding additional land points over the IIA domain. Further the vegetation fraction from the international geosphere-biosphere program (IGBP) data classified as 9 tiles in the ancillary file is replaced by the environmental-geographic information system (E-GIS) data to see the effect on the UM model’s wind gust predictions. The prediction of two wind gust events on 30-August-2016 and 02-October-2016 reveals only modest improvements in the prediction with respect to AWS observations, even after the modification of ancillaries with land points over the IIA domain, and only minor improvements are noted for the vegetation fraction replacement from IGBP to E-GIS vegetation dataset over the Incheon International Airport and exhibited only a marginal wind speed decrease due to warming up of the land part, particularly on the peripheries of the IIA-domain.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others

References

Download references

Acknowledgements

This work is supported by the "Research and Development for KMA Weather, Climate, and Earth System Services" of National Institute of Meteorological Sciences (NIMS). Authors would like to sincerely thank Joao Teixeira of UK Met Office for his guidance in fixing model errors. Authors would also like to thank the anonymous reviewers and Editor for reviewing the manuscript.

Author information

Authors and Affiliations

Authors

Contributions

VP conceived the work plan, conducted model experiments, performed diagnostics and prepared the manuscript, HWC and SOH provided support for model experiments, GHK provided support for diagnostics and finally YGL and BJK provided comments for improving the manuscript.

Corresponding author

Correspondence to Venkatraman Prasanna.

Ethics declarations

Conflict of interest

The authors have no potential conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Prasanna, V., Choi, H.W., Hong, S.O.K. et al. Surface wind gust prediction over Incheon international airport using the unified model. Nat Hazards 103, 1499–1535 (2020). https://doi.org/10.1007/s11069-020-04047-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11069-020-04047-z

Keywords

Navigation