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한국형 수치예보모델 기반의 화산재 확산 예측시스템 구축 및 사례검증

A Case Study of the Forecasting Volcanic Ash Dispersion Using Korea Integrated Model-based HYSPLIT

신승숙|강현석|강미선|이우정
한국기상학회 (Korean Meteorological Society)|2024.05|대기 (Atmosphere)|제34권 제2호|pp. 217-231|DOI 10.14191/Atmos.2024.34.2.217

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키워드

Volcanic ashKorea integrated modelHYSPLIT modelDispersion model
주제분류대기과학

초록

The Korea Integrated Model (KIM)-based real-time volcanic ash dispersion prediction system, which employs the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, has been developed to quantitatively predict volcanic ash dispersion in East Asia and the Northwest Pacific airspace. This system, known as KIM-HYSPLIT, automatically generates forecasts for the vertical and horizontal spread of volcanic ash up to 72 hours. These forecasts are initiated upon the receipt of a Volcanic Ash Advisory (VAA) from the Tokyo Volcanic Ash Advisory Center by the server at the Korea Meteorological Administration (KMA). This system equips KMA forecasters with diverse volcanic ash prediction information, complemented by the Unified Model (UM)-based HYSPLIT (UM-HYSPLIT) system. Extensive experiments have been conducted using KIM-HYSPLIT across 128 different volcanic scenarios, along with qualitative comparisons with UM-HYSPLIT. The results indicate that the ash direction predictions from KIM-HYSPLIT are consistent with those from UM-HYSPLIT. However, there are slight differences in the horizontal extent and movement speed of the volcanic ash. Additionally, quantitative verifications of the KIM-HYSPLIT forecasts have been performed, including threat score evaluations, based on recent eruption cases. On average, the KIMHYSPLIT forecasts for 6 and 12 hours show better quantitative alignment with the VAA forecasts compared to UM-HYSPLIT. Nevertheless, both models tend to predict a broader horizontal spread of the ash cloud than indicated in the VAA forecasts, particularly noticeable in the 6- hour forecast period.

Abstract

The Korea Integrated Model (KIM)-based real-time volcanic ash dispersion prediction system, which employs the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, has been developed to quantitatively predict volcanic ash dispersion in East Asia and the Northwest Pacific airspace. This system, known as KIM-HYSPLIT, automatically generates forecasts for the vertical and horizontal spread of volcanic ash up to 72 hours. These forecasts are initiated upon the receipt of a Volcanic Ash Advisory (VAA) from the Tokyo Volcanic Ash Advisory Center by the server at the Korea Meteorological Administration (KMA). This system equips KMA forecasters with diverse volcanic ash prediction information, complemented by the Unified Model (UM)-based HYSPLIT (UM-HYSPLIT) system. Extensive experiments have been conducted using KIM-HYSPLIT across 128 different volcanic scenarios, along with qualitative comparisons with UM-HYSPLIT. The results indicate that the ash direction predictions from KIM-HYSPLIT are consistent with those from UM-HYSPLIT. However, there are slight differences in the horizontal extent and movement speed of the volcanic ash. Additionally, quantitative verifications of the KIM-HYSPLIT forecasts have been performed, including threat score evaluations, based on recent eruption cases. On average, the KIMHYSPLIT forecasts for 6 and 12 hours show better quantitative alignment with the VAA forecasts compared to UM-HYSPLIT. Nevertheless, both models tend to predict a broader horizontal spread of the ash cloud than indicated in the VAA forecasts, particularly noticeable in the 6- hour forecast period.

참고문헌 (51)

  1. Beckett, F. M., "Atmospheric dispersion modelling at the London VAAC : A review of developments since the 2010 eyjafjallajökull volcano ash cloud", Atmosphere, 11, pp.352~ (2020)[DOI]
  2. Bessho, K., "An introduction to Himawari-8", 9—Japan’s new-generation geostationary meteorological satellites, 2016, pp.94, 151~183
  3. Blake, S., "Correlations between eruption magnitude, SO2 yield, and surface cooling", Geological Society, London, Special Publications, 213, pp.371~380 (2003)[DOI]
  4. Chen, B., "Air pollution and population health : a global challenge", Environ. Health Prev. Med, 13, pp.94~101 (2008)[DOI]
  5. Chen, S., "Volcanic Eruptions and their impacts in the Past 13, 000 years", Highlights in Sci., Eng. Technol, 50, pp.233~240 (2023)[DOI]
  6. Cole-Dai, J., "Volcanoes and climate", Wiley Interdisciplinary Reviews. Climate Change, 1, pp.824~839 (2010)[DOI]
  7. Crawford, A. M., "Initializing HYSPLIT with satellite observations of volcanic ash : A case study of the 2008 Kasatochi eruption", J. Geophys. Res. Atmospheres, 121, pp.10786~10803 (2016)[DOI]
  8. Crawford, A., "Evaluation and bias correction of probabilistic volcanic ash forecasts", Atmos. Chem. Phys, 22, pp.13967~13996 (2022)[DOI]
  9. Dare, R. A., "Ensemble prediction of the dispersion of volcanic ash from the 13 February 2014 eruption of kelut, Indonesia", J. Appl. Meteor Climatol (2016)[DOI]
  10. Dogan, G. G., "Global propagation of air pressure waves and consequent ocean waves due to the January 2022 Hunga Tonga-Hunga Ha'apai eruption", Ocean Eng, 267, pp.113174~ (2023)[DOI]
  11. HYSPLIT4 User’s Guide, "Draxler, R. R.", NOAA, 38~, pp.NOAA Tech. Memo. ERL ARL-230 (1999)
  12. Engwell, S., "Near-real-time volcanic cloud monitoring : insights into global explosive volcanic eruptive activity through analysis of Volcanic Ash Advisories", Bull. Volcanology, 83, pp.1~17 (2021)[DOI]
  13. Gudmundsson, M. T., "Eruptions of Eyjafjallajökull Volcano, Iceland", Eos Trans. AGU, 91, pp.190~191 (2010)[DOI]
  14. Guffanti, M., "Volcanic-ash hazard to aviation during the 2003~2004 eruptive activity of Anatahan volcano, Commonwealth of the Northern Mariana Islands", J. Volcanology and Geothermal Res, 146, pp.241~255 (2005)[DOI]
  15. Han, J. -Y., "The performance of a revised simplified Arakawa-Schubert(SAS)convection scheme in the medium-range forecasts of the Korean Integrated Model(KIM)", Wea. Forecasting, 35, pp.1113~1128 (2020)[DOI]
  16. Hansell, A. L., "The health hazards of volcanoes and geothermal areas", Occup. Environ. Med, 63, pp.149~156 (2006)[DOI]
  17. Hasegawa, Y., "Improvements of volcanic ash fall forecasts issued by the Japan Meteorological Agency", J. Applied Volcanology, 4, pp.1~12 (2015)[DOI]
  18. Hong, S. -Y., "The Korean Integrated Model(KIM)system for global weather forecasting", Asia-Pac. J. Atmos. Sci, 54, pp.267~292 (2018)[DOI]
  19. Hurst, T., "Forecasting volcanic ash deposition using HYSPLIT", J. Appl. Volcanology, 6, pp.1~8 (2017)[DOI]
  20. "Korea’s COMS satellite has been captured Italian volcanic gas" (2021)[URL]
  21. Igarashi, Y., "A dv s. Volcanology", pp.529~547 (2018)
  22. Research on application and support for the earthquake and volcanic service (I): Improvement of volcanic eruption rate for ash diffusion model, "KMA", Korea Meteorological Administration, 88~95 (2018)
  23. KMA, "Working-level Manual on crisis response of large volcanic eruptions", Korea Meteorological Administration, ~ (2023)
  24. KMA, "Verification of numerical weather forecasting system (2022)", Korea Meteorological Administration, 5~6 (2023)
  25. "Earthquake and volcano notification standard" (2024)[URL]
  26. Kwon, Y. C., "Numerical Wea. Prediction:East Asian Perspectives", pp.105~123 (2023)
  27. Lechner, P., "Advs in Volcanology", pp.51~64 (2018)
  28. Lee, S. -K., "A case study of the 17 Sep, 2013 eruption in SAKURAJIMA volcano", J. Remote Sens, 30, pp.303~314 (2014)[DOI]
  29. Lee, W. -J., "Numerical weather prediction and forecast application", Atmosphere, 33, pp.73~104 (2023)[DOI]
  30. Marshall, L. R., "Volcanic effects on climate : recent advances and future avenues", Bull. Volcanology, 84, pp.54~ (2022)[DOI]
  31. Mastin, L. G., "A multidisciplinary effort to assign realistic source parameters to models of volcanic ash-cloud transport and dispersion during eruptions", J. Volcanology and Geothermal Res, 186, pp.10~21 (2009)[DOI]
  32. Mbizvo, G. K., "Critical success index or F measure to validate the accuracy of administrative healthcare data identifying epilepsy in deceased adults in Scotland", Epilepsy Res, 199, pp.107275~ (2024)[DOI]
  33. Müller, D., "Mineralogical and thermal characterization of a volcanic ash : Implications for turbine interaction", J. Volcanology and Geothermal Res, 377, pp.43~52 (2019)[DOI]
  34. Murray, S. A., "The importance of ensemble techniques for operational space weather forecasting", Space Wea, 16, pp.777~783 (2018)[DOI]
  35. Developing Technology for Asian Dust and Haze Monitoring and prediction, "NIMS", National Institute of Meteorological Sciences, 24~28 (2020)
  36. Developing Technology for Asian Dust and Haze Monitoring and prediction, "NIMS", National Institute of Meteorological Sciences, 115~, pp.National Institute of Meteorological Sciences Report No. 11-1360620-000168-10 (2021)
  37. "HYSPLIT Tutorial September 2019 (Version 4.2.0)" (2024)[URL]
  38. "NOAA READY News" (2024)[URL]
  39. Prata, A. J., "Retrieval of microphysical and morphological properties of volcanic ash plumes from satellite data: Application to Mt. Ruapehu, New Zealand", Quart. J. Roy. Meteor. Soc, 127, pp.2153~2179 (2001)[DOI]
  40. Sato, E., "Aso volcano eruption on October 8, 2016, observed by weather radars", Earth, Planets and Space, 70, pp.1~8 (2018)[DOI]
  41. Schaefer, J. T., "The critical success index as an indicator of warning skill", Wea. Forecasting, 5, pp.570~575 (1990)[DOI]
  42. Shirato, S., "Volcanic Ash Advisories", Volcanic Hazard Maps of Japan, ~ (2013)
  43. Simpson, J. J., "Failures in detecting volcanic ash from a satellitebased technique, Remote Sens", Environ, 72, pp.191~217 (2000)[DOI]
  44. Stein, A. F., "NOAA’s HYSPLIT atmospheric transport and dispersion modeling system", Bull. Amer. Meteor. Soc, 96, pp.2059~2077 (2015)[DOI]
  45. Stunder, B. J. B., "Airborne volcanic ash forecast area reliability", Wea. Forecasting, 22, pp.1132~1139 (2007)[DOI]
  46. Sun, J., "Analysis of Japanese volcanic ash dispersion on the Korean Peninsula using satellite imagery", J. the Korean Soc. Hazard Mitigation, 20, pp.269~275 (2020)[DOI]
  47. Timmreck, C., "Modeling the climatic effects of large explosive volcanic eruptions", Wiley Interdiscip. Rev. Clim. Change, 3, pp.545~564 (2012)[DOI]
  48. Toulkeridis, T., "Wind directions of volcanic ash-charged clouds in Ecuador-implications for the public and flight safety", Geomatics, Nat. Hazards and Risk, 8, pp.242~256 (2017)[DOI]
  49. Trancoso, R., "Towards real-time probabilistic ash deposition forecasting for New Zealand", J. Appl. Volcanology, 11, pp.13~ (2022)[DOI]
  50. Zhu, Y., "Ensemble forecast : A new approach to uncertainty and predictability", Adv. Atmos. Sci, 22, pp.781~788 (2005)[DOI]
  51. Zidikheri, M. J., "Estimation of optimal dispersion model source parameters using satellite detections of volcanic ash", J. Geophys. Res. Atmos, 122, pp.8207~8232 (2017)[DOI]

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