본문 바로가기
KERD
논문KCI 등재

기상청 기후예측시스템(GloSea6-GC3.2)의 열대저기압 계절 예측 특성

The Seasonal Forecast Characteristics of Tropical Cyclones from the KMA’s Global Seasonal Forecasting System (GloSea6-GC3.2)

0

조회

0

다운로드

1

인용

0

참고문헌

키워드

주제분류대기과학

초록

The seasonal forecast skill of tropical cyclones (TCs) in the Northern Hemisphere from the Korea Meteorological Administration (KMA) Global Seasonal Forecast System version 6 (GloSea6) hindcast has been verified for the period 1993 to 2016. The operational climate prediction system at KMA was upgraded from GloSea5 to GloSea6 in 2022, therefore further validation was warranted for the seasonal predictability and variability of this new system for TC forecasts. In this study, we examine the frequency, track density, duration, and strength of TCs in the North Indian Ocean, the western North Pacific, the eastern North Pacific, and the North Atlantic against the best track data. This methodology follows a previous study covering the period 1996 to 2009 published in 2020. GloSea6 indicates a higher frequency of TC generation compared to observations in the western North Pacific and the eastern North Pacific, suggesting the possibility of more TC generation than GloSea5. Additionally, GloSea6 exhibits better interannual variability of TC frequency, which shows relatively good correlation with observations in the North Atlantic and the western North Pacific. Regarding TC intensity, GloSea6 still underestimates the minimum surface pressures and maximum wind speeds from TCs, as is common among most climate models due to lower horizontal resolutions. However, GloSea6 is likely capable of simulating slightly stronger TCs than GloSea5, partly attributed to more frequent 6-hourly outputs compared to the previous daily outputs.

Abstract

The seasonal forecast skill of tropical cyclones (TCs) in the Northern Hemisphere from the Korea Meteorological Administration (KMA) Global Seasonal Forecast System version 6 (GloSea6) hindcast has been verified for the period 1993 to 2016. The operational climate prediction system at KMA was upgraded from GloSea5 to GloSea6 in 2022, therefore further validation was warranted for the seasonal predictability and variability of this new system for TC forecasts. In this study, we examine the frequency, track density, duration, and strength of TCs in the North Indian Ocean, the western North Pacific, the eastern North Pacific, and the North Atlantic against the best track data. This methodology follows a previous study covering the period 1996 to 2009 published in 2020. GloSea6 indicates a higher frequency of TC generation compared to observations in the western North Pacific and the eastern North Pacific, suggesting the possibility of more TC generation than GloSea5. Additionally, GloSea6 exhibits better interannual variability of TC frequency, which shows relatively good correlation with observations in the North Atlantic and the western North Pacific. Regarding TC intensity, GloSea6 still underestimates the minimum surface pressures and maximum wind speeds from TCs, as is common among most climate models due to lower horizontal resolutions. However, GloSea6 is likely capable of simulating slightly stronger TCs than GloSea5, partly attributed to more frequent 6-hourly outputs compared to the previous daily outputs.

참고문헌 (21)

  1. Ahn, S. -H., "The characteristics of the frequency and damage for meteorological disasters in Korea", J. Korean Soc. Hazard Mitig, 15, pp.133~144 (2015)[DOI]
  2. Basconcillo, J., "Increasing peak intensity of tropical cyclones passing through the Korean Peninsula", Sci. Rep, 13, pp.5097~ (2023)[DOI]
  3. Bengtsson, L., "How may tropical cyclones change in a warmer climate?", Tellus A, 59, pp.539~561 (2007)[DOI]
  4. Camargo, S. J., "Global and regional aspects of tropical cyclone activity in the CMIP5 models", J. Climate, 26, pp.9880~9902 (2013)[DOI]
  5. Camargo, S. J., "An update on the influence of natural climate variability and anthropogenic climate change on tropical cyclones", Trop. Cyclone Res. Rev, 12, pp.216~239 (2023)[DOI]
  6. Camp, J., "Seasonal forecasting of tropical storms using the Met Office GloSea5 seasonal forecast system", Quart. J. Roy. Meteorol. Soc, 141, pp.2206~2219 (2015)[DOI]
  7. Ho, C. -H., "Review of the weather hazard research : Focused on typhoon, heavy rain, drought, heat wave, cold surge, heavy snow, and strong gust", Atmosphere, 33, pp.223~246 (2023)[DOI]
  8. Hodges, K. I., "Adaptive constraints for feature tracking", Mon. Wea. Rev, 127, pp.1362~1373 (1999)[DOI]
  9. Hyun, Y. -K., "The KMA global seasonal forecasting system(GloSea6)-part 2 : climatological mean bias characteristics", Atmosphere, 32, pp.87~101 (2022)[DOI]
  10. Kang, H., "A Study on the time-periodic characteristics of changes in typhoon activities and typhoon-induced rainfall over the Korean peninsula", J. Korean. Soc. Hazard Mitig, 18, pp.395~402 (2018)[DOI]
  11. Kim, H., "The KMA Global Seasonal forecasting system(GloSea6)-Part 1 : Operational system and improvements", Atmosphere, 31, pp.341~359 (2021)[DOI]
  12. Kim, H. -S., "Tropical cyclone simulation and response to CO2 doubling in the GFDL CM2.5 high-resolution coupled climate model", J. Climate, 27, pp.8034~8054 (2014)[DOI]
  13. Kim, J., "Algorithms for determining Korea Meteorological Administration(KMA)’s official typhoon best tracks in the National Typhoon Center", Atmosphere, 32, pp.381~394 (2022)[DOI]
  14. Landsea, C. W., "Atlantic hurricane database uncertainty and presentation of a new database format", Mon. Wea. Rev, 141, pp.3576~3592 (2013)[DOI]
  15. Lee, S. -M., "Seasonal Forecasting of Tropical Storms using GloSea5 Hindcast", Atmosphere, 30, pp.209~220 (2020)[DOI]
  16. Na, H., "Autumn Typhoon Affecting the Korean Peninsula-Past and present characteristics", J. Korean Soc. Atmos. Environ, 36, pp.482~491 (2020)[DOI]
  17. Park, D. -S. R., "Sea surface temperature warming to inhibit mitigation of tropical cyclone destructiveness over East Asia in El Niño", Npj. Clim. Atmos. Sci, 7, pp.24~ (2024)[DOI]
  18. Strachan, J., "Investigating global tropical cyclone activity with a hierarchy of AGCMs : The role of model resolution", J. Climate, 26, pp.133~152 (2013)[DOI]
  19. Utsumi, N., "Observed influence of anthropogenic climate change on tropical cyclone heavy rainfall", Nat. Clim. Chang, 12, pp.436~440 (2022)[DOI]
  20. Walters, D. N., "The Met Office Unified Model Global Atmosphere 7.0", 7.1 and JULES Global Land 7.0 configurations, 2019, pp.12, 1909~1963
  21. "WMO atlas of mortality and economic losses from weather, climate and water extremes (1970~2019). WMO-No. 1267" (2021)[URL]

관련 논문AI추천

이 간행물의 다른 논문 (9건)