The KMA Global Seasonal forecasting system (GloSea6) - Part 2: Climatological Mean Bias Characteristics
![]() |
Hyun, Yu-Kyung
(Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences)
Lee, Johan (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences) Shin, Beomcheol (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences) Choi, Yuna (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences) Kim, Ji-Yeong (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences) Lee, Sang-Min (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences) Ji, Hee-Sook (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences) Boo, Kyung-On (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences) Lim, Somin (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences) Kim, Hyeri (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences) Ryu, Young (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences) Park, Yeon-Hee (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences) Park, Hyeong-Sik (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences) Choo, Sung-Ho (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences) Hyun, Seung-Hwon (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences) Hwang, Seung-On (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences) |
1 | Hyun, Y.-K., J. Park, J. Lee, S. Lim, S.-I. Heo, H. Ham, S.-M. Lee, H.-S. Ji, and Y. Kim, 2020: Reliability assessment of temperature and precipitation seasonal probability in current climate prediction systems. Atmosphere, 30, 141-154, doi:10.14191/Atmos.2021.31.2.229 (in Korean with English abstract). DOI |
2 | Adler, F. A., and Coauthors, 2018: The Global Precipitation Climatology Project (GPCP) Monthly analysis (new version 2.3) and a review of 2017 global precipitation. Atmosphere, 9, 138, doi:10.3390/atmos9040138. DOI |
3 | Alberto, A., and Coauthors, 2011: The GloSea4 ensemble prediction system for seasonal forecasting. Mon. Wea. Rev., 139, 1891-1910, doi:10.1175/2010MWR3615.1. DOI |
4 | Boutle, I. A., S. J. Abel, P. G. Hill, and C. J. Morcrette, 2014: Spatial variability of liquid cloud and rain: observations and microphysical effects. Q. J. R. Meteorol. Soc., 140, 583-594, doi:10.1002/qj.2140. DOI |
5 | Davis, P., C. Ruth, A. A. Scaife, and J. Kettleborough, 2020: A large ensemble seasonal forecasting system: GloSea6. Abstract, AGU Fall Meeting 2020, #A192-05, American Geophysical Union. |
6 | Dee, D. P., and Coauthors, 2011: The ERA-interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc., 137, 553-597, doi:10.1002/qj.828. DOI |
7 | Kang, D., D. Kim, M.-S. Ahn, and S.-I. Ahn, 2021: The role of the background meridional moisture gradient on the propagation of the MJO over the Maritime Continent. J. Climate, 34, 6565-6581, doi:10.1175/JCLI-D-20-0085.1. DOI |
8 | KMA, 2015: Long-range Forecast Work Manual, Korea Meteorological Administration, 110 pp [Available online at http://book.kma.go.kr] (in Korean). |
9 | Kim, H., J. Lee, Y.-K. Hyun, and S.-O. Hwang, 2021a: The KMA Global Seasonal forecasting system (GloSea6) - Part 1: Operational system and improvements. Atmosphere, 31, 341-359, doi:10.14191/Atmos.2021.31.3. 341 (in Korean with English abstract). DOI |
10 | Kim, J.-Y., Y.-K. Hyun, J. Lee, and B.-C. Shin, 2021b: Assessment on the East Asian summer monsoon simulation by improved Global Coupled (GC) model. Atmosphere, 31, 563-576, doi:10.14191/Atmos.2021.31.5.563 (in Korean with English abstract). DOI |
11 | Lee, S.-J., Y.-K. Hyun, S.-M. Lee, S.-O. Hwang, J. Lee, and K.-O. Boo, 2020: Prediction skill for East Asian summer monsoon indices in a KMA Global Seasonal forecasting system (GloSea5). Atmosphere, 30, 293-309, doi:10.14191/Atmos.2020.30.3.293 (in Korean with English abstract). DOI |
12 | Lim, S., Y.-K. Hyun, H. Ji, and J. Lee, 2021: Application of land initialization and its impact in KMA's operational climate prediction system. Atmosphere, 31, 327-340, doi:10.14191/Atmos.2021.31.3.327 (in Korean with English abstract). DOI |
13 | MacLachlan C., and Coauthors, 2015: Global Seasonal forecast system version 5 (GloSea5): a high-resolution seasonal forecast system. Q. J. R. Meteorol. Soc., 141, 1072-1084, doi:10.1002/qj.2396. DOI |
14 | Park, Y.-H., Y.-K. Hyun, S.-I. Heo, and H.-S. Ji, 2021: Assessment of the prediction performance of ensemble size-related in GloSea5 hindcast data. Atmosphere, 31, 511-523, doi:10.14191/Atmos.2021.31.5.511 (in Korean with English abstract). DOI |
15 | Williams, K. D., and Coauthors, 2018: The Met Office Global Coupled Model 3.0 and 3.1 (GC3.0 and GC3.1) Configurations. J. Adv. Model. Earth Sys., 10, 357-380, doi:10.1002/2017MS001115. DOI |
16 | Rae, J. G. L., H. T. Hewitt, A. B. Keen, J. K. Ridley, A. E. West, C. M. Harris, E. C. Hunke, and D. N. Walters, 2015: Development of the Global Sea Ice 6.0 CICE configuration for the Met Office Global Coupled model. Geosci. Model Dev., 8, 2221-2230, doi:10.5194/gmd8-2221-2015. DOI |
17 | Kim, S.-W., H. Kim, K. Song, S.-W. Son, Y. Lim, H.-S. Kang, and Y.-K. Hyun, 2018: Subseasonal-to-seasonal (S2S) prediction skills of GloSea5 model: Part 1. Geopotential height in the Northern Hemisphere extratropics. Atmosphere, 28, 233-245, doi:10.14191/Atmos.2018.28.3.233 (in Korean with English abstract). DOI |
18 | Storkey, D., and Coauthors, 2018: UK Global Ocean GO6 and GO7: a traceable hierarchy of model resolutions. Geosci. Model Dev., 11, 3187-3213, doi:10.5194/gmd11-3187-2018. DOI |
19 | Waters, J., D. J. Lea, M. J. Martin, I. Mirouze, A. Weaver, and J. While, 2015: Implementing a variational data assimilation system in an operational 1/4 degree global ocean model. Q. J. R. Meteorol. Soc., 141, 333-349, doi:10.1002/qj.2388. DOI |
20 | Walters, D., and Coauthors, 2019: The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations. Geosci. Model Dev., 12, 1909-1963. DOI |
21 | Seo, E., M.-I., and Coauthors, 2019: Impact of soil moisture initialization on boreal summer subseasonal forecasts: mid-latitude surface air temperature and heat wave events. Climate Dyn., 52, 1695-1709, doi:10.1007/s00382-018-4221-4. DOI |
22 | Ahn, M.-S., D. Kim, D. Kang, J. Lee, K. R. Sperber, P. J. Gleckler, X. Jiang, Y.-G. Ham, and H. Kim, 2020: MJO propagation across the Maritime Continent: Are CMIP6 models better than CMIP5 models? Geophys. Res. Lett., 47, e2020GL087250, doi:10.1029/2020GL087250. DOI |
23 | Megann, A., D. Storkey, Y. Aksenov, S. Alderson, D. Calvert, T. Graham, P. Hyder, J. Siddorn, and B. Sinha, 2014: GO5.0: the joint NERC-Met Office NEMO global ocean model for use in coupled and forced applications. Geosci. Model Dev., 7, 1069-1092, doi:10.5194/gmd-7-1069-2014. DOI |
24 | Chang, P.-H., S.-O. Hwang, S.-H. Choo, J. Lee, S.-M. Lee, and K.-O. Boo, 2021: Global Ocean Data Assimilation and Prediction System in KMA: Description and assessment. Atmosphere, 31, 229-240, doi:10.14191/Atmos.2021.31.2.229 (in Korean with English abstract). DOI |
25 | Gonzalez, A. O., and X. Jiang, 2017: Winter mean lower tropospheric moisture over the Maritime Continent as a climate model diagnostic metric for the propagation of the Madden-Julian oscillation. Geophys. Res. Lett., 44, 2588-2596, doi:10.1002/2016GL072430. DOI |
26 | Kim, H., M. A. Janiga, and K. Pegion, 2019: MJO propagation processes and mean biases in the SubX and S2S reforecasts. J. Geophys. Res. Atmos., 124, 9314-9331, doi:10.1029/2019JD031139. DOI |
27 | Rayner, N. A., D. E. Parker, E. B. Horton, C. K. Folland, L. V. Alexander, D. P. Rowell, E. C. Kent, and A. Kaplan, 2003: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res., Atmos., 108, 4407, doi:10.1029/2002JD002670. DOI |
28 | Ridley, J. K., E. W. Blockley, A. B. Keen, J. G. L. Rae, A. E. West, and D. Schroeder, 2018: The sea ice model component of HadGEM3-GC3.1. Geosci. Model Dev., 11, 713-723, doi:10.5194/gmd-11-713-2018. DOI |
29 | Scaife, A. A., and Coauthors, 2014: Skillful long-range prediction of European and North American winters. Geophys. Res. Lett., 41, 2514-2519, doi:10.1002/2014GL059637. DOI |
30 | Seo, E., M.-I. Lee, J.-H. Jeong, H.-S. Kang, and D.-J. Won, 2016: Improvement of soil moisture initialization for a global seasonal forecast system. Atmosphere, 26, 35-45, doi:10.14191/Atmos.2016.26.1.035 (in Korean with English abstract). DOI |
31 | Walters, D., and Coauthors, 2017: The Met Office Unified Model Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations. Geosci. Model Dev., 10, 1487-1520, doi:10.5194/gmd-10-1487-2017. DOI |
32 | Yang, Y.-M., T. Shim, J.-Y. Moon, K.-Y. Kim, and Y.-K. Hyun, 2021: Diagnosing ISO Forecast from GloSea5 Using Dynamic-Oriented ISO Theory. Atmosphere, 12, 114, doi:10.3390/atmos12010114. DOI |
![]() |