Subseasonal-to-Seasonal (S2S) Prediction Skills of GloSea5 Model: Part 1. Geopotential Height in the Northern Hemisphere Extratropics
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Kim, Sang-Wook
(School of Earth and Environmental Sciences, Seoul National University)
Kim, Hera (School of Earth and Environmental Sciences, Seoul National University) Song, Kanghyun (School of Earth and Environmental Sciences, Seoul National University) Son, Seok-Woo (School of Earth and Environmental Sciences, Seoul National University) Lim, Yuna (School of Earth and Environmental Sciences, Seoul National University) Kang, Hyun-Suk (Earth System Research Division, National Institute of Meteorological Sciences) Hyun, Yu-Kyung (Earth System Research Division, National Institute of Meteorological Sciences) |
1 | Choi, J., S.-W. Son, Y.-G. Ham, J.-Y. Lee, and H.-M. Kim, 2016: Seasonal-to-interannual prediction skills of near-surface air temperature in the CMIP5 decadal hindcast experiments. J. Climate, 29, 1511-1527. DOI |
2 | Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis:configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553-597, doi:10.1002/qj.828. DOI |
3 | Goddard, L., and Coauthors, 2013: A verification framework for interannual-to-decadal predictions experiments. Climate Dyn., 40, 245-272, doi:10.1007/s00382-012-1481-2. DOI |
4 | Gupta, A. S., N. C. Jourdain, J. N. Brown, and D. Monselesan, 2013: Climate drift in the CMIP5 models. J. Climate, 26, 8597-8615, doi:10.1175/JCLI-D-12-00521.1. DOI |
5 | Jung, M.-I., S.-W. Son, J. Choi, and H.-S. Kang, 2015:Assessment of 6-month lead prediction skill of the GloSea5 hindcast experiment. Atmosphere, 25, 323-337, doi:10.14191/Atmos.2015.25.2.323 (in Korean with English abstract). DOI |
6 | Jung, M.-I., S.-W. Son, Y. Lim, K. Song, D. J. Won, and H.-S. Kang, 2016: Assessment of stratospheric prediction skill of the GloSea5 hindcast experiment. Atmosphere, 26, 203-214, doi:10.14191/Atmos.2016.26.1.203 (in Korean with English abstract). DOI |
7 | Kobayashi, S., and Coauthors, 2015: The JRA-55 Reanalysis:General specifications and basic characteristics. J. Meteor. Soc. Japan, 93, 5-48, doi:10.2151/jmsj.2015-001. DOI |
8 | Lee, S.-M., H.-S. Kang, Y.-H. Kim, Y.-H. Byun, and C. Cho, 2016: Verification and comparison of forecast skill between global seasonal forecasting system version 5 and unified model during 2014. Atmosphere, 26, 59-72, doi:10.14191/Atmos.2016.26.1.059 (in Korean with English abstract). DOI |
9 | MacLachlan, C., and Coaurhors, 2015: Global seasonal forecast system version 5 (GloSea5): a high-resolution seasonal forecast system. Quart. J. Roy. Meteor. Soc., 141, 1072-1084, doi:10.1002/qj.2396. DOI |
10 | Madec, G., 2008: NEMO ocean engine. IPSL Tech. Rep. 27, 401 pp. |
11 | Murphy, A. H., 1988: Skill scores based on the mean square error and their relationships to the correlation coefficient. Mon. Wea. Rev., 116, 2417-2424. DOI |
12 | Palmer, T. N., and D. L. T. Anderson, 1994: The prospects for seasonal forecasting-A review paper. Q. J. R. Meteor. Soc., 120, 755-793. |
13 | Persson, A., 2015: User guide to ECMWF forecast products Ver. 1.2. ECMWF, 129 pp. |
14 | Tripathi, O. P., and Coauthors, 2015: The predictability of the extratropical stratosphere on monthly time-scales and its impact on the skill of tropospheric forecasts. Quart. J. Roy. Meteor. Soc., 141, 987-1003, doi:10.1002/qj.2432. DOI |
15 | 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/gmd-8-2221-2015. DOI |
16 | Song, K., H. Kim, S.-W. Son, S.-W. Kim, H.-S. Kang, and Y.-K. Hyun, 2018: Subseasonal-to-Seasonal (S2S) prediction of GloSea5 model: Part 2. Stratospheric sudden warming. Atmosphere, 28, 123-139, doi:10.14191/Atmos.2018.28.2.123 (in Korean with English abstract). |
17 | Stan, C., and D. M. Straus, 2009: Stratospheric predictability and sudden stratospheric warming events. J. Geophys. Res., 114, D12103. DOI |
18 | Vitart, F., and Coaurhors, 2017: The Subseasonal to Seasonal (S2S) prediction project database. Bull. Amer. Meteor. Soc., 98, 163-173, doi:10.1175/BAMS-D-16-0017.1. DOI |
19 | Walters, D., and Coaurhors, 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 |
20 | Williams, K. D., and Coauthors, 2015: The Met Office Global Coupled model 2.0 (GC2) configuration. Geosci. Model Dev., 8, 1509-1524, doi:10.5194/gmd-8-1509-2015. DOI |
21 | WMO, 2006: Standardised verification system (SVS) for long-range forecasts (LRF). [Available online at https://www.wmo.int/pages/prog/www/DPS/LRF/ATTACHII-8SVSfrom%20WMO_485_Vol_I.pdf ]. |
22 | WMO, 2013: Sub-seasonal to seasonal prediction research implementation plan. [Available online at https://www.wmo.int/pages/prog/arep/wwrp/new/documents/S2S_Implem_plan_en.pdf]. |
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