Browse > Article
http://dx.doi.org/10.14191/Atmos.2021.31.2.215

Evaluation of Sea Surface Temperature Prediction Skill around the Korean Peninsula in GloSea5 Hindcast: Improvement with Bias Correction  

Gang, Dong-Woo (School of Earth and Environmental Sciences, Seoul National University)
Cho, Hyeong-Oh (School of Earth and Environmental Sciences, Seoul National University)
Son, Seok-Woo (School of Earth and Environmental Sciences, Seoul National University)
Lee, Johan (Operational Systems Development Department, National Institute of Meteorological Sciences)
Hyun, Yu-Kyung (Operational Systems Development Department, National Institute of Meteorological Sciences)
Boo, Kyung-On (Operational Systems Development Department, National Institute of Meteorological Sciences)
Publication Information
Atmosphere / v.31, no.2, 2021 , pp. 215-227 More about this Journal
Abstract
The necessity of the prediction on the Seasonal-to-Subseasonal (S2S) timescale continues to rise. It led a series of studies on the S2S prediction models, including the Global Seasonal Forecasting System Version 5 (GloSea5) of the Korea Meteorological Administration. By extending previous studies, the present study documents sea surface temperature (SST) prediction skill around the Korean peninsula in the GloSea5 hindcast over the period of 1991~2010. The overall SST prediction skill is about a week except for the regions where SST is not well captured at the initialized date. This limited prediction skill is partly due to the model mean biases which vary substantially from season to season. When such biases are systematically removed on daily and seasonal time scales the SST prediction skill is improved to 15 days. This improvement is mostly due to the reduced error associated with internal SST variability during model integrations. This result suggests that SST around the Korean peninsula can be reliably predicted with appropriate post-processing.
Keywords
GloSea5; SST; prediction skill; bias correction; S2S;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 Vitart, F., and Coauthors, 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
2 Luo, J.-J., S. Masson, S. K. Behera, and T. Yamagata, 2008: Extended ENSO predictions using a fully coupled ocean-atmosphere model. J. Climate, 21, 84-93, doi:10.1175/2007JCLI1412.1.   DOI
3 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
4 Moon, Y.-I., H.-H. Kwon, and D.-K. Kim, 2005: A study of relationships between the sea surface temperatures and rainfall in Korea. J. Korea Water Resour. Assoc., 38, 995-1008 (in Korean with English abstract).   DOI
5 Murphy, A. H., and E. S. Epstein, 1989: Skill scores and correlation coefficients in model verification. Mon. Wea. Rev., 117, 572-582.   DOI
6 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
7 Ahn, J.-B., J.-H. Ryu, E.-H. Cho, J.-Y. Park, and S.-B. Ryoo, 1997: A study of correlations between air-temperature and precipitation of Korea and SST around Korean peninsula. J. Korean Meteor. Soc., 33, 327-336 (in Korean with English abstract).
8 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:10.1175/JCLI-D-15-0182.1.   DOI
9 Best, M. J., and Coauthors, 2011: The Joint UK Land Environment Simulator (JULES), model description - Part 1: energy and water fluxes. Geosci. Model Dev., 4, 677-699, doi:10.5194/gmd-4-677-2011.   DOI
10 Brown, A., S. Milton, M. Cullen, B. Golding, J. Mitchell, and A. Shelly, 2012: Unified modeling and prediction of weather and climate: A 25-year journey. Bull. Amer. Meteor. Soc., 93, 1865-1877, doi:10.1175/BAMS-D-12-00018.1.   DOI
11 Gupta, A. S., L. C. Muir, J. N. Brown, S. J. Phipps, P. J. Durack, D. Monselesan, and S. E. Wijffels, 2012: Climate drift in the CMIP3 models. J. Climate, 25, 4621-4640, doi:10.1175/JCLI-D-11-00312.1.   DOI
12 Han, Y.-J., H.-J. Lee, J.-W. Kim, J.-Y. Koo, and Y.-G. Lee, 2019: A study of the influence of short-term air-sea Interaction on precipitation over the Korean peninsula using atmosphere-ocean coupled model. J. Korean Earth Sci. Soc., 40, 584-598 (in Korean with English abstract).   DOI
13 Jeong, Y. Y., I.-J. Moon, and P.-H.Chang, 2016: Accuracy of short-term ocean prediction and the effect of atmosphere-ocean coupling on KMA global seasonal forecast system (GloSea5) during the development of ocean stratification. Atmosphere, 26, 599-615, doi: 10.14191/Atmos.2016.26.4.599 (in Korean with English abstract).   DOI
14 Yu, C.-S., G.-H. Jeong, and J.-H. Kim, 2000: A study on the correlation between sea surface temperature and temperature and precipitation in Korea. J. Korea Water Resour. Assoc., 33, 145-150 (in Korean).
15 Jin, E. K., and Coauthors, 2008: Current status of ENSO prediction skill in coupled ocean-atmosphere models. Climate Dyn., 31, 647-664, doi:10.1007/s00382-008-0397-3.   DOI
16 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
17 Wang, B., and Coauthors, 2009: Advance and prospectus of seasonal prediction: assessment of the APCC/CliPAS 14-model ensemble retrospective seasonal prediction (1980-2004). Climate Dyn., 33, 93-117, doi: 10.1007/s00382-008-0460-0.   DOI
18 WCRP, 2011: Data and bias correction for decadal climate predictions. World Climate Research Programme, International CLIVAR Project Office Publication Series no. 150, 5 pp [Available online at https://www.clivar.org/sites/default/files/documents/ICPO150_Bias.pdf].
19 Williams, K. D., and Coauthors, 2015: The Met Office global coupled model 2.0 (GC2) configuration. Geosci. Model Dev., 88, 1509-1524, doi:10.5194/gmd-88-1509-2015.   DOI
20 Haerter, J. O., S. Hagemann, C. Moseley, and C. Piani, 2011: Climate model bias correction and the role of timescales. Hydrol. Earth Syst. Sci., 15, 1065-1079, doi:10.5194/hess-15-1065-2011.   DOI
21 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
22 Lim, S.-M., Y.-K. Hyun, H.-S. Kang, and S.-W. Yeh, 2018: Prediction skill of East Asian precipitation and temperature associated with El Nino in GloSea5 hindcast data. Atmosphere, 28, 37-51, doi:10.14191/Atmos.2018.28.1.037 (in Korean with English abstract).   DOI
23 Madec, G., and Coauthors, 2017: NEMO ocean engine. Notes du Pole de modelisation de l'Institut PierreSimon Laplace (IPSL) No. 27, 402 pp.
24 Son, S.-W., H. Kim, K. Song, S.-W. Kim, P. Martineau, Y.-K. Hyun, and Y. Kim, 2020: Extratropical prediction skill of the Subseasonal-to-Seasonal (S2S) prediction models. J. Geophys. Res. Atmos., 125, e2019JD031273, doi:10.1029/2019JD031273.   DOI
25 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).   DOI
26 Hunke, E. C., W. H. Lipscomb, A. K. Turner, N. Jeffery, and S. Elliott, 2015: CICE: the los alamos sea ice model documentation and software user's manual version 5.1. LA-CC-06-012. T-3 Fluid Dynamics Group, Los Alamos National Laboratory, 116 pp.
27 Walters, D. N., and Coauthors, 2011: The Met Office Unified Model global atmosphere 3.0/3.1 and JULES global land 3.0/3.1 configurations. Geosci. Model Dev., 4, 919-941, doi:10.5194/gmd-4-919-2011.   DOI
28 Jang, S.-M., S.-S. Kim, Y.-C. Choi, and S.-G. Kim, 2006: A study of correlations between air-temperature of Jeju and SST around Jeju island. J. Korean Soc. Marine Environ. Engin., 9, 55-62 (in Korean with English abstract).