Ham, Yoo-Geun

• 2009.09
  Ph.D., Atmospheric Sciences, Seoul National University
• 2003.02
  B.S., Atmospheric Sciences, Seoul National University

- 2024

J. -H. Kim, Y. –G. Ham, D. Kim, T. Li, and C. Ma, 2024: Deep learning model for short-term forecasts of tropical cyclone intensity and their rapid intensification. Artificial Intell. for Earth Systems, 3(2), https://doi.org/10.1175/AIES-D-23-0052.1.

W. -Y. Cheng, D. Kim, S. Henderson., Y. –G. Ham, J. -H. Kim, and R. H. Holzworth, 2024: Machine learning based lightning parameterizations for CONUS. Artificial Intelligence for the Earth Systems. 3(2), https://doi.org/10.1175/AIES-D-23-0024.1.

C. Eayrs, et al., 2024: Advances in machine learning techniques can assist across a variety of stages in sea ice applications. Bulletin of the American Meteorological Society, 105(3), E527-E531.

 

- 2023

H. -S. Jo, and Y. –G. Ham, 2023: Enhanced joint impact of the western hemispheric precursors on the El Nino-Southern Oscillation under greenhouse warming. Nature Comms. 14(1), 6356. (CA).

Y. -M. Yang, J. -H. Kim, J. -H. Park, Y. -G. Ham, S. -I. An, J. -Y. Lee, and B. Wang, 2023: Exploring dominant processes for multi-month predictability of western Pacific precipitation using deep learning, npj Climate and Atmospheric Science., 6, 157. https://doi.org/10.1038/s41612-023-00478-0.

Y. –G. Ham, J. –H. Kim, S. –K. Min, D. Kim, T. Li, A. Timmermann, and M. F. Stuecker, 2023: Anthropogenic fingerprints in daily precipitation revealed by deep learning. Nature, 622, 301-307. https://doi.org/10.1038/s41586-023-06474-x.

J. -G. Lee, and Y. –G. Ham, 2023: Impact of thickness satellite data assimilation on bias reduction in Arctic sea ice concentration. npj climate and atmospheric science., 6, 73, http://doi.org/10.10038/s41612-023-00402-6 (CA).

S. –H. Oh, and Y. -G. Ham 2023: Taylor expansion of the correlation metric for an individual forecast verification and its application to East Asian climate forecasts, Clim. Dyn., 61, 2623-2636. (CA)

L. Jiang, T. Li, and Y. -G. Ham, 2023: Asymmetric Impacts of El Niño and La Niña on Equatorial Atlantic Warming.Journal of Climate, 36(1), 193-212.

 

- 2022

H. -S. Jo, Y. -G. Ham, J. -S. Kug, T. Li, J. -H. Kim, and J. -G. Kim, 2022: Southern Indian Ocean Dipole as a trigger for El Niño events since the 2000s, Nature Communications, 13(1), 6965. (CA)

I. Park, S. -W. Yeh, S. -K. Min, Y. -G. Ham, and B. Kirtman 2022: Present-day warm pool constrains future tropical precipitation. Communications earth & environment, 3(1), 310.

N. -Y. Shin, Y. -G. Ham, J. -H. Kim, M. -S. Cho, and J. -S. Kug, 2022: Application of deep learning to understanding ENSO dynamics, Arti. Intell. for the Earth Systems., 1-37. https://doi.org/10.1175/AIES-D-21-0011.1.

L. Gao, Y. –M. Yang, Q. Li, Y. –G. Ham, and J. –H. Kim, 2002: Deep learning for predicting winter temperature in North China, Atmosphere, 13, 702. https://doi.org/10.3390/atmos13050702.

W. Choi, M. Bang, Y. Joh, Y. –G. Ham, N. Kang, and C. –J. Jang, 2022: Characteristics and Mechanisms of Marine Heatwaves in the East Asian Marginal Seas: Regional and Seasonal Differences, Remote Sens., 14, 3522. https://doi.org/10.3390/rs14153522

Y. -G. Ham, S. -Y. Kang, Y. Jeong, J. -H. Jeong, and T. Li, 2022: Large-scale sea surface temperature forcing contributed to the 2013–2017 record-breaking drought in Korea, J. Clim., 35, 3767-3783 (CA)

L. Jiang, T. Li, and Y. -G. Ham, 2022: Critical role of tropical North Atlantic SSTA in boreal summer in affecting subsequent ENSO evolution, Geo. Res. Lett., https://doi.org/10.1029/2021GL097606.

J. -G. Lee, and Y. -G. Ham, 2022: Satellite based data assimilation system for the initialization of Arctic sea ice concentration and thickness using CICE5. Frontiers in Climate., 4, 797733, doi: 10.3389/fclim.2022.797733 (CA)

 

- 2021

J. -S. Kug, J. -H. Oh, S. -I. An, S. -W. Yeh, S. -K. Min, S. -W. Son, J. Kam, Y. -G. Ham, and J. Shin, 2021: Hysteresis of the Intertropical Convergence Zone to CO2 Forcing, Nat. Clim. Chang., 12(1), 47-53. https://doi.org/10.1038/s41558-021-01211-6.

C. Park, S. -W. Son, H. –R. Kim, Y. -G. Ham., and co-authors, 2021: Record-breaking summer rainfall in South Korea in 2020: Synoptic characteristics and the role of large-scale circulations. Mon. Wea. Rev. 149(9), 3085-3100.

Y. -G. Ham, J. -G. Kim, J. -G. Lee, T. Li, M. -I. Lee, S. -W. Son, and Y. -K. Hyun, 2021: The origin of systematic forecast errors of extreme 2020 East Asian Summer Monsoon rainfall in GloSea5, Geo. Res. Lett. e2021GL094179. (CA)

Y. -G. Ham, H. -J. Lee, H. -S. Jo, S. -G. Lee, W. Cai, and R. R. Rodrigues, 2021: Inter-Basin Interaction Between Variability in the South Atlantic Ocean and the El Nino/Southern Oscillation, Geo. Res. Lett. e2021GL093338. (CA)

W. Cai., et al., 2021 : Changing El Niño–Southern Oscillation in a warming climate, Nature Reviews on Earth & Environment, 2, 628-644. https://doi.org/10.1038/s43017-021-00199-z.

Y. –G. Ham, J. –H. Kim, E. –S. Kim, and K. –Y. On, 2021: Unified deep learning model for ENSO forecasts by incorporating seasonality in climate data, Sci. Bull., 66(13), 1358-1366. https://doi.org/10.1016/j.scib.2021.03.009. (CA)

H. Kim, Y. -G. Ham, Y. -S. Joo, and S. Son, 2021: Deep learning for bias correction of MJO prediction. Nature Comm., 12(1), 3087. https://doi.org/10.1038/s41467-021-23406-3.

S. –W. Yeh, H. –S. Jo, S. Hyun, W. Cai, and Y. –G. Ham, 2021: Role of eastern subtropical North Pacific Ocean on the El Nino’s transition process. Clim. Dyn., 56, 1285-1301.

Y. –G. Ham, Y. –S. Joo, and J. –Y. Park, 2021: Mechanism of skillful seasonal surface chlorophyll prediction over the southern Pacific using a global Earth system model, Clim. Dyn., 56, 45-64. (CA)

 

- 2020

Ham Y. –G., S. –G. Lee, and M. –K. Sung, 2020: A distinct sub-seasonal modulation in the Atlantic-originated atmospheric teleconnection influence on East Asian monthly climates. Env. Res. Lett. 16(1), 014033. (CA)

M. –S. Ahn, 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? Geophy. Res. Lett., 47(11), e2020GL087250. (CA)

Cai. W., et al., 2020: Impact of El Nino-Southern Oscillation on South America in a changing climate, Nature Reviews on Earth & Environment, 1, 215-231.

M. –S. Ahn, D. Kim, Y. –G. Ham, and S. Park, 2020: Role of Maritime Continent Land Convection on the Mean State and MJO Propagation, J. Clim., 33(5), 1659-1675.

 

- 2019

Ham. Y. –G., J. –H. Kim, and J. –J. Luo, 2019: Deep learning for multi-year ENSO forecasts. Nature, 573, 568-572. https://doi.org/10.1038/s41586-019-1559-7. (CA)

J. –Y. Choi, Y. –G. Ham, and S. McGregor, 2019: Atlantic-Pacific SST gradient change responsible for the weakening of North Tropical Atlantic-ENSO relationship due to global warming, Geo. Res. Lett. 46(13), 7574-7582. (CA)

Cai, W., and co-authors, 2019 : Pantropical climate interactions, Science, 363, eaav4236. DOI: 10.1126/science.aav4236.

Ham. Y. –G., H. –Y. Na, and S. -H. Oh, 2019 : Role of sea surface temperature over the Kuroshio Extension region on heavy rainfall events over the Korean Peninsula, Asia-Pacific J. Atmos. Sci., 55, 19-29. (CA)

M. -S. Ahn, D. Kim, S. Park, and Y. –G. Ham, 2019 : Do we need to parameterize mesoscale convective organization to mitigate the MJO-mean state tradeoff?, Geophy. Res. Lett., 46, https://doi.org/10.1029/2018GL080314. (CA)

 

- 2018

Ham Y. -G., 2018 : El Nino events set to intensify, Nature, 564, 192-193. doi:10.1038/d41586-018-07638-w.

Ham Y. -G., Y. Hwang, Y. –K. Lim, and M. Kwon, 2018 : Inter-decadal variation of the Tropical Atlantic - Korea (TA-K) teleconnection pattern during boreal summer season, Clim. Dyn. 51, 2609-2621. https://doi.org/10.1007/s00382-017-4031-0. (CA)

Timmermann, A., and co-authors, 2018 : El Nino-Southern Oscillation Complexity, Nature., 559, 535-545. https://doi.org/10.1038/s41586-018-0252-6

Ham. –Y. –G., J. –S. Kug, W. –H. Yang, and W. Cai, 2018 : Future changes in Extreme El Nino events modulated by North Tropical Atlantic variability, Geophysical Research Letters, 45, 6646-6653. https:// doi.org/10.1029/2018GL078085

S. –W. Yeh, Y. –J. Won, J. –S. Hong, K. –H. Seo, M. Kwon, and Y. -G. Ham, 2018 : The record-breaking heat wave in 2016 over South Korea and its physical mechanism, Mon. Wea. Rev., 146, 1463-1474.

Ham, Y. -G., J. –S. Kug, J. –Y. Choi, F. –F. Jin, and M. Watanabe 2018 : Inverse relationship between present-day tropical precipitation and its sensitivity to greenhouse warming, Nature Climate Change, 8, 64-69, doi:10.1038/s41558-017-0033-5.

 

- 2017

Ham Y. -G., and H. –Y. Na, 2017 : Marginal sea variation as a pre-cursor of heat waves over the Korean peninsula, Asia-Pacific J. Atmos. Sci., 53(4), 445-455, doi:10.1007/s13143-017-0047-y (CA)

Ham Y. -G., 2017 : A reduction in the asymmetry of ENSO amplitude due to global warming: the role of atmospheric feedback, Geophy. Res. Lett., 44, 8576–8584, doi:10.1002/2017GL074842. (CA)

Ham Y. -G., Y. Chikamoto, J. –S. Kug, M. Kimoto, and T. Mochizuki, 2017 : Tropical Atlantic–Korea teleconnection pattern during boreal summer season, Climate Dynamics., 49, 2649-2664, DOI 10.1007/s00382-016-3474-z. (CA)

Ham Y. -G., J. –Y. Choi and J. –S. Kug, 2017 : The weakening of the ENSO-Indian Ocean Dipole (IOD) coupling strength in recent decades, Climate Dynamics., 49, 249-261. DOI 10.1007/s00382-016-3339-5. (CA)

J.-Y. Lee, M. –H. Kwon, K. –S. Yun, S. –K. Min, I. –H. Park, Y. –G. Ham, E. K. Jin, J. –H. Kim, K. –H. Seo, W. –M. Kim, S. –Y. Yim, and J. –H. Yoon, 2017: The long-term variability of Changma in the East Asian summer monsoon system: A review and revisit, Asia-Pacific J. Atmos. Sci., 53(2), 257-272. DOI:10.1007/s13143-017-0032-5.

 

- 2016

Ham Y. -G., and J. –S. Kug, 2016 : Present-day constraint for tropical precipitation changes due to global warming in CMIP5 models, Asia-Pacific J. Atmos. Sci., 52(5), 459-466, DOI:10.1007/s13143-016-0030-z

Ham Y. -G., H.-J. Song, and G.-H. Lim, 2016 : Development of the Nonstationary Incremental Analysis Update Algorithm for Sequential Data Assimilation System, Advances in Meteorology. vol. 2016, Article ID 4305204, 11 pages, doi:10.1155/2016/4305204.

Ham Y. -G., and J. –S. Kug, 2016 : ENSO amplitude changes due to greenhouse warming in CMIP5: Role of mean tropical precipitation in the 20th century, Geophy. Res. Lett. 43, 422-430, doi:10.1002/2015GL066864.

Choi J., S. -W. Son, Y. –G. Ham, J.-Y. Lee, and H.-M. Kim, 2016 : Seasonal to interannual predictability of surface air temperature in the CMIP5 decadal hindcast experiments, J. Clim., 29, 1511- 1527.

Ham Y. -G., and J. –S. Kug, S. –W. Yeh, and M. Kwon, 2016 : Impact of two distinct teleconnection patterns induced by western Central Pacific SST anomalies on Korean temperature variability during the early boreal summer, J. Clim., 29, 743–759. (CA)

 

- 2015

Ham Y. -G., and J. –S. Kug, 2015 : Role of North Tropical Atlantic SST on the ENSO simulated using CMIP3 and CMIP5 models, Clim. Dyn., 45, 3103-3117.

Ham Y. –G., Y. –R. Jeong, and J. –S. Kug, 2015 : Changes in Independency between Two Types of El Niño Events under Greenhouse Warming Scenario in CMIP5 Models, J. Clim., 28, 7561-7575.

Ham Y. -G., and J. –S. Kug, 2015 : Improvement of ENSO simulation based on intermodel diversity, J. Clim., 28, 998-1015.

 

- 2014

Kim, H. -M., Y. –G. Ham, and A. A. Scaife, 2014 : Improvement of Initialized Decadal Predictions over the North Pacific Ocean by Systematic Anomaly Pattern Correction, J. Clim., 27, 5148-5162.

Ham, Y. –G., S. Schubert, Y. Vikhliaev, and M. J. Suarez, 2014 : An Assessment of the ENSO forecast skill of GEOS-5 system, Clim. Dyn., 43, 2415-2430. DOI 10.1007/s00382-014-2063-2. (CA)

Ham Y. -G., and J. –S. Kug, 2014 : ENSO phase-locking to the boreal winter in CMIP3 and CMIP5 models, Clim. Dyn., 43, 305-318. DOI 10.1007/s00382-014-2064-1.

Wang, H., S. Schubert, R. Koster, Y. -G. Ham, and M. Suarez, 2014 : On the Role of SST Forcing in the 2011 and 2012 Extreme U.S. Heat and Drought: A Study in Contrasts, J. Hydrometeorology. 15, 1255-1273. doi: http://dx.doi.org/10.1175/JHM-D-13-069.1

Ham Y. -G., and J. –S. Kug 2014 : Effects of Pacific Intertropical Convergence Zone precipitation bias on ENSO phase transition, Env. Res. Lett. 9, 064008. doi:10.1088/1748-9326/9/6/064008

Ham Y. -G., M. -K. Sung, S. -I. An, S. Schubert, J. –S. Kug, 2014 : Role of tropical atlantic SST variability as a modulator of El Nino teleconnections, Asia-Pacific J. Atmos. Sci. 50(3), 247-261. DOI:10.1007/s13143-014-0013-x.

Yeh, S.-W., Y. -G. Ham, and B. Kirtman, 2014 : A possible explanation on the changes in the spatial structure of ENSO from CMIP3 to CMIP5, Geophy. Res. Lett., 41, 140-145. doi:10.1002/2013GL058478.

Ham, Y.-G., M. M. Rienecker, M. J. Suarez, Y. Vikhliaev, B. Zhao, J. Marshak, G. Vernieres, and S. Schubert, 2014 : Decadal Prediction Skill in the GEOS-5 Forecast System, Clim. Dyn., 42, 1-20. 10.1007/s00382-013-1858-x. (CA)

 

- 2013

Ham Y. -G., M.-J. Lim, and J.-S. Kug, 2013 : Importance of mean state in simulating different types of El Nino revealed by SNU coupled GCMs, Progress in Oceanography, 116, 130-141.

Ham Y. -G., J. –S. Kug, and J.-Y. Park 2013 : Two distinct roles of Atlantic SSTs in ENSO variability: North Tropical Atlantic SST and Atlantic Niño, Geophy. Res. Lett., 40, 4012-4017, doi:10.1002/grl.50729.

Ham, Y.-G., J.-S. Kug, J.-Y. Park, and F.-F. Jin, 2013 : Sea surface temperature in the north tropical Atlantic as a trigger for El Niño/Southern Oscillation events, Nature Geoscience, 6, 112-116, 10.1038/ngeo1686.

Sung, M.-K., Y. -G. Ham, J. -S. Kug, and S. -I. An, 2013 : An alternative effect by the Tropical North Atlantic SST in Intraseasonally Varying El Niño Teleconnection over the North Atlantic, Tellus A., 65, 19863, 10.3402/tellusa.v65i0.19863.

Ham, Y. -G., J. –S. Kug, D. Kim, Y. -H. Kim, and D. –H. Kim, 2013 : What controls phase-locking of ENSO to boreal winter in coupled GCMs?, Clim. Dyn., 40, 1551-1568. 10.1007/s00382-012-1420-2.

Hong, S., I.–S. Kang, I. Choi, and Y.–G. Ham, 2013 : Climate responses in the tropical Pacific associated with Atlantic warming in recent decades, Asia-Pacific J. Atmos. Sci, 49, 209-217.

 

- 2012

Yeh, S. –W., Y. –G. Ham, and J. –Y. Lee, 2012 : Changes in the tropical Pacific SST trend from CMIP3 to CMIP5 and its implication of ENSO, J. Clim. 25, 7764-7771. 10.1175/JCLI-D-12-00304.1. (CA)

Ham Y. –G., M. M. Rienecker, S. Schubert, J. Marshak, S. –W. Yeh, and S. –C. Yang, 2012 : The decadal Modulation of coupled bred vectors, Geophy. Res. Lett., 37, L20712, 10.1029/2012GL053719. (CA)

Kug, J.-S., and Y. -G. Ham, 2012 : Indian Ocean feedback to the ENSO transition in a multi-model ensemble, J. Clim., 25, 6942-6957, 10.1175/JCLI-D-12-00078.1. (CA)

Ham, Y. -G., J.-S. Kug, and M. –J. Lim, 2012 : Rectification Feedback of high-frequency atmospheric variability into low-frequency zonal flows in the tropical Pacific, J. Clim., 25, 5088–5101. 10.1175/JCLI-D-11-00303.1.

Ham, Y. -G., and J.-S. Kug, 2012 : How well do current climate models simulate two types of El Nino?, Climate Dynamics. 39, 383-398, 10.1007/s00382-011-1157-3.

Kug, J.-S., Y. -G. Ham, J. –Y. Lee, and F. –F Jin, 2012 : Improved simulation of two types of El Niño in CMIP5 models, Env. Res. Lett., 7, 034002, 10.1088/1748-9326/7/3/034002. (CA)

Ham, Y.-G., I.-S. Kang, and J.-S. Kug, 2012 : Coupled Bred Vectors in the Tropical Pacific and Their Application to ENSO prediction, Prog. Oceanogr., 105, 90-101, 10.1016/j.pocean.2012.04.005.

Ham, Y. –G., and M. M. Rienecker, 2012 : Flow-dependent Empirical Singular Vector with an Ensemble Kalman Filter data assimilation for El Nino prediction, Clim. Dyn., 39, 1727-1738, 10.1007/s00382-012-1302-7. (CA)

Ham, Y. –G., S. Schubert, and Y. Chang, 2012 : Optimal Initial Perturbations for Ensemble Prediction of the Madden-Julian Oscillation during Boreal Winter, J. Clim., 25, 4932-4945, 10.1175/JCLI-D-11-00344.1 (CA)

Lim, Y.–K., Y.-G. Ham, J.–H. Jeong, and J.-S. Kug, 2012 : Improvement in simulation of Eurasian winter climate variability with a realistic Arctic sea ice condition in an atmospheric GCM, Env. Res. Lett., 7, 044041, 10.1088/1748-9326/7/4/004041. (CA)

Jeong, H.-I, D. Y. Lee, K. Ashok, J.-B. Ahn, J.-Y. Lee, J.-J. Luo, J.-K. E. Schemm, H. H. Hendon, K. Braganza, and Y. -G. Ham, 2012 : Assessment of the APCC coupled MME suite in predicting the distinctive climate impacts of two flavors of ENSO during boreal winter, Climate Dynamics., 39, 475-493, 10.1007/s00382-012-1359-3.

Ham, Y. -G., I. -S. Kang, D. Kim, and J.-S. Kug, 2012 : El-Nino Southern Oscillation Simulated and Predicted in SNU Coupled GCMs, Climate Dynamics., 38, 2227-2242, 10.1007/s00382-011-1171-5. (CA)

 

- 2011

Kug, J.-S., Y. -G. Ham, E. -J. Lee, and I. -S. Kang, 2011 : Empirical singular vector method for ensemble El Nino-Southern Oscillation Prediction with a coupled general circulation model, J. Geophy. Res., 116, C08029, 10.1029/2010JC006851. (CA)

Ham, Y.-G., and I.-S. Kang, 2011 : Improvement of Seasonal Forecasts with Inclusion of Tropical Instability Waves on Initial Conditions, Clim. Dyn, 36, 1277-1290, 10.1007/s00382-010-0743-0.

Kug, J.-S, and Y. -G. Ham, 2011 : Are there two types of La Nina?, Geophy. Res. Lett., 38, L16704, 10.1029/2011GL048237. (CA)

Kug, J.-S., K. P. Sooraj, F. –F. Jin, Y.-G. Ham, and D. Kim, 2011 : A Possible Mechanism for El Nino-like Warming in Response to the Future Greenhouse Warming. Int. J. Climatol , 31, 1567-1572, 10.1002/joc.2163

 

- 2010

Ham, Y.-G., and I.-S. Kang, 2010 : Growing-Error Correction of Ensemble Kalman Filter using Empirical Singular Vectors, Q. J. R. Meteorol. Soc. 136, 2051-2060, 10.1002/qj.711.

Kug, J.-S., Y.-G. Ham, evisedevisedevisedevisedevisedM. Kimoto, F.-F. Jin, and I.-S. Kang, 2010 : New approach for optimal perturbation method in ensemble climate prediction with empirical singular vector, Clim. Dyn. 35, 331–340, 10.1007/s00382-009-0664-y.

Kug, J.-S., Y.-G. Ham, F.-F. Jin, and I.-S. Kang, 2010 : Scale Interactions between Tropical Instability Waves and Low-frequency Oceanic Flows, Geophy. Res. Lett., 37, L02710, 10.1029/2009GL041020. (CA)

An, S.-I., Y.-G. Ham, J.-S. Kug, A. Timmermann, J. Choi, and I.-S Kang, 2010 : The inverse effect of annual-mean state and annual-cycle changes on ENSO. J. Climate., 23, 1095-1110.

Ham, Y.-G., J.-S. Kug, I.-S. Kang, F.-F. Jin, and A. Timmermann, 2010 : Impact of diurnal atmosphere-ocean coupling on tropical climate simulations using a coupled GCM. Clim. Dyn., 34, 905-917, 10.1007/s00382-009-0586-8.

Kug, J.-S., S.-I. An, Y.-G. Ham, and I.-S. Kang, 2010 : Changes in El Nino and La Nina teleconnections over North Pacific-America in global warming simulations, Theor. Appl. Climatol. 100, 275–282, 10.1007/ s00704-009-0183-0

 

- 2005-2009

Ham, Y.-G., J.-S. Kug, and I.-S. Kang, 2009 : Optimal initial perturbations for El Nino ensemble prediction with Ensemble Kalman Filter, Clim. Dyn. 33, 959–973, 10.1007/s00382-009-0582-z.

An, S.-I., J.-S. Kug, Y.-G. Ham, and I.-S. Kang, 2008 : Successive modulation of ENSO to the future greenhouse warming. J. Climate, 21, 3-21.

Ham, Y.-G., J.-S. Kug, and I.-S. Kang, 2007 : Role of moist energy advection in formulating anomalous Walker Circulation associated with ENSO. J. Geophy. Res., 112, D24105, 10.1029/2007JD008744.

An, S.-I, Y.-G. Ham, J.-S. Kug, and I.-S. Kang, 2005 : El Nino-La Nina Asymmetry in the Coupled Model Intercomparison Project Simulations, J. Climate., 18, 2617-2627.