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  • • Min, Y.‐M., C.‐M. Im, V. N. Kryjov, D. Jeong, 2024: Recent challenges in the APCC multi‐model ensemble seasonal prediction: Hindcast period issue. J. Geophys. Res., 129, e2023JD039787, https://doi.org/10.1029/2023JD039787


  • • Kim, O.-Y., and C.-M.. Lim, 2023: Predictability of the Western North Pacific Subtropical High and Associated East Asian Monsoon Rainfall in APCC Multi-Models. J. Geophys. Res. Atmos., 128, e2023JD038476, https://doi.org/10.1029/2023JD038476
  • • Wang, F., L. Wang, T. Dai, and Y. Han, 2023: Interplay between Boreal Summer Intraseasonal Oscillation and Southern Hemisphere Stratospheric Polar Vortex Warming. J. Climate, 36, 6839-6853, https://doi.org/10.1175/JCLI-D-22-0786.1


  • • Rhee, J. and B. Myoung, 2022: Objective and Probabilistic Long-Range Forecasts of Summertime Air Temperatures in South Korea Based on Gaussian Processes. Wea. Forecasting, 37, 329–349, https://doi.org/10.1175/WAF-D-21-0148.1


  • • Kim, S. T., Y.-Y. Lee, J.-H. Oh, and A.-Y. Lim, 2021: Errors in the Winter Temperature Response to ENSO over North America in Seasonal Forecast Models. J. Climate, 34, 8257–8271, https://doi.org/10.1175/JCLI-D-21-0094.1
  • • Park, C. and Coauthors, 2021: Record-Breaking Summer Rainfall in South Korea in 2020: Synoptic Characteristics and the Role of Large-Scale Circulations. Mon. Wea. Rev., 149, 3085-3100, https://doi.org/10.1175/MWR-D-21-0051.1
  • • Dandi, A. R., P. A. Pillai, and J. S. Chowdary, 2021: Inter-annual variability and skill of tropical rainfall and SST in APCC seasonal forecast models. Clim. Dyn., 56, 439-456, https://doi.org/10.1007/s00382-020-05487-w


  • • Jung, E., J.-H. Jeong, S.-H. Woo, B.-M. Kim, J.-H. Yoon, and G.-H. Lim, 2020: Impacts of the Arctic-Midlatitude Teleconnection on Wintertime Seasonal Climate Forecasts. Environ. Res. Lett., 15, 94045, https://doi.org/10.1088/1748-9326/aba3a3
  • • Kim, M., S. T. Kim, and Y. Jeong, 2020: Weather Generator–Based Downscaling of EAWM Strength Prediction to the Climate of a Korean Basin. J. Appl. Meteor. Climatol., 59, 1581–1605, https://doi.org/10.1175/JAMC-D-19-0282.1
  • • Lee, Y.-Y., and J.-H. Oh, 2020: West Pacific teleconnection pattern in dynamical seasonal predictions: how is it connected to the Atlantic atmospheric mean bias? Clim. Dyn., 54, 3671–3683, https://doi.org/10.1007/s00382-020-05198-2
  • • Myoung, B., J. Rhee, and C. Yoo, 2020: Long-Lead Predictions of Warm Season Droughts in South Korea Using North Atlantic SST. J. Climate, 33, 4659-4677, https://doi.org/10.1175/JCLI-D-19-0082.1
  • • Shin, J. Y., H.-H. Kwon, and J.-H. Lee, 2020: Probabilistic long-term hydrological drought forecast using Bayesian networks and drought propagation. Meteorol. Appl., 27, e1827, https://doi.org/10.1002/met.1827
  • • Sohn, S.-J. and W. Kim, 2020: Toward a better multi-model ensemble prediction of East Asian and Australasian precipitation during non-mature ENSO seasons. Sci. Rep., 10, 20289, https://doi.org/10.1038/s41598-020-77482-4


  • • Lee, J.-Y., H.-J. Kim, and Y.-R. Jeong, 2019: Influence of Boreal Summer Intraseasonal Oscillation on the 2016 Heat Wave over Korea. Atmos., 29(5), 627–637, https://doi.org/10.14191/ATMOS.2019.29.5.627
  • • Sohn, S.-J., C.-Y. Tam, and J.-S. Kug, 2019: How does ENSO diversity limit the skill of tropical Pacific precipitation forecasts in dynamical seasonal predictions?. Clim. Dyn., 53, 5815–5831, https://doi.org/10.1007/s00382-019-04901-2


  • • Alessandri, A., M. D. Felice, F. Catalano, J.-Y. Lee, B. Wang, D. Y. Lee, J.-H. Yoo, and A. Weisheimer, 2018: Grand European and Asian-Pacific multi-model seasonal forecasts: maximization of skill and of potential economical value to end-users. Clim. Dyn., 50, 2719–2738, https://doi.org/10.1007/s00382-017-3766-y
  • • Iizumi, T., Y. Shin, W. Kim, M. Kim, and J. Choi, 2018: Global crop yield forecasting using seasonal climate information from a multi-model ensemble. Clim. Serv., 11, 13-23, https://doi.org/10.1016/j.cliser.2018.06.003
  • • Kim, O.-Y., 2018: Assessment of seasonal prediction of South Pacific Convergence Zone using APCC multi-model ensembles. Clim. Dyn., 50, 3237–3250, https://doi.org/10.1007/s00382-017-3802-y
  • • Kim, O.-Y., J. C. and L. Chan, 2018: Cyclone-track based seasonal prediction for South Pacific tropical cyclone activity using APCC multi-model ensemble prediction. Clim. Dyn., 51, 3209–3229, https://doi.org/10.1007/s00382-018-4075-9
  • • Kim, W., S.-R. Yeo, and Y. Kim, 2018: Development of the Expert Seasonal Prediction System: an Application for the Seasonal Outlook in Korea. Asia-Pacific J Atmos Sci., 54, 563–573, https://doi.org/10.1007/s13143-018-0052-9
  • • Lee, R. W.-K., C.-Y. Tam, S.-J. Sohn, and J.-B. Ahn, 2018: Predictability of two types of El Niño and their climate impacts in boreal spring to summer in coupled models. Clim. Dyn., 51, 4555-4571, https://doi.org/10.1007/s00382-017-4039-5
  • • Park, H.-J., V. N. Kryjov, and J.-B. Ahn, 2018: One-Month-Lead Predictability of Asian Summer Monsoon Indices Based on the Zonal Winds by the APCC Multimodel Ensemble. J. Climate, 31, 8945–8960, https://doi.org/10.1175/JCLI-D-17-0816.1
  • • Sohn, S.-J., and Coauthors, 2018: The Republic of Korea-Pacific Islands Climate Prediction Services Project. Bull. Amer. Meteor. Soc., 99, 253–257, https://doi.org/10.1175/BAMS-D-17-0075.1
  • • Wu, S., M. Notaro, S. Vavrus, E. Mortensen, R. Montgomery, J. Pieroloa, and P. Block, 2018: Efficacy of tendency and linear inverse models to predict southern Peru's rainy season precipitation. Int. J. Climatol., 38, 2590-2604, https://doi.org/10.1002/joc.5442
  • • Yeo, S.-R., S.-W. Yeh, Y. Kim, and S.-Y. Yim, 2018: Monthly climate variation over Korea in relation to the two types of ENSO evolution. Int. J. Climatol., 38, 811-824, https://doi.org/10.1002/joc.5212
  • • You, Y., and X. Jia, 2018: Interannual Variations and Prediction of Spring Precipitation over China. J. Climate, 31, 655-670, https://doi.org/10.1175/JCLI-D-17-0233.1


  • • Ham, Y.-G., Y. Chikamoto, J.-S. Kug, M. Kimoto, and T. Mochizuki, 2017: Tropical Atlantic-Korea teleconnection pattern during boreal summer season. Clim. Dyn., 49, 2649–2664, https://doi.org/10.1007/s00382-016-3474-z
  • • Jeong, J.-H., and Coauthors, 2017: The status and prospect of seasonal climate prediction of climate over Korea and East Asia: A review. Asia-Pacific J Atmos Sci., 53, 149–173, https://doi.org/10.1007/s13143-017-0008-5
  • • Kim, O.-Y., H.-M. Kim, M.-I. Lee, and Y.-M. Min, 2017: Dynamical–statistical seasonal prediction for western North Pacific typhoons based on APCC multi-models. Clim. Dyn., 48, 71–88, https://doi.org/10.1007/s00382-016-3063-1
  • • Kim, S. T., S.-J. Sohn, and J.-S. Kug, 2017: Winter temperatures over the Korean Peninsula and East Asia: development of a new index and its application to seasonal forecast. Clim. Dyn., 49, 1567–1581, https://doi.org/10.1007/s00382-016-3402-2
  • • Lee, S.-S., J.-Y. Moon, B. Wang, and H.-J. Kim, 2017: Subseasonal Prediction of Extreme Precipitation over Asia: Boreal Summer Intraseasonal Oscillation Perspective. J. Climate, 30, 2849–2865, https://doi.org/10.1175/JCLI-D-16-0206.1
  • • Min, Y.-M., V. N. Kryjov, S. M. Oh, and H.-J. Lee, 2017: Skill of real-time operational forecasts with the APCC multi-model ensemble prediction system during the period 2008–2015. Clim. Dyn., 49, 4141–4156, https://doi.org/10.1007/s00382-017-3576-2


  • • Pradhan, P. K., V. Prasanna, D. Y. Lee, and M.-I. Lee, 2016: El Niño and Indian summer monsoon rainfall relationship in retrospective seasonal prediction runs: experiments with coupled global climate models and MMEs. Meteorol. Atmos. Phys., 128, 97-115, https://doi.org/10.1007/s00703-015-0396-y
  • • Shin, J. Y., M. Ajmal, J. Yoo, and T.-W. Kim, 2016: A Bayesian Network-Based Probabilistic Framework for Drought Forecasting and Outlook. Adv. Meteol., 2016, 1-10, https://doi.org/10.1155/2016/9472605
  • • Sohn, S.-J., and C.-Y. Tam, 2016: Long-lead station-scale prediction of hydrological droughts in South Korea based on bivariate pattern-based downscaling. Clim. Dyn., 46, 3305-3321, https://doi.org/10.1007/s00382-015-2770-3
  • • Sohn, S.-J., C.-Y. Tam, and H.-I. Jeong, 2016: How do the strength and type of ENSO affect SST predictability in coupled models. Sci. Rep., 6, 33790, https://doi.org/10.1038/srep33790


  • • Jeong, H.-I., J.-B. Ahn, J.-Y. Lee, A. Alessandri, and H. H. Hendon, 2015: Interdecadal change of interannual variability and predictability of two types of ENSO. Clim. Dyn., 44, 1073–1091, https://doi.org/10.1007/s00382-014-2127-3
  • • Lee, D. Y., J.-B. Ahn, and J.-H. Yoo, 2015: Enhancement of seasonal prediction of East Asian summer rainfall related to western tropical Pacific convection. Clim. Dyn., 45, 1025–1042, https://doi.org/10.1007/s00382-014-2343-x
  • • Lee, J.-Y., and K.-J. Ha, 2015: Understanding of Interdecadal Changes in Variability and Predictability of the Northern Hemisphere Summer Tropical-Extratropical Teleconnection. J. Climate, 28, 9634-9647, https://doi.org/10.1175/JCLI-D-15-0154.1
  • • Ye, K.-H., C.-Y. Tam, W. Zhou, and S.-J. Sohn, 2015: Seasonal prediction of June rainfall over South China: Model assessment and statistical downscaling. Adv. Atmos. Sci., 32(5), 680–689, https://doi.org/10.1007/s00376-014-4047-x
  • • Yim, S.-Y., B. Wang, W. Xing, and M.-M. Lu, 2015: Prediction of Meiyu rainfall in Taiwan by multi-lead physical–empirical models. Clim. Dyn., 44, 3033–3042, https://doi.org/10.1007/s00382-014-2340-0


  • • Jia, X., H. Lin, and X. Yao, 2014: The Influence of Tropical Pacific SST Anomaly on Surface Air Temperature in China. J. Climate, 27, 1425-1444, https://doi.org/10.1175/JCLI-D-13-00176.1
  • • Jia, X., J.-Y. Lee, H. Lin, A. Alessandri, and K.-J. Ha, 2014: Interdecadal change in the Northern Hemisphere seasonal climate prediction skill: part I. The leading forced mode of atmospheric circulation. Clim. Dyn., 43, 1595–1609, https://doi.org/10.1007/s00382-013-1988-1
  • • Jia, X., J.-Y. Lee, H. Lin, H. Hendon, and K.-J. Ha, 2014: Interdecadal change in the Northern Hemisphere seasonal climate prediction skill: part II. predictability and prediction skill. Clim. Dyn., 43, 1611–1630, https://doi.org/10.1007/s00382-014-2084-x
  • • Kang, S., J. Hur, and J.-B. Ahn, 2014: Statistical downscaling method based on APCC multi-model ensemble for seasonal prediction over South Korea. Int. J. Climatol., 34, 3801-3810, https://doi.org/10.1002/joc.3952
  • • Min, Y.-M., V. N. Kryjov, and S. M. Oh, 2014: Assessment of APCC multimodel ensemble prediction in seasonal climate forecasting: Retrospective (1983–2003) and real-time forecasts (2008–2013). J. Geophys. Res. Atmos., 119, 12,132–12,150, https://doi.org/10.1002/2014JD022230
  • • Yim, S.-Y., B. Wang, and W. Xing, 2014: Prediction of early summer rainfall over South China by a physical-empirical model. Clim Dyn., 43, 1883–1891, https://doi.org/10.1007/s00382-013-2014-3


  • • Gottschalck, J., P. E. Roundy, C. J. Schreck III, A. Vintzileos, and C. Zhang, 2013: Large-Scale Atmospheric and Oceanic Conditions during the 2011–12 DYNAMO Field Campaign. Mon. Wea. Rev., 141, 4173–4196, https://doi.org/10.1175/MWR-D-13-00022.1
  • • Lee, D. Y., J.-B. Ahn, and K. Ashok, 2013: Improvement of Multimodel Ensemble Seasonal Prediction Skills over East Asian Summer Monsoon Region Using a Climate Filter Concept. J. Appl. Meteorol. Climatol., 52, 1127-1138, https://doi.org/10.1175/JAMC-D-12-0123.1
  • • Lee, D. Y., J.-B. Ahn, K. Ashok, and A. Alessandri, 2013: Improvement of grand multi-model ensemble prediction skills for the coupled models of APCC/ENSMEBLES using a climate filter. Atmos. Sci. Lett., 14, 139-145, https://doi.org/10.1002/asl2.430
  • • Lee, J.-Y., S.-S. Lee, B. Wang, K.-J. Ha, and J.-G. Jhun, 2013: Seasonal prediction and predictability of the Asian winter temperature variability. Clim. Dyn., 41, 573–587, https://doi.org/10.1007/s00382-012-1588-5
  • • Sohn, S.-J., J.-B. Ahn, and C.-Y. Tam, 2013: Six month-lead downscaling prediction of winter to spring drought in South Korea based on a multimodel ensemble. Geophys. Res. Lett., 40, 579–583, https://doi.org/10.1002/grl.50133
  • • Sohn, S.-J., C.-Y. Tam, and J.-B. Ahn, 2013: Development of a multimodel-based seasonal prediction system for extreme droughts and floods : a case study for South Korea. Int. J. Climatol., 33, 793-805, https://doi.org/10.1002/joc.3464
  • • Tang, W., Z.-H. Lin, and L.-F. Luo, 2013: Assessing the Seasonal Predictability of Summer Precipitation over the Huaihe River Basin with Multiple APCC Models, Atmospheric and Oceanic Science Letters, 6:4, 185-190, https://doi.org/10.3878/j.issn.1674-2834.13.0025
  • • Tung, Y. L., C.-Y. Tam, S.-J. Sohn, and J.-L. Chu, 2013: Improving the seasonal forecast for summertime South China rainfall using statistical downscaling, J. Geophys. Res. Atmos., 118, 5147–5159, https://doi.org/10.1002/jgrd.50367


  • • Jeong, H., and Coauthors, 2012: Assessment of the APCC coupled MME suite in predicting the distinctive climate impacts of two flavors of ENSO during boreal winter. Clim. Dyn., 39, 475–493, https://doi.org/10.1007/s00382-012-1359-3
  • • Jia, X., H. Lin, J. Lee, and B. Wang, 2012: Season-Dependent Forecast Skill of the Leading Forced Atmospheric Circulation Pattern over the North Pacific and North American Region. J. Climate, 25, 7248-7265, https://doi.org/10.1175/JCLI-D-11-00522.1
  • • Kosaka, Y., J. S. Chowdary, S. Xie, Y.-M. Min, and J. Lee, 2012: Limitations of Seasonal Predictabiliy for Summer Climate over East Asia and the Northwestern Pacific. J. Climate, 25, 7574-7589, https://doi.org/10.1175/JCLI-D-11-00009.1
  • • Krishnamurti, T. N., and V. Kumar, 2012: Improved Seasonal Precipitation Forecasts for the Asian Monsoon Using 16 Atmosphere-Ocean Coupled Models. Part 2:Anomaly. J. Climate, 25, 65-88, https://doi.org/10.1175/2011JCLI4126.1
  • • Kumar, V., and T. N. Krishnamurti, 2012: Improved Seasonal Precipitation Forecasts for the Asian Monsoon Using 16 Atmosphere-Ocean Coupled Models. Part I:Climatology. J. Climate, 25, 39-64, https://doi.org/10.1175/2011JCLI4125.1
  • • Sohn, S.-J., Y.-M. Min, J.-Y. Lee, C.-Y. Tam, I.-S. Kang, B. Wang, J.-B. Ahn, and T. Yamagata, 2012: Assessment of the longlead probabilistic prediction for the Asian summer monsoon precipitation (1983–2011) based on the APCC multimodel system and a statistical model. J. Geophys. Res., 117, D04102, https://doi.org/10.1029/2011JD016308
  • • Stefanova, L., V. Misra, J. J. O’Brien, E. P. Chassignet, and S. Hameed, 2012: Hindcast skill and predictability for precipitation and two-meter air temperature anomalies in global circulation models over the Southeast United States. Clim. Dyn., 38, 161–173, https://doi.org/10.1007/s00382-010-0988-7


  • • Lee, J.-Y., B. Wang, Q. Ding, K.-J. Ha, J.-B. Ahn, A. Kumar, B. Stern, and O. Alves, 2011: How predictable is the northern hemisphere summer upper-tropospheric circulation?. Clim. Dyn., 37, 1189–1203, https://doi.org/10.1007/s00382-010-0909-9
  • • Min, Y.-M., V. N. Kryjov, and J.-H. Oh, 2011: Probabilistic interpretation of regression-based downscaled seasonal ensemble prediction with the estimation of uncertainty. J. Geophys. Res., 116, D08101, https://doi.org/10.1029/2010JD015284
  • • Sohn, S.-J., C.-Y. Tam, and C.-K. Park, 2011: Leading modes of East Asian winter climate variability and their predictability: An assessment of the APCC multi-model ensemble. J. Meteor. Soc. Jpn., 89(5), 455-474, https://doi.org/10.2151/jmsj.2011-504


  • • Chowdary, J. S., S.-P. Xie, J.-Y. Lee, Y. Kosaka, and B. Wang, 2010: Predictability of summer northwest Pacific climate in 11 coupled model hindcasts: Local and remote forcing. J. Geophys. Res., 115, D22121, https://doi.org/10.1029/2010JD014595
  • • Juneng, L., F. T. Tangang, H. Kang, W. Lee, and Y. K. Seng, 2010: Statistical Downscaling Forecasts for Winter Monsoon Precipitation in Malaysia Using Multimodel Output Variables. J. Climate, 23, 17–27, https://doi.org/10.1175/2009JCLI2873.1
  • • Lee, J., and Coauthors, 2010: How are seasonal prediction skills related to models’ performance on mean state and annual cycle?. Clim. Dyn., 35, 267–283, https://doi.org/10.1007/s00382-010-0857-4


  • • Kang, H., C.-K. Park, S. N. Hameed, and K. Ashok, 2009: Statistical Downscaling of Precipitation in Korea Using Multimodel Output Variables as Predictors. Mon. Wea. Rev., 137, 1928-1938, https://doi.org/10.1175/2008MWR2706.1
  • • Min, Y.-M., V. N. Kryjov, and C.-K. Park, 2009: A Probabilistic Multimodel Ensemble Approach to Seasonal Prediction. Wea. Forecasting, 24, 812–828, https://doi.org/10.1175/2008WAF2222140.1
  • • Wang, B., and Coauthors, 2009: Advance and prospectus of seasonal prediction: assessment of the APCC/CliPAS 14-model ensemble retrospective seasonal prediction (1980–2004). Clim. Dyn., 33, 93–117, https://doi.org/10.1007/s00382-008-0460-0


  • • Chu, J.-L., H. Kang, C.-Y. Tam, C.-K. Park, and C.-T. Chen, 2008: Seasonal forecast for local precipitation over northern Taiwan using statistical downscaling. J. Geophys. Res., 113, D12118, https://doi.org/10.1029/2007JD009424
  • • Kug, J.-S., J.-Y. Lee, I.-S. Kang, B. Wang, and C.-K. Park, 2008: Optimal Multi-model Ensemble Method in Seasonal Climate Prediction. Asia-Pacific J. Atmos. Sci., 44, 259-267.
  • • Shin, D. W., S.-D. Kang, S. Cocke, T.-Y. Goo, and H.-D. Kim, 2008: Seasonal probability of precipitation forecasts using a weighted ensemble approach. Int. J. Climatol., 28, 1971-1976, https://doi.org/10.1002/joc.1690
  • • Wang, B., and Coauthors, 2008: How accurately do coupled climate models predict the leading modes of Asian-Australian monsoon interannual variability?. Clim. Dyn., 30, 605–619, https://doi.org/10.1007/s00382-007-0310-5
  • • Zhu, C., C.-K. Park, W.-S. Lee, and W.-T. Yun, 2008: Statistical downscaling for multi-model ensemble prediction of summer monsoon rainfall in the Asia-Pacific region using geopotential height field. Adv. Atmos. Sci., 25, 867–884, https://doi.org/10.1007/s00376-008-0867-x


  • • Kang, H., and C.-K. Park, 2007: Error analysis of dynamical seasonal predictions of summer precipitation over the East Asian-western Pacific region. Geophys. Res. Lett., 34, L13705, https://doi.org/10.1029/2007GL029392
  • • Kang, H., K.-H. An, C.-K. Park, A. L. S. Solis, and K. Stitthichivapak, 2007: Multimodel output statistical downscaling prediction of precipitation in the Philippines and Thailand. Geophys. Res. Lett., 34, 15, L15710, https://doi.org/10.1029/2007GL030730


  • • Kar, S. C., A. Hovsepyanm, and C. K. Park, 2006: Economic values of the APCN multi-model ensemble categorical seasonal predictions. Meteorol. Appl., 13, 267-277, https://doi.org/10.1017/S1350482706002271


  • • Yoo, J. H., and I.-S. Kang, 2005: Theoretical examination of a multi-model composite for seasonal prediction. Geophys. Res. Lett., 32, L18707, https://doi.org/10.1029/2005GL023513