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All research papers and news utilizing APCC's climate information are listed below. 
If you have published any relevant papers or articles with APCC's climate information and want them to be listed here, please e-mail apcc@apcc21.org.

2024

  • • 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

2023

  • • 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

2022

  • • 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

2021

  • • 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

2020

  • • 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

2019

  • • 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

2018

  • • 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

2017

  • • 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

2016

  • • 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

2015

  • • 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

2014

  • • 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

2013

  • • 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

2012

  • • 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

2011

  • • 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

2010

  • • 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

2009

  • • 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

2008

  • • 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

2007

  • • 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

2006

  • • 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

2005

  • • 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