Asia-Pacific Journal of Atmospheric Sciences

, Volume 53, Issue 1, pp 149–173 | Cite as

The status and prospect of seasonal climate prediction of climate over Korea and East Asia: A review

  • Jee-Hoon Jeong
  • Hyunsoo Lee
  • Jin Ho Yoo
  • MinHo Kwon
  • Sang-Wook Yeh
  • Jong-Seong Kug
  • Jun-Yi Lee
  • Baek-Min Kim
  • Seok-Woo Son
  • Seung-Ki Min
  • Hansu Lee
  • Woo-Seop Lee
  • Jin-Ho Yoon
  • Hyun-kyung Kim
Review

Abstract

Over the last few decades, there have been startling advances in our understanding of climate system and in modelling techniques. However, the skill of seasonal climate prediction is still not enough to meet the various needs from industrial and public sectors. Therefore, there are tremendous on-going efforts to improve the skill of climate prediction in the seasonal to interannual time scales. Since seasonal to interannual climate variabilities in Korea and East Asia are influenced by many internal and external factors including East Asian monsoon, tropical ocean variability, and other atmospheric low-frequency variabilities, comprehensive understanding of these factors are essential for skillful seasonal climate prediction for Korea and East Asia. Also, there are newly suggested external factors providing additional prediction skill like soil moisture, snow, Arctic sea ice, and stratospheric variability, and techniques to realize skills from underlying potential predictability. In this review paper, we describe current status of seasonal climate prediction and future prospect for improving climate prediction over Korea and East Asia.

Key words

Seasonal climate prediction climate variability global climate model Korea and East Asia 

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References

  1. Ahn, J.-B., J.-H. Ryu, E.-H. Cho, J.-Y. Park, and S.-B. Ryoo, 1997: A Study on correlations between air-temperature and precipitation in Korea and SST over the Tropical Pacific. J. Korean Meteor. Soc., 33, 487–495 (in Korean with English abstract).Google Scholar
  2. Alexander, M. A., I. Blade, M. Newman, J. R. Lanzante, N.-C. Lau, and J. D. Scott, 2002: The atmospheric bridge: The influence of ENSO teleconnections on air-sea interaction over the global oceans. J. Climate, 15, 2205–2231, doi:10.1175/1520-0442(2002)015<2205:TABTIO>2.0.CO;2.CrossRefGoogle Scholar
  3. Armstrong, R., 2001: Historical Soviet daily snow depth version 2 (HSDSD). National Snow and Ice Data Center.Google Scholar
  4. Ashok, K., S. K. Behera, S. A. Rao, H. Weng, and T. Yamagata, 2007: El Niño Modoki and its possible teleconnection. J. Geophys. Res., 112, C11007, doi:10.1029/2006JC003798.CrossRefGoogle Scholar
  5. Badr, H., B. Zaitchik, and S. Guikema, 2014: Application of statistical models to the prediction of seasonal rainfall anomalies over the Sahel. J. Appl. Meteor. Clim., 53, 614–636, doi:10.1175/JAMC-D-13-0181.1.CrossRefGoogle Scholar
  6. Baldwin, M. P., and T. J. Dunkerton, 2001: Stratospheric harbingers of anomalous weather regimes. Science, 294, 581–584, doi:10.1126/science.1063315.CrossRefGoogle Scholar
  7. Barnston, A., and S. J. Mason, 2011: Evaluation of IRI’s seasonal climate forecasts for the extreme 15% tails. Wea. Forecasting, 26, 545–554, doi:10.1175/WAF-D-10-05009.1.CrossRefGoogle Scholar
  8. Becker, E. J., H. van den Dool, and M. Peña, 2013: Short-term climate extremes: Prediction skill and predictability. J. Climate, 26, 512–531, doi:10.1175/JCLI-D-12-00177.1.CrossRefGoogle Scholar
  9. Brown, R. D., B. Brasnett, and D. Robinson, 2003: Gridded North American monthly snow depth and snow water equivalent for GCM evaluation. Atmos.-Ocean, 41, 1–14, doi:10.3137/ao.410101.CrossRefGoogle Scholar
  10. Cai, W., and Coauthors, 2015: ENSO and greenhouse warming. Nature Clim. Change, 5, 849–859, doi:10.1038/nclimate2743.CrossRefGoogle Scholar
  11. Cassou, C., L. Terray, and A. S. Phillips, 2005: Tropical Atlantic influence on European heat waves. J. Climate, 18, 2805–2811, doi:10.1175/ JCLI3506.1.CrossRefGoogle Scholar
  12. Cha, E.-J., J.-G. Jhun, and H.-S. Chung, 1999: A study of characteristics of climate in South Korea for El Niño/La Niña years. J. Korean Meteor. Soc., 35, 98–117 (in Korean with English abstract).Google Scholar
  13. Chang, C.-P., Z. Wang, J. Ju, and T. Li, 2004: On the relationship between western maritime continent monsoon rainfall and ENSO during northern winter. J. Climate, 17, 665–672, doi:10.1175/1520-0442(2004) 017<0665:OTRBWM>2.0.CO;2.CrossRefGoogle Scholar
  14. Charron, M., and Coauthors, 2012: The stratospheric extension of the Canadian global deterministic medium-range weather forecasting system and its impact on tropospheric forecasts. Mon. Wea. Rev., 140, 1924–1944, doi:10.1175/MWR-D-11-00097.1.CrossRefGoogle Scholar
  15. 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, doi:10.1029/2010JD014595.Google Scholar
  16. Cohen, J., and C. Fletcher, 2007: Improved skill of Northern Hemisphere winter surface temperature predictions based on land-atmosphere fall anomalies. J. Climate, 20, 4118–4132, doi:10.1175/JCLI4241.1.CrossRefGoogle Scholar
  17. Cohen, J., J. Foster, M. Barlow, K. Saito, and J. Jones, 2010: Winter 2009-2010: A case study of an extreme Arctic Oscillation event. Geophys. Res. Lett., 37, doi:10.1029/2010GL044256.Google Scholar
  18. Cohen, J., and J. Jones, 2011: A new index for more accurate winter predictions. Geophys. Res. Lett., 38, L21701, doi:10.1029/2011GL-049626.Google Scholar
  19. Collins, W. D., and Coauthors, 2004: Description of the NCAR Community Atmosphere Model (CAM 3.0). NCAR Tech. Note NCAR/ TN-464+STR, 226 pp.Google Scholar
  20. Collow, T. W., W. Wang, A. Kumar, and J. Zhang, 2015: Improving Arctic sea ice prediction using PIOMAS initial sea ice thickness in a coupled ocean-atmosphere model. Mon. Wea. Rev., 143, 4618–4630, doi:10. 1175/MWR-D-15-0097.1.CrossRefGoogle Scholar
  21. Coumou, D., and S. Rahmstorf, 2012: A decade of weather extremes. Nature Clim. Change, 2, 491–496, doi:10.1038/nclimate1452.Google Scholar
  22. Day, J. J., E. Hawkins, and S. Tietsche, 2014: Will Arctic sea ice thickness initialization improve seasonal forecast skill? Geophys. Res. Lett., 41, 7566–7575, doi:10.1002/2014GL061694.CrossRefGoogle Scholar
  23. 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.CrossRefGoogle Scholar
  24. Delsole, T., X. Yang, and M. K. Tippett, 2013: Is unequal weighting significantly better than equal weighting for multi-model forecasting? Quart. J. Roy. Meteor. Soc., 139, 176–183, doi:10.1002/qj.1961.CrossRefGoogle Scholar
  25. Diaz, H. F., M. P. Hoerling, and J. K. Eischeid, 2001: ENSO variability, teleconnections and climate change. Int. J. Climatol., 21, 1845–1862, doi:10.1002/joc.631.CrossRefGoogle Scholar
  26. Dirmeyer, P. A., 2000: Using a global soil wetness dataset to improve seasonal climate simulation. J. Climate, 13, 2900–2922, doi:10.1175/ 1520-0442(2000)013<2900:UAGSWD>2.0.CO;2.CrossRefGoogle Scholar
  27. Dirmeyer, P. A., 2003: The role of the land surface background state in climate predictability. Clim. Hydrometeorol., 4, 599–610, doi:10.1175/1525-7541(2003)004<0599:TROTLS>2.0.CO;2.CrossRefGoogle Scholar
  28. Dirmeyer, P. A., X. Gao, M. Zhao, Z. Guo, T. Oki, and N. Hanasaki, 2006: The second Global Soil Wetness Project (GSWP-2): Multimodel analysis and implications for our perception of the land surface. Bull. Amer. Meteor. Soc., 87, 1381–1397, doi:10.1175/BAMS-87-10-1381.CrossRefGoogle Scholar
  29. Doblas-Reyes, F. J., J. García-Serrano, F. Lienert, A. P. Biescas, and L. R. L. Rodrigues, 2013: Seasonal climate predictability and forecasting: status and prospects. WIREs Clim. Change, 4, 245–268, doi:10.1002/ wcc.217.CrossRefGoogle Scholar
  30. Douville, H., 2004: Relevance of soil moisture for seasonal atmospheric predictions: is it an initial value problem? Climate Dyn., 22, 429–446, doi:10.1007/s00382-003-0386-5.CrossRefGoogle Scholar
  31. Eade, R., E. Hamilton, D. M. Smith, R. J. Graham, and A. A. Scaife, 2012: Forecasting the number of extreme daily events out to a decade ahead. J. Geophys. Res., 117, D21110, doi:10.1029/2012JD018015.CrossRefGoogle Scholar
  32. Entin, J. K., A. Robock, K. Y. Vinnikov, S. E. Hollinger, S. Liu, and A. Namkhai, 2000: Temporal and spatial scales of observed soil moisture variations in the extratropics. J. Geophys. Res., 105, 11865–11877, doi: 10.1029/2000JD900051.CrossRefGoogle Scholar
  33. Fan, K., Y. Liu, and H. Chen, 2012: Improving the prediction of the East Asian summer monsoon: New Approaches. Wea. Forecasting, 27, 1017–1030, doi:10.1175/WAF-D-11-00092.1.CrossRefGoogle Scholar
  34. Fischer, E. M., S. I. Seneviratne, D. Lüthi, and C. Schär, 2007: Contribution of land-atmosphere coupling to recent European summer heat waves. Geophys. Res. Lett., 34, L06707, doi:10.1029/2006GL-029068.CrossRefGoogle Scholar
  35. Fletcher, C. G., S. C. Hardiman, P. J. Kushner, and J. Cohen, 2009: The dynamical response to snow cover perturbations in a large ensemble of atmospheric GCM integrations. J. Climate, 22, 1208–1222, doi:10.1175/ 2008JCLI2505.1.CrossRefGoogle Scholar
  36. Francis, J. A., and S. J. Vavrus, 2012: Evidence linking Arctic amplification to extreme weather in mid-latitudes. Geophys. Res. Lett., 39, L06801, doi:10.1029/2012GL051000.CrossRefGoogle Scholar
  37. Gerber, E. P., and Coauthors, 2012: Assessing and understanding the impact of stratospheric dynamics and variability on the earth system. Bull. Amer. Meteor. Soc., 93, 845–859, doi:10.1175/BAMS-D-11-00145.1.CrossRefGoogle Scholar
  38. Gong, D. Y., S. W. Wang, and J. H. Zhu, 2001: East Asian winter monsoon and Arctic oscillation. Geophys. Res. Lett., 28, 2073–2076, doi:10.1029/ 2000GL012311.CrossRefGoogle Scholar
  39. 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. Geophys. Res. Lett., 40, 1–6, doi:10.1002/grl.50729.CrossRefGoogle Scholar
  40. Hamilton, E., R. Eade, R. J. Graham, A. A. Scaife, D. M. Smith, A. Maidens, and C. MacLachlan, 2012: Forecasting the number of extreme daily events on seasonal timescales. J. Geophys. Res., 117, D03113, doi:10.1029/2011JD016541.Google Scholar
  41. Hawkins, E., S. Tietsche, J. J. Day, N. Melia, K. Haines, and S. Keeley, 2016: Aspects of designing and evaluating seasonal-to-interannual Arctic sea-ice prediction systems. Quart. J. Roy. Meteor. Soc., 142, 672–683, doi:10.1002/qj.2643.CrossRefGoogle Scholar
  42. Honda, M., J. Inoue, and S. Yamane, 2009: Influence of low Arctic sea-ice minima on anomalously cold Eurasian winters. Geophys. Res. Lett., 36, L08707, doi:10.1029/2008gl037079.CrossRefGoogle Scholar
  43. Hsieh, W., and B. Tang, 1998: Applying neural network models to prediction and data analysis in meteorology and oceanography. Bull. Amer. Meteor. Soc., 79, 1855–1870, doi:10.1175/1520-0477(1998)079<1855: ANNMTP>2.0.CO;2.CrossRefGoogle Scholar
  44. Hu, Q., and S. Feng, 2010: Influence of the Arctic Oscillation on central United States summer rainfall. J. Geophys. Res., 115, D01102, doi:10. 1029/2009JD011805.Google Scholar
  45. Jeong, H.-I., and Coauthors, 2012: Assessment of the APCC coupled MME suite in predicting the distinctive climate impacts of two flavors of ENSO during boreal winter. Climate Dyn., 39, 475–493, doi:10.1007/ s00382-012-1359-3.CrossRefGoogle Scholar
  46. 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. Climate Dyn., 44, 1073–1091, doi:10.1007/s00382-014-2127-3.CrossRefGoogle Scholar
  47. Jeong, J. H., and C. H. Ho, 2005: Changes in occurrence of cold surges over east Asia in association with Arctic Oscillation. Geophys. Res. Lett., 32, L14704, doi:10.1029/2005GL023024.CrossRefGoogle Scholar
  48. Jeong, H.-I., B. Kim, C. Ho, D. Chen, and G. Lim, 2006: Stratospheric origin of cold surge occurrence in East Asia. Geophys. Res. Lett., 33, L14710, doi:10.1029/2006GL026607.Google Scholar
  49. Jeong, H.-I., C.-H. Ho, D. Chen, and T.-W. Park, 2008: Land surface initialization using an offline CLM3 simulation with the GSWP-2 forcing dataset and its impact on CAM3 simulations of the boreal summer climate. J. Hydrometeorol., 9, 1231–1248, doi:10.1175/2008-JHM941.1.CrossRefGoogle Scholar
  50. Jeong, H.-I., T. Ou, H. W. Linderholm, B.-M. Kim, S.-J. Kim, J.-S. Kug, and D. Chen, 2011: Recent recovery of the Siberian high intensity. J. Geophys. Res., 116, D23102, doi:10.1029/2011JD015904.Google Scholar
  51. Jeong, H.-I., H. W. Linderholm, S.-H. Woo, C. Folland, B.-M. Kim, S.-J. Kim, and D. Chen, 2013: Impacts of snow initialization on subseasonal forecasts of surface air temperature for the cold season. J. Climate, 26, 1956–1972, doi:10.1175/JCLI-D-12-00159.1.CrossRefGoogle Scholar
  52. Jeong, H.-I., T.-W. Park, J.-H. Choi, S.-W. Son, K. Song, J.-S. Kug, B.-M. Kim, H.-K. Kim, and S.-Y. Yim, 2016: Assessment of climate variability over East Asia-Korea for 2015/16 winter. Atmosphere, 26, 337–345 (in Korean with English abstract).CrossRefGoogle Scholar
  53. Jung, T., M. A. Kasper, T. Semmler, and S. Serrar, 2014: Arctic influence on subseasonal midlatitude prediction. Geophys. Res. Lett., 41, 3676–3680, doi:10.1002/2014GL059961.CrossRefGoogle Scholar
  54. Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-year reanalysis project. Bull. Amer. Meteor. Soc., 77, 437–471, doi:10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.CrossRefGoogle Scholar
  55. Kang, D., M.-I. Lee, J. Im, D. Kim, H.-M. Kim, H.-S. Kang, S. D. Schubert, A. Arribas, and C. MacLachlan, 2014: Prediction of the Arctic Oscillation in boreal winter by dynamical seasonal forecasting systems. Geophys. Res. Lett., 41, 3577–3585, doi:10.1002/2014GL-060011.CrossRefGoogle Scholar
  56. Kang, I.-S., C.-H. Ho, and K.-D. Min, 1992: Long-range forecast of summer precipitation in Korea. J. Korean Meteor. Soc., 28, 283–292 (in Korean with English abstract).Google Scholar
  57. Kang, I.-S., 1998: Relationship between El Niño and climate variation over Korea peninsula. J. Korean Meteor. Soc., 34, 390–396 (in Korean with English abstract).Google Scholar
  58. Kang, I.-S., and Coauthors, 2002: Intercomparison of the climatological variations of Asian summer monsoon precipitation simulated by 10 GCMs. Climate Dyn., 19, 383–395, doi:10.1007/s00382-002-0245-9.CrossRefGoogle Scholar
  59. Kang, I.-S., and J. H. Yoo, 2006: Examination of multi-model ensemble seasonal prediction methods using a simple climate system. Climate Dyn., 26, 285–294, doi:10.1007/s00382-005-0074-8.CrossRefGoogle Scholar
  60. Kim, H.-J., and J.-B. Ahn, 2015: Improvement in Prediction of the Arctic Oscillation with a Realistic Ocean Initial Condition in a CGCM. J. Climate, 28, 8951–8967, doi:10.1175/JCLI-D-14-00457.1.CrossRefGoogle Scholar
  61. Kim, B.-M., E. Jung, G. Lim, and H. Kim, 2014a: Analysis on winter atmosphereic variability related to Arctic warming. Atmosphere, 24, 131–140 (in Korean with English abstract).CrossRefGoogle Scholar
  62. Kim, B.-M., S.-W. Son, S.-K. Min, J.-H. Jeong, S.-J. Kim, X. Zhang, T. Shim, and J.-H. Yoon, 2014b: Weakening of the stratospheric polar vortex by Arctic sea-ice loss. Nat. Commun., 5, 4646, doi:10.1038/ncomms5646.CrossRefGoogle Scholar
  63. Kim, G., J.-B. Ahn, V. N. Kryjov, S.-J. Sohn, W.-T. Yun, R. Graham, R. K. Kolli, A. Kumar, and J.-P. Ceron, 2016: Global and regional skill of the seasonal predictions by WMO Lead Centre for Long-Range Forecast Multi-Model Ensemble. Int. J. Climatol., 36, 1657–1675, doi:10.1002/ joc.4449.CrossRefGoogle Scholar
  64. Kim, H., P. J. Webster, and J. A. Curry, 2012: Seasonal prediction skill of ECMWF System 4 and NCEP CFSv2 retrospective forecast for the Northern Hemisphere Winter. Climate Dyn., 39, 2957–2973, doi:10. 1007/s00382-012-1364-6.CrossRefGoogle Scholar
  65. Kim, S., H.-S. Kim, S.-K. Min, H.-Y. Son, D.-J. Won, H.-S. Jung, and J.-S. Kug, 2015: Intra-winter atmospheric circulation changes over East Asia and North Pacific associated with ENSO in a seasonal prediction model. Asia-Pac. J. Atmos. Sci., 51, 49–60, doi:10.1007/s13143-014-0059-9.CrossRefGoogle Scholar
  66. Kim, S., H.-Y. Son, and J.-S. Kug, 2016: How well do climate models simulate atmospheric teleconnctions over the North Pacific and East Asia associated with ENSO? Climate Dyn., doi:100.1007/s00382-016-3121-8.Google Scholar
  67. Kirtman, B., and A. Pirani, 2009: The state of art of seasonal prediction: outcomes and recommendations from the first world climate research program workshop on seasonal prediction. Bull. Amer. Meteor. Soc., 90, 455–458, doi:10.1175/2008BAMS2707.1.CrossRefGoogle Scholar
  68. Kirtman, B., and Coauthors, 2014: The North American multimodel ensemble: phase-1 seasonal-to-interannual prediction; phase-2 toward developing intraseasonal prediction. Bull. Amer. Meteor. Soc., 95, 585–601, doi:10. 1175/BAMS-D-12-00050.1.CrossRefGoogle Scholar
  69. Kosaka, Y., J. S. Chowdary, S.-P. Xie, Y.-M. Min, and J.-Y. Lee, 2012: Limitations of seasonal predictability for summer climate over East Asia and the Northwestern Pacific. J. Climate, 25, 7574–7589, doi:10.1175/JCLI-D-12-00009.1.CrossRefGoogle Scholar
  70. Koster, R. D., and Coauthors, 2004a: Regions of strong coupling between soil moisture and precipitation. Science, 305, 1138–1140, doi:10.1126/ science.1100217.CrossRefGoogle Scholar
  71. Koster, R. D., M. J. Suarez, P. Liu, U. Jambor, A. Berg, M. Kistler, R. Reichle, M. Rodell, and J. Famiglietti, 2004b: Realistic initialization of land surface states: Impacts on subseasonal forecast skill. J. Hydrometeorol., 5, 1049–1063, doi:10.1175/JHM-387.1.CrossRefGoogle Scholar
  72. Koster, R. D., and Coauthors, 2006: GLACE: The Global Land-Atmosphere Coupling Experiment. Part I: Overview. J. Hydrometeorol., 7, 590–610, doi:10.1175/JHM510.1.Google Scholar
  73. Koster, R. D., and Coauthors, 2010: Contribution of land surface initialization to subseasonal forecast skill: First results from a multi-model experiment. Geophys. Res. Lett., 37, L02402, doi:10.1029/2009GL041677.CrossRefGoogle Scholar
  74. Koster, R. D., and Coauthors, 2011: The second phase of the global landatmosphere coupling experiment: Soil moisture contributions to subseasonal forecast skill. J. Hydrometeorol., 12, 805–822, doi:10.1175/ 2011JHM1365.1.CrossRefGoogle Scholar
  75. 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-Pac. J. Atmos. Sci., 44, 259–267.Google Scholar
  76. Kug, J.-S., F.-F. Jin, and S.-I. An, 2009: Two types of El Niño events: Cold tongue El Niño and warm pool El Niño. J. Climate, 22, 1499–1515, doi:10.1175/2008JCLI2624.1.CrossRefGoogle Scholar
  77. Kug, J.-S., M.-S. Ahn, M.-K. Sung, S.-W. Yeh, H.-S. Min, and Y.-H. Kim, 2010: Statistical relationship between two types of El Nino events and climate variation over Korean Peninsula. Asia-Pac. J. Atmos. Sci., 46, 467–474, doi:10.1007/s13143-010-0027-y.CrossRefGoogle Scholar
  78. Kug, J.-S., J.-H. Jeong, Y.-S. Jang, B.-M. Kim, C. K. Folland, S.-K. Min, and S.-W. Son, 2015: Two distinct influences of Arctic warming on cold winters over North America and East Asia. Nat. Geosci., 8, 759–762, doi:10.1038/ngeo2517.CrossRefGoogle Scholar
  79. Kumar, A., and F. Yang, 2003: Comparative influence of snow and SST variability on extratropical climate in northern winter. J. Climate, 16, 2248–2261, doi:10.1175/2771.1.CrossRefGoogle Scholar
  80. Kumar, A., D. Pai, J. Singh, R. Singh, and D. Sikka, 2012: Statistical models for long-range forecasting of Southwest monsoon rainfall over India using stepwise regression and neural network. Atm. Clim. Sci., 2, 322–336, doi:10.4236/acs.2012.23029.Google Scholar
  81. Kunkel, K. E., S. A. Changnon, B. C. Reinke, and R. W. Arritt, 1996: The July 1995 heat wave in the Midwest: A climatic perspective and critical weather factors. Bull. Amer. Meteor. Soc., 77, 1507–1518, doi:10.1175/ 1520-0477(1996)077<1507:TJHWIT>2.0.CO;2.CrossRefGoogle Scholar
  82. Kuroda, Y., 2008: Role of the stratosphere on the predictability of mediumrange weather forecast: A case study of winter 2003-2004. Geophys. Res. Lett., 35, L19701, doi:10.1029/2008GL034902.CrossRefGoogle Scholar
  83. Kwon, M., and K.-J. Lee, 2014: A prediction of Northeast Asian summer precipitation using the NCEP climate forecast system and canonical correlation analysis. J. Korean Meteor. Soc., 35, 88–94 (in Korean with English abstract).Google Scholar
  84. Lau, K.-M., K.-M. Kim, and S. Yang, 2000: Dynamical and boundary forcing characteristics of regional components of the Asian summer monsoon. J. Climate, 13, 2461–2482, doi:10.1175/1520-0442(2000)013 <2461:DABFCO>2.0.CO;2.CrossRefGoogle Scholar
  85. Lau, K.-M., K.-M. Kim, and J.-Y. Lee, 2004: Interannual variability, global teleconnection, and potential predictability associated with the Asian summer monsoon. In C.-P. Chang Ed., World Scientific Series on Meteorology of East Asia, Vol. 2. World Scientific, 153–176.Google Scholar
  86. Lau, K.-M., and K.-M. Kim, 2012: The 2010 Pakistan flood and Russian heat wave: Teleconnection of hydrometeorological extremes. J. Hydrometeorol., 13, 392–403, doi:10.1175/JHM-D-11-016.1.CrossRefGoogle Scholar
  87. Lee, D.-Y., J.-B. Ahn, and K. Ashok, 2013a: Improvement of multimodel ensemble seasonal prediction skill over East Asia summer monsoon region using a climate filter concept. J. Appl. Meteor. Clim., 52, 1127–1138, doi:10.1175/JAMC-D-12-0123.1.CrossRefGoogle Scholar
  88. 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. Climate Dyn., 45, 1025–1042, doi:10.1007/s00382-014-2343-x.CrossRefGoogle Scholar
  89. Lee, E.-J., J.-G., Jhun, and C.-K. Park, 2005: Remote connection of the east-Asian summer rainfall variation revealed by a newly defined monsoon index. J. Climate, 17, 4381–4393, doi:10.1175/JCLI3545.1.CrossRefGoogle Scholar
  90. Lee, H.-J., W.-S. Lee, and J.-H. Yoo, 2016: Assessment of medium-range ensemble forecasts of heat waves. Atmos. Sci. Lett., 17, 19–25, doi: 10.1002/asl.593.CrossRefGoogle Scholar
  91. Lee, J.-Y., and Coauthors, 2010: How are seasonal prediction skills related to models’ performance on mean state and annual cycle? Climate Dyn., 35, 267–283, doi:10.1007/s00382-010-0857-4.Google Scholar
  92. Lee, J.-Y., and Coauthors, 2011a: How predictable is the Northern Hemisphere summer upper-tropospheric circulation? Climate Dyn., 37, 1189–1203, doi:10.1007/s00382-010-0909-9.Google Scholar
  93. Lee, J.-Y., S.-S. Lee, B. Wang, K.-J. Ha, and J.-G. Jhun, 2013b: Seasonal prediction and predictability of the Asian winter temperature variability. Climate Dyn., 41, 573–587, doi:10.1007/s00382-012-1588-5.CrossRefGoogle Scholar
  94. 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, 8634–8647, doi:10. 1175/JCLI-D-15-0154.1.CrossRefGoogle Scholar
  95. Lee, S.-E., and K.-H. Seo, 2013: The development of a statistical forecast model for Changma. Wea. Forecasting, 28, 1304–1321, doi:10.1175/ WAF-D-13-00003.1.CrossRefGoogle Scholar
  96. Lee, S.-S., J.-Y. Lee, K.-J. Ha, B. Wang, and J. K. E. Schemm, 2011b: Deficiencies and possibilities for long-lead coupled climate prediction of the western North Pacific-East Asian summer monsoon. Climate Dyn., 36, 1173–1188, doi:10.1007/s00382-010-0832-0.CrossRefGoogle Scholar
  97. Lee, W.-S., and M.-I. Lee, 2016: Interannual variability of heat waves in South Korea and their connection with large-scale atmospheric circulation patterns. Int. J. Climatol., 36, 4815–4830, doi:10.1002/joc.4671.CrossRefGoogle Scholar
  98. Li, J.-Y., and J.-Y. Mao, 2016: Experimental 15-day-lead statistical forecast of intraseasonal summer monsoon rainfall over Eastern China. Atmos. Ocean. Sci. Lett., 9, 66–73, doi:10.1080/16742834.2015.1126152.CrossRefGoogle Scholar
  99. Liptak, J., and C. Strong, 2014: The winter atmospheric response to sea ice anomalies in the Barents Sea. J. Climate, 27, 914–924, doi:10.1175/ JCLI-D-13-00186.1.CrossRefGoogle Scholar
  100. Liu, J., J. A. Curry, H. Wang, M. Song, and R. M. Horton, 2012: Impact of declining Arctic sea ice on winter snowfall. Proc. National Academy of Sciences, 109, 4074–4079, doi:10.1073/pnas.1114910109.CrossRefGoogle Scholar
  101. Luo, J.-J., S. K. Behera, Y. Masumoto, and T. Yamagata, 2011: Impact of global ocean surface warming on seasonal-to-interannual climate prediction. J. Climate, 24, 1626–1646, doi: 10.1175/2010JCLI3645.1.CrossRefGoogle Scholar
  102. MacLachlan, C., and Coauthors, 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.CrossRefGoogle Scholar
  103. Manney, G. L., and Coauthors, 2008: The high Arctic in extreme winters: vortex, temperature, and MLS and ACE-FTS trace gas evolution. Atmos. Chem. Phys., 8, 505–522, doi:10.5194/acp-8-505-2008.CrossRefGoogle Scholar
  104. Marshall, A. G., D. Hudson, M. C. Wheeler, O. Alves, H. H. Hendon, M. J. Pook, and J. S. Risbey, 2014: Intra-seasonal drivers of extreme heat over Australia in observations and POAMA-2. Climate Dyn., 43, 1915–1937, doi:10.1007/s00382-013-2016-1.CrossRefGoogle Scholar
  105. Martineau, P., and S.-W. Son, 2015: Onset of circulation anomalies during stratospheric vortex weakening events: The role of planetary-scale waves. J. Climate, 28, 7347–7370, doi:10.1175/JCLI-D-14-00478.1.CrossRefGoogle Scholar
  106. McPhaden, M. J., S. E. Zebiak, and M. H. Glantz, 2006: ENSO as an integrating concept in Earth science. Science, 314, 1740–1745, doi:10. 1126/science.1132588.CrossRefGoogle Scholar
  107. Meehl, G. A., and C. Tebaldi., 2004: More intense, more frequent, and longer lasting heatwaves in the 21st century. Science, 305, 994–997, doi:10.1126/science.1098704.CrossRefGoogle Scholar
  108. Michaelsen, J., 1987: Cross-validation in statistical climate forecast models. J. Climate Appl. Meteor., 26, 1589–1600, doi:10.1175/1520-0450(1987)026<1589:CVISCF>2.0.CO;2.CrossRefGoogle Scholar
  109. Min, S.-K., X. Zhang, F. W. Zwiers, and G. C. Hegerl, 2011: Human contribution to more-intense precipitation extremes. Nature, 470, 378–381, doi:10.1038/nature09763.CrossRefGoogle Scholar
  110. Min, S.-K., Y.-H. Kim, M.-K. Kim, and C. Park, 2014: Assessing human contribution to the summer 2013 Korean heat wave. Bull. Amer. Meteor. Soc., 95, S48–S51, doi:10.1175/1520-0477-95.9.S1.1.Google Scholar
  111. Min, S.-K., and Coauthors, 2015: Changes in weather and climate extremes over Korea and possible causes: A review. Asia-Pac. J. Atmos. Sci., 51, 103–121, doi:10.1007/s13143-015-0066-5.CrossRefGoogle Scholar
  112. Min, Y.-M., V. N. Kryjov, and C.-K. Park, 2009: A probabilistic multimodel ensemble approach to seasonal prediction. Wea. Forecasting, 24, 812–828, doi:10.1175/2008WAF2222140.1.CrossRefGoogle Scholar
  113. Miralles, D. G., A. J. Teuling, C. C. van Heerwaarden, and J. V.-G. de Arellano, 2014: Mega-heatwave temperatures due to combined soil desiccation and atmospheric heat accumulation. Nat. Geosci., 7, 345–349, doi:10.1038/ngeo2141.CrossRefGoogle Scholar
  114. Mo, R., and D. M. Straus, 2002: Statistical-dynamical seasonal prediction based on principal component regression of GCM ensemble integrations. Mon. Wea. Rev., 130, 2167–2187, doi:10.1175/1520-0493 (2002)130<2167:SDSPBO>2.0.CO;2.CrossRefGoogle Scholar
  115. Mori, M., M. Watanabe, H. Shiogama, J. Inoue, and M. Kimoto, 2014: Robust Arctic sea-ice influence on the frequent Eurasian cold winters in past decades. Nat. Geosci., 7, 869–873, doi:10.1038/ngeo2277.CrossRefGoogle Scholar
  116. Msadek, R., G. A. Vecchi, M. Winton, and R. G. Gudgel, 2014: Importance of initial conditions in seasonal predictions of Arctic sea ice extent. Geophys. Res. Lett., 41, 5208–5215, doi:10.1002/2014GL060799.CrossRefGoogle Scholar
  117. National Research Council, 2010: Assessment of Intraseasonal to Interannual Climate Prediction and Predictability. National Academies Press, 192 pp.Google Scholar
  118. Oglesby, R. J., and D. J. Erickson III, 1989: Soil moisture and the persistence of North American drought. J. Climate, 2, 1362–1380, doi: 10.1175/1520-0442(1989)002<1362:SMATPO>2.0.CO;2.CrossRefGoogle Scholar
  119. Oleson, K. W., and Coauthors, 2010: Technical Description of version 4.0 of the Community Land Model (CLM). NCAR Technical Note NCAR/ TN-478+STR, National Center for Atmospheric Research, Boulder, CO, 257 pp.Google Scholar
  120. Orsolini, Y. J., and N. G. Kvamstø, 2009: Role of Eurasian snow cover in wintertime circulation: Decadal simulations forced with satellite observations. J. Geophys. Res., 114, D19108, doi:10.1029/2009JD-012253.CrossRefGoogle Scholar
  121. Orsolini, Y. J., R. Senan, F. Vitart, G. Balsamo, A. Weisheimer, and F. J. Doblas-Reyes, 2016: Influence of the Eurasian snow on the negative North Atlantic Oscillation in subseasonal forecasts of the cold winter 2009/ 2010. Climate Dyn., 47, 1325–1334, doi:10.1007/s00382-015-2903-8.CrossRefGoogle Scholar
  122. Overland, J. E., K. R. Wood, and M. Wang, 2011: Warm Arctic -cold continents: climate impacts of the newly open Arctic Sea. Polar Res., 30, doi:10.3402/polar.v30i0.15787.Google Scholar
  123. Palecki, M. A., S. A. Changnon, and K. E. Kunkel, 2001: The nature and impacts of the July 1999 heat wave in the Midwestern United States: learning from the lessons of 1995. Bull. Amer. Meteor. Soc., 82, 1353–1367, doi:10.1175/1520-0477(2001)082<1353:TNAIOT>2.3.CO;2.CrossRefGoogle Scholar
  124. Palmer, T., and Coauthors, 2004: Development of a European Multi-Model Ensemble System for Seasonal to Inter-Annual Prediction (DEMETER) Bull. Amer. Meteor. Soc., 85, 853–872, doi:10.1175/BAMS-85-6-853.CrossRefGoogle Scholar
  125. Park, C. K., and S. D. Schubert, 1997: On the nature of the 1994 East Asian summer drought. J. Climate, 10, 1056–1070, doi:10.1175/1520-0442(1997)010<1056:OTNOTE>2.0.CO;2.CrossRefGoogle Scholar
  126. Peings, Y., H. Douville, R. Alkama, and B. Decharme, 2011: Snow contribution to springtime atmospheric predictability over the second half of the twentieth century. Climate Dyn., 37, 985–1004, doi:10.1007/ s00382-010-0884-1.CrossRefGoogle Scholar
  127. Pepler, A. S., L. B. Diaz, C. Prodhomme, F. J. Doblas-Reyes, and A. Kumar 2015: The ability of a multi-model seasonal forecasting ensemble to forecast the frequency of warm, cold and wet extremes. Wea. Clim. Extremes, 9, 68–77, doi:10.1016/j.wace.2015.06.005.CrossRefGoogle Scholar
  128. Petoukhov, V., and V. A. Semenov, 2010: A link between reduced Barents-Kara sea ice and cold winter extremes over northern continents. J. Geophys. Res., 115, D21111, doi:10.1029/2009JD013568.CrossRefGoogle Scholar
  129. Robertson, A. W., A. Kumar, M. Peña, and F. Vitart, 2015: Improving and promoting subseasonal to seasonal prediction. Bull. Amer. Meteor. Soc., 96, ES49–ES53, doi:10.1175/BAMS-D-14-00139.1.CrossRefGoogle Scholar
  130. Robock, A., K. Y. Vinnikov, G. Srinivasan, J. K. Entin, S. E. Hollinger, N. A. Speranskaya, S. Liu, and A. Namkhai, 2000: The global soil moisture data bank. Bull. Amer. Meteor. Soc., 81, 1281–1299, doi:10. 1175/1520-0477(2000)081<1281:TGSMDB>2.3.CO;2.CrossRefGoogle Scholar
  131. Roff, G., D. W. J. Thompson, and H. Hendon, 2011: Does increasing model stratospheric resolution improve extended-range forecast skill? Geophys. Res. Lett., 38, doi:10.1029/2010GL046515.Google Scholar
  132. Ropelewski, C. F., and M. S. Halpert, 1987: Global and regional scale precipitation patterns associated with the El Nino/Southern Oscillatoin. Mon. Wea. Rev., 115, 1606–1626, doi:10.1175/1520-0493(1987)115 <1606:GARSPP>2.0.CO;2.CrossRefGoogle Scholar
  133. Scaife, A. A., and Coauthors, 2014: Skillful long-range prediction of European and North American winters. Geophys. Res. Lett., 41, 2514–2519, doi:10.1002/2014GL059637.CrossRefGoogle Scholar
  134. Scaife, A. A., and Coauthors, 2016: Seasonal winter forecasts and the stratosphere. Atmos. Sci. Lett., 17, 51–56, doi:10.1002/asl.598.CrossRefGoogle Scholar
  135. Schubert, S., H. Wang, and M. Suarez, 2011: Warm season subseasonal variability and climate extremes in the Northern Hemisphere: the role of stationary Rossby waves. J. Climate, 24, 4773–4792, doi:10.1175/JCLID-10-05035.1.CrossRefGoogle Scholar
  136. Screen, J. A., and I. Simmonds, 2010: The central role of diminishing sea ice in recent Arctic temperature amplification. Nature, 464, 1334–1337, doi:10.1038/nature09051.CrossRefGoogle Scholar
  137. Shukla, J., and Coauthors, 2000: Dynamical seasonal prediction. Bull. Amer. Meteor. Soc., 81, 2593–2606, doi:10.1175/1520-0477(2000)081 <2593:DSP>2.3.CO;2.CrossRefGoogle Scholar
  138. Semenov, V. A., and M. Latif, 2015: Nonlinear winter atmospheric circulation response to Arctic sea ice concentration anomalies for different periods during 1966-2012. Environ. Res. Lett., 10, 054020, doi:10.1088/1748-9326/10/5/054020.CrossRefGoogle Scholar
  139. Seneviratne, S. I., T. Corti, E. L. Davin, M. Hirschi, E. B. Jaeger, I. Lehner, B. Orlowsky, and A. J. Teuling, 2010: Investigating soil moistureclimate interactions in a changing climate: A review. Earth-Sci. Rev., 99, 125–161, doi:10.1016/j.earscirev.2010.02.004.CrossRefGoogle Scholar
  140. Seo, K.-H., J.-H. Son, J.-Y. Lee, and H.-S. Park, 2015: Northern East Asian monsoon precipitation revealed by airmass variability and its prediction. J. Climate, 28, 6221–6223, doi:10.1175/JCLI-D-14-00526.1.CrossRefGoogle Scholar
  141. Seviour, W. J. M., S. C. Hardiman, L. J. Gray, N. Butchart, C. MacLachlan, and A. A. Scaife, 2014: Skillful seasonal prediction of the Southern Annular Mode and Antarctic ozone. J. Climate, 27, 7462–7474, doi:10. 1175/JCLI-D-14-00264.1.CrossRefGoogle Scholar
  142. Sheffield, J., G. Goteti, and E. F. Wood, 2006: Development of a 50-yr high-resolution global dataset of meteorological forcings for land surface modeling. J. Climate, 19, 3088–3111, doi:10.1175/JCLI3790.1.CrossRefGoogle Scholar
  143. Shim, T., J.-H. Jeong, J. OK, H.-S. Jeong, and B.-M. Kim, 2015: Development and assessment of dynamical seasonal forecast system using the cryospheric variables. Atmosphere, 25, 155–167, doi:10. 14191/Atmos.2015.25.1.155 (in Korean with English abstract).CrossRefGoogle Scholar
  144. Sigmond, M., J. F. Scinocca, V. V. Kharin, and T. G. Shepherd, 2013: Enhanced seasonal forecast skill following stratospheric sudden warmings. Nat. Geosci., 6, 98–102, doi:10.1038/ngeo1698.CrossRefGoogle Scholar
  145. 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 long-lead 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, doi:10.1029/2011JD016308.CrossRefGoogle Scholar
  146. Son, S.-W., A. Purich, H. H. Hendon, B.-M. Kim, and L. M. Polvani, 2013: Improved seasonal forecast using ozone hole variability? Geophys. Res. Lett., 40, 6231–6235, doi:10.1002/2013GL057731.CrossRefGoogle Scholar
  147. Song, K., S.-W. Son, and S.-H. Woo, 2015: Impact of sudden stratospheric warming on the surface air temperature in East Asia. Atmosphere, 25, 461–472, doi:10.14191/Atmos.2015.25.3.461 (in Korean with English abstract).CrossRefGoogle Scholar
  148. Sperber, K. R., C. Brankovic, M. Déqué, C. S. Frederiksen, R. Graham, A. Kitoh, C. Kobayashi, T. Palmer, K. Puri, W. Tennant, and E. Volodin, 2001: Dynamical seasonal predictability of the Asian summer monsoon. Mon. Wea. Rev., 129, 2226–2248, doi:10.1175/1520-0493(2001) 129<2226:DSPOTA>2.0.CO;2.CrossRefGoogle Scholar
  149. Stockdale, T., 2013: The EUROSIP system -a multi-model approach. Proc. ECMWF Seminar on Seasonal Prediction, 257–268.Google Scholar
  150. Stroeve, J., L. C. Hamilton, C. M. Bitz, and E. Blanchard-Wrigglesworth, 2014: Predicting September sea ice: Ensemble skill of the SEARCH sea ice outlook 2008-2013. Geophys. Res. Lett., 41, 2411–2418, doi:10. 1002/2014GL059388.CrossRefGoogle Scholar
  151. Sun, J. Q., 2014: Record-breaking SST over mid-North Atlantic and extreme high temperature over the Jianghuai-Jiangnan region of China in 2013. Chinese Sci. Bull., 59, 3465–3470, doi:10.1007/s11434-014-0425-0.CrossRefGoogle Scholar
  152. Sun, J., and J.-B. Ahn, 2015: Dynamical seasonal predictability of the Arctic Oscillation using a CGCM. Int. J. Climatol., 35, 1342–1353, doi: 10.1002/joc.4060.CrossRefGoogle Scholar
  153. Tang, Q., X. Zhang, X. Yang, and J. Francis, 2013: Cold winter extremes in northern continents linked to Arctic sea ice loss. Environ. Res. Lett., 8, 014036, doi:10.1088/1748-9326/8/1/014036.CrossRefGoogle Scholar
  154. Teng, H., G. Branstator, H. Wang, G. A. Meehl, and W. M. Washington, 2013: Probability of US heat waves affected by a subseasonal planetary wave pattern. Nat. Geosci., 6, 1056–1061, doi:10.1038/ngeo1988.CrossRefGoogle Scholar
  155. Thompson, D. W. J., and J. M. Wallace, 1998: The Arctic oscillation signature in the wintertime geopotential height and temperature fields. Geophys. Res. Lett., 25, 1297–1300, doi:10.1029/98GL00950.CrossRefGoogle Scholar
  156. Thompson, D. W. J., and J. M. Wallace, 2001: Regional climate impacts of the Northern Hemisphere annular mode. Science, 293, 85–89, doi:10.1126/science. 1058958.CrossRefGoogle Scholar
  157. Thompson, D. W. J., M. P. Baldwin, and J. M. Wallace, 2002: Stratospheric connection to Northern Hemisphere wintertime weather: implications for prediction. J. Climate, 15, 1421–1428, doi:10.1175/1520-0442(2002) 015<1421:SCTNHW>2.0.CO;2.CrossRefGoogle Scholar
  158. Tietsche, S., J. J. Day, V. Guemas, W. J. Hurlin, S. P. E. Keeley, D. Matei, R. Msadek, M. Collins, and E. Hawkins, 2014: Seasonal to interannual Arctic sea ice predictability in current global climate models. Geophys. Res. Lett., 41, 1035–1043, doi:10.1002/2013GL058755.CrossRefGoogle Scholar
  159. Tomita, T., and T. Yasunari, 1996: Role of the northeast winter monsoon on the biennial oscillation of the ENSO/monsoon system. J. Meteor. Soc. Japan, 74, 399–413.Google Scholar
  160. Trenberth, K., G. W. Branstator, D. karoly, A. Kumar, N.-C. Lau, and C. Ropelewski, 1998: Progress during TOGA in understanding and modeling global teleconnections associated with tropical sea surface temperatures. J. Geophys. Res., 103, 14291–14324, doi:10.1029/97JC-01444.CrossRefGoogle Scholar
  161. Tripathi, O. P., and Coauthors, 2015a: 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.CrossRefGoogle Scholar
  162. Tripathi, O. P., A. Charlton-Perez, M. Sigmond, and F. Vitart, 2015b: Enhancing long-range forecast skill in boreal winter following stratospheric strong vortex conditions. Environ. Res. Lett., 10, 104007, doi:10.1088/1748-9326/10/10/104007.CrossRefGoogle Scholar
  163. 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., 118, 5147–5159, doi:10.1002/jgrd.50367.CrossRefGoogle Scholar
  164. Vihma, T., 2014: Effects of Arctic sea ice decline on weather and climate: A review. Surv. Geophys., 35, 1175–1214, doi:10.1007/s10712-014-9284-0.CrossRefGoogle Scholar
  165. Vitart, F., 2014: Evolution of ECMWF sub-seasonal forecast skill scores. Quart. J. Roy. Meteor. Soc., 140, 1889–1899, doi:10.1002/qj.2256.CrossRefGoogle Scholar
  166. Wagner, W., G. Lemoine, and H. Rott, 1999: A method for estimating soil moisture from ERS scatterometer and soil data. Remote Sens. Environ., 70, 191–207, doi:10.1016/S0034-4257(99)00036-X.CrossRefGoogle Scholar
  167. Wang, B., R. Wu, and X. Fu, 2000: Pacific-East Asian teleconnection: how does ENSO affect East Asian climate? J. Climate, 13, 1571–1536, doi:10.1175/1520-0442(2000)013<1517:PEATHD>2.0.CO;2.Google Scholar
  168. Wang, B., and T. Li, 2004: East Asian Monsoon-ENSO interactions. In C.-P. Chang Ed., East Asian Monsoon, World Scientific Series on Meteorology of East Asia, Vol. 2. World Scientific, 177–212.CrossRefGoogle Scholar
  169. Wang, B., and Coauthors, 2008: How accurately do coupled climate models predict the leading modes of Asian-Australian monsoon interannual variability? Climate Dyn., 30, 605–619, doi:10.1007/s00382-007-0310-5.CrossRefGoogle Scholar
  170. Wang, B., and Coauthors, 2009: Advance and prospectus of seasonal prediction: Assessment of APCC/CliPAS 14-model ensemble retrospective seasonal prediction (1980-2004). Climate Dyn., 33, 93–117, doi:10.1007/s00382-008-0460-0.CrossRefGoogle Scholar
  171. Wang, B., B. Xiang, and J.-Y. Lee, 2013a: Subtropical high predictability establishes a promising way for monsoon and tropical storm predictions. Proc. Natl. Acad. Sci., 110, 2718–2722, doi:10.1073/pnas. 1214626110.CrossRefGoogle Scholar
  172. Wang, B., J.-Y. Lee, and B. Xiang, 2015: Asian summer monsoon rainfall predictability: A predictable mode analysis. Climate Dyn., 44, 61–74, doi:10.1007/s00382-014-2218-1.CrossRefGoogle Scholar
  173. Wang, L., and W. Chen, 2014: The East Asian winter monsoon: Reamplification in the mid-2000s. Chinese Sci. Bull., 59, 430–436, doi:10.1007/s11434-013-0029-0.CrossRefGoogle Scholar
  174. Wang, W. W., W. Zhou, X. Wang, S. K. Fong, and K. C. Leong, 2013b: Summer high temperature extremes in southeast China associated with the East Asian jet stream and circumglobal teleconnection. J. Geophys. Res., 118, 8306–8319, doi:10.1002/jgrd.50633.Google Scholar
  175. Weisheimer, A., and Coauthors, 2009: ENSEMBLES: A new multi-model ensemble for seasonal-to-annual predictions—Skill and progress beyond DEMETER in forecasting tropical Pacific SSTs. Geophy. Res. Lett., 36, doi:10.1029/2009GL040896.Google Scholar
  176. Weng, H., K. Ashok, S. K. Behera, S. A. Rao, and T. Yamagata, 2007: Impacts of recent El Niño Modoki on dry/wet conditions in the Pacific rim during boreal summer. Climate Dyn., 29, 113–129, doi:10.1007/ s00382-007-0234-0.CrossRefGoogle Scholar
  177. Winton, M., 2006a: Amplified Arctic climate change: What does surface albedo feedback have to do with it? Geophys. Res. Lett., 33, L03701, doi:10.1029/2005GL025244.Google Scholar
  178. Winton, M., 2006b: Surface albedo feedback estimates for the AR4 climate models. J. Climate, 19, 359–365, doi:10.1175/JCLI3624.1.CrossRefGoogle Scholar
  179. Woo, S.-H., M.-K. Sung, S.-W. Son, and J.-S. Kug, 2015: Connection between weak stratospheric vortex events and the Pacific Decadal Oscillation. Climate Dyn., 45, 3481–3492, doi:10.1007/s00382-015-2551-z.CrossRefGoogle Scholar
  180. Wu, Z., B. Wang, J. Li, and F.-F. Jin, 2009: An empirical seasonal prediction model of the East Asian summer monsoon using ENSO and NAO. J. Geophys. Res., 114, D18120, doi:10.1029/2009JD011733.CrossRefGoogle Scholar
  181. Wu, Z., and L. Yu, 2016: Seasonal prediction of the East Asian summer monsoon with a partial-least square model. Climate Dyn., 46, 3067–3078, doi:10.1007/s00382-015-2753-4.CrossRefGoogle Scholar
  182. Wu, Z., H. Lin, J. Li, Z. Jiang, and T. Ma, 2012: Heat wave frequency variability over North America: Two distinct leading modes. J. Geophys. Res., 117, D02102, doi:10.1029/2011JD016908.Google Scholar
  183. Xoplaki, E., J. F. González-Rouco, J. Luterbacher, and H. Wanner, 2003: Mediterranean summer air temperature variability and its connection to the large-scale atmospheric circulation and SSTs. Climate Dyn., 20, 723–739, doi:10.1007/s00382-003-0304-x.Google Scholar
  184. Yang, S., Z. Zhang, V. Kousky, R. Higgins, S.-H. Yoo, J. Liang, and Y. Fan, 2008: Simulations and seasonal prediction of Asian summer monsoon in the NCEP climate forecast system. J. Climate, 21, 3755–3775, doi:10.1175/2008JCLI1961.1.CrossRefGoogle Scholar
  185. Yeh, S.-W., J.-S. Kug, B. Dewitte, M.-H. Kwon, B. P. Kirtman, and F.-F. Jin, 2009: El Nino in a changing climate. Nature, 461, 511–514, doi:10.1038/nature08316.CrossRefGoogle Scholar
  186. Yoo, J. H., and I.-S. Kang, 2005: Theoretical examination of a multi-model composite for seasonal prediction. Geophys. Res. Lett., 32, L18707, doi:10.1029/ 2005GL023513.CrossRefGoogle Scholar
  187. Yoo, J. H., J. Cho, S. Hameed, R. Field, K. F. Kwan, and I. Albar, 2016: Toward a fire and haze early warning system for Southeast Asia. APN Science Bull., 6, 13–20.Google Scholar
  188. Yun, K.-S., Y.-W. Seo, K.-J. Ha, J.-Y. Lee, and Y. Kajikawa, 2014: Interdecadal changes in the Asian winter monsoon variability and its relationship with ENSO and AO. Asia-Pac. J. Atmos. Sci., 50, 531–540, doi:10.1007/s13143-014-0042-5.CrossRefGoogle Scholar
  189. Yun, W. T., L. Stefanova, and T. N. Krishnamurti, 2003: Improvement of the multimodel superensemble technique for seasonal forecasts. J. Climate, 16. 3834–3840, doi:10.1175/1520-0442(2003)016<3834: IOTMST> 2.0.CO;2.CrossRefGoogle Scholar
  190. Zhang, R., A. Sumi, and M. Kimoto, 1996: Impact of El Niño on the East Asian monsoon: A diagnostic study of the ‘86/87 and ‘91/92 events. J. Meteor. Soc. Japan, 74, 49–62.Google Scholar
  191. Zhang, X., L. Alexander, G. C. Hegerl, P. Jones, A. K. Tank, T. C. Peterson, B. Trewin, and F. W. Zwiers, 2011: Indices for monitoring changes in extremes based on daily temperature and precipitation data. Clim. Change, 2, 851–870, doi:10.1002/wcc.147.Google Scholar

Copyright information

© Korean Meteorological Society and Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  • Jee-Hoon Jeong
    • 1
    • 11
  • Hyunsoo Lee
    • 2
  • Jin Ho Yoo
    • 3
  • MinHo Kwon
    • 4
  • Sang-Wook Yeh
    • 5
  • Jong-Seong Kug
    • 6
  • Jun-Yi Lee
    • 7
  • Baek-Min Kim
    • 8
  • Seok-Woo Son
    • 9
  • Seung-Ki Min
    • 6
  • Hansu Lee
    • 6
  • Woo-Seop Lee
    • 3
  • Jin-Ho Yoon
    • 10
  • Hyun-kyung Kim
    • 2
  1. 1.Faculty of Earth and Environmental SciencesChonnam National UniversityGwangjuKorea
  2. 2.Korea Meteorological AdministrationSeoulKorea
  3. 3.APEC Climate CenterBusanKorea
  4. 4.Physical Oceanography DivisionKorea Institute of Ocean Science and TechnologyAnsanKorea
  5. 5.Department of Marine Sciences and Convergent Technology, Hanyang UniversityERICAAnsanKorea
  6. 6.Division of Environmental Science and EngineeringPohang University of Science and Technology (POSTECH)PohangKorea
  7. 7.Research Center for Climate SciencesPusan National UniversityBusanKorea
  8. 8.Korea Polar Research InstituteInchonKorea
  9. 9.School of Earth and Environmental SciencesSeoul National UniversitySeoulKorea
  10. 10.School of Earth Sciences and Environmental EngineeringGwangju Institute of Science and TechnologyGwangjuKorea
  11. 11.Faculty of Earth and Environmental SciencesChonnam National UniversityGwangjuKorea

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