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8 - Basin Interactions and Predictability

Published online by Cambridge University Press:  13 January 2021

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Summary

The general public is familiar with weather forecasts and their utility, and the field of weather forecasting is well-established. Even the theoretical limit of the weather forecasting – two weeks – is known. In contrast, familiarity with climate prediction is low outside of the research field, the theoretical basis is not fully established, and we do not know the extent to which climate can be predicted. Variations in climate, however, can have large societal and economic consequences, as they can lead to droughts and floods, and spells of extreme hot and cold weather. Thus, improving our capabilities to predict climate is important and urgent, as it can enhance climate services and thereby contribute to the sustainable development of humans in this era of climate change.

Type
Chapter
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Interacting Climates of Ocean Basins
Observations, Mechanisms, Predictability, and Impacts
, pp. 258 - 292
Publisher: Cambridge University Press
Print publication year: 2020

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References

Ahn, M.-S., Kim, D., Sperber, K. R., Kang, I.-S., Maloney, E., Waliser, D., Hendon, H., on behalf of, W. M. J. O. T. F. (2017). MJO simulation in CMIP5 climate models: MJO skill metrics and process-oriented diagnosis. Climate Dynamics, 49(11), 40234045.Google Scholar
Alexander, M. A., Blade, I., Newman, M., Lanzante, J. R., Lau, N. C., Scott, J. D. (2002). The atmospheric bridge: The influence of ENSO teleconnections on air-sea interaction over the global oceans. Journal of Climate, 15(16), 22052231.2.0.CO;2>CrossRefGoogle Scholar
Annamalai, H., Kida, S., Hafner, J. (2010). Potential impact of the tropical Indian Ocean–Indonesian Seas on El Niño characteristics. Journal of Climate, 23(14), 39333952.CrossRefGoogle Scholar
Annamalai, H., Murtugudde, R., Potemra, J., Xie, S. P., Liu, P., Wang, B. (2003). Coupled dynamics over the Indian Ocean: Spring initiation of the Zonal Mode. Deep Sea Research Part II: Topical Studies in Oceanography, 50(12), 23052330.Google Scholar
Baldwin, M. P., Stephenson, D. B., Thompson, D. W. J., Dunkerton, T. J., Charlton, A. J., O’Neill, A. (2003). Stratospheric memory and extended-range weather forecasts. Science, 301, 636640.Google Scholar
Barnston, A. G., Tippett, M. K., Ranganathan, M., L’Heureux, M. L. (2019). Deterministic skill of ENSO predictions from the North American Multimodel Ensemble. Climate Dynamics, 53(12), 72157234.CrossRefGoogle ScholarPubMed
Barreiro, M., Chang, P., Ji, L., Saravanan, R., Giannini, A. (2005). Dynamical elements of predicting boreal spring tropical Atlantic sea-surface temperatures. Dynamics of Atmospheres and Oceans, 39(1), 6185.Google Scholar
Bauer, P., Thorpe, A., Brunet, G. (2015). The quiet revolution of numerical weather prediction. Nature, 525(7567), 4755.CrossRefGoogle ScholarPubMed
Becker, E., den Dool, H. v., Zhang, Q. (2014). Predictability and forecast skill in NMME. Journal of Climate, 27 (15), 58915906.Google Scholar
Bellenger, H., Guilyardi, E., Leloup, J., Lengaigne, M., Vialard, J. (2014). ENSO representation in climate models: From CMIP3 to CMIP5. Climate Dynamics, 42(7–8), 19992018.Google Scholar
Booth, B. B. B., Dunstone, N. J., Halloran, P. R., Andrews, T., Bellouin, N. (2012). Aerosols implicated as a prime driver of twentieth-century North Atlantic climate variability. Nature, 484(7393), 228232.Google Scholar
Brandt, P., Funk, A., Hormann, V., Dengler, M., Greatbatch, R. J., Toole, J. M. (2011). Interannual atmospheric variability forced by the deep equatorial Atlantic Ocean. Nature, 473(7348), 497500.Google Scholar
Cai, W., Wu, L., Lengaigne, M., Li, T., McGregor, S., Kug, J.-S., Yu, J.-Y., Stuecker, M. F., Santoso, A., Li, X., Ham, Y.-G., Chikamoto, Y., Ng, B., McPhaden, M. J., Du, Y., Dommenget, D., Jia, F., Kajtar, J. B., Keenlyside, N., Lin, X., Luo, J.-J., Martín-Rey, M., Ruprich-Robert, Y., Wang, G., Xie, S.-P., Yang, Y., Kang, S. M., Choi, J.-Y., Gan, B., Kim, G.-I., Kim, C.-E., Kim, S., Kim, J.-H., Chang, P. (2019). Pantropical climate interactions. Science, 363(6430), eaav4236.Google Scholar
Camargo, S. J., Barnston, A. G., Klotzbach, P. J., Landsea, C. W. (2007). Seasonal tropical cyclone forecasts. WMO Bulletin, 56(4), 297.Google Scholar
Caron, L.-P., Hermanson, L., Dobbin, A., Imbers, J., Lledó, L., Vecchi, G. A. (2017). How Skillful are the Multiannual Forecasts of Atlantic Hurricane Activity? Bulletin of the American Meteorological Society, 99(2), 403413.Google Scholar
Cassou, C. (2008). Intraseasonal interaction between the Madden-Julian Oscillation and the North Atlantic Oscillation. Nature, 455(7212), 523527.Google Scholar
Chang, P., Fang, Y., Saravanan, R., Ji, L., Seidel, H. (2006a). The cause of the fragile relationship between the Pacific El Nino and the Atlantic Nino. Nature, 443(7109), 324328.Google Scholar
Chang, P., Saravanan, R., Ji, L. (2003). Tropical Atlantic seasonal predictability: The roles of El Niño remote influence and thermodynamic air-sea feedback. Geophysical Research Letters, 30(10), 1501.CrossRefGoogle Scholar
Chang, P., Yamagata, T., Schopf, P., Behera, S. K., Carton, J., Kessler, W. S., Meyers, G., Qu, T., Schott, F., Shetye, S., Xie, S. P. (2006b). Climate fluctuations of tropical coupled systems: The role of ocean dynamics. Journal of Climate, 19(20), 51225174.CrossRefGoogle Scholar
Chen, D., Cane, M. A., Kaplan, A., Zebiak, S. E., Huang, D. (2004). Predictability of El Nino over the past 148 years. Nature, 428(6984), 733736.Google Scholar
Chikamoto, Y., Mochizuki, T., Timmermann, A., Kimoto, M., Watanabe, M. (2016). Potential tropical Atlantic impacts on Pacific decadal climate trends. Geophysical Research Letters, 43(13), 71437151.CrossRefGoogle Scholar
Chikamoto, Y., Timmermann, A., Luo, J.-J., Mochizuki, T., Kimoto, M., Watanabe, M., Ishii, M., Xie, S.-P., Jin, F.-F. (2015). Skilful multi-year predictions of tropical trans-basin climate variability. Nature Communications, 6, 6869.Google Scholar
Chikamoto, Y., Timmermann, A., Widlansky, M. J., Balmaseda, M. A., Stott, L. (2017). Multi-year predictability of climate, drought, and wildfire in southwestern North America. Scientific Reports, 7(1), 6568.Google Scholar
Choi, K.-S., Wu, C.-C., Cha, E.-J. (2010). Change of tropical cyclone activity by Pacific-Japan teleconnection pattern in the western North Pacific. Journal of Geophysical Research: Atmospheres, 115, D19114.Google Scholar
Choudhury, D., Sen Gupta, A., Sharma, A., Taschetto, A. S., Mehrotra, R., Sivakumar, B. (2017). Impacts of the tropical trans-basin variability on Australian rainfall. Climate Dynamics, 49(5), 16171629.Google Scholar
Coelho, C. A. S., Stephenson, D. B., Balmaseda, M., Doblas-Reyes, F. J., van Oldenborgh, G. J. (2006). Toward an integrated seasonal forecasting system for South America. Journal of Climate, 19 (15), 37043721.Google Scholar
Compo, G. P., Whitaker, J. S., Sardeshmukh, P. D., Matsui, N., Allan, R. J., Yin, X., Gleason, B. E., Vose, R. S., Rutledge, G., Bessemoulin, P., Brönnimann, S., Brunet, M., Crouthamel, R. I., Grant, A. N., Groisman, P. Y., Jones, P. D., Kruk, M. C., Kruger, A. C., Marshall, G. J., Maugeri, M., Mok, H. Y., Nordli, Ø., Ross, T. F., Trigo, R. M., Wang, X. L., Woodruff, S. D., Worley, S. J. (2011). The twentieth century reanalysis project. Quarterly Journal of the Royal Meteorological Society, 137(654), 128.Google Scholar
Corti, S., Palmer, T., Balmaseda, M., Weisheimer, A., Drijfhout, S., Dunstone, N., Hazeleger, W., Kröger, J., Pohlmann, H., Smith, D., Storch, J.-S. v., Wouters, B. (2015). Impact of initial conditions versus external forcing in decadal climate predictions: A sensitivity experiment. Journal of Climate, 28(11), 44544470.Google Scholar
Crespo, L. R., Keenlyside, N., Koseki, S. (2019). The role of sea surface temperature in the atmospheric seasonal cycle of the equatorial Atlantic. Climate Dynamics, 52(9), 59275946.Google Scholar
Dai, A., Fyfe, J. C., Xie, S.-P., Dai, X. (2015). Decadal modulation of global surface temperature by internal climate variability. Nature Climate Change, 5, 555.CrossRefGoogle Scholar
De Souza, E. B., Ambrizzi, T. (2006). Modulation of the intraseasonal rainfall over tropical Brazil by the Madden–Julian oscillation. International Journal of Climatology, 26(13), 17591776.Google Scholar
DeMott, C. A., Klingaman, N. P., Woolnough, S. J. (2015). Atmosphere-ocean coupled processes in the Madden-Julian oscillation. Reviews of Geophysics, 53(4), 10991154.CrossRefGoogle Scholar
Deppenmeier, A.-L., Haarsma, R. J., Hazeleger, W. (2016). The Bjerknes feedback in the tropical Atlantic in CMIP5 models. Climate Dynamics, 47(7), 26912707.Google Scholar
Ding, H., Greatbatch, R. J., Latif, M., Park, W., Gerdes, R. (2013). Hindcast of the 1976/77 and 1998/99 Climate Shifts in the Pacific. Journal of Climate, 26(19), 76507661.CrossRefGoogle Scholar
Ding, H., Keenlyside, N., Latif, M. (2012). Impact of the Equatorial Atlantic on the El Niño Southern Oscillation. Climate Dynamics, 38(9), 19651972.CrossRefGoogle Scholar
Ding, H., Keenlyside, N. S., Latif, M. (2010). Equatorial Atlantic interannual variability: Role of heat content. Journal of Geophysical Research, 115(C9), C09020.Google Scholar
Ding, H., Newman, M., Alexander, M. A., Wittenberg, A. T. (2018). Skillful climate forecasts of the tropical Indo-Pacific Ocean using model-analogs. Journal of Climate, 31(14), 54375459.Google Scholar
Dippe, T., Greatbatch, R. J., Ding, H. (2019). Seasonal prediction of equatorial Atlantic sea surface temperature using simple initialization and bias correction techniques. Atmospheric Science Letters, 20(5), e898.CrossRefGoogle Scholar
Doblas-Reyes, F. J., Andreu-Burillo, I., Chikamoto, Y., Garcia-Serrano, J., Guemas, V., Kimoto, M., Mochizuki, T., Rodrigues, L. R. L., van Oldenborgh, G. J. (2013a). Initialized near-term regional climate change prediction. Nature Communications, 4, 1715.Google Scholar
Doblas-Reyes, F. J., García-Serrano, J., Lienert, F., Biescas, A. P., Rodrigues, L. R. L. (2013b). Seasonal climate predictability and forecasting: status and prospects. Wiley Interdisciplinary Reviews: Climate Change, 4(4), 245268.Google Scholar
Doblas-Reyes, F. J., Hagedorn, R., Palmer, T. N., Morcrette, J. J. (2006). Impact of increasing greenhouse gas concentrations in seasonal ensemble forecasts. Geophysical Research Letters, 33(7), L07708.Google Scholar
Doi, T., Storto, A., Behera, S. K., Navarra, A., Yamagata, T. (2017). Improved Prediction of the Indian Ocean dipole mode by use of subsurface ocean observations. Journal of Climate, 30(19), 79537970.Google Scholar
Doi, T., Tozuka, T., Yamagata, T. (2010). The Atlantic Meridional Mode and its coupled variability with the Guinea Dome. Journal of Climate, 23(2), 455475.Google Scholar
Dommenget, D. (2011). An objective analysis of the observed spatial structure of the tropical Indian Ocean SST variability. Climate Dynamics, 36(11), 21292145.Google Scholar
Dommenget, D., Latif, M. (2000). Interannual to Decadal Variability in the Tropical Atlantic. Journal of Climate, 13 (4), 777792.Google Scholar
Dommenget, D., Latif, M. (2002). A cautionary note on the interpretation of EOFs. Journal of Climate, 15(2), 216225.Google Scholar
Dommenget, D., Semenov, V., Latif, M. (2006). Impacts of the tropical Indian and Atlantic Oceans on ENSO. Geophysical Research Letters, 33, L11701.CrossRefGoogle Scholar
Dommenget, D., Yu, Y. (2017). The effects of remote SST forcings on ENSO dynamics, variability and diversity. Climate Dynamics, 49(7), 26052624.Google Scholar
Du, Y., Xie, S.-P., Huang, G., Hu, K. (2009). Role of air–sea interaction in the long persistence of El Niño–induced North Indian Ocean warming. Journal of Climate, 22(8), 20232038.Google Scholar
Duan, W., Wei, C. (2013). The “spring predictability barrier” for ENSO predictions and its possible mechanism: results from a fully coupled model. International Journal of Climatology, 33(5), 12801292.Google Scholar
England, M. H., McGregor, S., Spence, P., Meehl, G. A., Timmermann, A., Cai, W., Gupta, A. S., McPhaden, M. J., Purich, A., Santoso, A. (2014). Recent intensification of wind-driven circulation in the Pacific and the ongoing warming hiatus. Nature Climate Change, 4 (3), 222227.Google Scholar
Flatau, M., Flatau, P. J., Phoebus, P., Niller, P. P. (1997). The feedback between equatorial convection and local radiative and evaporative processes: The implications for intraseasonal oscillations. Journal of the Atmospheric Sciences, 54 (19), 23732386.Google Scholar
Folland, C. K., Colman, A. W., Rowell, D. P., Davey, M. K. (2001). Predictability of Northeast Brazil rainfall and real-time forecast skill, 1987–98. Journal of Climate, 14(9), 19371958.Google Scholar
Foltz, G. R., McPhaden, M. J. (2010). Interaction between the Atlantic meridional and Niño modes. Geophysical Research Letters, 37(18), L18604.CrossRefGoogle Scholar
Frauen, C., Dommenget, D. (2012). Influences of the tropical Indian and Atlantic Oceans on the predictability of ENSO. Geophysical Research Letters, 39(2), L02706.CrossRefGoogle Scholar
Giannini, A., Saravanan, R., Chang, P. (2004). The preconditioning role of Tropical Atlantic Variability in the development of the ENSO teleconnection: Implications for the prediction of Nordeste rainfall. Climate Dynamics, 22(8), 839855.Google Scholar
Gleixner, S., Keenlyside, N. S., Demissie, T. D., Counillon, F., Wang, Y., Viste, E. (2017). Seasonal predictability of Kiremt rainfall in coupled general circulation models. Environmental Research Letters, 12(11), 114016.Google Scholar
Grimm, A. M. (2019). Madden–Julian Oscillation impacts on South American summer monsoon season: precipitation anomalies, extreme events, teleconnections, and role in the MJO cycle. Climate Dynamics, 53(1), 907932.Google Scholar
Guemas, V., Corti, S., García-Serrano, J., Doblas-Reyes, F. J., Balmaseda, M., Magnusson, L. (2012). The Indian Ocean: The region of highest skill worldwide in decadal climate prediction. Journal of Climate, 26(3), 726739.Google Scholar
Ham, Y.-G., Kug, J.-S., Park, J.-Y. (2013a). Two distinct roles of Atlantic SSTs in ENSO variability: North Tropical Atlantic SST and Atlantic Niño. Geophysical Research Letters, 40(15), 40124017.Google Scholar
Ham, Y.-G., Kug, J.-S., Park, J.-Y., Jin, F.-F. (2013b). Sea surface temperature in the north tropical Atlantic as a trigger for El Niño/Southern Oscillation events. Nature Geoscience, 6(2), 112116.Google Scholar
Handoh, I. C., Matthews, A. J., Bigg, G. R., Stevens, D. P. (2006). Interannual variability of the tropical Atlantic independent of and associated with ENSO: Part I. The North Tropical Atlantic. International Journal of Climatology, 26(14), 19371956.CrossRefGoogle Scholar
Hannachi, A., Dommenget, D. (2009). Is the Indian Ocean SST variability a homogeneous diffusion process? Climate Dynamics, 33(4), 535547.Google Scholar
Hawkins, E., Sutton, R. (2009). The potential to narrow uncertainty in regional climate predictions. Bulletin of the American Meteorological Society, 90(8), 10951107.Google Scholar
Hendon, H. H., Liebmann, B., Newman, M., Glick, J. D., Schemm, J. E. (2000). Medium-Range forecast errors associated with active episodes of the Madden–Julian oscillation. Monthly Weather Review, 128(1), 6986.Google Scholar
Hendon, H. H., Salby, M. L. (1994). The life-cycle of the Madden-Julian oscillation. Journal of the Atmospheric Sciences, 51(15), 22252237.Google Scholar
Hendon, H. H., Wheeler, M. C., Zhang, C. (2007). Seasonal dependence of the MJO–ENSO relationship. Journal of Climate, 20(3), 531543.Google Scholar
Hsu, H. H., Weng, C. H., Wu, C. H. (2004). Contrasting characteristics between the northward and eastward propagation of the intraseasonal oscillation during the boreal summer. Journal of Climate, 17(4), 727743.Google Scholar
Hsu, W.-C., Patricola, C. M., Chang, P. (2019). The impact of climate model sea surface temperature biases on tropical cyclone simulations. Climate Dynamics. 53(1), 173192.Google Scholar
Hu, K., Huang, G., Qu, X., Huang, R. (2012). The impact of Indian Ocean variability on high temperature extremes across the southern Yangtze River valley in late summer. Advances in Atmospheric Sciences, 29(1), 91100.Google Scholar
Hu, S., Fedorov, A. V. (2016). Exceptionally strong easterly wind burst stalling El Niño of 2014'. Proceedings of the National Academy of Sciences, 113(8), 2005.Google Scholar
Huang, B., Thorne, P. W., Banzon, V. F., Boyer, T., Chepurin, G., Lawrimore, J. H., Menne, M. J., Smith, T. M., Vose, R. S., Zhang, H.-M. (2017). Extended Reconstructed Sea Surface Temperature, Version 5 (ERSSTv5): Upgrades, validations, and intercomparisons. Journal of Climate, 30(20), 81798205.Google Scholar
Huang, R., Chen, W., Yang, B., Zhang, R. (2004). Recent advances in studies of the interaction between the East Asian winter and summer monsoons and ENSO cycle. Advances in Atmospheric Sciences, 21(3), 407424.Google Scholar
Huang, R., Sun, F. (1992). Impacts of the tropical western Pacific on the East Asian summer monsoon. Journal of the Meteorological Society of Japan. Ser. II, 70(1B), 243256.Google Scholar
Izumo, T., Vialard, J., Lengaigne, M., Montegut, C. D., Behera, S. K., Luo, J. J., Cravatte, S., Masson, S. and Yamagata, T. (2010). Influence of the state of the Indian Ocean Dipole on the following year's El Niño. Nature Geoscience, 3(3), 168172.CrossRefGoogle Scholar
Jansen, M. F., Dommenget, D., Keenlyside, N. (2009). Tropical atmosphere-ocean interactions in a conceptual framework. Journal of Climate, 22(3), 550567.Google Scholar
Jiang, X., Waliser, D. E., Xavier, P. K., Petch, J., Klingaman, N. P., Woolnough, S. J., Guan, B., Bellon, G., Crueger, T., DeMott, C., Hannay, C., Lin, H., Hu, W., Kim, D., Lappen, C.-L., Lu, M.-M., Ma, H.-Y., Miyakawa, T., Ridout, J. A., Schubert, S. D., Scinocca, J., Seo, K.-H., Shindo, E., Song, X., Stan, C., Tseng, W.-L., Wang, W., Wu, T., Wu, X., Wyser, K., Zhang, G. J., Zhu, H. (2015). Vertical structure and physical processes of the Madden-Julian oscillation: Exploring key model physics in climate simulations. Journal of Geophysical Research: Atmospheres, 120(10), 47184748.Google Scholar
Joseph, S., Sahai, A. K., Goswami, B. N. (2009). Eastward propagating MJO during boreal summer and Indian monsoon droughts. Climate Dynamics, 32(7), 11391153.CrossRefGoogle Scholar
Jouanno, J., Hernandez, O., Sanchez-Gomez, E. (2017). Equatorial Atlantic interannual variability and its relation to dynamic and thermodynamic processes. Earth System Dynamics, 8(4), 10611069.Google Scholar
Keenlyside, N. S., Latif, M. (2007). Understanding equatorial Atlantic interannual variability'. Journal of Climate, 20(1), 131142.Google Scholar
Keenlyside, N. S., Latif, M., Jungclaus, J., Kornblueh, L., Roeckner, E. (2008). Advancing decadal-scale climate prediction in the North Atlantic Sector. Nature, 453, 8488.Google Scholar
Keenlyside, N. S., Ba, J. (2010). Prospects for decadal climate prediction. Wiley Interdisciplinary Reviews: Climate Change, 1(5), 627635.Google Scholar
Keenlyside, N. S., Ding, H., Latif, M. (2013). Potential of equatorial Atlantic variability to enhance El Niño prediction. Geophysical Research Letters, 40(10), 22782283.Google Scholar
Kirtman, B. P., Min, D., Infanti, J. M., Kinter, J. L., Paolino, D. A., Zhang, Q., van den Dool, H., Saha, S., Mendez, M. P., Becker, E., Peng, P., Tripp, P., Huang, J., DeWitt, D. G., Tippett, M. K., Barnston, A. G., Li, S., Rosati, A., Schubert, S. D., Rienecker, M., Suarez, M., Li, Z. E., Marshak, J., Lim, Y.-K., Tribbia, J., Pegion, K., Merryfield, W. J., Denis, B., Wood, E. F. (2014). The North American Multimodel Ensemble: Phase-1 seasonal-to-interannual prediction; phase-2 toward developing intraseasonal prediction. Bulletin of the American Meteorological Society, 95(4), 585601.CrossRefGoogle Scholar
Klein, S. A., Soden, B. J., Lau, N.-C. (1999). Remote sea surface temperature variations during ENSO: Evidence for a tropical atmospheric bridge. Journal of Climate, 12(4), 917932.Google Scholar
Klingaman, N. P., Woolnough, S. J. (2014). Using a case-study approach to improve the Madden–Julian oscillation in the Hadley Centre model. Quarterly Journal of the Royal Meteorological Society, 140(685), 24912505.Google Scholar
Klingaman, N. P., Woolnough, S. J., Jiang, X., Waliser, D., Xavier, P. K., Petch, J., Caian, M., Hannay, C., Kim, D., Ma, H.-Y., Merryfield, W. J., Miyakawa, T., Pritchard, M., Ridout, J. A., Roehrig, R., Shindo, E., Vitart, F., Wang, H., Cavanaugh, N. R., Mapes, B. E., Shelly, A., Zhang, G. J. (2015). Vertical structure and physical processes of the Madden-Julian oscillation: Linking hindcast fidelity to simulated diabatic heating and moistening. Journal of Geophysical Research: Atmospheres, 120(10), 46904717.Google Scholar
Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi, K., Kamahori, H., Kobayashi, C., Endo, H., Miyaoka, K., Takahashi, K. (2015). The JRA-55 reanalysis: General specifications and basic characteristics. Journal of the Meteorological Society of Japan. Ser. II, 93(1), 548.Google Scholar
Kosaka, Y. (2018). Slow warming and the ocean see-saw. Nature Geoscience, 11(1), 1213.Google Scholar
Kosaka, Y., Nakamura, H. (2006). Structure and dynamics of the summertime Pacific–Japan teleconnection pattern. Quarterly Journal of the Royal Meteorological Society, 132 (619), 20092030.CrossRefGoogle Scholar
Kosaka, Y., Xie, S.-P. (2013). Recent global-warming hiatus tied to equatorial Pacific surface cooling'. Nature, 501(7467), 403407.Google Scholar
Kosaka, Y., Xie, S.-P. (2016). The tropical Pacific as a key pacemaker of the variable rates of global warming. Nature Geoscience, 9, 669673.Google Scholar
Kosaka, Y., Xie, S.-P., Lau, N.-C., Vecchi, G. A. (2013). Origin of seasonal predictability for summer climate over the Northwestern Pacific. Proceedings of the National Academy of Sciences, 110 (19), 75747579.Google Scholar
Kosaka, Y., Xie, S.-P., Nakamura, H. (2011). Dynamics of interannual variability in summer precipitation over east Asia. Journal of Climate, 24(20), 54355453.Google Scholar
Kucharski, F., Ikram, F., Molteni, F., Farneti, R., Kang, I.-S., No, H.-H., King, M. P., Giuliani, G., Mogensen, K. (2016). Atlantic forcing of Pacific decadal variability. Climate Dynamics, 46(7), 23372351.Google Scholar
Kug, J.-S., Kang, I.-S. (2006). Interactive feedback between ENSO and the Indian Ocean. Journal of Climate, 19(9), 17841801.Google Scholar
Kushnir, Y., Scaife, A. A., Arritt, R., Balsamo, G., Boer, G., Doblas-Reyes, F., Hawkins, E., Kimoto, M., Kolli, R. K., Kumar, A., Matei, D., Matthes, K., Müller, W. A., O’Kane, T., Perlwitz, J., Power, S., Raphael, M., Shimpo, A., Smith, D., Tuma, M., Wu, B. (2019). Towards operational predictions of the near-term climate. Nature Climate Change, 9(2), 94101.Google Scholar
Latif, M., Anderson, D., Barnett, T., Cane, M., Kleeman, R., Leetmaa, A., O'Brien, J., Rosati, A., Schneider, E. (1998). A review of the predictability and prediction of ENSO. Journal of Geophysical Research-Oceans, 103(C7), 1437514393.CrossRefGoogle Scholar
Latif, M., Keenlyside, N. S. (2009). El Niño/Southern Oscillation response to global warming, Proceedings of the National Academy of Sciences, 106(49), 2057820583.CrossRefGoogle ScholarPubMed
Latif, M., Keenlyside, N. S. (2011). A perspective on decadal climate variability and predictability. Deep Sea Research Part II: Topical Studies in Oceanography, 58, 18801894.Google Scholar
Lavender, S. L., Matthews, A. J. (2009). Response of the West African monsoon to the Madden–Julian oscillation, Journal of Climate, 22(15), 40974116.Google Scholar
Lee, J.-Y., Fu, X., Wang, B. (2017). Predictability and prediction of the Madden–Julian oscillation: A review on progress and current status. In Chang, C.-P., Kuo, H.-C., Lau, N.-C., Johnson, R. H., Wang, B., Wheeler, M. C. The Global Monsoon System: Vol. Volume 9 World Scientific Series on Asia-Pacific Weather and Climate. Singapore: World Scientific, 147159.Google Scholar
Lee, S.-K., Enfield, D. B., Wang, C. (2008). Why do some El Niños have no impact on tropical North Atlantic SST? Geophysical Research Letters, 35(16), L16705.Google Scholar
Lee, Y.-Y., Grotjahn, R. (2019). Evidence of specific MJO phase occurrence with summertime California Central Valley extreme hot weather. Advances in Atmospheric Sciences, 36(6), 589602.Google Scholar
Lengaigne, M., Guilyardi, E., Boulanger, J.-P., Menkes, C., Delecluse, P., Inness, P., Cole, J., Slingo, J. (2004). Triggering of El Niño by westerly wind events in a coupled general circulation model. Climate Dynamics, 23(6), 601620.Google Scholar
Levine, A., Jin, F. F., McPhaden, M. J. (2016). Extreme noise – extreme El Niño: How state-dependent noise forcing creates El Niño–La Niña asymmetry. Journal of Climate, 29(15), 54835499.Google Scholar
Levine, A. F. Z., McPhaden, M. J. (2016). How the July 2014 easterly wind burst gave the 2015–2016 El Niño a head start. Geophysical Research Letters, 43(12), 65036510.Google Scholar
Li, X., Xie, S.-P., Gille, S. T. Yoo, C. (2015). Atlantic-induced pan-tropical climate change over the past three decades. Nature Climate Change, 6, 275.Google Scholar
Liebmann, B., Hendon, H. H., Glick, J. D. (1994). The relationship between tropical cyclones of the western Pacific and Indian Oceans and the Madden–Julian oscillation. Journal of the Meteorological Society of Japan. Ser. II, 72(3), 401412.Google Scholar
Lin, H., Brunet, G. and Fontecilla, J. S. (2010). Impact of the Madden–Julian oscillation on the intraseasonal forecast skill of the North Atlantic oscillation. Geophysical Research Letters, 37(19), L19803.Google Scholar
Lübbecke, J. F., McPhaden, M. J. (2012). On the inconsistent relationship between Pacific and Atlantic Niños. Journal of Climate, 25(12), 42944303.Google Scholar
Lübbecke, J. F., Rodríguez-Fonseca, B., Richter, I., Martín-Rey, M., Losada, T., Polo, I., Keenlyside, N. S. (2018). Equatorial Atlantic variability: Modes, mechanisms, and global teleconnections. Wiley Interdisciplinary Reviews: Climate Change, 9(4), e527.Google Scholar
Luo, J.-J., Behera, S., Masumoto, Y., Sakuma, H., Yamagata, T. (2008a). Successful prediction of the consecutive IOD in 2006 and 2007. Geophysical Research Letters, 35(14), L14S02.Google Scholar
Luo, J.-J., Liu, G., Hendon, H., Alves, O., Yamagata, T. (2017). Inter-basin sources for two-year predictability of the multi-year La Niña event in 2010–2012. Scientific Reports, 7(1), 2276.Google Scholar
Luo, J.-J., Masson, S., Behera, S., Yamagata, T. (2007). Experimental forecasts of the Indian Ocean dipole using a coupled OAGCM. Journal of Climate, 20(10), 21782190.Google Scholar
Luo, J.-J., Masson, S., Behera, S. K.. Yamagata, T. (2008b). Extended ENSO predictions using a fully coupled ocean–atmosphere model. Journal of Climate, 21(1), 8493.Google Scholar
Luo, J.-J., Sasaki, W., Masumoto, Y. (2012). Indian Ocean warming modulates Pacific climate change. Proceedings of the National Academy of Sciences, 109(46), 18701.Google Scholar
Luo, J.-J., Wang, G., Dommenget, D. (2018), May common model biases reduce CMIP5’s ability to simulate the recent Pacific La Niña-like cooling? Climate Dynamics, 50 (3), 13351351.Google Scholar
Luo, J.-J., Yuan, C., Sasaki, W., Behera, S. K., Masumoto, Y., Yamagata, T., Lee, J.-Y. and Masson, S. (2016). Current status of intraseasonal-seasonal-to-interannual prediction of the Indo-Pacific climate. In Behera, S. K., Yamagata, T. Indo-Pacific Climate Variability and Predictability: Vol. Volume 7 World Scientific Series on Asia-Pacific Weather and Climate. Singapore: World Scientific, 63107.Google Scholar
Luo, J. J., Zhang, R., Behera, S. K., Masumoto, Y., Jin, F. F., Lukas, R., Yamagata, T. (2010). Interaction between El Niño and extreme Indian Ocean dipole. Journal of Climate, 23(3), 726742.Google Scholar
Madden, R. A., Julian, P. R. (1972). Description of global-scale circulation cells in tropics with a 40–50 day period. Journal of the Atmospheric Sciences, 29(6), 11091123.Google Scholar
Majda, A. J. and Stechmann, S. N. (2009). The skeleton of tropical intraseasonal oscillations. Proceedings of the National Academy of Sciences, 106(21), 8417.Google Scholar
Maloney, E. D., Hartmann, D. L. (1998). Frictional moisture convergence in a composite life cycle of the Madden–Julian oscillation. Journal of Climate, 11(9), 23872403.Google Scholar
Maloney, E. D., Hartmann, D. L. (2000). Modulation of hurricane activity in the Gulf of Mexico by the Madden–Julian oscillation. Science, 287(5460), 20022004.Google Scholar
Maloney, E. D., Sobel, A. H. (2004). Surface fluxes and ocean coupling in the tropical intraseasonal oscillation. Journal of Climate, 17(22), 43684386.Google Scholar
Marshall, A. G., Hendon, H. H. Wang, G. (2016). On the role of anomalous ocean surface temperatures for promoting the record Madden–Julian Oscillation in March 2015. Geophysical Research Letters, 43(1), 472481.Google Scholar
Martín-Rey, M., Rodríguez-Fonseca, B., Polo, I., Kucharski, F. (2014). On the Atlantic–Pacific Niños connection: a multidecadal modulated mode. Climate Dynamics, 43(11), 31633178.CrossRefGoogle Scholar
Martín-Rey, M., Rodríguez-Fonseca, B., Polo, I. (2015). Atlantic opportunities for ENSO prediction. Geophysical Research Letters, 42(16), 68026810.Google Scholar
Matsueda, S., Takaya, Y. (2015). The global influence of the Madden–Julian oscillation on extreme temperature events. Journal of Climate, 28(10), 41414151.Google Scholar
Matthews, A. J. (2004). Intraseasonal variability over tropical Africa during northern summer. Journal of Climate, 17(12), 24272440.2.0.CO;2>CrossRefGoogle Scholar
Matthews, A. J. and Meredith, M. P. (2004). Variability of Antarctic circumpolar transport and the Southern Annular Mode associated with the Madden–Julian Oscillation. Geophysical Research Letters, 31(24), doi:10.1029/2004GL021666.Google Scholar
McGregor, S., Stuecker, M. F., Kajtar, J. B., England, M. H., Collins, M. (2018). Model tropical Atlantic biases underpin diminished Pacific decadal variability. Nature Climate Change, 8(6), 493498.Google Scholar
McGregor, S., Timmermann, A., Stuecker, M. F., England, M. H., Merrifield, M., Jin, F.-F., Chikamoto, Y. (2014). Recent Walker circulation strengthening and Pacific cooling amplified by Atlantic warming. Nature Climate Change, 4(10), 888892.Google Scholar
McPhaden, M. J. (1999). Genesis and evolution of the 1997–98 El Niño. Science, 283(5404), 950954.Google Scholar
McPhaden, M. J. (2003). Tropical Pacific Ocean heat content variations and ENSO persistence barriers. Geophysical Research Letters, 30 (9), 1480.Google Scholar
McPhaden, M. J., Busallacchi, A. J., Cheney, R., Donguy, J.-R., Gage, K. S., Halpern, D., Ji, M., Julian, P., Meyers, G., Mitchum, G. T., Niiler, P. P., Picaut, J., Reynolds, R. W., Smith, N., Takeuchi, K. (1998). The tropical ocean global atmosphere observing system: A decade of progress. Journal of Geophysical Research, 103(C7), 1416914240.Google Scholar
McPhaden, M. J., Zhang, X., Hendon, H. H., Wheeler, M. C. (2006). Large scale dynamics and MJO forcing of ENSO variability. Geophysical Research Letters, 33(16), L16702.Google Scholar
Mechoso, C. R., Robertson, A. W., Barth, N., Davey, M. K., Delecluse, P., Gent, P. R., Ineson, S., Kirtman, B., Latif, M., Le Treut, L., Nagai, T. Neelin, J. D., Philander, S. G. H., Polcher, J., Schopf, P. S., Stockdale, T. Suarez, M. J., Terray, L., Thual, O., Tribbia, J. J. (1995). The seasonal cycle over the Tropical Pacific in General Circulation Models. Monthly Weather Review, 123, 28252838.Google Scholar
Meehl, G. A., Goddard, L., Murphy, J., Stouffer, R. J., Boer, G., Danabasoglu, G., Dixon, K., Giorgetta, M. A., Greene, A. M., Hawkins, E., Hegerl, G., Karoly, D., Keenlyside, N., Kimoto, M., Kirtman, B., Navarra, A., Pulwarty, R., Smith, D., Stammer, D., Stockdale, T. (2009). Decadal prediction: Can it be skillful? Bulletin of the American Meteorological Society, 90 (10), 14671485.Google Scholar
Meehl, G. A., Teng, H. (2012). Case studies for initialized decadal hindcasts and predictions for the Pacific region. Geophysical Research Letters, 39(22), L22705.Google Scholar
Meyers, G., McIntosh, P., Pigot, L., Pook, M. (2007). The years of El Niño, La Niña, and interactions with the tropical Indian Ocean. Journal of Climate, 20(13), 28722880.Google Scholar
Mochizuki, T., Kimoto, M., Watanabe, M., Chikamoto, Y., Ishii, M. (2016). Interbasin effects of the Indian Ocean on Pacific decadal climate change. Geophysical Research Letters, 43(13), 71687175.Google Scholar
Mohino, E., Keenlyside, N., Pohlmann, H. (2016). Decadal prediction of Sahel rainfall: Where does the skill (or lack thereof) come from? Climate Dynamics, 47(11), 35933612.Google Scholar
Mutai, C. C., Ward, M. N. (2000). East African rainfall and the tropical circulation/convection on intraseasonal to interannual timescales. Journal of Climate, 13(22), 39153939.Google Scholar
Neelin, J. D., Battisti, D. S., Hirst, A. C., Jin, F.-F., Wakata, Y., Yamagata, T., Zebiak, S. E. (1998). ENSO theory. Journal of Geophysical Research, 103, 1426114290.Google Scholar
Neena, J. M., Lee, J. Y., Waliser, D., Wang, B., Jiang, X. (2014). Predictability of the Madden–Julian oscillation in the Intraseasonal Variability Hindcast Experiment (ISVHE). Journal of Climate, 27(12), 45314543.Google Scholar
Newman, M., Alexander, M.A., Ault, T. R., Cobb, K. M., Deser, C., Di Lorenzo, E., Mantua, N. J., Miller, A. J., Minobe, S., Nakamura, H., Schneider, N., Vimont, D. J., Phillips, A. S., Scott, J. D., Smith, C. A. (2016). The Pacific decadal oscillation, revisited. Journal of Climate, 29, 43994427Google Scholar
Newman, M., Sardeshmukh, P. D. (2017). Are we near the predictability limit of tropical Indo-Pacific sea surface temperatures? Geophysical Research Letters, 44(16), 85208529.Google Scholar
Niang, C., Mohino, E., Gaye, A. T., Omotosho, J. B. (2017). Impact of the Madden–Julian oscillation on the summer West African monsoon in AMIP simulations. Climate Dynamics, 48(7), 22972314.Google Scholar
Nitta, T. (1987). Convective activities in the tropical western Pacific and their impact on the northern hemisphere summer circulation. Journal of the Meteorological Society of Japan. Ser. II, 65(3), 373390.Google Scholar
Nnamchi, H. C., Li, J., Kucharski, F., Kang, I.-S., Keenlyside, N. S., Chang, P., Farneti, R. (2015). Thermodynamic controls of the Atlantic Nino, Nature Communications, 6, 8895.Google Scholar
Nnamchi, H. C., Li, J., Kucharski, F., Kang, I.-S., Keenlyside, N. S., Chang, P., Farneti, R. (2016). An equatorial–extratropical dipole structure of the Atlantic Niño. Journal of Climate, 29(20), 72957311.Google Scholar
Orsolini, Y. J., Senan, R., Vitart, F., Balsamo, G., Weisheimer, A., Doblas-Reyes, F. J. (2016). Influence of the Eurasian snow on the negative North Atlantic Oscillation in subseasonal forecasts of the cold winter 2009/2010. Climate Dynamics, 47(3), 13251334.Google Scholar
Palmer, T. N. (1993). Extended-range atmospheric prediction and the Lorenz model. Bulletin of the American Meteorological Society, 74(1), 4966.Google Scholar
Palmer, T. N., Alessandri, A., Andersen, U., Cantelaube, P., Davey, M., Delecluse, P., Deque, M., Diez, E., Doblas-Reyes, F. J., Feddersen, H., Graham, R., Gualdi, S., Gueremy, J. F., Hagedorn, R., Hoshen, M., Keenlyside, N., Latif, M., Lazar, A., Maisonnave, E., Marletto, V., Morse, A. P., Orfila, B., Rogel, P., Terres, J. M., Thomson, M. C. (2004). Development of a European multimodel ensemble system for seasonal-to-interannual prediction (DEMETER). Bulletin of the American Meteorological Society, 85(6), 853872.Google Scholar
Pariyar, S. K., Keenlyside, N., Bhatt, B. C., Omrani, N.-E. (2019). The dominant patterns of intra-seasonal rainfall variability in May-October and November-April over the Tropical Western Pacific. Monthly Weather Review, 147(8), 29412960.Google Scholar
Philander, S. G. H. (1990) El Niño, La Niña, and the Southern Oscillation. London: Academic Press.Google Scholar
Philippon, N., Doblas-Reyes, F. J., Ruti, P. M. (2010). Skill, reproducibility and potential predictability of the West African monsoon in coupled GCMs. Climate Dynamics, 35(1), 5374.Google Scholar
Prodhomme, C., Batté, L., Massonnet, F., Davini, P., Bellprat, O., Guemas, V., Doblas-Reyes, F. J. (2016). Benefits of increasing the model resolution for the seasonal forecast quality in EC-Earth. Journal of Climate, 29(24), 91419162.Google Scholar
Rashid, H. A., Hendon, H. H., Wheeler, M. C., Alves, O. (2011). Prediction of the Madden–Julian oscillation with the POAMA dynamical prediction system. Climate Dynamics, 36(3-4), 649661.Google Scholar
Rayner, N. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L. V., Rowell, D. P., Kent, E. C., Kaplan, A. (2003). Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. Journal of Geophysical Research, 108(D14), 4407.Google Scholar
Richter, I. (2015). Climate model biases in the eastern tropical oceans: Causes, impacts and ways forward. Wiley Interdisciplinary Reviews: Climate Change, 6(3), 345358.Google Scholar
Richter, I., Behera, S., Doi, T., Taguchi, B., Masumoto, Y., Xie, S.-P. (2014). What controls equatorial Atlantic winds in boreal spring. Climate Dynamics, 43(11), 30913104.Google Scholar
Richter, I., Behera, S. K., Masumoto, Y., Taguchi, B., Sasaki, H., Yamagata, T. (2013). Multiple causes of interannual sea surface temperature variability in the equatorial Atlantic Ocean, Nature Geoscence, 6(1), 4347.Google Scholar
Richter, I., Doi, T., Behera, S. K., Keenlyside, N. (2018). On the link between mean state biases and prediction skill in the tropics: an atmospheric perspective. Climate Dynamics, 50(9), 33553374.Google Scholar
Robertson, A. W., Kumar, A., Peña, M., Vitart, F. (2014). Improving and promoting subseasonal to seasonal prediction. Bulletin of the American Meteorological Society, 96(3), ES49ES53.CrossRefGoogle Scholar
Rodriguez-Fonseca, B., Polo, I., Garcia-Serrano, J., Losada, T., Mohino, E., Mechoso, C. R., Kucharski, F. (2009). Are Atlantic Niños enhancing Pacific ENSO events in recent decades? Geophysical Research Letters, 36(20), L20705.Google Scholar
Ruiz-Barradas, A., Carton, J. A., Nigam, S. (2000). Structure of interannual-to-decadal climate variability in the tropical Atlantic sector. Journal of Climate, 13(18), 32853297.Google Scholar
Ruiz-Barradas, A., Carton, J. A., Nigam, S. (2003). Role of the atmosphere in climate variability of the tropical Atlantic. Journal of Climate, 16(12), 20522065.2.0.CO;2>CrossRefGoogle Scholar
Ruprich-Robert, Y., Msadek, R., Castruccio, F., Yeager, S., Delworth, T., Danabasoglu, G. (2016). Assessing the climate impacts of the observed Atlantic multidecadal variability using the GFDL CM2.1 and NCAR CESM1 global coupled models. Journal of Climate, 30(8), 27852810.CrossRefGoogle Scholar
Saji, N. H., Goswami, B. N., Vinayachandran, P. N., Yamagata, T. (1999). A dipole mode in the tropical Indian Ocean. Nature, 401(6751), 360363.Google Scholar
Servain, J., Wainer, I., McCreary, J. P., Dessier, A. (1999). Relationship between the equatorial and meridional modes of climatic variability in the tropical Atlantic. Geophysical Research Letters, 26(4), 485488.CrossRefGoogle Scholar
Sheen, K. L., Smith, D. M., Dunstone, N. J., Eade, R., Rowell, D. P., Vellinga, M. (2017). Skilful prediction of Sahel summer rainfall on inter-annual and multi-year timescales. Nature Communications, 8, 14966.CrossRefGoogle ScholarPubMed
Shen, M.-L., Keenlyside, N., Selten, F., Wiegerinck, W., Duane, G. S. (2016). Dynamically combining climate models to “supermodel” the tropical Pacific. Geophysical Research Letters, 43(1), 359366.Google Scholar
Shi, L., Hendon, H. H., Alves, O., Luo, J.-J., Balmaseda, M., Anderson, D. (2012). How predictable is the Indian Ocean dipole? Monthly Weather Review, 140(12), 38673884.Google Scholar
Smith, D. M., Cusack, S., Colman, A. W., Folland, C. K., Harris, G. R., Murphy, J. M. (2007). Improved surface temperature prediction for the coming decade from a global climate model. Science, 317, 796799.Google Scholar
Smith, D. M., Eade, R., Dunstone, N. J., Fereday, D., Murphy, J. M., Pohlmann, H., Scaife, A. A. (2010). Skilful multi-year predictions of Atlantic hurricane frequency. Nature Geoscience, 3(12), 846849.Google Scholar
Smith, N., Kessler, W. S., Cravatte, S., Sprintall, J., Wijffels, S., Cronin, M. F., Sutton, A., Serra, Y. L., Dewitte, B., Strutton, P. G., Hill, K., Sen Gupta, A., Lin, X., Takahashi, K., Chen, D., Brunner, S. (2019). Tropical Pacific observing system. Frontiers in Marine Science, doi:10.3389/fmars.2019.00031.CrossRefGoogle Scholar
Sobel, A. H., Maloney, E. D., Bellon, G., Frierson, D. M. (2010). Surface fluxes and tropical intraseasonal variability: A reassessment. Journal of Advances in Modeling Earth Systems, 2(1), 27, doi:10.3894/JAMES.2010.2.2.Google Scholar
Song, Q., Vecchi, G. A., Rosati, A. J. (2008). Predictability of the Indian Ocean sea surface temperature anomalies in the GFDL coupled model. Geophysical Research Letters, 35(2), doi:10.1029/2007GL031966.Google Scholar
Jacob, D., Runge, T., Street, R., Parry, M., Scott, J. (2015). A European research and innovation roadmap for climate services. European Commission Publication Office, doi:10.2777/702151.Google Scholar
Suárez-Moreno, R., Rodríguez-Fonseca, B. (2015). S4CAST v2.0: Sea surface temperature based statistical seasonal forecast model. Geoscience Model Development Discussions, 8(5), 39714018.Google Scholar
Sun, C., Kucharski, F., Li, J., Jin, F.-F., Kang, I.-S., Ding, R. (2017). Western tropical Pacific multidecadal variability forced by the Atlantic multidecadal oscillation. Nature Communications, 8, 15998.Google Scholar
Sutton, R. T., Jewson, S. P., Rowell, D. P. (2000). The elements of climate variability in the tropical Atlantic region. Journal of Climate, 13 (18), 32613284.Google Scholar
Takaya, Y., Yasuda, T., Fujii, Y., Matsumoto, S., Soga, T., Mori, H., Hirai, M., Ishikawa, I., Sato, H., Shimpo, A., Kamachi, M., Ose, T. (2017). Japan Meteorological Agency/Meteorological Research Institute-Coupled Prediction System version 1 (JMA/MRI-CPS1) for operational seasonal forecasting, Climate Dynamics, 48(1), 313333.Google Scholar
Tang, Y., Zhang, R.-H., Liu, T., Duan, W., Yang, D., Zheng, F., Ren, H., Lian, T., Gao, C., Chen, D., Mu, M. (2018). Progress in ENSO prediction and predictability study. National Science Review, 5(6), 826839.Google Scholar
Timmermann, A., An, S.-I., Kug, J.-S., Jin, F.-F., Cai, W., Capotondi, A., Cobb, K. M., Lengaigne, M., McPhaden, M. J., Stuecker, M. F., Stein, K., Wittenberg, A. T., Yun, K.-S., Bayr, T., Chen, H.-C., Chikamoto, Y., Dewitte, B., Dommenget, D., Grothe, P., Guilyardi, E., Ham, Y.-G., Hayashi, M., Ineson, S., Kang, D., Kim, S., Kim, W., Lee, J.-Y., Li, T., Luo, J.-J., McGregor, S., Planton, Y., Power, S., Rashid, H., Ren, H.-L., Santoso, A., Takahashi, K., Todd, A., Wang, G., Wang, G., Xie, R., Yang, W.-H., Yeh, S.-W., Yoon, J., Zeller, E., Zhang, X. (2018). El Niño–Southern oscillation complexity. Nature, 559(7715), 535545.Google Scholar
Ting, M. F., Kushnir, Y., Seager, R., Li, C. H. (2009). Forced and internal twentieth-century SST trends in the north Atlantic. Journal of Climate, 22(6), 14691481.Google Scholar
Tokinaga, H., Xie, S. P. (2011). Weakening of the equatorial Atlantic cold tongue over the past six decades. Nature Geoscience, 4(4), 222226.Google Scholar
Tseng, W.-L., Tsuang, B.-J., Keenlyside, N. S., Hsu, H.-H., Tu, C.-Y. (2015). Resolving the upper-ocean warm layer improves the simulation of the Madden–Julian oscillation. Climate Dynamics, 44(5), 14871503.CrossRefGoogle Scholar
Vaughan, C., Dessai, S. (2014). Climate services for society: Origins, institutional arrangements, and design elements for an evaluation framework. Wiley Interdisciplinary Reviews: Climate Change, 5(5), 587603.Google Scholar
Vecchi, G. A., Delworth, T., Gudgel, R., Kapnick, S., Rosati, A., Wittenberg, A. T., Zeng, F., Anderson, W., Balaji, V., Dixon, K., Jia, L., Kim, H. S., Krishnamurthy, L., Msadek, R., Stern, W. F., Underwood, S. D., Villarini, G., Yang, X. Zhang, S. (2014). On the seasonal forecasting of regional tropical cyclone activity. Journal of Climate, 27(21), 79948016.Google Scholar
Vigaud, N., Robertson, A. W., Tippett, M. K. (2017a). Multimodel ensembling of subseasonal precipitation forecasts over North America. Monthly Weather Review, 145(10), 39133928.Google Scholar
Vigaud, N., Robertson, A. W., Tippett, M. K., Acharya, N. (2017b). Subseasonal predictability of boreal summer monsoon rainfall from ensemble forecasts. Frontiers in Environmental Science, 5, 67.CrossRefGoogle Scholar
Vigaud, N., Tippett, M. K., Robertson, A. W. (2018). Probabilistic skill of subseasonal precipitation forecasts for the East Africa–West Asia sector during September–May. Weather and Forecasting, 33(6), 15131532.Google Scholar
Vijayeta, A., Dommenget, D. (2018). An evaluation of ENSO dynamics in CMIP simulations in the framework of the recharge oscillator model. Climate Dynamics, 51(5), 17531771.Google Scholar
Vitart, F. (2014). Evolution of ECMWF sub-seasonal forecast skill scores. Quarterly Journal of the Royal Meteorological Society, 140(683), 18891899.Google Scholar
Vitart, F. (2017). Madden–Julian Oscillation prediction and teleconnections in the S2S database. Quarterly Journal of the Royal Meteorological Society, 143(706), 22102220.Google Scholar
Vitart, F., Ardilouze, C., Bonet, A., Brookshaw, A., Chen, M., Codorean, C., Déqué, M., Ferranti, L., Fucile, E., Fuentes, M., Hendon, H., Hodgson, J., Kang, H. S., Kumar, A., Lin, H., Liu, G., Liu, X., Malguzzi, P., Mallas, I., Manoussakis, M., Mastrangelo, D., MacLachlan, C., McLean, P., Minami, A., Mladek, R., Nakazawa, T., Najm, S., Nie, Y., Rixen, M., Robertson, A. W., Ruti, P., Sun, C., Takaya, Y., Tolstykh, M., Venuti, F., Waliser, D., Woolnough, S., Wu, T., Won, D. J., Xiao, H., Zaripov, R., Zhang, L. (2016). The subseasonal to seasonal (S2S) Prediction Project Database. Bulletin of the American Meteorological Society, 98(1), 163173.CrossRefGoogle Scholar
Vitart, F., Robertson, A. W. (2018). The sub-seasonal to seasonal prediction project (S2S) and the prediction of extreme events. NPJ Climate and Atmospheric Science, 1(1), 3.Google Scholar
Wakabayashi, S., Kawamura, R. (2004). Extraction of major teleconnection patterns possibly associated with the anomalous summer climate in Japan. Journal of the Meteorological Society of Japan, 82(6), 15771588.Google Scholar
Waliser, D. E., Jones, C., Schemm, J.-K. E., Graham, N. E. (1999). A statistical extended-range tropical forecast model based on the slow evolution of the Madden–Julian oscillation. Journal of Climate, 12(7), 19181939.Google Scholar
Wang, B., Wu, R. Fu, X. (2000). Pacific–East Asian teleconnection: How does ENSO affect East Asian climate? Journal of Climate, 13(9), 15171536.Google Scholar
Wang, B., Wu, R., Li, T. (2003). Atmosphere–Warm ocean interaction and its impacts on Asian–Australian monsoon variation. Journal of Climate, 16(8), 11951211.Google Scholar
Wang, B., Ding, Q., Fu, X., Kang, I.-S., Jin, K., Shukla, J., Doblas-Reyes, F. (2005). Fundamental challenge in simulation and prediction of summer monsoon rainfall. Geophysical Research Letters, 32(15), L15711.Google Scholar
Wang, B., Xiang, B., Lee, J.-Y. (2013). Subtropical high predictability establishes a promising way for monsoon and tropical storm predictions. Proceedings of the National Academy of Sciences, 110 (8), 2718.Google Scholar
Wang, L., Yu, J.-Y., Paek, H. (2017). Enhanced biennial variability in the Pacific due to Atlantic capacitor effect. Nature Communications, 8, 14887.Google Scholar
Wang, Y., Counillon, F., Keenlyside, N., Svendsen, L., Gleixner, S., Kimmritz, M., Dai, P., Gao, Y. (2019). Seasonal predictions initialised by assimilating sea surface temperature observations with the EnKF. Climate Dynamics, 53(9–10), 57775797.Google Scholar
Webster, P. J. (1995). The annual cycle and the predictability of the tropical coupled ocean-atmosphere system. Meteorology and Atmospheric Physics, 56(1), 3355.Google Scholar
Webster, P. J., Moore, A. M., Loschnigg, J. P., Leben, R. R. (1999). Coupled ocean–atmosphere dynamics in the Indian Ocean during 1997–98. Nature, 401(6751), 356360.Google Scholar
Weisheimer, A., Doblas-Reyes, F. J., Jung, T., Palmer, T. N. (2011). On the predictability of the extreme summer 2003 over Europe. Geophysical Research Letters, 38(5), L05704.Google Scholar
Weisheimer, A., Palmer, T. N. (2014). On the reliability of seasonal climate forecasts. Journal of the Royal Society Interface, 11(96), 20131162.Google Scholar
Wheeler, M. C., Hendon, H. H. (2004). An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction. Monthly Weather Review, 132(8), 19171932.Google Scholar
Woolnough, S. J., Slingo, J. M.. Hoskins, B. J. (2000). The relationship between convection and sea surface temperature on intraseasonal timescales. Journal of Climate, 13(12), 20862104.Google Scholar
Xiang, B., Zhao, M., Jiang, X., Lin, S.-J., Li, T., Fu, X., Vecchi, G. (2015). The 3–4-week MJO prediction skill in a GFDL coupled model. Journal of Climate, 28 (13), 53515364.Google Scholar
Xie, S.-P., Philander, S. G. H. (1994). A coupled ocean-atmosphere model of relevance to the ITCZ in the eastern Pacific. Tellus A, 46(4), 340350.Google Scholar
Xie, P., Arkin, P. A. (1997). Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bulletin of the American Meteorological Society, 78(11), 25392558.Google Scholar
Xie, S.-P., Annamalai, H., Schott, F. A., McCreary, J. P. (2002). Structure and mechanisms of South Indian Ocean climate variability. Journal of Climate, 15(8), 864878.Google Scholar
Xie, S.-P., Hu, K., Hafner, J., Tokinaga, H., Du, Y., Huang, G., Sampe, T. (2009). Indian Ocean capacitor effect on indo–western Pacific Climate during the summer following El Niño. Journal of Climate, 22(3), 730747.CrossRefGoogle Scholar
Xie, S.-P., Kosaka, Y., Du, Y., Hu, K., Chowdary, J. S., Huang, G. (2016). Indo-western Pacific Ocean capacitor and coherent climate anomalies in post-ENSO summer: A review. Advances in Atmospheric Sciences, 33(4), 411432.CrossRefGoogle Scholar
Yang, J., Liu, Q., Xie, S.-P., Liu, Z., Wu, L. (2007). Impact of the Indian Ocean SST basin mode on the Asian summer monsoon. Geophysical Research Letters, 34(2), L02708.Google Scholar
Yeager, S. G., Danabasoglu, G., Rosenbloom, N. A., Strand, W., Bates, S. C., Meehl, G. A., Karspeck, A. R., Lindsay, K., Long, M. C., Teng, H., Lovenduski, N. S. (2018). Predicting near-term changes in the Earth system: A large ensemble of initialized decadal prediction simulations using the community Earth system model. Bulletin of the American Meteorological Society, 99(9), 18671886.Google Scholar
Yeager, S. G., Robson, J. I. (2017). Recent progress in understanding and predicting Atlantic decadal climate variability. Current Climate Change Reports, 3(2), 112127.Google Scholar
Yu, J.-Y., Kao, P.-k., Paek, H., Hsu, H.-H., Hung, C.-W., Lu, M.-M., An, S.-I. (2014). Linking emergence of the central Pacific El Niño to the Atlantic multidecadal oscillation. Journal of Climate, 28(2), 651662.Google Scholar
Yu, J.-Y., Mechoso, C. R. (2001). A coupled atmosphere-ocean GCM study of the ENSO cycle. Journal of Climate, 14, 23292350.Google Scholar
Zebiak, S. E. (1993). Air–sea interaction in the equatorial Atlantic region. Journal of Climate, 6(8), 15671568.Google Scholar
Zhang, C., Gottschalck, J., Maloney, E. D., Moncrieff, M. W., Vitart, F., Waliser, D. E., Wang, B., Wheeler, M. C. (2013). Cracking the MJO nut. Geophysical Research Letters, 40(6), 12231230.Google Scholar
Zhang, C. D. (2005). Madden–Julian oscillation. Reviews of Geophysics, 43 (2), RG2003.Google Scholar
Zhang, L., Wang, B., Zeng, Q. (2009). Impact of the Madden–Julian Oscillation on Summer Rainfall in Southeast China. Journal of Climate, 22(2), 201216.Google Scholar
Zhou, Q., Duan, W., Mu, M., Feng, R. (2015). Influence of positive and negative Indian Ocean Dipoles on ENSO via the Indonesian Throughflow: Results from sensitivity experiments. Advances in Atmospheric Sciences, 32(6), 783793.Google Scholar
Zhou, Q., Mu, M., Duan, W. (2019). The initial condition errors occurring in the Indian Ocean temperature that cause “spring predictability barrier” for El Niño in the Pacific Ocean. Journal of Geophysical Research: Oceans, 124(2), 12441261.Google Scholar
Zhou, S., Miller, A. J. (2005). The interaction of the Madden–Julian oscillation and the Arctic oscillation. Journal of Climate, 18(1), 143159.Google Scholar
Zhu, J., Huang, B., Kumar, A., Kinter Iii, J. L. (2015). Seasonality in prediction skill and predictable pattern of tropical Indian Ocean SST. Journal of Climate, 28(20), 79627984.Google Scholar