Abstract
Based on the empirical orthogonal function (EOF) analysis, the East Asia-Pacific (EAP) teleconnection is extracted as the leading mode of the subseasonal variability over East Asia in summer, with a meridional tripole structure and significant periods of 10–30 and 50–70 days. A two-dimensional phase-space diagram is established for the EAP index and its time tendency so as to monitor the real-time state of EAP events. Based on the phase composite analysis, the general circulation anomalies first occur over the high-latitude area of Europe centered near Novaya Zemlya at the beginning of EAP events. These general circulation anomalies then influence rainfall over Northeast China, North China, and the region south of the Yangtze River valley (YRV) as the phases of EAP event progress. The representation, predictability, and prediction skill of the EAP teleconnection are examined in the two fully coupled sub-seasonal prediction systems of the Beijing Climate Center (BCC) and UK Met Office (UKMO GloSea5). Both models are able to simulate the EAP meridional tripole over East Asia as the leading mode and its characteristics of evolution as well, except for the weaker precursors over Novaya Zemlya and an inconspicuous influence on precipitation over Northeast China. The actual prediction skill of the EAP teleconnection during May-September (MJJAS) is about 10 days in the BCC model and 15 days in the UKMO model based on correlation measures, but is higher when initialized from the EAP peak phases or when targeted on strong EAP scenarios. However, both of the ensemble prediction systems are under-dispersive and the predictable signals extend to 18 and 30 days in BCC and UKMO models based on signal-to-error metrics, indicating that there may be further scope for enhancing the capability of these models for the EAP teleconnection prediction and the associated impacts studies.
Similar content being viewed by others
References
Ahn, M.-S., D. Kim, K. R. Sperber, et al., 2017: MJO simulation in CMIP5 climate models: MJO skill metrics and process-oriented diagnosis. Climate Dyn., 49, 4023–1045, doi: https://doi.org/10.1007/s00382-017-3558-4.
Bueh, C., N. Shi, L. R. Ji, et al., 2008: Features of the EAP events on the medium-range evolution process and the mid- and high-latitude Rossby wave activities during the Meiyu period. Chinese Sci. Bull., 53, 610–623, doi: https://doi.org/10.1007/s11434-008-0005-2.
Chen, Y., and P. M. Zhai, 2015: Synoptic-scale precursors of the East Asia/Pacific teleconnection pattern responsible for persistent extreme precipitation in the Yangtze River Valley. Quart. J. Roy. Meteor. Soc., 141, 1389–1403, doi: https://doi.org/10.1002/qj.2448.
de Andrade, F. M., C. A. S. Coelho, and I. F. A. Cavalcanti, 2019: Global precipitation hindcast quality assessment of the Sub-seasonal to Seasonal (S2S) prediction project models. Climate Dyn., 52, 5451–5475, doi: https://doi.org/10.1007/s00382-018-4457-z.
Dee, D. P., S. M. Uppala, A. J. Simmons, et al., 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553–597, doi: https://doi.org/10.1002/qj.828.
Ding, Y. H., 2011: Progress and prospects of seasonal climate prediction. Adv. Meteor. Sci. Technol., 1, 14–27. (in Chinese)
Fu, X. H., and B. Wang, 2004: The boreal-summer intraseasonal oscillations simulated in a hybrid coupled atmosphere—ocean model. Mon. Wea. Rev., 132, 2628–2649, doi: https://doi.org/10.1175/MWR2811.1.
Hart, R. E., and R. H. Grumm, 2001: Using normalized climatological anomalies to rank synoptic-scale events objectively. Mon. Wea. Rev., 129, 2426–2442, doi: https://doi.org/10.1175/1520-0493(2001)129<2426:UNCATR>2.0.CO;2.
He, Z., P. C. Hsu, X. W. Liu, et al., 2019: Factors limiting the forecast skill of the boreal summer intraseasonal oscillation in a subseasonal-to-seasonal model. Adv. Atmos. Sci., 36, 104–118, doi: https://doi.org/10.1007/s00376-018-7242-3.
Hirons, L. C., P. Inness, F. Vitart, et al., 2013: Understanding advances in the simulation of intraseasonal variability in the ECMWF model. Part I: The representation of the MJO. Quart. J. Roy. Meteor. Soc., 139, 1417–1426, doi: https://doi.org/10.1002/qj.2060.
Hirota, N., and M. Takahashi, 2012: A tripolar pattern as an internal mode of the East Asian summer monsoon. Climate Dyn., 39, 2219–2238, doi: https://doi.org/10.1007/s00382-012-1416-y.
Hsu, P.-C., T. Li, L. J. You, et al., 2015: A spatial—temporal projection model for 10–30 day rainfall forecast in South China. Climate Dyn., 44, 1227–1244, doi: https://doi.org/10.1007/s00382-014-2215-4.
Hsu, P.-C., J.-Y. Lee, and K.-J. Ha, 2016: Influence of boreal summer intraseasonal oscillation on rainfall extremes in southern China. Int. J. Climatol., 36, 1403–1412, doi: https://doi.org/10.1002/joc.4433.
Hsu, P.-C., Y. T. Qian, Y. Liu, et al., 2020: Role of abnormally enhanced MJO over the western Pacific in the formation and subseasonal predictability of the record-breaking Northeast Asian heatwave in the summer of 2018. J. Climate, 33, 3333–3349, doi: https://doi.org/10.1175/JCLI-D-19-0337.1.
Huang, G., 2004: An index measuring the interannual variation of the East Asian summer monsoon—The EAP index. Adv. Atmos. Sci., 21, 41–52, doi: https://doi.org/10.1007/BF02915679.
Huang, R. H., 1992: The East Asia/Pacific pattern teleconnection of summer circulation and climate anomaly in East Asia. Acta Meteor. Sinica, 6, 25–37.
Huang, R. H., 1994: Interactions between the 30–60 day oscillation, the Walker circulation and the convective activities in the tropical western Pacific and their relations to the interannual oscillation. Adv. Atmos. Sci., 11, 367–384, doi: https://doi.org/10.1007/BF02658156.
Huang, R. H., and W. J. Li, 1987: Influence of the heat source anomaly over the tropical western Pacific on the subtropical high over East Asia. Proc. International Conference on the General Circulation of East Asia, Natl. Nat. Sci. Found. China (NSFC), Chengdu, 40–51.
Huang, R. H., and W. J. Li, 1988: Influence of heat source anomaly over the western tropical Pacific on the subtropical high over East Asia and its physical mechanism. Scientia Atmos. Sinica, 12, 107–116, doi: https://doi.org/10.3878/jissn.1006-9895.1988.t1.08. (in Chinese)
Huang, R. H., and F. Y. Sun, 1992: Interannual variation of the summer teleconnection pattern over the Northern Hemisphere and its numerical simulation. Scientia Atmos. Sinica, 16, 52–61, doi: https://doi.org/10.3878/jissn.1006-9895.1992.01.08. (in Chinese)
Huang, R. H., and F. Y. Sun, 1994: Impacts of the thermal state and the convective activities in the tropical western warm pool on the summer climate anomalies in East Asia. Scientia Atmos. Sinica, 18, 141–151, doi: https://doi.org/10.3878/j.sssn.1006-9895.1994.02.02. (in Chinese)
Huang, R. H., and L. Wang, 2010: Interannual variation of the landfalling locations of typhoons in China and its association with the summer East Asia/Pacific pattern teleconnection. Chinese J. Atmos. Sci., 34, 853–864, doi: https://doi.org/10.3878/j.issn.1006-9895.2010.05.01. (in Chinese)
Jie, W. H., T. W. Wu, J. Wang, et al., 2014: Improvement of 6–15 day precipitation forecasts using a time-lagged ensemble method. Adv. Atmos. Sci., 31, 293–304, doi: https://doi.org/10.1007/s00376-013-3037-8.
Jie, W. H., F. Vitart, T. W. Wu, et al., 2017: Simulations of the Asian summer monsoon in the sub-seasonal to seasonal prediction project (S2S) database. Quart. J. Roy. Meteor. Soc., 143, 2282–2295, doi: https://doi.org/10.1002/qj.3085.
Kalnay, E., M. Kanamitsu, R. Kistler, et al., 1996: The NCEP/NCAR 40-year reanalysis project. Bull. Amer. Meteor. Soc., 77, 437–472, doi:https://doi.org/10.11775/552-0047<(999)00770043:TNYPRP>2.0.CO;2.
Kim, H., F. Vitart, and D. E. Waliser, 2018: Prediction of the Madden-Julian oscillation: A review. J. Climate, 31, 9425–9443, doi: https://doi.org/10.1175/JCLI-D-18-0210.1.
Kim, H.-M., P. J. Webster, V. E. Toma, et al., 2014: Predictability and prediction skill of the MJO in two operational forecasting systems. J. Climate, 27, 5364–5378, doi: https://doi.org/10.1175/JCLI-D-13-00480.1.
Ko, K.-C., and J.-H. Liu, 2016: Quasi-periodic behavior of the Pacific-Japan pattern affecting propagation routes of summer-time wave patterns and the associated tropical cyclone tracks over the western North Pacific. Mon. Wea. Rev., 444, 393–408, doi: https://doi.org/10.1175/MWR-D-15-0080.1.
Kosaka, Y., and H. Nakamura, 2006: Structure and dynamics of the summertime Pacific-Japan teleconnection pattern. Quart. J. Roy. Meteor. Soc., 132, 2009–2030, doi: https://doi.org/10.1256/qj.05.204.
Kosaka, Y., and H. Nakamura, 2010: Mechanisms of meridional teleconnection observed between a summer monsoon system and a subtropical anticyclone. Part I: The Pacific-Japan pattern. J. Climate, 223, 5085–5108, doi: https://doi.org/10.1175/2010JCLI3413.1.
Kosaka, Y., S.-P. Xie, and H. Nakamura, 2011: Dynamics of interannual variability in summer precipitation over East Asia. J. Climate, 24, 5435–5453, doi: https://doi.org/10.1175/2011JCLI4099.1.
Kumar, A., P. T. Peng, and M. Y. Chen, 2014: Is there a relationship between potential and actual skill? Mon. Wea. Rev., 142, 2220–2227, doi: https://doi.org/10.1175/MWR-D-13-00287.1.
Lau, K.-M., and H. Y. Weng, 2002: Recurrent teleconnection patterns linking summertime precipitation variability over East Asia and North America. J. Meteor. Soc. Japan Ser. II, 80, 1309–1324, doi: https://doi.org/10.2151/jmsj.80.1309.
Lee, J.-Y., B. Wang, M. C. Wheeler, et al., 2013: Real-time multivariate indices for the boreal summer intraseasonal oscillation over the Asian summer monsoon region. Climate Dyn., 40, 493–509, doi: https://doi.org/10.1007/s00382-012-1544-4.
Lee, S.-S., and B. Wang, 2016: Regional boreal summer intraseasonal oscillation over Indian Ocean and western Pacific: Comparison and predictability study. Climate Dyn., 6, 2213–2229, doi: https://doi.org/10.1007/s00382-015-2698-7.
Li, C. F., A. A. Scaife, R. Y. Lu, et al., 2016: Skillful seasonal prediction of Yangtze river valley summer rainfall. Environ. Res. Lett., 11, 094002, doi: https://doi.org/10.1088/1748-9326/11/9/094002.
Li, H., P. M. Zhai, Y. Chen, et al., 2018: Potential influence of the East Asia-Pacific teleconnection pattern on persistent precipitation in South China: Implications of atypical Yangtze River valley cases. Wea. Forecasting, 33, 267–282, doi: https://doi.org/10.1175/WAF-D-17-0011.1.
Li, L., P. M. Zhai, Y. Chen, et al., 2016: Low-frequency oscillations of the East Asia-Pacific teleconnection pattern and their impacts on persistent heavy precipitation in the Yangtze-Huai River valley. J. Meteor. Res., 330, 459–471, doi: https://doi.org/10.1007/s13351-016-6024-z.
Li, R. C. Y., W. Zhou, and T. Li, 2014: Influences of the Pacific-Japan teleconnection pattern on synoptic-scale variability in the western North Pacific. J. Climate, 27, 140–154, doi: https://doi.org/10.1175/JCLI-D-13-00183.1.
Li, Y., F. Li, and P.-C. Hsu, 2020: Modulation of the intraseasonal variability of Pacific-Japan pattern by ENSO. J. Meteor. Res., 34, 1–13, doi: https://doi.org/10.1007/s13351-020-9182-y.
Liebmann, B., and C. A. Smith, 1996: Description of a complete (interpolated) outgoing longwave radiation dataset. Bull. Amer. Meteor. Soc., 77, 1275–1277, doi: https://doi.org/10.1175/1520-0477-77.6.1274.
Lim, Y., S.-W. Son, and D. Kim, 2018: MJO prediction skill of the subseasonal-to-seasonal prediction models. J. Climate, 31, 40 75–40 94, doi: https://doi.org/10.1175/JCLI-D-17-0545.1.
Lin, H., 2013: Monitoring and predicting the intraseasonal variability of the East Asian-western North Pacific summer monsoon. Mon. Wea. Rev., 141, 1124–1138, doi: https://doi.org/10.1175/MWR-D-12-00087.1.
Lin, H., G. Brunet, and J. Derome, 2008: Forecast skill of the Madden-Julian oscillation in two Canadian atmospheric models. Mon. Wea. Rev., 136, 4130–4149, doi: https://doi.org/10.1175/2008MWR2459.1.
Lin, X. Z., C. F. Li, R. Y. Lu, et al., 2018: Predictable and unpredictable components of the summer East Asia–Pacific teleconnection pattern. Adv. Atmos. Sci., 35, 1372–1380, doi: https://doi.org/10.1007/s00376-018-7305-5.
Liu, X. W., T. W. Wu, S. Yang, et al., 2017: MJO prediction using the sub-seasonal to seasonal forecast model of Beijing Climate Center. Climate Dyn., 48, 3283–3307, doi: https://doi.org/10.1007/s00382-016-3264-7.
Liu, X. W., W. J. Li, T. W. Wu, et al., 2019: Validity of parameter optimization in improving MJO simulation and prediction using the sub-seasonal to seasonal forecast model of Beijing Climate Center. Climate Dyn., 52, 3823–3843, doi: https://doi.org/10.1007/s00382-018-4369-y.
Liu, Y., H.-L. Ren, A. A. Scaife, et al., 2018: Evaluation and statistical downscaling of East Asian summer monsoon forecasting in BCC and MOHC seasonal prediction systems. Quart. J. Roy. Meteor. Soc., 144, 2798–2811, doi: https://doi.org/10.1002/qj.3405.
Lu, R. Y., 2004: Associations among the components of the East Asian summer monsoon system in the meridional direction. J. Meteor. Soc. Japan Ser. II, 82, 155–165, doi: https://doi.org/10.2151/jmsj.82.155.
Lu, R. Y., and Z. D. Lin, 2009: Role of subtropical precipitation anomalies in maintaining the summertime meridional teleconnection over the western North Pacific and East Asia. J. Climate, 22, 2058–2072, doi: https://doi.org/10.1175/2008JCLI2444.1.
MacLachlan, C., A. Arribas, K. A. Peterson, et al., 2015: Global Seasonal forecast system version 5 (GloSea5): A high-resolution seasonal forecast system. Quart. J. Roy. Meteor. Soc., 141, 1072–1084, doi: https://doi.org/10.1002/qj.2396.
Megann, A. P., D. Storkey, Y. Aksenov, et al., 2014: GO5.0: The joint NERC–Met Office NEMO global ocean model for use in coupled and forced applications. Geosci. Model Dev., 7, 1069–1092, doi: https://doi.org/10.5194/gmdd-6-5747-2013.
Min, J.-Z., C. Li, and F. Wu, 2005: A study of the relationship between summer tropical convection over the western Pacific and the rainfall in the middle–lower reaches of the Yangtze River. Chinese J. Atmos. Sci., 29, 947–954, doi: https://doi.org/10.3878/j.issn.1006-9895.2005.06.10. (in Chinese)
Neena, J. M., J. Y. Lee, D. Waliser, et al., 2014: Predictability of the Madden–Julian oscillation in the Intraseasonal Variability Hindcast Experiment (ISVHE). J. Climate, 27, 45 31–45 43, doi: https://doi.org/10.1175/JCLI-D-13-00624.1.
Nitta, T., 1987: Convective activities in the tropical western Pacific and their impact on the Northern Hemisphere summer circulation. J. Meteor. Soc. Japan Ser. II, 65, 373–390, doi: https://doi.org/10.2151/jmsj1965.65.3_373.
Nitta, T., and Z.-Z. Hu, 1996: Summer climate variability in China and its association with 500 hPa height and tropical convection. J. Meteor. Soc. Japan Ser. II, 74, 425–445, doi: https://doi.org/10.2151/jmsj1965.74.4_425.
Pegion, K., and B. P. Kirtman, 2008: The impact of air–sea interactions on the predictability of the tropical intraseasonal oscillation. J. Climate, 21, 5870–5886, doi: https://doi.org/10.1175/2008JCLI2209.1.
Plaut, G., and R. Vautard, 1994: Spells of low-frequency oscillations and weather regimes in the Northern Hemisphere. J. Ati mos. Sci., 51, 210–236, doi: https://doi.org/10.1175/1520-0469(1994)051<0210:SOLFOA>2.0.CO;2.
Rae, J. G. L., H. T. Hewitt, A. B. Keen, et al., 2015: Development of the global sea ice 6.0 CICE configuration for the Met Office global coupled model. Geosci. Model Dev., 8, 2221–2230, doi: https://doi.org/10.5194/gmd-8-2221-2015.
Rashid, H. A., H. H. Hendon, M. C. Wheeler, et al., 2011: Prediction of the Madden–Julian oscillation with the POAMA dynamical prediction system. Climate Dyn., 36, 649–661, doi: https://doi.org/10.1007/s00382-010-0754-x.
Ren, P. F., H.-L. Ren, J.-X. Fu, et al., 2018: Impact of boreal summer intraseasonal oscillation on rainfall extremes in southeastern China and its predictability in CFSv2. J. Geophys. Res. Atmos., 123, 4423–4442, doi: https://doi.org/10.1029/2017JD028043.
Robertson, A. W., A. Kumar, M. Peña, et al., 2015: Improving and promoting subseasonal to seasonal prediction. Bull. Amer. Meteor. Soc., 96, ES49–ES53, doi: https://doi.org/10.1175/BAMS-D-14-00139.1.
Scaife, A. A., and D. Smith, 2018: A signal-to-noise paradox in climate science. npj Climate Atmos. Sci., 1, 28, doi: https://doi.org/10.1038/s41612-018-0038-4.
Scaife, A. A., M. Athanassiadou, M. Andrews, et al., 2014: Predictability of the quasi-biennial oscillation and its northern winter teleconnection on seasonal to decadal timescales. Geoi phys. Res. Lett., 41, 1752–1758, doi: https://doi.org/10.1002/2013GL059160.
Shi, N., C. Bueh, L. R. Ji, et al., 2008: The impact of mid- and high-latitude Rossby wave activities on the medium-range evolution of EAP events in the pre-rainy period of South China. Acta Meteor. Sinica, 66, 1020–1031, doi: https://doi.org/10.11676/qxxb2008.091. (in Chinese)
Takaya, K., and H. Nakamura, 2001: A formulation of a phase-independent wave-activity flux for stationary and migratory quasigeostrophic eddies on a zonally varying basic flow. J. Atmos. Sci., 58, 608–627, doi: https://doi.org/10.1175/1520-0469(2001)058<0608:AFOAPI>2.0.CO;2.
Vitart, F., 2017: Madden–Julian Oscillation prediction and teleconnections in the S2S database. Quart. J. Roy. Meteor. Soc., 143, 2210–2220, doi: https://doi.org/10.1002/qj.3079.
Vitart, F., C. Ardilouze, A. Bonet, et al., 2017: The subseasonal to seasonal (S2S) prediction project database. Bull. Amer. Meti eor. Soc., 98, 163–175, doi: https://doi.org/10.1175/BAMS-D-16-0017.1.
Wakabayashi, S., and R. Kawamura, 2004: Extraction of major teleconnection patterns possibly associated with the anomalous summer climate in Japan. J. Meteor. Soc. Japan Ser. II, 82, 1577–1588, doi: https://doi.org/10.2151/jmsj.82.1577.
Walters, D., I. Boutle, M. Brooks, et al., 2017: The Met Office Unified Model Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations. Geosci. Model Dev., 10, 1487–1520, doi: https://doi.org/10.5194/gmd-10-1487-2017.
Wang, B., J.-Y. Lee, I.-S. Kang, et al., 2009: Advance and prospectus of seasonal prediction: Assessment of the APCC/Cli-PAS 14-model ensemble retrospective seasonal prediction (1980–2004). Climate Dyn., 33, 93–117, doi: https://doi.org/10.1007/s00382-008-0460-0.
Wang, J. B., Z. P. Wen, R. G. Wu, et al., 2016: The mechanism of growth of the low-frequency East Asia–Pacific teleconnection and the triggering role of tropical intraseasonal oscillation. Climate Dyn., 46, 3965–3977, doi: https://doi.org/10.1007/s00382-015-2815-7.
Wang, L. J., C. Wang, and D. Guo, 2018: Evolution mechanism of synoptic-scale EAP teleconnection pattern and its relationship to summer precipitation in China. Atmos. Res., 214, 150–162, doi: https://doi.org/10.1016/j.atmosres.2018.07.023.
Weng, H. Y., A. Sumi, Y. N. Takayabu, et al., 2004: Interannual—interdecadal variation in large-scale atmospheric circulation and extremely wet and dry summers in China/Japan during 1951–2000. Part I: Spatial patterns. J. Meteor. Soc. Japan Ser. II, 82, 775–788, doi: https://doi.org/10.2151/jmsj.2004.775.
Wheeler, M. C., and H. H. Hendon, 2004: An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction. Mon. Wea. Rev., 132, 1917–1932, doi: https://doi.org/10.1175/1520-0493(2004)<132o1917:AARMMI>2.0.CO;2.
Woolnough, S. J., F. Vitart, and M. A. Balmaseda, 2007: The role of the ocean in the Madden-Julian Oscillation: Implications for MJO prediction. Quart. J. Roy. Meteor. Soc., 133, 117–128, doi: https://doi.org/10.1002/qj.4.
Wu, J., and X.-J. Gao, 2013: A gridded daily observation dataset over China region and comparison with the other datasets. Chinese J. Geophys., 56, 1102–1111. (in Chinese)
Wu, J., X. F. Xu, F. F. Jin, et al., 2013: Research of the intraseasonal evolution of the East Asia-Pacific pattern and its maintenance mechanism. Acta Meteor. Sinica, 71, 476–491, doi: https://doi.org/10.11676/qxxb2013.038. (in Chinese)
Wu, J., H.-L. Ren, J. Q. Zuo, et al., 2016a: MJO prediction skill, predictability, and teleconnection impacts in the Beijing Climate Center Atmospheric General Circulation Model. Dyn. Atmos. Oceans, 75, 78–90, doi: https://doi.org/10.1016/j.dynatmoce.2016.06.001.
Wu, J., X.-F. Xu, F.-F. Jin, et al., 2016b: Numerical simulation of the influence of baroclinic basic flow on cyclone perturbation low-frequency development in East Asia summer monsoon areas. Chinese J. Geophys., 59, 1222–1234, doi: https://doi.org/10.6038/cjg20160405. (in Chinese)
Wu, J., H.-L. Ren, X. F. Xu, et al., 2018: Seasonal modulation of MJO’s impact on precipitation in China and its dynamical-statistical downscaling prediction. Meteor. Mon., 44, 737–751. (in Chinese)
Wu, J., H.-L. Ren, B. Lu, et al., 2020: Effects of moisture initialization on MJO and its teleconnection prediction in BCC sub-seasonal coupled model. J. Geophys. Res. Atmos., 125, e2019 JD031537, doi: https://doi.org/10.1029/2019JD031537.
Wu, T. W., L. C. Song, W. P. Li, et al., 2014: An overview of BCC climate system model development and application for climate change studies. J. Meteor. Res., 28, 34–56, doi: https://doi.org/10.1007/s13351-014-3041-7.
Yang, Y., Z. W. Zhu, T. Li, et al., 2020: Effects of western Pacific intraseasonal convection on surface air temperature anomalies over North America. Int. J. Climatol., 40, 2913–2923, doi: https://doi.org/10.1002/joc.6373.
Zhu, Z. W., and T. Li, 2017: The statistical extended-range (10–30-day) forecast of summer rainfall anomalies over the entire China. Climate Dyn., 48, 209–224, doi: https://doi.org/10.1007/s00382-016-3070-2.
Acknowledgments
The computations were conducted on the China Meteorological Administration (CMA) Shuguang-PI high-performance computing platform and the computational resources are gratefully acknowledged. The CN05.1 rainfall data were provided by Dr. Jia Wu (wujia@cma.gov.cn) of the National Climate Center (NCC) of CMA.
Author information
Authors and Affiliations
Corresponding author
Additional information
Supported by the National Key Research and Development Program of China (2018YFC1505906), National Natural Science Foundation of China (41905067 and 41775066), National (Key) Basic Research and Development (973) Program of China (2015CB453203), and UK-China Research and Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund.
Rights and permissions
About this article
Cite this article
Wu, J., Zhang, P., Li, L. et al. Representation and Predictability of the East Asia-Pacific Teleconnection in the Beijing Climate Center and UK Met Office Subseasonal Prediction Systems. J Meteorol Res 34, 941–964 (2020). https://doi.org/10.1007/s13351-020-0040-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13351-020-0040-8