• Camargo, S. J., A. W. Robertson, S. J. Gaffney, P. Smyth, and M. Ghil, 2007: Cluster analysis of typhoon tracks. Part I: General properties. J. Climate, 20, 36353653, https://doi.org/10.1175/JCLI4188.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chan, J. C. L., 2000: Tropical cyclone activity over the western North Pacific associated with El Niño and La Niña events. J. Climate, 13, 29602972, https://doi.org/10.1175/1520-0442(2000)013<2960:TCAOTW>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, G., T. Iwasaki, H. Qin, and W. Sha, 2014: Evaluation of the warm-season diurnal variability over East Asia in recent reanalyses JRA-55, ERA-Interim, NCEP CFSR, and NASA MERRA. J. Climate, 27, 55175537, https://doi.org/10.1175/JCLI-D-14-00005.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, J.-M., and H.-S. Chen, 2011: Interdecadal variability of summer rainfall in Taiwan associated with tropical cyclones and monsoon. J. Climate, 24, 57865798, https://doi.org/10.1175/2011JCLI4043.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, J.-M., and C.-F. Shih, 2012: Association between northward-moving tropical cyclones and southwesterly flows modulated by intraseasonal oscillation. J. Climate, 25, 50725087, https://doi.org/10.1175/JCLI-D-11-00264.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, J.-M., F.-C. Lu, S.-L. Kuo, and C.-F. Shih, 2005: Summer climate variability in Taiwan and associated large-scale processes. J. Meteor. Soc. Japan, 83, 499516, https://doi.org/10.2151/jmsj.83.499.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, J.-M., T. Li, and C.-F. Shih, 2010: Tropical cyclone– and monsoon-induced rainfall variability in Taiwan. J. Climate, 23, 41074120, https://doi.org/10.1175/2010JCLI3355.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, J.-M., H.-S. Chen, and J.-S. Liu, 2013a: Coherent interdecadal variability of tropical cyclone rainfall and seasonal rainfall in Taiwan during October. J. Climate, 26, 308321, https://doi.org/10.1175/JCLI-D-11-00697.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, J.-M., P.-H. Tan, and C.-F. Shih, 2013b: Heavy rainfall induced by tropical cyclones across northern Taiwan and associated intraseasonal oscillation modulation. J. Climate, 26, 79928007, https://doi.org/10.1175/JCLI-D-12-00692.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, T.-C., and J.-M. Chen, 1993: The 10–20-day mode of the 1979 Indian monsoon: Its relationship with the time variation of monsoon rainfall. Mon. Wea. Rev., 121, 24652482, https://doi.org/10.1175/1520-0493(1993)121<2465:TDMOTI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, T.-C., and J.-M. Chen, 1995: An observational study of the South China Sea monsoon during the 1979 summer: Onset and life cycle. Mon. Wea. Rev., 123, 22952318, https://doi.org/10.1175/1520-0493(1995)123<2295:AOSOTS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, T.-C., S.-P. Weng, N. Yamazaki, and S. Kiehne, 1998: Interannual variation in the tropical cyclone formation over the western North Pacific. Mon. Wea. Rev., 126, 10801090, https://doi.org/10.1175/1520-0493(1998)126<1080:IVITTC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, T.-C., S.-Y. Wang, M.-C. Yen, and A. J. Clark, 2009: Impact of the intraseasonal variability of the western North Pacific large-scale circulation on tropical cyclone tracks. Wea. Forecasting, 24, 646666, https://doi.org/10.1175/2008WAF2222186.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chia, H. H., and C. F. Ropelewski, 2002: The interannual variability in the genesis location of tropical cyclones in the northwest Pacific. J. Climate, 15, 29342944, https://doi.org/10.1175/1520-0442(2002)015<2934:TIVITG>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Choi, K.-S., C.-C. Wu, and E.-J. Cha, 2010: Change of tropical cyclone activity by Pacific–Japan teleconnection pattern in the western North Pacific. J. Geophys. Res., 115, D19114, https://doi.org/10.1029/2010JD013866.

    • Search Google Scholar
    • Export Citation
  • Chu, J.-H., C. R. Sampson, A. S. Levine, and E. Fukada, 2002: The Joint Typhoon Warning Center tropical cyclone best tracks, 1945–2000. U. S. Naval Research Laboratory Tech. Rep. NRL/MR/7540-02-16, 22 pp., http://www.usno.navy.mil/NOOC/nmfc-ph/RSS/jtwc/best_tracks/TC_bt_report.html.

  • Chu, P.-S., X. Zhao, C.-H. Ho, H.-S. Kim, M.-M. Lu, and J.-H. Kim, 2010: Bayesian forecasting of seasonal typhoon activity: A track-pattern-oriented categorization approach. J. Climate, 23, 66546668, https://doi.org/10.1175/2010JCLI3710.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Colbert, A. J., B. J. Soden, and B. P. Kirtman, 2015: The impact of natural and anthropogenic climate change on western North Pacific tropical cyclone tracks. J. Climate, 28, 18061823, https://doi.org/10.1175/JCLI-D-14-00100.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ding, Y. H., 2007: The variability of the Asian summer monsoon. J. Meteor. Soc. Japan, 85B, 2154, https://doi.org/10.2151/jmsj.85B.21.

  • Feng, X., R. Wu, J. Chen, and Z. Wen, 2013: Factors for interannual variations of September–October rainfall in Hainan, China. J. Climate, 26, 89628978, https://doi.org/10.1175/JCLI-D-12-00728.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gill, A. E., 1980: Some simple solutions for heat-induced tropical circulation. Quart. J. Roy. Meteor. Soc., 106, 447462, https://doi.org/10.1002/qj.49710644905.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Harr, P. A., and R. L. Elsberry, 1991: Tropical cyclone track characteristics as a function of large-scale circulation anomalies. Mon. Wea. Rev., 119, 14481468, https://doi.org/10.1175/1520-0493(1991)119<1448:TCTCAA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Harr, P. A., and R. L. Elsberry, 1995a: Large-scale circulation variability over the tropical western North Pacific. Part I: Spatial patterns and tropical cyclone characteristics. Mon. Wea. Rev., 123, 12251246, https://doi.org/10.1175/1520-0493(1995)123<1225:LSCVOT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Harr, P. A., and R. L. Elsberry, 1995b: Large-scale circulation variability over the tropical western North Pacific. Part II: Persistence and transition characteristics. Mon. Wea. Rev., 123, 12471268, https://doi.org/10.1175/1520-0493(1995)123<1247:LSCVOT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hsu, H.-H., and C.-H. Weng, 2001: Northwestward propagation of the intraseasonal oscillation in the western North Pacific during the boreal summer: Structure and mechanism. J. Climate, 14, 38343850, https://doi.org/10.1175/1520-0442(2001)014<3834:NPOTIO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huang, P., C. Chou, and R. Huang, 2011: Seasonal modulation of tropical intraseasonal oscillations on tropical cyclone geneses in the western North Pacific. J. Climate, 24, 63396352, https://doi.org/10.1175/2011JCLI4200.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jiang, H., and E. J. Zipser, 2010: Contribution of tropical cyclones to the global precipitation from eight seasons of TRMM data: Regional, seasonal, and interannual variations. J. Climate, 23, 15261543, https://doi.org/10.1175/2009JCLI3303.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437471, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kanamitsu, M., W. Ebisuzaki, J. Woollen, S.-K. Yang, J. J. Hnilo, M. Fiorino, and G. L. Potter, 2002: NCEP–DOE AMIP-II Reanalysis (R-2). Bull. Amer. Meteor. Soc., 83, 16311643, https://doi.org/10.1175/BAMS-83-11-1631.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kikuchi, K., and B. Wang, 2010: Formation of tropical cyclones in the northern Indian Ocean associated with two types of tropical intraseasonal oscillation modes. J. Meteor. Soc. Japan, 88, 475496, https://doi.org/10.2151/jmsj.2010-313.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kim, J.-E., and M. J. Alexander, 2013: Tropical precipitation variability and convectively coupled equatorial waves on submonthly time scales in reanalysis and TRMM. J. Climate, 26, 30133030, https://doi.org/10.1175/JCLI-D-12-00353.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kim, H.-M., M.-I. Lee, P. J. Webster, D. Kim, and J. H. Yoo, 2013: A physical basis for the probabilistic prediction of the accumulated tropical cyclone kinetic energy in the western North Pacific. J. Climate, 26, 79817991, https://doi.org/10.1175/JCLI-D-12-00679.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Klein, S. A., B. J. Soden, and N.-C. Lau, 1999: Remote sea surface temperature variations during ENSO: Evidence for a tropical atmospheric bridge. J. Climate, 12, 917932, https://doi.org/10.1175/1520-0442(1999)012<0917:RSSTVD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ko, K.-C., and H.-H. Hsu, 2006: Sub-monthly circulation features associated with tropical cyclone tracks over the East Asian monsoon area during July–August season. J. Meteor. Soc. Japan, 84, 871889, https://doi.org/10.2151/jmsj.84.871.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ko, K.-C., and H.-H. Hsu, 2009: ISO modulation on the submonthly wave pattern and recurving tropical cyclones in the tropical western North Pacific. J. Climate, 22, 582599, https://doi.org/10.1175/2008JCLI2282.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kubota, H., and B. Wang, 2009: How much do tropical cyclones affect seasonal and interannual rainfall variability over the western North Pacific? J. Climate, 22, 54955510, https://doi.org/10.1175/2009JCLI2646.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lander, M. A., 1994: An exploratory analysis of the relationship between tropical storm formation in the western North Pacific and ENSO. Mon. Wea. Rev., 122, 636651, https://doi.org/10.1175/1520-0493(1994)122<0636:AEAOTR>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lau, N.-C., and M. J. Nath, 2000: Impacts of ENSO on the variability of the Asian–Australian monsoons as simulated in GCM experiments. J. Climate, 13, 42874309, https://doi.org/10.1175/1520-0442(2000)013<4287:IOEOTV>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, D. E., and M. Biasutti, 2014: Climatology and variability of precipitation in the Twentieth-Century Reanalysis. J. Climate, 27, 59645981, https://doi.org/10.1175/JCLI-D-13-00630.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, R. C. Y., and W. Zhou, 2013a: Modulation of western North Pacific tropical cyclone activity by the ISO. Part I: Genesis and intensity. J. Climate, 26, 29042918, https://doi.org/10.1175/JCLI-D-12-00210.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, R. C. Y., and W. Zhou, 2013b: Modulation of western North Pacific tropical cyclone activity by the ISO. Part II: Tracks and landfalls. J. Climate, 26, 29192930, https://doi.org/10.1175/JCLI-D-12-00211.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, R. C. Y., and W. Zhou, 2015: Interdecadal changes in summertime tropical cyclone precipitation over southeast China during 1960–2009. J. Climate, 28, 14941509, https://doi.org/10.1175/JCLI-D-14-00246.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, R. C. Y., W. Zhou, and T. C. Lee, 2015: Climatological characteristics and observed trends of tropical cyclone–induced rainfall and their influences on the long-term rainfall variations in Hong Kong. Mon. Wea. Rev., 143, 21922206, https://doi.org/10.1175/MWR-D-14-00332.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ling, Z., Y. Wang, and G. Wang, 2016: Impact of intraseasonal oscillation on the activity of tropical cyclones in summer over the South China Sea. Part I: Local tropical cyclones. J. Climate, 29, 855868, https://doi.org/10.1175/JCLI-D-15-0617.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, Q., T. Marchok, H.-L. Pan, M. Bender, and S. Lord, 2000: Improvements in hurricane initialization and forecasting at NCEP with global and regional (GFDL) models. NOAA Tech. Proc. Bull. 472, 7 pp., http://www.nws.noaa.gov/om/tpb/472.pdf.

  • Lonfat, M., F. D. Marks Jr., and S. S. Chen, 2004: Precipitation distribution in tropical cyclones using the Tropical Rainfall Measuring Mission (TRMM) microwave imager: A global perspective. Mon. Wea. Rev., 132, 16451660, https://doi.org/10.1175/1520-0493(2004)132<1645:PDITCU>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Madden, R. A., and P. R. Julian, 1971: Detection of a 40–50 day oscillation in the zonal wind in the tropical Pacific. J. Atmos. Sci., 28, 702708, https://doi.org/10.1175/1520-0469(1971)028<0702:DOADOI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Madden, R. A., and P. R. Julian, 1972: Description of global-scale circulation cells in the tropics with a 40–50 day period. J. Atmos. Sci., 29, 11091123, https://doi.org/10.1175/1520-0469(1972)029<1109:DOGSCC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mao, J., and J. C. L. Chan, 2005: Intraseasonal variability of the South China Sea summer monsoon. J. Climate, 18, 23882402, https://doi.org/10.1175/JCLI3395.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matsuno, T., 1966: Quasi-geostrophic motions in the equatorial area. J. Meteor. Soc. Japan, 44, 2543, https://doi.org/10.2151/jmsj1965.44.1_25.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McBride, J. J., 1995: Tropical cyclone formation. Global perspectives on tropical cyclones, R. L. Elsberry, Ed., WMO/TD-693, TCP-38, 63–105.

  • Murakami, M., 1979: Large-scale aspects of deep convective activity over the GATE area. Mon. Wea. Rev., 107, 9941013, https://doi.org/10.1175/1520-0493(1979)107<0994:LSAODC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Murakami, T., L.-X. Chen, A. Xie, and M. L. Shrestha, 1986: Eastward propagation of 30–60 day perturbations as revealed from outgoing longwave radiation data. J. Atmos. Sci., 43, 961971, https://doi.org/10.1175/1520-0469(1986)043<0961:EPODPA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nakazawa, T., and K. Rajendran, 2007: Relationship between tropospheric circulation over the western North Pacific and tropical cyclone approach/landfall on Japan. J. Meteor. Soc. Japan, 85, 101114, https://doi.org/10.2151/jmsj.85.101.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Philander, S. G., 1990: El Niño, La Niña, and the Southern Oscillation. International Geophysics Series, Vol. 46, Academic Press, 293 pp.

  • Rasmusson, E. M., and T. H. Carpenter, 1982: Variations in tropical sea surface temperature and surface wind fields associated with the Southern Oscillation/El Niño. Mon. Wea. Rev., 110, 354384, https://doi.org/10.1175/1520-0493(1982)110<0354:VITSST>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rodgers, E. B., R. F. Adler, and H. F. Pierce, 2000: Contribution of tropical cyclones to the North Pacific climatological rainfall as observed from satellites. J. Appl. Meteor., 39, 16581678, https://doi.org/10.1175/1520-0450(2000)039<1658:COTCTT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Saha, S., and Coauthors, 2010: The NCEP Climate Forecast System Reanalysis. Bull. Amer. Meteor. Soc., 91, 10151057, https://doi.org/10.1175/2010BAMS3001.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schenkel, B. A., and R. E. Hart, 2012: An examination of tropical cyclone position, intensity, and intensity life cycle within atmospheric reanalysis datasets. J. Climate, 25, 34533475, https://doi.org/10.1175/2011JCLI4208.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Silva, V. B. S., V. E. Kousky, and R. W. Higgins, 2011: Daily precipitation statistics for South America: An intercomparison between NCEP reanalysis and observations. J. Hydrometeor., 12, 101117, https://doi.org/10.1175/2010JHM1303.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Skok, G., J. Bacmeister, and J. Tribbia, 2013: Analysis of tropical cyclone precipitation using an object-based algorithm. J. Climate, 26, 25632579, https://doi.org/10.1175/JCLI-D-12-00135.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, T. M., and R. W. Reynolds, 2003: Extended reconstruction of global sea surface temperatures based on COADS data (1854–1997). J. Climate, 16, 14951510, https://doi.org.10.1175/1520-0442-16.10.1495.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, T. M., and R. W. Reynolds, 2004: Improved extended reconstruction of SST (1854–1997). J. Climate, 17, 24662477, https://doi.org/10.1175/1520-0442(2004)017<2466:IEROS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, T. M., R. W. Reynolds, T. C. Peterson, and J. Lawrimore, 2008: Improvements to NOAA’s historical merged land–ocean surface temperature analysis (1880–2006). J. Climate, 21, 22832296, https://doi.org/10.1175/2007JCLI2100.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, B., and J. C. L. Chan, 2002: How strong ENSO events affect tropical storm activity over the western North Pacific. J. Climate, 15, 16431658, https://doi.org/10.1175/1520-0442(2002)015<1643:HSEEAT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, C., C. Li, M. Mu, and W. Duan, 2013: Seasonal modulations of different impacts of two types of ENSO events on tropical cyclone activity in the western North Pacific. Climate Dyn., 40, 28872902, https://doi.org/10.1007/s00382-012-1434-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 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, 19171932, https://doi.org/10.1175/1520-0493(2004)132<1917:AARMMI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, L., Z. Wen, R. Huang, and R. Wu, 2012: Possible linkage between the monsoon trough variability and the tropical cyclone activity over the western North Pacific. Mon. Wea. Rev., 140, 140150, https://doi.org/10.1175/MWR-D-11-00078.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, Y., S. Wu, and P. Zhai, 2007 :The impact of tropical cyclones on Hainan Island’s extreme and total precipitation. Int. J. Climatol., 27, 10591064, https://doi.org/10.1002/joc.1464.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xie, P., and P. A. Arkin, 1997: Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull. Amer. Meteor. Soc., 78, 25392558, https://doi.org/10.1175/1520-0477(1997)078<2539:GPAYMA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yasunari, T., 1979: Cloudiness fluctuations associated with the Northern Hemisphere summer monsoon. J. Meteor. Soc. Japan, 57, 227242, https://doi.org/10.2151/jmsj1965.57.3_227.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhao, H., L. Wu, and W. Zhou, 2011: Interannual changes of tropical cyclone intensity in the western North Pacific. J. Meteor. Soc. Japan, 89, 243253, https://doi.org/10.2151/jmsj.2011-305.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • View in gallery

    Characteristics of summer TCR depicted by the CFSR data: (a) 1979–2010 climatological mean (mm), (b) fraction of TCR to total rainfall (%), and (c) RMS values (mm) during the 1979–2010 period. The region around the maximum RMS center is selected as the index region (19°–28°N, 120°–128°E) and marked by a rectangular box.

  • View in gallery

    The 1979–2010 time series of summer TCR (mm) averaged from the index region. The red (green) horizontal line indicates TCR values larger (smaller) than the climatological mean by one standard deviation.

  • View in gallery

    Composite differences in summer between more-TCR and less-TCR years (more minus less): (a) TCR, (b) TC passage frequency, and (c) TC formation frequency. The green box indicates the index region of TCR (19°–28°N, 120°–128°E). Contours are 50 mm in (a) and 0.3 in (b). Difference patterns significant at the 0.1 level are shaded in (a) and (b).

  • View in gallery

    Composite differences in summer between more-TCR and less-TCR years (more minus less): (a) SST, (b) X850, and (c) S850. In (c), TC formation locations in more-TCR years are marked by green dots. Contours are 0.1°C, 2 × 105 m2 s−1, and 3 × 105 m2 s−1 in (a)–(c), respectively. Difference patterns significant at the 0.1 level are shaded.

  • View in gallery

    (a) Composite differences of summer 500-hPa winds between more-TCR and less-TCR years (more minus less). The green box indicates the index region of TCR. Difference patterns significant at the 0.1 level are shaded. (b) Variability of the monsoon trough between more-TCR years, less-TCR years, and climatology is illustrated by the 1 × 106 m2 s−1 S850 contours.

  • View in gallery

    Composite S850 anomalies for five TCR groups defined in Table 1 with the largest TCR in group 1, followed by groups 2, 3, and 4, and with the smallest TCR in group 5. Composite anomalies significant at the 0.1 level are shaded. Contour intervals are 3 × 105 m2 s−1.

  • View in gallery

    The 1979–2010 time series of convective index (106 m2 s−1) for 10–90-day ISO. The index is the mean of days with negative 10–90-day S850 values averaged from the rainfall index region near Taiwan in each summer.

  • View in gallery

    TC tracks in the six more-TCR years: (a) 26 TCs with a northwestward/northward track from the tropical WNP into the index region (the red box) near Taiwan, and (b) 6 TCs with tracks of the other type.

  • View in gallery

    Composite 10–24-day S850 anomalies for 26 TCs with a northwestward/northward track from the tropical WNP into the index region near Taiwan during the six more-TCR years. The entering day of a TC into the index region is defined as day 0. The evolution is from 6 days before entering the index region (day −6) to 4 days after entering this region (day 4). The green box indicates the index region of TCR. Contours are 3 × 105 m2 s−1 with the zero contour suppressed. Anomalies significant at the 0.1 level are shaded.

  • View in gallery

    As in Fig. 9, except for composite 30–60-day S850 anomalies. Contours are 2 × 105 m2 s−1 with the zero contour suppressed. Anomalies significant at the 0.1 level are shaded.

  • View in gallery

    The propagations of the major cyclonic anomaly center of ISO mode from day −6 to day 4 (red dots) superimposed on composite difference patterns of TC passage frequency (contours): (a) 10–24-day ISO and (b) 30–60-day ISO. The green box indicates the index region of TCR. Contour intervals are 0.3.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 14 14 7
PDF Downloads 11 11 5

Interannual Variability of Summer Tropical Cyclone Rainfall in the Western North Pacific Depicted by CFSR and Associated Large-Scale Processes and ISO Modulations

View More View Less
  • 1 Department of Maritime Information and Technology, National Kaohsiung Marine University, Kaohsiung, Taiwan
  • 2 Department of Applied History, National Chiayi University, Chiayi, Taiwan
  • 3 Center for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
  • 4 Department of Maritime Information and Technology, National Kaohsiung Marine University, Kaohsiung, Taiwan
  • 5 Marine Meteorology Center, Central Weather Bureau, Taipei, Taiwan
© Get Permissions
Full access

Abstract

This study examines the interannual variability of summer tropical cyclone (TC) rainfall (TCR) in the western North Pacific (WNP) depicted by the Climate Forecast System Reanalysis (CFSR). This interannual variability exhibits a maximum region near Taiwan (19°–28°N, 120°–128°E). Significantly increased TCR in this region is modulated by El Niño–Southern Oscillation (ENSO)-related large-scale processes. They feature elongated sea surface temperature warming in the tropical eastern Pacific and a southeastward-intensified monsoon trough. Increased TC movements are facilitated by interannual southerly/southeasterly flows in the northeastern periphery of the intensified monsoon trough to move from the tropical WNP toward the region near Taiwan, resulting in increased TCR. The coherent dynamic relations between interannual variability of summer TCR and large-scale environmental processes justify CFSR as being able to reasonably depict interannual characteristics of summer TCR in the WNP. For intraseasonal oscillation (ISO) modulations, TCs tend to cluster around the center of a 10–24-day cyclonic anomaly and follow its northwestward propagation from the tropical WNP toward the region near Taiwan. The above TC movements are subject to favorable background conditions provided by a northwest–southeasterly extending 30–60-day cyclonic anomaly. Summer TCR tends to increase (decrease) during El Niño (La Niña) years and strong (weak) ISO years. By comparing composite TCR anomalies and correlations with TCR variability, it is found that ENSO is more influential than ISO in modulating the interannual variability of summer TCR in the WNP.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Jau-Ming Chen, cjming@mail.nkmu.edu.tw

Abstract

This study examines the interannual variability of summer tropical cyclone (TC) rainfall (TCR) in the western North Pacific (WNP) depicted by the Climate Forecast System Reanalysis (CFSR). This interannual variability exhibits a maximum region near Taiwan (19°–28°N, 120°–128°E). Significantly increased TCR in this region is modulated by El Niño–Southern Oscillation (ENSO)-related large-scale processes. They feature elongated sea surface temperature warming in the tropical eastern Pacific and a southeastward-intensified monsoon trough. Increased TC movements are facilitated by interannual southerly/southeasterly flows in the northeastern periphery of the intensified monsoon trough to move from the tropical WNP toward the region near Taiwan, resulting in increased TCR. The coherent dynamic relations between interannual variability of summer TCR and large-scale environmental processes justify CFSR as being able to reasonably depict interannual characteristics of summer TCR in the WNP. For intraseasonal oscillation (ISO) modulations, TCs tend to cluster around the center of a 10–24-day cyclonic anomaly and follow its northwestward propagation from the tropical WNP toward the region near Taiwan. The above TC movements are subject to favorable background conditions provided by a northwest–southeasterly extending 30–60-day cyclonic anomaly. Summer TCR tends to increase (decrease) during El Niño (La Niña) years and strong (weak) ISO years. By comparing composite TCR anomalies and correlations with TCR variability, it is found that ENSO is more influential than ISO in modulating the interannual variability of summer TCR in the WNP.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Jau-Ming Chen, cjming@mail.nkmu.edu.tw

1. Introduction

Tropical cyclone (TC) activity over the Asia–Pacific region is very active. It often induces significant amounts of rainfall over short periods and causes severe flooding during landfall. Over land and islands, the contribution of TC rainfall (TCR) to total rainfall is usually estimated by meteorological station data. In Taiwan, the regional fractional distributions are about 48% during summer and 27% during October (e.g., Chen et al. 2010; Chen and Chen 2011; Chen et al. 2013a). In Hong Kong, about 25% of the total rainfall is from TCs during the active TC season (June–November) (e.g., Li et al. 2015). Over Hainan Island, the proportion of total rainfall due to TCs is about 28% over the entire year (e.g., Wu et al. 2007) and 20%–40% over southeastern China in the summer months (e.g., Li and Zhou 2015). For islands at the western edge of the Pacific subtropical high along 125°E, TCR accounts for 50%–60% of total rainfall in the region between 18° and 26°N (e.g., Kubota and Wang 2009). Over oceans where station observations are generally rare, satellite observations provide remote estimates of rainfall over global basins. TCR is normally estimated from rainfall that occurs within a range of radii from the center of TCs. The radii vary from about 2.5° in Skok et al. (2013) to 4° in Rodgers et al. (2000) and 5° in Lonfat et al. (2004) and Jiang and Zipser (2010). Even with different radius ranges, analyses of TCR in the western North Pacific (WNP) exhibit some common features. The fraction of TCR to total rainfall tends to be larger than 20% in the TC-active region over 15°–28°N, 110°–140°E, with a maximum value up to 40%–50% in the open oceans southeast of Taiwan or northeast of the Philippines [see Fig. 6c of Jiang and Zipser (2010) and Fig. 6d of Skok et al. (2013)].

In addition to satellite observations, another rainfall dataset available for TCR analysis over ocean regions is the global reanalysis dataset. Taking the National Centers for Environmental Prediction (NCEP) reanalysis data as an example, the early released Reanalysis 1 (R1) and Reanalysis 2 (R2) data (e.g., Kalnay et al. 1996; Kanamitsu et al. 2002) have a spatial resolution on a 2.5° × 2.5° grid (about 250 km). This resolution is too coarse to depict TC-related phenomenon given that TCs have a normal radius size of 200–500 km. The recently released NCEP Climate Forecast System Reanalysis (CFSR) has greatly increased the spatial resolution onto a 0.5° × 0.5° grid (e.g., Saha et al. 2010), which makes TCR features resolvable. Chen et al. (2014) demonstrated that CFSR can reasonably reproduce the diurnal cycle of rainfall over East Asia in the aspects of the summer migration of monsoon rainbands and interannual variability. Silva et al. (2011) showed evident improvements in the large-scale precipitation patterns of CFSR over South America compared with previous analyses of R1 and R2. In the tropical region, CFSR has noticeably increased accuracy over R1 and R2 in reproducing observed climatological monthly mean precipitation over tropical oceans (e.g., Lee and Biasutti 2014) and in reproducing more realistic variability of the diurnal cycle of precipitation and seasonality of regional precipitation variations associated with submonthly scale waves (e.g., Kim and Alexander 2013). Saha et al. (2010) demonstrated that the cooling of sea surface temperature (SST) by precipitation reaches a maximum at lag day 5 in CFSR. Schenkel and Hart (2012) compared the position of TCs depicted by five reanalysis datasets: the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis, the ECMWF interim reanalysis, the Modern-Era Retrospective Analysis for Research and Application (MERRA), CFSR, and the Japanese 25-yr Reanalysis. They found that with the use of vortex relocation the CFSR exhibits the smallest TC position differences among these reanalysis datasets (e.g., Liu et al. 2000). Based upon the above work, it is reasonable to infer that high-resolution CFSR data may adequately portray TC-related features in the WNP region. The parameter TCR can be representative of many aspects of TC activity, which include frequency, lifespan, size, and intensity (e.g., Skok et al. 2013). TC genesis frequency and ensuing passage frequency in the WNP can be strongly affected by large-scale environments. Favorable conditions for TC genesis include reduced vertical wind shear, warm SST, enhanced lower-level relative vorticity, and upward motion (e.g., McBride 1995; Chan 2000; Chia and Ropelewski 2002; Wu et al. 2012). After formation, TCs are steered by large-scale circulations associated with the variability of the monsoon trough and Pacific subtropical high to exhibit different types of tracks (e.g., Harr and Elsberry 1991, 1995a,b; Camargo et al. 2007). The westward movements of TCs are normally steered by anomalous easterly flows in company with an intensified Pacific subtropical high, while anomalous westerly flows associated with an enhanced monsoon trough tend to drive TCs northward (e.g., Harr and Elsberry 1991; Nakazawa and Rajendran 2007; Chen et al. 2009).

The large-scale circulation features exhibit interannual and intraseasonal variations that exert noticeable modulations on TC activity. On an interannual time scale, an El Niño event causes the monsoon trough to extend eastward by which TC formation location shifts eastward with an increase in the southeastern quadrant of the WNP (e.g., Lander 1994; Wang and Chan 2002; Wang et al. 2013). These TCs tend to have a northward recurving track in association with an enhanced monsoon trough (e.g., Wang and Chan 2002; Zhao et al. 2011; Kim et al. 2013; Colbert et al. 2015). On the other hand, the increased intensity of the Pacific subtropical high is associated with more TC passages from the WNP into East Asia and the South China Sea (SCS) via a westward straight track (e.g., Nakazawa and Rajendran 2007; Choi et al. 2010). On an intraseasonal time scale, both the 30–60- and 10–24-day intraseasonal oscillation (ISO) modes can effectively modulate TC formation and movement tracks via their various propagating features and convective phases (e.g., Li and Zhou 2013a,b; Ling et al. 2016). Both the 30–60- and 10–24-day ISOs may propagate northward, northwestward, or westward (e.g., Kikuchi and Wang 2010; Huang et al. 2011; Chen et al. 2013b). Among the seven types of major TC tracks in the WNP, two recurving types and one straight type tend to concur with convective ISO phases in the WNP (e.g., Camargo et al. 2007). Both the 10–24- and 30–60-day ISOs also exert impacts on TC tracks to impinge on the islands of Hainan (e.g., Feng et al. 2013) and Taiwan (e.g., Chen and Shih 2012).

The above results indicate that CFSR may be capable of depicting TCR features with the increased resolution of a 0.5° × 0.5° grid. However, the capability of CFSR in delineating TCR features has not been examined so far. TCR variability was found to connect closely with TC track features that can be evidently modulated by El Niño–Southern Oscillation (ENSO) and ISO (e.g., Li and Zhou 2013b; Wang and Chan 2002). As such, TCR variability is likely to be systematically modulated by major intraseasonal and interannual modes in the WNP. The relative impacts of ENSO and ISO on major TCR variability in the WNP remain unclear and need to be analyzed. Three questions are examined in this study:

  • Can CFSR reasonably depict interannual characteristics of summer (June–August) TCR in the WNP?
  • How do the large-scale interannual and intraseasonal modes affect interannual variability of summer TCR? Specifically, what are the large-scale modulating effects associated with ENSO, 10–24-day ISO, and 30–60-day ISO?
  • What are the relative influences of ENSO and ISO in modulating interannual variability of summer TCR?

Results of this study should serve as an examination of the suitability of using CFSR precipitation data in examining WNP TCR. Given adequate representation, CFSR precipitation data may be used to validate precipitation patterns obtained from high-resolution global simulations (e.g., Skok et al. 2013). These results can provide insight into the modulating processes of large-scale circulations on WNP TC activity on interannual and intraseasonal time scales.

2. Data

Variability of summer TCR in the WNP is depicted by CFSR precipitation data. As documented by Saha et al. (2010), the major improvements of CFSR relative to NCEP R1 and R2 include the coupling of the atmosphere and ocean in generating the 6-h guess field and the assimilation of satellite radiances. CFSR is the first NCEP global reanalysis to use raw observed radiance measurements in the assimilation system over the entire period, whereas satellite retrievals were assimilated in NCEP R1 and R2. In CFSR, observed satellite radiances were bias corrected with spinup runs to enable smooth transitions of climate records due to continuous changes in the satellite observing system. Comparisons in the 5-day forecast anomaly correlation of 500-hPa height over the Northern Hemisphere and Southern Hemisphere indicate that CFSR is considerably more accurate than previous reanalyses of R1 and R2. CFSR uses two sets of global precipitation analyses: the Climate Prediction Center (CPC) pentad Merged Analysis of Precipitation (CMAP; Xie and Arkin 1997) on a 2.5° × 2.5° grid over the globe and the CPC unified global daily gauge analysis on a 0.5° × 0.5° grid over global land. The CMAP dataset combines information from gauge observations and satellite observations. Readers are referred to Saha et al. (2010) for detailed descriptions of CFSR data.

The TCR variability is examined with respect to environmental characteristics, which include large-scale circulations and winds as represented in CFSR. All CFSR data are on a 0.5° × 0.5° grid. Monthly Extended Reconstructed SST (ERSST) version 3 data (e.g., Smith and Reynolds 2003, 2004; Smith et al. 2008) on a 2° × 2° grid are used to define large-scale oceanic conditions. The 6-h Joint Typhoon Warning Center (JTWC) best-track data (Chu et al. 2002) are used to analyze TC activity in the WNP. The analyzed characteristics include formation frequency, passage frequency, and movement tracks. The analysis period spans from 1979 to 2010.

3. TCR characteristics in the WNP

To date, no consensus has been reached on the use of a TC radius size for estimating TCR. In general, a radius of 2.5°–3° is considered near the low end of the size. To take into account the existence of some large TCs in the WNP, a 5° radius used by Jiang and Zipser (2010) is adopted in this study. TCR is estimated using CFSR precipitation data with the following procedures. The 6-h JTWC best track data are used to locate the center of a TC. The corresponding 6-h accumulated CFSR precipitation in the grids within the range of a 5° radius from the center of a TC is defined as TCR. The defined TCR is accumulated from June to August to compute summer TCR for all grids. The 1979–2010 mean of the summer TCR accumulated from June to August over the WNP is shown in Fig. 1a. It exhibits regional maxima over the islands of Taiwan and the Philippines. Over the ocean, the region of maximum TCR extends from the Luzon Strait between Taiwan and the Philippines southeastward into the tropical WNP. The fraction of TCR to total rainfall (Fig. 1b) is commonly larger than 20% in the TC-active 15°–25°N zone over the WNP. The fraction reaches a maximum value of about 40%–50% to the southeast of Taiwan/northeast of the Philippines. This maximum center is spatially and quantitatively consistent with analyses of the TCR fraction obtained by Jiang and Zipser (2010) and Skok et al. (2013) using satellite observations. The above results indicate that climatological TCR features depicted by CFSR data in the present study are reasonable and thus suitable for further studies of interannual variability.

Fig. 1.
Fig. 1.

Characteristics of summer TCR depicted by the CFSR data: (a) 1979–2010 climatological mean (mm), (b) fraction of TCR to total rainfall (%), and (c) RMS values (mm) during the 1979–2010 period. The region around the maximum RMS center is selected as the index region (19°–28°N, 120°–128°E) and marked by a rectangular box.

Citation: Journal of Climate 31, 5; 10.1175/JCLI-D-16-0805.1

Major features of interannual TCR variability are interpreted from root-mean-square (RMS) values of 31 summer TCR patterns during 1979–2010. As shown in Fig. 1c, the interannual variability of summer TCR shows a dominant center to the southeast of Taiwan and a secondary center to the east of the Philippines. The former center overlaps with the maximum center of TCR fraction patterns in Fig. 1b, indicating the existence of TC activity in this region. The above region with a dominant RMS center near Taiwan (19°–28°N, 120°–128°E) is thus selected as the index region. TCR variability in this region is used as an index to portray the interannual variability of summer TCR in the WNP.

For delineating temporal features, the 1979–2010 time series of summer TCR averaged from the index region near Taiwan are shown in Fig. 2. Based upon these 31 values, the TCR index has a climatological mean of 249 mm and a standard deviation (STD) of 127 mm. A year with a TCR value larger (smaller) than the climatological mean by an STD is defined as a more-TCR (less TCR) year. This definition results in six more-TCR years (1979, 1982, 1990, 1994, 2004, 2005) and seven less-TCR years (1983, 1988, 1989, 1993, 1998, 1999, 2010). Spatial patterns for major interannual variability in summer TCR are delineated by composite differences in summer TCR between more-TCR and less-TCR years (more minus less) in Fig. 3a.The test statistic for the difference between two group means associated with more-TCR and less-TCR years is defined as , where , , , is the mean of group A with n1 members (n1 = 6 for the more-TCR group), and is the mean of group B with n2 members (n2 = 7 for the less-TCR group). Hereafter, composite differences significant at a 0.1 level with the Student’s t test are shaded. The TCR difference patterns exhibit two significant centers: one over the index region near Taiwan, and the other one located eastward in a subtropical zone at 130°–140°E.

Fig. 2.
Fig. 2.

The 1979–2010 time series of summer TCR (mm) averaged from the index region. The red (green) horizontal line indicates TCR values larger (smaller) than the climatological mean by one standard deviation.

Citation: Journal of Climate 31, 5; 10.1175/JCLI-D-16-0805.1

Fig. 3.
Fig. 3.

Composite differences in summer between more-TCR and less-TCR years (more minus less): (a) TCR, (b) TC passage frequency, and (c) TC formation frequency. The green box indicates the index region of TCR (19°–28°N, 120°–128°E). Contours are 50 mm in (a) and 0.3 in (b). Difference patterns significant at the 0.1 level are shaded in (a) and (b).

Citation: Journal of Climate 31, 5; 10.1175/JCLI-D-16-0805.1

TCR is an integrated result affected by the formation and passage frequency of TCs. To investigate these two factors, composite differences of TC passage frequency and TC formation frequency corresponding to Fig. 3a are shown in Figs. 3b and 3c, respectively. Using the 6-h records of the JTWC best-track data, TC passage frequency is estimated by the count of TC appearance in every 2° × 2° box throughout a summer season. A TC may have several appearances in any specific box, leading to several counts in the passage frequency in that box. TC formation frequency is the count of TC formation in every 5° × 5° box throughout a summer season. The location when the maximum sustained wind speed of a TC first reaches or is greater than 34 kt (1 kt = 0.51 m s−1) is defined as the formation location. A TC has only one count in the formation frequency. A comparison between Figs. 3a and 3b reveals that the major increase in summer TCR in the index region is associated with increased passage frequency of TCs from the tropical WNP with a northwestward track toward this region. It appears that a significant increase of northwestward TC movements occurs in more-TCR years. The increased passage frequency is accompanied by increased TC formation in the tropical WNP over the 10°–20°N, 125°–150°E region (Fig. 3c). Chu et al. (2010) demonstrated seven major TC tracks in the WNP and SCS regions, which include four northward tracks toward the northern WNP, two westward tracks toward or within the SCS, and one northwestward track from the Philippine Sea/western WNP region toward Taiwan/southeastern China. TC movements in Fig. 3b fall in the category of the northwestward track. Chen et al. (2005) demonstrated that a favorable condition for more TC rainfall in Taiwan is to have more TCs forming to the southeast of Taiwan, as these TCs are influenced by an anomalous cyclonic circulation in the WNP to move northwestward/northward toward Taiwan. The above analyses reveal that TCR variability appears to relate to the variability of passage and formation frequency of TCs. Interannual variability of summer TCR depicted above has to be justified by coherent dynamic relations with the large-scale modulating processes.

4. Interannual variability of large-scale processes modulating TC activity

Interannual variability of TC activity can be effectively modulated by SSTs and lower-level large-scale circulations (e.g., Chia and Ropelewski 2002; Wang and Chan 2002). To demonstrate large-scale modulatory processes, composite differences of SST, 850-hPa velocity potential (X850), and 850-hPa streamfunction (S850) between more-TCR and less-TCR years are shown in Fig. 4. As disclosed by statistically significant differences, composite SST differences exhibit elongated warming patterns in the tropical eastern Pacific and cooling patterns in the western Pacific (Fig. 4a). The zonal contrast in SST differences corresponds to a center of low-level convergence (positive X850 difference pattern) in the tropical eastern Pacific and a center of low-level divergence (negative X850 difference pattern) in the Maritime Continent (Fig. 4b). The above SST and X850 centers act as tropical forcings to provoke a Matsuno–Gill-type response in tropical circulations (e.g., Matsuno 1966; Gill 1980). The composite difference patterns of S850 reveal a pair of cyclonic circulations straddling the equator in the western and central Pacific (Fig. 4c). In the WNP, an elongated cyclonic difference pattern possesses a center at the 15°–20°N, 130°–150°E region with a northwestward extension toward Taiwan. This cyclonic difference pattern represents an enhanced monsoon trough and is a favorable environment for enhanced TC activity in the WNP (e.g., Chan 2000), as revealed by packed TC formation locations in this region during more-TCR years (marked by green dots in Fig. 4c).

Fig. 4.
Fig. 4.

Composite differences in summer between more-TCR and less-TCR years (more minus less): (a) SST, (b) X850, and (c) S850. In (c), TC formation locations in more-TCR years are marked by green dots. Contours are 0.1°C, 2 × 105 m2 s−1, and 3 × 105 m2 s−1 in (a)–(c), respectively. Difference patterns significant at the 0.1 level are shaded.

Citation: Journal of Climate 31, 5; 10.1175/JCLI-D-16-0805.1

The modulation of TC movement is investigated via the 500-hPa steering flow (V500) (e.g., Chan 2000; Camargo et al. 2007). Composite differences of 500-hPa winds between more-TCR and less-TCR years (more minus less) are illustrated in Fig. 5a. As shown previously, increased TC formation mainly occurs to the southeast of Taiwan over the 10°–20°N, 125°–150°E region (see Fig. 3c). After formation, the steering flows of the 500-hPa winds feature cyclonic shear, which extends from the SCS southeastward into the tropical WNP (Fig. 5a). This cyclonic pattern corresponds with the northwest–southeasterly extension of negative S850 difference patterns (see Fig. 4c), indicating a southeastward intensification of the monsoon trough. Figure 5b shows the composite patterns of 1 × 106 m2 s−1 contours of S850 for more-TCR years, less-TCR years, and climatology. Comparison clearly reveals that the monsoon trough exhibits a notable southeastward intensification during more-TCR years and a northwestward retreat during less-TCR years. Wu et al. (2012) demonstrated that an intensified monsoon trough provides favorable environments for enhanced TC formation and development over the WNP. The formed TCs tend to move northwestward steered by interannual components of southeasterly/southerly flows over the northeastern periphery of the southeastward-intensified monsoon trough toward a region nearby Taiwan. Along this path, TCs experience favorable growth conditions such as cyclonic shearing patterns.

Fig. 5.
Fig. 5.

(a) Composite differences of summer 500-hPa winds between more-TCR and less-TCR years (more minus less). The green box indicates the index region of TCR. Difference patterns significant at the 0.1 level are shaded. (b) Variability of the monsoon trough between more-TCR years, less-TCR years, and climatology is illustrated by the 1 × 106 m2 s−1 S850 contours.

Citation: Journal of Climate 31, 5; 10.1175/JCLI-D-16-0805.1

The above analyses reveal that large-scale interannual features responsible for more summer TCR in the WNP regions near Taiwan appear as a southeastward intensification of the monsoon trough to facilitate TC formation in the tropical WNP to the southwest of Taiwan. The formed TCs then move along the northeastern periphery of the intensified monsoon trough to move northwestward/northward, resulting in more summer TCR in the region near Taiwan. Interannual variability of summer TCR in the WNP exhibits consistent dynamic relations with large-scale ocean–atmospheric processes. These results show that CFSR rainfall can reasonably depict the interannual characteristics of summer TCR in the WNP.

It is important to examine whether the cyclonic circulation pattern in the WNP shown in Fig. 4c is a unique feature over the globe to affect the major TCR changes analyzed in this study. To pursue this goal, the 1979–2010 years are separated into five groups based on the magnitude of TCR. As shown in Table 1, TCR is the largest in group 1, followed by group 2, group 3, and group 4, and the smallest in group 5. Member years in group 1 are the same as the more-TCR years, and member years in group 5 are the same as less-TCR years. These five groups have comparable number of members (six or seven). Composite S850 anomalies of these five groups are shown in Fig. 6. Hereafter, composite anomalies significant at the 0.1 level are shaded. In the WNP, the rainfall index region (denoted by the green box) is affected by significant cyclonic anomalies in group 1 (more-TCR years) and by significant anticyclonic anomalies in group 5 (less-TCR years). The index region is affected by insignificant cyclonic anomalies in groups 2 and 4 and by insignificant anticyclonic anomalies in group 3. The cyclonic anomalies in group 1 and anticyclonic anomalies in group 5 both show a similar zonally elongated pattern extending from the tropical eastern Pacific (around 150°W) northwestward into the index region near Taiwan. The above significant cyclonic and anticyclonic anomalies are parts of a statistically significant Matsuno–Gill-type pattern across the Pacific. They appear to exert systematic impacts on the interannual variability of summer TCR near Taiwan. The insignificant cyclonic and anticyclonic anomalies in the WNP in groups 2, 3, and 4 exhibit a spatial pattern different from the significant anomalies shown in groups 1 and 5. For the regions other than the Pacific, no significant and organized anomalies with the opposite polarity between group 1 and group 5 are found. It is clear that the significant cyclonic anomalies in the WNP in group 1 are related to more TCR in the index region near Taiwan, whereas the significant anticyclonic anomalies in the WNP in group 5 are responsible for less TCR. The above comparisons reveal that the significant cyclonic and anticyclonic anomalies over the WNP are the unique features that modulate the major interannual variability of summer TCR near Taiwan in groups 1 and 5. For the other interannual variability of summer TCR in groups 2, 3, and 4, no significant anomalies are found to be responsible for the modulation of TCR near Taiwan.

Table 1.

The 1979–2010 years are separated into five groups based on the magnitude of TCR with the largest TCR in group 1, followed by groups 2, 3, and 4, and the smallest TCR in group 5. Member years in group 1 are the same as the more-TCR years, and those in group 5 are the same as less-TCR years.

Table 1.
Fig. 6.
Fig. 6.

Composite S850 anomalies for five TCR groups defined in Table 1 with the largest TCR in group 1, followed by groups 2, 3, and 4, and with the smallest TCR in group 5. Composite anomalies significant at the 0.1 level are shaded. Contour intervals are 3 × 105 m2 s−1.

Citation: Journal of Climate 31, 5; 10.1175/JCLI-D-16-0805.1

One significant interannual mode in the Pacific is ENSO. The modulating processes associated with interannual TCR variability illustrated in Fig. 4 reveal some key ENSO signatures. They are elongated SST warming over the tropical central-eastern Pacific (e.g., Rasmusson and Carpenter 1982; Philander 1990), the large-scale convergent and divergent centers between the tropical eastern Pacific and the Maritime Continent that reflect an atmospheric bridge conveying ENSO’s impacts to the WNP (e.g., Klein et al. 1999; Lau and Nath 2000), and elongated cyclonic circulation patterns across the SCS and the WNP to reflect the southeastward extension of the monsoon trough (e.g., Lander 1994; Chen et al. 1998). We thus examine the relations between the interannual variability of summer TCR and ENSO. The ENSO phases are defined by the National Oceanic and Atmospheric Administration (NOAA) Oceanic Niño Index (ONI) represented by SST anomalies in the Niño-3.4 region (5°S–5°N, 120°–170°W). The ONI values in summer (JJA) and ensuing winter (DJF) for more-TCR and less-TCR years are shown in Table 2. The DJF ONI values in the El Niño and La Niña phases are marked in bold and italic fonts, respectively. Table 2 reveals that four out of six more-TCR years occur in the El Niño developing phase, while two other years are in the normal phase. Four out of seven less-TCR years occur in the La Niña developing phase, while the other three years are in the normal phase. The simultaneous correlation between 1979–2010 time series of summer TCR and DJF ONI (JJA ONI) is 0.53 (0.46), statistically significant at the 0.01 (0.05) level. The above results indicate that the interannual variability of summer TCR in the index region near Taiwan significantly connects with ENSO. Increased summer TCR tends to occur in the El Niño developing year, whereas decreased summer TCR occurs in the La Niña developing year.

Table 2.

Summer TCR values, ONI values in summer (JJA) and ensuing winter (DJF), and ENSO phases for more-TCR and less-TCR years. The DJF ONI values in the El Niño (La Niña) phase defined by the ONI are marked in bold (italic) fonts.

Table 2.

5. ISO processes modulating TC activity

As shown in Fig. 3, interannual variability of summer TCR is closely related to variability of TC passage frequency or TC tracks. Variability of TC tracks is modulated by large-scale processes on both interannual and intraseasonal time scales. The ISO mode contains two major components: overmonthly scale 30–60-day and submonthly scale 10–24-day modes (e.g., Chen and Chen 1995; Ding 2007). A convective (nonconvective) phase of the 30–60-day Madden–Julian oscillation (e.g., Madden and Julian 1971, 1972) in the WNP tends to concur with a straight (recurving) track in the WNP TC (e.g., Li and Zhou 2013b). On a submonthly time scale, its circulation anomaly features a wavelike pattern propagating northwestward/northward from the tropical WNP into the East China Sea, and mainly concurs with a recurving TC (e.g., Ko and Hsu 2006, 2009). Both 30–60- and 10–24-day ISOs exhibit evident propagation features in the WNP. The 30–60-day ISO may propagate northward (e.g., Yasunari 1979; Murakami et al. 1986), northwestward (e.g., Hsu and Weng 2001), or eastward (e.g., Wheeler and Hendon 2004). The 10–24-day ISO may propagate westward (e.g., Chen and Chen 1993; Mao and Chan 2005), northwestward (e.g., Chen et al. 2013b; Li and Zhou 2013b), or northward (e.g., Chen and Shih 2012). How do ISOs modulate TC movements associated with interannual variability of summer TCR in the WNP? This question is examined in this section.

The connection between ISO circulation variability and interannual variability in summer TCR is illustrated in terms of how the ISO signal correlates with interannual TCR variability in the rainfall index region near Taiwan. To do so, daily S850 values averaged from the rainfall index region are computed for all 92 days of each summer. The 92-day time series are first subtracted from their seasonal mean. The 92 daily deviations are then subject to a fourth-order Butterworth bandpass filter (e.g., Murakami 1979) to extract the 10–90-day total ISO signal. After filtering, days with a negative 10–90-day S850 value are averaged in each summer; this value is used as an ISO convective index. The 1979–2010 time series of this ISO convective index is shown in Fig. 7. The long-term mean is −3.43 × 106 m2 s−1, and the standard deviation is 0.86 × 106 m2 s−1. Their simultaneous correlation coefficient with the summer TCR time series in Fig. 2 is −0.31, which is statistically significant at the 0.1 level. The composite values of the ISO convective index are −3.76 × 106 m2 s−1 for the six more-TCR years and −3.03 × 106 m2 s−1 for the seven less-TCR years. The Student’s t statistic for the difference of ISO convective index between more-TCR and less-TCR years is 1.40. It is statistically significant at the 0.1 level. These results indicate that in the rainfall index region near Taiwan more-TCR years tend to correspond with stronger convective intensity and less-TCR years with weaker convective intensity for total ISO modes, showing a coherent connection between ISO modes and interannual variability for summer TCR in the WNP.

Fig. 7.
Fig. 7.

The 1979–2010 time series of convective index (106 m2 s−1) for 10–90-day ISO. The index is the mean of days with negative 10–90-day S850 values averaged from the rainfall index region near Taiwan in each summer.

Citation: Journal of Climate 31, 5; 10.1175/JCLI-D-16-0805.1

To depict ISO processes modulating TC movements, the six more-TCR years with above-normal TC passage frequency in the index region near Taiwan are employed for illustration. In these more-TCR years, 32 summer TCs enter the index region. Among them, 26 TCs exhibit a northward/northwestward track from the tropical WNP toward the index region (Fig. 8a). Their tracks resemble the major composite difference patterns of TC passage frequency shown in Fig. 3b. The other six TCs exhibit a different track feature with either a northeastward movement from the SCS into the WNP or a southwestward/westward movement from the WNP into the SCS (Fig. 8b). To focus on primary and consistent processes, 26 out of 32 TCs (about 81%) as shown in Fig. 8a are used to portray the ISO modulations of these TC movements.

Fig. 8.
Fig. 8.

TC tracks in the six more-TCR years: (a) 26 TCs with a northwestward/northward track from the tropical WNP into the index region (the red box) near Taiwan, and (b) 6 TCs with tracks of the other type.

Citation: Journal of Climate 31, 5; 10.1175/JCLI-D-16-0805.1

The ISOs are represented by 30–60- and 10–24-day modes of S850. They are extracted by the bandpass filter scheme from the 92 daily deviations in June–August with respect to their summer mean in each year. To portray the evolution phases, the day when the selected TC enters the index region near Taiwan is defined as day 0. TC movement is illustrated by an evolution from 6 days before a TC entering the index region (day −6) to 4 days after entering the index region (day 4). The composite evolution features of the 10–24-day S850 associated with the 26 selected TCs from day −6 to day 4 are shown in Fig. 9. The locations of TCs in different phase days are marked by green dots. On day −6 (Fig. 9a), the salient feature of the 10–24-day ISO is a significant cyclonic anomaly over the tropical WNP, with a center around 11°N, 146°E (marked by a red dot). This cyclonic anomaly moves northwestward persistently, with its center reaching 15°N, 138°E, on day −4 (Fig. 9b) and 18°N, 130°E on day −2 (Fig. 9c). The continuous northwestward propagation of this center enters the index region at 21°N, 125°E on day 0 (Fig. 9d), overlying Taiwan at 24°N, 121°E on day 2 (Fig. 9e), and over southeastern China at 28°N, 119°E on day 4 (Fig. 9e). In these phases, TCs tend to cluster around the central region of a 10–24-day cyclonic anomaly and move northwestward/northward in company with the northwestward propagations of this cyclonic anomaly from the tropical WNP toward the index region near Taiwan, corresponding to more summer TCR over this region.

Fig. 9.
Fig. 9.

Composite 10–24-day S850 anomalies for 26 TCs with a northwestward/northward track from the tropical WNP into the index region near Taiwan during the six more-TCR years. The entering day of a TC into the index region is defined as day 0. The evolution is from 6 days before entering the index region (day −6) to 4 days after entering this region (day 4). The green box indicates the index region of TCR. Contours are 3 × 105 m2 s−1 with the zero contour suppressed. Anomalies significant at the 0.1 level are shaded.

Citation: Journal of Climate 31, 5; 10.1175/JCLI-D-16-0805.1

Composite anomalies of 30–60-day S850 corresponding to movements of the 26 selected TCs are shown in Fig. 10. The salient feature is a significant cyclonic anomaly extending northwest–southeasterly across the tropical and subtropical WNP with its center in the northwestern section. Its center (marked by a red dot) is right off the southeastern corner of the index region near Taiwan on day −6 (Fig. 10a). It moves northwestward slowly across the southern boundary of the index region toward Taiwan from day −4 to day 0. It approaches the east coast of Taiwan on day 2 and crosses Taiwan to be off its northwest coast on day 4. The center of the 30–60-day cyclonic anomaly shows a slow northwestward propagation around the index region near Taiwan. In terms of spatial structures, the 30–60-day cyclonic anomaly extends northwest–southeast across the entire 110°–150°E region from day −6 to day 0 and shrinks northwestward on day 2 and day 4. TCs tend to locate in the southeastern section of the extending cyclonic anomaly on day −4 and day −2, and move northwestward along the cyclonic anomaly toward the central region in the northwestern section on day 0 and day 2. The northwest–southeasterly extending 30–60-day cyclonic anomaly provides favorable environments for TCs to form in its southeastern section and to develop within the cyclonic anomaly via a northwestward movement toward its central region in the northwestern section. In addition to the more-TCR years, our composite analyses for the medium-TCR and less-TCR years (not shown) also reveal that TCs tend to cluster around the 10–24-day cyclonic anomalies and follow their northwestward propagation to move from the tropical WNP into the index region near Taiwan. The above TC movements are within a zonally extended 30–60-day cyclonic anomaly. The spatial relationships between 10–24- and 30–60-day ISOs and TC movement are consistent with those found from more-TCR years as shown in Figs. 9 and 10 above. These analysis results indicate that the spatial relationships between ISOs and TC movement discussed in Figs. 9 and 10 are robust in the other TCR years.

Fig. 10.
Fig. 10.

As in Fig. 9, except for composite 30–60-day S850 anomalies. Contours are 2 × 105 m2 s−1 with the zero contour suppressed. Anomalies significant at the 0.1 level are shaded.

Citation: Journal of Climate 31, 5; 10.1175/JCLI-D-16-0805.1

The composite ISO anomalies shown in Figs. 9 and 10 demonstrate that the key 10–24- and 30–60-day cyclonic anomalies modulating TC movements exist before TC formation as revealed by their appearances on day −6 (see Figs. 9a and 10a). It means that the circulations are leading to the TC occurrences. To further depict ISO modulation effects on TC movements, propagation paths of the center of the key 10–24- and 30–60-day S850 cyclonic anomalies are compared with the composite difference patterns of TC passage frequency shown in Fig. 3b. In Fig. 11, difference patterns of TC passage frequency (contours) reveal that TC activity exhibits increased northwestward movements across a region from the tropical WNP around 15°N, 140°E to the northwestern side of the index region around 27°N, 117°E. In Fig. 11a, the center of 10–24-day cyclonic anomaly exhibits a northwestward propagation path from 10°N, 145°E on day −6 toward the northwestern corner of the index region around 28°N, 119°E on day 4. For the 30–60-day ISO (Fig. 11b), its anomalous cyclonic center is less propagating and moves slowly from 18°N, 128°E on day −6 to 25°N, 120°E on day 4. Overall, the 10–24-day ISO propagates northwestward across the 119°–145°E regions, which spatially matches better the entire northwestward TC movement paths across the 117°–140°E region when compared with the limited propagation path of the 30–60-day ISO within the 120°–128°E region. As such, the propagation of 10–24-day ISO is more coherent with northwestward TC movements from day −6 to day 4 than the propagation of 30–60-day ISO. The above features indicate that TCs mainly move in accordance with the propagation of the 10–24-day cyclonic anomaly in an environment favorable for TC development that is provided by the northwest–southeasterly extending cyclonic anomaly of the 30–60-day ISO. The above features are related to the slower movement and larger spatial extent of the 30–60-day ISO than the 10–24-day ISO. Under these ISO modulations, TCs tend to move northwestward from the tropical WNP into the index region near Taiwan, leading to increased passage frequency and summer TCR on an interannual time scale.

Fig. 11.
Fig. 11.

The propagations of the major cyclonic anomaly center of ISO mode from day −6 to day 4 (red dots) superimposed on composite difference patterns of TC passage frequency (contours): (a) 10–24-day ISO and (b) 30–60-day ISO. The green box indicates the index region of TCR. Contour intervals are 0.3.

Citation: Journal of Climate 31, 5; 10.1175/JCLI-D-16-0805.1

6. The relative influences of ENSO and ISO

The above analyses have demonstrated that both ENSO and ISO influence the interannual variability of summer TCR in the WNP via the modulations of TC movements. It is of interest to compare the relative influences of ENSO and ISO on summer TCR variability. The comparisons are summarized in Table 3. During the 1979–2010 period, there had been 11 El Niño years and 8 La Niña years as defined by the DJF ONI including December of that year. The ISO convective index derived from 10–90-day S850 anomalies in the index region near Taiwan (see Fig. 7) is used to select ISO cases. The year with an ISO convective index smaller (larger) than the negative climatological mean by 0.7 standard deviation is categorized as a strong (weak) ISO year. This selection results in eight strong ISO years and eight weak ISO years (see Table 3). Composite TCR anomalies over the index region for these four climate classifications are 80 mm for El Niño years, −84 mm for La Niña years, 53 mm for strong ISO years, and −52 mm for weak ISO years. Summer TCR tends to increase during El Niño years and strong ISO years and decrease during La Niña years and weak ISO years. Composite TCR anomalies are greater in magnitude in El Niño and La Niña years than strong and weak ISO years. Moreover, the composite TCR anomalies are statistically significant (at the 0.05 level) in El Niño and La Niña years, but insignificant in strong and weak ISO years. The partial correlation of summer TCR and ensuing DJF ONI for the 19 ENSO years (11 El Niño plus eight La Niña years) is 0.67, which is statistically significant at the 0.01 level. This result indicates that summer TCR tends to significantly increase in El Niño years and significantly decrease in La Niña years. Summer TCR and 16 selected ISO years (eight strong ISO years and eight weak ISO years) have a partial correlation of −0.35 that does not reach the 0.1 significance level. This result reveals that summer TCR is less significantly influenced by strong and weak ISO years. By comparing the magnitude and statistical significance of composite TCR anomalies and partial correlations with TCR variability, we conclude that ENSO effects are more influential than ISO effects in modulating the interannual variability of summer TCR in the WNP.

Table 3.

Composite TCR anomalies in different classifications of ENSO and ISO. The partial correlations of summer TCR with DJF ONI for the 19 El Niño and La Niña years and ISO convective index for the 16 strong and week ISO years are computed. Composite TCR anomalies and partial correlations significant at the 0.05 and 0.01 levels are marked by ** and ***, respectively.

Table 3.

7. Concluding remarks

In this study, the capability of CFSR in depicting interannual characteristics of summer TC rainfall (TCR) in the WNP is examined. This capability is justified by the coherent dynamic relations between the interannual variability of summer TCR and large-scale environmental processes. The effects and relative influences of ENSO and ISO in modulating the interannual variability of summer TCR are analyzed.

In this study, TCR is defined as rainfall that occurs within a 5° radius of a TC’s center and estimated from high-resolution (0.5° × 0.5°) CFSR precipitation data. For the climatological (1979–2010) summer mean, the fraction of TCR to total rainfall reaches a maximum value of about 40%–50% in the oceans to the area southeast of Taiwan and northeast of the Philippines, showing a reasonable value when compared with previous analysis results using satellite data (e.g., Jiang and Zipser 2010; Skok et al. 2013). Interannual variability of summer TCR exhibits a maximum region (19°–28°N, 120°–128°E) near Taiwan. This area is selected as the index region. On an interannual time scale, significantly increased TCR in the index region near Taiwan is associated with increased TC passage frequency from the tropical WNP into this region and more TC formation in the 10°–20° zone of the WNP. The corresponding interannual large-scale processes include an elongated SST warming in the tropical eastern Pacific and a cooling in the tropical western Pacific. These features concur with interannual lower-level circulations of a convergent center in the eastern Pacific and a divergent center in the western Pacific. Through a Matsuno–Gill-type response, an elongated lower-level cyclonic circulation appears in the subtropical and tropical WNP, reflecting a southeastward intensification of the monsoon trough from the SCS into the tropical WNP. Increased TC formation occurs within the intensified monsoon trough. After formation, TCs are steered by interannual southerly/southeasterly flows in the northeastern periphery of the intensified monsoon trough to move northwestward from the tropical WNP toward the index region near Taiwan, leading to increased summer TCR over this region. The above results demonstrate that the interannual variability of summer TCR depicted by CFSR exhibits coherent dynamic relations with large-scale ocean–atmospheric processes and TC activity. These coherent relations justify the interannual variability of summer TCR in the WNP being reasonably depicted by CFSR. Moreover, the aforementioned large-scale processes reveal noticeable ENSO signatures. The 1979–2010 time series of summer TCR and the DJF ONI have a significantly positive correlation of 0.53. Summer TCR tends to increase in the El Niño developing year and decrease in the La Niña developing year.

The major interannual variability of summer TCR in the WNP is shown to closely relate to variability of TC passage frequency or TC tracks that are greatly modulated by ISOs. During the six more-TCR years, 26 out of 32 TCs (about 81%) exhibit a northward/northwestward track from the tropical WNP into the index region, resembling the major patterns for increased TC passage frequency during these years. Composite anomalies of 10–24- and 30–60-day ISOs corresponding to the moving phases of these 26 TCs both show northwestward propagation in the WNP. TCs tend to cluster around the center of a 10–24-day cyclonic anomaly and move northwestward in company with the northwestward propagation of this cyclonic anomaly from the tropical WNP into the index region near Taiwan. This TC movement occurs under favorable conditions for TC development provided by a northwest–southeasterly extending 30–60-day cyclonic anomaly. TCs form in the southeastern section of this 30–60-day cyclonic anomaly and move northwestward toward its central region near Taiwan in the northwestern section.

Analyses also show that summer TCR in the index region tends to increase during El Niño years and strong ISO years and decrease during La Niña years and weak ISO years. Composite TCR anomalies are greater in magnitude and more significant in El Niño and La Niña years than strong and weak ISO years. The partial correlation between summer TCR and 19 El Niño and La Niña years is larger and more significant than that with the 16 strong and weak ISO years. The comparisons of composite TCR anomalies and correlations with TCR variability show that ENSO is more influential than ISO in modulating interannual variability of summer TCR in the WNP.

ISO can affect TCR variability by modulating TC movements. Chen et al. (2013b) showed that rainfall induced by the passage of the WNP TCs across northern Taiwan varies evidently in correspondence with different ISO propagation features. TC-induced rainfall in Taiwan is strong when it corresponds to the northwestward propagations of both 30–60- and 10–24-day ISOs, while a northward-propagating 30–60-day ISO and a westward-propagating 10–24-day ISO correspond to weak rainfall. According to Chen et al.’s (2013b) findings, the northwestward propagations of both 30–60- and 10–24-day ISOs analyzed in this study tend to induce strong rainfall around Taiwan. This is consistent with the resulting more summer TCR over the index region near Taiwan in this study.

Acknowledgments

The authors thank the anonymous reviewers for their valuable comments to improve the quality of this paper. This study was supported by the Minister of Science and Technology, Taiwan, under MOST 103-2111-M-022-002-MY3, 105-2119-M-022-001, and 105-2111-M-415-001. Liang Wu was supported by the National Natural Science Foundation of China Grants 41461164005 and 41475077.

REFERENCES

  • Camargo, S. J., A. W. Robertson, S. J. Gaffney, P. Smyth, and M. Ghil, 2007: Cluster analysis of typhoon tracks. Part I: General properties. J. Climate, 20, 36353653, https://doi.org/10.1175/JCLI4188.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chan, J. C. L., 2000: Tropical cyclone activity over the western North Pacific associated with El Niño and La Niña events. J. Climate, 13, 29602972, https://doi.org/10.1175/1520-0442(2000)013<2960:TCAOTW>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, G., T. Iwasaki, H. Qin, and W. Sha, 2014: Evaluation of the warm-season diurnal variability over East Asia in recent reanalyses JRA-55, ERA-Interim, NCEP CFSR, and NASA MERRA. J. Climate, 27, 55175537, https://doi.org/10.1175/JCLI-D-14-00005.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, J.-M., and H.-S. Chen, 2011: Interdecadal variability of summer rainfall in Taiwan associated with tropical cyclones and monsoon. J. Climate, 24, 57865798, https://doi.org/10.1175/2011JCLI4043.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, J.-M., and C.-F. Shih, 2012: Association between northward-moving tropical cyclones and southwesterly flows modulated by intraseasonal oscillation. J. Climate, 25, 50725087, https://doi.org/10.1175/JCLI-D-11-00264.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, J.-M., F.-C. Lu, S.-L. Kuo, and C.-F. Shih, 2005: Summer climate variability in Taiwan and associated large-scale processes. J. Meteor. Soc. Japan, 83, 499516, https://doi.org/10.2151/jmsj.83.499.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, J.-M., T. Li, and C.-F. Shih, 2010: Tropical cyclone– and monsoon-induced rainfall variability in Taiwan. J. Climate, 23, 41074120, https://doi.org/10.1175/2010JCLI3355.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, J.-M., H.-S. Chen, and J.-S. Liu, 2013a: Coherent interdecadal variability of tropical cyclone rainfall and seasonal rainfall in Taiwan during October. J. Climate, 26, 308321, https://doi.org/10.1175/JCLI-D-11-00697.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, J.-M., P.-H. Tan, and C.-F. Shih, 2013b: Heavy rainfall induced by tropical cyclones across northern Taiwan and associated intraseasonal oscillation modulation. J. Climate, 26, 79928007, https://doi.org/10.1175/JCLI-D-12-00692.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, T.-C., and J.-M. Chen, 1993: The 10–20-day mode of the 1979 Indian monsoon: Its relationship with the time variation of monsoon rainfall. Mon. Wea. Rev., 121, 24652482, https://doi.org/10.1175/1520-0493(1993)121<2465:TDMOTI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, T.-C., and J.-M. Chen, 1995: An observational study of the South China Sea monsoon during the 1979 summer: Onset and life cycle. Mon. Wea. Rev., 123, 22952318, https://doi.org/10.1175/1520-0493(1995)123<2295:AOSOTS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, T.-C., S.-P. Weng, N. Yamazaki, and S. Kiehne, 1998: Interannual variation in the tropical cyclone formation over the western North Pacific. Mon. Wea. Rev., 126, 10801090, https://doi.org/10.1175/1520-0493(1998)126<1080:IVITTC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, T.-C., S.-Y. Wang, M.-C. Yen, and A. J. Clark, 2009: Impact of the intraseasonal variability of the western North Pacific large-scale circulation on tropical cyclone tracks. Wea. Forecasting, 24, 646666, https://doi.org/10.1175/2008WAF2222186.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chia, H. H., and C. F. Ropelewski, 2002: The interannual variability in the genesis location of tropical cyclones in the northwest Pacific. J. Climate, 15, 29342944, https://doi.org/10.1175/1520-0442(2002)015<2934:TIVITG>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Choi, K.-S., C.-C. Wu, and E.-J. Cha, 2010: Change of tropical cyclone activity by Pacific–Japan teleconnection pattern in the western North Pacific. J. Geophys. Res., 115, D19114, https://doi.org/10.1029/2010JD013866.

    • Search Google Scholar
    • Export Citation
  • Chu, J.-H., C. R. Sampson, A. S. Levine, and E. Fukada, 2002: The Joint Typhoon Warning Center tropical cyclone best tracks, 1945–2000. U. S. Naval Research Laboratory Tech. Rep. NRL/MR/7540-02-16, 22 pp., http://www.usno.navy.mil/NOOC/nmfc-ph/RSS/jtwc/best_tracks/TC_bt_report.html.

  • Chu, P.-S., X. Zhao, C.-H. Ho, H.-S. Kim, M.-M. Lu, and J.-H. Kim, 2010: Bayesian forecasting of seasonal typhoon activity: A track-pattern-oriented categorization approach. J. Climate, 23, 66546668, https://doi.org/10.1175/2010JCLI3710.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Colbert, A. J., B. J. Soden, and B. P. Kirtman, 2015: The impact of natural and anthropogenic climate change on western North Pacific tropical cyclone tracks. J. Climate, 28, 18061823, https://doi.org/10.1175/JCLI-D-14-00100.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ding, Y. H., 2007: The variability of the Asian summer monsoon. J. Meteor. Soc. Japan, 85B, 2154, https://doi.org/10.2151/jmsj.85B.21.

  • Feng, X., R. Wu, J. Chen, and Z. Wen, 2013: Factors for interannual variations of September–October rainfall in Hainan, China. J. Climate, 26, 89628978, https://doi.org/10.1175/JCLI-D-12-00728.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gill, A. E., 1980: Some simple solutions for heat-induced tropical circulation. Quart. J. Roy. Meteor. Soc., 106, 447462, https://doi.org/10.1002/qj.49710644905.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Harr, P. A., and R. L. Elsberry, 1991: Tropical cyclone track characteristics as a function of large-scale circulation anomalies. Mon. Wea. Rev., 119, 14481468, https://doi.org/10.1175/1520-0493(1991)119<1448:TCTCAA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Harr, P. A., and R. L. Elsberry, 1995a: Large-scale circulation variability over the tropical western North Pacific. Part I: Spatial patterns and tropical cyclone characteristics. Mon. Wea. Rev., 123, 12251246, https://doi.org/10.1175/1520-0493(1995)123<1225:LSCVOT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Harr, P. A., and R. L. Elsberry, 1995b: Large-scale circulation variability over the tropical western North Pacific. Part II: Persistence and transition characteristics. Mon. Wea. Rev., 123, 12471268, https://doi.org/10.1175/1520-0493(1995)123<1247:LSCVOT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hsu, H.-H., and C.-H. Weng, 2001: Northwestward propagation of the intraseasonal oscillation in the western North Pacific during the boreal summer: Structure and mechanism. J. Climate, 14, 38343850, https://doi.org/10.1175/1520-0442(2001)014<3834:NPOTIO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huang, P., C. Chou, and R. Huang, 2011: Seasonal modulation of tropical intraseasonal oscillations on tropical cyclone geneses in the western North Pacific. J. Climate, 24, 63396352, https://doi.org/10.1175/2011JCLI4200.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jiang, H., and E. J. Zipser, 2010: Contribution of tropical cyclones to the global precipitation from eight seasons of TRMM data: Regional, seasonal, and interannual variations. J. Climate, 23, 15261543, https://doi.org/10.1175/2009JCLI3303.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437471, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kanamitsu, M., W. Ebisuzaki, J. Woollen, S.-K. Yang, J. J. Hnilo, M. Fiorino, and G. L. Potter, 2002: NCEP–DOE AMIP-II Reanalysis (R-2). Bull. Amer. Meteor. Soc., 83, 16311643, https://doi.org/10.1175/BAMS-83-11-1631.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kikuchi, K., and B. Wang, 2010: Formation of tropical cyclones in the northern Indian Ocean associated with two types of tropical intraseasonal oscillation modes. J. Meteor. Soc. Japan, 88, 475496, https://doi.org/10.2151/jmsj.2010-313.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kim, J.-E., and M. J. Alexander, 2013: Tropical precipitation variability and convectively coupled equatorial waves on submonthly time scales in reanalysis and TRMM. J. Climate, 26, 30133030, https://doi.org/10.1175/JCLI-D-12-00353.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kim, H.-M., M.-I. Lee, P. J. Webster, D. Kim, and J. H. Yoo, 2013: A physical basis for the probabilistic prediction of the accumulated tropical cyclone kinetic energy in the western North Pacific. J. Climate, 26, 79817991, https://doi.org/10.1175/JCLI-D-12-00679.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Klein, S. A., B. J. Soden, and N.-C. Lau, 1999: Remote sea surface temperature variations during ENSO: Evidence for a tropical atmospheric bridge. J. Climate, 12, 917932, https://doi.org/10.1175/1520-0442(1999)012<0917:RSSTVD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ko, K.-C., and H.-H. Hsu, 2006: Sub-monthly circulation features associated with tropical cyclone tracks over the East Asian monsoon area during July–August season. J. Meteor. Soc. Japan, 84, 871889, https://doi.org/10.2151/jmsj.84.871.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ko, K.-C., and H.-H. Hsu, 2009: ISO modulation on the submonthly wave pattern and recurving tropical cyclones in the tropical western North Pacific. J. Climate, 22, 582599, https://doi.org/10.1175/2008JCLI2282.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kubota, H., and B. Wang, 2009: How much do tropical cyclones affect seasonal and interannual rainfall variability over the western North Pacific? J. Climate, 22, 54955510, https://doi.org/10.1175/2009JCLI2646.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lander, M. A., 1994: An exploratory analysis of the relationship between tropical storm formation in the western North Pacific and ENSO. Mon. Wea. Rev., 122, 636651, https://doi.org/10.1175/1520-0493(1994)122<0636:AEAOTR>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lau, N.-C., and M. J. Nath, 2000: Impacts of ENSO on the variability of the Asian–Australian monsoons as simulated in GCM experiments. J. Climate, 13, 42874309, https://doi.org/10.1175/1520-0442(2000)013<4287:IOEOTV>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, D. E., and M. Biasutti, 2014: Climatology and variability of precipitation in the Twentieth-Century Reanalysis. J. Climate, 27, 59645981, https://doi.org/10.1175/JCLI-D-13-00630.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, R. C. Y., and W. Zhou, 2013a: Modulation of western North Pacific tropical cyclone activity by the ISO. Part I: Genesis and intensity. J. Climate, 26, 29042918, https://doi.org/10.1175/JCLI-D-12-00210.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, R. C. Y., and W. Zhou, 2013b: Modulation of western North Pacific tropical cyclone activity by the ISO. Part II: Tracks and landfalls. J. Climate, 26, 29192930, https://doi.org/10.1175/JCLI-D-12-00211.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, R. C. Y., and W. Zhou, 2015: Interdecadal changes in summertime tropical cyclone precipitation over southeast China during 1960–2009. J. Climate, 28, 14941509, https://doi.org/10.1175/JCLI-D-14-00246.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, R. C. Y., W. Zhou, and T. C. Lee, 2015: Climatological characteristics and observed trends of tropical cyclone–induced rainfall and their influences on the long-term rainfall variations in Hong Kong. Mon. Wea. Rev., 143, 21922206, https://doi.org/10.1175/MWR-D-14-00332.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ling, Z., Y. Wang, and G. Wang, 2016: Impact of intraseasonal oscillation on the activity of tropical cyclones in summer over the South China Sea. Part I: Local tropical cyclones. J. Climate, 29, 855868, https://doi.org/10.1175/JCLI-D-15-0617.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, Q., T. Marchok, H.-L. Pan, M. Bender, and S. Lord, 2000: Improvements in hurricane initialization and forecasting at NCEP with global and regional (GFDL) models. NOAA Tech. Proc. Bull. 472, 7 pp., http://www.nws.noaa.gov/om/tpb/472.pdf.

  • Lonfat, M., F. D. Marks Jr., and S. S. Chen, 2004: Precipitation distribution in tropical cyclones using the Tropical Rainfall Measuring Mission (TRMM) microwave imager: A global perspective. Mon. Wea. Rev., 132, 16451660, https://doi.org/10.1175/1520-0493(2004)132<1645:PDITCU>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Madden, R. A., and P. R. Julian, 1971: Detection of a 40–50 day oscillation in the zonal wind in the tropical Pacific. J. Atmos. Sci., 28, 702708, https://doi.org/10.1175/1520-0469(1971)028<0702:DOADOI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Madden, R. A., and P. R. Julian, 1972: Description of global-scale circulation cells in the tropics with a 40–50 day period. J. Atmos. Sci., 29, 11091123, https://doi.org/10.1175/1520-0469(1972)029<1109:DOGSCC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mao, J., and J. C. L. Chan, 2005: Intraseasonal variability of the South China Sea summer monsoon. J. Climate, 18, 23882402, https://doi.org/10.1175/JCLI3395.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matsuno, T., 1966: Quasi-geostrophic motions in the equatorial area. J. Meteor. Soc. Japan, 44, 2543, https://doi.org/10.2151/jmsj1965.44.1_25.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McBride, J. J., 1995: Tropical cyclone formation. Global perspectives on tropical cyclones, R. L. Elsberry, Ed., WMO/TD-693, TCP-38, 63–105.

  • Murakami, M., 1979: Large-scale aspects of deep convective activity over the GATE area. Mon. Wea. Rev., 107, 9941013, https://doi.org/10.1175/1520-0493(1979)107<0994:LSAODC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Murakami, T., L.-X. Chen, A. Xie, and M. L. Shrestha, 1986: Eastward propagation of 30–60 day perturbations as revealed from outgoing longwave radiation data. J. Atmos. Sci., 43, 961971, https://doi.org/10.1175/1520-0469(1986)043<0961:EPODPA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nakazawa, T., and K. Rajendran, 2007: Relationship between tropospheric circulation over the western North Pacific and tropical cyclone approach/landfall on Japan. J. Meteor. Soc. Japan, 85, 101114, https://doi.org/10.2151/jmsj.85.101.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Philander, S. G., 1990: El Niño, La Niña, and the Southern Oscillation. International Geophysics Series, Vol. 46, Academic Press, 293 pp.

  • Rasmusson, E. M., and T. H. Carpenter, 1982: Variations in tropical sea surface temperature and surface wind fields associated with the Southern Oscillation/El Niño. Mon. Wea. Rev., 110, 354384, https://doi.org/10.1175/1520-0493(1982)110<0354:VITSST>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rodgers, E. B., R. F. Adler, and H. F. Pierce, 2000: Contribution of tropical cyclones to the North Pacific climatological rainfall as observed from satellites. J. Appl. Meteor., 39, 16581678, https://doi.org/10.1175/1520-0450(2000)039<1658:COTCTT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Saha, S., and Coauthors, 2010: The NCEP Climate Forecast System Reanalysis. Bull. Amer. Meteor. Soc., 91, 10151057, https://doi.org/10.1175/2010BAMS3001.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schenkel, B. A., and R. E. Hart, 2012: An examination of tropical cyclone position, intensity, and intensity life cycle within atmospheric reanalysis datasets. J. Climate, 25, 34533475, https://doi.org/10.1175/2011JCLI4208.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Silva, V. B. S., V. E. Kousky, and R. W. Higgins, 2011: Daily precipitation statistics for South America: An intercomparison between NCEP reanalysis and observations. J. Hydrometeor., 12, 101117, https://doi.org/10.1175/2010JHM1303.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Skok, G., J. Bacmeister, and J. Tribbia, 2013: Analysis of tropical cyclone precipitation using an object-based algorithm. J. Climate, 26, 25632579, https://doi.org/10.1175/JCLI-D-12-00135.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, T. M., and R. W. Reynolds, 2003: Extended reconstruction of global sea surface temperatures based on COADS data (1854–1997). J. Climate, 16, 14951510, https://doi.org.10.1175/1520-0442-16.10.1495.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, T. M., and R. W. Reynolds, 2004: Improved extended reconstruction of SST (1854–1997). J. Climate, 17, 24662477, https://doi.org/10.1175/1520-0442(2004)017<2466:IEROS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, T. M., R. W. Reynolds, T. C. Peterson, and J. Lawrimore, 2008: Improvements to NOAA’s historical merged land–ocean surface temperature analysis (1880–2006). J. Climate, 21, 22832296, https://doi.org/10.1175/2007JCLI2100.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, B., and J. C. L. Chan, 2002: How strong ENSO events affect tropical storm activity over the western North Pacific. J. Climate, 15, 16431658, https://doi.org/10.1175/1520-0442(2002)015<1643:HSEEAT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, C., C. Li, M. Mu, and W. Duan, 2013: Seasonal modulations of different impacts of two types of ENSO events on tropical cyclone activity in the western North Pacific. Climate Dyn., 40, 28872902, https://doi.org/10.1007/s00382-012-1434-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 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, 19171932, https://doi.org/10.1175/1520-0493(2004)132<1917:AARMMI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, L., Z. Wen, R. Huang, and R. Wu, 2012: Possible linkage between the monsoon trough variability and the tropical cyclone activity over the western North Pacific. Mon. Wea. Rev., 140, 140150, https://doi.org/10.1175/MWR-D-11-00078.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, Y., S. Wu, and P. Zhai, 2007 :The impact of tropical cyclones on Hainan Island’s extreme and total precipitation. Int. J. Climatol., 27, 10591064, https://doi.org/10.1002/joc.1464.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xie, P., and P. A. Arkin, 1997: Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull. Amer. Meteor. Soc., 78, 25392558, https://doi.org/10.1175/1520-0477(1997)078<2539:GPAYMA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yasunari, T., 1979: Cloudiness fluctuations associated with the Northern Hemisphere summer monsoon. J. Meteor. Soc. Japan, 57, 227242, https://doi.org/10.2151/jmsj1965.57.3_227.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhao, H., L. Wu, and W. Zhou, 2011: Interannual changes of tropical cyclone intensity in the western North Pacific. J. Meteor. Soc. Japan, 89, 243253, https://doi.org/10.2151/jmsj.2011-305.

    • Crossref
    • Search Google Scholar
    • Export Citation
Save