Abstract
This study focuses on the seasonal forecasting of the June–November frequency of the western North Pacific tropical cyclones (WNP TCF) by combining observations and the North-American multi-model ensemble (NMME) forecasts. We model the interannual variability in WNP TCF using Poisson regression with two sea surface temperature (SST)-based predictors, the first empirical orthogonal function of SST in the Pacific meridional mode (PMM) region (“PSPMM”) after linearly removing the impacts of the El Niño Southern Oscillation, and the SST anomalies averaged over the North Atlantic Ocean (“NASST”). The Poisson regression model trained with the observed WNP TCF and the two predictors exhibits a high skill (correlation coefficient of 0.73 and root mean square error equal to 3.2 TC/year) for the 1965–2016 period. Using SST forecasts by eight models from the NMME as predictors, we can forecast the WNP TCF with promising skill in terms of correlation coefficient (0.63) and root mean square error (3.27 TC/year) for forecasts initialized in June. This study highlights the crucial role played by PMM and NASST in modulating WNP TCF, and suggests the use of PSPMM and NASST as potentially valuable predictors for WNP TCF.
Similar content being viewed by others
References
Ashok K, Behera SK, Rao SA, Weng H, Yamagata T (2007) El Niño Modoki and its possible teleconnection. J Geophys Res Oceans. https://doi.org/10.1029/2006JC003798
Camargo SJ, Zebiak SE (2002) Improving the detection and tracking of tropical cyclones in atmospheric general circulation models. Weather Forecast 17:1152–1162. https://doi.org/10.1175/1520-0434(2002)017%3C1152:itdato%3E2.0.co;2
Camargo SJ, Robertson AW, Gaffney SJ, Smyth P, Ghil M (2007) Cluster analysis of typhoon tracks. Part II: large-scale circulation and ENSO. J Clim 20:3654–3676. https://doi.org/10.1175/jcli4203.1
Camp J et al (2015) Seasonal forecasting of tropical storms using the met office GloSea5 seasonal forecast system. Q J R Meteorol Soc 141:2206–2219. https://doi.org/10.1002/qj.2516
Chan JCL (1985) Tropical cyclone activity in the Northwest Pacific in relation to the El-Nino Southern oscillation phenomenon. Mon Weather Rev 113:599–606
Chan JCL, Liu KS (2004) Global warming and Western North Pacific typhoon activity from an observational perspective. J Clim 17(23):4590–4602. https://doi.org/10.1175/3240.1
Chan JCL, Shi J-E, Lam C-M (1998) Seasonal forecasting of tropical cyclone activity over theWestern North Pacific and the South China Sea Weather Forecast 13:997–1004. https://doi.org/10.1175/1520-0434(1998)013%3C0997:sfotca%3E2.0.co;2
Chang P, Zhang L, Saravanan R, Vimont DJ, Chiang JCH, Ji L, Seidel H, Tippett MK (2007), Pacific meridional mode and El Niño—southern oscillation. Geophys Res Lett. https://doi.org/10.1029/2007GL030302
Chen J-H, Lin S-J (2013) Seasonal predictions of tropical cyclones using a 25-km-resolution general circulation model. J Clim 26:380–398. https://doi.org/10.1175/jcli-d-12-00061.1
Chen G, Tam C-Y (2010) Different impacts of two kinds of Pacific Ocean warming on tropical cyclone frequency over the western North Pacific. Geophys Res Lett. https://doi.org/10.1029/2009GL041708
Chia HH, Ropelewski CF (2002) The interannual variability in the genesis location of tropical cyclones in the Northwest Pacific. J Clim 15:2934–2944. https://doi.org/10.1175/1520-0442(2002)015%3C2934:tivitg%3E2.0.co;2
Chiang JCH, Vimont DJ (2004) Analogous Pacific and Atlantic meridional modes of tropical atmosphere–ocean variability. J Clim 17:4143–4158. https://doi.org/10.1175/jcli4953.1
Choi W, Ho C-H, Kim J, Kim H-S, Feng S, Kang K (2016) A track pattern–based seasonal prediction of tropical cyclone activity over the North Atlantic. J Clim 29:481–494. https://doi.org/10.1175/jcli-d-15-0407.1
Du Y, Yang L, Xie S-P (2011) Tropical Indian Ocean influence on Northwest Pacific tropical cyclones in summer following Strong El Niño. J Clim 24:315–322. https://doi.org/10.1175/2010jcli3890.1
Elsner JB, Jagger TH (2006) Prediction models for annual US hurricane counts. J Clim 19:2935–2952. https://doi.org/10.1175/jcli3729.1
Fan K, Wang H (2009) A new approach to forecasting typhoon frequency over the western North Pacific. Weather Forecast 24:974–986. https://doi.org/10.1175/2009waf2222194.1
Gill AE (1980) Some simple solutions for heat-induced tropical circulation. Q J R Meteorol Soc 106:447–462. https://doi.org/10.1002/qj.49710644905
Gray WM (1968) Global view of the origin of tropical disturbance and storms Mon Weather Rev 96:669–700. https://doi.org/10.1175/1520-0493(1968)096%3C0669:GVOTOO%3E2.0.CO;2
Hong C-C, Lee M-Y, Hsu H-H, Tseng W-L (2018) Distinct influences of the ENSO-Like and PMM-Like SST Anomalies on the Mean TC genesis location in the Western North Pacific: the 2015 Summer as an extreme example. J Clim 31(8):3049–3059. https://doi.org/10.1175/jcli-d-17-0504.1
Huang W-R, Chan JCL (2014) Dynamical downscaling forecasts of Western North Pacific tropical cyclone genesis and landfall. Clim Dyn 42:2227–2237. https://doi.org/10.1007/s00382-013-1747-3
Huo L, Guo P, Hameed SN, Jin D (2015) The role of tropical Atlantic SST anomalies in modulating western North Pacific tropical cyclone genesis. Geophys Res Lett 42:2378–2384. https://doi.org/10.1002/2015GL063184
Kim H-M, Webster PJ, Curry JA (2011) Modulation of North Pacific tropical cyclone activity by three phases of ENSO. J Clim 24:1839–1849. https://doi.org/10.1175/2010jcli3939.1
Kim O-Y, Kim H-M, Lee M-I, Min Y-M (2017) Dynamical–statistical seasonal prediction for western North Pacific typhoons based on APCC multi-models. Clim Dyn 48:71–88. https://doi.org/10.1007/s00382-016-3063-1
Kirtman BP et al (2014) The North American multimodel ensemble: phase-1 seasonal-to-interannual prediction; phase-2 toward developing intraseasonal prediction. Bull Am Meteorol Soc 95:585–601. https://doi.org/10.1175/bams-d-12-00050.1
Knapp KR, Kruk MC, Levinson DH, Diamond HJ, Neumann CJ (2010) The international best track archive for climate stewardship (IBTrACS). Bull Am Meteor Soc 91:363–376. https://doi.org/10.1175/2009bams2755.1
Kumar A, Chen M, Wang W (2011) An analysis of prediction skill of monthly mean climate variability. Clim Dyn 37:1119–1131. https://doi.org/10.1007/s00382-010-0901-4
Li RCY, Zhou W (2012) Changes in Western Pacific tropical cyclones associated with the El Niño–Southern Oscillation Cycle. J Clim 25:5864–5878. https://doi.org/10.1175/jcli-d-11-00430.1
Li X, Yang S, Wang H, Jia X, Kumar A (2013) A dynamical-statistical forecast model for the annual frequency of western Pacific tropical cyclones based on the NCEP Climate Forecast System version 2. J Geophys Res Atmos 118:12061–12074. https://doi.org/10.1002/2013JD020708
Li X, Xie S-P, Gille ST, Yoo C (2016) Atlantic-induced pan-tropical climate change over the past three decades. Nat Clim Change 6:275–279. https://doi.org/10.1038/nclimate2840
Lu M-M, Chu P-S, Lin Y-C (2010) Seasonal prediction of tropical cyclone activity near Taiwan using the Bayesian multivariate regression method. Weather Forecast 25:1780–1795. https://doi.org/10.1175/2010waf2222408.1
McGregor S, Timmermann A, Stuecker MF, England MH, Merrifield M, Jin F-F, Chikamoto Y (2014) Recent Walker circulation strengthening and Pacific cooling amplified by Atlantic warming. Nat Clim Change 4:888. https://doi.org/10.1038/nclimate2330
Mendelsohn R, Emanuel K, Chonabayashi S, Bakkensen L (2012) The impact of climate change on global tropical cyclone damage. Nat Clim Change 2:205–209. https://doi.org/10.1038/nclimate1357
Murakami H et al (2015) Simulation and prediction of category 4 and 5 hurricanes in the high-resolution GFDL HiFLOR coupled climate model. J Clim 28:9058–9079. https://doi.org/10.1175/jcli-d-15-0216.1
Murakami H et al (2016a) Seasonal forecasts of major hurricanes and landfalling tropical cyclones using a high-resolution GFDL coupled climate model. J Clim 29:7977–7989. https://doi.org/10.1175/jcli-d-16-0233.1
Murakami H, Villarini G, Vecchi GA, Zhang W, Gudgel R (2016b) Statistical–dynamical seasonal forecast of North Atlantic and US landfalling tropical cyclones using the high-resolution GFDL FLOR COUPLED MODEL. Mon Weather Rev 144(6):2101–2123. https://doi.org/10.1175/mwr-d-15-0308.1
Pielke R Jr, Gratz J, Landsea C, Collins D, Saunders M, Musulin R (2008) Normalized hurricane damage in the United States: 1900–2005. Nat Hazards Rev 9:29
Pielke RA, Landsea C, Mayfield M, Laver J, Pasch R (2005) Hurricanes and Global Warming. Bull Am Meteor Soc 86:1571–1575
Rayner NA et al (2003) Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J Geophys Res Atmos 108(D14):4407. https://doi.org/10.1029/2002JD002670
Vecchi GA et al (2011) Statistical–dynamical predictions of seasonal North Atlantic hurricane activity. Mon Weather Rev 139:1070–1082. https://doi.org/10.1175/2010mwr3499.1
Vecchi GA et al (2013) Multiyear predictions of North Atlantic hurricane frequency: promise and limitations. J Clim 26:5337–5357. https://doi.org/10.1175/jcli-d-12-00464.1
Vecchi GA et al (2014) On the seasonal forecasting of regional tropical cyclone activity. J Clim 27:7994–8016. https://doi.org/10.1175/jcli-d-14-00158.1
Villarini G, Vecchi GA, Smith JA (2010) Modeling the dependence of tropical storm counts in the North Atlantic Basin on climate indices. Mon Weather Rev 138:2681–2705. https://doi.org/10.1175/2010mwr3315.1
Villarini G, Luitel B, Vecchi GA, Ghosh J (2018) Multi-model ensemble forecasting of North Atlantic tropical cyclone activity. Clim Dyn. https://doi.org/10.1007/s00382-016-3369-z
Vitart FEE (2006) Seasonal forecasting of tropical storm frequency using a multi-model ensemble. Q J R Meteorol Soc 132:647–666. https://doi.org/10.1256/qj.05.65
Wang B, Chan JCL (2002) How strong ENSO events affect tropical storm activity over the Western North Pacific. J Clim 15:1643–1658
Wang B, Xiang B, Lee J-Y (2013) Subtropical High predictability establishes a promising way for monsoon and tropical storm predictions. Proc Natl Acad Sci 110:2718–2722. https://doi.org/10.1073/pnas.1214626110
Wehner MF et al (2014) The effect of horizontal resolution on simulation quality in the community Atmospheric Model, CAM5.1. J Adv Model Earth Syst 6:980–997. https://doi.org/10.1002/2013MS000276
Woodruff JD, Irish JL, Camargo SJ (2013) Coastal flooding by tropical cyclones and sea-level rise. Nature 504:44–52. https://doi.org/10.1038/nature12855
Xiang B et al (2015) Beyond weather time-scale prediction for hurricane sandy and super typhoon haiyan in a global climate model. Mon Weather Rev 143:524–535. https://doi.org/10.1175/mwr-d-14-00227.1
Xie S-P, Hu K, Hafner J, Tokinaga H, Du Y, Huang G, Sampe T (2009) Indian Ocean capacitor effect on Indo–Western Pacific climate during the summer following El Niño. J Clim 22:730–747. https://doi.org/10.1175/2008jcli2544.1
Yu J, Li T, Tan Z, Zhu Z (2016) Effects of tropical North Atlantic SST on tropical cyclone genesis in the western North. Pac Clim Dyn 46:865–877. https://doi.org/10.1007/s00382-015-2618-x
Zhan R, Wang Y (2016) CFSv2-based statistical prediction for seasonal accumulated cyclone energy (ACE) over the Western North Pacific. J Clim 29:525–541. https://doi.org/10.1175/jcli-d-15-0059.1
Zhan R, Wang Y, Lei X (2011) Contributions of ENSO and East Indian Ocean SSTA to the interannual variability of Northwest Pacific tropical cyclone frequency. J Clim 24:509–521. https://doi.org/10.1175/2010jcli3808.1
Zhan R, Wang Y, Liu Q (2017) Salient differences in tropical cyclone activity over the Western North Pacific between 1998 and 2016. J Clim 30:9979–9997. https://doi.org/10.1175/jcli-d-17-0263.1
Zhang Q, Liu Q, Wu L (2009) Tropical cyclone damages in China 1983–2006. Bull Am Meteor Soc 90:489–495
Zhang W, Graf H-F, Leung Y, Herzog M (2012) Different El Niño types and tropical cyclone landfall in East Asia. J Clim 25(19):6510–6523. https://doi.org/10.1175/jcli-d-11-00488.1
Zhang W, Leung Y, Min J (2013) North Pacific Gyre oscillation and the occurrence of western North Pacific tropical cyclones. Geophys Res Lett 40:5205–5211. https://doi.org/10.1002/grl.50955
Zhang W et al (2016a) Improved simulation of tropical cyclone responses to ENSO in the Western North Pacific in the High-Resolution GFDL HiFLOR coupled climate model. J Clim 29:1391–1415. https://doi.org/10.1175/jcli-d-15-0475.1
Zhang W, Vecchi GA, Murakami H, Villarini G, Jia L (2016b) The Pacific meridional mode and the occurrence of tropical cyclones in the Western North Pacific. J Clim 29:381–398. https://doi.org/10.1175/JCLI-D-15-0282.1
Zhang W, Villarini G, Vecchi GA, Murakami H, Gudgel R (2016c) Statistical-dynamical seasonal forecast of western North Pacific and East Asia landfalling tropical cyclones using the high-resolution GFDL FLOR coupled model. J Adv Model Earth Syst 8:538–565. https://doi.org/10.1002/2015MS000607
Zhang W, Vecchi GA, Villarini G, Murakami H, Gudgel R, Yang X (2017a) Statistical–dynamical seasonal forecast of Western North Pacific and East Asia landfalling tropical cyclones using the GFDL FLOR coupled climate model. J Clim 30:2209–2232. https://doi.org/10.1175/jcli-d-16-0487.1
Zhang W et al (2017b) Modulation of western North Pacific tropical cyclone activity by the Atlantic Meridional. Mode Clim Dyn 48:631–647. https://doi.org/10.1007/s00382-016-3099-2
Zhang W, Vecchi GA, Murakami H, Villarini G, Delworth TL, Yang X, Jia L (2018) Dominant role of Atlantic multidecadal oscillation in the recent decadal changes in Western North Pacific tropical cyclone activity. Geophys Res Lett 45:354–362. https://doi.org/10.1002/2017GL076397
Acknowledgements
The authors thank Dr. Kun Gao and an anonymous reviewer for insightful comments. The authors thank the NMME program partners and acknowledge the help of NCEP, IRI and NCAR personnel in creating, updating and maintaining the NMME archive, with the support of NOAA, NSF, NASA and DOE. The authors acknowledge support by the Award NA14OAR4830101 from the National Oceanic and Atmospheric Administration, U.S. Department of Commerce.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Zhang, W., Villarini, G. Seasonal forecasting of western North Pacific tropical cyclone frequency using the North American multi-model ensemble. Clim Dyn 52, 5985–5997 (2019). https://doi.org/10.1007/s00382-018-4490-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00382-018-4490-y