NMME-based hybrid prediction of Atlantic hurricane season activity

  • Daniel S. HarnosEmail author
  • Jae-Kyung E. Schemm
  • Hui Wang
  • Christina A. Finan


A hybrid dynamical–statistical model is pursued for prediction of Atlantic seasonal hurricane activity driven by output of the North American Multimodel Ensemble (NMME). This is an updated version of a proven multiple linear regression method conditioned on forecast vertical wind shear from the Climate Forecast System and observed sea surface temperatures (SSTs). The method pursued for prediction utilizes August–October (ASO) Main Development Region (MDR; 10–20°N, 20–80°W) vertical wind shear and observed North Atlantic (NATL; 55–65°N, 30–60°W) SST averaged over the 3 months preceding the forecast in conjunction with the full hurricane climatology. NMME forecasts improve upon representations relative to individual members. The NMME multi-model mean better reproduces vertical wind shear distributions over the MDR and captures the observed relationships between SST and vertical wind shear with hurricane trend and interannual variability despite occasionally poor reproductions by individual members. Cross-validation reveals the multi-model average of the hybrid model outputs from the individual NMME members yields forecast errors 10–30% less than the individual members, while correlations with observed hurricane-related activity typically improve. The NMME methodology is shown to be competitive with official outlooks from Colorado State University and the National Oceanic and Atmospheric Administration over recent years.


Tropical cyclone Hurricane Typhoon North American Multimodel Ensemble Interannual variability Seasonal prediction 



This project was funded by NOAA’s High Impact Weather Prediction Project (HIWPP) under the NMME extension. Feedback from two anonymous reviewers as well as internal reviews from Drs. Emily Becker and Peitao Peng greatly improved the quality of this manuscript. Additional helpful discussions with Gerry Bell, Lindsey Long, and Michelle L’Heureux helped drive this project. We acknowledge the agencies that support the NMME-Phase II system, and we thank the climate modeling groups (listed in Table 1) for producing and making available their model output. NOAA National Centers for Environmental Prediction, NOAA Climate Test Bed and NOAA Climate Program Office jointly provide coordinating support and led development of the NMME-Phase II system. NMME hindcast data was retrieved from the NCAR Earth System Grid repository that is supported financially by DOE, NASA, NOAA, and NSF. Maintenance, support, and development of the Earth System Grid repository is provided by CPC, IRI, and NCAR personnel.


  1. Barnston AG, Tippett MK (2013) Predictions of Nino 3.4 SST in CFSv1 and CFSv2: a diagnostic comparison. Clim Dyn 41:1615–1633. doi: 10.1007/s00382-013-1845-2 CrossRefGoogle Scholar
  2. Barnston AG, Tippett MK, L’Heureux ML, Li S, Dewitt DG (2012) Skill of real-time seasonal ENSO model predictions during 2002-11: Is our capability increasing? Bull Amer Meteor Soc 93:631–651. doi: 10.1175/BAMS-D-11-00111.1 CrossRefGoogle Scholar
  3. Becker EJ, van den Dool H, Zhang Q (2014) Predictability and forecast skill in NMME. J Clim 27:5891–5906. doi: 10.1175/JCLI-D-13-00597.1 CrossRefGoogle Scholar
  4. Bell GD, Chelliah M (2006) Leading tropical modes associated with interannual and multidecadal fluctuations in North Atlantic hurricane activity. J Clim 19:590–612. doi: 10.1175/JCLI3659.1 CrossRefGoogle Scholar
  5. Choi W, Ho C-H, Kim J, Kim H-S, Feng S, Kang K (2015) A track-pattern based seasonal prediction of tropical cyclone activities over the North Atlantic. J Clim 29:481–494. doi: 10.1175/JCLI-D-15-0407.1 CrossRefGoogle Scholar
  6. Davis K, Zheng X, Ritchie EA (2015) A new statistical model for predicting seasonal North Atlantic hurricane activity. Weather Forecasting 30:730–741. doi: 10.1175/WAF-D-14-00156.1 CrossRefGoogle Scholar
  7. Dee D et al (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J Roy Meteor Soc 137:553–597. doi: 10.1002/qj.828 CrossRefGoogle Scholar
  8. DeWitt DG (2005) Retrospective forecasts of interannual sea surface temperature anomalies from 1982 to present using a directly coupled atmosphere-ocean general circulation model. Mon Weather Rev 133:2972–2995. doi: 10.1175/MWR3016.1 CrossRefGoogle Scholar
  9. Enfield DB, Mestas-Nuñez AM, Trimble PJ (2001) The Atlantic multidecadal oscillation and its relation to rainfall and river flows in the continental US. Geophys Res Lett 28:2077–2080. doi: 10.1029/2000GL012745 CrossRefGoogle Scholar
  10. Goldenberg SB, Shapiro LJ (1996) Physical mechanisms for the association of El Niño and West African rainfall with Atlantic major hurricane activity. J Clim 9:1169–1187. doi: 10.1175/1520-0442(1996)009<1169:PMFTAO>2.0.CO;2 CrossRefGoogle Scholar
  11. Goldenberg SB, Landsea CW, Mestas-Nuñez AM, Gray WM (2001) The recent increase in Atlantic hurricane activity: cause and implications. Science 293:474–479. doi: 10.1126/science.1060040 CrossRefGoogle Scholar
  12. Gray WM (1984a) Atlantic seasonal hurricane frequency. Part I: El Niño and 30-mb quasi-biennial oscillation influences. Mon Weather Rev 112:1649–1668. doi: 10.1175/1520-0492(1984)112<1649:ASHFPI>2.0.CO;2 CrossRefGoogle Scholar
  13. Gray WM (1984b) Atlantic seasonal hurricane frequency. Part II: forecasting its variability. Mon Weather Rev 112:1649–1668. doi: 10.1175/1520-0493(1984)112<1669:ASHFPI>2.0.CO;2 CrossRefGoogle Scholar
  14. Kalnay E et al (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteor Soc 77:437–471. doi: 10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2 CrossRefGoogle Scholar
  15. Kim HM, Webster PJ (2010) Extended-range seasonal hurricane forecasts for the North Atlantic with a hybrid dynamical-statistical model. Geophys Res Lett 37:L21705. doi: 10.1029/2010GL044792 Google Scholar
  16. Kim O, Kim HM, Lee MI (2017) Dynamical-statistical seasonal prediction for western North Pacific typhoons based on APCC multi-models. Clim Dynamics 48:71–88CrossRefGoogle Scholar
  17. Kirtman BP (2003) The COLA anomaly coupled model: Ensemble ENSO prediction. Mon Weather Rev 131:2324–2341. doi: 10.1175/1520-0493(2003)131<2324:TCACME>2.0.CO;2 CrossRefGoogle Scholar
  18. Kirtman BP et al (2014) The North American multimodel ensemble: phase-1 seasonal-to-interannual prediction; phase-2 toward developing intraseasonal prediction. Bull Am Meteor Soc 95:585–601. doi: 10.1175/BAMS-D-12-00050.1 CrossRefGoogle Scholar
  19. Klotzbach PJ (2014) The Madden–Julian oscillation’s impacts on worldwide tropical cyclone activity. J Clim 27:2317–2330. doi: 10.1175/JCLI-D-13-00483.1 CrossRefGoogle Scholar
  20. Klotzbach PJ, Oliver E. C. J. (2015) Modulation of Atlantic basin tropical cyclone activity by the Madden–Julian Oscillation (MJO) from 1905 to 2011. J Clim 28:204–217. doi: 10.1175/JCLI-D-14-00509.1 CrossRefGoogle Scholar
  21. Knutson TR, Sirutis JJ, Garner ST, Held IM, Tuleya RE (2007) Simulation of the recent multidecadal increase of Atlantic hurricane activity using an 18-km-grid regional model. Bull Am Meteor Soc 88:1549–1565. doi: 10.1175/BAMS-88-10-1549 CrossRefGoogle Scholar
  22. Knutson TR, McBride JL, Chan J, Emanuel K, Holland G, Landsea C, Held I, Kossin JP, Srivastava AK, Sugi M (2010) Tropical cyclones and climate change. Nat Geosci 3:157–163. doi: 10.1038/ngeo779 CrossRefGoogle Scholar
  23. Koltermann KP, Sokov AV, Terschnekov VP, Dobroliubov SA, Lorbacher K, Sy A (1999) Decadal changes in the thermohaline circulation of the North Atlantic. Deep Sea Res Part II 46:109–138. doi: 10.1016/S0967-0645(98)00115-5 CrossRefGoogle Scholar
  24. Kossin JP, Vimont DJ (2007) A more general framework for understanding Atlantic hurricane variability and trends. Bull Am Meteor Soc 88:1767–1781. doi: 10.1175/BAMS-88-11-1767 CrossRefGoogle Scholar
  25. Krishnamurti TN, Kishtawal CM, LaRow TE, Bachiochi DR, Zhang Z, Williford CE, Gadgil S, Surendran S (1999) Improved weather and seasonal climate forecasts from multimodel superensemble. Science 285:1548–1550. doi: 10.1126/science.285.5433.1548 CrossRefGoogle Scholar
  26. Landsea CW, Pielke RA Jr, Maestas-Nunez AM, Knaff JA (1999) Atlantic basin hurricanes. Clim Change 42:89–129Google Scholar
  27. Landsea CW et al (2004) The Atlantic hurricane database re-analysis project: documentation for the 1851–1910 alterations and additions to the HURDAT database. In: Murnane RJ, Liu K-B (eds) Hurricanes and typhoons: past, present and future. Columbia University Press, New York, pp 177–221Google Scholar
  28. 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. doi: 10.1002/2013JD020708 CrossRefGoogle Scholar
  29. 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. doi: 10.1038/nclimate1357 CrossRefGoogle Scholar
  30. Merryfield WJ et al (2013) The Canadian seasonal to interannual prediction system. Part I: models and initialization. Mon Weather Rev 141:2910–2945. doi: 10.1175/MWR-D-12-00216.1 CrossRefGoogle Scholar
  31. Min Y-M, Kryjov VN, Park C-K (2009) A probabilistic multimodel ensemble approach to seasonal prediction. Weather Forecasting 24:812–828. doi: 10.1175/2008WAF2222140.1 CrossRefGoogle Scholar
  32. Palmer TN, Brankovic C, Richardson DS (2000) A probability and decision-model analysis of PROVOST seasonal multimodel ensemble integrations. Q J Roy Meteor Soc 126:2013–2034. doi: 10.1002/qj.49712656703 CrossRefGoogle Scholar
  33. Patricola CM, Saravanan R, Chang P (2014) The impact of the El Niño-Southern Oscillation and Atlantic meridional mode on seasonal Atlantic tropical cyclone activity. J Clim 27:5311–5328. doi: 10.1175/JCLI-D-13-00687.1 CrossRefGoogle Scholar
  34. Peduzzi P, Chatenoux B, Dao H, De Bono A, Herold C, Kossin J, Mouton F, Nordbeck O (2012) Global trends in tropical cyclone risk. Nat Clim Change 2:289–294. doi: 10.1038/nclimate1410 CrossRefGoogle Scholar
  35. Pegion K (2015) Development of a subseasonal North American multi-model ensemble prediction system. AGU Fall Meeting, San FranciscoGoogle Scholar
  36. Pielke RAJ Jr, Gratz CW, Landsea D, Collins MA, Saunders, Musulin R (2008) Normalized hurricane damage in the United States: 1900–2005. Nat Haz Rev 9:29–42. doi: 10.1061/(ASCE)/1527-6988(2008)9:1(29) CrossRefGoogle Scholar
  37. Reynolds RW, Rayner NA, Smith TM, Stokes DC, Wang W (2002) An improved in situ and satellite SST analysis for climate. J Clim 15:1609–1625. doi: 10.1175/1520-0442(2002)015<1609:AIISAS>2.0.CO;2 CrossRefGoogle Scholar
  38. Saha S et al (2010) The NCEP climate forecast system reanalysis. Bull Am Meteor Soc 91:1015–1057. doi: 10.1175/2010BAMS3001.1 CrossRefGoogle Scholar
  39. Saha S et al (2014) The NCEP Climate Forecast System version 2. J Clim 27:2185–2208. doi: 10.1175/JCLI-D-12-00823.1 CrossRefGoogle Scholar
  40. Schemm J-KE, Long L (2014) CPC dynamic hurricane season prediction system upgrade with the NCEP CFSv2. 39th Climate Diagnostics Prediction Workshop, St. Louis, MO, National Oceanic and Atmospheric Association. ay_3/Session_7/Long.pdf
  41. Schlesinger ME, Ramankutty N (1994) An oscillation in the global climate system of period 65–70 years. Nature 367:723–726. doi: 10.1038/367723a0 CrossRefGoogle Scholar
  42. Trenberth KE, Shea DJ (2006) Atlantic hurricane and natural variability in 2005. Geophys Res Lett 33:L12704. doi: 10.1029/2006GL026894 CrossRefGoogle Scholar
  43. Unger DA, van den Dool H, O’Lenic E, Collins D (2009) Ensemble regression. Mon Weather Rev 137:2365–2379. doi: 10.1175/2008MWR2605.1 CrossRefGoogle Scholar
  44. Vecchi GA, Zhao M, Wang H, Villarini G, Rosati A, Kumar A, Held IM, Gudgel R (2011) Statistical–dynamical predictions of seasonal North Atlantic hurricane activity. Mon Weather Rev 139:1070–1082. doi: 10.1175/2010MWR3499.1 CrossRefGoogle Scholar
  45. Vernieres G, Rienecker MM, Kovach R, Keppenne CL (2012) The GEOS-iODAS: description and evaluation. Technical report series on global modeling and data assimilation 30, 73 p, NASA Goddard Space Flight Center, Greenbelt, MD, USA. NASA/TM-2012-104606/VOL30Google Scholar
  46. Villarini G, Vecchi GA (2013) Multiseason lead forecast of the North Atlantic power dissipation index (PDI) and accumulated cyclone energy (ACE). J Clim 26:3631–3643. doi: 10.1175/JCLI-D-12-00448.1 CrossRefGoogle Scholar
  47. Vimont DJ, Kossin JP (2007) The Atlantic meridional mode and hurricane activity. Geophys Res Lett 34:L07709. doi: 10.1029/2007GL029683 CrossRefGoogle Scholar
  48. Vitart F, Coauthors (2007) Dynamically-based seasonal forecasts of Atlantic tropical storm activity issued in June by EUROSIP. Geophys Res Lett 34:L16815. doi: 10.1029/2007GL030740 CrossRefGoogle Scholar
  49. Vitart F, Stockdale TN (2001) Seasonal forecasting of tropical storms using coupled GCM integrations. Mon Weather Rev 129:2521–2537. doi: 10.1175/1520-0493(2001)129<2521:SFOTSU>2.0.CO;2 CrossRefGoogle Scholar
  50. Wang H, Schemm J.-K. E., Kumar A, Wang W, Long L, Chelliah M, Bell GD, Peng P (2009a) A statistical forecast model for Atlantic seasonal hurricane activity based on the NCEP dynamical season forecast. J Clim 22:4481–4500. doi: 10.1175/2009JCLI2753.1 CrossRefGoogle Scholar
  51. Wang B et al (2009b) Advance and prospectus of seasonal prediction: assessment of the APCC/CliPAS 14-model ensemble retrospective seasonal prediction (1980–2004). Clim Dyn 33:93–117. doi: 10.1007/s00382-008-0460-0 CrossRefGoogle Scholar
  52. Wang H et al (2014) How well do global climate models simulate the variability of Atlantic tropical cyclones associated with ENSO? J Clim 27:5673–5692. doi: 10.1175/JCLI-D-13-00625.1 CrossRefGoogle Scholar
  53. Willoughby HE (2012) Distributions and trends of death and destruction from hurricanes in the United States, 1900–2008. Nat Haz Rev 13:57–64. doi: 10.1061/(ASCE)NH.1527-6996.00000046 CrossRefGoogle Scholar
  54. Zhang G, Wang Z, Dunkerton TJ, Peng MS, Magnusdottir G (2016) Extratropical impacts on Atlantic tropical cyclone activity. J Atmos Sci 73:1401–1418. doi: 10.1175/JAS-D-15-0154.1 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Daniel S. Harnos
    • 1
    Email author
  • Jae-Kyung E. Schemm
    • 1
  • Hui Wang
    • 1
  • Christina A. Finan
    • 1
    • 2
  1. 1.Climate Prediction CenterNCEP/NWS/NOAACollege ParkUSA
  2. 2.Innovim LLCGreenbeltUSA

Personalised recommendations