Abstract
Super Typhoon Mangkhut (2018) was the most high-impact typhoon in 2018 because of its long lifespan and significant intensity. The operational track forecasts in the short-to-medium range (deterministic and probabilistic forecast) showed a great uncertainty and the forecast landing points varied with different lead times. This study applied ensembles of high-resolution ECMWF forecasts to investigate the major factors and mechanisms of the bias production of the Mangkhut forecast track. The ensembles with the largest track bias were analyzed to examine the possible bias associated factors. The results suggested that environmental steering flows were the main cause for the erroneous southward track error with a variance contribution of 72%. The tropical cyclone (TC) size difference and the interaction of the TC with the subtropical high (SH) were other two key factors that contributed to the track error. Particularly, larger TCs may have led to a stronger erosion of the southern part of the SH, and thus induced significant changes in the large-scale environment and eventually resulted in an additional northward movement of TC.
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References
Aberson, S. D., and M. DeMaria, 1994: Verification of a nested barotropic hurricane track forecast model (VICBAR). Mon. Wea. Rev., 122, 2804–2815, doi: https://doi.org/10.1175/1520-0493(1994)122<2804:VOANBH>2.0.CO;2.
Bai, L. Q., Z. Y. Meng, L. Yan, et al., 2017: An integrated damage, visual, and radar analysis of the 2015 Foshan, Guangdong, EF3 tornado in China produced by the landfalling Typhoon Mujigae (2015). Bull. Amer. Meteor. Soc., 98, 2619–2640, doi: https://doi.org/10.1175/BAMS-D-16-0015.1.
Bai, L. Q., Z. Y. Meng, K. Sueki, et al., 2020: Climatology of tropical cyclone tornadoes in China from 2006 to 2018. Sci. China Earth Sci., 62, 37–51, doi: https://doi.org/10.1007/s11430-019-9391-1.
Bartholmes, J. C., J. Thielen, M. H. Ramos, et al., 2009: The European flood alert system EFAS—Part 2: Statistical skill assessment of probabilistic and deterministic operational forecasts. Hydrol. Earth Syst. Sci., 13, 141–153, doi: https://doi.org/10.5194/hess-13-141-2009.
Bassill, N. P., 2014: Accuracy of early GFS and ECMWF Sandy (2012) track forecasts: Evidence for a dependence on cumulus parameterization. Geophys. Res. Lett., 41, 3274–3281, doi: https://doi.org/10.1002/2014GL059839.
Bonavita, M., L. Raynaud, and L. Isaksen, 2011: Estimating background-error variances with the ECMWF Ensemble of Data Assimilations system: Some effects of ensemble size and day-to-day variability. Quart. J. Roy. Meteor. Soc., 137, 423–434, doi: https://doi.org/10.1002/qj.756.
Bougeault, P., Z. Toth, C. Bishop, et al., 2010: The THORPEX interactive grand global ensemble. Bull. Amer. Meteor. Soc., 91, 1059–1072, doi: https://doi.org/10.1175/2010BAMS2853.1.
Brown, D. P., J. L. Beven, J. L. Franklin, et al., 2010: Atlantic hurricane season of 2008. Mon. Wea. Rev., 138, 1975–2001, doi: https://doi.org/10.1175/2009MWR3174.1.
Carr, III L. E., and R. L. Elsberry, 2000a: Dynamical tropical cyclone track forecast errors. Part I: Tropical region error sources. Wea. Forecasting, 15, 641–661, doi: https://doi.org/10.1175/1520-0434(2000)015<0641:DTCTFE>2.0.CO;2.
Carr, III L. E., and R. L. Elsberry, 2000b: Dynamical tropical cyclone track forecast errors. Part II: Midlatitude circulation influences. Wea. Forecasting, 15, 662–681, doi: https://doi.org/10.1175/1520-0434(2000)015<0662:DTCTFE>2.0.CO;2.
Chan, J. C. L., and W. M. Gray, 1982: Tropical cyclone movement and surrounding flow relationships. Mon. Wea. Rev., 110, 1354–1374, doi: https://doi.org/10.1175/1520-0493(1982)110<1354:TCMASF>2.0.CO;2.
Chan, K. T. F., and J. C. L. Chan, 2013: Angular momentum transports and synoptic flow patterns associated with tropical cyclone size change. Mon. Wea. Rev., 141, 3985–4007, doi: https://doi.org/10.1175/MWR-D-12-00204.1.
Chen, J. H., M. S. Peng, C. A. Reynolds, et al., 2009: Interpretation of tropical cyclone forecast sensitivity from the singular vector perspective. J. Atmos. Sci., 66, 3383–3400, doi: https://doi.org/10.1175/2009JAS3063.1.
Colbert, A. J., and B. J. Soden, 2012: Climatological variations in North Atlantic tropical cyclone tracks. J. Climate, 25, 657–673, doi: https://doi.org/10.1175/JCLI-D-11-00034.1.
Dong, K. Q., and C. J. Neumann, 1986: The relationship between tropical cyclone motion and environmental geostrophic flows. Mon. Wea. Rev., 114, 115–122, doi: https://doi.org/10.1175/1520-0493(1986)114<0115:TRBTCM>2.0.CO;2.
Du, J., S. L. Mullen, and F. Sanders, 1997: Short-range ensemble forecasting of quantitative precipitation. Mon. Wea. Rev., 122, 2427–2459, doi: https://doi.org/10.1175/5220-4493(1997)125<4227:SREFOQ>2.0.CO;2.
Elsberry, R. L., Ed., 1987: A Global View of Tropical Cyclones. Office of Naval Research, Arlington, 185 pp.
Elsberry, R. L., H. C. Tsai, and M. S. Jordan, 2014: Extended-range forecasts of Atlantic tropical cyclone events during 2012 using the ECMWF 32-day ensemble predictions. Wea. Forecasting, 29, 271–288, doi: https://doi.org/10.1175/WAF-D-13-00104.1.
Elsner, J. B., K. B. Liu, and B. Kocher, 2000: Spatial variations in major U.S. hurricane activity: Statistics and a physical mechanism. J. Climate, 13, 2293–2305, doi: https://doi.org/10.1175/1520-0442(2000)013<2293:SVIMUS>2.0.CO;2.
Galarneau, T. J. Jr., and C. A. Davis, 2013: Diagnosing forecast errors in tropical cyclone motion. Mon. Wea. Rev., 141, 405–430, doi: https://doi.org/10.1175/MWR-D-12-00071.1.
George, J. E., and W. M. Gray, 1976: Tropical cyclone motion and surrounding parameter relationships. J. Appl. Meteor., 15, 1252–1264, doi: https://doi.org/10.1175/1520-0450(1976)015<1252:tcmasp>2.0.co;2.
Goerss, J. S., and R. A. Jeffries, 1994: Assimilation of synthetic tropical cyclone observations into the Navy Operational Global Atmospheric Prediction System. Wea. Forecasting, 9, 557–576, doi: https://doi.org/10.1175/1520-0434(1994)009<0557:AOSTCO>2.0.CO;2.
Hamill, T. M., G. T. Bates, J. S. Whitaker, et al., 2013: NOAA’s second-generation global medium-range ensemble reforecast dataset. Bull. Amer. Meteor. Soc., 94, 1553–1565, doi: https://doi.org/10.1175/BAMS-D-12-00014.1.
Heming, J. T., and A. M. Radford, 1998: The performance of the United Kingdom Meteorological Office Global Model in predicting the tracks of Atlantic tropical cyclones in 1995. Mon. Wea. Rev., 126, 1323–1331, doi: https://doi.org/10.1175/1520-0493(1998)126<1323:TPOTUK>2.0.CO;2.
Hewson, T. D., and H. A. Titley, 2010: Objective identification, typing and tracking of the complete life-cycles of cyclonic features at high spatial resolution. Meteor. Appl., 17, 355–381, doi: https://doi.org/10.1002/met.204.
Holland, G. J., 1983: Tropical cyclone motion: Environmental interaction plus a beta effect. J. Atmos. Sci., 40, 328–342, doi: https://doi.org/10.1175/1520-0469(1983)040<0328:TCMEIP>2.0.CO;2.
Huang, L., and Y. L. Luo, 2017: Evaluation of quantitative precipitation forecasts by TIGGE ensembles for South China during the presummer rainy season. J. Geophys. Res. Atmos., 122, 8494–8516, doi: https://doi.org/10.1002/2017JD026512.
Jung, B.-J., H.-M. Kim, F. Q. Zhang, et al., 2012: Effect of targeted dropsonde observations and best track data on the track forecasts of Typhoon Sinlaku (2008) using an ensemble Kalman filter. Tellus A, 64A, 14984, doi: https://doi.org/10.3402/tellusa.v64i0.14984.
Kehoe, R. M., M. A. Boothe, and R. L. Elsberry, 2007: Dynamical tropical cyclone 96- and 120-h track forecast errors in the western North Pacific. Wea. Forecasting, 22, 520–538, doi: https://doi.org/10.1175/WAF1002.1.
König, W., R. Sausen, and F. Sielmann, 1993: Objective identification of cyclones in GCM simulations. J. Climate, 6, 2217–2231, doi: https://doi.org/10.1175/1520-0442(1993)006<2217:OIOCIG>2.0.CO;2.
Lander, M., and G. J. Holland, 1993: On the interaction of tropical-cyclone-scale vortices. I: Observations. Quart. J. Roy. Meteor. Soc., 119, 1347–1361, doi: https://doi.org/10.1002/qj.49711951406.
Lang, S. T. K., M. Leutbecher, and S. C. Jones, 2012: Impact of perturbation methods in the ECMWF ensemble prediction system on tropical cyclone forecasts. Quart. J. Roy. Meteor. Soc., 138, 2030–2046, doi: https://doi.org/10.1002/qj.1942.
Lee, C. S., K. K. W. Cheung, W.-T. Fang, et al., 2010: Initial maintenance of tropical cyclone size in the western North Pacific. Mon. Wea. Rev., 138, 3207–3223, doi: https://doi.org/10.1175/2010MWR3023.1.
Lee, D. K., and M. S. Suh, 2000: Ten-year East Asian summer monsoon simulation using a regional climate model (RegCM2). J. Geophys. Res. Atmos., 105, 29565–29577, doi: https://doi.org/10.1029/2000JD900438.
Leung, L. R., S. J. Ghan, Z. C. Zhao, et al., 1999: Intercomparison of regional climate simulations of the 1991 summer monsoon in eastern Asia. J. Geophys. Res. Atmos., 104, 6425–6454, doi: https://doi.org/10.1029/1998jd200016.
Kossin, J. P., S. J. Camargo, and M. Sitkowski, 2010: Climate modulation of North Atlantic hurricane tracks. J. Climate, 23, 3057–3076, doi: https://doi.org/10.1175/2010JCLI3497.1.
Majumdar, S. J., S. D. Aberson, C. H. Bishop, et al., 2006: A comparison of adaptive observing guidance for Atlantic tropical cyclones. Mon. Wea. Rev., 134, 2354–2372, doi: https://doi.org/10.1175/MWR3193.1.
Magnusson, L., J. R. Bidlot, S. T. K. Lang, et al., 2014: Evaluation of medium-range forecasts for Hurricane Sandy. Mon. Wea. Rev., 142, 1962–1981, doi: https://doi.org/10.1175/MWR-D-13-00228.1.
McTaggart-Cowan, R., L. F. Bosart, J. R. Gyakum, et al., 2006: Hurricane Juan (2003). Part II: Forecasting and numerical simulation. Mon. Wea. Rev., 134, 1748–1771, doi: https://doi.org/10.1175/MWR3143.1.
Meehl, G. A., J. M. Arblaster, C. M. Bitz, et al., 2016: Antarctic sea-ice expansion between 2000 and 2014 driven by tropical Pacific decadal climate variability. Nat. Geosci., 9, 590–595, doi: https://doi.org/10.1038/ngeo2751.
Melhauser, C., F. Q. Zhang, Y. H. Weng, et al., 2017: A multiple-model convection-permitting ensemble examination of the probabilistic prediction of tropical cyclones: Hurricanes Sandy (2012) and Edouard (2014). Wea. Forecasting, 32, 665–688, doi: https://doi.org/10.1175/WAF-D-16-0082.1.
Munsell, E. B., and F. Q. Zhang, 2014: Prediction and uncertainty of Hurricane Sandy (2012) explored through a real-time cloud-permitting ensemble analysis and forecast system assimilating airborne Doppler radar observations. J. Adv. Model. Earth Syst., 6, 38–58, doi: https://doi.org/10.1002/2013ms000297.
Peng, M. S., and C. A. Reynolds, 2006: Sensitivity of tropical cyclone forecasts as revealed by singular vectors. J. Atmos. Sci., 63, 2508–2528, doi: https://doi.org/10.1175/JAS3777.1.
Peng, X. D., J. F. Fei, X. G. Huang, et al., 2017: Evaluation and error analysis of official forecasts of tropical cyclones during 2005–14 over the western North Pacific. Part I: Storm tracks. Wea. Forecasting, 32, 689–712, doi: https://doi.org/10.1175/WAF-D-16-0043.1.
Qian, C. H., F. Q. Zhang, B. W. Green, et al., 2013: Probabilistic evaluation of the dynamics and prediction of Supertyphoon Megi (2010). Wea. Forecasting, 28, 1562–1577, doi: https://doi.org/10.1175/WAF-D-12-00121.1.
Rappaport, E. N., J. L. Franklin, L. A. Avila, et al., 2009: Advances and challenges at the National Hurricane Center. Wea. Forecasting, 24, 395–419, doi: https://doi.org/10.1175/2008WAF2222128.1.
Ren, S. L., Y. M. Liu, and G. X. Wu, 2007: Interactions between typhoon and subtropical anticyclone over western Pacific revealed by numerical experiments. Acta Meteor. Sinica, 65, 329–340, doi: https://doi.org/10.3321/j.issn:0577-6619.2007.03.003. (in Chinese)
Richardson, D., R. Buizza, and R. Hagedorn, 2005: First Workshop on the THORPEX Interactive Grand Global Ensemble (TIGGE): Final Report. World Meteorological Organization Rep. WMO/TD-No. 1273, 39 pp.
Ritchie, E. A., and G. J. Holland, 1997: Scale interactions during the formation of Typhoon Irving. Mon. Wea. Rev., 125, 1377–1396, doi: https://doi.org/10.1175/1520-0493(1997)125<1377:SIDTFO>2.0.CO;2.
Sanders, F., A. L. Adams, N. J. B. Gordon, et al., 1980: Further development of a barotropic operational model for predicting paths of tropical storms. Mon. Wea. Rev., 108, 642–654, doi: https://doi.org/10.1175/1520-0493(1980)108<0642:FDOABO>2.0.CO;2.
Sheets, R. C., 1990: The National Hurricane Center—Past, present, and future. Wea. Forecasting, 5, 185–232, doi: https://doi.org/10.1175/1520-0434(1990)005<0185:TNHCPA>2.0.CO;2.
Simpson, J., E. Ritchie, G. J. Holland, et al., 1997: Mesoscale interactions in tropical cyclone genesis. Mon. Wea. Rev., 125, 2643–2661, doi: https://doi.org/10.1175/1520-0493(1997)125<2643:MIITCG>2.0.CO;2.
Speer, M. S., and L. M. Leslie, 1997: An example of the utility of ensemble rainfall forecasting. Austr. Meteor. Mag., 46, 75–78.
Sun, Y., Z. Zhong, W. Lu, et al., 2014: Why are tropical cyclone tracks over the western North Pacific sensitive to the cumulus parameterization scheme in regional climate modeling? A case study for Megi (2010). Mon. Wea. Rev., 142, 1240–1249, doi: https://doi.org/10.1175/MWR-D-13-00232.1.
Sun, Y., Z. Zhong, and W. Lu, 2015: Sensitivity of tropical cyclone feedback on the intensity of the western Pacific subtropical high to microphysics schemes. J. Atmos. Sci., 72, 1346–1368, doi: https://doi.org/10.1175/JAS-D-14-0051.1.
Torn, R. D., J. S. Whitaker, P. Pegion, et al., 2015: Diagnosis of the source of GFS medium-range track errors in Hurricane Sandy (2012). Mon. Wea. Rev., 143, 132–152, doi: https://doi.org/10.1175/MWR-D-14-00086.1.
Tracton, M. S., and E. Kalnay, 1993: Operational ensemble prediction at the National Meteorological Center: Practical aspects. Wea. Forecasting, 8, 379–398, doi: https://doi.org/10.1175/1520-0434(1993)008<0379:OEPATN>2.0.CO;2.
Velden, C. S., and L. M. Leslie, 1991: The basic relationship between tropical cyclone intensity and the depth of the environmental steering layer in the Australian region. Wea. Forecasting, 6, 244–253, doi: 1520-0434(1991)006<0244:TBRBTC>2.0.CO;2.
Wang, Y. Q., and G. J. Holland, 1996: Tropical cyclone motion and evolution in vertical shear. J. Atmos. Sci., 53, 3313–3332, doi: https://doi.org/10.1175/1520-0469(1996)053<3313:TCMAEI>2.0.CO;2.
Wang, Y. Q., and H. Wang, 2013: The inner-core size increase of Typhoon Megi (2010) during its rapid intensification phase. Trop. Cycl. Res. Rev., 2, 65–80, doi: https://doi.org/10.6057/2013TCRR02.01.
Williford, C. E., R. J. Correra-Torres, and T. N. Krishnamurti, 1998: Tropical cyclone forecasts made with the FSU Global Spectral Model. Mon. Wea. Rev., 126, 1332–1336, doi: https://doi.org/10.1175/1520-0493(1998)126<1332:TCFMWT>2.0.CO;2.
Wu, C.-C., and K. A. Emanuel, 1993: Interaction of a baroclinic vortex with background shear: Application to hurricane movement. J. Atmos. Sci., 50, 62–76, doi: https://doi.org/10.1175/1520-0469(1993)050<0062:IOABVW>2.0.CO;2.
Wu, C.-C., J.-H. Chen, P.-H. Lin, et al., 2007: Targeted observations of tropical cyclone movement based on the adjoint-derived sensitivity steering vector. J. Atmos. Sci., 64, 2611–2626, doi: https://doi.org/10.1175/JAS3974.1.
Wu, C.-C., J. H. Chen, S. J. Majumdar, et al., 2009: Intercomparison of targeted observation guidance for tropical cyclones in the northwestern Pacific. Mon. Wea. Rev., 137, 2471–2492, doi: https://doi.org/10.1175/2009MWR2762.1.
Wu, L. G., W. Tian, Q. Y. Liu, et al., 2015: Implications of the observed relationship between tropical cyclone size and intensity over the western North Pacific. J. Climate, 22, 9501–9506, doi: https://doi.org/10.1175/JCLI-D-15-0628.1.
Yamaguchi, M., and S. J. Majumdar, 2010: Using TIGGE data to diagnose initial perturbations and their growth for tropical cyclone ensemble forecasts. Mon. Wea. Rev., 138, 3634–3655, doi: https://doi.org/10.1175/2010MWR3176.1.
Ying, M., W. Zhang, H. Yu, et al., 2014: An overview of the China Meteorological Administration tropical cyclone database. J. Atmos. Oceanic Technol., 31, 287–301, doi: https://doi.org/10.1175/JTECH-D-12-00119.1.
Zhang, G. J., 1994: Effects of cumulus convection on the simulated monsoon circulation in a general circulation model. Mon. Wea. Rev., 122, 2022–2038, doi: https://doi.org/10.1175/1520-0493(1994)122<2022:EOCCOT>2.0.CO;2.
Zhong, Z., and Y. J. Hu, 2007: Impacts of tropical cyclones on the regional climate: An East Asian summer monsoon case. Atmos. Sci. Lett., 8, 93–99, doi: https://doi.org/10.1002/asl.158.
Zhu, Y. J., 2005: Ensemble forecast: A new approach to uncertainty and predictability. Adv. Atmos. Sci., 22, 781–788, doi: https://doi.org/10.1007/BF02918678.
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Supported by the Research and Development Projects in Key Areas of Guangdong Province (2019B111101002) and National Natural Science Foundation of China (41805035, 41675021, 41675019, and 41875021).
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The TIGGE data were downloaded from http://apps.ecmwf.int/datasets. The observed data can be achieved by contacting the corresponding author. Additional gratitude is extended to the three anonymous reviewers who have greatly aided in the improvement of this paper.
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Huang, L., Wan, Q., Liu, C. et al. Ensemble Based Diagnosis of the Track Errors of Super Typhoon Mangkhut (2018). J Meteorol Res 34, 353–367 (2020). https://doi.org/10.1007/s13351-020-9086-x
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DOI: https://doi.org/10.1007/s13351-020-9086-x