System for numerical forecast of intensity and trajectory of tropical cyclones in the North Atlantic basin
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Abstract
A system for the numerical forecast of tropical cyclones (TCs) named Numerical Tools for Hurricane Forecast (NTHF), that uses movable computing meshes, was implemented in a small computing cluster. The simulations are initialized with the forecast outputs of the Global Forecast System at 0000 UTC and the storm position provided by the National Hurricane Center (NHC) and are extended up to a period of 5 days. For the evaluation of the system, tropical cyclones formed in the North Atlantic basin in the seasons from 2016 to 2018 were used. The mean error in the NTHF trajectory forecast ranged between 56 km for 12 hours and 356 km for 120 hours; however, NTHF does not perform as well as NHC official forecast. Nevertheless, the system showed good ability to predict the track of intense hurricanes. Besides, it is useful for the forecast of the intensity of tropical cyclones from depression to category 3 hurricanes on the Saffir-Simpson scale between 36 and 120 hours, while for intense hurricanes (category 4 and 5) the lowest errors are between 72 and 108 forecast hours, with an error in the maximum wind speed close to 25 kmh-1. Moreover, NTHF is adaptable to low computational resources and will allow the development of studies to deepen the knowledge of the physical and dynamic mechanisms that control the intensification or weakening of TCs.
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Pérez-AlarcónA., Fernández-AlvarezJ. C., Díaz-RodríguezO., Batista-LeyvaA. J., & Pérez-SuárezR. (1). System for numerical forecast of intensity and trajectory of tropical cyclones in the North Atlantic basin. Revista Cubana De Meteorología, 27(1). Retrieved from http://rcm.insmet.cu/index.php/rcm/article/view/552
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References
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Aligo, E; Ferrier, B.; Thompson, G; Carley, J. R; Rogers, E and Dimego, J. (2017) The New-Ferrier-Aligo Microphysics in the NCEP 3-km NAM nest. In: Proceedings of the 97th AMS Annual Meeting, 21-26 January, Seattle, WA.
Bao, J.-W.; Gopalakrishnan, S. G.; Michelson, S.; Marks, F. and Montgomery, M. (2012) Impact of physics representations in the HWRFX on simulated hurricane structure and pressure-wind relationships. Monthly Weather Review, 140(10): 3278–3299. DOI:10.1175/MWR-D-11-00332.1
Bender, M. A. and Ginis, I. (2000). Real case simulation of hurricane-ocean interaction using a high-resolution coupled model: Effects on hurricane intensity. Monthly Weather Review, 128: 917–946. DOI: 10.1175/1520-0493(2000)128<0917:RCSOHO>2.0.CO;2
Bender, M. A.; Ginis, I.; Tuleya, R.; Thomas, B. and Marchok, T. (2007). The operational GFDL Coupled Hurricane-Ocean Prediction System and a summary of its performance. Monthly Weather Review, 135: 3965-3989. DOI: 10.1175/2007MWR2032.1
Biswas, M. K.; Carson, L.; Newman, K.; Bernardet, L.; Kalina,E.; Grell, E. and Frimel, J. (2017) Community HWRF Users’ Guide v3.9a,160 pp.
Bozeman, M. L. (2011) Land surface feedbacks on the post-landfall tropical cyclone characteristics using the Hurricane Weather Research and Forecasting (HWRF) modeling system, Master Degree Thesis, Pursue University, West Lafayette,
Cangialosi, P. J. (2019) National Hurricane Center Forecast Verification Report. 2018 Hurricane Season. National Hurricane Center, https://www.nhc.noaa.Gov/verification/pdfs/Verification_2018.pdf, retrieved June 14, 2019.
Chen, F. and Dudhia, J. (2001) Coupling an advanced land surface–hydrology model with the Penn State–NCAR MM5 modeling system. Part I: Model description and implementation. Monthly Weather Review, 129: 569 –585. DOI: 10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2
Chen, H. and Gopalakrishnan, S. G. (2015) A study on the asymmetric rapid intensification of HurricaneEarl (2010) using the HWRF system. Journal of the Atmospheric Sciences, 72(2): 531–550. DOI: 10.1175/JAS-D-14-0097.1
Cione, J. J. and Uhlhorn, E. W. (2003) Sea surface temperature variability in hurricanes: Implications with respect to intensity change. Monthly Weather Review, 131: 1783–1796. DOI: 10.1175//2562.1
DeMaria, M.; Knaff, J. A. and Kaplan, J. (2006) On the decay of tropical cyclone winds crossing narrow landmasses. Journal of Applied Meteorology, 45: 491–499. DOI: 10.1175/JAM2351.1
Ferrier, B. S.; Jin, Y.; Lin, Y.; Black, T.; Rogers, E. and DiMego, G. (2002) Implementation of a new grid-scale cloud and precipitation scheme in the NCEP ETA model. In: Proceedings of the 19th Conference on weather analysis and forecasting/15th conference on numerical weather prediction. American Meteorological Society.
Gall, R.; Franklin, J.; Marks, F. D.; Rappaport, E. E. and Toepfer, F. (2013) The Hurricane Forecast Improvement Project. Bulletin of the American Meteorological Society, 94: 329–343. DOI: 10.1175/BAMS-D-12-00071.1
Goerss, J. S. (2006) Prediction of tropical cyclone track forecast error for Hurricanes Katrina, Rita,and Wilma. In: Proceedings of the 27th Conference on Hurricanes and Tropical Meteorology, Monterey, CA, USA, 8: 2447–2469.
Gopalakrishnan, S. G.; Goldenberg, S.; Quirino, T.; Zhang, X.; Marks, F.; Yeh, K.-S.; Atlas, R. and Tallapragada, V. (2012) Toward improving high-resolution numerical hurricane forecasting:Influence of model horizontal grid resolution, initialization, and physics. Weather and Forecasting, 27(3): 647–666. DOI: 10.1175/WAF-D-11-00055.1
Gopalakrishnan, S. G.; Marks, F.; Zhang, J. A.; Zhang, X.; Bao, J.-W. and Tallapragada, V. (2013) A study of the impacts of vertical diffusion on the structure and intensity of the tropical cyclones using the high-resolution HWRF system. Journal of the Atmospheric Sciences, 70(2): 524–541. DOI: 10.1175/JAS-D-11-0340.1
Gopalakrishnan, S. G.; Marks, F.; Zhang, X.; Baoand, J.-W.; Yeh, K.-S. and Atlas R. (2011) The experimental HWRF system: A study on the influence of horizontal resolution on the structure and intensity changes in tropical cyclones using an idealized framework. Monthly Weather Review, 139: 1762–1784. DOI: 10.1175/2010MWR3535.1
Han, J.; Wang, W; Kwon, Y.; Hong, S.; Tallapragada, V. and Yang, F. (2017) Updates in the NCEP GFS Cumulus Convection Schemes with Scale and Aerosol Awareness. Weather and Forecasting, 32(5): 1989-2004. DOI: 10.1175/WAF-D-17-0046.1
Holt, Ch.; Bernardet, L.; Brown, T. and Yablonsky, R. (2014) Community HWRF Users’ Guide V3.6a. NOAA-ESRL-GSD, Developmental Testbed Center and CIRES-CU
Hu, Y. X. and Stamnes, K. (1993) An accurate parameterization of the radiative properties of water clouds suitable for use in climate models. Journal of Climate, 6: 728–742. DOI: 10.1175/1520-0442(1993)006<0728:AAPOTR>2.0.CO;2
Iacono, M. J.; Delamere, J. S.; Mlawer, E. J.; Shephard, M. W.; Clough, S. A. and Collins, W. D. (2008) Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. Journal of Geophysical Research,133, D13103. DOI: 10.1029/2008JD009944
Kurihara, Y. and Tuleya, R. E. (1974) Structure of a tropical cyclone developed in a three dimensional numerical simulation model. Journal of the Atmospheric Sciences, 31: 893–919. DOI: 10.1175/1520-0469(1974)031<0893:SOATCD>2.0.CO;2
Landsea, C. W. and Franklin, J. L. (2013) Atlantic Hurricane Database Uncertainty and Presentation of a New Database Format. Monthly Weather Review, 141: 3576–3592. DOI: 10.1175/MWR-D-12-00254.1
Marks, F. D. and Shay, L.K. (1998) Landfalling tropical cyclones: Forecast problems and associated research opportunities. Bulletin of the American Meteorological Society, 79: 305–323.
Mesinger, F. (1977) Forward-backward scheme, and its use in a limited area model. Contributions to Atmospheric Physics, 50: 200–210.
May, R.; Arms, S.; Marsh, P.; Bruning, E. and Leeman, J. (2020). Metpy: A Python package for meteorological data. https://doi.org/10.5065/D6WW7G29. (last accessed May 2020)
Misirli, E. and Gurefe, Y. (2011) Multiplicative Adams Bashforth–Moulton methods. Numerical Algorithms, 57: 425–439. DOI: 10.1007/s11075-010-9437-2
Mitrani, A. I.; Pérez, B. A.; Vichot, L. A.; Alonso, D. Y.; González, M. Y. and Díaz, R. O. (2017) Numerical forecast of weather and wind waves, using WRF and WW3, on the Cuban territory and surrounding waters, and comparison with MM5+WW3. Ciencias de la Tierra y el Espacio, 18 (2): 86 – 100.
Mitrani, A. I.; Pérez, B.A.; Cabrales, I. J.; Pérez, P. Y.; Hernández, G. M. and Díaz, R. O. (2019) Coastal flood forecast in Cuba, due to hurricanes, using a combination of numerical models. Revista Cubana de Meteorología, 25(2): 121–138.
Pérez-Alarcón, A. and Fernández-Alvarez, J. C, (2020). Alarconpy: A Python Package for Meteorologists. https://github.com/apalarcon/alarconpy. (last accessed June 2020).
Pérez, B. A.; Díaz, O. O. and Mitrani, I. (2013) Sistema de pronóstico numérico océano–atmósfera para la República de Cuba. In VII Congreso Cubano de Meteorología. Boletín de SOMETCUBA.
Pérez-Bello, A., Mitrani, A. I., Díaz, R. O., Wettre, C., and Robert, L. H. (2019). A numerical prediction system combining ocean, waves and atmosphere models in the Inter-American Seas and Cuba. Revista Cubana de Meteorología, 25 (1): 109–120.
Rogers, E.; Black, T.; Ferrier, B.; Lin, Y.; Parrish, D. and DiMego, G. (2001) Changes to the NCEP meso ETA analysis and forecast system: Increase in resolution, new cloud microphysics, modified precipitation assimilation, modified 3DVAR analysis. NWS Technical Procedures Bulletin 488, NOAA/NWS. https://www.emc.ncep.noaa.gov/mmb/mmpbll/eta12tpb/, retrieved: August 13, 2019.
Sierra, L.M.; Ferrer, H.A.L.; Valdes, R.; Mayor, G.Y.; Cruz, R.C.; Borrajero, I.; Rodrıguez, C.F.; Rodríguez, N. and Roque, A. (2015) Sistema automático de predicción a mesoescala de cuatro ciclos diarios. Informe de Resultado. Instituto de Meteorología. La Habana, Cuba, 65. doi: 10.13140/RG.2.1.2888.1127.
Sirutis, J. J. and Miyakoda, K. (1990) Subgrid scale physics in 1-month forecasts. Part I: Experiment with four parameterization packages. Monthly Weather Review, 118: 1043–1064. DOI: 10.1175/1520-0493(1990)118,1043:SSPIMF.2.0.CO;2.
Smagorinsky, J. (1963) General circulation experiments with the primitive equations. Monthly Weather Review, 91: 99–164. DOI: 10.1175/1520-0493(1963)091<0099:GCEWTP>2.3.CO;2
Tallapragada, V.; Bernardet, L.; Biswas, M. K.; Gopalakrishnan, S.; Kwon, Y.; Liu, Q.; Marchok, T.; Sheinin, D.; Tong, M.; Trahan, S.; Tuleya, R.; Yablonsky, R. and Zhang, X. (2014) Hurricane Weather Research and Forecasting (HWRF) Model: Scientific Documentation, 55–56.
Tamsir, M. and Kumar, V. S. (2011) A semi-implicit finite-difference approach for two-dimensional coupled Burges’equations. International Journal of Scientific and Engineering Research, 2(6): 2229-5518.
Zhang, J. A. and Marks, F. D. (2015) Effects of Horizontal Diffusion on Tropical Cyclone Intensity Change and Structure in Idealized Three-Dimensional Numerical Simulations. Monthly Weather Review, 143(10): 3981 – 3995. DOI: 10.1175/MWR-D-14-00341.1
Aligo, E; Ferrier, B.; Thompson, G; Carley, J. R; Rogers, E and Dimego, J. (2017) The New-Ferrier-Aligo Microphysics in the NCEP 3-km NAM nest. In: Proceedings of the 97th AMS Annual Meeting, 21-26 January, Seattle, WA.
Bao, J.-W.; Gopalakrishnan, S. G.; Michelson, S.; Marks, F. and Montgomery, M. (2012) Impact of physics representations in the HWRFX on simulated hurricane structure and pressure-wind relationships. Monthly Weather Review, 140(10): 3278–3299. DOI:10.1175/MWR-D-11-00332.1
Bender, M. A. and Ginis, I. (2000). Real case simulation of hurricane-ocean interaction using a high-resolution coupled model: Effects on hurricane intensity. Monthly Weather Review, 128: 917–946. DOI: 10.1175/1520-0493(2000)128<0917:RCSOHO>2.0.CO;2
Bender, M. A.; Ginis, I.; Tuleya, R.; Thomas, B. and Marchok, T. (2007). The operational GFDL Coupled Hurricane-Ocean Prediction System and a summary of its performance. Monthly Weather Review, 135: 3965-3989. DOI: 10.1175/2007MWR2032.1
Biswas, M. K.; Carson, L.; Newman, K.; Bernardet, L.; Kalina,E.; Grell, E. and Frimel, J. (2017) Community HWRF Users’ Guide v3.9a,160 pp.
Bozeman, M. L. (2011) Land surface feedbacks on the post-landfall tropical cyclone characteristics using the Hurricane Weather Research and Forecasting (HWRF) modeling system, Master Degree Thesis, Pursue University, West Lafayette,
Cangialosi, P. J. (2019) National Hurricane Center Forecast Verification Report. 2018 Hurricane Season. National Hurricane Center, https://www.nhc.noaa.Gov/verification/pdfs/Verification_2018.pdf, retrieved June 14, 2019.
Chen, F. and Dudhia, J. (2001) Coupling an advanced land surface–hydrology model with the Penn State–NCAR MM5 modeling system. Part I: Model description and implementation. Monthly Weather Review, 129: 569 –585. DOI: 10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2
Chen, H. and Gopalakrishnan, S. G. (2015) A study on the asymmetric rapid intensification of HurricaneEarl (2010) using the HWRF system. Journal of the Atmospheric Sciences, 72(2): 531–550. DOI: 10.1175/JAS-D-14-0097.1
Cione, J. J. and Uhlhorn, E. W. (2003) Sea surface temperature variability in hurricanes: Implications with respect to intensity change. Monthly Weather Review, 131: 1783–1796. DOI: 10.1175//2562.1
DeMaria, M.; Knaff, J. A. and Kaplan, J. (2006) On the decay of tropical cyclone winds crossing narrow landmasses. Journal of Applied Meteorology, 45: 491–499. DOI: 10.1175/JAM2351.1
Ferrier, B. S.; Jin, Y.; Lin, Y.; Black, T.; Rogers, E. and DiMego, G. (2002) Implementation of a new grid-scale cloud and precipitation scheme in the NCEP ETA model. In: Proceedings of the 19th Conference on weather analysis and forecasting/15th conference on numerical weather prediction. American Meteorological Society.
Gall, R.; Franklin, J.; Marks, F. D.; Rappaport, E. E. and Toepfer, F. (2013) The Hurricane Forecast Improvement Project. Bulletin of the American Meteorological Society, 94: 329–343. DOI: 10.1175/BAMS-D-12-00071.1
Goerss, J. S. (2006) Prediction of tropical cyclone track forecast error for Hurricanes Katrina, Rita,and Wilma. In: Proceedings of the 27th Conference on Hurricanes and Tropical Meteorology, Monterey, CA, USA, 8: 2447–2469.
Gopalakrishnan, S. G.; Goldenberg, S.; Quirino, T.; Zhang, X.; Marks, F.; Yeh, K.-S.; Atlas, R. and Tallapragada, V. (2012) Toward improving high-resolution numerical hurricane forecasting:Influence of model horizontal grid resolution, initialization, and physics. Weather and Forecasting, 27(3): 647–666. DOI: 10.1175/WAF-D-11-00055.1
Gopalakrishnan, S. G.; Marks, F.; Zhang, J. A.; Zhang, X.; Bao, J.-W. and Tallapragada, V. (2013) A study of the impacts of vertical diffusion on the structure and intensity of the tropical cyclones using the high-resolution HWRF system. Journal of the Atmospheric Sciences, 70(2): 524–541. DOI: 10.1175/JAS-D-11-0340.1
Gopalakrishnan, S. G.; Marks, F.; Zhang, X.; Baoand, J.-W.; Yeh, K.-S. and Atlas R. (2011) The experimental HWRF system: A study on the influence of horizontal resolution on the structure and intensity changes in tropical cyclones using an idealized framework. Monthly Weather Review, 139: 1762–1784. DOI: 10.1175/2010MWR3535.1
Han, J.; Wang, W; Kwon, Y.; Hong, S.; Tallapragada, V. and Yang, F. (2017) Updates in the NCEP GFS Cumulus Convection Schemes with Scale and Aerosol Awareness. Weather and Forecasting, 32(5): 1989-2004. DOI: 10.1175/WAF-D-17-0046.1
Holt, Ch.; Bernardet, L.; Brown, T. and Yablonsky, R. (2014) Community HWRF Users’ Guide V3.6a. NOAA-ESRL-GSD, Developmental Testbed Center and CIRES-CU
Hu, Y. X. and Stamnes, K. (1993) An accurate parameterization of the radiative properties of water clouds suitable for use in climate models. Journal of Climate, 6: 728–742. DOI: 10.1175/1520-0442(1993)006<0728:AAPOTR>2.0.CO;2
Iacono, M. J.; Delamere, J. S.; Mlawer, E. J.; Shephard, M. W.; Clough, S. A. and Collins, W. D. (2008) Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. Journal of Geophysical Research,133, D13103. DOI: 10.1029/2008JD009944
Kurihara, Y. and Tuleya, R. E. (1974) Structure of a tropical cyclone developed in a three dimensional numerical simulation model. Journal of the Atmospheric Sciences, 31: 893–919. DOI: 10.1175/1520-0469(1974)031<0893:SOATCD>2.0.CO;2
Landsea, C. W. and Franklin, J. L. (2013) Atlantic Hurricane Database Uncertainty and Presentation of a New Database Format. Monthly Weather Review, 141: 3576–3592. DOI: 10.1175/MWR-D-12-00254.1
Marks, F. D. and Shay, L.K. (1998) Landfalling tropical cyclones: Forecast problems and associated research opportunities. Bulletin of the American Meteorological Society, 79: 305–323.
Mesinger, F. (1977) Forward-backward scheme, and its use in a limited area model. Contributions to Atmospheric Physics, 50: 200–210.
May, R.; Arms, S.; Marsh, P.; Bruning, E. and Leeman, J. (2020). Metpy: A Python package for meteorological data. https://doi.org/10.5065/D6WW7G29. (last accessed May 2020)
Misirli, E. and Gurefe, Y. (2011) Multiplicative Adams Bashforth–Moulton methods. Numerical Algorithms, 57: 425–439. DOI: 10.1007/s11075-010-9437-2
Mitrani, A. I.; Pérez, B. A.; Vichot, L. A.; Alonso, D. Y.; González, M. Y. and Díaz, R. O. (2017) Numerical forecast of weather and wind waves, using WRF and WW3, on the Cuban territory and surrounding waters, and comparison with MM5+WW3. Ciencias de la Tierra y el Espacio, 18 (2): 86 – 100.
Mitrani, A. I.; Pérez, B.A.; Cabrales, I. J.; Pérez, P. Y.; Hernández, G. M. and Díaz, R. O. (2019) Coastal flood forecast in Cuba, due to hurricanes, using a combination of numerical models. Revista Cubana de Meteorología, 25(2): 121–138.
Pérez-Alarcón, A. and Fernández-Alvarez, J. C, (2020). Alarconpy: A Python Package for Meteorologists. https://github.com/apalarcon/alarconpy. (last accessed June 2020).
Pérez, B. A.; Díaz, O. O. and Mitrani, I. (2013) Sistema de pronóstico numérico océano–atmósfera para la República de Cuba. In VII Congreso Cubano de Meteorología. Boletín de SOMETCUBA.
Pérez-Bello, A., Mitrani, A. I., Díaz, R. O., Wettre, C., and Robert, L. H. (2019). A numerical prediction system combining ocean, waves and atmosphere models in the Inter-American Seas and Cuba. Revista Cubana de Meteorología, 25 (1): 109–120.
Rogers, E.; Black, T.; Ferrier, B.; Lin, Y.; Parrish, D. and DiMego, G. (2001) Changes to the NCEP meso ETA analysis and forecast system: Increase in resolution, new cloud microphysics, modified precipitation assimilation, modified 3DVAR analysis. NWS Technical Procedures Bulletin 488, NOAA/NWS. https://www.emc.ncep.noaa.gov/mmb/mmpbll/eta12tpb/, retrieved: August 13, 2019.
Sierra, L.M.; Ferrer, H.A.L.; Valdes, R.; Mayor, G.Y.; Cruz, R.C.; Borrajero, I.; Rodrıguez, C.F.; Rodríguez, N. and Roque, A. (2015) Sistema automático de predicción a mesoescala de cuatro ciclos diarios. Informe de Resultado. Instituto de Meteorología. La Habana, Cuba, 65. doi: 10.13140/RG.2.1.2888.1127.
Sirutis, J. J. and Miyakoda, K. (1990) Subgrid scale physics in 1-month forecasts. Part I: Experiment with four parameterization packages. Monthly Weather Review, 118: 1043–1064. DOI: 10.1175/1520-0493(1990)118,1043:SSPIMF.2.0.CO;2.
Smagorinsky, J. (1963) General circulation experiments with the primitive equations. Monthly Weather Review, 91: 99–164. DOI: 10.1175/1520-0493(1963)091<0099:GCEWTP>2.3.CO;2
Tallapragada, V.; Bernardet, L.; Biswas, M. K.; Gopalakrishnan, S.; Kwon, Y.; Liu, Q.; Marchok, T.; Sheinin, D.; Tong, M.; Trahan, S.; Tuleya, R.; Yablonsky, R. and Zhang, X. (2014) Hurricane Weather Research and Forecasting (HWRF) Model: Scientific Documentation, 55–56.
Tamsir, M. and Kumar, V. S. (2011) A semi-implicit finite-difference approach for two-dimensional coupled Burges’equations. International Journal of Scientific and Engineering Research, 2(6): 2229-5518.
Zhang, J. A. and Marks, F. D. (2015) Effects of Horizontal Diffusion on Tropical Cyclone Intensity Change and Structure in Idealized Three-Dimensional Numerical Simulations. Monthly Weather Review, 143(10): 3981 – 3995. DOI: 10.1175/MWR-D-14-00341.1