Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Track Dependence of Tropical Cyclone Intensity Forecast Errors in the COAMPS-TC Model

Track Dependence of Tropical Cyclone Intensity Forecast Errors in the COAMPS-TC Model AbstractThis study examines the dependence of tropical cyclone (TC) intensity forecast errors on track forecast errors in the Coupled Ocean–Atmosphere Mesoscale Prediction System for Tropical Cyclones (COAMPS-TC) model. Using real-time forecasts and retrospective experiments during 2015–18, verification of TC intensity errors conditioned on different 5-day track error thresholds shows that reducing the 5-day track errors by 50%–70% can help reduce the absolute intensity errors by 18%–20% in the 2018 version of the COAMPS-TC model. Such impacts of track errors on the TC intensity errors are most persistent at 4–5-day lead times in all three major ocean basins, indicating a significant control of global models on the forecast skill of the COAMPS-TC model. It is of interest to find, however, that lowering the 5-day track errors below 80 n mi (1 n mi = 1.852 km) does not reduce TC absolute intensity errors further. Instead, the 4–5-day intensity errors appear to be saturated at around 10–12 kt (1 kt ≈ 0.51 m s−1) for cases with small track errors, thus suggesting the existence of some inherent intensity errors in regional models. Additional idealized simulations under a perfect model scenario reveal that the COAMPS-TC model possesses an intrinsic intensity variation at the TC mature stage in the range of 4–5 kt, regardless of the large-scale environment. Such intrinsic intensity variability in the COAMPS-TC model highlights the importance of potential chaotic TC dynamics, rather than model deficiencies, in determining TC intensity errors at 4–5-day lead times. These results suggest a fundamental limit in the improvement of TC intensity forecasts by numerical models that one should consider in future model development and evaluation. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Weather and Forecasting American Meteorological Society

Track Dependence of Tropical Cyclone Intensity Forecast Errors in the COAMPS-TC Model

Download PDF
17 pages

Loading next page...
 
/lp/american-meteorological-society/track-dependence-of-tropical-cyclone-intensity-forecast-errors-in-the-nckc73PizI

References

References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.

Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0434
eISSN
1520-0434
DOI
10.1175/WAF-D-20-0085.1
Publisher site
See Article on Publisher Site

Abstract

AbstractThis study examines the dependence of tropical cyclone (TC) intensity forecast errors on track forecast errors in the Coupled Ocean–Atmosphere Mesoscale Prediction System for Tropical Cyclones (COAMPS-TC) model. Using real-time forecasts and retrospective experiments during 2015–18, verification of TC intensity errors conditioned on different 5-day track error thresholds shows that reducing the 5-day track errors by 50%–70% can help reduce the absolute intensity errors by 18%–20% in the 2018 version of the COAMPS-TC model. Such impacts of track errors on the TC intensity errors are most persistent at 4–5-day lead times in all three major ocean basins, indicating a significant control of global models on the forecast skill of the COAMPS-TC model. It is of interest to find, however, that lowering the 5-day track errors below 80 n mi (1 n mi = 1.852 km) does not reduce TC absolute intensity errors further. Instead, the 4–5-day intensity errors appear to be saturated at around 10–12 kt (1 kt ≈ 0.51 m s−1) for cases with small track errors, thus suggesting the existence of some inherent intensity errors in regional models. Additional idealized simulations under a perfect model scenario reveal that the COAMPS-TC model possesses an intrinsic intensity variation at the TC mature stage in the range of 4–5 kt, regardless of the large-scale environment. Such intrinsic intensity variability in the COAMPS-TC model highlights the importance of potential chaotic TC dynamics, rather than model deficiencies, in determining TC intensity errors at 4–5-day lead times. These results suggest a fundamental limit in the improvement of TC intensity forecasts by numerical models that one should consider in future model development and evaluation.

Journal

Weather and Forecasting – American Meteorological Society

Published: Apr 12, 2021

References

  • Improvements in tropical cyclone track and intensity forecasts using the GFDL initialization system
    Bender, M. A.; Ross, R. J.; Tuleya, R. E.; Kurihara, Y.
  • The operational GFDL coupled hurricane–ocean prediction system and a summary of its performance
    Bender, M. A.; Ginis, I.; Tuleya, R.; Thomas, B.; Marchok, T.
  • Sensitivity of high-resolution simulations of Hurricane Bob (1991) to planetary boundary layer parameterizations
    Braun, S. A.; Tao, W. K.
  • Variability and predictability of a three-dimensional hurricane in statistical equilibrium
    Brown, B. R.; Hakim, G. J.
  • Asymmetric structures in a simulated landfalling hurricane
    Chen, Y. S.; Yau, M. K.
  • The BMRC high-resolution tropical cyclone prediction system: TC-LAPS
    Davidson, N. E.; Weber, H. C.
  • Numerical simulations of the genesis of Hurricane Diana (1984), Part II: Sensitivity of track and intensity prediction
    Davis, C.; Bosart, L. F.
  • Evaluation of long-term trends in tropical cyclone intensity forecasts
    DeMaria, M.; Knaff, J. A.; Sampson, C.
  • Is tropical cyclone intensity guidance improving?
    DeMaria, M.; Sampson, C. R.; Knaff, J. A.; Musgrave, K. D.
  • Tropical cyclone prediction using COAMPS-TC
    Doyle, J. D.
  • A view of tropical cyclones from above: The tropical cyclone intensity experiment
    Doyle, J. D.
  • A study of connection between tropical cyclone track and intensity errors in the WRF model
    Du, T. D.; Ngo-Duc, T.; Hoang, M. T.; Kieu, C. Q.
  • An air-sea interaction theory for tropical cyclones. Part I: Steady-state maintenance
    Emanuel, K. A.
  • On the predictability and error sources of tropical cyclone intensity forecasts
    Emanuel, K. A.; Zhang, F.
  • Parameterization of the radiative properties of cirrus clouds
    Fu, Q.; Liou, K. N.
  • The Hurricane Forecast Improvement Project
    Gall, R.; Franklin, J.; Marks, F.; Rappaport, E. N.; Toepfer, F.
  • Tropical cyclone motion and surrounding parameter relationships
    George, J. E.; Gray, W. M.
  • Global view of the origin of tropical disturbances and storms
    Gray, W. M.
  • The variability and predictability of axisymmetric hurricanes in statistical equilibrium
    Hakim, G. J.
  • Responses of the summertime subtropical anticyclones to global warming
    He, C.; Wu, B.; Zou, L.; Zhou, T.
  • Influence of environmental humidity on tropical cyclone size
    Hill, K. A.; Lackmann, G. M.
  • The Naval Research Laboratory’s Coupled Ocean/Atmospheric Mesoscale Prediction System (COAMPS)
    Hodur, R. M.
  • The maximum potential intensity of tropical cyclones
    Holland, G. J.
  • An evaluation of the impact of horizontal resolution on tropical cyclone predictions using COAMPS-TC
    Jin, H.; Peng, M. S.; Jin, Y.; Doyle, J. D.
  • Predictability of tropical cyclone intensity: Scale-dependent forecast error growth in high-resolution stochastic kinetic energy backscatter ensembles
    Judt, F.; Chen, S. S.; Berner, J.
  • Hurricane maximum potential intensity equilibrium
    Kieu, C.
  • Hurricane intensity predictability
    Kieu, C.; Moon, Z.
  • Stability of tropical cyclone equilibrium
    Kieu, C.; Wang, Q.
  • The control of environmental stratification on the hurricane maximum potential intensity
    Kieu, C.; Zhang, D.-L.
  • Vertical structure of tropical cyclones at onset of the rapid intensification in the HWRF model
    Kieu, C.; Tallapragada, V.; Hogsett, W.
  • On the growth of intensity forecast errors in the operational Hurricane Weather Research and Forecasting (HWRF) model
    Kieu, C.; Keshavamurthya, K.; Tallapragada, V.; Gopalakrishnan, S.; Trahan, S.
  • Time-mean response over the tropical Pacific to increased CO2 in a coupled ocean–atmosphere model
    Knutson, T. R.; Manabe, S.
  • GFDL-type typhoon initialization in MM5
    Kwon, H. J.; Won, S. H.; Suh, A. S.; Chung, H. S.
  • A reanalysis of the 1931–43 Atlantic hurricane database
    Landsea, C. W.; Hagen, A.; Bredemeyer, W.; Carrasco, C.; Glenn, D. A.; Santiago, A.; Strahan-Sakoskie, D.; Dickinson, M.
  • Bulk parameterization of the snow field in a cloud model
    Lin, Y.-L.; Farley, R. D.; Orville, H. D.
  • A multiscale numerical study of Hurricane Andrew (1992). Part I: Explicit simulation and verification
    Liu, Y.; Zhang, D. L.; Yau, M. K.
  • Deterministic nonperiodic flow
    Lorenz, E.N.
  • Impact of sea surface temperature in modulating movement and intensity of tropical cyclones
    Mandal, M.; Mohanty, U. C.; Sinha, P.; Ali, M. M.
  • Development of a turbulence closure model for geophysical fluid problems
    Mellor, G. L.; Yamada, T.
  • Numerical simulation of the life cycle of tropical cyclones
    Ooyama, K.
  • Customization of WRF-ARW model with physical parameterization schemes for the simulation of tropical cyclones over North Indian Ocean
    Osuri, K. K.; Mohanty, U. C.; Routray, A.; Kulkarni, M. A.; Mohapatra, M.
  • Impact of cloud microphysical processes on hurricane intensity, Part I: Control run
    Pattnaik, S.; Krishnamurti, T. N.
  • Evaluation of a time-dependent model for the intensification of tropical cyclones
    Peng, K.; Rotunno, R.; Bryan, G.
  • An air–sea interaction theory for tropical cyclones. Part II: Evolutionary study using a nonhydrostatic axisymmetric numerical model
    Rotunno, R.; Emanuel, K. A.
  • The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. Part VIII: A model for the “seeder-feeder” process in warm-frontal rainbands
    Rutledge, S. A.; Hobbs, P. V.
  • A sensitivity study of the thermodynamic environment on GFDL model hurricane intensity: Implications for global warming
    Shen, W.; Tuleya, R. E.; Ginis, I.
  • Evaluation of storm structure from the operational HWRF during 2012 implementation
    Tallapragada, V.; Kieu, C.; Kwon, Y.; Trahan, S.; Liu, Q.; Zhang, Z.; Kwon, I.
  • Forecasting tropical cyclones in the western North Pacific basin using the NCEP operational HWRF: Real-time implementation in 2012
    Tallapragada, V.
  • Impact of assimilating aircraft reconnaissance observations on tropical cyclone initialization and prediction using operational HWRF and GSI ensemble–variational hybrid data assimilation
    Tong, M.
  • Uncertainty of tropical cyclone best-track information
    Torn, R. D.; Snyder, C.
  • How do outer spiral rainbands affect tropical cyclone structure and intensity?
    Wang, Y.
  • Seasonal forecasts of tropical cyclone activity over the Western North Pacific: A review
    Zhan, R.; Wang, Y.; Ying, M.