References
- Brown, B.R. and Hakim, G.J. (2013) Variability and predictability of a three-dimensional hurricane in statistical equilibrium. J. Atmos. Sci., 70: 1806–1820. DOI: 10.1175/JAS-D-12-0112.1
- Bryan, G.H. and Fritsch, J.M. (2002) A benchmark Simulation for moist nonhydrostatic numerical models. Mon. Wea. Rev., 130: 2917–2928. DOI: 10.1175/1520-0493(2002)130<;2917:ABSFMN>2.0.CO;2
- Bryan, G.H. and Rotunno, R. (2009) The maximum intensity of tropical cyclones in axisymmetric numerical model simulations. Mon. Wea. Rev., 137: 1770–1789. DOI: 10.1175/2008MWR2709.1
- DelSole, T. and Tippett, M.K. (2007) Predictability: recent insights from information theory. Rev. Geophys., 45:
RG4002 . DOI: 10.1029/2006RG000202 - DelSole, T. and Tippett, M.K. (2009) Average predictability time. Part II: seamless diagnosis of predictability on multiple time scales. J. Atmos. Sci., 66: 1188–1204. DOI: 10.1175/2008JAS2869.1
- DeMaria, M. (2009) A simplified dynamical system for tropical cyclone intensity prediction. Mon. Wea. Rev., 137: 68–82. DOI: 10.1175/2008MWR2513.1
- Durran, D.R. and Gingrich, M. (2014) Atmospheric predictability: why butterflies are not of practical importance. J. Atmos. Sci., 71: 2476–2488. DOI: 10.1175/JAS-D-14-0007.1
- Emanuel, K.A. (1986) An air–sea interaction theory for tropical cyclones. Part I: Steady-state maintenance. J. Atmos. Sci., 43: 585–605. DOI: 10.1175/1520-0469(1986)043<;0585:AASITF>2.0.CO;2
- Emanuel, K.A. (2003) Tropical cyclones. Ann. Rev. Earth Plan. Sci., 31: 75–104. DOI: 10.1146/annurev.earth.31.100901.141259
- Emanuel, K. and Zhang, F. (2016) On the predictability and error sources of tropical cyclone intensity forecasts. J. Atmos. Sci., 73: 3739–3747. DOI: 10.1175/JAS-D-16-0100.1
- Hakim, G.J. (2011) The mean state of axisymmetric hurricanes in statistical equilibrium. J. Atmos. Sci., 68: 1364–1376. DOI: 10.1175/2010JAS3644.1
- Hakim, G.J. (2013) The variability and predictability of axisymmetric hurricanes in statistical equilibrium. J. Atmos. Sci., 70: 993–1005. DOI: 10.1175/JAS-D-12-0188.1
- Judt, F., Chen, S.S. and Berner, J. (2016) Predictability of tropical cyclone intensity: scale-dependent forecast error growth in high-resolution stochastic kinetic-energy backscatter ensembles. Q.J.R. Meteorol. Soc., 142: 43–57. DOI: 10.1002/qj.2626
- Kantz, H. and Schreiber, T. (2003)
Nonlinear time series analysis . 2nd ed. Cambridge: Cambridge University Press. DOI: 10.1017/CBO9780511755798 - Keshavamurthy, K. and Kieu, C. (2021) Dependence of tropical cyclone intrinsic intensity variability on the large-scale environment. Quarterly Journal of the Royal Meteorological Society, 147: 1606–1625. DOI: 10.1002/qj.3984
- Kieu, C.Q. (2015) Hurricane maximum potential intensity equilibrium. Q. J. Royal Meteor. Soc. 141: 2471–2480. DOI: 10.1002/qj.2556
- Kieu, C.Q., Cai, W. and Fan, L. (2022) On the existence of low-dimensional chaos of the tropical cyclone intensity in an idealized axisymmetric simulation? Journal of the Atmospheric Sciences, 80: 797–811. DOI: 10.1175/JAS-D-22-0115.1
- Kieu, C.Q. and Moon, Z. (2016) Hurricane intensity predictability. Bulletin of the American Meteorological Society, 97: 1847–1857. DOI: 10.1175/BAMS-D-15-00168.1
- Kieu, C.Q. and Rotunno, R. (2022) Characteristics of tropical-cyclone turbulence and intensity predictability. Geophysical Research Letter, 49:
e2021GL096544 . DOI: 10.1029/2021GL096544 - Kieu, C.Q. and Wang, Q. (2017) Stability of tropical cyclone equilibrium. Journal of the Atmospheric Sciences, 74: 3591–3608. DOI: 10.1175/JAS-D-17-0028.1
- Klotzbach, P.J., Bell, M.M., Bowen, S.G., Gibney, E.J., Knapp, K.R. and Schreck, C.J. (2020) Surface pressure a more skillful predictor of normalized hurricane damage than maximum sustained wind. Bulletin of the American Meteorological Society, 101: 830–846. DOI: 10.1175/BAMS-D-19-0062.1
- Leith, C.E. (1971) Atmospheric predictability and two-dimensional turbulence. J. Atmos. Sci., 28: 145–161. DOI: 10.1175/1520-0469(1971)028<;0145:APATDT>2.0.CO;2
- Leith, C.E. and Kraichnan, R.H. (1972) Predictability of turbulent flows. J. Atmos. Sci., 29: 1041–1058. DOI: 10.1175/1520-0469(1972)029<;1041:POTF>2.0.CO;2
- Lorenz, E.N. (1963) Deterministic nonperiodic flow. J. Atmos. Sci., 20: 130–141. DOI: 10.1175/1520-0469(1963)020<;0130:DNF>2.0.CO;2
- Lorenz, E.N. (1969) The predictability of a flow which possesses many scales of motion. Tellus, 21: 289–307. DOI: 10.3402/tellusa.v21i3.10086
- Magnusson, L. and Coauthors. (2019) ECMWF Activities for Improved Hurricane Forecasts. Bull. Amer. Meteor. Soc., 100: 445–458. DOI: 10.1175/BAMS-D-18-0044.1
- Métais, O. and Lesieur, M. (1986) Statistical predictability of decaying turbulence. J. Atmos. Sci., 43: 857–870. DOI: 10.1175/1520-0469(1986)043<;0857:SPODT>2.0.CO;2
- Nguyen, P., Kieu, C. and Fan, W.T. (2020) Stochastic variability of tropical cyclone intensity at the asymptotic potential intensity equilibrium. Journal of Atmospheric Sciences, 77: 3105–3118. DOI: 10.1175/JAS-D-20-0070.1
- Persing, J., Montgomery, M.T., Smith, R.K. and McWilliams, J.C. (2019) Quasi steady-state hurricanes revisited. Tropical Cyclone Science Reviews, 8: 1–17. DOI: 10.1016/j.tcrr.2019.07.001
- Rotunno, R. and Emanuel, K.A. (1987) An air–sea interaction theory for tropical cyclones. Part II: Evolutionary study using a non-hydrostatic axisymmetric numerical model. J. Atmos. Sci., 44: 542–561. DOI: 10.1175/1520-0469(1987)044<;0542:AAITFT>2.0.CO;2
- Rotunno, R. and Snyder, C. (2007) A generalization of Lorenz’s model for the predictability of flows with many scales of motion. J. Atmos. Sci., 65: 1063–1076. DOI: 10.1175/2007JAS2449.1
- Schonemann, D. and Frisius, T. (2012) Dynamical system analysis of a low-order tropical cyclone model. Tellus A, 64:
15817 . DOI: 10.3402/tellusa.v64i0.15817 - Shukla, J. (1981) Dynamical predictability of monthly means. J. Atmos. Sci., 38: 2547–2572. DOI: 10.1175/1520-0469(1981)038<;2547:DPOMM>2.0.CO;2
- Smith, R.K., Kilroy, G. and Montgomery, M.T. (2021) Tropical cyclone life cycle in a three-dimensional numerical simulation. Quart. J. Royal Meteorol. Soc., 1: 3373–3393. DOI: 10.1002/qj.4133
- Smith, R.K., Montgomery, M.T. and Persing, J. (2014) On steady-state tropical cyclones. Q. J. R. Meteorolo. Soc., 139: 1–15.
- Sugihara, G. and May, R. (1990) Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series. Journal of Economic Theory, 344: 734–741. DOI: 10.1038/344734a0
- Vallis, G.K. (2017)
Atmospheric and oceanic fluid dynamics . Cambridge: Cambridge University Press. DOI: 10.1017/9781107588417 - Wang, Y., Li, Y. and Xu, J. (2021) A new time-dependent theory of tropical cyclone intensification. J. Atmos. Sci., 78: 3855–3865. DOI: 10.1175/JAS-D-21-0169.1
- Zhong, Q., Li, J., Zhang, L., Ding, R. and Li, B. (2018) Predictability of tropical cyclone intensity over the Western North Pacific using the IBTrACS dataset. Mon. Wea. Rev., 146: 2741–2755. DOI: 10.1175/MWR-D-17-0301.1
DOI: https://doi.org/10.16993/tellusa.4074 | Journal eISSN: 3035-9554
Language: English
Page range: 166 - 176
Submitted on: May 14, 2024
Accepted on: Jul 14, 2024
Published on: Jul 29, 2024
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services
Keywords:
© 2024 Chanh Kieu, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.