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1. Introduction Upper-tropospheric temperatures have been shown to be important for determining the maximum intensity that a tropical cyclone (TC) can reach, but the physical mechanisms through which the upper troposphere impacts TC intensity and structure have not been fully explored, due in part to limited observations and the complex interactions between clouds, radiation, and TC dynamics. A seminal theory on the potential intensity (PI) that a TC can attain was formulated by Emanuel (1986
1. Introduction Upper-tropospheric temperatures have been shown to be important for determining the maximum intensity that a tropical cyclone (TC) can reach, but the physical mechanisms through which the upper troposphere impacts TC intensity and structure have not been fully explored, due in part to limited observations and the complex interactions between clouds, radiation, and TC dynamics. A seminal theory on the potential intensity (PI) that a TC can attain was formulated by Emanuel (1986
. As in Fig. 8 , but for the lifetime maximum intensity (LMI, kt) and (b) its meridional mean profile. Fig . 10. As in Fig. 8 , but for the TC lifetime (h) and (b) its meridional mean profile. Table 1. Pattern correlations between the modified accumulated cyclone energy (MACE), the lifetime maximum intensity (LMI), and the lifetime of TCs over the WNP basin based on observational data. To know if uncertainty of land interaction causes changes in the predictability of TC intensity, we further
. As in Fig. 8 , but for the lifetime maximum intensity (LMI, kt) and (b) its meridional mean profile. Fig . 10. As in Fig. 8 , but for the TC lifetime (h) and (b) its meridional mean profile. Table 1. Pattern correlations between the modified accumulated cyclone energy (MACE), the lifetime maximum intensity (LMI), and the lifetime of TCs over the WNP basin based on observational data. To know if uncertainty of land interaction causes changes in the predictability of TC intensity, we further
as eight RD-94 sondes can be operated simultaneously. The initial development of the XDD was known as the expendable digital radiosonde (XDR) and was tested on the NASA DC-8 during the Arctic Mechanisms of Interaction between the Surface and Atmosphere (AMISA) in 2008. A total of 36 XDRs were deployed over 6 days. Comparison with simultaneous radiosonde ascents from the Swedish Icebreaker Oden showed good results ( Gasiewski et al. 2009 ; Persson 2010 ). Modern XDD sondes are activated and
as eight RD-94 sondes can be operated simultaneously. The initial development of the XDD was known as the expendable digital radiosonde (XDR) and was tested on the NASA DC-8 during the Arctic Mechanisms of Interaction between the Surface and Atmosphere (AMISA) in 2008. A total of 36 XDRs were deployed over 6 days. Comparison with simultaneous radiosonde ascents from the Swedish Icebreaker Oden showed good results ( Gasiewski et al. 2009 ; Persson 2010 ). Modern XDD sondes are activated and
) field. Model dynamics will then adjust the mean and asymmetric wind fields, which in the lower model levels will take into account the planetary boundary layer frictional effects and enthalpy fluxes. Whereas these internal adjustments will determine the intensity change, the TC vortex dynamics and physics prediction are expected to also improve the interaction between the vortex and its environment in conjunction with the better depiction of the outflow jets from the high temporal and spatial
) field. Model dynamics will then adjust the mean and asymmetric wind fields, which in the lower model levels will take into account the planetary boundary layer frictional effects and enthalpy fluxes. Whereas these internal adjustments will determine the intensity change, the TC vortex dynamics and physics prediction are expected to also improve the interaction between the vortex and its environment in conjunction with the better depiction of the outflow jets from the high temporal and spatial
preferentially from different quadrants of the TC depending on the nature of the TC’s environment. Jet streak dynamics play a crucial role in extratropical storm development (e.g., Uccellini 1990 ) and may have a similar role in TC intensity change. The overarching goal of the TCI program is to improve the prediction of TC intensity change, especially rapid intensification (RI) and rapid decay (RD), as well as TC structural changes that are hypothesized to occur through synergistic interaction with outflow
preferentially from different quadrants of the TC depending on the nature of the TC’s environment. Jet streak dynamics play a crucial role in extratropical storm development (e.g., Uccellini 1990 ) and may have a similar role in TC intensity change. The overarching goal of the TCI program is to improve the prediction of TC intensity change, especially rapid intensification (RI) and rapid decay (RD), as well as TC structural changes that are hypothesized to occur through synergistic interaction with outflow
1. Introduction Accurate forecasts of tropical cyclone (TC) intensity changes remain one of the most difficult weather predictions, even for short lead times. This is in part due to multiscale interactions, which require operational forecast models to precisely capture the evolution of the atmosphere over a vast range of scales in the vicinity of a TC. DeMaria et al. (2014) demonstrated that although intensity forecast errors have not improved as much as track forecast errors over the past
1. Introduction Accurate forecasts of tropical cyclone (TC) intensity changes remain one of the most difficult weather predictions, even for short lead times. This is in part due to multiscale interactions, which require operational forecast models to precisely capture the evolution of the atmosphere over a vast range of scales in the vicinity of a TC. DeMaria et al. (2014) demonstrated that although intensity forecast errors have not improved as much as track forecast errors over the past
Atmosphere, Oceans, and Land Surface (IOAS-AOLS), Phoenix, AZ, Amer. Meteor. Soc., 6.3, https://ams.confex.com/ams/95Annual/webprogram/Paper269008.html Zhu , P. , K. Menelaou , and Z. Zhu , 2014 : Impact of subgrid-scale vertical turbulent mixing on eyewall asymmetric structures and mesovortices of hurricanes . Quart. J. Roy. Meteor. Soc. , 140 , 416 – 438 , https://doi.org/10.1002/qj.2147 . 10.1002/qj.2147 Zhu , P. , B. Tyner , J. A. Zhang , E. Aligo , S. Gopalakrishnan , F
Atmosphere, Oceans, and Land Surface (IOAS-AOLS), Phoenix, AZ, Amer. Meteor. Soc., 6.3, https://ams.confex.com/ams/95Annual/webprogram/Paper269008.html Zhu , P. , K. Menelaou , and Z. Zhu , 2014 : Impact of subgrid-scale vertical turbulent mixing on eyewall asymmetric structures and mesovortices of hurricanes . Quart. J. Roy. Meteor. Soc. , 140 , 416 – 438 , https://doi.org/10.1002/qj.2147 . 10.1002/qj.2147 Zhu , P. , B. Tyner , J. A. Zhang , E. Aligo , S. Gopalakrishnan , F
