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- Author or Editor: Matthieu Plu x
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Abstract
The inherent predictability of tropical cyclone tracks has received much attention since the 1980s. It is still an issue because of the recent improvement of track forecasts by numerical models. The aim of this study is to assess this predictability limit globally using an approach devised by Lorenz on several up-to-date numerical models. The differences between forecasts valid at the same instant are considered to be error values; the doubling time of these small errors leads to an estimated upper bound on predictability. This method is here applied on cyclone position forecasts obtained from three different global operational models (from ECMWF, Météo-France, and the Met Office) over the main tropical cyclone basins in the world and during three recent cyclone seasons (2006–09).
The resulting estimates of predictability largely exceed the values that are commonly accepted in the literature. The doubling time of small errors is found between 30 and 50 h. An important consequence is that cyclone track forecasts have not reached their predictability limit yet. It is argued that the previous methods for computing the predictability of tropical cyclone tracks did not constrain the environment and the structure of the cyclones initially. But the Lorenz method could still underestimate the inherent predictability of tropical cyclone tracks. The sensitivity of the predictability estimates to the model characteristics is discussed. In particular, the use of wind bogus is suggested to avoid serial correlations between successive forecasts and to accelerate error growth.
Abstract
The inherent predictability of tropical cyclone tracks has received much attention since the 1980s. It is still an issue because of the recent improvement of track forecasts by numerical models. The aim of this study is to assess this predictability limit globally using an approach devised by Lorenz on several up-to-date numerical models. The differences between forecasts valid at the same instant are considered to be error values; the doubling time of these small errors leads to an estimated upper bound on predictability. This method is here applied on cyclone position forecasts obtained from three different global operational models (from ECMWF, Météo-France, and the Met Office) over the main tropical cyclone basins in the world and during three recent cyclone seasons (2006–09).
The resulting estimates of predictability largely exceed the values that are commonly accepted in the literature. The doubling time of small errors is found between 30 and 50 h. An important consequence is that cyclone track forecasts have not reached their predictability limit yet. It is argued that the previous methods for computing the predictability of tropical cyclone tracks did not constrain the environment and the structure of the cyclones initially. But the Lorenz method could still underestimate the inherent predictability of tropical cyclone tracks. The sensitivity of the predictability estimates to the model characteristics is discussed. In particular, the use of wind bogus is suggested to avoid serial correlations between successive forecasts and to accelerate error growth.
Abstract
In a nonlinear quasigeostrophic model with uniform potential vorticity, an idealized initial state sharing some features with atmospheric low-predictability situations is built. Inspired by previous work on idealized cyclogenesis, two different cyclogenesis scenarios are obtained as a result of a small change of the initial location of one structure. This behavior is interpreted by analyzing the baroclinic interaction between upper- and lower-level anomalies. The error growth mechanism is nonlinear; it does not depend on the linear stability properties of the jet, which are the same in both evolutions.
The ability of ensemble forecasts to capture these two possible evolutions is then assessed given some realistic error bounds in the knowledge of the initial conditions. First, a reference statistical distribution of each of the evolutions is obtained by means of a large Monte Carlo ensemble. Smaller ensembles with size representative of what is available in current operational implementations are then built and compared to the Monte Carlo reference: several singular-vector-based ensembles, a small Monte Carlo ensemble, and a “coherent structure”-based ensemble. This new technique relies on a sampling of the errors on the precursors of the cyclogenesis: amplitude and position errors. In this context, the precursors are handled as coherent structures that may be amplified or moved within realistic error bounds. It is shown that the singular vector ensemble fails to reproduce the bimodal distribution of the variability if the ensemble is not initially constrained, whereas it is accessible at a relatively low cost to the new coherent structures initialization.
Abstract
In a nonlinear quasigeostrophic model with uniform potential vorticity, an idealized initial state sharing some features with atmospheric low-predictability situations is built. Inspired by previous work on idealized cyclogenesis, two different cyclogenesis scenarios are obtained as a result of a small change of the initial location of one structure. This behavior is interpreted by analyzing the baroclinic interaction between upper- and lower-level anomalies. The error growth mechanism is nonlinear; it does not depend on the linear stability properties of the jet, which are the same in both evolutions.
The ability of ensemble forecasts to capture these two possible evolutions is then assessed given some realistic error bounds in the knowledge of the initial conditions. First, a reference statistical distribution of each of the evolutions is obtained by means of a large Monte Carlo ensemble. Smaller ensembles with size representative of what is available in current operational implementations are then built and compared to the Monte Carlo reference: several singular-vector-based ensembles, a small Monte Carlo ensemble, and a “coherent structure”-based ensemble. This new technique relies on a sampling of the errors on the precursors of the cyclogenesis: amplitude and position errors. In this context, the precursors are handled as coherent structures that may be amplified or moved within realistic error bounds. It is shown that the singular vector ensemble fails to reproduce the bimodal distribution of the variability if the ensemble is not initially constrained, whereas it is accessible at a relatively low cost to the new coherent structures initialization.
Abstract
This study is part of the efforts undertaken to resolve the “bad trough/good trough” issue for tropical cyclone (TC) intensity changes and to improve the prediction of these challenging events. Sensitivity experiments are run at 8-km resolution with vortex bogusing to extend the previous analysis of a real case of TC–trough interaction (Dora in 2007). The initial position and intensity of the TC are modified, leaving the trough unchanged to describe a realistic environment. Simulations are designed to analyze the sensitivity of TC prediction to both the variety of TC–trough configurations and the current uncertainty in model analysis of TC intensity and position.
Results show that TC intensification under upper-level forcing is greater for stronger vortices. The timing and geometry of the interaction between the two cyclonic potential vorticity anomalies associated with the cutoff low and the TC also play a major role in storm intensification. The intensification rate increases when the TC (initially located 12° northwest of the trough) is displaced 1° closer. By allowing a gradual deformation and equatorward tilting of the trough, both scenarios foster an extended “inflow channel” of cyclonic vorticity at midlevels toward the vortex inner core. Conversely, unfavorable interaction is found for vortices displaced 3° or 4° east or northeast. Variations in environmental forcing relative to the reference simulation illustrate that the relationship between intensity change and the 850–200-hPa wind shear is not systematic and that the 200-hPa divergence, 335–350-K mean potential vorticity, or 200-hPa relative eddy momentum fluxes may be better predictors of TC intensification during TC–trough interactions.
Abstract
This study is part of the efforts undertaken to resolve the “bad trough/good trough” issue for tropical cyclone (TC) intensity changes and to improve the prediction of these challenging events. Sensitivity experiments are run at 8-km resolution with vortex bogusing to extend the previous analysis of a real case of TC–trough interaction (Dora in 2007). The initial position and intensity of the TC are modified, leaving the trough unchanged to describe a realistic environment. Simulations are designed to analyze the sensitivity of TC prediction to both the variety of TC–trough configurations and the current uncertainty in model analysis of TC intensity and position.
Results show that TC intensification under upper-level forcing is greater for stronger vortices. The timing and geometry of the interaction between the two cyclonic potential vorticity anomalies associated with the cutoff low and the TC also play a major role in storm intensification. The intensification rate increases when the TC (initially located 12° northwest of the trough) is displaced 1° closer. By allowing a gradual deformation and equatorward tilting of the trough, both scenarios foster an extended “inflow channel” of cyclonic vorticity at midlevels toward the vortex inner core. Conversely, unfavorable interaction is found for vortices displaced 3° or 4° east or northeast. Variations in environmental forcing relative to the reference simulation illustrate that the relationship between intensity change and the 850–200-hPa wind shear is not systematic and that the 200-hPa divergence, 335–350-K mean potential vorticity, or 200-hPa relative eddy momentum fluxes may be better predictors of TC intensification during TC–trough interactions.
