Typhoon-Position-Oriented Sensitivity Analysis. Part I: Theory and Verification

Abstract

A new sensitivity analysis method is proposed for the ensemble prediction system in which a tropical cyclone (TC) position is taken as a metric. Sensitivity is defined as a slope of linear regression (or its approximation) between state variable and a scalar representing the TC position based on ensemble simulation. The experiment results illustrate important regions for ensemble TC track forecast. The typhoon-positionoriented sensitivity analysis (TyPOS) is applied to Typhoon Shanshan (2006) for the verification time of up to 48 h. The sensitivity field of the TC central latitude with respect to the vorticity field obtained from large-scale random initial perturbation is characterized by a horizontally tilted pattern centered at the initial TC position. These sensitivity signals are generally maximized in the middle troposphere and are far more significant than those with respect to the divergence field. The results are consistent with the sensitivity signals obtained from existing methods. The verification experiments indicate that the signals from TyPOS quantitatively reflect an ensemble-mean position change as a response to the initial perturbation. Another experiment with Typhoon Dolphin (2008) demonstrates the long-term analysis of forecast sensitivity up to 96 h. Several additional tests have also been carried out to investigate the dependency among ensemble members, the impacts of using different horizontal grid spacing, and the effectiveness of ensemble-Kalman-filter-based perturbations.

Impact on predictability of tropical and mid-latitude cyclones by extra Arctic observations

“…Observing system experiments (OSEs) have shown that dropsonde observations in sensitive regions, depicted by a singular vector method 11 , have strong impact on TC location forecasts in comparison with observations made outside such regions 7 , 8 . However, when a TC reaches the mid-latitudes, its motion becomes sensitive to the present upper-troposphere circulations 12 .…”

Tropical Cyclone Track Sensitivity in Deformation Steering Flow

“…One method of evaluating the origin of TC position errors is through sensitivity analysis, which provides information about how small changes to the initial conditions can impact a forecast metric, such as TC position, at a particular time. Although position forecast sensitivity can exhibit large case-to-case variability and within methods (e.g., Majumdar et al 2006;Wu et al 2009;Hoover et al 2013), previous studies have suggested that TC position forecasts can be sensitive to specific flow features, such as weaknesses in the subtropical ridge, the motion and evolution of midlatitude troughs, the position and speed of the subtropical jet, as well as uncertainty in the 0-h TC steering flow (e.g., Majumdar et al 2006;Peng and Reynolds 2006;Wu et al 2007;Chen et al 2009;Wu et al 2009;Komaromi et al 2011;Gombos et al 2012;Ido and Wu 2013;Nystrom et al 2018). Furthermore, latent heat release associated with a TC and nearby convection can have an important impact on TC motion by modifying the nearby environment (e.g., Wu and Emanuel 1995a,b;Henderson et al 1999;Anwender et al 2008;Harr et al 2008).…”

Ensemble transform sensitivity for adaptive observations: a general formulation and its practicable implementation

“…In addition to several adjoint-based methods, such as the singular vector method (SVs; Palmer et al 1998;Buizza and Montani 1999) and the conditional nonlinear optimal perturbation method (Mu, Zhou, and Wang 2009;Wang, Mu, and Huang 2011;Yu et al 2017), ensemble-based methods, such as the ensemble transformation method (ET; Toth 1999, hereafter BT1999) and the ensemble transform Kalman filter method (ETKF; Bishop, Etherton, and Majumdar 2001) are also widely applied in field campaigns (Chang, Zheng, and Raeder 2013;Xie et al 2013). Compared to the adjoint-based methods, the ensemble-based methods do not require adjoint models and are also less computationally demanding (Ancell and Hakim 2007;Ito and Wu 2013).…”