Two-Dimensional Retrieval of Typhoon Tracks from an Ensemble of Multimodel Outputs

Abstract

In this study a method of retrieving optimum information of typhoon tracks in a multimodel ensemble of forecasts is explored. By treating the latitudes and longitudes of typhoon centers as components of twodimensional track vectors and using the full ensemble mean as a first guess, it is shown that such a twodimensional approach for the typhoon track forecast can be formulated as a multivariate optimization problem. Experiments with five nonhydrostatic primitive equation models during the 2004-08 typhoon seasons in the western North Pacific basin show some noticeable improvements in the forecasts of typhoon tracks in terms of the forecast errors and track smoothness with this multivariate approach. The advantages of the multivariate optimization approach are its portability and simplicity, which could make it easily adaptable to any operational typhoon forecast center that synthesizes typhoon track forecast products from different sources.

Application of Kalman Filter and Breeding Ensemble Technique to Forecast the Tropical Cyclone Activity

“…With limited range of predictability at the convective scale and short timescale and the complex variation of nature, predicting tropical cyclone (TC) tracks and intensity is one specific example that demonstrates vividly the sensitivity of numerical models to uncertainties in the atmosphere [26,38,39]. The inherent uncertainties associated with our current incomplete understanding of model physical processes or numerical approximations often lead to large errors in track and intensity forecast, especially at the lead times longer 3 days or under circumstances interacting with uneven terrain or complicated vortex mergers [40][41][42]. Currently, the US Joint Typhoon Warning Center (JTWC) showed that the official track errors in the North Western Pacific (WPAC) basin are as high as 220 km at 3-day estimation and 450 km at 5-day estimation.…”

Multi-model ensemble forecasts of tropical cyclones in 2010 and 2011 based on the Kalman Filter method

“…For example, Qi et al (2014) proposed a selective ensemble mean technique for TC track forecast based on the errors of ensemble prediction system members at short lead times. Similarly, a method of retrieving optimum information of typhoon tracks in a multi-model ensemble of forecasts is explored by Tien et al (2012). Twenty-four-to seventy-two-hour TC track forecast errors have been reduced by nearly half from 1990 to 2008; however, track prediction errors exceeding 1000 km for 3-day predictions still occur (Franklin 2012;DeMaria et al 2014).…”