Dynamics of Rossby dipole with effect of scalar nonlinearity

Zhang, Xiping; Zhao, Qiang

doi:10.1016/j.cnsns.2015.08.017

Cited by 2 publications

(1 citation statement)

References 25 publications

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“…However, the chaotic nature of the atmosphere and the imperfections inherent in numerical weather prediction systems mean that small initial errors can grow into large prediction errors (Lorenz, 1963, 1965, 1993; Thompson, 1957). A single prediction cannot explicitly capture the forecast uncertainty (Palmer, 2000; Zhang & Zhao, 2016). To solve this problem, the ensemble prediction method was developed to generate a set of predictions that start from different initial states instead of a single prediction (Demeritt et al, 2007; Ehrendorfer & Tribbia, 1997; Leith, 1974).…”

Section: Introductionmentioning

confidence: 99%

Comparison of different global ensemble prediction systems for tropical cyclone intensity forecasting

Lu,

Ding,

Mao

et al. 2024

Atmospheric Science Letters

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Many meteorological centers have operationally implemented global model‐based ensemble prediction systems (GEPSs), making tropical cyclone (TC) forecasts from these systems available. The relatively low resolution of these GEPSs means that limits previous studies primarily focused on TC track forecasting. However, recent GEPS upgrades mean that TC intensity predictions from GEPSs are now also becoming of interest. This study focuses on the verification and comparison of the latest generation of GEPSs for TC intensity forecasts, particularly during the rapid intensification (RI) period over the western North Pacific (WP), eastern North Pacific (EP), and North Atlantic (NA) basins in 2021–2022. On average, the National Centers for Environmental Prediction (NCEP) GEPS performed best in predicting both TC intensity and RI across all three basins. Nevertheless, the exact timing of RI remains highly uncertain for these GEPS, indicating significant limitations in using GEPSs to forecast RI.

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Section: Introductionmentioning

confidence: 99%

Comparison of different global ensemble prediction systems for tropical cyclone intensity forecasting

Lu,

Ding,

Mao

et al. 2024

Atmospheric Science Letters

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A Probabilistic Tropical Cyclone Track Forecast Scheme Based on the Selective Consensus of Ensemble Prediction Systems

Zhang

2017

Weather and Forecasting

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Selective consensus and a grand ensemble based on an ensemble prediction system (EPS) have been found to be effective in improving deterministic tropical cyclone (TC) track forecasts, while little attention has been paid to quantitative applications of the forecast uncertainty information provided by EPSs. In this paper the forecast uncertainty information is evaluated for two operational EPSs and their grand ensemble. Then, a probabilistic TC track forecast scheme is proposed based on the selective consensus of the two EPSs; this scheme is composed of member picking, mean track shifting, and probability ellipses. The operational EPSs are from the European Centre for Medium-Range Weather Forecasts (ECMWF-EPS) and the National Centers for Environmental Prediction (NCEP-GEFS). Evaluation exhibits that the hit ratios of ECMWF-EPS are above 80% for the 70% probability ellipses at all lead times until 120 h and are used in the proposed scheme. The other components of the proposed scheme are about picking potentially good EPS members. A picking ratio of 1/2 is found to be the best choice, and the member-picking technique is used for the grand ensemble but only for lead times out to 48 h. For lead times longer than 48 h, all of the grand ensemble members are used in obtaining the mean track. The effectiveness of the proposed scheme shows a 10% improvement in the mean track forecast errors over the grand ensemble and a 4.5% improvement in the hit ratio of 70% probability ellipses over the ECMWF-EPS at 24 h, demonstrating its good potential to be applied in operations.

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Dynamics of Rossby dipole with effect of scalar nonlinearity

Cited by 2 publications

References 25 publications

Comparison of different global ensemble prediction systems for tropical cyclone intensity forecasting

Comparison of different global ensemble prediction systems for tropical cyclone intensity forecasting

A Probabilistic Tropical Cyclone Track Forecast Scheme Based on the Selective Consensus of Ensemble Prediction Systems

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