Dynamical Seasonal Prediction of Tropical Cyclone Activity Using the FGOALS-f2 Ensemble Prediction System
| العنوان: | Dynamical Seasonal Prediction of Tropical Cyclone Activity Using the FGOALS-f2 Ensemble Prediction System |
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| المؤلفون: | Lei Wang, Xiaofei Wu, Zili Shen, Yimin Liu, Jinxiao Li, Jing Yang, Guoxiong Wu, Bian He, Qing Bao, Xiaocong Wang |
| المصدر: | Weather and Forecasting. 36:1759-1778 |
| بيانات النشر: | American Meteorological Society, 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Atmospheric Science, Climatology, Ensemble prediction, Environmental science, Tropical cyclone |
| الوصف: | There is a distinct gap between tropical cyclone (TC) prediction skill and the societal demand for accurate predictions, especially in the western Pacific (WP) and North Atlantic (NA) basins, where densely populated areas are frequently affected by intense TC events. In this study, seasonal prediction skill for TC activity in the WP and NA of the fully coupled FGOALS-f2 V1.0 dynamical prediction system is evaluated. In total, 36 years of monthly hindcasts from 1981 to 2016 were completed with 24 ensemble members. The FGOALS-f2 V1.0 system has been used for real-time predictions since June 2017 with 35 ensemble members, and has been operationally used in the two operational prediction centers of China. Our evaluation indicates that FGOALS-f2 V1.0 can reasonably reproduce the density of TC genesis locations and tracks in the WP and NA. The model shows significant skill in terms of the TC number correlation in the WP (0.60) and the NA (0.61) from 1981 to 2015; however, the model underestimates accumulated cyclone energy. When the number of ensemble members was increased from 2 to 24, the correlation coefficients clearly increased (from 0.21 to 0.60 in the WP, and from 0.18 to 0.61 in the NA). FGOALS-f2 V1.0 also successfully reproduces the genesis potential index pattern and the relationship between El Niño–Southern Oscillation and TC activity, which is one of the dominant contributors to TC seasonal prediction skill. However, the biases in large-scale factors are barriers to the improvement of the seasonal prediction skill, e.g., larger wind shear, higher relative humidity, and weaker potential intensity of TCs. For real-time predictions in the WP, FGOALS-f2 V1.0 demonstrates a skillful prediction for track density in terms of landfalling TCs, and the model successfully forecasts the correct sign of seasonal anomalies of landfalling TCs for various regions in China. |
| تدمد: | 1520-0434 0882-8156 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::d8e6ac1d9baa2927c3e79d69c3d74c88 https://doi.org/10.1175/waf-d-20-0189.1 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi...........d8e6ac1d9baa2927c3e79d69c3d74c88 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 15200434 08828156 |
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