Abstract
An ensemble Kalman filter (EnKF) combined with the Advanced Research Weather Research and Forecasting model (WRF) is cycled and evaluated for western North Pacific (WNP) typhoons of year 2016. Conventional in situ data, radiance observations, and tropical cyclone (TC) minimum sea level pressure (SLP) are assimilated every 6 h using an 80-member ensemble. For all TC categories, the 6-h ensemble priors from the WRF/EnKF system have an appropriate amount of variance for TC tracks but have insufficient variance for TC intensity. The 6-h ensemble priors from the WRF/EnKF system tend to overestimate the intensity for weak storms but underestimate the intensity for strong storms. The 5-d deterministic forecasts launched from the ensemble mean analyses of WRF/EnKF are compared to the NCEP and ECMWF operational control forecasts. Results show that the WRF/EnKF forecasts generally have larger track errors than the NCEP and ECMWF forecasts for all TC categories because the regional simulation cannot represent the large-scale environment better than the global simulation. The WRF/EnKF forecasts produce smaller intensity errors and biases than the NCEP and ECMWF forecasts for typhoons, but the opposite is true for tropical storms and severe tropical storms. The 5-d ensemble forecasts from the WRF/EnKF system for seven typhoon cases show appropriate variance for TC track and intensity with short forecast lead times but have insufficient spread with long forecast lead times. The WRF/EnKF system provides better ensemble forecasts and higher predictability for TC intensity than the NCEP and ECMWF ensemble forecasts.
摘 要
本文搭建了结合 WRF 模式和集合 Kalman 滤波 (WRF/EnKF)的同化系统, 对 2016 年西北太平洋台风季进行了循环同化和预报, 并对结果进行了评估. 该 WRF/EnKF 同化系统使用 80 个集合成员, 每 6 小时同化一次常规观测资料、 卫星资料、 及热带气旋(TC)的最低海平面气压. WRF/EnKF 同化系统的 6 小时集合预报对 TC 路径有较为合适的方差, 但对 TC 强度的方差估计不足; 同时 WRF/EnKF 同化系统会高估弱 TC 的强度, 但低估强 TC 的强度. 将由 WRF/EnKF 同化系统的集合平均分析场起报的5天确定性预报与 NCEP 和 ECMWF 的控制预报相比可得, WRF/EnKF 预报比 NCEP 和 ECMWF 预报有更大的 TC 路径误差, 这是因为相对于全球模式, 区域模式不能更好地模拟大尺度环境. 对于强 TC, WRF/EnKF 的预报比 NCEP 和 ECMWF 预报强度预报误差更小, 但对于弱 TC 则相反. 针对 7 个台风个例, WRF/EnKF 同化系统所得的 5 天集合预报在短预报时效上对 TC 路径和强度均有合适的离散度, 但在长预报时效上却离散度不足; 并且 WRF/EnKF 同化系统的集合预报优于 NCEP 和 ECMWF, 对 TC 强度有更高的可预报性.
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Acknowledgements
We thank the editor and three anonymous reviewers for their insightful and constructive comments and suggestions. This work is jointly sponsored by the National Key R&D Program of China through Grant No. 2017YFC1501603, and the National Natural Science Foundation of China through Grant Nos. 41675052 and 41775057.
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Article Highlights
• An 80-member cycled WRF/EnKF with 6-h data assimilation is operated and evaluated for western North Pacific typhoons of year 2016.
• The WRF/EnKF system has an appropriate amount of variance for 6-h track forecasts and better typhoon intensity forecasts than global models.
• The WRF/EnKF system provides better ensemble forecasts and higher predictability for typhoon intensity than global models.
This paper is a contribution to the special topic on Key Dynamic and Thermodynamic Processes and Prediction of Typhoon (KPPT).
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Lei, L., Ge, Y., Tan, ZM. et al. Evaluation of a Regional Ensemble Data Assimilation System for Typhoon Prediction. Adv. Atmos. Sci. 39, 1816–1832 (2022). https://doi.org/10.1007/s00376-022-1444-4
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DOI: https://doi.org/10.1007/s00376-022-1444-4