EnKF Assimilation of Satellite-retrieved Cloud Water Path to Improve Tropical Cyclone Rainfall Forecast

IF 1.5 4区 地球科学 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES
Xiao-yu Gao, Yan-luan Lin, Yue Jian
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引用次数: 0

Abstract

Tropical cyclone(TC) rainfall forecast has remained a challenge. To create initial conditions with high quality for simulation, the present study implemented a data assimilation scheme based on the EnKF method to ingest the satellite-retrieved cloud water path(Cw) and tested it in WRF. The scheme uses the vertical integration of forecasted cloud water content to transform control variables to the observation space, and creates the correlations between Cw and control variables in the flow-dependent background error covariance based on all the ensemble members, so that the observed cloud information can affect the background temperature and humidity. For two typhoons in 2018(Yagi and Rumiba), assimilating Cw significantly increases the simulated rainfalls and TC intensities. In terms of the average equitable threat score of daily moderate to heavy rainfall(5-120 mm), the improvements are over 130%, and the dry biases are cut by about 30%. Such improvements are traced down to the fact that Cw assimilation increases the moisture content, especially that further away from the TC center, which provides more precipitable water for the rainfall, strengthens the TC and broadens the TC size via latent heat release and internal wind field adjustment.
卫星反演云水路径的EnKF同化以改善热带气旋降雨预报
热带气旋(TC)的雨量预测仍然是一个挑战。为了创造高质量的模拟初始条件,本研究实现了一种基于EnKF方法的数据同化方案,以摄取卫星反演的云水路径(Cw),并在WRF中进行了测试。该方案利用预测云水含量的垂直积分将控制变量转换到观测空间,并在基于所有集合成员的流相关背景误差协方差中建立Cw与控制变量之间的相关性,使观测云信息能够影响背景温度和湿度。对于2018年的八木和伦巴两个台风,同化Cw显著增加了模拟降雨量和TC强度。在日中强降水(5 ~ 120 mm)平均公平威胁得分方面,改善幅度超过130%,干旱偏倚减少约30%。这主要是由于连续波同化增加了水汽含量,特别是远离TC中心的水汽含量增加,为降雨提供了更多的可降水量,通过潜热释放和内部风场调整增强了TC,扩大了TC的大小。
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来源期刊
热带气象学报
热带气象学报 METEOROLOGY & ATMOSPHERIC SCIENCES-
CiteScore
1.80
自引率
8.30%
发文量
2793
审稿时长
6-12 weeks
期刊介绍: Information not localized
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