合成孔径雷达观测到的热带气旋强风同化对分析和预测的影响

IF 2.8 3区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Monthly Weather Review Pub Date : 2024-02-14 DOI:10.1175/mwr-d-23-0103.1
Yasutaka Ikuta, Udai Shimada
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引用次数: 0

摘要

在热带气旋(TC)周围的海洋上空,已经从卫星上获得了一些大风观测数据,但这些海洋上空的观测数据同化对预报的影响尚不明确。空间合成孔径雷达(SAR)提供了热带气旋中心周围高分辨率和大范围的海洋表面风速数据。本研究调查了合成孔径雷达海洋表面风速数据同化对区域模式预报的影响。同化数据由 Sentinel-1 和 RADARSAT-2 上的合成孔径雷达估算得出。OWSAR 的偏差取决于风速,观测误差方差取决于风速和入射角,空间观测误差相关性取决于入射角。观测到的 OWSAR 采用 Huber 准则的变分质量控制方法进行筛选。在台风 "黑格比"(2019 年)中,OWSAR 同化改变了热带气旋的低层流入气流,这也改变了热带气旋的高层流出气流。这种 OWSAR 同化效应从地表向对流层上部的传播是通过四维变分法给出的,该方法在预报模式时间演化的强约束条件下寻找最优解。统计验证证实,热带气旋强度预报误差在 15 小时的准备时间内有所减小,但在统计上并不显著。利用风廓线观测数据进行的验证表明,OWSAR 同化显著提高了对流层中层至高层风速预测的准确性。
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Impact of Assimilation of the Tropical Cyclone Strong Winds Observed by Synthetic Aperture Radar on Analyses and Forecasts
A few high-wind observations have been obtained from satellites over the ocean around tropical cyclones (TCs), but the impact of data assimilation of such observations over the sea on forecasting has not been clear. The spaceborne synthetic aperture radar (SAR) provides high-resolution and wide-area ocean surface wind speed data around the center of a TC. In this study, the impact of data assimilation of the ocean surface wind speed of SAR (OWSAR) on regional model forecasts was investigated. The assimilated data were estimated from SAR onboard Sentinel-1 and RADARSAT-2. The bias of OWSAR depends on wind speed, the observation error variance depends on wind speed and incidence angle, and the spatial observation error correlation depends on the incidence angle. The observed OWSAR is screened using the variational quality control method with the Huber norm. In the case of Typhoon Hagibis (2019), OWSAR assimilation modified the TC low-level inflow, which also modified the TC upper-level outflow. The propagation of this OWSAR assimilation effect from the surface to the upper troposphere was given by a four-dimensional variational method that searches for the optimal solution within strong constraints on the time evolution of the forecast model. Statistical validation confirmed that errors in the TC intensity forecast decreased over lead times of 15 h, but this was not statistically significant. The validation using wind profiler observations showed that OWSAR assimilation significantly improved the accuracy of wind speed predictions from the middle to the upper-level of the troposphere.
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来源期刊
Monthly Weather Review
Monthly Weather Review 地学-气象与大气科学
CiteScore
6.40
自引率
12.50%
发文量
186
审稿时长
3-6 weeks
期刊介绍: Monthly Weather Review (MWR) (ISSN: 0027-0644; eISSN: 1520-0493) publishes research relevant to the analysis and prediction of observed atmospheric circulations and physics, including technique development, data assimilation, model validation, and relevant case studies. This research includes numerical and data assimilation techniques that apply to the atmosphere and/or ocean environments. MWR also addresses phenomena having seasonal and subseasonal time scales.
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