Analysis of temporal and spatial variation characteristics of rainstorm based on BeiDou PWV
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摘要: 利用49个山东省连续运行参考站(SDCORS) 2020年的北斗观测数据，使用GAMIT软件进行了大气水汽反演，得到了全年逐小时的大气可降水量(PWV)序列. 将反演得到的PWV与探空气象站观测的PWV对比，平均偏差为2.4 mm，均方根误差(RMSE)为3.4 mm，相关系数达到0.98，结果表明反演结果的精度符合气象研究需求. 分别从单连续运行参考站(CORS)和全省范围对PWV在暴雨过程中的变化进行了分析，发现PWV在暴雨产生前5~12 h开始上升，至暴雨产生时刻，PWV最大值普遍达到60 mm以上，平均变化率达到1~3 mm/h，越临近暴雨产生，PWV变化幅度越大，降水结束后，PWV会迅速下降. PWV的变化与暴雨的产生具有高度相关性，PWV在暴雨产生前后的剧烈变化，可用于暴雨预警研究，对于生产生活活动具有重要现实指导意义.
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关键词:
- 北斗卫星导航系统(BDS) /
- 连续运行参考站(CORS) /
- 大气可降水量(PWV) /
- 暴雨预警 /
- 水汽反演
Abstract: Using the BeiDou observation data of 49 continuously operating reference stations in Shandong Province (SDCORS) in 2020, the atmospheric water vapor inversion was carried out using GAMIT software, and the annual hourly precipitable water vapor (PWV) series were obtained. Comparing the PWV obtained by inversion with the PWV observed by radiosonde weather station, the average deviation is 2.4 mm, the root mean square error is 3.4 mm, and the correlation coefficient reaches 0.98, indicating that the accuracy of inversion results meets the needs of meteorological research. The changes of PWV in the rainstorm process were analyzed from a single CORS station and the whole province. It was found that PWV began to rise 5 hours to 12 hours before the rainstorm. At the time of the rainstorm, the maximum value of PWV generally reached more than 60 mm, and the average change rate reached 1 to 3 mm/h. The closer the rainstorm occurred, the greater the change range of PWV. After the precipitation ended, PWV will decline rapidly. The change of PWV is highly correlated with the occurrence of rainstorm, which can be used for rainstorm warning research. -
表 2 PWV变化情况统计表
PWVmax/
mm频次 ∆PWV/
mm频次 ∆T/h 频次 PWVr/
(mm·h−1)频次 >70 38 >25 14 >12 6 >3 7 60~70 70 15~25 22 9~12 32 2~3 38 50~60 22 5~15 75 5~8 58 1~2 76 <50 3 <5 22 <5 37 <1 12 
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[1] 郭英莲, 王继竹, 王海燕, 等. GPS可降水量在湖北暴雨预报中的指示性[J]. 气象科技, 2015, 43(4): 666-674. DOI: 10.3969/j.issn.1671-6345.2015.04.018 [2] 姚宜斌, 张顺, 孔建. GNSS空间环境学研究进展和展望[J]. 测绘学报, 2017, 46(10): 1408-1420. DOI: 10.11947/j.AGCS.2017.20170333 [3] ZHAO Q Z, MA X W, YAO Y B. Preliminary result of capturing the signature of heavy rainfall events using the 2-d-/4-d water vapour information derived from GNSS measurement in Hong Kong[J]. Advances in space research, 2020, 66(7): 1537-1550. DOI: 10.1016/j.asr.2020.06.013 [4] KHANIANI A S, MOTIEYAN H, MOHAMMADI A. Rainfall forecast based on GPS PWV together with meteorological parameters using neural network models[J]. Journal of atmospheric and solar-terrestrial physics, 2021, 214(1-2): 105533. DOI: 10.1016/j.jastp.2020.105533 [5] HUANG L K, MO Z X, XIE S F, et al. Spatiotemporal characteristics of GNSS-derived precipitable water vapor during heavy rainfall events in Guilin, China[J]. Satellite navigation, 2021, 2(1): 175-191. DOI: 10.1186/s43020-021-00046-y [6] 施闯, 张卫星, 曹云昌, 等. 基于北斗/GNSS的中国-中南半岛地区大气水汽气候特征及同降水的相关分析[J]. 测绘学报, 2020, 49(9): 1112-1119. DOI: 10.11947/j.AGCS.2020.20200339 [7] 杨军建, 姚宜斌, 许超钤, 等. 大气可降水量与实际降水量的关联性分析[J]. 测绘地理信息, 2016, 41(1): 18-21,26. DOI: 10.14188/j.2095-6045.2016.01.005 [8] 单路路, 姚宜斌, 赵庆志, 等. 基于GNSS PWV的短临降雨预测方法[J]. 测绘地理信息, 2019, 44(1): 22-26. [9] 杜爱军, 张强, 杨世琦, 等. 北斗CORS探测的大气可降水量与重庆降雨的关系[J]. 大地测量与地球动力学, 2020, 40(2): 134-139. [10] 张振, 李黎, 田莹, 等. 连续运行参考站网的暴雨过程时空变化分析[J]. 测绘科学, 2020, 45(8): 19-25. DOI: 10.16251/j.cnki.1009-2307.2020.08.004 [11] 陈明东. GPS/PWV在台风“玛莉亚”袭闽期间的变化特征研究[J]. 测绘通报, 2019(1): 93-96,137. [12] 秦鑫, 赵姝慧, 马嘉理, 等. 辽宁地区大气可降水量与降水关系的研究[J]. 气象, 2020, 46(1): 80-88. DOI: 10.7519/j.issn.1000-0526.2020.01.008 [13] 刘洋, 赵庆志, 姚顽强. 基于多隐层神经网络的GNSS PWV和气象数据的降雨预测研究[J]. 测绘通报, 2019(S1): 36-40. [14] LI H B, WANG X M, CHOY S, et al. Detecting heavy rainfall using anomaly-based percentile thresholds of predictors derived from GNSS-PWV[J]. Atmospheric research, 2022(265): 105912. DOI: 10.1016/j.atmosres.2021.105912 [15] 施闯, 周凌昊, 范磊, 等. 利用北斗/GNSS观测数据分析“21·7”河南极端暴雨过程[J]. 地球物理学报, 2022, 65(1): 186-196. DOI: 10.6038/cjg2022P0706 [16] BOEHM J, NIELL A, TREGONING P, et al. Global mapping function(GMF): a new empirical mapping function based on numerical weather model data[J]. Geophysical research letters, 2006, 33(7): L07304. DOI: 10.1029/2005GL025546 [17] 尹恒毅. 地基GNSS反演大气可降水量的研究[D]. 西安: 西安科技大学, 2020. [18] SAASTAMOINEN J. Contributions to the theory of atmospheric refraction[J]. Bulletin géodésique, 1972, 105(1): 279-298. DOI: 10.1007/BF02522083 -
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