桂林地区暴雨天气下两种对流层模型的适用性分析

Applicability analysis of two troposphere models during rainstorms in Guilin

针对对流层延迟误差改正模型在不同区域的影响各不相同,为分析常用的GPT2w和UNB3m模型在桂林地区暴雨天气下的适用性,以暴雨频发的2017年6—7月为研究时段,基于桂林地区该时间段内8个CORS基准站解算的对流层天顶总延迟(ZTD)产品为参考值,对模型在桂林地区暴雨天气下的适用性进行分析。结果表明:在暴雨天气下,GPT2w-1和GPT2w-5模型的平均偏差BIAS分别为-2.94和-4.37 cm,RMS分别为3.77和4.86 cm,而UNB3m表现出较大的平均偏差(-11.26 cm)和RMS(11.37 cm);相比暴雨天气,GPT2w-1、GPT2w-5和UNB3m模型在晴朗天气下的精度(RMS值)分别提高了1.18、2.52和3.95 cm。综合分析发现,常用GNSS对流层延迟模型在晴朗天气下的精度及稳定性普遍要优于暴雨天气,同时在桂林地区暴雨天气下GPT2w模型的精度及稳定性都优于UNB3m模型。因此,在桂林地区暴雨天气下GPT2w相较于UNB3m模型具有更好的适用性。

There are different effects for tropospheric delay error correction model in different regions.The applicability,generally by GPT2w and UNB3m models under the rainstorm weather in Guilin,is analyzed,based on frequent rainstorm events from June to July in 2017.The ZTD products,derived from 8 CORS stations as reference,can analyze the applicability of GPT2w and UNB3m models under the rainstorm events in Guilin.The mean BIAS of GPT2w-1 and GPT2w-1 models are-2.94 and-4.37 cm,respectively,and the RMS errors are 3.77 and 4.86 cm,respectively.However,UNB3m model shows larger BIAS(-11.26 cm)and RMS(11.37 cm).Compared with rainstorm weather,the accuracies of GPT2w-1,GPT2w-5 and UNB3m models in sunny weather(RMS values)are improved 1.18,2.52 and 3.95 cm,respectively.In general,the performance of the commonly used GNSS tropospheric delay models in sunny weather is better than those of the rainstorm weather.The accuracy and stability of the GPT2w model are better than those of the UNB3m model under the rainstorm weather.Hence,the GPT2w model has better applicability than UNB3m model under the rainstorm weather in Guilin.