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Tropospheric delay performance for GNSS integrated water vapor estimation by using GPT2w model, ECMWF's IFS operational model and in situ meteorological data

机译:通过使用GPT2W模型,ECMWF的IFS运行模型和原位气象数据,GNSS集成水蒸气估计的对流层延迟性能

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摘要

Tropospheric delay comprises one of the most important error sources insatellite navigation and is caused when radio signals broadcasted by GPSsatellites propagate into the atmosphere. It is usually projected onto zenithdirection by using mapping functions named as Zenith Tropospheric Delay(ZTD). ZTD is described as the sum of the Zenith Hydrostatic Delay (ZHD) andthe Zenith Wet Delay (ZWD) and with the aid of surface pressure andtemperature the integrated water vapor can be estimated. The main objectiveof this study is to evaluate the tropospheric delay performance for GNSSintegrated water vapor estimation by using GPT2w model, ECMWF's IFS (ECMWFstands for the European Centre for Medium-Range Weather Forecasts) reanalysismodel and ground meteorological data from two stations of the permanentnetwork of Cyprus and Greece. The period from 27 May to 3 June 2018 ischaracterized by two different synoptic conditions: high pressure with fairweather in central Mediterranean (Greece), on the one hand, and highinstability over the upper levels of the atmosphere that resulted inthunderstorms inland and mountainous areas during midday over the EasternMediterranean (Cyprus), on the other hand. In general, the results show thatboth the empirical blind model GPT2w and the ECMWF (IFS) operational modelperform well in particular over Nicosia when used for the retrieval ofIntegrated Water Vapor (IWV) from GNSS measurements, although appreciabledeviations were observed between ECMWF (IFS)-retrieved IWV and the oneretrieved from GNSS observations by using meteorological measurements. Asharp increase of IWV prior to the abrupt rainfall events during noon on 30 and 31 May over Nicosia was also found.
机译:对流层延迟包括最重要的错误来源之一卫星导航,并在GPS广播的无线电信号时导致卫星宣传到大气中。它通常投射到Zenith上通过使用映射函数命名为Zenith的对流层延迟的方向(ZTD)。 ZTD被描述为Zenith静水延迟(ZHD)和Zenith潮湿延迟(ZWD)和借助表面压力和温度可以估计集成的水蒸气。主要目标是本研究是评估GNSS的对流层延迟性能通过使用GPT2W模型,ECMWF的IFS(ECMWF)综合水蒸气估算代表欧洲中距离的天气预报中心)重新分析来自永久的两个站的模型和地面气象数据塞浦路斯网络和希腊。从2018年5月27日至6月3日的期间是以两种不同的天气条件为特征:高压与展平天气在地中海(希腊),一方面,高导致大气层的上层稳定性在东部午间的内陆和山区雷暴另一方面,地中海(塞浦路斯)。一般来说,结果表明经验盲模型GPT2W和ECMWF(IFS)操作模型当用于检索时,特别是在尼科西亚上表现良好来自GNSS测量的综合水蒸气(IWV),但也是可观的在ECMWF(IFS) - Retrieve IWV和One之间观察到偏差通过使用气象测量从GNSS观察中检索。一种还发现了在中午突然降雨事件之前,IWV在5月30日和31日临时降雨前增加。

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