GNSS-retrieved precipitable water vapour in the Atlantic coast of France and Spain with GPT3 model

IF 1.4 4区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS Acta Geodaetica et Geophysica Pub Date : 2023-10-31 DOI:10.1007/s40328-023-00427-6
Raquel Perdiguer-Lopez, José Luis Berne Valero, Natalia Garrido-Villen
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Abstract

Water vapour is a critical atmospheric parameter to understand the Earth's climate system and it is characterized by a complex variability in time and space. GNSS observations have become an important source of information of the water vapour, thanks to its high temporal and spatial resolution. However, the lack of meteorological sites collocated with the GNSS site could hamper water vapour retrieval. The empirical blind models can fill this gap. This study analyses the temporal and spatial distribution of the water vapour using nine GNSS sites located on the Atlantic coast of Spain and France, with the empirical blind model GPT3 as the source of meteorological information. The observations were processed with Bernese 5.2 software on a double difference approach and validated with Zenith Total Delay EUREF REPRO2 values. Consequently, four-years series of water vapour was determined and validated using two matched radiosonde sites. The characterization of the water vapour on the area shows clear seasonal characteristics that the technique captures, using an empirical blind model for the whole process. Maximum values are observed in summer season and minimum in winter. The PWV tends to decrease with increasing latitude in the area of the study. The short-term variations can be reproduced by the high temporal resolution of the GNSS-retrieved water vapour and show a different behaviour over the area, but a similar pattern with a peak in the afternoon and minimum at night was found. Also, less variability is observed in winter season and higher in summertime.

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利用 GPT3 模型获取的法国和西班牙大西洋沿岸全球导航卫星系统可降水水蒸气数据
水蒸气是了解地球气候系统的一个关键大气参数,其特点是在时间和空间上的复杂变化。全球导航卫星系统观测由于具有较高的时间和空间分辨率,已成为水蒸气信息的重要来源。然而,缺乏与全球导航卫星系统站点相匹配的气象站点可能会妨碍水蒸气检索。经验盲模型可以填补这一空白。本研究利用位于西班牙和法国大西洋沿岸的九个全球导航卫星系统站点,以经验盲模型 GPT3 作为气象信息源,分析了水蒸气的时空分布。观测数据使用 Bernese 5.2 软件以双重差分法进行处理,并与天顶总延迟 EUREF REPRO2 数值进行验证。因此,利用两个匹配的无线电探空仪站点确定并验证了四年的水蒸气序列。该地区的水蒸气特征显示出明显的季节性特征,该技术利用经验盲模型对整个过程进行了捕捉。观测到的最大值出现在夏季,最小值出现在冬季。在研究区域内,随着纬度的增加,水蒸汽值呈下降趋势。全球导航卫星系统检索到的水蒸气的高时间分辨率可以再现短期变化,并在该地区显示出不同的行为,但发现了一个类似的模式,即下午达到峰值,晚上达到最小值。此外,在冬季观测到的变化较小,而在夏季观测到的变化较大。
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来源期刊
Acta Geodaetica et Geophysica
Acta Geodaetica et Geophysica GEOCHEMISTRY & GEOPHYSICS-
CiteScore
3.10
自引率
7.10%
发文量
26
期刊介绍: The journal publishes original research papers in the field of geodesy and geophysics under headings: aeronomy and space physics, electromagnetic studies, geodesy and gravimetry, geodynamics, geomathematics, rock physics, seismology, solid earth physics, history. Papers dealing with problems of the Carpathian region and its surroundings are preferred. Similarly, papers on topics traditionally covered by Hungarian geodesists and geophysicists (e.g. robust estimations, geoid, EM properties of the Earth’s crust, geomagnetic pulsations and seismological risk) are especially welcome.
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