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Autor(en) / Beteiligte
Titel
Spatiotemporal characteristics of GNSS-derived precipitable water vapor during heavy rainfall events in Guilin, China
Ist Teil von
  • Satellite navigation, 2021-08, Vol.2 (1), p.1-17, Article 13
Ort / Verlag
Singapore: Springer Singapore
Erscheinungsjahr
2021
Link zum Volltext
Quelle
Free E-Journal (出版社公開部分のみ)
Beschreibungen/Notizen
  • Precipitable Water Vapor (PWV), as an important indicator of atmospheric water vapor, can be derived from Global Navigation Satellite System (GNSS) observations with the advantages of high precision and all-weather capacity. GNSS-derived PWV with a high spatiotemporal resolution has become an important source of observations in meteorology, particularly for severe weather conditions, for water vapor is not well sampled in the current meteorological observing systems. In this study, an empirical atmospheric weighted mean temperature ( T m ) model for Guilin is established using the radiosonde data from 2012 to 2017. Then, the observations at 11 GNSS stations in Guilin are used to investigate the spatiotemporal features of GNSS-derived PWV under the heavy rainfalls from June to July 2017. The results show that the new T m model in Guilin has better performance with the mean bias and Root Mean Square (RMS) of − 0.51 and 2.12 K, respectively, compared with other widely used models. Moreover, the GNSS PWV estimates are validated with the data at Guilin radiosonde station. Good agreements are found between GNSS-derived PWV and radiosonde-derived PWV with the mean bias and RMS of − 0.9 and 3.53 mm, respectively. Finally, an investigation on the spatiotemporal characteristics of GNSS PWV during heavy rainfalls in Guilin is performed. It is shown that variations of PWV retrieved from GNSS have a direct relationship with the in situ rainfall measurements, and the PWV increases sharply before the arrival of a heavy rainfall and decreases to a stable state after the cease of the rainfall. It also reveals the moisture variation in several regions of Guilin during a heavy rainfall, which is significant for the monitoring of rainfalls and weather forecast.
Sprache
Englisch
Identifikatoren
ISSN: 2662-1363
eISSN: 2662-1363
DOI: 10.1186/s43020-021-00046-y
Titel-ID: cdi_doaj_primary_oai_doaj_org_article_0434722f4e60477eb8b898796852025f

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