Water vapor estimation using digital terrestrial broadcasting waves
| Autor: | Jun Amagai, Satoshi Yasuda, Tadahiro Goto, Toshio Iguchi, Seiji Kawamura, Kuniyasu Imamura, Shigeo Sugitani, Hiroshi Hanado, R. Ichikawa, Nobuyasu Shiga, Hiroki Ohta, Hironori Iwai, Masayuki K. Yamamoto, Kouta Kido, Miho Fujieda |
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| Rok vydání: | 2017 |
| Předmět: |
010504 meteorology & atmospheric sciences
Severe weather System of measurement Time resolution Propagation delay Software-defined radio Condensed Matter Physics 01 natural sciences 010309 optics Data assimilation Broadcasting (networking) 0103 physical sciences General Earth and Planetary Sciences Environmental science Electrical and Electronic Engineering Physics::Atmospheric and Oceanic Physics Water vapor 0105 earth and related environmental sciences Remote sensing |
| Zdroj: | Radio Science. 52:367-377 |
| ISSN: | 0048-6604 |
| Popis: | A method of estimating water vapor (propagation delay due to water vapor) using digital terrestrial broadcasting waves is proposed. Our target is to improve the accuracy of numerical weather forecast for severe weather phenomena such as localized heavy rainstorms in urban areas through data assimilation. In this method, we estimate water vapor near a ground surface from the propagation delay of digital terrestrial broadcasting waves. A real-time delay measurement system with a software-defined radio technique is developed and tested. The data obtained using digital terrestrial broadcasting waves show good agreement with those obtained by ground-based meteorological observation. The main features of this observation are, no need for transmitters (receiving only), applicable wherever digital terrestrial broadcasting is available and its high time resolution. This study shows a possibility to estimate water vapor using digital terrestrial broadcasting waves. In the future, we will investigate the impact of these data toward numerical weather forecast through data assimilation. Developing a system that monitors water vapor near the ground surface with time and space resolutions of 30 s and several kilometers would improve the accuracy of the numerical weather forecast of localized severe weather phenomena. |
| Databáze: | OpenAIRE |
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