Water vapor estimation using digital terrestrial broadcasting waves

S Kawamura, H Ohta, H Hanado, MK Yamamoto… - Radio …, 2017 - Wiley Online Library
S Kawamura, H Ohta, H Hanado, MK Yamamoto, N Shiga, K Kido, S Yasuda, T Goto…
Radio Science, 2017Wiley Online Library
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 …
Abstract
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.
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