Assimilation of GNSS PWV with NCAR-RTFDDA to Improve Prediction of a Landfall Typhoon

Autor: Haishen Wang, Yubao Liu, Yuewei Liu, Yunchang Cao, Hong Liang, Heng Hu, Jingshu Liang, Manhong Tu
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Remote Sensing, Vol 14, Iss 1, p 178 (2022)
Druh dokumentu: article
ISSN: 14010178
2072-4292
DOI: 10.3390/rs14010178
Popis: Precipitable water vapor (PWV) retrieved from ground-based global navigation satellite system (GNSS) stations acquisition signal of a navigation satellite system provides high spatial and temporal resolution atmospheric water vapor. In this paper, an observation-nudging-based real-time four-dimensional data assimilation (RTFDDA) approach was used to assimilate the PWV estimated from GNSS observation into the WRF (Weather Research and Forecasting) modeling system. A landfall typhoon, “Mangkhut”, is chosen to evaluate the impact of GNSS PWV data assimilation on its track, intensity, and precipitation prediction. The results show that RTFDDA can assimilate GNSS PWV data into WRF to improve the water vapor distribution associated with the typhoon. Assimilating the GNSS PWV improved the typhoon track and intensity prediction when and after the typhoon made landfall, correcting a 5–10 hPa overestimation (too deep) of the central pressure of the typhoon at landfall. It also improved the occurrence and the intensity of the major typhoon spiral rainbands.
Databáze: Directory of Open Access Journals
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