Abstract
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.
Highlights
Academic Editor: Gad LevyWater vapor is one of most important components in the atmosphere, which plays a key role in the energy and water cycle of the earth’s climate system
The water vapor measured by ground-based global navigation satellite system (GNSS) remote sensing is in the form of Precipitable water vapor (PWV), which is not a model prognostic variable, and it cannot be directly assimilated with the nudging method
It can be water vapor in most layers is lower than that in the control experiment (CTRL) experiment and the largest seen from Figure 4 that after assimilating the GNSS PWV data, at Points A and B, the water reduction corresponds to the maximum waterthan vapor layer
Summary
Water vapor is one of most important components in the atmosphere, which plays a key role in the energy and water cycle of the earth’s climate system. Cucurull et al [5] used a 3DVAR (three-dimension variational) method to assimilate GPS PWV for modeling a heavy precipitation process in the Western Mediterranean Their results showed that the GPS PWV data improved the forecast of the wind and temperature while adjusting the humidity field. There are three main advantages of the nudging method One is that it only requires an additional trend term in the prognostic equations of the numerical weather prediction models, and it is very computing efficient, the second is that it allows effective and continuous assimilation of the observations available at high time frequency, and the third is that it achieves spin-up and dynamics-physical consistent initial conditions for the model forecast. The effect of assimilating GNSS PWV data into the WRF prediction of a landfall typhoon was evaluated using observations of the automatic weather stations (AWSs)
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