| Summary: | Proper dynamic modelling of the troposphere wet delay using the Global Navigation Satellite Systems (GNSS) measurements is important in precise point positioning and in estimation of the Perceptible Water Vapour (PWV) for weather forecast. The random walk (RW) and the first-order Gauss-Markov (GM) autocorrelation models are commonly used for this purpose. However, it was found that these models consistently underestimate the temporal correlations that exist among the ZWD estimates. Therefore, a new dynamic model is proposed. The performance of the proposed model in following the autocorrelation of actual data is demonstrated and its impact on the near-real time estimation of the ZWD was tested and compared to that of the GM and RW models. Results showed that the proposed model outperformed these models. When the computed ZWD were used to compute PWV, their estimated values were very close to actual PWV data measured by radiosonde with differences less than 1 mm.
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