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Global Ensemble Learning-Based Refined Models for VMF1-FC Forecasted Weighted Mean Temperature

Remote Sensing
Accurately forecasting the weighted mean temperature (Tm) is critical for converting the zenith wet delay (ZWD) into global navigation satellite system (GNSS)-based precipitable water vapor (PWV) for real-time sensing and forecasting applications.
Liying Cao, Jizhang Sang, Feijuan Li, Bao Zhang +3 more
doaj +1 more source

Methods and Evaluation of AI-Based Meteorological Models for Zenith Tropospheric Delay Prediction

Remote Sensing
Zenith Tropospheric Delay (ZTD) is a significant error source affecting the accuracy of certain space geodetic measurements. This study evaluates the performance of Artificial Intelligence (AI) based meteorological models, such as Fengwu and Pangu, in ...
Si Xiong +4 more
doaj +1 more source

Evaluation of Tropospheric Delays over China from the High-Resolution Pangu-Weather Model at Multiple Forecast Scales

Remote Sensing
Tropospheric delay is recognized as one of the main error sources affecting Global Navigation Satellite System (GNSS) positioning accuracy. Previous studies have only employed artificial intelligence-based weather models with low temporal resolution for ...
Shuangping Li +5 more
doaj +1 more source

Automatic generation of creative text in Portuguese: an overview. [PDF]