An hourly 0.02° total precipitable water dataset for all-weather conditions over the Tibetan Plateau through the fusion of observations of geostationary and multi-source microwave satellites

Abstract. The Tibetan Plateau (TP), known as the “Asian Water Tower”, plays a critical role in the regulation of the water cycle in the region. Obtaining high spatiotemporal resolution, and all-weather total precipitable water (TPW) data is essential for understanding water vapor transport mechanisms, improving precipitation forecasting, and managing regional water resources over the TP. However, existing single-sensor remote sensing techniques cannot provide high spatiotemporal resolution TPW data under cloudy conditions. Multi-source fusion approaches often produce anomalous distributions in the fused TPW data due to inter-sensor biases, particularly over the complex terrain of the TP. This study proposed a multi-source remote sensing TPW fusion framework that integrates TPW products from eight microwave satellites and the Himawari-8/9 (H8/9) geostationary satellite to produce an all-weather TPW data with the highest spatiotemporal resolution at present. Methodologically, two correction strategies were developed. First, a bias correction approach was proposed using H8/9 TPW data as a reference to calibrate multi-source microwave remote sensing TPW and reduce inter-sensor discrepancies. Second, an adaptive correction method was created to improve the accuracy and spatial continuity of the fused TPW data under cloudy conditions. Based on the newly developed fusion framework, an all-weather TPW dataset with hourly temporal and 0.02° spatial resolution covering the TP from 2016 to 2022 was produced for the first time. The new dataset has been published by the National Tibetan Plateau Data Center and is available at: https://doi.org/10.11888/Atmos.tpdc.301518. Taking the 2017 product as an example, it was verified against GNSS TPW. The RMSE of the fused TPW product at the hourly scale was 3.79 mm, which was 10.82 % and 6.19 % lower than MIMIC-TPW2 and ERA5, respectively. Compared to ERA5 with a spatial resolution of 0.25°, the fused product achieves a 12.5-fold improvement in spatial resolution, which make it possible to significantly grasp the transportation of water vapor in the valley of Yarlung Zsangbo River. It also demonstrates higher reliability in station-sparse regions, providing high-quality, high-resolution vapor data to support vapor flux estimation and forecasting of extreme weather events over the TP.