Precipitable water vapor (PWV) is an important and active part of the atmosphere. As known, microwave PWV retrieval well applied for ocean but challenging over land. In this article, we creatively established a spatial model land using back-propagation (BP) neural network to combine high precision ground-based Global Navigation Satellite System (GNSS) data continuity satellite-borne data. Three...

Abstract. The neXtSIM-F (neXtSIM forecast) forecasting system consists of a stand-alone sea ice model, neXtSIM (neXt-generation Sea Ice Model), forced by the TOPAZ ocean forecast and ECMWF atmospheric forecast, combined with daily data assimilation concentration. It uses novel brittle Bingham–Maxwell (BBM) rheology, making it first based on continuum model not to use viscous–plastic (VP) rheolo...

The sea ice cover is changing rapidly in polar regions, and products with high temporal spatial resolution are of great importance studying global climate change navigation. In this paper, an map generation model based on Moderate-Resolution Imaging Spectroradiometer (MODIS) reflectance bands constructed to obtain data a resolution. By constructing training sample library using multi-feature fu...

The modelling of Earth observation data is a challenging problem, typically approached by either purely mechanistic or data-driven methods. Mechanistic models encode the domain knowledge and physical rules governing system. Such models, however, need correct specification all interactions between variables in problem appropriate parameterization challenge itself. On other hand, machine learning...

Satellite-derived soil moisture (SM) products have become an important information source for the study of land surface processes in hydrology and monitoring. Characterizing estimating memory persistence from satellite observations is paramount relevance, has deep implications ecology, water management, climate modeling. In this work, we address problem SM estimation microwave sensors using sev...