The world witnessed an accelerated development of various types of meteorological observing technology, an evolution of numerical weather prediction (NWP) models from single atmospheric component to coupled multi-components of the earth system, as well as the multi graphics processing unit technology in computer sciences, a new era for rapidly advancing data assimilation science and technology development has arrived. The multi-source data assimilation is important not only for NWP but also for further understanding of global and regional weather changes. This article firstly selectively reviews past methods of multi-source data assimilation. New opportunities are then discussed for future development of data assimilation system framework, for innovative uses of high-resolution observations, and for applications of artificial intelligence machine learning in meteorological data assimilation.
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