A method to estimate the cloud water content (CWC) over land at several-kilometer resolutions using satellite-based passive microwave remote sensing was proposed in this study. Satellite-based microwave remote sensing is an effective way to estimate CWC of extensive and heterogeneous cloud systems all at once and over a long period, but it is challenging to estimate CWC over land due to not only complexities of cloud processes but also uncertainties in representing strong and heterogeneous land radiation. Our method overcomes the difficulty of retrieving clouds over land by simultaneously optimizing land state (land radiation) and atmospheric fields (clouds and cloud-affected atmosphere) over land using multi-frequency microwave brightness temperatures. Moreover, this method can concurrently assimilate the estimated CWC into the physical models and produce successive time evolution of the cloud systems. In this study, the CWC was estimated from AMSR-E brightness temperature and validated by CloudSat products. The results showed that estimated CWC was in good accordance with CloudSat products in terms of cloud water path and the vertical distribution of CWC. In addition, we examined the uncertainties of this method by sensitivity analysis of CWC estimates to TBs and cloud top heights. The results suggested that the sensitivity of estimation to uncertainties in TBs is not so large, and those in cloud top heights affects the estimated CWC more sensitively than TBs. The addition of cloud top height information from other satellite observations as a constraint of optimization allows further improvement of the vertical distributions of CWC. This study revealed that the proposed method has great potential to provide unprecedented data for CWC with adequate accuracy, which is continuously distributed over land and ocean.
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