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Representing Cloud Water Content of Extensive Cloud Systems Over Land Using Satellite‐Based Passive Microwave Observations With a Coupled Land and Atmosphere Assimilation Method
Author(s) -
Seto R.,
Koike T.,
Kanae S.
Publication year - 2018
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1029/2018jd028864
Subject(s) - environmental science , satellite , cloud computing , remote sensing , liquid water path , cloud height , data assimilation , atmosphere (unit) , meteorology , geostationary orbit , cloud cover , computer science , geology , geography , aerospace engineering , engineering , operating system
We proposed a method to estimate cloud water content (CWC) over land using satellite‐based passive microwave brightness temperatures (TBs) at multiple‐kilometer resolutions with land and atmosphere assimilation to overcome the challenges associated with estimating the CWC of broad cloud systems over land. This method enables estimation of broad cloud systems over land using multifrequency TBs, which have different sensitivities to land and cloud, by concurrently optimizing land emissions and CWC estimates from models. Estimated CWC was validated using vertical two‐dimensional CloudSat products (2B‐CWC‐RVOD and 2C‐ICE). The results were in good accordance with 2B‐CWC‐RVOD in terms of cloud water path and the vertical distribution of CWC but represented underestimates in comparison to 2C‐ICE. We performed sensitivity analysis of CWC estimates of TBs and cloud top height. The results suggested that the error in TBs is not large uncertainty, and that cloud top height affects the estimated CWC more sensitively than TBs. The addition of cloud top height information, as determined from CloudSat products as a constraint of optimization, allows further improvement of the vertical distributions of CWC in case studies. Sensitivity analysis indicated that it is effective to utilize cloud top height data from other satellites, such as next‐generation geostationary meteorological satellites, within an error of about ±600 m for further development of our method. This study revealed that the proposed method has great potential to provide unprecedented data for cloud water path and CWC that are continuously distributed over land and ocean with adequate accuracy.