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- W302435047 abstract "Assimilation of remotely sensed land surface observations into regional to global scale numerical models have the potential to significantly advance our ability, to assess, understand, and predict surface water, energy, and carbon cycles. This session seeks to assess the state-of-the-art in data assimilation methods for integrating land surface remote sensing and modeling, with a focus on practical applications and techniques. Assimilated land surface variables of interest include (but are not limited to, soil moisture, surface temperature, snowpack, streamflow, vegetation dynamics, and carbon storage. Contributions describing the development of practical land surface data assimilation methods, multivariate land surface data assimilation strategies, evaluation of the required accuracy and resolution of remote sensing observations, the effects of scale, process complexity, and uncertainty on data assimilation, and the optimal treatment of model and observation errors are encouraged." @default.
- W302435047 created "2016-06-24" @default.
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- W302435047 date "2001-01-01" @default.
- W302435047 modified "2023-09-27" @default.
- W302435047 title "Advances in Land Data Assimilation Systems" @default.
- W302435047 hasPublicationYear "2001" @default.
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