Abstract
AbstractThis study explores multi‐sensor data assimilation (DA) using synthetic Advanced Microwave Scanning Radiometer (AMSR‐E) passive microwave brightness temperature spectral differences () and synthetic Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage (TWS) retrievals to improve estimates of snow water equivalent (SWE), subsurface water storage, and TWS across snow‐covered terrain. Results show that multi‐sensor DA improves SWE estimates by reducing the RMSE by 14.1% relative to a model‐only simulation. Multi‐sensor assimilation also yields the smallest TWS RMSE (reduced by 13.0% relative to a model‐only simulation). However, multi‐sensor DA does not always yield complementary updates, and can sometimes lead to conflicting changes to SWE, where the assimilation of synthetic generates positive SWE increments while the assimilation of synthetic TWS removes SWE, which can ultimately degrade the posterior SWE estimates. This synthetic experiment provides useful insight for future DA experiments using real‐world AMSR‐E/AMSR‐2 observations and GRACE/GRACE‐FO TWS retrievals to better characterize terrestrial freshwater storage across regional scales.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.