Towards Assimilation of Terrestrial Water Storage Derived from GRACE and Ground-based GPS into a Land Surface Model
Abstract
Terrestrial water storage (TWS) plays a critical role in the hydrologic cycle and climate system. The launch of GRACE and GRACE Follow-On (GRACE-FO) missions provide an unprecedented opportunity in monitoring the change in TWS at a global scale, but the spatial and temporal resolution provided by GRACE / GRACE-FO is too coarse for many hydrologic applications. In order to mitigate the coarse resolution provided by GRACE and GRACE-FO, as well as to fill in the gap in time between GRACE and GRACE-FO missions, this study explores the use of ground-based GPS observations of vertical displacement to improve our understanding of TWS and its variability at a finer spatial and temporal scale.
GPS pre-processing is first performed to remove the effects of non-hydrologic loadings in GPS observations of vertical displacement, such as secular motions and atmospheric loadings. The pre-processed GPS observations of vertical displacement are then used in an inverse model in order to estimate gridded TWS. The inverse model is based on Green's function to solve for the spatially-continuous TWS variations that dictate the measured vertical displacement at the ground-based GPS stations. Results are compared against TWS retrievals derived from GRACE and the NASA Catchment Land Surface Model as a means of evaluation. Preliminary results show that the inverse method provides good accuracy in estimating TWS with a slight overestimation during the winter and a small underestimation during the summer. The validated GPS-based TWS is then assimilated into an advanced land surface model using an ensemble Kalman filter in order to investigate the potential of improving prediction accuracy of modeled TWS. Three simulation cases include: (1) open loop (OL), (2) GRACE-DA (i.e., using GRACE-based TWS observations during assimilation), and (3) GPS-DA (i.e., using GPS-based TWS observations during assimilation). Results from these three runs are evaluated using in-situobservations of groundwater, soil moisture, and snow water equivalent.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFM.H43M2243Y
- Keywords:
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- 1836 Hydrological cycles and budgets;
- HYDROLOGY;
- 1847 Modeling;
- HYDROLOGY;
- 1855 Remote sensing;
- HYDROLOGY;
- 1873 Uncertainty assessment;
- HYDROLOGY