Estimating snow mass in North America through assimilation of AMSR-E brightness temperature observations using the Catchment land surface model and support vector machines
| dc.contributor.advisor | Forman, Barton | |
| dc.contributor.author | Xue, Yuan | |
| dc.contributor.author | Forman, Barton | |
| dc.contributor.author | Reichle, Rolf | |
| dc.date.accessioned | 2018-04-16T12:14:46Z | |
| dc.date.available | 2018-04-16T12:14:46Z | |
| dc.date.issued | 2018-04-16 | |
| dc.description.abstract | To estimate snow mass across North America, multi-frequency brightness temperature (Tb) observations collected by the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) from 2002 to 2011 were assimilated into the Catchment land surface model using a support vector machine (SVM) as the observation operator as part of a one-dimensional ensemble Kalman filter. The performance of the assimilation system is evaluated through comparisons against ground-based measurements and publicly-available reference SWE and snow depth products. Assimilation estimates agree better with ground-based snow depth measurements than model-only (“open loop”, or OL) estimates in approximately 82% (56 out of 62) of pixels that are colocated with at least two ground-based stations. In addition, assimilation estimates tend to agree better with all snow products over tundra snow, alpine snow, maritime snow, as well as sparsely-vegetated snow-covered pixels. Improvements in snow mass via assimilation translate into improvements in cumulative runoff estimates when compared against discharge measurements in 11 out of 13 major snow-dominated basins in Alaska. These results prove that a SVM can serve as an efficient and effective observation operator for snow mass estimation within a radiance assimilation system. | en_US |
| dc.description.sponsorship | NASA | en_US |
| dc.description.uri | https://doi.org/10.1029/2017WR022219 | |
| dc.identifier | https://doi.org/10.13016/M2HH6C789 | |
| dc.identifier.uri | http://hdl.handle.net/1903/20570 | |
| dc.relation.isAvailableAt | A. James Clark School of Engineering | en_us |
| dc.relation.isAvailableAt | Civil & Environmental Engineering | en_us |
| dc.relation.isAvailableAt | Digital Repository at the University of Maryland | en_us |
| dc.relation.isAvailableAt | University of Maryland (College Park, MD) | en_us |
| dc.subject | snow | en_US |
| dc.subject | model | en_US |
| dc.subject | data assimilation | en_US |
| dc.subject | passive microwave | en_US |
| dc.subject | brightness temperature | en_US |
| dc.subject | support vector machine | en_US |
| dc.title | Estimating snow mass in North America through assimilation of AMSR-E brightness temperature observations using the Catchment land surface model and support vector machines | en_US |
| dc.type | Dataset | en_US |
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