| Issue |
E3S Web Conf.
Volume 38, 2018
2018 4th International Conference on Energy Materials and Environment Engineering (ICEMEE 2018)
|
|
|---|---|---|
| Article Number | 03009 | |
| Number of page(s) | 5 | |
| Section | Water Conservancy and Civil Engineering | |
| DOI | https://doi.org/10.1051/e3sconf/20183803009 | |
| Published online | 04 June 2018 | |
One-dimensional soil temperature assimilation experiment based on unscented particle filter and Common Land Model
1
College of Civil Engineering, Fuzhou University, Fuzhou 350116, China
2
State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China
* Corresponding author: Email: fuxiaolei518@163.com
Data assimilation is an efficient way to improve the simulation/prediction accuracy in many fields of geosciences especially in meteorological and hydrological applications. This study takes unscented particle filter (UPF) as an example to test its performance at different two probability distribution, Gaussian and Uniform distributions with two different assimilation frequencies experiments (1) assimilating hourly in situ soil surface temperature, (2) assimilating the original Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) once per day. The numerical experiment results show that the filter performs better when increasing the assimilation frequency. In addition, UPF is efficient for improving the soil variables (e.g., soil temperature) simulation/prediction accuracy, though it is not sensitive to the probability distribution for observation error in soil temperature assimilation.
© The Authors, published by EDP Sciences, 2018.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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