Filtering GRACE temporal gravity field solutions using ensemble empirical mode decomposition approach
Due to the strong noise that exists in GRACE (Gravity Recovery and Climate Experiment) temporal gravity field solutions, geophysical signals are normally drowned which need many effective filtering approaches. Considering the advantage of the ensemble empirical mode decomposition (EEMD) approach, we...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-03-01
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| Series: | Frontiers in Earth Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/feart.2023.1132862/full |
| _version_ | 1811157670617415680 |
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| author | Changmin Huan Fengwei Wang Shijian Zhou Xiaomeng Qiu |
| author_facet | Changmin Huan Fengwei Wang Shijian Zhou Xiaomeng Qiu |
| author_sort | Changmin Huan |
| collection | DOAJ |
| description | Due to the strong noise that exists in GRACE (Gravity Recovery and Climate Experiment) temporal gravity field solutions, geophysical signals are normally drowned which need many effective filtering approaches. Considering the advantage of the ensemble empirical mode decomposition (EEMD) approach, we used the EEMD to filter the noise in this study together with the empirical mode decomposition (EMD) for comparisons. EMD method is a spectrum analysis method, which is very effective for non-stationary signals. EMD process is essentially a means to process non-stationary signals. It has been applied in many fields in recent years. Considering the characteristics of the spherical harmonic coefficient model that the noise level higher with the increasing degree, we divided the gravity field solutions into two parts (degrees 2–28 and degrees 29–60) based on the ratios of the latitude-weighted root mean square (RMS) over the land and ocean signals when adopting different truncated degrees. For the real GRACE solution experiments, the results show that the fitting errors of EEMD approach are always smaller than those of EMD approach, and the mean RMS ratio of EEMD is 3.45, larger than 3.40 of EMD. The simulation results show that the latitude weighted root mean square errors for EEMD approach are smaller than those of EMD, indicating that EEMD can extract the geophysical signals more accurately. Therefore, it is reasonable to conclude that EEMD performs better than EMD for filtering GRACE solutions. |
| first_indexed | 2024-04-10T05:11:15Z |
| format | Article |
| id | doaj.art-20b32759244e49d28f402a9d52925098 |
| institution | Directory Open Access Journal |
| issn | 2296-6463 |
| language | English |
| last_indexed | 2024-04-10T05:11:15Z |
| publishDate | 2023-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Earth Science |
| spelling | doaj.art-20b32759244e49d28f402a9d529250982023-03-09T07:24:44ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632023-03-011110.3389/feart.2023.11328621132862Filtering GRACE temporal gravity field solutions using ensemble empirical mode decomposition approachChangmin Huan0Fengwei Wang1Shijian Zhou2Xiaomeng Qiu3College of Surveying and Mapping Engineering, East China University of Technology, Nanchang, ChinaState Key Laboratory of Marine Geology, Tongji University, Shanghai, ChinaNanchang Hangkong University, Nanchang, ChinaGandong College, Fuzhou, ChinaDue to the strong noise that exists in GRACE (Gravity Recovery and Climate Experiment) temporal gravity field solutions, geophysical signals are normally drowned which need many effective filtering approaches. Considering the advantage of the ensemble empirical mode decomposition (EEMD) approach, we used the EEMD to filter the noise in this study together with the empirical mode decomposition (EMD) for comparisons. EMD method is a spectrum analysis method, which is very effective for non-stationary signals. EMD process is essentially a means to process non-stationary signals. It has been applied in many fields in recent years. Considering the characteristics of the spherical harmonic coefficient model that the noise level higher with the increasing degree, we divided the gravity field solutions into two parts (degrees 2–28 and degrees 29–60) based on the ratios of the latitude-weighted root mean square (RMS) over the land and ocean signals when adopting different truncated degrees. For the real GRACE solution experiments, the results show that the fitting errors of EEMD approach are always smaller than those of EMD approach, and the mean RMS ratio of EEMD is 3.45, larger than 3.40 of EMD. The simulation results show that the latitude weighted root mean square errors for EEMD approach are smaller than those of EMD, indicating that EEMD can extract the geophysical signals more accurately. Therefore, it is reasonable to conclude that EEMD performs better than EMD for filtering GRACE solutions.https://www.frontiersin.org/articles/10.3389/feart.2023.1132862/fullGRACEensemble empirical mode decompositionequivalent water heightcombined filteringtime variable gravity |
| spellingShingle | Changmin Huan Fengwei Wang Shijian Zhou Xiaomeng Qiu Filtering GRACE temporal gravity field solutions using ensemble empirical mode decomposition approach Frontiers in Earth Science GRACE ensemble empirical mode decomposition equivalent water height combined filtering time variable gravity |
| title | Filtering GRACE temporal gravity field solutions using ensemble empirical mode decomposition approach |
| title_full | Filtering GRACE temporal gravity field solutions using ensemble empirical mode decomposition approach |
| title_fullStr | Filtering GRACE temporal gravity field solutions using ensemble empirical mode decomposition approach |
| title_full_unstemmed | Filtering GRACE temporal gravity field solutions using ensemble empirical mode decomposition approach |
| title_short | Filtering GRACE temporal gravity field solutions using ensemble empirical mode decomposition approach |
| title_sort | filtering grace temporal gravity field solutions using ensemble empirical mode decomposition approach |
| topic | GRACE ensemble empirical mode decomposition equivalent water height combined filtering time variable gravity |
| url | https://www.frontiersin.org/articles/10.3389/feart.2023.1132862/full |
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