Spatio-temporal analysis of GRACE gravity field variations using the principal component analysis
Gravity Recovery and Climate Experiment (GRACE) mission has amplified the knowledge of both static and time-variable part of the Earth’s gravity field. Currently, GRACE maps the Earth’s gravity field with a near-global coverage and over a five year period, which makes it possible to apply statistica...
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
Curtin University
2008
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/957 |
| _version_ | 1848743530252468224 |
|---|---|
| author | Anjasmara, Ira Mutiara |
| author_facet | Anjasmara, Ira Mutiara |
| author_sort | Anjasmara, Ira Mutiara |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Gravity Recovery and Climate Experiment (GRACE) mission has amplified the knowledge of both static and time-variable part of the Earth’s gravity field. Currently, GRACE maps the Earth’s gravity field with a near-global coverage and over a five year period, which makes it possible to apply statistical analysis techniques to the data. The objective of this study is to analyse the most dominant spatial and temporal variability of the Earth’s gravity field observed by GRACE using a combination of analytical and statistical methods such as Harmonic Analysis (HA) and Principal Component Analysis (PCA). The HA is used to gain general information of the variability whereas the PCA is used to find the most dominant spatial and temporal variability components without having to introduce any presetting. The latter is an important property that allows for the detection of anomalous or a-periodic behaviour that will be useful for the study of various geophysical processes such as the effect from earthquakes. The analyses are performed for the whole globe as well as for the regional areas of: Sumatra- Andaman, Australia, Africa, Antarctica, South America, Arctic, Greenland, South Asia, North America and Central Europe. On a global scale the most dominant temporal variation is an annual signal followed by a linear trend. Similar results mostly associated to changing land hydrology and/or snow cover are obtained for most regional areas except over the Arctic and Antarctic where the secular trend is the prevailing temporal variability.Apart from these well-known signals, this contribution also demonstrates that the PCA is able to reveal longer periodic and a-periodic signal. A prominent example for the latter is the gravity signal of the Sumatra-Andaman earthquake in late 2004. In an attempt to isolate these signals, linear trend and annual signal are removed from the original data and the PCA is once again applied to the reduced data. For a complete overview of these results the most dominant PCA modes for the global and regional gravity field solutions are presented and discussed. |
| first_indexed | 2025-11-14T05:47:02Z |
| format | Thesis |
| id | curtin-20.500.11937-957 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T05:47:02Z |
| publishDate | 2008 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-9572017-02-20T06:40:31Z Spatio-temporal analysis of GRACE gravity field variations using the principal component analysis Anjasmara, Ira Mutiara Earth’s gravity field GRACE spatial and temporal variability PCA Gravity Recovery and Climate Experiment (GRACE) mission has amplified the knowledge of both static and time-variable part of the Earth’s gravity field. Currently, GRACE maps the Earth’s gravity field with a near-global coverage and over a five year period, which makes it possible to apply statistical analysis techniques to the data. The objective of this study is to analyse the most dominant spatial and temporal variability of the Earth’s gravity field observed by GRACE using a combination of analytical and statistical methods such as Harmonic Analysis (HA) and Principal Component Analysis (PCA). The HA is used to gain general information of the variability whereas the PCA is used to find the most dominant spatial and temporal variability components without having to introduce any presetting. The latter is an important property that allows for the detection of anomalous or a-periodic behaviour that will be useful for the study of various geophysical processes such as the effect from earthquakes. The analyses are performed for the whole globe as well as for the regional areas of: Sumatra- Andaman, Australia, Africa, Antarctica, South America, Arctic, Greenland, South Asia, North America and Central Europe. On a global scale the most dominant temporal variation is an annual signal followed by a linear trend. Similar results mostly associated to changing land hydrology and/or snow cover are obtained for most regional areas except over the Arctic and Antarctic where the secular trend is the prevailing temporal variability.Apart from these well-known signals, this contribution also demonstrates that the PCA is able to reveal longer periodic and a-periodic signal. A prominent example for the latter is the gravity signal of the Sumatra-Andaman earthquake in late 2004. In an attempt to isolate these signals, linear trend and annual signal are removed from the original data and the PCA is once again applied to the reduced data. For a complete overview of these results the most dominant PCA modes for the global and regional gravity field solutions are presented and discussed. 2008 Thesis http://hdl.handle.net/20.500.11937/957 en Curtin University fulltext |
| spellingShingle | Earth’s gravity field GRACE spatial and temporal variability PCA Anjasmara, Ira Mutiara Spatio-temporal analysis of GRACE gravity field variations using the principal component analysis |
| title | Spatio-temporal analysis of GRACE gravity field variations using the principal component analysis |
| title_full | Spatio-temporal analysis of GRACE gravity field variations using the principal component analysis |
| title_fullStr | Spatio-temporal analysis of GRACE gravity field variations using the principal component analysis |
| title_full_unstemmed | Spatio-temporal analysis of GRACE gravity field variations using the principal component analysis |
| title_short | Spatio-temporal analysis of GRACE gravity field variations using the principal component analysis |
| title_sort | spatio-temporal analysis of grace gravity field variations using the principal component analysis |
| topic | Earth’s gravity field GRACE spatial and temporal variability PCA |
| url | http://hdl.handle.net/20.500.11937/957 |