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Seasonal variations of vertical crustal motion in Australia observed by joint analysis of GPS and GRACE / Hao Wang in Geomatics and Information Science of Wuhan University, vol 47 n° 2 (February 2022)
Titre : Seasonal variations of vertical crustal motion in Australia observed by joint analysis of GPS and GRACE Type de document : Article/Communication Auteurs : Hao Wang, Auteur ; Jianping Yue, Auteur ; Yunfei Xiang, Auteur Année de publication : 2022 Article en page(s) : pp 197 - 207 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] analyse de spectre singulier
[Termes IGN] Australie
[Termes IGN] déformation verticale de la croute terrestre
[Termes IGN] données GPS
[Termes IGN] données GRACE
[Termes IGN] transformation en ondelettes
[Termes IGN] variation saisonnièreRésumé : (auteur) Objectives There are obvious seasonal variations in the GPS height time series, which affect the improvement of precision and can be corrected by both mathematical modelling and geophysical mechanisms. Compared to least square fitting, singular spectrum analysis (SSA) can extract random seasonal signals effectively through signal reconstruction, which is unaffected by the assumed sinusoidal waves. According to the elastic loading theory, the gravity recovery and climate experiment (GRACE) can be used to calculate the vertical surface displacement caused by changes in terrestrial water storage. Methods This paper mainly studies the feasibility of correcting the seasonal variations in GPS heights using SSA and GRACE inversion results. The height time series of 27 GPS stations in Australia with a time span of from 5 to 10 years were chosen and combined with GRACE simultaneous inversions. Results Because the spatial resolutions of GRACE are coarse and the loading displacement is much more sensitive to near-field mass changes than far-field ones, the amplitudes of GRACE-inferred hydrological loading deformations are significantly smaller than GPS. The weighted root mean square (WRMS) are reduced at 22 stations after GRACE-inferred displacement corrections, and the correlation coefficients between deformations estimated by GPS and GRACE range from 0.12 to 0.78 with a mean value of 0.43, indicating that GPS and GRACE results have good consistency and correlation. SSA is used to extract the annual signals of vertical displacements derived from GPS and GRACE, and contribution rates of singular spectral variance of annual signals are 21.60% and 34.48%, respectively, expressing that annual signals are the main components of GRACE-inferred results. Geographical climatic conditions have a significant impact on the consistency of annual signals derived from GPS and GRACE. Compared with the arid areas in central and western Australia, the amplitude and phase of annual signals derived from GPS and GRACE are more consistent in the northern region with seasonal rainfall. Furthermore, cross wavelet transform (XWT) finds that the vertical displacement series derived from GPS and GRACE of each station have a significant resonance period of one year. The circular average phase angles of GPS/GRACE at the period closet to 1 cycle per year (cpy) outside the cone of influence range from -74.03° to 67.23°. The mean XWT-based semblances range from 0.28 to 0.99 with an average value of 0.79, showing that there is a significant positive correlation between the annual variations derived from GPS and GRACE. Conclusions Overall, GRACE-inferred deformations can explain the annual variations of GPS-derived displacements, particularly in areas with high hydrological loading. It is possible to correct the annual signals of GPS heights by GRACE inversions, but the effect is not as good as the SSA-filtered annual signals. Numéro de notice : A2022-150 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.13203/j.whugis20190282 Date de publication en ligne : 05/02/2022 En ligne : http://dx.doi.org/10.13203/j.whugis20190282 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100109
in Geomatics and Information Science of Wuhan University > vol 47 n° 2 (February 2022) . - pp 197 - 207[article]
Titre : Study on the inter-annual hydrology-induced deformations in Europe using GRACE and hydrological models Type de document : Article/Communication Auteurs : Artur Lenczuk, Auteur ; Grzegorz Leszczuk, Auteur ; Anna Klos, Auteur Année de publication : 2020 Article en page(s) : pp 393 – 403 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] amplitude
[Termes IGN] analyse de spectre singulier
[Termes IGN] bassin hydrographique
[Termes IGN] déformation de la croute terrestre
[Termes IGN] données GLDAS
[Termes IGN] données GRACE
[Termes IGN] Europe (géographie politique)
[Termes IGN] modèle hydrographique
[Termes IGN] surcharge hydrologique
[Termes IGN] variation saisonnièreRésumé : (auteur) Earth’s crust deforms in various time and spatial resolutions. To estimate them, geodetic observations are widely employed and compared to geophysical models. In this research, we focus on the Earth’s crust deformations resulting from hydrology mass changes, as observed by GRACE (Gravity Recovery and Climate Experiment) gravity mission and modeled using WGHM (WaterGAP Global Hydrological Model) and GLDAS (Global Land Data Assimilation System), hydrological models. We use the newest release of GRACE Level-2 products, i. e. RL06, provided by the CSR (Center for Space Research, Austin) analysis center in the form of a mascon solution. The analysis is performed for the European area, divided into 29 river basins. For each basin, the average signal is estimated. Then, annual amplitudes and trends are calculated. We found that the eastern part of Europe is characterized by the largest annual amplitudes of hydrology-induced Earth’s crust deformations, which decrease with decreasing distance to the Atlantic coast. GLDAS largely overestimates annual amplitudes in comparison to GRACE and WGHM. Hydrology models underestimate trends, which are observed by GRACE. For the basin-related average signals, we also estimate the non-linear variations over time using the Singular Spectrum Analysis (SSA). For the river basins situated on the southern borderline of Europe and Asia, large inter-annual deformations between 2004 and 2009 reaching a few millimeters are found; they are related to high precipitation and unexpectedly large drying. They were observed by GRACE but mismodelled in the GLDAS and WGHM models. Few smaller inter-annual deformations were also observed by GRACE between 2002-2017 for central and eastern European river basins, but these have been also well-covered by the WGHM and GLDAS hydrological models. Numéro de notice : A2020-677 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2020-0017 Date de publication en ligne : 27/10/2020 En ligne : https://doi.org/10.1515/jag-2020-0017 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96170
in Journal of applied geodesy > vol 14 n° 4 (October 2020) . - pp 393 – 403[article]
Titre : Data-adaptive spatio-temporal filtering of GRACE data Type de document : Article/Communication Auteurs : Paoline Prevost, Auteur ; Kristel Chanard Année de publication : 2019 Projets : 2-Pas d'info accessible - article non ouvert / Article en page(s) : pp 2034 - 2055 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal
[Termes IGN] analyse de spectre singulier
[Termes IGN] données géophysiques
[Termes IGN] données GRACE
[Termes IGN] filtrage spatiotemporel
[Termes IGN] harmonique sphériqueRésumé : (auteur) Measurements of the spatio-temporal variations of Earth’s gravity field from the Gravity Recovery and Climate Experiment (GRACE) mission have led to new insights into large spatial mass redistribution at secular, seasonal and subseasonal timescales. GRACE solutions from various processing centres, while adopting different processing strategies, result in rather coherent estimates. However, these solutions also exhibit random as well as systematic errors, with specific spatial patterns in the latter.
In order to dampen the noise and enhance the geophysical signals in the GRACE data, we propose an approach based on a data-driven spatio-temporal filter, namely the Multichannel Singular Spectrum Analysis (M-SSA). M-SSA is a data-adaptive, multivariate, and non-parametric method that simultaneously exploits the spatial and temporal correlations of geophysical fields to extract common modes of variability.
We perform an M-SSA analysis on 13 yr of GRACE spherical harmonics solutions from five different processing centres in a simultaneous setup. We show that the method allows us to extract common modes of variability between solutions, while removing solution-specific spatio-temporal errors that arise from the processing strategies. In particular, the method efficiently filters out the spurious north–south stripes, which are caused in all likelihood by aliasing, due to the imperfect geophysical correction models and low-frequency noise in measurements.
Comparison of the M-SSA GRACE solution with mass concentration (mascons) solutions shows that, while the former remains noisier, it does retrieve geophysical signals masked by the mascons regularization procedure.Numéro de notice : A2019-276 Affiliation des auteurs : Géodésie+Ext (mi2018-2019) Thématique : MATHEMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/gji/ggz409 Date de publication en ligne : 19/09/2019 En ligne : https://doi.org/10.1093/gji/ggz409 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95381
in Geophysical journal international > vol 219 n° 3 (December 2019) . - pp 2034 - 2055[article]
Titre : On the application of Monte Carlo singular spectrum analysis to GPS position time series Type de document : Article/Communication Auteurs : Seyed Mohsen Khazraei, Auteur ; Ali Reza Amiri-Simkooei, Auteur Année de publication : 2019 Article en page(s) : pp 1401 - 1418 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal
[Termes IGN] analyse de spectre singulier
[Termes IGN] bruit (théorie du signal)
[Termes IGN] bruit blanc
[Termes IGN] bruit rose
[Termes IGN] coordonnées GPS
[Termes IGN] factorisation de Cholesky
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] méthode des moindres carrés
[Termes IGN] positionnement par GPS
[Termes IGN] série temporelleRésumé : (Auteur) Singular spectrum analysis (SSA) has recently been applied to various geodetic time series studies. As a data-adaptive method, SSA is capable of extracting signals with non-constant phase and amplitudes. Although SSA is a competent method in the presence of white noise, the contribution of colored noise, having semi-periodic behavior, degrades its performance. Parts of colored noise can be absorbed in the SSA eigenmodes, which specifies signals and hence resulting in spurious modulation or losing significant signals. Signals and colored noise are thus to be discriminated in the signal identification procedure. Monte Carlo SSA (MCSSA) in its original formulation, providing a significance test against the AR(1) noise null hypothesis, can be misinterpreted when other colored noise structures contribute to the series. We propose an algorithm for MCSSA that is not limited to the AR(1) noise hypothesis. It estimates the noise model parameters using LS-VCE and generates the surrogate data using the Cholesky decomposition. The algorithm is adapted to GPS position time series where the underlying noise is a combination of white noise and flicker noise. GPS position time series, postulated real situation, are first simulated to include annual and semiannual signals plus white and flicker noise. The results indicate that MCSSA can extract the annual and semiannual signals with 2.11 and 1.25 mm amplitudes (the global mean values) from 20-year-long time series, with 95% confidence level, if flicker noise is less than 17 and 13 mm/year1/4mm/year1/4, respectively. The longer the time series or the stronger the signals are, the higher these thresholds will be. This conclusion is also verified when applying MCSSA to the up component of GPS position time series of 347 JPL stations. Numéro de notice : A2019-505 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-019-01253-x Date de publication en ligne : 08/04/2019 En ligne : https://doi.org/10.1007/s00190-019-01253-x Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93788
in Journal of geodesy > vol 93 n° 9 (September 2019) . - pp 1401 - 1418[article]
Titre : Long-term prediction of polar motion using a combined SSA and ARMA model Type de document : Article/Communication Auteurs : Y. Shen, Auteur ; Jinyun Guo, Auteur ; X. Liu, Auteur ; Qiaoli Kong, Auteur ; Linxi Guo, Auteur ; Li Wang, Auteur Année de publication : 2018 Article en page(s) : pp 333 - 343 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] analyse de spectre singulier
[Termes IGN] analyse en composantes principales
[Termes IGN] modèle de simulation
[Termes IGN] mouvement du pôleMots-clés libres : modèle ARMA Résumé : (Auteur) To meet the need for real-time and high-accuracy predictions of polar motion (PM), the singular spectrum analysis (SSA) and the autoregressive moving average (ARMA) model are combined for short- and long-term PM prediction. According to the SSA results for PM and the SSA prediction algorithm, the principal components of PM were predicted by SSA, and the remaining components were predicted by the ARMA model. In applying this proposed method, multiple sets of PM predictions were made with lead times of two years, based on an IERS 08 C04 series. The observations and predictions of the principal components correlated well, and the SSA + ARMA model effectively predicted the PM. For 360-day lead time predictions, the root-mean-square errors (RMSEs) of PMx and PMy were 20.67 and 20.42 mas, respectively, which were less than the 24.46 and 24.78 mas predicted by IERS Bulletin A. The RMSEs of PMx and PMy in the 720-day lead time predictions were 28.61 and 27.95 mas, respectively. Numéro de notice : A2018-061 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-017-1065-3 Date de publication en ligne : 12/09/2017 En ligne : https://doi.org/10.1007/s00190-017-1065-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89397
in Journal of geodesy > vol 92 n° 3 (March 2018) . - pp 333 - 343[article]
