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Examples of top-selling biaryl products ( 31 , 32 ). Worldwide sales: Diovan, US$3.1 billion (2004); Micardis, US$704 million (2004); Boscalid, EUR 150 million (projected).
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We report the detection of an earthquake by a space-based measurement. The Gravity Recovery and Climate Experiment (GRACE)
satellites observed a ±15-microgalileo gravity change induced by the great December 2004 Sumatra-Andaman earthquake. Coseismic
deformation produces sudden changes in the gravity field by vertical displacement of Earth's layered...
Contexts in source publication
Context 1
... 2. Gravity changes (in m Gal) after the Sumatra- Andaman earthquake, computed from averaging and filtering the two gravity changes between two different time periods (Fig. 1, E and F).
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... : 03 0 : 01 6 The spatial distributions of aerosol over the oceans and their absorption properties are highly heterogeneous. Consequently, the estimated average impact is uncertain and should be viewed as a first approximation. The clouds sampled by the AERONET procedure do not include extended cloud systems that are sensitive to aerosol effect. The analysis applies to urban industrial pollution and aerosol produced by biomass burning rather than land-use–generated dust. The relationship between cloud cover and aerosol given by Eq. 5 can serve as a constraint on models of the aerosol and cloud interaction, independently of the cause-and-effect relationship. The robustness of the effect of aerosols on clouds, presented here, makes it more likely that most of the observed changes in the cloud cover are due to the aerosol impact. The large effect of elevated aerosol concentration on cloud cover, an increase of 0.03 (5%) in average cloud cover (Eq. 6), can have a profound effect on the hydrological cycle and climate. he devastating 26 December 2004 Sumatra- T Andaman moment magnitude undersea earthquake, ( M ) between with 9.1 a w and 9.3, ruptured more than 1000 km of a locked subduction interface near northern Sumatra, Nicobar, and the Andaman islands ( 1 ). Measure- ments from global seismic network and Global Positioning System (GPS) stations have been used to infer the coseismic slip history of this event ( 1–4 ). The earthquake permanently changed the mass distribution within Earth and has conse- quently perturbed the motion of Earth-orbiting satellites by an amount that is measurable from the ranging instrument onboard the Gravity Recovery and Climate Experiment (GRACE) satellites ( 5 ). GRACE consists of two identical satellites co- orbiting at low altitude ( È 450 km), separated by 220 km and linked with the K-band micro- wave ranging (KBR) satellite-to-satellite tracking (SST) system ( 6 ). Minute changes in the distance between the GRACE satellites (measured by KBR) reflect mass anomalies within the Earth system and manifest as changes in Earth _ s gravity field ( 5 ). Some of the better known time-variable gravity signals observed by the GRACE satellites, including tides (of the solid earth, ocean, atmo- sphere, and pole) and atmospheric and ocean barotropic mass variations, have been removed from GRACE observations using a priori models ( 5–7 ). Although the solid-earth mass transport induced by earthquakes is abrupt and permanent, climate-related signals such as hydrological ( 8–10 ) and ocean mass fluxes ( 11 ) are periodic, with primarily seasonal and possibly interannual or longer time scales. In order to eliminate signals other than those associated with the earthquake, we took differences of the gravity solutions (from the same months in various years), using measurements obtained before and after the earthquake. By doing so, we suppressed the normally dominant gravity variations driven by seasonal changes. By using multiple months of data, we can further enhance the tectonic signal-to-noise ratio (SNR) in the GRACE gravity solutions. Our method is based on the direct use of KBR SST data to measure the range changes between the centers of mass of the GRACE satellites and accelerometer and attitude data to measure and remove the effect of nongravita- tional forces acting on the satellites. We used the energy conservation principle and regional gravity field inversion to enhance the spatial and temporal resolutions ( 12 , 13 ). The technique has been demonstrated by successful analysis of various geophysical phenomena, including hydrological variations in the Amazon ( 10 ) and ocean tides underneath the Antarctica ice shelves ( 14 ), with improved spatial (500 km) and temporal (5 days) resolutions. The data for the first 6 months of the years 2003, 2004, and 2005 were used, except for January and June 2003 and the last half of January 2004, during which there are no available data. The gravity changes in each year were computed using data from the available months (that is, February to May 2003 and January to June 2004 and 2005) with respect to a reference gravity model GGM01C ( 6 ) (Fig. 1, A to C). We find that (Fig. 1) (i) the gravity anomalies appearing along the coastal area of the Bay of Bengal and the east of Thailand exist in all years; (ii) the negative gravity anomalies are observed to be getting larger near the south of the Mekong River, Cambodia/Vietnam, every year; and (iii) the gravity anomalies appear north of the Sumatra Islands and Andaman Sea with a 30- m Gal peak-to-peak variation only in 2005. The gravity variation in 2004 with re- spect to 2003 (Fig. 1D) is insignificant, whereas the variation in 2005 with respect to 2003 or 2004 shows strong negatives in the Andaman Sea and positives along the west of the Sumatra, Nicobar, and Andaman Islands (Fig. 1, E and F), indicating the occurrence of a strong earthquake during 2004. The other dominant anomaly found south of the Mekong River implicates hydrolog- ic variations. The anomalies in all differenced pairs are negative, and the magnitude is larger in the 2-year differenced pair of 2005 and 2003 than in the 1-year differenced pairs (2005 and 2004 or 2004 and 2003). This implies negative interannual variation or mass decreasing every year, which could result from the droughts oc- curring during the same time period in southeast- ern Asia. To retain only the anomalies relevant to the earthquake, we filtered the average of two pairs, 2005/2003 and 2005/2004 (Fig. 2). The gravity anomalies outside a spherical cap cen- tered at the earthquake epicenter (3.5 - N, 96 - E), with a spherical radius of 7 - , were further filtered by downweighing the anomalies with a factor of inverse square of distance away from the edges of the spherical cap. We analyzed the GRACE gravity observations using a seismically derived dislocation model for the Sumatra-Andaman (26 December 2004) and the Nias (28 March 2005) earthquakes ( 15 ). The geometry (size, orientation, and location) of the fault planes is assumed to be known. Assuming an elastic half-space ( 16 , 17 ), the fault slip data were used to model the uplift and subsidence at the sea floor and at the Moho ( 18 ), where large density contrasts exist. The computed topography changes for both levels were used to predict the gravity changes at sea level (Fig. 3, A to C) E see the supporting online material (SOM) for the formalism of computing gravity changes due to vertical displacement at sea level . We then applied Gaussian smoothing to the computed gravity from the model ( 15 ), with averaging radii of 300 km in longitude and 200 km in latitude ( 19 ), to be commensurate with the spatial resolution of the GRACE observations. The larger positive gravity change (Fig. 3A) is due to the dominant up-warping of the hanging wall and the density contrast at the sea floor, which is three to four times larger than that at the Moho. The negative gravity change is due to the (smaller) down-warping of the hanging wall (Fig. 3A) and subsidence of the foot wall at the Moho (Fig. 3B). The resulting largely positive gravity change due to vertical displacement (Fig. 3C) cannot fully explain the negative components also seen in the GRACE observations (Fig. 2). There must be another mechanism causing the large negative signals in the GRACE observation. We considered the internal mass redistribution (density change caused by dilatation of a compressible Earth) due to the earthquake. With the strains computed using the seismic model, we calculated the density changes by multiplying the sum of the normal strains (that is, the divergence of the displacement field) by the density at the corresponding depth. Assuming that there are two distinct densities for the crust and the mantle (fig. S1), the respective gravity changes due to density changes in the crust and the mantle were calculated separately (SOM). The negative gravity change in the crust (Fig. 3D) is primarily due to the expansion caused by horizontal (mostly in the east-west direction) and vertical motions of the sea floor. The gravity change caused by the compression in the mantle (Fig. 3E) is due to down-warping of the subsurface. The total gravity effect of the density change (Fig. 3F) shows negatives around the faults and smaller positives over the surrounding regions and variations along the strike. The combined effects of uplift and subsidence and dilatation and compression from the seismically driven model (Fig. 4) yield excellent agreement (a correlation coefficient of 0.85) with the GRACE observations (Fig. 2). In addition to our regional inversion of the overflight GRACE tracking data (Figs. 1 and 2), we also processed monthly mean GRACE gravity estimates expressed in terms of spherical harmonic (SH) coefficients ( 5 ). The global SH spectra are, however, less effective for modeling the regional gravity signals (such as earthquakes) because the spatially limited signals spread across the entire SH spectra ( 10 ). The GRACE SH coefficients have a good SNR limited only to low degree coefficients (that is, a long-wavelength spatial scale larger than 1300 km). ...
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... anomalies appear north of the Sumatra Islands and Andaman Sea with a 30- m Gal peak-to-peak variation only in 2005. The gravity variation in 2004 with re- spect to 2003 (Fig. 1D) is insignificant, whereas the variation in 2005 with respect to 2003 or 2004 shows strong negatives in the Andaman Sea and positives along the west of the Sumatra, Nicobar, and Andaman Islands (Fig. 1, E and F), indicating the occurrence of a strong earthquake during 2004. The other dominant anomaly found south of the Mekong River implicates hydrolog- ic variations. The anomalies in all differenced pairs are negative, and the magnitude is larger in the 2-year differenced pair of 2005 and 2003 than in the 1-year differenced pairs (2005 and 2004 or 2004 and 2003). This implies negative interannual variation or mass decreasing every year, which could result from the droughts oc- curring during the same time period in southeast- ern Asia. To retain only the anomalies relevant to the earthquake, we filtered the average of two pairs, 2005/2003 and 2005/2004 (Fig. 2). The gravity anomalies outside a spherical cap cen- tered at the earthquake epicenter (3.5 - N, 96 - E), with a spherical radius of 7 - , were further filtered by downweighing the anomalies with a factor of inverse square of distance away from the edges of the spherical cap. We analyzed the GRACE gravity observations using a seismically derived dislocation model for the Sumatra-Andaman (26 December 2004) and the Nias (28 March 2005) earthquakes ( 15 ). The geometry (size, orientation, and location) of the fault planes is assumed to be known. Assuming an elastic half-space ( 16 , 17 ), the fault slip data were used to model the uplift and subsidence at the sea floor and at the Moho ( 18 ), where large density contrasts exist. The computed topography changes for both levels were used to predict the gravity changes at sea level (Fig. 3, A to C) E see the supporting online material (SOM) for the formalism of computing gravity changes due to vertical displacement at sea level . We then applied Gaussian smoothing to the computed gravity from the model ( 15 ), with averaging radii of 300 km in longitude and 200 km in latitude ( 19 ), to be commensurate with the spatial resolution of the GRACE observations. The larger positive gravity change (Fig. 3A) is due to the dominant up-warping of the hanging wall and the density contrast at the sea floor, which is three to four times larger than that at the Moho. The negative gravity change is due to the (smaller) down-warping of the hanging wall (Fig. 3A) and subsidence of the foot wall at the Moho (Fig. 3B). The resulting largely positive gravity change due to vertical displacement (Fig. 3C) cannot fully explain the negative components also seen in the GRACE observations (Fig. 2). There must be another mechanism causing the large negative signals in the GRACE observation. We considered the internal mass redistribution (density change caused by dilatation of a compressible Earth) due to the earthquake. With the strains computed using the seismic model, we calculated the density changes by multiplying the sum of the normal strains (that is, the divergence of the displacement field) by the density at the corresponding depth. Assuming that there are two distinct densities for the crust and the mantle (fig. S1), the respective gravity changes due to density changes in the crust and the mantle were calculated separately (SOM). The negative gravity change in the crust (Fig. 3D) is primarily due to the expansion caused by horizontal (mostly in the east-west direction) and vertical motions of the sea floor. The gravity change caused by the compression in the mantle (Fig. 3E) is due to down-warping of the subsurface. The total gravity effect of the density change (Fig. 3F) shows negatives around the faults and smaller positives over the surrounding regions and variations along the strike. The combined effects of uplift and subsidence and dilatation and compression from the seismically driven model (Fig. 4) yield excellent agreement (a correlation coefficient of 0.85) with the GRACE observations (Fig. 2). In addition to our regional inversion of the overflight GRACE tracking data (Figs. 1 and 2), we also processed monthly mean GRACE gravity estimates expressed in terms of spherical harmonic (SH) coefficients ( 5 ). The global SH spectra are, however, less effective for modeling the regional gravity signals (such as earthquakes) because the spatially limited signals spread across the entire SH spectra ( 10 ). The GRACE SH coefficients have a good SNR limited only to low degree coefficients (that is, a long-wavelength spatial scale larger than 1300 km). Therefore, we applied Gaussian smoothing with an averaging radius of 800 km to reduce errors in higher degree coefficients ( 5 ). The months from February to May in 2003, 2004, and 2005 were used because they are available in common. We computed 4-month mean differences in various years, similar to Fig. 1. One, 2004–2003, (fig. S2A) shows nothing notable except the negative gravity change over the Mekong River; however, the pairs 2005–2003 (fig. S2B) and 2005– 2004 (fig. S2C) show significant negative anomalies around the Malay Peninsula, Thailand. The magnitude of the anomaly is larger for the 2-year differenced pair (fig. S2B), and the location of the peak in 2005–2003 (fig. S2B) is moved toward the east from the north of the Sumatra Islands, when compared to the predic- tion (fig. S2F). The mislocation of the peak signal is explained by the combined effects of the earthquake and hydrology in the Mekong river due to the smoothing of GRACE global spectra. At this low spatial resolution, we cannot isolate the earthquake anomalies from other signals. However, the gravity effects of vertical displacement (fig. S2D) and density change (fig. S2E) predicted by the seismic model still agree with the GRACE SH observations when combined and smoothed to the commensurate spatial resolution (fig. S2F). The 1-year difference pair (fig. S2C) was less affected by the Mekong hydrology and was in better agreement with the predicted gravity change from the seismic model (fig. S2F), in terms of strength and location of the peak. Finally, we quantified the signal spectra sensitive to GRACE observations by analyzing the power spectral density (PSD) of predicted gravity changes from the seismic model ( 15 ). The PSD of the gravity changes due to uplift and subsidence from the model without smoothing (Fig. 5A) indicates that the dominant power is focused on spherical degree 40 in latitude and 100 in longitude ( 20 ). Higher degree components are found in longitude because the uplift and subsidence have a north-south elongated feature with variation of sign along longitude (fig. S3C). The power spectra of gravity changes induced by dilatation from the seismic model without smoothing (Fig. 5B) indicate that most powers are at the low degrees. Unlike the uplift and subsidence, higher degree components are found in latitude because the dilatation has an east-west elongated feature with variation of sign along latitude (fig. S3F). Because of the poor SNR in the higher degrees ( 21 , 22 ), GRACE is expected to provide reliable estimates that are limited to low degree components for uplift and subsidence (Fig. 5C) and for dilatation (Fig. 5D). Most of signals are within less than 40 to 50 degrees (on a spatial scale or resolution larger than 400 to 500 km). Although GRACE would miss the main power of the uplift and subsidence (out of the re- coverable degrees), it successfully captures the main power of dilatation (within the recover- able degrees). According to the ratio between the total power of uplift and subsidence commensurate with GRACE resolution and the predicted power from the seismic model (table S1), it is found that GRACE retains only 2% of the power of uplift and subsidence signals. However, GRACE retains almost half of the power of dilatation signals. The seismic model predicts that the power of uplift and subsidence is 20 to 30 times larger than that of dilatation; however, for the band-limited GRACE observations, they are almost equal in magnitude. GRACE _ s sensitivity to low degree spectra only does not allow observations of a major portion of the coseismic uplift and subsidence, but the coseismic dilatation is well observed. Like other shallow subduction earthquakes, the Sumatra-Andaman undersea earthquake has produced sparse geodetic measurements except for distant GPS measurements at surrounding islands. GRACE has mapped the coseismic mass redistribution directly above the faults with a resolution of approximately 400 to 500 km. Comparison with an independent seismic model and consideration of the fault mechanism with the geometry of subduction along the trench consistently indicate that the stronger negative gravity anomaly in the east of the Java trench observed by GRACE is due to substantial expansion of the seafloor crust. This unusual sensitivity to the coseismic dilatation suggests that GRACE can provide a new class of observa- tional constraints on geophysical models of great subduction-zone earthquakes. he biaryl substructure is a widely oc- T curring and functional component molecules of biologically ( 1–4 ). Its active im- portance is reflected in the immense economic value of pharmaceuticals including Valsartan ( 5 , 6 ) and Telmisartan ( 7 , 8 ), agrochemicals such as Boscalid ( 9 ), and liquid crystals for LCD screens ( 10 ) (Fig. 1). Over the past several decades, the mild and selective Suzuki coupling of nucleophilic arylbo- ronic acids with aryl halides ( 11–14 ) has almost completely replaced classical methods of biaryl synthesis ( 15–18 ) and has become the method of choice for laboratory and industrial applications ( 19 ). More than 4000 publications ( 20 ) attest to the tremendous interest in improving this transformation. However, the Suzuki reaction still suffers from a ...
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... the entire SH spectra ( 10 ). The GRACE SH coefficients have a good SNR limited only to low degree coefficients (that is, a long-wavelength spatial scale larger than 1300 km). Therefore, we applied Gaussian smoothing with an averaging radius of 800 km to reduce errors in higher degree coefficients ( 5 ). The months from February to May in 2003, 2004, and 2005 were used because they are available in common. We computed 4-month mean differences in various years, similar to Fig. 1. One, 2004–2003, (fig. S2A) shows nothing notable except the negative gravity change over the Mekong River; however, the pairs 2005–2003 (fig. S2B) and 2005– 2004 (fig. S2C) show significant negative anomalies around the Malay Peninsula, Thailand. The magnitude of the anomaly is larger for the 2-year differenced pair (fig. S2B), and the location of the peak in 2005–2003 (fig. S2B) is moved toward the east from the north of the Sumatra Islands, when compared to the predic- tion (fig. S2F). The mislocation of the peak signal is explained by the combined effects of the earthquake and hydrology in the Mekong river due to the smoothing of GRACE global spectra. At this low spatial resolution, we cannot isolate the earthquake anomalies from other signals. However, the gravity effects of vertical displacement (fig. S2D) and density change (fig. S2E) predicted by the seismic model still agree with the GRACE SH observations when combined and smoothed to the commensurate spatial resolution (fig. S2F). The 1-year difference pair (fig. S2C) was less affected by the Mekong hydrology and was in better agreement with the predicted gravity change from the seismic model (fig. S2F), in terms of strength and location of the peak. Finally, we quantified the signal spectra sensitive to GRACE observations by analyzing the power spectral density (PSD) of predicted gravity changes from the seismic model ( 15 ). The PSD of the gravity changes due to uplift and subsidence from the model without smoothing (Fig. 5A) indicates that the dominant power is focused on spherical degree 40 in latitude and 100 in longitude ( 20 ). Higher degree components are found in longitude because the uplift and subsidence have a north-south elongated feature with variation of sign along longitude (fig. S3C). The power spectra of gravity changes induced by dilatation from the seismic model without smoothing (Fig. 5B) indicate that most powers are at the low degrees. Unlike the uplift and subsidence, higher degree components are found in latitude because the dilatation has an east-west elongated feature with variation of sign along latitude (fig. S3F). Because of the poor SNR in the higher degrees ( 21 , 22 ), GRACE is expected to provide reliable estimates that are limited to low degree components for uplift and subsidence (Fig. 5C) and for dilatation (Fig. 5D). Most of signals are within less than 40 to 50 degrees (on a spatial scale or resolution larger than 400 to 500 km). Although GRACE would miss the main power of the uplift and subsidence (out of the re- coverable degrees), it successfully captures the main power of dilatation (within the recover- able degrees). According to the ratio between the total power of uplift and subsidence commensurate with GRACE resolution and the predicted power from the seismic model (table S1), it is found that GRACE retains only 2% of the power of uplift and subsidence signals. However, GRACE retains almost half of the power of dilatation signals. The seismic model predicts that the power of uplift and subsidence is 20 to 30 times larger than that of dilatation; however, for the band-limited GRACE observations, they are almost equal in magnitude. GRACE _ s sensitivity to low degree spectra only does not allow observations of a major portion of the coseismic uplift and subsidence, but the coseismic dilatation is well observed. Like other shallow subduction earthquakes, the Sumatra-Andaman undersea earthquake has produced sparse geodetic measurements except for distant GPS measurements at surrounding islands. GRACE has mapped the coseismic mass redistribution directly above the faults with a resolution of approximately 400 to 500 km. Comparison with an independent seismic model and consideration of the fault mechanism with the geometry of subduction along the trench consistently indicate that the stronger negative gravity anomaly in the east of the Java trench observed by GRACE is due to substantial expansion of the seafloor crust. This unusual sensitivity to the coseismic dilatation suggests that GRACE can provide a new class of observa- tional constraints on geophysical models of great subduction-zone earthquakes. he biaryl substructure is a widely oc- T curring and functional component molecules of biologically ( 1–4 ). Its active im- portance is reflected in the immense economic value of pharmaceuticals including Valsartan ( 5 , 6 ) and Telmisartan ( 7 , 8 ), agrochemicals such as Boscalid ( 9 ), and liquid crystals for LCD screens ( 10 ) (Fig. 1). Over the past several decades, the mild and selective Suzuki coupling of nucleophilic arylbo- ronic acids with aryl halides ( 11–14 ) has almost completely replaced classical methods of biaryl synthesis ( 15–18 ) and has become the method of choice for laboratory and industrial applications ( 19 ). More than 4000 publications ( 20 ) attest to the tremendous interest in improving this transformation. However, the Suzuki reaction still suffers from a fundamental drawback common to almost all catalytic couplings between aryl nucleophiles and electrophiles: It requires the use of stoichi- ometric amounts of an expensive organometallic compound, in this case a boronic acid, which must generally be prepared from sensitive precursors under elaborate anaerobic conditions ( 16 ). Living organisms, which generally lack an air- and water-free environment, have long evolved to generate carbanion equivalents by straightforward enzymatic decarboxylation of ubiquitously available carboxylic acid derivatives, including as an example the heteroarenecarboxylic acid orotidine monophosphate (OMP, Fig. 2) ( 21–24 ). This biochemical transformation inspired us to adopt a loosely analogous approach for the chemical synthesis of biaryls, using carboxylate salts rather than organometallics as the source of carbon nucleophiles. However, whereas b -ketocarboxylic acids are capable of forming a six-membered cyclic transition state, lowering the activation barrier for decarboxylation ( 25 , 26 ), metal salts of aromatic carboxylates require extreme temper- atures to lose CO ( 27–29 ), and under the re- 2 ported conditions, the aryl-metal species are rapidly protonated by the surrounding medium to give the corresponding arenes. In mechanistic studies of such protodecarboxylation reactions, Nilsson proved the intermediacy of an aryl-copper species in the pyrolysis of copper 2-nitrobenzenecarboxylate (250 - C) by captur- ing it with excess iodobenzene and isolating 2-nitrobiphenyl along with nitrobenzene and several by-products ( 29 ). Because of the intrinsic limitations of related copper-mediated Ullmann-type couplings (insuf- ficient selectivity for the heterocoupling, stoichi- ometric use of copper), we saw little opportunity to turn this trapping experiment into a prepara- tively useful biaryl synthesis from arenecarboxylates. However, we envisioned that such a synthesis could be achieved with a bimetallic catalyst—a copper complex capable of mediating the strongly endothermic extrusion of carbon dioxide from arenecarboxylates, combined with a two-electron catalyst capable of catalyzing the cross-coupling with an aryl halide (Fig. 3). The copper derivative would thus initially coordinate to the carboxylate oxygen, then shift to the aryl p system and insert into the C–C(O) bond under extrusion of CO to form a stable aryl-copper 2 intermediate ( 28 ). The two-electron catalyst (e.g., Pd) could then cross-couple this species with an aryl electrophile to form the desired biaryl and the corresponding metal halide. To test our hypothesis and identify systems capable of mediating this highly desirable pro- cess, we chose as a model reaction the commercially important cross-coupling of 2-nitrobenzoic acid with 4-bromochlorobenzene to form the Boscalid intermediate 3a (Fig. 4). Selected results from our screening experiments are sum- marized in table ...
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... : 03 0 : 01 6 The spatial distributions of aerosol over the oceans and their absorption properties are highly heterogeneous. Consequently, the estimated average impact is uncertain and should be viewed as a first approximation. The clouds sampled by the AERONET procedure do not include extended cloud systems that are sensitive to aerosol effect. The analysis applies to urban industrial pollution and aerosol produced by biomass burning rather than land-use–generated dust. The relationship between cloud cover and aerosol given by Eq. 5 can serve as a constraint on models of the aerosol and cloud interaction, independently of the cause-and-effect relationship. The robustness of the effect of aerosols on clouds, presented here, makes it more likely that most of the observed changes in the cloud cover are due to the aerosol impact. The large effect of elevated aerosol concentration on cloud cover, an increase of 0.03 (5%) in average cloud cover (Eq. 6), can have a profound effect on the hydrological cycle and climate. he devastating 26 December 2004 Sumatra- T Andaman moment magnitude undersea earthquake, ( M ) between with 9.1 a w and 9.3, ruptured more than 1000 km of a locked subduction interface near northern Sumatra, Nicobar, and the Andaman islands ( 1 ). Measure- ments from global seismic network and Global Positioning System (GPS) stations have been used to infer the coseismic slip history of this event ( 1–4 ). The earthquake permanently changed the mass distribution within Earth and has conse- quently perturbed the motion of Earth-orbiting satellites by an amount that is measurable from the ranging instrument onboard the Gravity Recovery and Climate Experiment (GRACE) satellites ( 5 ). GRACE consists of two identical satellites co- orbiting at low altitude ( È 450 km), separated by 220 km and linked with the K-band micro- wave ranging (KBR) satellite-to-satellite tracking (SST) system ( 6 ). Minute changes in the distance between the GRACE satellites (measured by KBR) reflect mass anomalies within the Earth system and manifest as changes in Earth _ s gravity field ( 5 ). Some of the better known time-variable gravity signals observed by the GRACE satellites, including tides (of the solid earth, ocean, atmo- sphere, and pole) and atmospheric and ocean barotropic mass variations, have been removed from GRACE observations using a priori models ( 5–7 ). Although the solid-earth mass transport induced by earthquakes is abrupt and permanent, climate-related signals such as hydrological ( 8–10 ) and ocean mass fluxes ( 11 ) are periodic, with primarily seasonal and possibly interannual or longer time scales. In order to eliminate signals other than those associated with the earthquake, we took differences of the gravity solutions (from the same months in various years), using measurements obtained before and after the earthquake. By doing so, we suppressed the normally dominant gravity variations driven by seasonal changes. By using multiple months of data, we can further enhance the tectonic signal-to-noise ratio (SNR) in the GRACE gravity solutions. Our method is based on the direct use of KBR SST data to measure the range changes between the centers of mass of the GRACE satellites and accelerometer and attitude data to measure and remove the effect of nongravita- tional forces acting on the satellites. We used the energy conservation principle and regional gravity field inversion to enhance the spatial and temporal resolutions ( 12 , 13 ). The technique has been demonstrated by successful analysis of various geophysical phenomena, including hydrological variations in the Amazon ( 10 ) and ocean tides underneath the Antarctica ice shelves ( 14 ), with improved spatial (500 km) and temporal (5 days) resolutions. The data for the first 6 months of the years 2003, 2004, and 2005 were used, except for January and June 2003 and the last half of January 2004, during which there are no available data. The gravity changes in each year were computed using data from the available months (that is, February to May 2003 and January to June 2004 and 2005) with respect to a reference gravity model GGM01C ( 6 ) (Fig. 1, A to C). We find that (Fig. 1) (i) the gravity anomalies appearing along the coastal area of the Bay of Bengal and the east of Thailand exist in all years; (ii) the negative gravity anomalies are observed to be getting larger near the south of the Mekong River, Cambodia/Vietnam, every year; and (iii) the gravity anomalies appear north of the Sumatra Islands and Andaman Sea with a 30- m Gal peak-to-peak variation only in 2005. The gravity variation in 2004 with re- spect to 2003 (Fig. 1D) is insignificant, whereas the variation in 2005 with respect to 2003 or 2004 shows strong negatives in the Andaman Sea and positives along the west of the Sumatra, Nicobar, and Andaman Islands (Fig. 1, E and F), indicating the occurrence of a strong earthquake during 2004. The other dominant anomaly found south of the Mekong River implicates hydrolog- ic variations. The anomalies in all differenced pairs are negative, and the magnitude is larger in the 2-year differenced pair of 2005 and 2003 than in the 1-year differenced pairs (2005 and 2004 or 2004 and 2003). This implies negative interannual variation or mass decreasing every year, which could result from the droughts oc- curring during the same time period in southeast- ern Asia. To retain only the anomalies relevant to the earthquake, we filtered the average of two pairs, 2005/2003 and 2005/2004 (Fig. 2). The gravity anomalies outside a spherical cap cen- tered at the earthquake epicenter (3.5 - N, 96 - E), with a spherical radius of 7 - , were further filtered by downweighing the anomalies with a factor of inverse square of distance away from the edges of the spherical cap. We analyzed the GRACE gravity observations using a seismically derived dislocation model for the Sumatra-Andaman (26 December 2004) and the Nias (28 March 2005) earthquakes ( 15 ). The geometry (size, orientation, and location) of the fault planes is assumed to be known. Assuming an elastic half-space ( 16 , 17 ), the fault slip data were used to model the uplift and subsidence at the sea floor and at the Moho ( 18 ), where large density contrasts exist. The computed topography changes for both levels were used to predict the gravity changes at sea level (Fig. 3, A to C) E see the supporting online material (SOM) for the formalism of computing gravity changes due to vertical displacement at sea level . We then applied Gaussian smoothing to the computed gravity from the model ( 15 ), with averaging radii of 300 km in longitude and 200 km in latitude ( 19 ), to be commensurate with the spatial resolution of the GRACE observations. The larger positive gravity change (Fig. 3A) is due to the dominant up-warping of the hanging wall and the density contrast at the sea floor, which is three to four times larger than that at the Moho. The negative gravity change is due to the (smaller) down-warping of the hanging wall (Fig. 3A) and subsidence of the foot wall at the Moho (Fig. 3B). The resulting largely positive gravity change due to vertical displacement (Fig. 3C) cannot fully explain the negative components also seen in the GRACE observations (Fig. 2). There must be another mechanism causing the large negative signals in the GRACE observation. We considered the internal mass redistribution (density change caused by dilatation of a compressible Earth) due to the earthquake. With the strains computed using the seismic model, we calculated the density changes by multiplying the sum of the normal strains (that is, the divergence of the displacement field) by the density at the corresponding depth. Assuming that there are two distinct densities for the crust and the mantle (fig. S1), the respective gravity changes due to density changes in the crust and the mantle were calculated separately (SOM). The negative gravity change in the crust (Fig. 3D) is primarily due to the expansion caused by horizontal (mostly in the east-west direction) and vertical motions of the sea floor. The gravity change caused by the compression in the mantle (Fig. 3E) is due to down-warping of the subsurface. The total gravity effect of the density change (Fig. 3F) shows negatives around the faults and smaller positives over the surrounding regions and variations along the strike. The combined effects of uplift and subsidence and dilatation and compression from the seismically driven model (Fig. 4) yield excellent agreement (a correlation coefficient of 0.85) with the GRACE observations (Fig. 2). In addition to our regional inversion of the overflight GRACE tracking data (Figs. 1 and 2), we also processed monthly mean GRACE gravity estimates expressed in terms of spherical harmonic (SH) coefficients ( 5 ). The global SH spectra are, however, less effective for modeling the regional gravity signals (such as earthquakes) because the spatially limited signals spread across the entire SH spectra ( 10 ). The GRACE SH coefficients have a good SNR limited only to low degree coefficients (that is, a long-wavelength spatial scale ...
Context 6
... : 03 0 : 01 6 The spatial distributions of aerosol over the oceans and their absorption properties are highly heterogeneous. Consequently, the estimated average impact is uncertain and should be viewed as a first approximation. The clouds sampled by the AERONET procedure do not include extended cloud systems that are sensitive to aerosol effect. The analysis applies to urban industrial pollution and aerosol produced by biomass burning rather than land-use–generated dust. The relationship between cloud cover and aerosol given by Eq. 5 can serve as a constraint on models of the aerosol and cloud interaction, independently of the cause-and-effect relationship. The robustness of the effect of aerosols on clouds, presented here, makes it more likely that most of the observed changes in the cloud cover are due to the aerosol impact. The large effect of elevated aerosol concentration on cloud cover, an increase of 0.03 (5%) in average cloud cover (Eq. 6), can have a profound effect on the hydrological cycle and climate. he devastating 26 December 2004 Sumatra- T Andaman moment magnitude undersea earthquake, ( M ) between with 9.1 a w and 9.3, ruptured more than 1000 km of a locked subduction interface near northern Sumatra, Nicobar, and the Andaman islands ( 1 ). Measure- ments from global seismic network and Global Positioning System (GPS) stations have been used to infer the coseismic slip history of this event ( 1–4 ). The earthquake permanently changed the mass distribution within Earth and has conse- quently perturbed the motion of Earth-orbiting satellites by an amount that is measurable from the ranging instrument onboard the Gravity Recovery and Climate Experiment (GRACE) satellites ( 5 ). GRACE consists of two identical satellites co- orbiting at low altitude ( È 450 km), separated by 220 km and linked with the K-band micro- wave ranging (KBR) satellite-to-satellite tracking (SST) system ( 6 ). Minute changes in the distance between the GRACE satellites (measured by KBR) reflect mass anomalies within the Earth system and manifest as changes in Earth _ s gravity field ( 5 ). Some of the better known time-variable gravity signals observed by the GRACE satellites, including tides (of the solid earth, ocean, atmo- sphere, and pole) and atmospheric and ocean barotropic mass variations, have been removed from GRACE observations using a priori models ( 5–7 ). Although the solid-earth mass transport induced by earthquakes is abrupt and permanent, climate-related signals such as hydrological ( 8–10 ) and ocean mass fluxes ( 11 ) are periodic, with primarily seasonal and possibly interannual or longer time scales. In order to eliminate signals other than those associated with the earthquake, we took differences of the gravity solutions (from the same months in various years), using measurements obtained before and after the earthquake. By doing so, we suppressed the normally dominant gravity variations driven by seasonal changes. By using multiple months of data, we can further enhance the tectonic signal-to-noise ratio (SNR) in the GRACE gravity solutions. Our method is based on the direct use of KBR SST data to measure the range changes between the centers of mass of the GRACE satellites and accelerometer and attitude data to measure and remove the effect of nongravita- tional forces acting on the satellites. We used the energy conservation principle and regional gravity field inversion to enhance the spatial and temporal resolutions ( 12 , 13 ). The technique has been demonstrated by successful analysis of various geophysical phenomena, including hydrological variations in the Amazon ( 10 ) and ocean tides underneath the Antarctica ice shelves ( 14 ), with improved spatial (500 km) and temporal (5 days) resolutions. The data for the first 6 months of the years 2003, 2004, and 2005 were used, except for January and June 2003 and the last half of January 2004, during which there are no available data. The gravity changes in each year were computed using data from the available months (that is, February to May 2003 and January to June 2004 and 2005) with respect to a reference gravity model GGM01C ( 6 ) (Fig. 1, A to C). We find that (Fig. 1) (i) the gravity anomalies appearing along the coastal area of the Bay of Bengal and the east of Thailand exist in all years; (ii) the negative gravity anomalies are observed to be getting larger near the south of the Mekong River, Cambodia/Vietnam, every year; and (iii) the gravity anomalies appear north of the Sumatra Islands and Andaman Sea with a 30- m Gal peak-to-peak variation only in 2005. The gravity variation in 2004 with re- spect to 2003 (Fig. 1D) is insignificant, whereas the variation in 2005 with respect to 2003 or 2004 shows strong negatives in the Andaman Sea and positives along the west of the Sumatra, Nicobar, and Andaman Islands (Fig. 1, E and F), indicating the occurrence of a strong earthquake during 2004. The other dominant anomaly found south of the Mekong River implicates hydrolog- ic variations. The anomalies in all differenced pairs are negative, and the magnitude is larger in the 2-year differenced pair of 2005 and 2003 than in the 1-year differenced pairs (2005 and 2004 or 2004 and 2003). This implies negative interannual variation or mass decreasing every year, which could result from the droughts oc- curring during the same time period in southeast- ern Asia. To retain only the anomalies relevant to the earthquake, we filtered the average of two pairs, 2005/2003 and 2005/2004 (Fig. 2). The gravity anomalies outside a spherical cap cen- tered at the earthquake epicenter (3.5 - N, 96 - E), with a spherical radius of 7 - , were further filtered by downweighing the anomalies with a factor of inverse square of distance away from the edges of the spherical cap. We analyzed the GRACE gravity observations using a seismically derived dislocation model for the Sumatra-Andaman (26 December 2004) and the Nias (28 March 2005) earthquakes ( 15 ). The geometry (size, orientation, and location) of the fault planes is assumed to be known. Assuming an elastic half-space ( 16 , 17 ), the fault slip data were used to model the uplift and subsidence at the sea floor and at the Moho ( 18 ), where large density contrasts exist. The computed topography changes for both levels were used to predict the gravity changes at sea level (Fig. 3, A to C) E see the supporting online material (SOM) for the formalism of computing gravity changes due to vertical displacement at sea level . We then applied Gaussian smoothing to the computed gravity from the model ( 15 ), with averaging radii of 300 km in longitude and 200 km in latitude ( 19 ), to be commensurate with the spatial resolution of the GRACE observations. The larger positive gravity change (Fig. 3A) is due to the dominant up-warping of the hanging wall and the density contrast at the sea floor, which is three to four times larger than that at the Moho. The negative gravity change is due to the (smaller) down-warping of the hanging wall (Fig. 3A) and subsidence of the foot wall at the Moho (Fig. 3B). The resulting largely positive gravity change due to vertical displacement (Fig. 3C) cannot fully explain the negative components also seen in the GRACE observations (Fig. 2). There must be another mechanism causing the large negative signals in the GRACE observation. We considered the internal mass redistribution (density change caused by dilatation of a compressible Earth) due to the earthquake. With the strains computed using the seismic model, we calculated the density changes by multiplying the sum of the normal strains (that is, the divergence of the displacement field) by the density at the corresponding depth. Assuming that there are two distinct densities for the crust and the mantle (fig. S1), the respective gravity changes due to density changes in the crust and the mantle were calculated separately (SOM). The negative gravity change in the crust (Fig. 3D) is primarily due to the expansion caused by horizontal (mostly in the east-west direction) and vertical motions of the sea floor. The gravity change caused by the compression in the mantle (Fig. 3E) is due to down-warping of the subsurface. The total gravity effect of the density change (Fig. 3F) shows negatives around the faults and smaller positives over the surrounding regions and variations along the strike. The combined effects of uplift and subsidence and dilatation and compression from the seismically driven model (Fig. 4) yield excellent agreement (a correlation coefficient of 0.85) with the GRACE observations (Fig. 2). In addition to our regional inversion of the overflight GRACE tracking data (Figs. 1 and 2), we also processed monthly mean GRACE gravity estimates expressed in terms of spherical harmonic (SH) coefficients ( 5 ). The global SH spectra are, however, less effective for modeling the regional gravity signals (such as earthquakes) because the spatially limited signals spread across the entire SH spectra ( 10 ). The GRACE SH coefficients have a good SNR limited only to low degree coefficients (that is, a long-wavelength spatial scale larger than 1300 km). Therefore, we applied Gaussian smoothing with an averaging radius of 800 km to reduce errors in higher degree coefficients ( 5 ). The months from February to May in 2003, 2004, and 2005 were used because they are available in common. We computed 4-month mean differences in various years, similar to Fig. 1. One, 2004–2003, (fig. S2A) shows nothing notable except the negative gravity change over the Mekong River; however, the pairs 2005–2003 (fig. S2B) and 2005– 2004 (fig. S2C) show significant negative anomalies around the Malay Peninsula, Thailand. The magnitude of the anomaly is larger for the 2-year differenced pair (fig. S2B), and the location of the peak in ...
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Citations
... Determining the structure of the Earth's gravity field and its temporal change is one of the main scientific objectives for modern geodesy (Davis et al., 2004;Plag and Pearlman, 2009;Zhou et al., 2020). Moreover, it provides essential geospatial information for solving contemporary challenges in geoscience, such as resource, environment monitoring and disaster mitigation (Tapley et al., 2004a;Han et al., 2006;Velicogna and Wahr, 2013). In the 21st century, the development of Earth's gravity field models has made substantial progress, largely due to successful gravity satellite exploration missions (Zhou et al., 2017). ...
... A number of gravity change studies following large shallow earthquakes have discussed two dominant effects causing perturbations in gravity, namely large-scale crustal density changes and vertical uplift or subsidence at density interfaces within the solid Earth and its surface (e.g., Okubo, 1992 for a half space modeling; Sun & Okubo, 1993;Pollitz, 1997a for a spherical Earth modeling). Those studies identified crustal deformation associated with volumetric change over an extensive region from the satellite observations (e.g., Han et al., 2006;Heki & Matsuo, 2010;Ogawa & Heki, 2007;Panet et al., 2007). They concluded that the total changes in surface gravity at large spatial scales (as detectable by satellites) are dominated by volumetric dilatation, as observed repeatedly for shallow thrust and strike-slip events (e.g., Han et al., 2013). ...
... They concluded that the total changes in surface gravity at large spatial scales (as detectable by satellites) are dominated by volumetric dilatation, as observed repeatedly for shallow thrust and strike-slip events (e.g., Han et al., 2013). In oceanic regions, this long wavelength gravity change is amplified by the relative sea level response to large-scale vertical motion (Broerse et al., 2011;Cambiotti et al., 2011;de Linage et al., 2009;Han et al., 2006). The observed gravity changes induced by shallow thrust events (e.g., Chao & Liau, 2019 and references therein) are markedly different from those due to the great deep earthquakes (depth ≥600 km) of 2013 Sea of Okhotsk and 2018 Fiji, for which the effect of a density change was greatly reduced in large-scale gravity observations (Tanaka, 2023;Tanaka et al., 2015;Xu et al., 2017). ...
... The observed spatial patterns of gravity changes of the 2016/2017 thrust earthquakes contrast with those of shallow inter-plate subduction zone events, including the great earthquakes in 2004, 2007(Han et al., 2013. Shallow thrust events involve substantial deformation by volumetric expansion, resulting in a drop in ambient rock density in the region of major slip (e.g., Okubo (1992) and see also Materials and Methods of Han et al. (2006)). The bulk modulus (i.e., resistance to compression) of the rocks at depths typical of shallow events is relatively small (50-75 GPa), allowing extensive dilatation over a wide region, thus leading to a broad negative gravity change, which is strong at the typical wavelengths that are resolvable with GRACE data. ...
Earthquakes involve mass redistribution within the solid Earth and the ocean, and as a result, perturb the Earth's gravitational field. For most of the shallow (<60 km) earthquakes with Mw > 8.0, the GRACE satellite gravity measurements suggest considerable volumetric disturbance of rocks. At a spatial scale of hundreds of km, the effect of volumetric change exceeds gravity change by vertical deformation; for example, negative gravity anomalies associated with volumetric expansion are characteristic patterns after shallow thrust events. In this study, however, we report contrasting observations of gravity change from two intermediate‐depth (100–150 km) earthquakes of 2016 & 2017 Mw 8.0 (two combined) Papua New Guinea thrust faulting events and 2019 Mw 8.0 Peru normal faulting and highlight the importance of compressibility in earthquake deformation. The combined 2016/17 thrust events resulted in a positive gravity anomaly of 5–6 microGal around the epicenter, while the 2019 normal faulting produced a negative gravity anomaly of 3–4 microGal. Our modeling found that these gravity changes are manifestation of vertical deformation with limited volumetric change, distinct from gravity changes after the shallow earthquakes. The stronger resistance of rocks to volume change at intermediate‐depth results in largely incompressible deformation and thus in a gravity change dominated by vertical deformation. In addition, malleable rocks under high pressure and temperature at depth facilitated substantial afterslip and/or fast viscoelastic relaxation causing additional vertical deformation and gravity change equivalent to the coseismic change. For the Papua New Guinea events, this means that postseismic relaxation enhanced coseismic uplift and relative sea level decrease.
... The investigation of gravity signals over time contributes to the understanding of mass transport processes. Surface gravimeters and gravity satellites (GRACE and GRACE-FO) have been successfully utilized to detect gravity variations caused by many processes, such as glacial isostatic adjustment, co-seismic dislocations, volcanic activity, and terrestrial water storage variations (Han et al., 2006;Miller et al., 2017;Rodell et al., 2018;Sun et al., 2010;Tanaka et al., 2001;Wang et al., 2012). ...
High-precision repeated absolute gravity observations conducted at the Luzhou observatory provide valuable insights into the processes of mass redistribution in the station's vicinity. In this study, we analyze four campaigns absolute measurements from two absolute gravimeters, FG5X-255 and FG5X-259, observed at the Luzhou gravity observatory and find a decrease in the gravity value of (− 93.3 ± 3.1) × 10–8 m·s⁻² from October 2020 to July 2022. By subtracting the contributions of vertical deformation, hydrological change, earthquake, and offset between instruments from the observation results, we derive a residual gravity change of (− 92.7 ± 4.1) × 10–8 m·s⁻². Further analysis of field site photos and satellite images reveals that excavation related to the construction of a building near the Luzhou station is responsible for the observed gravity decrease. We use the load theory to calculate the gravity change at the Luzhou station due to the mass removal in the construction area and find that this factor could produce a gravity decrease consistent with the magnitude of the residual gravity change. Our results demonstrate that localized sources of mass redistribution, such as excavation at construction sites, can cause gravity variations exceeding 90 × 10–8 m·s⁻² nearby. Overall, our study highlights the importance of considering local mass redistribution when interpreting gravity variations.
... The coseismic and postseismic signatures at Mizusawa show the stepwise gravity decrease at the occurrence of the earthquake followed by gradual gravity increase. The coseismic gravity decrease can be explained mainly by dilatation of crust above the down-dip edge of the (Han et al. 2006(Han et al. , 2011Matsuo and Heki 2011), whereas the postseismic gravity increase is interpreted as viscoelastic relaxation of the coseismic stress in the lower crust and upper mantle (e.g., Han et al. 2014). ...
Postseismic gravity changes after the 2011 Tohoku earthquake (Mw9.0) were investigated using the data from superconducting gravimeters (SGs) at Mizusawa, Japan. The data in the period from 2014 to 2021 were used in the analysis. The SG data were first corrected for instrumental drift using the results of absolute gravity measurements. Then, correction for the hydrological effect was applied based on physical modeling of soil moisture. Finally, the effect of vertical displacement of the station (free-air effect) was corrected using GNSS data. After these corrections, residual gravity indicated a long-term increase, with its rate gradually decreasing with time. This fact suggests that viscoelastic relaxation after the earthquake played an important role in producing the long-term gravity changes. Fitting a decaying exponential function of time to the residual series yielded 89.4 ± 4.4 µGal (1 µGal = 10 –8 ms –2 ) as the total gravity change and 635 ± 17 days as the characteristic time scale. In addition to the ground-based observations, the data from satellite gravity missions GRACE/GRACE-FO were analyzed to retrieve gravity changes at Mizusawa. Similar analysis of the satellite-based data yielded 15.2 ± 1.6 µGal as the total gravity change and 3444 ± 599 days as the characteristic time scale. The difference in the estimates of the total gravity change, of a factor of about 6, from the ground-based and the satellite-based observations may be attributed to the limited spatial resolution in the latter method. The difference in the estimates of the time scale, of a factor of about 1/5, may originate from the difference in the depth where the two kinds of gravimetry are mainly sensitive. Referring to recent theoretical studies on postseismic deformations after the 2011 Tohoku earthquake, our results can be interpreted consistently by assuming the existence of a layer of viscoelastic materials with viscosity $$2\times {10}^{18} \text{Pa s}$$ 2 × 10 18 Pa s underneath the Tohoku area of Japan.
Graphical Abstract
... During the last two decades, the successful satellite gravity mission, for example, Gravity Recovery And Climate Experiment (GRACE) mission (Tapley et al., 2004(Tapley et al., , 2019, and its successor GRACE Follow On (GRACE-FO) (Flechtner et al., 2016;Landerer et al., 2020;Loomis et al., 2012), have primarily contributed to the understanding of the temporal variations of Earth's gravity field. GRACE and GRACE-FO have not only provided valuable data to refine the gravity field modeling in the Geodesy community but also contributed to the progress of other geosciences, for example, glaciology (e.g., Jacob et al., 2012;, hydrology (e.g., Rodell et al., 2018;Tregoning et al., 2009), seismology (e.g., Fuchs et al., 2016;Han et al., 2006), oceanography (e.g., Knudsen et al., 2011;Rignot et al., 2011), and so on. ...
... The GRACE mission has shown great abilities to detect coseismic and postseismic gravitational deformation caused by earthquakes (e.g., J. L. Chen et al., 2007;Han et al., 2006). This section analyzes the gravitational deformation caused by the Sumatra earthquake. ...
Over the past 20 years, the Gravity Recovery and Climate Experiment (GRACE), and its successor mission, GRACE‐Follow On (GRACE‐FO) have made significant contributions to time‐variable gravity field modeling. A Chinese low‐low satellite‐to‐satellite tracking gravimetry mission (i.e., Chinese future gravimetry mission) has been confirmed to be selected as the polar‐orbiting satellite gravimetry mission for China, because of the capability to collect gravity data globally. However, the analysis of potential contributions to geosciences from GRACE‐FO coupling with the Chinese future gravimetry mission is still limited. This study combines GRACE‐FO and Chinese future gravimetry missions as the Dual GRACE‐like Polar satellite Constellation (DGPC). By carefully choosing the initial orbit parameters of the Chinese future gravimetry mission with the differential evolution algorithm, the DGPC is expected to mitigate the temporal aliasing effects by improving the temporal resolution of time‐variable gravity solutions (i.e., 1‐day and 3‐day solutions). Regarding the spectral‐domain evaluation, zonal, tesseral, and sectorial coefficients estimated by the DGPC show approximately 6.01%–13.42% noise reductions compared with GRACE‐FO. Regarding the spatial‐domain evaluation, the DGPC can suppress noises of about 39.44% and 31.12% in annual amplitude and long‐term trend, respectively. On this basis, this paper analyzes the effectiveness of the DGPC in potential contributions to geosciences (e.g., hydrology, glaciology, and seismology). Specifically, the DGPC can improve accuracy by about 36.96%, 25.85%, and 33.16% with respect to GRACE‐FO for signals in the subhumid basin, signals of ice‐sheet mass balance over Greenland, and coseismic displacement of the fault zone, respectively. In general, the potential capability for high‐frequency signals recovery of the DGPC would facilitate contributions of satellite gravimetry to geosciences.
... The GRACE satellites orbited Earth from 2002 to 2017 (Tapley et al., 2019), and the GRACE-FO satellites were launched in May 2018 and are still operational today Loomis et al., 2020;Velicogna et al., 2020). Benefiting from the GRACE and GRACE Follow-On observations over nearly two decades, numerous achievements related to mass changes associated with water reserve changes over land, ice, and oceans (Chandanpurkar et al., 2017;Cui et al., 2020;Ghobadi-Far et al., 2020;Xie et al., 2020;Yi et al., 2020;Zhou et al., 2018), continental tectonics (Fang et al., 2021;van Dam et al., 2007;Wu et al., 2017Wu et al., , 2021, earthquakes (Chen et al., 2007;de Viron et al., 2008;Han et al., 2006Zhang et al., 2020), and many other surface processes have been obtained. ...
The Gravity Recovery and Climate Experiment (GRACE) mission and its successor GRACE Follow‐On (GRACE‐FO) mission provide humans with a unique perspective on mass distribution through accurate temporal gravity field models. However, these models suffer from unavoidable stripe errors in the spatial domain. A new approach based on image processing has been developed for filtering GRACE and GRACE‐FO spherical harmonic solutions. In this approach, the gravity fields are treated as noise‐contaminated images, and the stripe errors are expected to be suppressed by convolving the input with an appropriate kernel. To verify the effectiveness of the proposed approach, a closed‐loop simulation environment over the nominal mission lifetime of 5 years is designed. Image processing indicators and geophysical information evaluation results demonstrate the superior performance of the new approach in suppressing stripe errors. In the context of real GRACE data processing, our new approach still yields better results as follows: (a) The comprehensive ability of de‐striping and retaining details has slight advantages over some commonly used filters, as demonstrated through spatial distributions, amplitude spectra, and coefficient spectra. (b) The equivalent water height time series at the basin scale is comparable to the results derived from other filters or Level‐3 products. (c) The estimated signal amplitude of the Mw9.1 2004 Sumatra earthquake co‐seismic gravity change is 52.7% larger than that derived from the Gaussian 300 km filter, which is much closer to the theoretical value derived from the dislocation theory.
... Sun et al. 2016 ;Seo et al. 2021 ), large earthquakes (e.g. Han et al. 2006 ;Cambiotti & Sabadini 2012 ;Han et al. 2014 ), etc. ...
... GRACE observations have been also used to understand giant earthquake e vents. Pre vious studies investigated earthquake sources of the 2004 Sumatra-Andaman earthquake (Han et al. 2006 ;de Linage et al. 2009 ;Broerse et al. 2011 ), the 2011 Tohoku-Oki earthquake (Han et al. 2011(Han et al. , 2014Cambiotti & Sabadini 2012 ;Panet et al. 2018 ;Cambiotti 2020 ;Ji et al. 2022 ) and other significant events (Heki & Matsuo 2010 ;Han et al. 2015 ;Xu et al. 2017 ;Chao & Liau 2019 ). Further, there are studies considering earthquake signal correction to obtain improved hydrological mass changes. ...
For more than a decade, GRACE data has provided global mass redistribution measurements due to water cycles, climate change, and giant earthquake events. Large earthquakes can yield gravity changes over thousands of kilometers from the epicenter for years to decades, and those solid Earth deformation signals can introduce significant biases in the estimate of regional-scale water and ice mass changes around the epicenters. We suggest a modeling scheme to understand their contribution to the estimates of water and ice mass changes and to remove the earthquake-related solid mass signals from GRACE data. This approach is composed of physics-based earthquake modeling, GRACE data correction, and high-resolution surface mass change recovery. In this study, we examined the case of the 2011 Tohoku-Oki earthquake to better estimate the regional sea level and hydrological mass changes in the East Asia. The co- and post-seismic changes from GRACE observations were used to constrain the earthquake model parameters to obtain optimal self-consistent models for the earthquake source and the asthenosphere rheology. The result demonstrated that our earthquake correction model significantly reduced the mass change signals by solid Earth deformation from the time series of regional surface mass changes on both land and oceans. For example, the apparent climate-related ocean mass increase over the East Sea was 1.59 ± 0.11 mm/yr for 2003-2016, significantly lower than the global mean ocean mass trend (2.04 ± 0.10 mm/yr) due to contamination of the earthquake signals. After accounting for the solid mass changes by the earthquake, the estimate was revised to 1.87 ± 0.11 mm/yr, that is increased by 20% and insignificantly different from the global estimate.
... TWS is defined as all forms of water stored above and underneath the surface of the Earth [40,41]. GRACE and GFO proved to be reliable for monitoring TWS change at large spatial scales [42][43][44][45]. As GRACE/GFO is not able to measure vertical profile of TWS changes, auxiliary data are used to isolate TWS changes into individual hydrological component [46], such as evapotranspiration [47,48], basin discharge [49,50], soil moisture [51,52] and groundwater storage (GWS) [53][54][55]. ...
In this study, multiple remote sensing data were used to quantitatively evaluate the contributions of surface water, soil moisture and groundwater to terrestrial water storage (TWS) changes in five groundwater resources zones of Inner Mongolia (GW_I, GW_II, GW_III, GW_IV and GW_V), China. The results showed that TWS increased at the rate of 2.14 mm/a for GW_I, while it decreased at the rate of 4.62 mm/a, 5.89 mm/a, 2.79 mm/a and 2.62 mm/a for GW_II, GW_III, GW_IV and GW_V during 2003–2021. Inner Mongolia experienced a widespread soil moisture increase with the rate of 4.17 mm/a, 2.13 mm/a, 1.20 mm/a, 0.25 mm/a and 1.36 mm/a for the five regions, respectively. Significant decreases were detected for regional groundwater storage (GWS) with the rate of 2.21 mm/a, 6.76 mm/a, 6.87 mm/a, 3.01 mm/a, and 4.14 mm/a, respectively. Soil moisture was the major contributor to TWS changes in GW_I, which accounted 58% of the total TWS changes. Groundwater was the greatest contributor to TWS changes in other four regions, especially GWS changes, which accounted for 76% TWS changes in GW_IV. In addition, this study found that the role of surface water was notable for calculating regional GWS changes.
... The Gravity Recovery and Climate Experiment (GRACE) twin satellites launched in 2002 provide global gravity data updates every 7 to 30 days [146]. GRACE data were applied by [147] in measurements of pre-seismic gravitational changes associated with the Mw 9.1 Sumatra-Andaman, Indonesia, earthquake and associated tsunami of 26 December 2004 that cost almost a quarter of a million lives. ...
... Reference [65] presented time-series studies of three massive earthquakes, namely, Chile (27 February 2010), Tohuku-Oki (11 March 2011), and Indian Ocean (11 April 2012), that weekly gravity solutions from GRACE satellite data produced striking anomalies near the epicenter of each of these earthquakes several weeks before their occurrence. Other studies have confirmed the value of the GRACE time-series data in the Mw 8.8 Chilean earthquake of 2010 [148] and the 2004 Sumatra-Andaman and 2011 Tohoku-Oki earthquakes [147,149]. Reference [150] adopted GRACE gravity data to determine the seismic changes at a higher level of spatial resolution using a Gaussian filter algorithm to separate signals from noise and applying a differential method to calculate spatial distributions of gravitational variations. ...
The level of destruction caused by an earthquake depends on a variety of factors, such as magnitude, duration, intensity, time of occurrence, and underlying geological features, which may be mitigated and reduced by the level of preparedness of risk management measures. Geospatial technologies offer a means by which earthquake occurrence can be predicted or foreshadowed; managed in terms of levels of preparation related to land use planning; availability of emergency shelters, medical resources, and food supplies; and assessment of damage and remedial priorities. This literature review paper surveys the geospatial technologies employed in earthquake research and disaster management. The objectives of this review paper are to assess: (1) the role of the range of geospatial data types; (2) the application of geospatial technologies to the stages of an earthquake; (3) the geospatial techniques used in earthquake hazard, vulnerability, and risk analysis; and (4) to discuss the role of geospatial techniques in earthquakes and related disasters. The review covers past, current, and potential earthquake-related applications of geospatial technology, together with the challenges that limit the extent of usefulness and effectiveness. While the focus is mainly on geospatial technology applied to earthquake research and management in practice, it also has validity as a framework for natural disaster risk assessments, emergency management, mitigation, and remediation, in general.
... It has been proved that, when the real data are compared with the synthetic anomalies calculated from the rupture surface models based on different kinds of ground measurements, the difference between the gravity anomalies corresponding to different rupture surface models exceeds the uncertainties of the GRACE data. Therefore, the coseismic gravity anomalies are at least suitable for rejecting part of the models that are equivalent to the ground data [18,50]. It should be noted that there has been an attempt to group the above-mentioned techniques into several categories and compare them through Tables 1 and 2. 3 Possibility of using geospatial artificial intelligence to integrate earthquake precursors for earthquake prediction Various models based on artificial intelligence techniques have been adopted by researchers over the last decade to predict future earthquakes. ...
The main factors contributing to the occurrence of an earthquake are under the crust. Also; due to the lack of access to direct measurements of these factors and the parameters involved in the occurrence of an earthquake, the main goal of researchers is to study the earthquake occurrence through its precursors. Currently, monitoring and identifying some of these precursors are made possible by geomatics technologies. It is an undeniable fact that the behavioral variations of the precursors don’t follow a common pattern in all earthquakes. Also, the variations of the precursors show peculiar behaviors in each region. So, it seems infeasible to provide an accurate prediction based on the analysis of the behavioral variations of a single precursor. Unlike previous studies, this study doesn’t have a single-parametrical orientation toward an earthquake prediction process. Accordingly, this study aims to extract the trend of variations in crustal deformation anomalies and thermal anomalies before the earthquake to analyze them through an integrated process based on data mining methods. As a result, the tests of earthquake predictions for 17 cases have shown that the proposed method can make a reliable prediction of the probable time and magnitude range of oblique-thrust earthquakes with a magnitude greater than 5.5. Moreover, the proposed method has been able to accurately estimate the occurrence of the 26th November 2019 Albania earthquake (Mw = 6.4) as well as 21th September 2019 Albania earthquake (Mw = 5.6) before they happen.
