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Spatio-Temporal Correlation Between Seasonal Variations in Seismicity and Horizontal Dilatational Strain in California
Abstract
We extract significant spatially coherent strain variations from horizontal seasonal Global Positioning System (GPS) displacements in the American Southwest. The dilatational strain is largest in northern California with maximum margin-normal contraction and extension in spring and fall, respectively, consistent with the Earth's surface going down and up at those times. The northern California signal has a phase shift with respect to that in southern California and the Great Basin. For northern and southern California the proportion of larger earthquakes are in-phase and the aftershock productivity out of phase with the inferred Coulomb stress on the San Andreas fault system. The intensity of mainshocks is in-phase in the north as well but not in the south. This suggests that a seasonal increase in fault-normal extension may or may not trigger mainshocks, but when an earthquake happens at those times, they grow larger than they otherwise would, which would cause a larger stress reduction and result in fewer aftershocks.
... Using vertical cGPS data, Johnson et al. (2017a) showed that the seismicity rates in northern California are modulated by the seasonal stress changes. Using horizontal cGPS data, Kreemer and Zaliapin (2018) quantified seasonal horizontal transient deformation patterns in California and investigated links between the associated transient stress changes and seismicity. Kreemer and Zaliapin (2018) and Johnson et al. (2017a) calculated the monthly averaged signal using a time series spanning several years. ...
... Using horizontal cGPS data, Kreemer and Zaliapin (2018) quantified seasonal horizontal transient deformation patterns in California and investigated links between the associated transient stress changes and seismicity. Kreemer and Zaliapin (2018) and Johnson et al. (2017a) calculated the monthly averaged signal using a time series spanning several years. However, seasonal hydrologic loading varies from year-to-year and prolonged drought also impacts the transient nontectonic deformation field (Argus et al., 2017;Borsa et al., 2014). ...
... Our method can be used to monitor loading-driven stress changes on vertical faults over space and time. Kreemer et al. (2018) showed that there is a correlation between long-wavelength horizontal seasonal stress anomalies (inferred from cGPS) and the rate of seismicity in California, especially in northern California. Their results suggest more main shocks (m ≥ 2.5) occurred in northern California during the summer than during the winter. ...
We invert continuously operating Global Positioning System (cGPS) data obtained between 2007 and 2019 to quantify non steady‐state horizontal strain anomalies in California. Our long‐wavelength transient strain model shows seasonal and multiannual variations in horizontal strain anomalies within the plate boundary zone. During the summer, in general, a zone of extensional dilatation develops along the San Andreas Fault zone and Sierra Nevada, whereas contractional dilatation develops along the Eastern California Shear Zone (ECSZ) north of 36.5°N. The patterns of dilatational strain are opposite during the winter. We find that these seasonal strain anomaly patterns vary in magnitude, depending on precipitation intensity in California. Investigating hydrologic loading models and their horizontal elastic responses reveal that water mass loads on the surface from the precipitation in California are the major sources of the observed long‐wavelength horizontal transient strains. We show, however, that a heavy damping in the inversion of the cGPS data is required for the long‐wavelength horizontal strain solutions to best match with the expected elastic response from hydrologic loading. Appropriate fitting of the horizontal cGPS yields amplified horizontal strain signals in the Sierra Nevada, along regions adjacent to the San Andreas Fault, and within the ECSZ. The larger‐than‐expected amplitudes may be associated with poroelastic responses or thermoelastic changes that are superimposed on the hydrologic response. We demonstrate that there is a persistent sharp boundary of horizontal dilatational strain domains at the transition between the High Sierra and Basin and Range Province, caused by the sharp gradient in hydrologic loading there.
... Several studies have highlighted the signature of these precipitation trends in deformation data, showing that observed subsidence/uplift trends at both seasonal and multiyear scales are driven mainly by surface loading/unloading from increasing/decreasing surface water and groundwater (Amos et al., 2014;Argus et al., 2017;Borsa et al., 2014;Kreemer & Zaliapin, 2018). These studies mostly focused on the vertical component of the deformation, since horizontal displacements induced by surface loading are typically much smaller (Wahr et al., 2013). ...
... Deformation records, such as those provided by GNSS data, are extensively used to study the different phases of LVC magmatic and seismic activity (Ji et al., 2013;Liu et al., 2011;Montgomery-Brown et al., 2015) and to analyze the effects of hydrological loading on the SNR (Argus et al., 2017;Amos et al., 2014;Borsa et al., 2014;Kreemer & Zaliapin, 2018). However, the interplay between the hydrological and solid earth systems and its effect on deformation in the LVC area have not been widely investigated. ...
... As also observed at larger scales by Kreemer and Zaliapin (2018), the GNSS seasonal vertical subsidence/uplift and horizontal inward/outward motion around the SNR (Figure 4a) suggests that the solid earth elastic response to snow and water loading plays a significant role in driving the observed deformation. We demonstrated this by estimating the expected displacement response in our study area from hydrological loads at both regional scale (i.e., at the scale of Sierra Nevada) and large scale (i.e., at the scale of the contiguous USA, or CONUS). ...
Plain Language Summary
Flowing water from hydrological processes like melting glaciers or snowpack, precipitation, streamflow, and groundwater can produce significant deformation of the Earth's surface. Long Valley Caldera (LVC), California, is a complex area with an active magmatic system, long‐term tectonic motion, and earthquakes. At the eastern edge of the Sierra Nevada range, LVC also has high snowfall in winter that melts in spring. Runoff water feeds the LVC hydrothermal system and triggers earthquakes swarms. We observe a clear correlation between surface deformation (measured by geodetic methods) and hydrological processes at multiple spatial and temporal scales. At large spatial scales, deformation is associated with Earth's surface response to hydrological loading: the surface subsides/uplifts when load increases/decreases. At local scales, however, anomalous seasonal deformation at the caldera rim is related to water infiltration into fractured rocks of adjacent Sierra Nevada slopes: snowmelt water infiltrates into fractures and causes rock expansion. This represents a nontectonic signal that could bias the interpretation of LVC volcanic system observations. Our study shows that a network of precise measurements of the Earth's surface motion can provide detailed information about groundwater features and improved understanding of the interactions between hydrological and tectonic processes over a wide range of scales.
... Recent studies have shown that active uplift of the Sierra Nevada Mountains in California and Nevada, western United States, is detectible in vertical component GPS measurements, with rates up to 2 mm/yr (Fay et al., 2008;Hammond et al., 2012). The geographic pattern and seasonality of the signals provide clear indications that surface mass unloading from loss of ground and surface water help drive the observed uplift (Amos et al., 2014;Argus et al., 2017;Kreemer & Zaliapin, 2018). As California entered severe drought conditions in late 2011, precipitation decreased and was followed by an intensification of the extraction of groundwater and reduction in water availability in California Central Valley aquifers (e.g., Faunt et al., 2016). ...
... MAGNET data constrain rates of motion nearly as well as continuous stations but in some cases do not well constrain seasonal oscillations since they are only occupied part of each year. Continuous stations are more common on the Sierra Nevada and LVC (since they monitor the active volcanic system), while MAGNET dominates to the east in the Great Basin where time-variable motion was thought to be less prevalent owing to generally drier conditions in the rain shadow of the Sierra Nevada (Amos et al., 2014;Kreemer & Zaliapin, 2018; Figure 1). ...
... both prior to the drought period (green vectors) and during the drought period (red vectors). The changes in lengths of these vectors resulting from LVC inflation change the distribution of shear and dilatational deformation in the CWL. Dashed lines help to visualize gradients in velocity and how they change between predrought and drought periods.Kreemer & Zaliapin, 2018). ...
We use GPS data to show synchronization between the 2011 and 2016 drought cycle in California, accelerated uplift of the Sierra Nevada Mountains, and enhanced magmatic inflation of the Long Valley Caldera (LVC) magmatic system. The drought period coincided with faster uplift rate, changes in gravity seen in the Gravity Recovery and Climate Experiment (GRACE), and changes in standardized relative climate dryness index. These observations together suggest that the Sierra Nevada elevation is sensitive to changes in hydrological loading conditions, which subsequently influences the LVC magmatic system. We use robust imaging of horizontal GPS velocities to derive time‐variable shear and dilatational strain rates in a region with highly variable station distribution. The results show that the highest strain rates are near the eastern margin of the Sierra Nevada and western edge of the Central Walker Lane (CWL) passing directly through LVC. The drought period saw geographic shifts in the distribution in active shear strain in the CWL more than 60 km from the LVC, delineating the minimum extent over which the active magmatic system affects the CWL tectonic environment. We analyze declustered seismicity data to show that locations with higher seismicity rates tend to be (1) areas with higher strain rates and (2) areas in which strain rates increased during drought‐enhanced inflation. We hypothesize that drought conditions reduce vertical surface mass loading, which decreases pressure at depth in the LVC system, in turn enhances magmatic inflation, and drives horizontal elastic stress changes that redistribute active CWL strain and modulate seismicity.
... This correlation also holds for damaging M>5.5 earthquakes in catalogs reaching back to 1781 (Johnson et al., 2017a). Horizontal GNSS displacements have also been used to estimate seasonal strain variations and to discuss their potential association with seismicity in California (e.g., Kreemer and Zaliapin, 2018;Kim et al., 2021b). Kreemer and Zaliapin (2018) proposed that hydrologically induced seasonal strain may cause a larger stress release in an earthquake and fewer aftershocks. ...
... Horizontal GNSS displacements have also been used to estimate seasonal strain variations and to discuss their potential association with seismicity in California (e.g., Kreemer and Zaliapin, 2018;Kim et al., 2021b). Kreemer and Zaliapin (2018) proposed that hydrologically induced seasonal strain may cause a larger stress release in an earthquake and fewer aftershocks. In the intra-continental New Madrid seismic zone, Craig et al (2017) identified annual and multi-annual variations in microseismicity rates (M ≤ 2.3) that coincide with stress variations driven by elastic hydrological loading. ...
There is long-standing interest in the interactions between atmospheric and hydrological processes and solid Earth deformation, including the occurrence of earthquakes. Here, we review evidence for the effects of climatic processes and weather on deformation and seismicity in the lithosphere over a wide range of time scales, ranging from load cycles associated with the ice ages to the effects of short-term weather events. Space- and ground-based geophysical observations allow us to capture the redistribution of surface loads in the form of water, ice, and sediments, as well as near-surface pressure and temperature changes in the atmosphere and varying fluid pressure in the shallow subsurface. While earthquakes are generally the result of tectonic or volcanic activity, the climatic forcings induce stress changes on faults that in some cases can be shown to significantly encourage or retard the occurrence of earthquakes, depending on the degree to which the external forces align with the background tectonic stress field. Stress changes associated with the emplacement and removal of km-thick ice sheets and lakes are large enough to substantially change slip- and earthquake rates on major plate-boundary faults and can also trigger events in largely aseismic continental interiors. However, climate-earthquake interactions are subtle and proving the interaction between climate and earthquakes requires careful mechanical modeling and statistical analysis. While investigations of earthquake weather and climate are not likely to be relevant for the characterization and mitigation of earthquake hazard, they provide important insights into the physical processes associated with lithospheric deformation, the earthquake cycle and frictional faulting in the Earth.
... Given the proximity of earthquakes after impoundment to the TGR and low background seismicity during the pre-impoundment period, the earthquakes are believed to be related to water storage changes in the TGR Zhang et al., 2017bZhang et al., , 2018b. Figure 13a shows the comparison between water level fluctuation in the TGR and earthquake counts prior to impoundment and at the three impoundment stages. To further investigate the possible link between earthquakes and water level fluctuation, we follow Kreemer and Zaliapin (2018) to smooth the earthquake counts (counted per half month) and daily water level time series with a moving window of 8 months. This procedure has been proven to be instrumental in revealing the hidden correlations between seismicity and its possible anthropogenic cause (Kreemer & Zaliapin, 2018). ...
... To further investigate the possible link between earthquakes and water level fluctuation, we follow Kreemer and Zaliapin (2018) to smooth the earthquake counts (counted per half month) and daily water level time series with a moving window of 8 months. This procedure has been proven to be instrumental in revealing the hidden correlations between seismicity and its possible anthropogenic cause (Kreemer & Zaliapin, 2018). The smoothed earthquake counts and water level time series at the three impoundment stages are shown in Fig. 13b-d. ...
Water storage changes in the Three Gorges Reservoir (TGR) cause large mass variations on the Earth's surface, which inevitably influences crustal stability. The quantitative relationship between the water storage changes in the TGR and nearby crustal deformation has not been thoroughly investigated; as a result, the impacts caused by water loading changes have not been fully understood. In this study, we apply multi-channel singular spectrum analysis (M-SSA) to the time series of water level data and Global Navigation Satellite System (GNSS) observed displacements from 2010 to 2018 and extract their seasonal variations. Results show that the seasonal displacements at three GNSS stations have amplitudes of 4–9 mm in the vertical direction and ~ 2 mm in the horizontal direction, while seasonal water level changes have an amplitude of ~ 28.632 ± 2.401 m. We find that seasonal vertical displacements at the three GNSS stations are anti-correlated with the seasonal water level change, the correlation coefficients (CC) can be as high as −0.83. Based on this finding, we propose linear models to predict GNSS stations' displacement from water level observations. We also forward-model the water storage-induced crustal displacements using the elastic Green's function method. Both the linear model and the elastic Green's function method yield displacement results consistent with the observed GNSS displacements. The results show that the water storage changes in the TGR contribute 32.8%, 8.8%, and 13.5% to the detrended coordinate variations at the three GNSS stations. The crustal uplift near the dam can be as large as ~ −40 mm under an extreme situation when the water level rises from 145 to 175 m. Analysis of the correlation between water level fluctuation and seismicity suggests that the earthquakes in stages 1 and 3 of TGR impoundment were likely associated with the water level changes and appeared to respond nearly instantaneously to the increasing water level, suggesting the water storage changes in the TGR has influenced the stability of the nearby crust. This study provides a new perspective toward understanding the impacts of the TGR on the nearby environment.
... These elastic displacements are dependent on the magnitude and distribution of the load variation, and return to their original position when equilibrium is re-attained. While many studies rely primarily on vertical GPS observations to identify and quantify TWS variation, some studies have shown that horizontal motion is a useful indicator of mass localization when regional trends are well accounted for (Fu et al., 2013;Kreemer & Zaliapin, 2018;Wahr et al., 2013). ...
... Events are limited to only mainshocks that occur to the west of the Wasatch fault. While studies have identified strong correlations between seasonal water level variation and seismicity (Amos et al., 2014;Craig et al., 2017;Kreemer & Zaliapin, 2018), we find no evidence of annual seismicity modulation, in agreement with the findings of Hu and Bürgmann (2020), so we inspect the catalog for evidence of temporally variable, drought-cycle induced seismicity modulation. To allow for an equal assessment of seismicity during wet and dry periods, we cut the catalog to the period of 1987.1-2020, in which there are equal timeframes where the PDSI indicates either wet or dry periods. ...
Great Salt Lake (GSL), Utah, lost 1.89 ± 0.04 m of water during the 2012–2016 drought. During this timeframe, data from the Gravity Recovery and Climate Experiment mission underestimate this mass loss, while nearby Global Positioning System (GPS) stations exhibit significant shifts in position. We find that crustal deformation, from unloading the Earth's crust consistent with the observed GSL water loss alone, does not explain the GPS displacements, suggesting contributions from additional water storage loss surrounding GSL. This study applies a damped least squares inversion to the three‐dimensional GPS displacements to test a range of distributions of groundwater loads to fit the observations. When considering the horizontal and vertical displacements simultaneously, we find a realistic distribution of water loss while also resolving the observed water loss of the lake. Our preferred model identifies mass loss up to 64 km from the lake via two radial rings. The contribution of exterior groundwater loss is substantial (10.9 ± 2.8 km³ vs. 5.5 ± 1.0 km³ on the lake), and greatly improves the fit to the observations. Nearby groundwater wells exhibit significant water loss during the drought, which substantiates the presence of significant water loss outside of the lake, but also highlights greater spatial variation than our model can resolve. We observe seismicity modulation within the inferred load region, while the region outside the (un)loading reveals no significant modulation. Drier periods exhibit higher quantities of events than wetter periods and changes in trend of the earthquake rate are correlated with regional mass trends.
... is~4-5 months out of phase with the rest of the fault, which might be due in part to its proximity to the irrigation-controlled groundwater recharge cycle in the southern part of the Valley that is~3 months out of phase with the rest of the Valley. Kreemer and Zaliapin (2018) found a similar~4-month phase lag for peak Coulomb stress change between the northern and southern San Andreas fault, although that study was based on seasonal horizontal strain. ...
... Other studies have noted that if the fault is critically stressed, small harmonic perturbations can push a fault to failure (Tanaka, 2012). Thus, although these stress perturbations from groundwater unloading and hydrologic stress fluctuations in general are small compared to the background tectonic stress, periods of higher-than-average stress might help to push a fault to rupture if it is already near failure or an earthquake might be larger than normal if it occurs during peak harmonic stressing (Ader et al., 2014;Kreemer & Zaliapin, 2018). For these reasons, harmonic stress perturbations should be included in earthquake hazard prediction and probability assessments. ...
Changes in terrestrial water content cause elastic deformation of the Earth's crust. This deformation is thought to play a role in modulating crustal stress and seismicity in regions where large water storage fluctuations occur. Groundwater is an important component of total water storage change in California, helping to drive annual water storage fluctuations and loss during periods of drought. Here we use direct estimates of groundwater volume loss during the 2007-2010 drought in California's Central Valley obtained from high resolution Interferometric Synthetic Aperture Radar-based vertical land motion data to investigate the effect of groundwater volume change on the evolution of the stress field. We show that GPS-derived elastic load models may not capture the contribution of groundwater to terrestrial water loading, resulting in an underestimation of nontectonic crustal stress change. We find that groundwater unloading during the drought causes Coulomb stress change of up to 5.5 kPa and seasonal fluctuations of up to 2.6 kPa at seismogenic depth. We find that faults near the Valley show the largest stress change and the San Andreas fault experiences only ~40 Pa of Coulomb stress change over the course of a year from groundwater storage change. Annual Coulomb stress change peaks dominantly in the fall, when the groundwater level is low; however, some faults experience peak stress in the spring when groundwater levels are higher. Additionally, we find that periods of increased stress correlate with higher than average seismic moment release but are not correlated with an increase in the number of earthquakes. This indicates groundwater loading likely contributes to nontectonic loading of faults, especially near the Valley edge, but is not a dominant factor in modulation of seismicity in California because the amplitude of stress change declines rapidly with distance from the Valley. By carefully quantifying and spatially locating groundwater fluctuations, we will improve our understanding of what drives nontectonic stress and forces that modulate seismicity in California.
... The uncertainties obtained through the MIDAS algorithm have a realistic meaning and usually do not require further scaling (e.g. Hammond et al. 2016;Caron et al. 2018;Kreemer & Zaliapin 2018;Yu et al. 2018;Ojo et al. 2021). Thus, time series length must be greater than 1 yr such that at least one full cycle of periodic seasonal behavior, if it exists, is captured and any transient signals can be distinguished from secular behavior. ...
The present-day sea-level variations and vertical movements in the northern Adriatic Sea and in the highly vulnerable Venetian Lagoon result from a number of simultaneously operating contributions. These include Glacial Isostatic Adjustment (GIA), the global, long-term process arising from interactions between the cryosphere, the solid Earth and the oceans in response to the melting of continental ice sheets. Although the GIA contribution in northern Adriatic Sea has been the subject of various investigations so far, significant uncertainties still exist, especially related to the extent and chronology of the Würm Alpine ice sheet and to the rheological profile of the mantle. Here, taking advantage of the recent publication of updated deglaciation chronologies for the far field late-Pleistocene ice sheets and for the near-field alpine ice complex, we produce up-to-date estimates of the present-day rates of GIA-induced relative sea-level variations and vertical displacements in the Venetian Lagoon and in the northern Adriatic Sea, which are compared with GNSS and tide-gauge observations. From high-resolution numerical simulations, we find that GIA is responsible for a complex pattern of geodetic signals across the Po plain and the northern Adriatic Sea. The modeled GIA rates are of the order of fractions of mm/yr, generally small – but not negligible – compared to the signals observed at local tide gauges and at GNSS sites in the Po plain and facing the Venetian Lagoon. Our results indicate that, while GIA represents a relatively small component among those responsible for present-day land movements and relative sea-level variations in the northern Adriatic Sea, its contribution needs to be taken into account for a correct interpretation of the observed geodetic variations.
... The concept of a "seasonal effect" or "seasonal component", apparently, first appeared in meteorology (Buys Ballot, 1847). Currently, seasonal changes in processes and phenomena are observed and studied in a variety of subject areas of knowledge (Brendstrup et al., 2004;Majrashi et al., 2008Majrashi et al., , 2020Polonskii and Shokurova, 2010;Economic…, 2012;Hillers et al., 2015;Dagum and Bianconcini, 2016;Magritskii and Kenzhebaeva, 2017;Kreemer and Zaliapin, 2018;Timofeeva and Yulin, 2020;Forestell et al., 2020;Goswami et al., 2020;Tiwaria et al., 2020;Kuzmenko et al., 2021;Shimizu et al., 2021). At the same time, the concept of a "seasonal effect" is interpreted in different ways, but an extended interpretation of seasonality is becoming more generally accepted, implying that seasonal variations may not be completely identical in different years. ...
An adaptive model is proposed to describe time-varying seasonal effects. The seasonal average
function is constructed using an iterative algorithm that provides a neat decomposition of the signal into a
generalized trend, seasonal and residual components. By a trend, we mean long-term evolutionary changes
in the average signal level, both unidirectional and chaotic, in the form of a slow random drift. This algorithm
allows one to obtain unbiased estimates for each of the signal components, even in the presence of a significant number of missing observations. The series length is not required to be a multiple of an integer number
of years. In contrast to the usual “Climate Normals” (CN) model, the considered adaptive model of seasonal
effects assumes a continuous slow change in the properties of the seasonal component over time. The degree
of allowable variability in seasonal effects from year to year is entered as a tunable parameter of the model. In
particular, this allows one to show the dynamics of the growth of the amplitude of seasonal fluctuations in
time in the form of a continuous (smooth) function without necessarily linking these changes to predetermined calendar epochs. The algorithm was tested on the atmospheric CO2 concentration monitoring series
at Barrow, Mauna Loa, Tutuila, and South Pole stations located at different latitudes. The form of the seasonal variation was estimated, and the average amplitude of the seasonal variation and the rate of its change
at each station were calculated. Noticeable differences in the dynamics of the studied parameters between stations are demonstrated. Mean amplitude of seasonal variation in CO2 concentration at Barrow, Mauna Loa,
Tutuila, and South Pole stations in the epoch 2010–2019 was estimated as 18.15, 7.08, 1.30, and 1.26 ppm,
respectively, and the average rate of increase in the amplitude of the seasonal variation in the increase in CO2
concentration in the interval 1976–2019 is 0.085, 0.0100, 0.0165, and 0.0031 ppm/year. In relative terms, the
increase is 0.57 ± 0.03, 0.11 ± 0.02, 2.24 ± 0.24, and 0.27 ± 0.04% per year.
... For annual period, seismicity rate variation is ∼24%. Using the seasonal geodetic strains in Southern California of ∼0.02 kPa (Kreemer & Zaliapin, 2018), we find ∼ 0.1 kPa . These seasonal strains are relatively small when comparing to similar studies (e.g., Amos et al., 2014;C. ...
Swarms are bursts of earthquakes without an obvious mainshock. Some have been observed to be associated with transient aseismic fault slip, while others are thought to be related to fluids. However, the association is rarely quantitative due to insufficient data quality. We use high‐quality GPS/GNSS, InSAR, and relocated seismicity to study a swarm of >2,000 earthquakes which occurred between 30 September and 6 October 2020, near Westmorland, California. Using 5 min sampled Global Positioning System (GPS) supplemented with InSAR, we document a spontaneous shallow Mw 5.2 slow slip event that preceded the swarm by 2–15 hr. The earthquakes in the early phase were predominantly non‐interacting and driven primarily by the slow slip event resulting in a nonlinear expansion. A stress‐driven model based on the rate‐and‐state friction successfully explains the overall spatial and temporal evolution of earthquakes, including the time lag between the onset of the slow slip event and the swarm. Later, a distinct back front and a square root of time expansion of clustered seismicity on en‐echelon fault structures suggest that fluids helped sustain the swarm. Static stress triggering analysis using Coulomb stress and statistics of interevent times suggest that 45%–65% of seismicity was driven by the slow slip event, 10%–35% by inter‐earthquake interactions, and 10%–30% by fluids. Our model also provides constraints on the friction parameter and the pore pressure and suggests that this swarm behaved like an aftershock sequence but with the mainshock replaced by the slow slip event.
... The distribution of seismic hazards induced by earthquakes varies substantially in spatial orientation in response to the focal mechanism. Kreemer and Zaliapin investigated the relationship between transitory stress fluctuations associated with seasonal horizontal deformation patterns in California and seismicity (Kreemer & Zaliapin, 2018). They established the relationship between long wavelength horizontal seasonal stress anomalies (as determined by cGPS) and the seismicity rate in California, particularly in northern California. ...
Earthquakes are the shaking of the Earth’s crust, making quick energy discharge in the Earth’s lithosphere by creating seismic waves. The global temperature is a significant climate variable that affects the Earth’s ecosystem and civilization. The global temperature record indicates the average temperature of various periods across all locations in the globe. It is dependent on the amount of energy Earth absorbs from the Sun and emits back into space. The earthquake has always been a challenging exploration topic for the last few decades. Finding its association with global temperature fluctuations is also popular nowadays. This work aims to investigate the correlation and causal relation between rising global temperature and earthquake occurrences. In this regard, two dynamics, namely global temperature anomalies and the occurrence of earthquakes, have been taken from the Intergovernmental Panel on Climate Change (IPCC) and US Geological Survey (USGS), respectively. An endeavour has been taken to determine the degree of association between earthquake occurrence and global temperature fluctuation through the temporal variation analysis and correlation analysis for the Alaska region and global consequences. The results show that the global temperature anomalies strongly influence the earthquakes of minor magnitudes, specifically magnitude of 2.0 to 4.9 M. The study further investigates the causal relationship between earthquake occurrences and global temperature fluctuations by using the Granger causality test, which reveals bidirectional causality exists between the two dynamics. These results will help future researchers to create a suitable mathematical model to predict the future values of each dynamics using other's previous records.
... The hydrologically driven deformation processes, on the other hand, involve both elastic load deformation across the region and poroelastic deformation in basins. Both processes are predominately vertical (Hammond et al., 2016), but there are appreciable horizontal components in both near the margins of the hydrological loads and aquifer systems (e.g., Kreemer & Zaliapin, 2018;Shen & Liu, 2020). ...
Tectonic, hydrological and industrial processes coexist in the dynamic natural environments. However, our knowledge of ground deformation associated with tectonic, hydrological and anthropogenic processes and their interactions remains limited. California represents a natural laboratory that hosts the San Andreas fault system, Central Valley and other aquifer systems, and extensive human extraction of natural resources. The attendant multi-scale ground deformation that has been mapped using Copernicus Sentinel-1 Synthetic Aperture Radar (SAR)-satellite constellation from four ascending and five descending tracks during 2015-2019. We consider the secular horizontal surface velocities and strain rates, constrained from GNSS measurements and tectonic models, as proxies for tectonic processes, and seasonal displacement amplitudes from interferometric SAR (InSAR) time series as proxies for hydrological processes. We synergize 23 types of multidisciplinary datasets, including ground deformation, sedimentary basins, precipitation, soil moisture, topography, and hydrocarbon production fields, using a machine learning algorithm – random forest, and we succeed in predicting 86%-95% of the representative data sets. High strain rates along the SAF system mainly occur in areas with a low-to-moderate vegetation fraction (~0.3), suggesting a correlation of rough/high-relief coastal range morphology and topography with the active faulting, seasonal and orographic rainfall, and vegetation growth. Linear discontinuities in the long-term, seasonal amplitude and phase of the surface displacement fields coincide with some fault strands, the boundary zone between the sediment-fill Central Valley and bedrock-dominated Sierra Nevada, and the margins of the inelastically deforming aquifer in the San Joaquin Valley, suggesting groundwater flow interruptions, contrasting elastic properties, and heterogeneous hydrological units.
... According to reports from the US Geological Survey, above one billion individuals have been affected as the result of this event during the past 20 years (United States Geological Survey (USGS) 2020). The damage caused by an earthquake depends on the seismic magnitudes and the focal mechanism (Kreemer and Zaliapin 2018;Ma et al. 2019). Therefore, developing an authentic system that estimates the time, location, and magnitude of the earthquake would be useful to mitigate the fatalities and potential damages (Ishii et al. 2005;Ma et al. 2019). ...
Earthquake is one of the most lethal natural disasters and a severe threat to human life. The damage maps are precious information to mitigate the casualties after an earthquake in guiding the rescuers towards the affected area. This paper proposes a novel method, named decision-level damage estimation (DLDE), to generate the building damage map using post-event high-resolution satellite imagery (HRSI) and light detection and ranging (LiDAR) raster data. The meaningful information which describes the available data is produced through texture analysis in the primary step of the proposed method. Support vector machine (SVM) classification algorithm is employed to extract the damaged buildings after the separation of the building area. In the next step, the damage degree based on LiDAR and satellite image for each building is calculated, and in the final stage, these damage degrees are fused to obtain the final damage degree for buildings. We evaluated the proposed DLDE method using the WorldView II satellite image and LiDAR data of Port-au-Prince, Haiti, which was acquired after the 2010 earthquake. The overall accuracy (OA) of 81% proved the high ability of the proposed method for the assessment of post-earthquake damage.
... However, statistical analyses are often hampered by the limited number of events associated with a low level of background seismicity, insufficient station coverage, or short catalog durations. To establish statistical significance, these analyses also require a careful consideration of catalog completeness and event clustering (8)(9)(10). ...
Delineation of physical factors that contribute to earthquake triggering is a challenging issue in seismology. We analyze hydrological modulation of seismicity in Taiwan using groundwater level data and GNSS time series. In western Taiwan, the seismicity rate reaches peak levels in February to April and drops to its lowest values in July to September, exhibiting a direct correlation with annual water unloading. The elastic hydrological load cycle may be the primary driving mechanism for the observed synchronized modulation of earthquakes, as also evidenced by deep earthquakes in eastern Taiwan. However, shallow earthquakes in eastern Taiwan (<18 km) are anticorrelated with water unloading, which is not well explained by either hydrological loading, fluid transport, or pore pressure changes and suggests other time-dependent processes. The moderate correlation between stacked monthly trends of large historic earthquakes and present-day seismicity implies a modestly higher seismic hazard during the time of low annual hydrological loading.
... The regional change shown in Fig. 5c cannot be associated with changes in surface loading due to non-tectonic processes. Seasonal and multi-year surface and ground hydrological changes are known to induce both vertical and horizontal crustal motion (Amos et al., 2014;Kreemer and Zaliapin, 2018), commonly with much stronger effect on vertical than horizontal motions. Some of the GNSS sites in Fig. 5, especially those near the coast and in the southern part of the study area, indeed exhibit faster vertical than horizontal motion. ...
After a great subduction earthquake, viscoelastic stress relaxation causes prolonged seaward motion of inland areas of the upper plate, as was observed around the turn of the century in the area of the 1960 Mw 9.5 Chile earthquake with Global Navigation Satellite System (GNSS) measurements. However, recent GNSS observations during 2010–2019 indicate a systematic decrease in the velocity of the seaward motion over a region covering the latitudinal range of the southern half of the 1960 rupture. Data from the only long-lived continuous site in this region (COYQ since 1997), situated over 200 km away from the trench, suggest that the decrease in the seaward velocity (or increase in the landward velocity) occurred within a few years prior to 2010. This rapid and regional change cannot be explained by viscoelastic relaxation. We thus propose that the change was caused by a relatively sudden downdip widening of the zone of locking along the megathrust. Using three-dimensional finite element modelling, we find that the observed velocity change cannot be otherwise explained, although the amount of the increase in locking cannot be uniquely determined because of trade-offs between, and uncertainties in, the various parameters involved. For example, the degree of the increase in locking is affected by the value of coseismic slip in 1960 in the southernmost part of the rupture zone. A postseismic deformation model with greater coseismic slip in accordance with the most recent coseismic slip model in the literature better fits COYQ data prior to 2005 and requires greater locking increase afterwards. A model with less coseismic slip requires less locking increase but an additional long-term slow slip event prior to 2005. The rapid surface velocity change and the inferred increase in megathrust locking several decades after a great earthquake present new challenges to the understanding of fault mechanics and subduction zone dynamics.
... Although beyond the scope of this article, data from the cGNSS networks discussed here also revealed deformation signals arising from a variety of hydrologic loading processes (Bawden et al., 2001;King et al., 2007;Amos et al., 2014;Argus et al., 2014;Borsa et al., 2014;Fu, Argus, and Landerer, 2015;Argus et al., 2017), some of which may influence seismicity patterns through the crustal stresses they impart (e.g., Johnson et al., 2017;Kraner et al., 2018;Kreemer and Zaliapin, 2018). cGNSS stations can augment tide-gauge networks for tracking global sea-level change by providing measures of vertical land motion that can be used to obtain absolute sealevel measurements in a terrestrial reference frame (Foster, 2015) and through analysis of cGNSS signal-to-noise ratio to directly estimate local sea level (Larson et al., 2013). ...
Regional networks of Global Navigation Satellite System (GNSS) stations cover seismically and volcanically active areas throughout the United States. Data from these networks have been used to produce high‐precision, three‐component velocity fields covering broad geographic regions as well as position time series that track time‐varying crustal deformation. This information has contributed to assessing interseismic strain accumulation and related seismic hazard, revealed previously unknown occurrences of aseismic fault slip, constrained coseismic slip estimates, and enabled monitoring of volcanic unrest and postseismic deformation. In addition, real‐time GNSS data are now widely available. Such observations proved invaluable for tracking the rapidly evolving eruption of Kīlauea in 2018. Real‐time earthquake source modeling using GNSS data is being incorporated into tsunami warning systems, and a vigorous research effort is focused on quantifying the contribution that real‐time GNSS can make to improve earthquake early warnings as part of the Advanced National Seismic System ShakeAlert system. Real‐time GNSS data can also aid in the tracking of ionospheric disturbances and precipitable water vapor for weather forecasting. Although regional GNSS and seismic networks generally have been established independently, their spatial footprints often overlap, and in some cases the same institution operates both types of networks. Further integration of GNSS and seismic networks would promote joint use of the two data types to better characterize earthquake sources and ground motion as well as offer opportunities for more efficient network operations. Looking ahead, upgrading network stations to leverage new GNSS technology could enable more precise positioning and robust real‐time operations. New computational approaches such as machine learning have the potential to enable full utilization of the large amounts of data generated by continuous GNSS networks. Development of seafloor Global Positioning System‐acoustic networks would provide unique information for fundamental and applied research on subduction zone seismic hazard and, potentially, monitoring.
... Global Navigation Satellite Systems (GNSS) have also improved in accuracy, precision, and overall availability over the last decades, increasing the ability to resolve relative plate motion and enabling the identification of previously unknown inter-, co-, and post-seismic deformation features. (Amos et al., 2014;Bartlow et al., 2014;Gualandi et al., 2017a;Gualandi et al., 2017b;Kreemer et al., 2014;Kreemer and Zaliapin;Reilinger and McClusky, 2011;Wallace et al., 2017). Similarly, radiometric dating methods have improved significantly over the last three decades due to identification of additional chronometers, a better understanding of nuclide production rates, and the availability of more sensitive mass spectrometers. ...
With a little more than 100 years since the publication of seminal and field-defining investigations, active tectonics is still a relatively young sub-discipline of structural geology. This research field addresses the accumulation of strain due to plate tectonic motion and more importantly release thereof through the occurrence of earthquakes (or other strain-releasing events). In that regard, active tectonics aims to characterize the incremental steps of plate tectonics. Determining earthquake chronologies, fault slip rates, and other common objectives importantly feed into our understanding of, for example, fault mechanics and crustal rheology. Characterizing the recurrence of large and potentially devastating earthquakes, is further motivated by seismic hazard assessment and risk mitigation. The primary data source in active tectonics is surface and shallow subsurface evidence of faulting –presenting itself in topographic and stratigraphic data sets respectively. Field observations and air photo interpretation of displaced stratigraphic and geomorphic markers were used almost 40 years ago to formulate end-member models of earthquake recurrence. Technological developments since then –especially within the last two decades– have dramatically increased the abundance and resolution of topographic data sets and the ability to date stratigraphic units and geomorphic surfaces, enabling the formulation of better-informed conceptual models of earthquake recurrence. Here, we provide an overview of the high-resolution topographic data sets and dating methods that enabled the recent advances of active tectonics.
Crustal deformation in the central Basin and Range between the Colorado plateau and the Eastern California Shear Zone is active but slow, making it a challenge to assess how strain is distributed and crustal motion transferred. However, knowledge of strain rates is very important, particularly for addressing the seismic hazard for both the Las Vegas urban area and the site of the proposed Yucca Mountain nuclear waste repository, in southern Nevada. Global Positioning System (GPS) data provide important constraints, particularly now that the GPS network in the area has substantially expanded in recent years. However, because deformation is slow, it is important to mitigate any transient tectonic and nontectonic signals to obtain the most accurate long-term interseismic motion and robust estimation of strain rates. We use data from all GPS stations in the region including both long-running continuous and semicontinuous stations. We model and remove postseismic displacements at these stations using source parameters for 41 events, dating back to the 1700 Cascadia megathrust earthquake, which contribute significantly to the deformation field within the central Basin and Range. We also remove correlated noise from the time series with the common-mode component imaging technique. We find that removal of both the postseismic transients and common-mode noise substantially reduces the uncertainties and spatial variation in the velocities. We find east–west extension across the Las Vegas Valley of 0.5–0.6 mm/yr. The interseismic strain rate field, calculated with the final velocities, reveals higher strain rates through southern Nevada than in previous studies, with rates within Las Vegas Valley of 8.5±2.4×10−9 yr−1. Our results also confirm shear along the Pahranagat shear zone, but the estimated amplitude is strongly affected by postseismic relaxation.
Plain Language Summary
Global navigation satellite system (GNSS) has provided precise records of the Earth’s surface motions, from which crustal deformation patterns can be estimated. In July 2019, two large earthquakes (magnitudes of 6.4 and 7.1) struck Ridgecrest, California. Using GNSS data, we estimate a 13‐year history of horizontal deformation patterns and associated stress loads on faults in the region surrounding Ridgecrest leading up to the 2019 Ridgecrest sequence. We detect seasonal variations in the horizontal deformation patterns in the Ridgecrest region, and we find the associated seasonal stress loads peaked every early summer during the last 13 years including during June 2019, a month prior to the 2019 Ridgecrest earthquakes. We further investigate a possible correlation between the seasonal stress changes and timing of small earthquakes by carrying out statistical analyses. This additional test reveals that more earthquakes occur when the seasonal stress is loading the faults than when it is unloading them. These results suggest that the timing of earthquakes, including the 2019 Ridgecrest events, may have been modulated by seasonal stress changes. There is a strong need to continue gathering GNSS data, together with other geodetic observations, for the purpose of the time‐dependent seismic hazard modeling.
Increasingly accurate, and spatio-temporally dense, measurements of Earth surface movements enable us to identify multiple deformation patterns and highlight the need to properly characterize the related source processes. This is particularly important in tectonically active areas, where deformation measurement is crucial for monitoring ongoing processes and assessing future hazard. Long Valley Caldera, California, USA, is a volcanic area where frequent episodes of unrest involve inflation and increased seismicity. Ground- and satellite-based instruments show that volcanic inflation renewed in 2011, and is continuing as of early 2021. Additionally, Long Valley Caldera is affected by the large, but spatially and temporally variable, amounts of precipitation falling on the adjacent Sierra Nevada Range. The density and long duration of deformation measurements at Long Valley Caldera provide an excellent collection of data to decompose time-series and separate multiple superimposed deformation sources. We analyze Global Navigation Satellite System (GNSS) time-series and apply variational Bayesian Independent Component Analysis (vbICA) decomposition method to isolate inflation-related signals from other processes. We show that hydrological forcing causes significant horizontal and vertical deformation at different temporal (seasonal and multiyear) and spatial (few to hundreds of km) scales that cannot be ignored while analyzing and modeling the tectonic signal. Focusing on the last inflation episode, we then improve on prior simplistic models of the inflation reservoir by including heterogeneous subsurface material properties and topography. Our results suggest the persistence and stability of the reservoir (prolate ellipsoid at about 8 km beneath the resurgent dome) and indicate a 40-50% reduction of the inflation rate after about 3 years from the inflation onset. The onset of the reduced inflation rate corresponded in time with the occurrence of a strong seismic swarm in the Caldera, but also to the temporal variation of climatic conditions in the area.
The study of the disturbance process of hydrologic load on crustal stressis helpful in clarifying the relationship between hydrologic load and seismic activity. Using the seasonal signal of GPS time series in Nepal, the seasonal three-dimensional displacement field and stress-strain field model in this region is constructed. The modulation effect of seasonal hydrological load on seismicity in this area is studied by combining rain fall and seismic catalogue. Theresultsshowthat:1) the reis a strong spatiotemporal correlation between seasonal surface displacement and rain fall; 2) the rain fall in monsoon period disturbs the long-term movement trend of the fault and releases the Coulomb stress to a certain extent, thus inhibiting the seismic activity and affecting the time of the earthquake
In central California, periodic earthquake occurrence suggests a relationship with annual hydrological, atmospheric, thermal, and tidal loadings. In catalogs of declustered earthquakes within 100 km from Parkfield, CA, we study a semiannual periodicity for the monthly number of ≤7.2‐km‐deep earthquakes and the monthly median hypocenter depth over 1994–2002 and 2006–2014. Peak‐trough months in fitted periodic components differ between time spans and event populations. Deeper earthquakes present no semiannual and a weak annual periodicity. Although modeled pore pressure shows a Spring peak, when added to the elastic Coulomb stress from surface hydrospheric loads, it fails to predict a 6‐month periodicity for 2006–2014. In 1994–2002, the pore‐pressure amplitude appears to be of same order as the elastic stress and may have had a stronger effect. In 2006–2014, we did not find load model parameters explaining the observed pattern or apparent changes following the 2003 San Simeon and 2004 Parkfield earthquakes.
Drought struck California during 7 of the 9 years from 2007 through 2015, reducing the state's available water resources. Pumping of Central Valley groundwater has produced spectacular land subsidence. Uplift of the adjacent Sierra Nevada mountains has been proposed to be either tectonic uplift or solid Earth's elastic response to unloading of Central Valley groundwater. We find that, of the 24 mm of uplift of the Sierra Nevada from October 2011 to October 2015, just 5 mm is produced by Central Valley groundwater loss, less than 2 mm is tectonic uplift, and 17 mm is solid Earth's elastic response to water loss in the Sierra Nevada. We invert GPS vertical displacements recording solid Earth's elastic response to infer changes in water storage across the western U.S. from January 2006 to October 2017. We find water changes to be sustained over periods of drought or heavy precipitation: the Sierra Nevada lost 15 ±19 km3 of water during drought from October 2006 to October 2009, gained 18 ±14 km3 of water during heavy precipitation from October 2009 to October 2011, and lost 45 ±21 km3 of water during severe drought from October 2011 to October 2015 (95% confidence limits). Such large changes are not in hydrology models: snow accumulation in October is negligible and long-term soil moisture change is small. We infer there must be large loss of either deep soil moisture or groundwater in river alluvium and in crystalline basement in the Sierra Nevada. The results suggest there to be parching of water in the ground during the summer of years of drought and seeping of melting snow into the Sierra Nevada in the spring of years of heavy precipitation.
The degree to which short-term non-tectonic processes, either natural and anthropogenic, influence the occurrence of earthquakes in active tectonic settings or 'stable' plate interiors, remains a subject of debate. Recent work in plate-boundary regions demonstrates the capacity for long-wavelength changes in continental water storage to produce observable surface deformation, induce crustal stresses and modulate seismicity rates. Here we show that a significant variation in the rate of microearthquakes in the intraplate New Madrid Seismic Zone at annual and multi-annual timescales coincides with hydrological loading in the upper Mississippi embayment. We demonstrate that this loading, which results in geodetically observed surface deformation, induces stresses within the lithosphere that, although of small amplitude, modulate the ongoing seismicity of the New Madrid region. Correspondence between surface deformation, hydrological loading and seismicity rates at both annual and multi-annual timescales indicates that seismicity variations are the direct result of elastic stresses induced by the water load.
We introduce "GPS Imaging," a new technique for robust estimation of the vertical velocity field of the Earth's surface, and apply it to the Sierra Nevada Mountain range in the western United States. Starting with vertical position time series from Global Positioning System (GPS) stations, we first estimate vertical velocities using the MIDAS robust trend estimator, which is insensitive to undocumented steps, outliers, seasonality and heteroscedasticity. Using the Delaunay triangulation of station locations, we then apply a weighted median spatial filter to remove velocity outliers and enhance signals common to multiple stations. Finally, we interpolate the data using weighted median estimation on a grid. The resulting velocity field is temporally and spatially robust and edges in the field remain sharp. Results from data spanning 5-20 years show that the Sierra Nevada is the most rapid and extensive uplift feature in the western United States, rising up to 2 mm/yr along most of the range. The uplift is juxtaposed against domains of subsidence attributable to groundwater withdrawal in California's Central Valley. The uplift boundary is consistently stationary, though uplift is faster over the 2011-2016 period of drought. Uplift patterns are consistent with groundwater extraction and concomitant elastic bedrock uplift, plus slower background tectonic uplift. A discontinuity in the velocity field across the southeastern edge of the Sierra Nevada reveals a contrast in lithospheric strength, suggesting a relationship between Late Cenozoic uplift of the southern Sierra Nevada and evolution of the southern Walker Lane.
Periodic earthquake occurrences may reflect links with semidiurnal to multiyear tides, seasonal hydrological loads, and ~14month pole tide forcing. The Schuster spectrum is a recent extension of Schuster's traditional test for periodicity analysis in seismology. We present an alternative approach: the multifrequential periodogram analysis (MFPA), performed on time series of monthly earthquake numbers. We explore if seismicity in two central California regions, the Central San Andreas Fault near Parkfield (CSAF-PKD) and the Sierra Nevada-Eastern California Shear Zone (SN-ECSZ), exhibits periodic behavior at periods of 2months to several years. Original and declustered catalogs spanning up to 26years were analyzed with both methods. For CSAF-PKD, the MFPA resolves ~1year periodicities, with additional statistically significant periods of ~6 and ~4months; for SN-ECSZ, it finds a strong ~14month periodic component. Unlike the Schuster spectrum, the MFPA has an exact modified statistic at non-Fourier frequencies. Informed by the MFPA period estimates, trigonometric models with periods of 12, 6, and 4months (Model 1) and 14.24 and 12months (Model 2) were fitted to time series of earthquake numbers. For CSAF-PKD, Model 1 shows a peak annual earthquake occurrence during August-November and a secondary peak in April. Similar peaks, or troughs, are found in annual and semiannual components of pole tide and tide-induced stress model time series and fault normal-stress reduction from seasonal hydrological unloading. For SN-ECSZ, the dominant ~14month periodicity prevents regular annual peaking, and Model 2 provides a better fit (Δ R-adjusted2: 2.4%). This new MFPA application resolves several periodicities in earthquake catalogs that reveal external periodic forcing.
Version 3.1 of the Generic Mapping Tools (GMT) has been released. More than 6000 scientists worldwide are currently using this free, public domain collection of UNIX tools that contains programs serving a variety of research functions. GMT allows users to manipulate (x,y) and (x,y,z) data, and generate PostScript illustrations, including simple x-y diagrams, contour maps, color images, and artificially illuminated, perspective, and/or shaded-relief plots using a variety of map projections (see Wessel and Smith [1991] and Wessel and Smith [1995], for details.). GMT has been installed under UNIX on most types of workstations and both IBM-compatible and Macintosh personal computers.
From December 2006 to November 2011, the Pacific Northwest Seismic Network (PNSN) reported 467 earthquakes in a swarm 60 km east of Mt Hood near the town of Maupin, Oregon. The swarm included 20 MD ≥ 3.0 events, which account for over 80 per cent of the cumulative seismic moment release of the sequence. Relocation of 45 MD ≥ 2.5 earthquakes and moment tensor analysis of nine 3.3 ≤ Mw ≤ 3.9 earthquakes reveals right-lateral strike-slip motion on a north-northwest trending, 70° west dipping, 1 km2 active fault patch at about 17 km depth. The swarm started at the southern end of the patch and migrated to the northwest at an average rate of 1-2 m d-1 during the first 18 months. Event migration was interrupted briefly in late 2007 when the swarm encountered a 10° fault bend acting as geometrical barrier. The slow migration rate suggests a pore pressure diffusion process. We speculate that the swarm was triggered by flow into the fault zone from upwards-migrating, subduction-derived fluids. Superimposed on the swarm is seasonal modulation of seismicity, with the highest rates in spring, which coincides with the maximum snow load in the nearby Cascade Mountains. The resulting surface load variation of about 4 × 1011 N km-1 arc length causes 1 cm annual vertical displacements at GPS sites in the Cascades and appears sufficient to modulate seismicity by varying normal stresses at the fault and fluid flow rates into the fault zone.
GPS is accurately recording vertical motion of Earth's surface in elastic response to seasonal changes in surface water storage in California. California's mountains subside up to 12 mm in the fall and winter due to the load of snow and rain, then rise an identical amount in the spring and summer when the snow melts, the rain runs off, and soil moisture evaporates. We invert the GPS observations of seasonal vertical motions to infer changes in equivalent water thickness. GPS resolves the distribution of change in total water across California's physiographic provinces at a resolution of 50 km, compared to 200 km resolution from GRACE. The seasonal surface water thickness change is 0.6 m in the Sierra Nevada, Klamath, and southern Cascade Mountains and decreases sharply to about 0.1 m east into the Great Basin and west toward the Pacific coast. GPS provides an independent inference of change in total surface water, indicating water storage to be on average 50 per cent larger than in the NLDAS–Noah hydrology model, likely due to larger changes in snow and reservoir water than in the model.
We determine a new relocated catalog, HYS_catalog_2011, for south-ern California from 1981 through June 2011. About 75.3% of the hypocenters are calculated with absolute and differential travel-time picks, and 24.7% could be relocated only by using absolute travel-time picks with 3D or 1D velocity models. The total catalog consists of more than 502,000 earthquakes in the region extending from Baja California in the south to Coalinga and Owens Valley in the north. The catalog consists of three M 7.1, M 7.2, and M 7.3 mainshocks; their foreshocks and aftershocks; and background seismicity caused by tectonic and other processes in the southern California crust. Hypocenters in the new relocated catalog exhibit tighter spatial clustering of seismicity than does the routinely generated catalog, and the depth distribution is tighter and reflects the thickness of the seismogenic zone more accurately. Compared to the standard catalog, the relocated hypocenters are more easily related to other data sets, such as mapped late Quaternary faults.
We use global positioning system (GPS) geodesy and synthetic aperture radar (SAR) interferometry to distinguish between interseismic strain accumulation and anthropogenic motion in metropolitan Los Angeles. We establish a relationship between horizontal and vertical seasonal oscillations of the Santa Ana aquifer, use this relationship to infer cumulative horizontal anthropogenic motions from cumulative vertical motions caused by water and oil resource management, and estimate horizontal interseismic velocities corrected for anthropogenic effects. Vertical anthropogenic rates from 1992 to 1999 are slower than 3 mm yr−1 in the Santa Ana and San Gabriel aquifers and faster than 5 mm yr−1 in the Chino aquifer and in many oil fields. Inferred horizontal anthropogenic velocities are faster than 1 mm yr−1 at 18 of 46 GPS sites. Northern metropolitan Los Angeles is contracting, with the 25 km south of the San Gabriel Mountains shortening at 4.5 ± 1 mm yr−1 (95% confidence limits). The thrust fault in an elastic edge dislocation model of the observed strain is creeping at 9 ± 2 mm yr−1 beneath and north of a position 6 ± 2 km deep and 8 ± 8 km north of downtown Los Angeles. The model fault is near the Los Angeles segment of the Puente Hills thrust but south of the Sante Fe Springs segment of the thrust. Disagreement between the 6 km locking depth in the model and the 15 km seismogenic depth inferred from earthquakes suggests that the elastic continuum model may be unsatisfactory; models with different stiffnesses of sedimentary basin and crystalline basement must be investigated.
[1] Detrended crustal deformation measurements from a global network of up to 200 continuous Global Positioning System (GPS) tracking sites are inverted for low degree and order (n, m less than or equal to 6) spherical harmonic series of surface mass variations. An independent geophysical model of the atmosphere, oceans, and water and snow on land is also used to guide the spherical harmonic truncation and to evaluate aliasing errors in the results. Inversion uncertainties decrease significantly as spatial coverage and data quality improve with time, especially in the last few years. Consequently, GPS inverted seasonal geocenter and low degree zonal harmonics converge to those determined by measurements from satellite laser ranging (SLR). Significant n > 1 and non-zonal variations have also been found.
We analyze seismic data from the San Andreas Fault (SAF) near Parkfield, California, to test for annual modulation in seismicity rates. We use statistical analyses to show that seismicity is modulated with an annual period in the creeping section of the fault and a semiannual period in the locked section of the fault. Although the exact mechanism for seasonal triggering is undetermined, it appears that stresses associated with the hydrologic cycle are sufficient to fracture critically stressed rocks either through pore-pressure diffusion or crustal loading/unloading. These results shed additional light on the state of stress along the SAF, indicating that hydrologically induced stress perturbations of ~2 kPa may be sufficient to trigger earthquakes.
To understand whether the 1992 M=7.4 Landers earthquake changed the proximity to failure on the San Andreas fault system, we examine the general problem of how one earthquake might trigger another. The tendency of rocks to fail in a brittle manner is thought to be a function of both shear and confining stresses, commonly formulated as the Coulomb failure criterion. Here we explore how changes in Coulomb conditions associated with one or more earthquakes may trigger subsequent events. We first consider a Coulomb criterion appropriate for the production of aftershocks, where faults most likely to slip are those optimally orientated for failure as a result of the prevailing regional stress field and the stress change caused by the main shock. We find that the distribution of aftershocks for the Landers earthquake, as well as for several other moderate events in its vicinity, can be explained by the Coulomb criterion: aftershocks are abundant where the Coulomb stress on optimally orientated faults rose by more than one-half bar, and aftershocks are sparse where the Coulomb stress dropped by a similar amount. Further, we find that several moderate shocks raised the stress at the future Landers epicenter and along much of the Landers rupture zone by about a bar, advancing the Landers shock by 1-3 centuries. The Landers rupture, in turn, raised the stress at site of the future M=6.5 Big Bear aftershock site by 3 bars. The Coulomb stress change on a specified fault is independent of regional stress but depends on the fault geometry, sense of slip, and the coefficient of friction. We use this method to resolve stress changes on the San Andreas and San Jacinto faults imposed by the Landers sequence. Together the Landers and Big Bear earthquakes raised the stress along the San Bernardino segment of the southern San Andreas fault by 2-6 bars, hastening the next great earthquake there by about a decade.
We mapped the minimum magnitude of complete reporting, Mc, for Alaska, the western United States, and for the JUNEC earthquake catalog of Japan. Mc was estimated based on its departure from the linear frequency-magnitude relation of the 250 closest earthquakes to grid
nodes, spaced 10 km apart. In all catalogs studied, Mc was strongly heterogeneous. In offshore areas the Mc was typically one unit of magnitude higher than onshore. On land also, Mc can vary by one order of magnitude over distance less than 50 km. We recommend that seismicity studies that depend on complete
sets of small earthquakes should be limited to areas with similar Mc, or the minimum magnitude for the analysis has to be raised to the highest common value of Mc. We believe that the data quality, as reflected by the Mc level, should be used to define the spatial extent of seismicity studies where Mc plays a role. The method we use calculates the goodness of fit between a power law fit to the data and the observed frequency-magnitude
distribution as a function of a lower cutoff of the magnitude data. Mc is defined as the magnitude at which 90% of the data can be modeled by a power law fit. Mc in the 1990s is approximately 1.2 ± 0.4 in most parts of California, 1.8 ± 0.4 in most of Alaska (Aleutians and Panhandle
excluded), and at a higher level in the JUNEC catalog for Japan. Various sources, such as explosions and earthquake families
beneath volcanoes, can lead to distributions that cannot be fit well by power laws. For the Hokkaido region we demonstrate
how neglecting the spatial variability of Mc can lead to erroneous assumptions about deviations from self-similarity of earthquake scaling.
We provide an explanation why earthquake occurrence does not correlate well with the daily solid Earth tides. The explanation is derived from analysis of laboratory experiments in which faults are loaded to quasiperiodic failure by the combined action of a constant stressing rate, intended to simulate tectonic loading, and a small sinusoidal stress, analogous to the Earth tides. Event populations whose failure times correlate with the oscillating stress show two modes of response; the response mode depends on the stressing frequency. Correlation that is consistent with stress threshold failure models, e.g., Coulomb failure, results when the period of stress oscillation exceeds a characteristic time tn; the degree of correlation between failure time and the phase of the driving stress depends on the amplitude and frequency of the stress oscillation and on the stressing rate. When the period of the oscillating stress is less than tn, the correlation is not consistent with threshold failure models, and much higher stress amplitudes are required to induce detectable correlation with the oscillating stress. The physical interpretation of tn is the duration of failure nucleation. Behavior at the higher frequencies is consistent with a second-order dependence of the fault strength on sliding rate which determines the duration of nucleation and damps the response to stress change at frequencies greater than 1/tn. Simple extrapolation of these results to the Earth suggests a very weak correlation of earthquakes with the daily Earth tides, one that would require >13,000 earthquakes to detect. On the basis of our experiments and analysis, the absence of definitive daily triggering of earthquakes by the Earth tides requires that for earthquakes, tn exceeds the daily tidal period. The experiments suggest that the minimum typical duration of earthquake nucleation on the San Andreas fault system is ∼1 year.
We find strong correlation between seasonal variation in CGPS time series and predicted response to annual snow load in Iceland. The load is modeled using Green's functions for an elastic halfspace and a simple sinusoidal load history on Iceland's four largest ice caps. We derive E = 40 ± 15 GPa as a minimum value for the effective Young's modulus in Iceland, increasing with distance from the Eastern Volcanic Zone. We calculate the elastic response over all of Iceland to maximum snow load at the ice caps using E = 40 GPa. Predicted annual vertical displacements are largest under the Vatnajökull ice cap with a peak-to-peak seasonal displacement of ∼37 mm. CGPS stations closest to the ice cap experience a peak-to-peak seasonal displacement of ∼16 mm, consistent with our model. East and north of Vatnajökull we find the maximum of annual horizontal displacements of ∼6 mm resulting in apparent modulation of plate spreading rates in this area.
For the period 1995–2000, the Nepal seismic network recorded 37 ± 8% fewer earthquakes in the summer than in the winter; for local magnitudes ML > 2 to ML > 4 the percentage increases from 31% to 63% respectively. We show the probability of observing this by chance is less than 1%. We find that most surface loading phenomena are either too small, or have the wrong polarity to enhance winter seismicity. We consider enhanced Coulomb failure caused by a pore-pressure increase at seismogenic depths as a possible mechanism. For this to enhance winter seismicity, however, we find that fluid diffusion following surface hydraulic loading would need to be associated with a six-month phase lag, which we consider to be possible, though unlikely. We favor instead the suppression of summer seismicity caused by stress-loading accompanying monsoon rains in the Ganges and northern India, a mechanism that is discussed in a companion article.
Earth deformation signals caused by atmospheric pressure loading are detected in vertical position estimates at Global Positioning System (GPS) stations. Surface displacements due to changes in atmospheric pressure account for up to 24% of the total variance in the GPS height estimates. The detected loading signals are larger at higher latitudes where pressure variations are greatest; the largest effect is observed at Fairbanks, Alaska (latitude 65 deg), with a signal root mean square (RMS) of 5 mm. Out of 19 continuously operating GPS sites (with a mean of 281 daily solutions per site), 18 show a positive correlation between the GPS vertical estimates and the modeled loading displacements. Accounting for loading reduces the variance of the vertical station positions on 12 of the 19 sites investigated. Removing the modeled pressure loading from GPS determinations of baseline length for baselines longer than 6000 km reduces the variance on 73 of the 117 baselines investigated. The slight increase in variance for some of the sites and baselines is consistent with expected statistical fluctuations. The results from most stations are consistent with approximately 65% of the modeled pressure load being found in the GPS vertical position measurements. Removing an annual signal from both the measured heights and the modeled load time series leaves this value unchanged. The source of the remaining discrepancy between the modeled and observed loading signal may be the result of (1) anisotropic effects in the Earth's loading response, (2) errors in GPS estimates of tropospheric delay, (3) errors in the surface pressure data, or (4) annual signals in the time series of loading and station heights. In addition, we find that using site dependent coefficients, determined by fitting local pressure to the modeled radial displacements, reduces the variance of the measured station heights as well as or better than using the global convolution sum.
We introduce a statistical methodology for clustering analysis of seismicity in the time-space-energy domain and use it to establish the existence of two statistically distinct populations of earthquakes: clustered and nonclustered. This result can be used, in particular, for nonparametric aftershock identification. The proposed approach expands the analysis of Baiesi and Paczuski [Phys. Rev. E 69, 066106 (2004)10.1103/PhysRevE.69.066106] based on the space-time-magnitude nearest-neighbor distance eta between earthquakes. We show that for a homogeneous Poisson marked point field with exponential marks, the distance eta has the Weibull distribution, which bridges our results with classical correlation analysis for point fields. The joint 2D distribution of spatial and temporal components of eta is used to identify the clustered part of a point field. The proposed technique is applied to several seismicity models and to the observed seismicity of southern California.
The mechanism responsible for the triggering of earthquakes remains one of the least-understood aspects of the earthquake process. The magnitude-7.3 Landers, California earthquake of 28 June 1992 was followed for several weeks by triggered seismic activity over a large area, encompassing much of the western United States. Here we show that this triggered seismicity marked the beginning of a five-year trend, consisting of an elevated microearthquake rate that was modulated by an annual cycle, decaying with time. The annual cycle is mainly associated with several hydrothermal or volcanic regions where short-term triggering was also observed. These data indicate that the Landers earthquake produced long-term physical changes in these areas, and that an environmental source of stress--plausibly barometric pressure--might be responsible for the annual variation.
More GPS stations, faster data delivery, and better data processing provide an abundance of information for all kinds of Earth scientists.
We analyze crustal strain corresponding to transient continuous Global Positioning System (cGPS) horizontal displacements in Northern California, detecting a seasonal positive dilatational strain and Coulomb stress transient in the South Napa region peaking just before the 24 August 2014 M6.0 South Napa earthquake. Using data from 2007 to 2014, we show that average dilatational strain within a 500-km² region encompassing South Napa and northern San Pablo Bay peaks in late summer at 76 ± 17 × 10⁻⁹, accompanied by a Coulomb stress change of 1.9 ± 0.8 kPa. The situation reverses in winter, with an average dilatational strain of −51 ± 17 × 10⁻⁹ and Coulomb stress change of −1.4 ± 0.8 kPa. Within a smaller 100-km² area centered on the South Napa rupture, peak values are considerably higher, including a summer Coulomb stress peak of 5.1 ± 1.6 kPa. We examine regional seismicity but see no statistically significant correlation with seasonal Coulomb stressing in the declustered earthquake catalog. Using western U.S. vertical cGPS displacements, we estimate that strain from hydrologic loading explains ≤10% of the observed long-wavelength strain and only 2–3% of peak strains around the South Napa rupture. Thermoelastic crustal strain estimated from temperature gradients between the San Francisco Bay and Sacramento Valley reaches values as high as 15% of the observed strain, but the strain patterns are not spatially consistent. Vertical deformation within the Sonoma and Napa Valley subbasins inferred from interferometric synthetic aperture radar explains large horizontal motions at nearby cGPS stations and suggests that seasonal changes in groundwater may contribute to observed strain and stress transients.
Glacial isostatic adjustment (GIA) is the main cause of deformation in intraplate North America. Here we use up to 3,271 Global Positioning System station velocities to image this 3-D deformation across the entire plate. We apply a new robust strain rate estimation algorithm (median estimation of local deformation), which does not require the assumption that part of the plate is unaffected by GIA, an assumption we show to be false. Our results show extension in the area underneath the Laurentide ice sheet, contrasted with a semiannular belt of horizontal contraction of up to ~4 × 10⁻⁹ yr⁻¹ around the former ice sheet. This contractional belt is kinematically linked to an ~1-2 mm yr⁻¹ far-field horizontal motion directed toward the ice sheet. Our results, together with a new robustly imaged vertical velocity field, are consistent with GIA as the main cause of deformation, although the contractional strain rates around the former ice sheet and the far-field horizontal velocities are significantly higher than those predicted by the ICE6G_C(VM5a) model. This finding suggests that our results, including the location of reversal in sign of horizontal motion relative to the ice sheet, will be useful to reevaluate the mantle viscosity structure used by GIA models. Besides the GIA-attributed deformation, we find almost no other region with significant strain accumulation. A plate-scale spatial correlation between strain rate and seismicity is absent, suggesting that GIA is a limited driver of contemporary seismogenesis and that intraplate seismicity must be attributable to factors other than secular strain accumulation.
Stresses in the lithosphere arises from multiple natural loading sources that include both surface and body forces. The largest surface loads include near-surface water storage, snow and ice, atmosphere pressure, ocean loading, and temperature changes. The solid Earth also deforms from celestial body interactions and variations in Earth's rotation. We model the seasonal stress changes in California from 2006 through 2014 for seven different loading sources with annual periods to produce an aggregate stressing history for faults in the study area. Our modeling shows that the annual water loading, atmosphere, temperature, and Earth pole-tides are the largest loading sources and should each be evaluated to fully describe seasonal stress changes. In California we find the hydrological loads are the largest source of seasonal stresses. We explore the seasonal stresses with respect to the background principal stress orientation constrained with regional focal mechanisms and analyze the modulation of seismicity. Our results do not suggest a resolvable seasonal variation for the ambient stress orientation in the shallow crust. When projecting the seasonal stresses into the background stress orientation we find the timing of microseismicity modestly increases from a ~8 kPa seasonal mean-normal-stress perturbation. The results suggest faults in California are optimally oriented with the background stress field and respond to subsurface pressure changes, possibly due to processes we have not considered in this study. At any time a population of faults are near failure as evident from earthquakes triggered by these slight seasonal stress perturbations.
Establishing what controls the timing of earthquakes is fundamental to understanding the nature of the earthquake cycle and critical to determining time-dependent earthquake hazard. Seasonal loading provides a natural laboratory to explore the crustal response to a quantifiable transient force. In California, water storage deforms the crust as snow and water accumulates during the wet wintermonths.We used 9 years of global positioning system (GPS) vertical deformation time series to constrain models of monthly hydrospheric loading and the resulting stress changes on fault planes of small earthquakes.The seasonal loading analysis reveals earthquakes occurring more frequently during stress conditions that favor earthquake rupture.We infer that California seismicity rates are modestly modulated by natural hydrological loading cycles.
We document space-dependent clustering properties of earthquakes with m ≥ 4 in the 1975–2015 worldwide seismic catalog of the Northern California Earthquake Data Center. Earthquake clusters are identified using a nearest-neighbor distance in time-space-magnitude domain. Multiple cluster characteristics are compared with the heat flow level and type of deformation defined by parameters of the strain rate tensor. The analysis suggests that the dominant type of seismicity clusters in a region depends strongly on the heat flow, while the deformation style and intensity play a secondary role. The results show that there are two dominant types of global clustering: burst-like clusters that represent brittle fracture in relatively cold lithosphere (e.g., shallow events in subduction zones) and swarm-like clusters that represent brittle-ductile deformation in relatively hot lithosphere (e.g., mid-oceanic ridges). The global results are consistent with theoretical expectations and previous analyses of earthquake clustering in southern California based on higher quality catalogs. The observed region-specific deviations from average universal description of seismicity provide important constraints on the physics governing earthquakes and can be used to improve local seismic hazard assessments.
Two types of signals are clearly visible in continuous GPS (cGPS) time-series in Iceland, in particular in the vertical component. The first one is a yearly seasonal cycle, usually sinusoidlike with a minimum in the spring and a maximum in the fall. The second one is a trend of uplift, with higher values the closer the cGPS stations are to the centre of Iceland and ice caps. Here, we study the seasonal cycle signal by deriving its average at 71 GPS sites in Iceland.We estimate the annual and semi-annual components of the cycle in their horizontal and vertical components using a least-squares adjustment. The peak-to-peak amplitude of the cycle of the vertical component at the studied sites ranges from 4 mm near the coastline up to 27 mm at the centre of the Vatnajökull, the largest ice cap in Iceland. The minimum of the seasonal cycle occurs earlier in low lying areas than in the central part of Iceland, consistent with snow load having a large influence on seasonal deformation. Modelling shows that the seasonal cycle is well explained by accounting for elastically induced surface displacements due to snow, atmosphere, reservoir lake and ocean variations. Model displacement fields are derived considering surface loads on a multilayered isotropic spherical Earth. Through forward and inverse modelling, we were able to reproduce a priori information on the average seasonal cycle of known loads (atmosphere, snow in non-glaciated areas and lake reservoir) and get an estimation of other loads (glacier mass balance and ocean). The seasonal glacier mass balance cycle in glaciated areas and snow load in non-glaciated areas are the main contributions to the seasonal deformation. For these loads, induced seasonal vertical displacements range from a few millimetres far from the loads in Iceland, to more than 20 mm at their centres. Lake reservoir load also has to be taken into account on local scale as it can generate up to 20 mm of vertical deformation. Atmosphere load and ocean load are observable and generate vertical displacements in the order of a few millimetres. Inversion results also shows that the Iceland crust is less rigid than the world average. Interannual deviation from the GPS seasonal cycle can occur and are caused by unusual weather conditions over extended period of time. © The Authors 2016. Published by Oxford University Press on behalf of The Royal Astronomical Society.
We review the theory of the Earth's elastic and gravitational response to a surface disk load. The solutions for displacement of the surface and the geoid are developed using expansions of Legendre polynomials, their derivatives and the load Love numbers. We provide a matlab function called
Diskload
that computes the solutions for both uncompensated and compensated disk loads. In order to numerically implement the Legendre expansions, it is necessary to choose a harmonic degree, nmax, at which to truncate the series used to construct the solutions. We present a rule of thumb (ROT) for choosing an appropriate value of nmax, describe the consequences of truncating the expansions prematurely and provide a means to judiciously violate the ROT when that becomes a practical necessity.
Using a probabilistic approximation of a mean-field mechanistic model of sheared systems, we analytically calculate the statistical properties of large failures under slow shear loading. For general shear F(t), the distribution of waiting times between large system-spanning failures is a generalized exponential distribution, ρT(t)=λ(F(t))P(F(t))exp−∫0tdτλ(F(τ))P(F(τ)), where λ(F(t)) is the rate of small event occurrences at stress F(t) and P(F(t)) is the probability that a small event triggers a large failure. We study the behavior of this distribution as a function of fault properties, such as heterogeneity or shear rate. Because the probabilistic model accommodates any stress loading F(t), it is particularly useful for modeling experiments designed to understand how different forms of shear loading or stress perturbations impact the waiting-time statistics of large failures. As examples, we study how periodic perturbations or fluctuations on top of a linear shear stress increase impact the waiting-time distribution.
Field and laboratory observations show that seismicity has non-trivial period-dependent response to periodic stress perturbations. In Nepal, seismicity shows significant variations in response to annual monsoon-induced stress variations but not to semidiurnal tidal stresses of the same magnitude. Such period dependence cannot be explained by the Coulomb failure model and spring-slider rate-and-state model (SRM). Here, we study seismicity response to periodic stress perturbations in a 2-D continuum model of a rate-and-state fault (that is, a finite rate-and-state fault). We find that the resulting seismicity indeed exhibits nearly periodic variations. Their amplitude is maximum at a certain period, T-a, and decreases with smaller and larger periods to the SRM predictions, remaining much larger than the SRM predictions for a wide range of periods around T-a. We attribute the higher sensitivity of finite faults to their finite nucleation zones which vary in space and have a different slip-velocity evolution than that of the SRM. At periods T >> T-a and T << T-a, the seismicity-rate variations are in phase with the stress-rate and stress variations, respectively, consistent with the SRM, although a gradual phase shift appears as T increases towards T-a. Based on the similarities with the SRM and our simulations, we propose a semi-analytical expression for T-a. Plausible sets of model parameters make T-a equal to 1 yr, potentially explaining Nepal observations and constraining the fault properties. Our finite-fault findings indicate that alpha sigma, where alpha is a rate-and-state parameter and sigma is the effective normal stress, can be severely underestimated based on the SRM.
The western United States has been experiencing severe drought since 2013. The solid earth response to the accompanying loss
of surface and near-surface water mass should be a broad region of uplift. We use seasonally adjusted time series from continuously
operating global positioning system stations to measure this uplift, which we invert to estimate mass loss. The median uplift
is 5 millimeters (mm), with values up to 15 mm in California’s mountains. The associated pattern of mass loss, ranging up
to 50 centimeters (cm) of water equivalent, is consistent with observed decreases in precipitation and streamflow. We estimate
the total deficit to be ~240 gigatons, equivalent to a 10-cm layer of water over the entire region, or the annual mass loss
from the Greenland Ice Sheet.
Groundwater use in California's San Joaquin Valley exceeds replenishment of the aquifer, leading to substantial diminution of this resource and rapid subsidence of the valley floor. The volume of groundwater lost over the past century and a half also represents a substantial reduction in mass and a large-scale unburdening of the lithosphere, with significant but unexplored potential impacts on crustal deformation and seismicity. Here we use vertical global positioning system measurements to show that a broad zone of rock uplift of up to 1-3 mm per year surrounds the southern San Joaquin Valley. The observed uplift matches well with predicted flexure from a simple elastic model of current rates of water-storage loss, most of which is caused by groundwater depletion. The height of the adjacent central Coast Ranges and the Sierra Nevada is strongly seasonal and peaks during the dry late summer and autumn, out of phase with uplift of the valley floor during wetter months. Our results suggest that long-term and late-summer flexural uplift of the Coast Ranges reduce the effective normal stress resolved on the San Andreas Fault. This process brings the fault closer to failure, thereby providing a viable mechanism for observed seasonality in microseismicity at Parkfield and potentially affecting long-term seismicity rates for fault systems adjacent to the valley. We also infer that the observed contemporary uplift of the southern Sierra Nevada previously attributed to tectonic or mantle-derived forces is partly a consequence of human-caused groundwater depletion.
We show that the Schuster test alone does not provide a sufficient
condition to assert the existence of a periodicity in an earthquake
catalog. Such periodicities can be detected by computing a spectrum of
Schuster p-values (the probability to observe such a level of periodic
variations in a catalog occurring out of a constant seismicity rate). We
show that the detection level is slightly period dependent, and we
provide an analytical expression relating the amplitude of
seismicity-rate variations to the confidence level at which the
probability that the observed variations be due to chance can be
discarded. The Schuster spectrum also provides information about the
deviation from a sinusoidal function of the periodicity of the
seismicity rate, and identifies an eventual imperfect declustering of
the catalog, making it coincidently a potential tool to determine
whether or not a catalog has been properly declustered. Applying this
tool to the Nepalese seismicity, we demonstrate annual variations of the
seismicity rate of amplitude up to 40%, while no other periodicity
appears. In particular, no variations of seismicity at any of the tidal
periods are observed, indicating that the relative amplitude response of
the seismicity at these periods is less than 18%.
Strainmeter records in three 176-323 m deep boreholes near Parkfield,
CA, are dominated by seasonal fluctuations. We show that a significant
part of the seasonal data may result from thermoelastic strain induced
by atmospheric temperature variations. We test this hypothesis by
computing thermoelastic strain in an elastic half-space covered by a
thin unconsolidated layer from atmospheric temperature and comparing the
results to the borehole strain records. The strain at depth is produced
by the temperature field at the bottom of the unconsolidated layer. The
model provides reasonable fits to the amplitudes and phases of the
seasonal borehole signals. The two key model parameters, thickness of
the unconsolidated layer (˜0.3-1.2 m at the used sites) and
wavelength of the temperature field (3 km), are sufficiently plausible
to support the physical validity of the model. Two instances with
persistent deviations between the trends of the predicted thermoelastic
strain and observed records may reflect shallow postseismic effects of
M⩾4 nearby earthquakes.
[1] We use recent results on statistical analysis of seismicity to present a robust method for comprehensive detection and analysis of earthquake clusters. The method is based on nearest-neighbor distances of events in space-time-energy domain. The method is applied to a 1981–2011 relocated seismicity catalog of southern California having 111,981 events with magnitudes m ≥ 2 and corresponding synthetic catalogs produced by the Epidemic Type Aftershock Sequence (ETAS) model. Analysis of the ETAS model demonstrates that the cluster detection results are accurate and stable with respect to (1) three numerical parameters of the method, (2) variations of the minimal reported magnitude, (3) catalog incompleteness, and (4) location errors. Application of the method to the observed catalog separates the 111,981 examined earthquakes into 41,393 statistically significant clusters comprised of foreshocks, mainshocks, and aftershocks. The results reproduce the essential known statistical properties of earthquake clusters, which provide overall support for the proposed technique. In addition, systematic analysis with our method allows us to detect several new features of seismicity that include (1) existence of a significant population of single-event clusters, (2) existence of foreshock activity in natural seismicity that exceeds expectation based on the ETAS model, and (3) dependence of all cluster properties, except area, on the magnitude difference of events from mainshocks but not on their absolute values. The classification of detected clusters into several major types, generally corresponding to singles, burst-like and swarm-like sequences, and correlations between different cluster types and geographic locations is addressed in a companion paper.
[1] Two catalogs of episodic tremor events in northern Cascadia, one from 2006 to 2012 and the other from 1997 to 2011, reveal two systematic patterns of tremor occurrence in southern Vancouver Island: (1) most individual events tend to occur in the third quarter of the year; (2) the number of events in prolonged episodes (i.e., episodic tremor and slip events), which generally propagate to Vancouver Island from elsewhere along the Cascadia subduction zone, is inversely correlated with the amount of precipitation that occurred in the preceding 2 months. We rationalize these patterns as the product of hydrologic loading of the crust of southern Vancouver Island and the surrounding continental region, superimposed with annual variations from oceanic tidal loading. Loading of the Vancouver Island crust in the winter (when the land surface receives ample precipitation) and unloading in the summer tends to inhibit and enhance downdip shear stress, respectively. Quantitatively, for an annually variable surface load, the predicted stress perturbation depends on mantle viscoelastic rheology. A mechanical model of downdip shear stress on the transition zone beneath Vancouver Island—driven predominantly by the annual hydrologic cycle—is consistent with the 1997–2012 tremor observations, with peak-to-peak downdip shear stress of about 0.4 kPa. This seasonal dependence of tremor occurrence appears to be restricted to southern Vancouver Island because of its unique situation as an elongated narrow-width land mass surrounded by ocean, which permits seasonal perturbations in shear stress at depth.
[1] We find seasonal horizontal crustal motions observed by GPS positioning in elastic response to heavy rainfall in the Amazon Basin and to monsoons in Southeast Asia to be consistent with those inferred from Gravity Recovery and Climate Experiment (GRACE) gravity observations of water mass loading. Solid Earth moves toward the Amazon during heavy spring rainfall and toward Southeast Asia during summer monsoons and back away from these areas 6 months later when the water load is minimum. Vertical oscillations observed by GPS and inferred from GRACE are 2 to 3 times larger than horizontal oscillation near the margins of the areas of large mass loading. Some discrepancies between GPS and GRACE are probably caused by local effects that influence GPS measurements, because the GPS sites that show significant discrepancies also do not match nearby GPS sites. However, when the load is short wavelength, the limited spatial resolution of GRACE can cause systematic misfits.
describe how GPS measurements of horizontal crustal motion can be used
to augment vertical crustal motion measurements, to improve and extend
GPS studies of surface loading. We show that the ratio of the vertical
displacement to the horizontal displacement, combined with the direction
of the horizontal motion, can help determine whether nearby loading is
concentrated in a small region (for example, in a single lake or
glacier), and where that region is. We illustrate this method by
applying it to two specific cases: an analysis of GPS data from northern
California to monitor the level of Lake Shasta, and the analysis of data
from a single GPS site in southeast Greenland to determine mass
variability of two large, nearby outlet glaciers: Helheim Glacier and
Midgaard Glacier. The California example serves largely as a
proof-of-concept, where the results can be assessed by comparing with
independent observations (Lake Shasta tide gauge data, in this case).
Our Greenland results show that both Helheim and Midgaard have
experienced notable interannual variations in mass loss rate over the
last decade. Helheim's mass loss accelerated rapidly in mid-2003,
decelerated in late 2005, and increased again in 2008-2009 before
returning to about its pre-2003 rate in late 2010. Midgaard's mass loss
accelerated in mid-2004, and remained more-or-less constant before
returning to its pre-2003 rate in late 2008.
The seasonal modulation of seismicity observed in Nepal is given to be
related to subtle stress changes, induced by strong seasonal variations
of ground deformation. Horizontal and vertical seasonal variations are
observed on GPS times series from stations located in Nepal, India and
Tibet (China). We demonstrate that this geodetic deformation is induced
by seasonal variations of continental water storage driven by the
Monsoon. We use data from the Gravity Recovery and Climate Experiment
(GRACE) to determine the time evolution of surface loading. We compute
the expected geodetic deformation assuming a perfectly elastic Earth
model. We consider Green's functions, describing the surface deformation
response to a point load, for an elastic homogeneous half-space model
and for a layered non-rotating spherical Earth model based on the
Preliminary Reference Earth Model (PREM) and a local seismic velocity
model. The amplitude and phase of the seasonal variation of the vertical
and horizontal geodetic positions can be jointly adjusted only with the
layered Earth model. The study emphasizes the importance of using a
realistic Earth elastic structure to model surface displacements induced
by surface loading. The study also shows that the modeling of geodetic
seasonal variations provides a way to probe the Elastic structure of the
Earth, even in the absence of direct measurements of surface load
variations. Finally, it enhances the possibility of evaluating, with
smaller uncertainties, the subtle stress changes given to be responsible
for the seasonal variations of seismicity.
Two sites of the BARGEN GPS network are located ~30 km south of Great Salt Lake (GSL). Lake-level records since mid-1996 indicate seasonal water elevation variations of ~0.3 m amplitude superimposed on a roughly ``decadal'' feature of amplitude ~0.6 m. Using an elastic Green's function and a simplified load geometry for GSL, we calculate that these variations translate into radial crustal loading signals of +/-0.5 mm (seasonal) and +/-1 mm (decadal). The horizontal loading signals are a factor of ~2 smaller. Despite the small size of the expected loading signals, we conclude that we can observe them using GPS time series for the coordinates of these two sites. The observed amplitudes of the variations agree with the predicted decadal variations to
Rainfall seasonality is clearly crucial to the hydrological, geomorphological, erosional, biological, ecological and agricultural impacts of a given annual precipitation total. However, meaningful comparisons of rainfall seasonality across space, or through time at single locations, can only be made if there is some quantification of this aspect of rainfall regimes. Many contemporary climate sources still only describe rainfall regimes and seasonality in qualitative terms. In this paper, a simple Seasonality Index (SI), designed to assess a key aspect of rainfall seasonality, is derived from monthly data and presented. Low seasonality areas attract SI values close to zero. Stations marked by extreme seasonality, with rainfall in 1-2 months only, return SI values at and above 1. It is shown by applications of this index across the world, including for the UK and Ireland (109 rainfall stations), Africa (224 stations) and also in central and South America and the Pacific, that it is possible quickly to analyse, categorise and plot spatial variations in rainfall seasonality (as for other climate variables) at local, national or continental scales. Such analyses can also help in pure or applied research to predict or interpret patterns of variables which may respond to rainfall seasonality specifically (e.g. river discharge; plant growth; crop yield and quality; habitats).
RESULTS. Results for the UK show clear increases in rainfall seasonality towards the west and north of the country, and is strongly linked to absolute annual rainfall totals. The same positive relation between average annual precipitation and seasonality occurs for Ireland, with low rainfall seasonality in the east around Dublin, and clear increases in SI towards the west. In Guyana, however, the relationship between annual rainfall and rainfall seasonality is shown to be inverse. Africa returns high rainfall seasonality values in the North, low scores in tropical regions, before they rise again to moderate levels in southern areas.
Another area of novelty in the paper, which adds a new dimension to global climate change research, is the analysis of CHANGE OVER TIME IN RAINFALL SEASONALITY, with respect to (a) the variability of the seasonal incidence of rainfall from year to year, and (b) long-term change and cyclicity in rainfall seasonality. Examples are discussed for Georgetown (Guyana) over an 80-year period.
1] We simultaneously reanalyzed two decades (1984–2003) of the digital seismic archive of Northern California using waveform cross-correlation (CC) and double-difference (DD) methods to improve the resolution in hypocenter locations in the existing earthquake catalog generated at the Northern California Seismic Network (NCSN) by up to three orders of magnitude. We used a combination of $3 billion CC differential times measured from all correlated pairs of events that are separated by less than 5 km and $7 million P wave arrival-time picks listed in the NCSN bulletin. Data were inverted for precise relative locations of 311,273 events using the DD method. The relocated catalog is able to image the fine-scale structure of seismicity associated with active faults and revealed characteristic spatiotemporal structures such as streaks and repeating earthquakes. We found that 90% of the earthquakes have correlated P wave and S wave trains at common stations and that 12% are colocated repeating events. An analysis of the repeating events indicates that uncertainties at the 95% confidence level in the existing network locations are on average 0.7 km laterally and 2 km vertically. Correlation characteristics and relative location improvement are remarkably similar across most of Northern California, implying the general applicability of these techniques to image high-resolution seismicity caused by a variety of plate tectonic and anthropogenic processes. We show that consistent long-term seismic monitoring and data archiving practices are key to increase resolution in existing hypocenter catalogs and to estimate the precise location of future events on a routine basis. Citation: Waldhauser, F., and D. P. Schaff (2008), Large-scale relocation of two decades of Northern California seismicity using cross-correlation and double-difference methods, J. Geophys. Res., 113, B08311, doi:10.1029/2007JB005479.
1] We suggest that strain in the elastic part of the Earth's crust induced by surface temperature variations is a significant contributor to the seasonal variations observed in the spatially filtered daily position time series of Southern California Integrated GPS Network (SCIGN) stations. We compute the predicted thermoelastic strain from the observed local atmospheric temperature record assuming an elastically decoupled layer over a uniform elastic half-space and compare the seasonal variations in thermoelastic strain to the horizontal GPS position time series. We consider three regions (Palmdale, 29 Palms, and Idyllwild), each with one temperature station and three to six GPS stations. The temperature time series is used to compute thermoelastic strain at each station on the basis of its relative location in the temperature field. For each region we assume a wavelength for the temperature field that is related to the local topography. The depth of the decoupled layer is inferred from the phase delay between the temperature record and the GPS time series. The relative amplitude of strain variation at each GPS station, calculated to be on the order of 0.1 mstrain, is related to the relative location of that station in the temperature field. The goodness of fit between model and data is evaluated from the relative amplitudes of the seasonal signals, as well as the appropriateness of the chosen temperature field wavelength and decoupled layer depth. The analysis shows a good fit between the predicted strains and the GPS time series. This suggests that the model captures the key first-order ingredients that determine the thermoelastic strain in a given area. The results can be used to improve the signal/noise ratio in GPS data.
It is known that GPS time series contain a seasonal variation that is not due to tectonic motions, and it has recently been shown that crustal seismic velocities may also vary seasonally. In order to explain these changes, a number of hypotheses have been given, among which thermoelastic and hydrology-induced stresses and strains are leading candidates. Un-fortunately, though, since a general framework does not exist for understanding such seasonal variations, it is currently not possible to quickly evaluate the plausibility of these hypotheses. To fill this gap in the literature, I generalize a two-dimensional thermoelastic strain model to provide an analytic solution for the displacements and wave speed changes due to either ther-moelastic stresses or hydrologic loading, which consists of poroelastic stresses and purely elas-tic stresses. The thermoelastic model assumes a periodic surface temperature, and the hydro-logic models similarly assume a periodic near-surface water load. Since all three models are two-dimensional and periodic, they are expected to only approximate any realistic scenario; but the models nonetheless provide a quantitative framework for estimating the effects of ther-moelastic and hydrologic variations. Quantitative comparison between the models and obser-vations is further complicated by the large uncertainty in some of the relevant parameters. De-spite this uncertainty, though, I find that maximum realistic thermoelastic effects are unlikely to explain a large fraction of the observed annual variation in a typical GPS displacement time series or of the observed annual variations in seismic wave speeds in Southern California. Hy-drologic loading, on the other hand, may be able to explain a larger fraction of both the an-nual variations in displacements and seismic wave speeds. Neither model is likely to explain all of the seismic wave speed variations inferred from observations. However, more definitive conclusions cannot be made until the model parameters are better constrained.
Terra Nova, 23, 19–25, 2011
A significant seasonal modulation of seismicity, with a peak in spring and summer, is evidenced in the Himalaya and the Alps, two regions characterized by present day mountain building and glacial retreat. In addition, a secular modulation of seismicity, which can be correlated with surface atmospheric temperature changes in the Northern Hemisphere, is found over the last ten centuries. Therefore, secular variations in permanent glacial dimensions, naturally associated with long-term average surface atmospheric temperature changes, and seasonal snow load may cause crustal deformations that modulate seismicity.
Snow load along the western flank of the backbone range of the Japanese Islands causes seasonal crustal deformation. It perturbs the interseismic strain buildup, and may seasonally influence the seismicity in Japan. Intraplate earthquakes in northeastern Japan occur on reverse faults striking parallel with the snow-covered zone. In central and southwestern Japan, they occur on strike-slip faults striking either parallel with, or perpendicular to the snow cover. The snow load enhances compression at these faults, reducing the Coulomb failure stress by a few kPa. This is large enough to modulate the secular stress buildup of a few tens of kPa/yr. Past inland earthquakes with magnitudes ≥7.0 that occurred in regions covered with snow in winter, tend to occur more in spring and summer than in autumn and winter, while those in the snow-free regions do not show such variation. Although its statistical significance is not strong due to limited number of past earthquakes, it suggests that the spring thaw enhances seismicity beneath the snow cover.
One way to probe earthquake nucleation processes and the relation between stress buildup and seismicity is to analyze the sensitivity of seismicity to stress perturbations. Here, we report evidence for seasonal strain and stress (~ 2–4 kPa) variations in the Nepal Himalaya, induced by water storage variations which correlate with seasonal variations of seismicity. The seismicity rate is twice as high in the winter as in the summer, and correlates with stress rate variations. We infer ~ 10–20 kPa/yr interseismic stress buildup within the seismicity cluster along the high Himalaya front. Given that Earth tides exert little influence on Himalayan seismicity, the correlated seasonal variation of stress and seismicity indicates that the duration of earthquake nucleation in the Himalaya is of the order of days to month, placing constraints on faults friction laws. The unusual sensitivity of seismicity to small stress changes in the Himalaya might be due to high pore pressure at seismogenic depth.
We examine 20-yr data sets of seismic activity from 10 volcanic areas in the western United States for annual periodic signals (seasonality), focusing on large calderas (Long Valley caldera and Yellowstone) and stratovolcanoes (Cascade Range). We apply several statistical methods to test for seasonality in the seismic catalogs. In 4 of the 10 regions, statistically significant seasonal modulation of seismicity (> 90% probability) occurs, such that there is an increase in the monthly seismicity during a given portion of the year. In five regions, seasonal seismicity is significant in the upper 3 km of the crust. Peak seismicity occurs in the summer and autumn in Mt. St. Helens, Hebgen Lake/Madison Valley, Yellowstone Lake, and Mammoth Mountain. In the eastern south moat of Long Valley caldera (LVC) peak seismicity occurs in the winter and spring. We quantify the possible external forcing mechanisms that could modulate seasonal seismicity. Both snow unloading and groundwater recharge can generate large stress changes of > 5 kPa at seismogenic depths and may thus contribute to seasonality.
Results of stability analyses for spring and slider systems, with state variable constitutive properties, are applied to slip on embedded fault patches. Unstable slip may nucleate only if the slipping patch exceeds some minimum size. Subsequent to the onset of instability the earthquake slip may propagate well beyond the patch. It is proposed that the seismicity of a volume of the earth's crust is determined by the distribution of initial conditions on the population of fault patches that nucleate earthquake slip, and the loading history acting upon the volume. Patches with constitutive properties inferred from laboratory experiments are characterized by an interval of self-driven accelerating slip prior to instability, if initial stress exceeds a minimum threshold. This delayed instability of the patches provides an explanation for the occurrence of aftershocks and foreshocks including decay of earthquake rates by time−1. A population of patches subjected to loading with a periodic component results in periodic variation of the rate of occurrence of instabilities. The change of the rate of seismicity for a sinusoidal load is proportional to the amplitude of the periodic stress component and inversely proportional to both the normal stress acting on the fault patches and the constitutive parameter, A1, that controls the direct velocity dependence of fault slip. Values of A1 representative of laboratory experiments indicate that in a homogeneous crust, correlation of earthquake rates with earth tides should not be detectable at normal stresses in excess of about 8 MPa. Correlation of earthquakes with tides at higher normal stresses can be explained if there exist inhomogeneities that locally amplify the magnitude of the tidal stresses. Such amplification might occur near magma chambers or other soft inclusions in the crust and possibly near the ends of creeping fault segments if the creep or afterslip rates vary in response to tides. Observations of seismicity rate variations associated with seasonal fluctuations of reservoir levels appear to be consistent with the model.
Seasonality of earthquake occurrence and its relations to meteorological phenomena were investigated in a number of seismically active areas of the world. For this purpose, the worldwide data set by NOAA, a historical earthquake data set in China and Korea, and also a microearthquake data set in Japan were analyzed by the use of a point process analysis method recently developed by Ogata (1983). By systematic and quantitative treatments, various characteristics of seasonality of earthquake occurrence were elucidated globally. Some areas showing clear seasonality of earthquake occurrence were found. Those areas are all situated in the middle latitude zone, and most of them are located in the intraplate seismic region just behind the active interplate seismic zone. On the other hand, seasonality of earthquake occurrence was not observed at all in oceanic regions and tropical regions. Correlations between seasonal variation of seismic activity and variations of precipitation and of its rate of change were high in areas with clear seasonality. This phenomenon was explained by a triggering effect of groundwater which penetrated into cracks of the crustal rocks.