DIN 18301 – Bohrarbeiten

Bielefeld, Bert; Fröhlich, Peter J.

doi:10.1007/978-3-658-00105-6_4

Cited by 2 publications

(3 citation statements)

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“…These changes in the subsurface can eventually result in fault slip and trigger earthquakes . For example, Frohlich and Brunt (2013) Antonio and Austin residents. The increase in magnitude and frequency of these large seismic events requires further scientific investigation, and InSAR data can play an important role in these future induced seismicity studies.…”

Section: The Eagle Ford Region Resultsmentioning

confidence: 99%

“…These changes in the subsurface can eventually result in fault slip and trigger earthquakes . For example, Frohlich and Brunt (2013) 165, 341, 336, 349 earthquakes recorded in 2017165, 341, 336, 349 earthquakes recorded in -2018165, 341, 336, 349 earthquakes recorded in , 2019165, 341, 336, 349 earthquakes recorded in -2020165, 341, 336, 349 earthquakes recorded in , 2021165, 341, 336, 349 earthquakes recorded in -2022165, 341, 336, 349 earthquakes recorded in , 2023165, 341, 336, 349 earthquakes recorded in -March 13, 2024, respectively (Fig. 4a) .…”

Section: The Eagle Ford Region Resultsmentioning

confidence: 99%

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A robust method for selecting a high-quality interferogram subset in InSAR surface deformation analysis

Zebker,

Chen

2024

Preprint

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The accuracy of surface deformation derived from Interferometric Synthetic Aperture Radar (InSAR) observations depends on the quality of the chosen interferogram subset. We present a method to select interferogram subsets based on unwrapping errors rather than temporal baseline thresholds. Using Sentinel-1 interferograms over the Tulare Basin (CA), we show that tropospheric noise dominates short temporal baseline subset solutions (with up to 2.9 cm/yr residuals at co-located GPS sites), while decorrelation leads to a systematic underestimation of true deformation rate in long temporal baseline subset solutions (with up to 5.5 cm/yr residuals). Our new workflow better mitigates these two noise sources at the same time. In the Eagle Ford (TX) region, our strategy revealed up to ~11 cm of cumulative line-of-sight (LOS) deformation over a ~900 km2 region. This deformation feature is associated with ongoing oil and gas activities and is reported for the first time here.

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Section: The Eagle Ford Region Resultsmentioning

confidence: 99%

Section: The Eagle Ford Region Resultsmentioning

confidence: 99%

A robust method for selecting a high-quality interferogram subset in InSAR surface deformation analysis

Zebker,

Chen

2024

Preprint

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“…The variations of the TSI have been reliable observed by precise radiometers during more than the 11-years of the solar activity cycle, and is about 0.1% or 1.3 W m −2 . Over a solar rotation time scale the variation caused but large sunspots can be as high as 0.5% (see, Fröhlich 2013).…”

Section: Solar and Stellar Brightness Variabilitymentioning

confidence: 99%

Understanding the brightness variations of Sun-like stars on timescales of stellar rotation

Gomez¹,

Maritza²

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Twenty-four years after the discoveries of the first exoplanets, the radial-velocity (RV) method is still one of the most productive techniques to detect and confirm exoplanets. But stellar magnetic activity can induce RV variations large enough to make it difficult to disentangle planet signals from the stellar noise. In this context, HD41248 is an interesting planet-host candidate, with RV observations plagued by activity-induced signals. We report on ESPRESSO observations of HD41248 and analyse them together with previous observations from HARPS with the goal of evaluating the presence of orbiting planets. Using different noise models within a general Bayesian framework designed for planet detection in RV data, we test the significance of the various signals present in the HD41248 dataset. We use Gaussian processes as well as a first-order moving average component to try to correct for activity-induced signals. At the same time, we analyse photometry from the TESS mission, searching for transits and rotational modulation in the light curve. The number of significantly detected Keplerian signals depends on the noise model employed, which can range from 0 with the Gaussian process model to 3 with a white noise model. We find that the Gaussian process alone can explain the RV data while allowing for the stellar rotation period and active region evolution timescale to be constrained. The rotation period estimated from the RVs agrees with the value determined from the TESS light curve. Based on the data that is currently available, we conclude that the RV variations of HD41248 can be explained by stellar activity (using the Gaussian process model) in line with the evidence from activity indicators and the TESS photometry.

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DIN 18301 – Bohrarbeiten

Cited by 2 publications

References 0 publications

A robust method for selecting a high-quality interferogram subset in InSAR surface deformation analysis

A robust method for selecting a high-quality interferogram subset in InSAR surface deformation analysis

Understanding the brightness variations of Sun-like stars on timescales of stellar rotation

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