Earth and Space Science

Journal: Earth and Space Science

Publisher

American Geophysical Union

ISSN

2333-5084

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Publications 1 - 10 of 26

Applications of Time-Frequency Domain Polarization Filtering to InSight Seismic Data
Brinkman, Nienke; Sollberger, David Andres; Schmelzbach, Cédric; et al. (2023)
Earth and Space Science
The seismometer Seismic Experiment for Interior Structure (SEIS) onboard the InSight lander was used to continuously record the seismicity on Mars from February 2019 to December 2022. To maximize the information that can be extracted from the seismic data, it is critical to identify and to suppress undesired features (e.g., environmental noise, scattered waves, seismic imprint of lander vibrations) and non-seismic noise (e.g., instrument related artifacts). We present an advanced polarization filtering workflow in the time-frequency domain to suppress undesired features and to enhance the signal-to-noise ratio of the SEIS recordings. We estimate time-frequency-dependent polarization attributes such as the ellipticity, directionality of the particle motion, and the degree of polarization to identify and filter out undesired data parts. After filtering in the time-frequency domain, the seismic data are transformed back to the time domain, yielding broadband waveform data that can be used for further seismological analysis. We illustrate the benefits of our filtering approach with three use cases. Firstly, we show how polarization filtered data can help to constrain the source mechanism of the sol 1,222 event, the largest marsquake detected so far. Using the proposed polarization filtering techniques, we are able to enhance the S-wave arrival by suppressing interfering randomly polarized scattered waves to successfully infer on the moment tensor of this event. Secondly, we show that polarization filters can be used to suppress instrument-related glitches and, thirdly, to remove the seismic imprint left by the vibrating lander (mechanical resonances of the lander).
Detection, Analysis, and Removal of Glitches From InSight's Seismic Data From Mars
Scholz, John‐Robert; Widmer-Schnidrig, Rudolf; Davis, Paul; et al. (2020)
Earth and Space Science
The instrument package SEIS (Seismic Experiment for Internal Structure) with the three very broadband and three short‐period seismic sensors is installed on the surface on Mars as part of NASA's InSight Discovery mission. When compared to terrestrial installations, SEIS is deployed in a very harsh wind and temperature environment that leads to inevitable degradation of the quality of the recorded data. One ubiquitous artifact in the raw data is an abundance of transient one‐sided pulses often accompanied by high‐frequency spikes. These pulses, which we term “glitches”, can be modeled as the response of the instrument to a step in acceleration, while the spikes can be modeled as the response to a simultaneous step in displacement. We attribute the glitches primarily to SEIS‐internal stress relaxations caused by the large temperature variations to which the instrument is exposed during a Martian day. Only a small fraction of glitches correspond to a motion of the SEIS package as a whole caused by minuscule tilts of either the instrument or the ground. In this study, we focus on the analysis of the glitch+spike phenomenon and present how these signals can be automatically detected and removed from SEIS's raw data. As glitches affect many standard seismological analysis methods such as receiver functions, spectral decomposition and source inversions, we anticipate that studies of the Martian seismicity as well as studies of Mars' internal structure should benefit from deglitched seismic data.
Assessment of Top of Atmosphere, Atmospheric and Surface Energy Budgets in CMIP6 Models on Regional Scales
Li, Donghao; Folini, Doris; Wild, Martin (2023)
Earth and Space Science
We examine top of atmosphere (TOA), atmospheric, and surface energy budget components of 53 CMIP6 models for the period 2000–2009 on regional scales with respect to two reference data sets: the NASA Energy and Water cycle Study (NEWS), from which we adopt the regional decomposition, and the Clouds and the Earth's Radiant Energy System (CERES) Energy Balanced and Filled (EBAF). Focusing on regional scale, CMIP6 models tend to have more energy entering or less energy leaving the climate systems at TOA over the Northern Hemisphere land, Southern Hemisphere ocean and the polar regions compared to CERES EBAF, while the contrary applies in other regions. Atmospheric net shortwave and longwave fluxes both tend to be underestimated in CMIP6 models as compared to EBAF, with substantial regional differences. Regional surface radiative fluxes as reported by NEWS and EBAF can differ substantially. Nevertheless, robust regional biases exist in CMIP6. Surface upward shortwave radiation is overestimated by 43 (81%) models over Eurasia. For almost all surface radiative flux components over the North Atlantic and Indian Ocean, there are at least 21 (40%) models which fall outside the NEWS uncertainty range. Latent heat flux is overestimated over most of the land and ocean regions while firm conclusions for sensible heat flux remain elusive due to discrepancies between different reference data sets. Compared to CMIP5, there is an overall improvement in CMIP6 on regional scale. Still, substantial deficiencies and spreads on regional scale remain, which are potentially translated into an inadequate simulation of atmospheric dynamics or hydrological cycle.
A Benchmark to Test Generalization Capabilities of Deep Learning Methods to Classify Severe Convective Storms in a Changing Climate
Molina, Maria J.; Gagne, David John; Prein, Andreas F. (2021)
Earth and Space Science
This is a test case study assessing the ability of deep learning methods to generalize to a future climate (end of 21st century) when trained to classify thunderstorms in model output representative of the present-day climate. A convolutional neural network (CNN) was trained to classify strongly rotating thunderstorms from a current climate created using the Weather Research and Forecasting model at high-resolution, then evaluated against thunderstorms from a future climate and found to perform with skill and comparatively in both climates. Despite training with labels derived from a threshold value of a severe thunderstorm diagnostic (updraft helicity), which was not used as an input attribute, the CNN learned physical characteristics of organized convection and environments that are not captured by the diagnostic heuristic. Physical features were not prescribed but rather learned from the data, such as the importance of dry air at mid-levels for intense thunderstorm development when low-level moisture is present (i.e., convective available potential energy). Explanation techniques also revealed that thunderstorms classified as strongly rotating are associated with learned rotation signatures. Results show that the creation of synthetic data with ground truth is a viable alternative to human-labeled data and that a CNN is able to generalize a target using learned features that would be difficult to encode due to spatial complexity. Most importantly, results from this study show that deep learning is capable of generalizing to future climate extremes and can exhibit out-of-sample robustness with hyperparameter tuning in certain applications.
Observed and CMIP5‐Simulated Radiative Flux Variability Over West Africa
Mackie, Anna; Wild, Martin; Brindley, Helen; et al. (2020)
Earth and Space Science
We explore the ability of general circulation models in the Coupled Model Intercomparison Project (CMIP5) to recreate observed seasonal variability in top‐of‐the‐atmosphere and surface radiation fluxes over West Africa. This tests CMIP5 models' ability to describe the radiative energy partitioning, which is fundamental to our understanding of the current climate and its future changes. We use 15 years of the monthly Clouds and the Earth's Radiant Energy System Energy Balanced and Filled (EBAF) product, alongside other satellite, reanalysis, and surface station products. We find that the CMIP5 multimodel mean is generally within the reference product range, with annual mean CMIP5 multimodel mean—EBAF of −0.5 W m−2 for top‐of‐the‐atmosphere reflected shortwave radiation, and 4.6 W m−2 in outgoing longwave radiation over West Africa. However, the range in annual mean of the model seasonal cycles is large (37.2 and 34.0 W m−2 for reflected shortwave radiation and outgoing longwave radiation, respectively). We use seasonal and regional contrasts in all‐sky fluxes to infer that the representation of the West African monsoon in numerical models affects radiative energy partitioning. Using clear‐sky surface fluxes, we find that the models tend to have more downwelling shortwave and less downwelling longwave radiation than EBAF, consistent with past research. We find models that are drier and have lower aerosol loading tend to show the largest differences. We find evidence that aerosol variability has a larger effect in modulating downwelling shortwave radiation than water vapor in EBAF, while the opposite effect is seen in the majority of CMIP5 models.
Scaling Laws in Rayleigh-Benard Convection
Plumley, Meredith; Julien, Keith (2019)
Earth and Space Science
The heat transfer scaling theories for Rayleigh‐Bénard convection (RBC) are reviewed and discussed for configurations with and without rotation and magnetic fields. Scaling laws are a useful tool in studying and characterizing geophysical flows as they provide a basis for extrapolation to extreme parameter regimes that remain unobtainable by current computational and experimental efforts. Specifically, power law scalings that relate the efficiency of the heat transport, as measured by the nondimensional Nusselt number Nu, to the thermal driving are pursued. Relations of the functional form urn:x-wiley:ess2:media:ess2369:ess2369-math-0001 are considered. Given the strongly stabilizing influences of rotation and magnetic fields, thermal driving is considered in the context of the supercriticality of the system given by the ratio of the Rayleigh number Ra, measuring the thermal forcing, to the critical Rac, above which convection occurs. Analytical predictions for the exponent α are presented for the regimes of convection, rotating convection, and magnetoconvection, and the scalings are benchmarked against available numerical and experimental results in the accessible regimes. The exponents indicate that the thermal bottleneck to heat transport occurs within the thermal boundary layers for nonrotating RBC and the turbulent interior for rotating RBC. For magnetoconvection, a single exponent of α=1 is obtained for all theories and no bottleneck is identified.
Seismic Wave Detectability on Venus Using Ground Deformation Sensors, Infrasound Sensors on Balloons and Airglow Imagers
Garcia, Raphael F.; van Zeist, Iris; Kawamura, Taichi; et al. (2024)
Earth and Space Science
The relatively unconstrained internal structure of Venus is a missing piece in our understanding of the formation and evolution of the Solar System. Detection of seismic waves generated by venusquakes is crucial to determine the seismic structure of Venus' interior, as recently shown by the new seismic and geodetic constraints on Mars' interior obtained by the InSight mission. In the next decade multiple missions will fly to Venus to explore its tectonic and volcanic activity, but they will not be able to conclusively detect seismic waves, despite their potential to detect fault movements. Looking toward the next fleet of Venus missions after the ones already decided, various concepts to measure seismic waves have been proposed. These detection methods include typical geophysical ground sensors already deployed on Earth, the Moon, and Mars; pressure sensors on balloons; and imagers of high altitude emissions (airglow) on orbiters. The latter two methods target the detection of the infrasound signals generated by seismic waves and amplified during their upward propagation. Here, we provide a first comparison between the detection capabilities of these different measurement techniques and recent estimates of Venus' seismic activity. In addition, we discuss the performance requirements and measurement durations required to detect seismic waves with the various detection methods. Our study clearly presents the advantages and limitations of the different seismic wave detection techniques and can be used to drive the design of future mission concepts aiming to study the seismicity of Venus.
A Method for Clear-Sky Identification and Lone-Term Trends Assessment Using Daily Surface Solar Radiation Records
Ferreira Correa, Lucas; Folini, Doris; Chtirkova, Boriana; et al. (2022)
Earth and Space Science
Time series of clear-sky irradiance are fundamental for the understanding of changes in the Earth Radiation budget, since they allow to examine radiative processes in the cloud-free atmosphere. Clear-sky data is usually derived from all-sky irradiances using one of several clear-sky methods proposed in the literature. However, most of the available clear-sky methods require additional in situ measurements and/or high temporal resolution (sub-daily), which restricts the derivation of clear-sky time series to a few well equipped stations. Here we propose a new clear-sky identification method that aims to overcome this problem, with the ultimate goal of deriving multidecadal clear-sky trends for many sites globally. The method uses site specific monthly transmittance thresholds to derive long term clear-sky time series for any station worldwide that has daily mean irradiance data. We exemplify the method for 24 stations. Transmittance thresholds are derived by combining 29 years (1990-2018) of satellite cloud cover data with in situ irradiance measurements. The thresholds are then applied to the whole time series (independent of satellite data availability) to screen out cloudy days. Comparison of our results with reference data derived using Long and Ackerman's (2000, https://doi. org/10.1029/2000jd900077) method shows good agreement after bias correction, especially for decadal trends. While limitations of the method, such as anomalies representation, are highlighted and discussed, validation results encourage its use to derive long term clear-sky time series and associated decadal-scale trends around the globe.
Seismic Detection of Euroquakes Originating From Europa's Silicate Interior
Marusiak, Angela G.; Panning, Mark P.; Vance, Steven D.; et al. (2022)
Earth and Space Science
Detecting a seismic event from Europa's silicate interior would provide information about the geologic and tectonic setting of the moon's rocky interior. However, the subsurface ocean will attenuate the signal, possibly preventing the waveforms from being detected by a surface seismometer. Here, we investigate the minimum magnitude of a detectable event originating from Europa's silicate interior. We analyze likely signal-to-noise ratios and compare the predicted signal strengths to current instrument sensitivities. We show that a magnitude Mw ≥ 3.5 would be sufficient to overcome the predicted background noise when the ice shell is 5 km thick. However, a minimum magnitude of Mw ≥ 5.5 would be required for current instrumentation to be able detect the event for any ice shell thickness, at any distance. A thinner ice shell transmits greater ground acceleration amplitudes than a thicker ice shell, which might allow for Mw ≥ 4.5 to be detectable.
Worldwide Rocket Launch Emissions 2019: An Inventory for Use in Global Models
Brown, Tyler F.M.; Bannister, Michele T.; Revell, Laura E.; et al. (2024)
Earth and Space Science
The rate of rocket launches is accelerating, driven by the rapid global development of the space industry. Rocket launches emit gases and particulates into the stratosphere, where they impact the ozone layer via radiative and chemical processes. We create a three-dimensional per-vehicle inventory of stratospheric emissions, accounting for flight profiles and all major fuel types in active use (solid, kerosene, cryogenic and hypergolic). In 2019, stratospheric (15-50 km) rocket launch emissions were 5.82 Gg CO2 ${\mathrm{C}\mathrm{O}}_{2}$, 6.38 Gg H2 ${\mathrm{H}}_{2}$O, 0.28 Gg black carbon, 0.22 Gg nitrogen oxides, 0.50 Gg reactive chlorine and 0.91 Gg particulate alumina. The geographic locations of launch sites are preserved in the inventory, which covers all active launch sites in 2019. We also report the emissions data from contemporary vehicles that were not launched in 2019, so that users have freedom to construct their own launch activity scenarios. A subset of the inventory-stratospheric emissions for successful launches in 2019-is freely available and formatted for direct use in global chemistry-climate or Earth system models.

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