Fault geometry is a key factor in controling the mechanics of faulting. However, there is currently limited theoretical knowledge regarding the effect of non-planar fault geometry on earthquake mechanics. Here, we address this gap by introducing an expansion of the relation between fault traction and slip, up to second order, relative to the deviation from a planar fault geometry. This expansion enables the separation of the effects of non-planarities from those of planar faults. This expansion is realised in the boundary integral equation, assuming a small fault slope. It provides an interpretation for the effect of complex fault geometry on fault traction, for any fault geometry and any slip distribution. Hence the results are also independent of the friction that applies on the fault. The findings confirm that fault geometry has a strong influence on in-plane faulting (mode II) by altering the normal traction on the fault and making it more resistant to slipping for any fault geometry. On the contrary, for out-of-plane faulting (mode III), fault geometry has a much smaller influence. Additionally, we analyse some singularities that arise for specific fault geometries often used in earthquake simulations and provide guidelines for their elimination. To conclude this study, we discuss the limits of the small strain approximation when non-planar faults are considered.

With ongoing climate change and more frequent high flows and droughts, it becomes inevitable to understand potentially altered catchment processes under changing climatic conditions. Water age metrics such as median transit times and young water fractions are useful variables to understand the process dynamics of catchments and the release of solutes to the streams. This study, based on extensive high-frequency stable isotope data, unravels the changing contribution of different water ages to stream water in six heterogeneous catchments, located in the Harz mountains and the adjacent northern lowlands in Central Germany. Fractions of water up to 7 days old (Fyw7), comparable with water from recent precipitation events, and fractions of water up to 60 days old (Fyw60) were simulated by the tran-SAS model. As Fyw7 and Fyw60 were sensitive to discharge, an integrated analysis of high and low flows was conducted. This revealed an increasing contribution of young water for increasing discharge, with larger contributions of young water during wet spells compared to dry spells. Considering the seasons, young water fractions increased in summer and autumn, which indicates higher contributions of young water after prolonged dry conditions. Moreover, the relationship between catchment characteristics and the water age metrics revealed an increasing amount of young water with increasing agricultural area, while the amount of young water decreased with increasing grassland proportion. By combining transit time modelling with high-frequency isotopic signatures in contrasting sub-catchments in Central Germany, our study extends the understanding of hydrological processes under high and low flow conditions.

A document by Eleonora Dallan. Click on the document to view its contents.

Following the Hunga Tonga–Hunga Ha’apai (HTHH) eruption in January 2022, stratospheric ozone depletion was observed in the Southern Hemisphere mid-latitudes and Antarctica during the 2022 austral wintertime and springtime. This eruption injected sulfur dioxide and unprecedented amounts of water vapor into the stratosphere. This work examines and quantifies the chemistry contribution of the volcanic materials to the ozone depletion using chemistry-climate model simulations with nudged meteorology. Simulated 2022 ozone and nitrogen oxides (NOx) anomalies show a good agreement with satellite observations. We find that chemistry only contributes up to 6% and 20% ozone destruction at mid-latitudes wintertime and Antarctic springtime respectively. The majority of the ozone depletion is attributed to the internal variability and dynamical changes forced by the eruption. Both the simulation and observations show a significant NOx reduction associated with the HTHH aerosol plume, indicating the enhanced dinitrogen pentoxide hydrolysis on sulfate aerosol.

A document by William S Kurth. Click on the document to view its contents.

We investigate error growth from small-amplitude initial condition perturbations, simulated with a recent artificial intelligence-based weather prediction model. From past simulations with standard physically-based numerical models as well as from theoretical considerations it is expected that such small-amplitude initial condition perturbations would grow very fast initially. This fast growth then sets a fixed and fundamental limit to the predictability of weather, a phenomenon known as the butterfly effect. We find however, that the AI-based model completely fails to reproduce the rapid initial growth and hence would suggest an infinite predictability of the atmosphere. In contrast, if the initial perturbations are large and comparable to current uncertainties in the estimation of the initial state, the AI-based model basically agrees with physically-based simulations, although some deficits are still present.

A document by Donald P. Cummins. Click on the document to view its contents.

Chemistry transport models (CTMs) are essential tools for characterizing and predicting the role of atmospheric composition and chemistry in Earth’s climate system. This study demonstrates the use of airborne in situ observations to diagnose the representation of atmospheric composition by global CTMs. Process-based diagnostics are developed which minimize the spatial and temporal sampling differences between airborne in situ measurements and CTM grid points. The developed diagnostics make use of dynamical and chemical vertical coordinates as a means of highlighting areas where focused model improvement is needed. The chosen process is the chemical impact of the Asian summer monsoon (ASM), where deep convection serves a unique pathway for rapid transport of surface emissions and pollutants to the stratosphere. Two global CTM configurations are examined for their representation of the ASM upper troposphere and lower stratosphere (UTLS), using airborne observations collected over south Asia. Application of the developed diagnostics to the CTMs reveals the limitations of zonally-averaged surface boundary conditions for species with sufficiently short tropospheric lifetimes, and that species whose stratospheric loss rates are dominated by photolysis have excellent agreement compared to that observed. Overall, the diagnostics demonstrate the strength of airborne observations toward improving model predictions, and highlight the utility of highly-resolved CTMs to improve the understanding of reactive transport of anthropogenic pollutants to the stratosphere.

Near-inertial waves (NIWs) originate in the ocean upper mixed layer. When they have a large horizontal scale which is characteristic of an atmospheric storm, they are difficult to propagate vertically below the mixed layer. The β-effect and the mesoscale vorticity are considered as two important mechanisms for guiding the downward propagation of near-inertial energy (NIE). In this paper, the effects of “heat pumping” and “cold suction” of typhoons on the ocean stratification are analyzed. It is found that changes in stratification enhance the vertical propagation of NIWs from the mixed layer into the ocean interior on the left side of the typhoon track. To illustrate the impact of stratification changes on both sides of typhoon tracks, the Regional Ocean Modelling System (ROMS) is used to simulate the NIWs generated by Typhoon Kalmaegi in 2014. The results show that, although the wind energy input on the right side of the typhoon track is higher than that on the left side, the NIE injection to the deep ocean from the left side is stronger due to the different dissipation and stratification responses. Our work improves the understanding of the generation, propagation, and dissipation mechanisms of NIWs during typhoons.

Changes in the seasonal sea level cycle (SSLC) can modulate the flooding risk along coastlines. Here, we use harmonic analysis to quantify changes in the amplitude and phase of the annual component of the sea level cycle at 663 tide gauge locations along the global coastline where long records are available. We identify coastal hotspots by applying clustering methods revealing coherent regions with similar patterns of variability in the annual sea level cycle (ASLC). Results show that for most tide gauges the annual amplitude reached its maximum after 1970 and its peak typically occurs during the fall season of the respective hemisphere. Many tide gauges exhibit non-stationarity in the annual cycle in terms of amplitude and/or phase. For example, at 125 tide gauges we find significant trends in the amplitude (either increasing or decreasing) while several sites (36 in total), mostly in the Mediterranean and around Pacific islands, experienced phase changes leading to shifts in the timing of the peak of the annual cycle by more than a month. Our results highlight the importance of accounting for potential non-stationarity in seasonal mean sea level (MSL) cycles along coastlines.

In the West Antarctic Peninsula (WAP), complex interactions between the cryosphere, ocean and atmosphere produce an environment with large geographical, seasonal and interannual variability which is highly vulnerable to climate change. The seasonal sea ice cycle and its interactions with upper-ocean mixing play an important role in structuring this environment. Here we show that the relationship between sea ice and mixed layer depth (MLD) varies regionally between the WAP shelf and off-shelf regions. Using an MITgcm regional model of the WAP and Bellingshausen Sea for 1989-2018, we find that on the WAP shelf, high winter sea ice coverage is related to shallow spring mixed layers, whereas in a region offshore of the shelf, high winter sea ice coverage is related to deep spring mixed layers. The exact boundary between positive and negative correlations between winter sea ice concentration (SIC) and spring MLD varies decadally. Our results can be explained by a nonlinear relationship between SIC and momentum flux into the ocean, with a minor additional role for the timing of seasonal processes. Transport of sea ice across the model domain dampens this mechanism except in regions of very large sea ice export such as polynyas. With sea ice conditions projected to undergo large changes over the course of the century, understanding the relationship between sea ice and upper-ocean mixing in this unique and vulnerable location is crucial for understanding the wider impacts of climate change on biological productivity in the polar oceans.

A document by Susanne Støle-Hentschel. Click on the document to view its contents.

Magmatism is a known driver of flank instability at volcanoes where flank slip has been observed. Studies of instability at Kīlauea, Piton de la Fournaise, and Etna imply that long-term flank motion likely requires the presence of a layer accommodating the sliding, and a force, such as magma intrusion, that promotes slip. We present a parametric study using 2D Finite Element Models (FEMs), to assess how edifice aspect ratio, detachment fault geometry, asymmetric buttressing, and intrusion depth affect the potential for development of magma-driven flank instability at volcanoes. We quantify whether the tested conditions would favor flank slip based on the Coulomb Stress Changes (CSCs) associated with endmember scenarios and showcase the expected surface displacements for each scenario, to highlight their deviations from half-space models. Development of instability is more likely when flank slip is along a shallower-dipping receiver fault and the dike intrusion spans the edifice, regardless of edifice steepness. Another favorable scenario occurs in steep edifices with a steeply-dipping receiver fault when the dike is beneath the edifice. Buttressing slightly enlarges the region with conducive CSCs on shallow-dipping faults when the dike is within the edifice but shrinks the region with conducive CSCs in the steep edifice case with steeply-dipping faults. We also find that neglecting topography yields different magnitudes and extents of surface deformation, especially for steeper volcanic edifices. This topographical effect is more important when modeling horizontal displacements and stress fields induced by shallower intrusions.

Large earthquakes rupture faults over hundreds of kilometers within minutes. Finite-fault models elucidate these processes and provide observational constraints for understanding earthquake physics. However, finite-fault inversions are subject to non-uniqueness and substantial uncertainties. The diverse range of published models for the well-recorded 2011 M_w 9.0 Tohoku-Oki earthquake aptly illustrates this issue, and details of its rupture process remain under debate. Here, we comprehensively compare 32 finite-fault models of the Tohoku-Oki earthquake and analyze the sensitivity of three commonly-used observational data types (geodetic, seismic, and tsunami) to the slip features identified. We first project all models to a realistic megathrust geometry and a 1-km subfault size. At this scale, we observe poor correlation among the models, irrespective of the data type. However, model agreement improves significantly when subfault sizes are increased, implying that their differences primarily stem from small-scale features. We then forward-compute geodetic and teleseismic synthetics and compare them with observations. We find that seismic observations are sensitive to rupture propagation, such as the peak-slip-rise time. However, neither teleseismic nor geodetic observations are sensitive to spatial slip features smaller than 64 km. In distinction, the synthesized seafloor deformation of all models exhibits poor correlation, indicating sensitivity to small-scale slip features. Our findings suggest that fine-scale slip features cannot be unambiguously resolved by remote or sparse observations, such as the three data types tested in this study. However, better resolution may become achievable from uniformly gridded dense offshore instrumentation.

Geomechanical simulations of induced seismicity generally involve a simple reservoir geometry in terms of reservoir structure and fault distribution. Because the depletion of the reservoir controls the incremental stress field, the geometry of the reservoir has a substantial influence on the occurrence of induced earthquakes. We develop geomechanical models based on a realistic geological model of the reservoir in the Groningen gas field. The model captures the main characteristics of the reservoir structures in the Zeerijp region. Through quasi-static and dynamic simulations, we observe that a smaller intersection angle between the two normal faults in the Zeerijp region causes an increase in the incremental Coulomb stress at the lower reservoir juxtaposition adjacent to the intersection. As a result, this intersection angle strongly affects the location of the initial seismic slip, the rupture pattern, and the location of the maximum slip. Our simulation produces an earthquake of magnitude MW 3.0, due to fault reactivation occurring at a reservoir depletion value of 26 MPa. These values are similar to those for the Zeerijp 2018 earthquake of ML 3.4. The location of the simulated rupture is close to the inverted hypocenter location for the 2018 earthquake. Our results suggest that it is crucial to incorporate realistic reservoir structures when simulating induced seismicity in a specific region.

The incompleteness of earthquake catalogs is a well-known issue caused by our technical limitation in detecting the small- to very small-magnitude seismicity falling near or below the level of background seismic noise. According to Gutenberg-Richter distribution, small earthquakes represent the majority of the events occurring in a certain area and their detection is key for improving our knowledge of: i) the geometry and kinematics of seismogenic sources; ii) the spatio-temporal characteristics of seismicity, thus leading to better models for seismic hazard. Template-matching (TM) is a well-known and powerful technique based on similarity measure that allows to find earthquakes hidden in the continuous recording, similar to to known events (templates). Nowadays, the larger availability of computational resources, allows the application of such technique to regional areas. This work represents the first application of template-matching to Southern Apennines (Italy), using about 4.000 high-quality events as templates and scanning 6-years long continuous recording (2009-2014) at more than 180 stations of the INGV network. About 20.000 new events are found, showing a comparable quality to the template catalog in terms of hypocentral solution, and reaching a decrease of the magnitude of completeness of about one unit. In order to highlight the improved quality of the TM catalog, we report on two main examples regarding the Sannio-Matese area, where TM allowed us to unravel relevant details on the spatio-temporal distribution of the local seismicity, providing useful insights for the understanding of the seismic hazard.

As climate modellers prepare their code for kilometre-scale global global simulations, the computationally demanding radiative transfer transfer parameterization is a prime candidate for machine learning (ML) (ML) emulation. Because of the computational demands, many weather centres centres use a reduced spatial grid and reduced temporal frequency for radiative radiative transfer calculations in their forecast models. This strategy is known known to affect forecast quality, which further motivates the use of ML-based ML-based radiative transfer parameterizations. This paper contributes to the the discussion on how to incorporate physical constraints into an ML-based ML-based radiative parameterization, and how different neural network (NN) (NN) designs and output normalisation affect prediction performance. A random random forest (RF) is used as a baseline method, with the European Centre for for Medium-Range Weather Forecasts (ECMWF) model ecRad, the operational operational radiation scheme in the Icosahedral Nonhydrostatic Weather and Climate Climate Model (ICON), used for training. Surprisingly, the RF is not affected by by the top-of-atmosphere (TOA) bias found in all NNs tested (e.g., MLP, MLP, CNN, UNet, RNN) in this and previously published studies. At lower lower atmospheric levels, the RF can is able to compete with all NNs tested, but but its memory requirements quickly become prohibitive. For a fixed memory memory size, most NNs outperform the RF except at TOA. The most accurate emulator is For the best emulator, we use a recurrent neural network architecture that which closely imitates imitates the physical process it emulates. The We additionally normalize the shortwave and longwave fluxes are normalized to reduce their dependence on from the solar solar angle and surface temperature respectively. The model are, furthermore, trained Finally, we train the model with an additional heating rates penalty in the loss function.function.

The gravity wave drag parametrization of the Whole Atmosphere Community Climate Model (WACCM) has been modified to include the wave-driven atmospheric vertical mixing caused by propagating, non-breaking, gravity waves. The strength of this atmospheric mixing is represented in the model via the "effective wave diffusivity" coefficient K_wave. Using K_wave, a new total dynamical diffusivity K_Dyn is defined. K_Dyn represents the vertical mixing of the atmosphere by both breaking (dissipating) and vertically propagating (non-dissipating) gravity waves. Here we show that, when the new diffusivity is used, the downward fluxes of Fe and Na between 80 and 100 km largely increase. Larger meteoric ablation injection rates of these metals (within a factor 2 of measurements) can now be used in WACCM, which produce Na and Fe layers in good agreement with lidar observations. Mesospheric CO2 is also significantly impacted, with the largest CO2 concentration increase occurring between 80-90 km, where model-observations agreement improves. However, in regions where the model overestimates CO2 concentration, the new parametrization exacerbates the model bias. The mesospheric cooling simulated by the new parametrization, while needed, is currently too strong almost everywhere. The summer mesopause in both hemispheres becomes too cold by about 30K compared to observations, but it shifts upward, partially correcting the WACCM low summer mesopause. Our results highlight the far-reaching implications and the necessity of representing vertically propagating gravity waves in climate models. This novel method of modelling gravity waves contributes to growing evidence that it is time to move away from dissipative-only gravity wave parametrizations.