Coastal stratocumulus clouds (Sc) have unique modeling challenges due to their development over coastal land, one of them being the accurate representation of surface fluxes. Unlike marine Sc, where the ocean can store significant heat and release relatively constant surface heat fluxes over the day, there are strong diurnal variations of both sensible and latent heat fluxes over land. Moreover, land surface fluxes have a strong feedback with cloud cover. Many modeling efforts have been directed to improve the representation of surface fluxes through developing more accurate land surface models with increasing complexity. Regarding the boundary layer turbulence, for marine Sc, greater sensible fluxes are known to intensify updrafts and increase entrainment, while greater latent heat fluxes have been linked to decoupling. An example of surface flux variations for Marine Sc is the transition of Sc to shallow Cumulus along the trade winds, which occurs over a number of days. For coastal land, changes of surface fluxes occur in a much shorter timescale (hours), and the sensitivity of their dynamical response has not been explored. In this work, we study the response of coastal Sc to controlled variations of surface fluxes using Large Eddy Simulations. Representative scenarios of diurnal profiles are generated using 12 years of surface flux measurements for cloudy days over southern California, and then simulated under several configurations that describe sudden and gradual changes of surface fluxes with varied timing and magnitude. Sudden changes result in increased cloud thinning and earlier dissipation times, although the timing of the sudden increase is also important, in relation to the original dissipation time. The response time to sudden changes of surface fluxes is evident in the evolution of maximum vertical velocity and vertically integrated Turbulent Kinetic Energy, with timescales of 1 and 2 eddy turnover times, respectively.

Apparently stable central Indian craton has been experiencing a number of micro-seismicity in and around the pristine Son-Narmada-South fault (SNSF), possibly because of creep along some reactivated or unidentified fracture planes. Drainage network being highly susceptible to even subtle active tectonics, a reconnaissance study of the area has been carried out using river morphometric analysis. Thereafter, a Principal Scattering Interferometry time series (PSInSAR-TS) analysis (Hooper et al 2004, 2007) was performed to precisely locate the surface-tip of the slip plane. And finally, the fracture geometry and orientation of the slip vector was enumerated by integrating PSINSAR with morphometric analysis. Generally, drainages respond to block uplift with abrupt incision and thereby making a very narrow channel width. However, delineating such incision from the standard Width-Depth ratio from DEM based studies becomes difficult, because of its coarser resolution. Therefore, considering rectangular channel flow for a stable river, the expected width was compared with the actual width of the river measured from high resolution Sentinel II images following the relation modified after Finnegan et al., 2005; which states that W =KA^(2/3)S^(-3/16), where the constant K depends on the rectangular channel geometry, manning constant and rainfall in the area, A is upper catchment area and S is slope of the river reaches. A NE-SW trending zone of narrower channel width was identified with this procedure which was interpreted as a result of block uplift, later confirmed from the rate of uplift preliminarily calculated using an expression derived from basic stream-power equation: U=K(((Z(a)-Z(o))/Χ)^n) (A^m), where the uplift (U) is a function of erodibility (K), river catchment area (A) and chi (χ) value as per Perron and Royden 2012. PSInSAR-TS analysis of the area delineated an average net-slip rate of 11mm/year along a number of NE-SW trending south dipping oblique slip reverse faults, with sinistral strike slip components, arranged in enechelon pattern and are softly linked to each other with jogs accommodating movements in normal sense. Lastly, the fault geometry was confirmed by comparing the deformation map generated from the InSAR technique with the field evidence and previous studies.

The Orbiting Carbon Observatories-2 and 3 make space-based measurements in the oxygen A-band and the weak and strong carbon dioxide (CO2) bands. A Bayesian optimal estimation approach is employed to retrieve the column averaged CO2 dry air mole fraction from these measurements. This retrieval requires a large number of polarized, multiple-scattering radiative transfer (RT) calculations for each iteration. These RT calculations take up the majority of the processing time for each retrieval, and slow down the algorithm to the point that reprocessing data from the mission over multiple years becomes very expensive. To accelerate the RT calculations and thereby ease this bottleneck, we have developed a novel approach that enables reproduction of the spectra for the three OCO-2/3 instrument bands from radiances calculated at a small subset of monochromatic wavelengths. This allows reduction of the number of monochromatic RT calculations by a factor of 20 and can be achieved with radiance errors of less than 0.1% with respect to the existing algorithm. The technique is applicable to similar retrieval algorithms for other greenhouse gas sensors with large data volumes, such as GeoCarb, GOSAT-3, and CO2M.

The Arecibo Observatory (AO) could modify the ionosphere using high frequency (HF) waves. During the HF experiments, the incoherent scatter radar (ISR) was used to study the behavior of the ion, plasma, and gyro lines with 150m height resolution. One year ago, the AO platform collapsed and put a pause for new experiments. However, the archived ISR data can answer open questions like the electron heating evolution in the interaction region. This paper presents a new methodology to estimate the electron temperature (Te) at the resonance altitude based on the physics of the HF wave-plasma interaction. Estimating Te inside regions where the ionospheric plasma interacts with the powerful HF ground waves is a challenge. Standard ISR techniques to assess the temperatures using the ion line are based on Maxwellian approximations. However, the irregularities generated by HF experiments induce non-Maxwellian behaviors. Therefore, a new approach is proposed using the ion-acoustic phase velocity (C_ia) of the ion-acoustic waves generated during the HF experiments. The ion acoustic velocity can be derived from the ISR enhanced plasma line (HFPL) produced during active experiments. The HFPL is mainly attributed to the HF wave decaying into a cascade of Langmuir and ion-acoustic waves, known as Parametric Decay Instability (PDI). The ion-acoustic waves travel at speed: C_ia=λf_ia, where f_ia is the ion-acoustic frequency, and λ is the radar (Bragg backscatter) wavelength. The PDI signature is characterized at the HFPL by cascaded lines spaced in frequency by multiples of f_ia. After measuring f_ia, Te is obtained using f_ia=1/λ √(k_B (Te+2Ti)/m_i), where Ti and mi are the ion temperature and mass. Estimates for one particular experiment on June 12, 2019 show that Te is usually higher at the top of the layer and the beginning of every HF pulse. For example, at 280s after 16:43:00LT, it reached a value near 3500 K, when the temperature outside of the interaction region was below 1600 K.

Ocean governance is characterised by social-ecological complexity and divergence in stakeholder values and perspectives. Meeting the challenges set out in the UN Decade of Ocean Science for Sustainable Development will require transdisciplinary approaches that can embrace multiple ways of knowing to develop shared understandings within interdependent communities of practice and ensure they can be applied in interventions that are adaptive, proactive, socially just, critically reflexive and fit to meet the Decade’s challenges. We present the outcomes of an innovative participatory art process, the Exquisite Corpse Project, with the aim of highlighting multiple perspectives, and developing empathy between participants. We will engage a selected group of researchers from the emerging ‘Ocean Art-Ocean Science’ community to explore the topic of marine heatwaves and their impacts based on data collected in the Northeast Pacific by Ocean Networks Canada and other sources. Through a facilitated process, participants will create three pieces of art that will build on each other and will be exchanged between participants. At the end, all created artworks will be reviewed by the full group to explore emerging insights on marine heatwaves and to surface participants’ underlying values and emotions, which is rarely done in scientific circles where the main mode of discourse employs rational dispassionate exchange. By creating a fun, emotionally-engaging process, we aim to show how the Exquisite Corpse project can strengthen interpersonal bonds, build social cohesion, create opportunities to surface people’s values and perspectives, and develop new transdisciplinary insights in a non-confrontational way. This study is part of an ongoing process exploring transdisciplinary approaches for multidirectional art-science collaborations and developing new research methods for including artistic insight and expression within the scientific discovery process. Instead of the conventional ‘outward looking’ strategy of many art-science projects translating scientific outputs to new formats, our approach is primarily ‘inward looking’. We aim to provide an opportunity for scientists to create art, thus allowing them to explore their own emotions, values and experiences through different ways of knowing.

Application of fixed timestep numerical schemes in engineering has long been criticized for their inaccuracy, inefficiency, and inconsistency across time-scales. Yet, to date, most hydrological models fix their timestep to the input rainfall resolution, instead of using adaptive schemes. Aside from their known maladies, we argue that fixed timestep schemes also suffer from ‘commensurability’ errors: errors that emerge when comparing quantities that are not precisely at the same spatial/temporal scales. At least at <= hourly resolutions, the observed discharge is a set of discrete measurements of an otherwise time-continuous (TC) quantity, but the modelled discharge is time-averaged (TA) across the fixed timestep. Hence the commensurability error when compared against one another during calibration. (In)significance of such errors simultaneously depends on the nonlinearity of the discharge within that timestep, and the timestep size. Consequently, these errors are the largest where they are potentially least acceptable to ignore, i.e., around peaks. Also, they tend to grow with timestep size (data resolution), unless timestep is detached from data resolution using adaptive schemes, which produce a TC solution. Importantly, since modern calibration procedures revolve around ‘fitting’ to observed discharge, such errors are likely undetectable in model’s curve-fitting performance, and instead are to be found in calibrated parameter-sets. Here, in a novel approach within the Generalize Likelihood Uncertainty Estimation (GLUE) framework with Limits of Acceptability (LOA) defined a-priori, and for a micro-catchment case study, we calibrate a TA and a TC version of Dynamic-TOPMODEL to datasets at different resolutions. Through experimentation with the calibrated parameter-sets, we estimate the relative (to TC version) magnitude of the time-commensurability errors resulting from fixing the timestep to input rainfall. Our findings confirm the overall insufficient accuracy, inefficiency of timestepping, and inconsistency across resolution when fixing the timestep. We find that for calibration data resolution >10min, time-commensurability errors become very significant.

Freshwater from rivers influences Indian summer monsoon rainfall and tropical cyclones by stratifying the upper layer and warming the subsurface ocean in the Bay of Bengal. Here, we use {\it in situ} and satellite data with reanalysis to showcase how river water experiences a significant increase in salinity on sub-seasonal timescales. This involves the trapping and homogenization of freshwater by a cyclonic eddy in the Bay. Using a specific example from 2015, river water is shown to enter an eddy along its attracting manifolds within a period of two weeks. This leads to the formation of a highly stratified subsurface layer within the eddy. When freshest, the eddy has the largest sea-level anomaly, spins fastest, and supports strong lateral gradients in salinity. Subsequently, observations reveal a progressive increase in salinity inside the eddy within a month. In particular, salty water spirals in, and freshwater is pulled out across the eddy boundary. Lagrangian experiments elucidate this process, whereby horizontal chaotic mixing provides a mechanism for the rapid increase in surface salinity. A salinity budget also suggests that horizontal advection explains much of the change in mixed layer salinity. Further, the adjustment of this freshwater eddy triggers submesoscale dynamics which appear to be an integral part of the process of salinity homogenization. This pathway is distinct from vertical diffusive mixing and is likely to be important for the evolution of salinity in the Bay of Bengal.

The Open Global Glacier Model (http://oggm.org) is an open source modelling framework, helping various research groups to simulate and understand mountain glacier change at the regional or global scale. OGGM is modular, which means that we encourage users to develop their own physical parameterizations while staying compatible with the OGGM workflow. To achieve this goal, we need OGGM to be easy to understand, install, apply, and extend. In this presentation, I will talk about how we make use of the wealth of open-source tools available in the python and Jupyter ecosystems to provide an online documentation platform for OGGM. Our documentation combines text with interactive examples that run in your web browser, avoiding the typical installation and data download burden for newcomers. With selected examples from the collaborative educational content platform OGGM-Edu (http://edu.oggm.org), I will show how anyone can apply these ideas and tools to their own documentation or outreach project. Finally, I will talk about some of the challenges faced by the OGGM project in its pursuit of becoming a community model. With the increasing pressure on geoscientists who have to learn new complex technologies while navigating the “publish or perish” career model, the growing demand for better open science practices can be a blessing as well as a curse for many early career scientists.

The Qinling-Dabie Orogenic Belt (QDOB) in Central China was built through prolonged subduction-accretion collision events and incorporates many exposures of exhumed ultrahigh-pressure (UHP) metamorphic rocks. We collected a large number of teleseismic and local earthquake data and performed a P-wave tomography and CCP stacking of receiver functions from this region. Our results reveal high-velocity horizontal anomalies at depths of 100-300 km beneath the QDOB, which may be related to the deep subduction or the delamination of the lower crust and lithosphere. We also imaged a low-velocity anomaly at depths of 200-400 km, which may be associated with mantle upwelling in this region. Based on a detailed analysis, we consider that the delamination of the lower crust and lithosphere might have contributed to the formation of the UHP rocks.

Positive and negative electric streamers are column-shaped discharges which are an important stage in lightning development. The mechanism, by which the streamer acquires a certain velocity and radius of its head, had been a long-standing puzzle. In [1], we proposed a parametric streamer model (PSM), which may explain this mechanism, as well as the mechanism of the streamer threshold electric field. The PSM results for a positive isolated streamer in constant uniform external electric field are verified by comparing with hydrodynamic calculations of a ‘steady-state’ streamer, namely a streamer whose length is kept constant by synchronizing the position of the electrode to which it is attached with the moving streamer head. For this particular streamer configuration, we found that both velocity and radius of a streamer increase with its length, a results which was also observed in previously performed hydrodynamic calculations and experiments. Beside the velocity and radius of the streamer, PSM allows to quickly estimate all other streamer parameters, such as the maximum field at the streamer tip and the field inside the streamer channel. The relatively low, compared to, e.g., hydrodynamic or particle-in-cell (PIC) models, computational costs of PSM suggest that generalizion of PSM principles to more complicated streamer structures may be very valuable. In the present work, we generalize PSM to evaluate how different background conditions affect streamer propagation. In particular, we find that, unlike the uniform-field case described above, (1) for the non-uniform electric field such as that of a spherical electrode, the streamer velocity decreases with length; (2) for a streamer propagating parallel to other similar streamers (as in a streamer “bunch’‘), both velocity and radius stabilize to an approximately constant value. [1] N. G. Lehtinen, “Physics and mathematics of electric streamers,” Radiophysics and Quantum Electronics, 2021, in print [Russian version: DOI: 10.52452/00213462_2021_64_01_12].

With a few exceptions extreme weather event attribution is recognised as necessarily oriented towards tracing the history of present (or past) extreme events. However, it must be noted that the usefulness of a true causal claim linking climate change to its specific, local impacts may not be exhausted by its being an answer to a pre-specified scientific question about event attribution. This is because there is an important difference between problem-solving and solution-use. And solution-use can neither be controlled by the problem-solving science nor by its taskmasters. The users can have other questions than the problem-solvers. This commentary defends detection and attribution science’s importance for individuals’ adaptation decisions.

Solar Radiation Management (SRM) is regarded as a tool to potentially counteract global warming by increasing planetary albedo. Even though it has shown effective results in offsetting global surface temperature, one of its main limits lies in the persistence of major regional anomalies, for both surface temperature and precipitation. Here, using the Globally Resolved Energy Balance (GREB) model, we present experiments designed to completely offset global and regional surface temperature response due to CO2 forcing. Our innovative idea, is to employ a spatially and seasonally optimized SRM, as opposed to the state-of-the-art geoengineering which utilizes a homogeneous one. This approach allows to cut down surface warming by more than 99% in nearly all regions and seasons, with the exception of polar regions. This pilot study is opening up interesting pathways for further experiments with more complex models, to completely compensate global warming with SRM.

The Raton Basin is known as an area of injection induced seismicity for the past two decades, but the reactivated fault zone structures and spatiotemporal response of seismicity to evolving injection have been poorly constrained in the past due to scarce public monitoring. Application of a machine-learning phase picker to four years of continuous data from a local array enables the detection and location of ~38,000 earthquakes. The events between 2016-2020 are ~2.5-6 km below sea level and range from ML<-1 to 4.2. Most earthquakes occur within previously identified ~N-S zones of seismicity, however our new catalog illuminates these zones are composed of many short faults with variable orientations. The two most active zones, the Vermejo Park and Tercio, are potentially linked by small intermediate faults. In total, we find ~60 short (<3 km) basement faults with strikes from WNW to slightly east of N. Faulting mechanisms are predominantly normal but some variability, including reverse dip-slip and oblique-slip, is observed. The Trinidad fault zone that hosted the 2011 Mw 5.3 earthquake is quiescent during 2016-2020, likely in response to decreased wastewater injection after 2012 and the shut-in of two nearby wells in 2015. Unlike some induced seismicity regions with higher injection rates, Raton Basin frequency-magnitude and spatiotemporal statistics are not distinguishable from tectonic seismicity. The similarity suggests that induced earthquakes in the Raton Basin are dominantly releasing tectonic stress.

The breakup of supercontinent Pangea occurred 200 Ma forming the Eastern North American Margin (ENAM). Yet, the precise timing and mechanics of breakup and onset of seafloor spreading remain poorly constrained. We investigate the relic lithosphere offshore eastern North America using ambient-noise Rayleigh-wave phase velocity (12–32 s) and azimuthal anisotropy (17–32 s) at the ENAM Community Seismic Experiment (CSE). Incorporating previous constraints on crustal structure, we construct a shear velocity model for the crust and upper 60 km of the mantle beneath the ENAM-CSE. A low-velocity lid ( of 4.4–4.55 km/s) is revealed in the upper 15–20 km of the mantle that extends 200 km from the margin, terminating at the Blake Spur Magnetic Anomaly (BSMA). East of the BSMA, velocities are fast (4.6 km/s) and characteristic of typical oceanic mantle lithosphere. We interpret the low-velocity lid as stretched continental mantle lithosphere embedded with up to 15% retained gabbro. This implies that the BSMA marks successful breakup and onset of seafloor spreading 170 Ma, consistent with ENAM-CSE active-source studies that argue for breakup 25 Myr later than previously thought. We observe margin-parallel Rayleigh-wave azimuthal anisotropy (2–4% peak-to-peak) in the lithosphere that approximately correlates with absolute plate motion (APM) at the time of spreading. We hypothesize that lithosphere formed during ultra-slow seafloor spreading records APM-modified olivine fabric rather than spreading-parallel fabric typical of higher spreading rates. This work highlights the importance of present-day passive margins for improving understanding of the fundamental rift-to-drift transition.

We study the problem of discrimination between earthquakes and explosions on the basis of seismic signals detected at teleseismic distances (over 2000 km). Most work in the field of discrimination has been limited to signals detected within a few hundred kilometers which limits their utility from the perspective of sparse global seismic networks for either treaty monitoring or seismic hazard analysis. We show that existing Deep Learning architectures that have been proposed for discrimination or related tasks such as phase classification or signal detection can be repurposed for teleseismic discrimination. Using hyperparameter tuning methods we have been able to improve the performance relative to the original architectures while reducing the model complexity. We present empirical analysis of a number of different methods, and demonstrate that our proposed Deep Learning architecture performs the best at teleseismic discrimination and is able to reliably identify rockburst events.

Carbonate platform background fracture networks are rarely utilized in subsurface models, and it is unclear how they relate to regional stress (other than faults and folds) and burial. We combine structural analysis and drone imagery to investigate the geometry, kinematics, and topological characteristics of (background) fractures at the Latemar platform (both limestones and dolostones; Northern Italy). Deformation was accommodated by a dense network of mode I and conjugate hybrid fractures/veins and conjugate reverse faults, all associated with sub-vertical stylolites. Conjugate fractures and associated sub-vertical stylolites are organized in two systems, constraining the major stress fields. Differences lie in the permutation of the position in the space of the principal stress with depth. Specific burial depth windows are significant in distinguishing the different spatial positions of the principal stresses. Changes in overburden provide the major driving factor in determining the position of background structures that develop during the burial trajectory. Topologically, background fractures in lime- and dolostone pavements show distinct characteristics. In limestone pavements, fractures form a network with a high proportion of I-node and I-C to C-C branches, resulting in a low to moderate connectivity (i.e., CB = ~ 1.5). In dolostones, a complex network with abundant Y-to X- nodes and I-C to C-C branches is found (moderate to a high degree of connectivity CB = ~ 1.7). Topological pathways provide important insights into how background fractures are connected and shed light on the significance of these features in the context of subsurface fluid flow.

Accurate estimation of the spatio-temporal distribution of snow water equivalent is essential given its global importance for understanding climate dynamics and climate change, and as a source of fresh water. Here, we explore the potential of using the Long Short-Term Memory (LSTM) network for continental and regional scale modeling of daily snow accumulation and melt dynamics at 4-km pixel resolution across the conterminous US (CONUS). To reduce training costs (data are available for ~0.31 million snowy pixels), we combine spatial sampling with stagewise model development, whereby the network is first pretrained across the entire CONUS and then subjected to regional fine-tuning. Accordingly, model evaluation is focused on out-of-sample predictive performance across space (analogous to the prediction in ungauged basins problem). We find that, given identical inputs (precipitation, temperature and elevation), a single CONUS-wide LSTM provides significantly better spatio-temporal generalization than a regionally calibrated version of the physical-conceptual temperature-index-based SNOW17 model. Adding more meteorological information (dew point temperature, vapor pressure deficit, longwave radiation and shortwave radiation) further improves model performance, while rendering redundant the local information provided by elevation. Overall, the LSTM exhibits better transferability than SNOW17 to locations that were not included in the training data set, reinforcing the advantages of structure learning over parameter learning. Our results suggest that an LSTM-based approach could be used to develop continental/global-scale systems for modeling snow dynamics.

The geologic origin of the ancient, phyllosilicate-bearing bedrock at Oxia Planum, Mars, the ExoMars rover landing site, is unknown. The phyllosilicates record ancient aqueous processes, but the processes that formed the host bedrock remain elusive. Here, we use high-resolution orbital and topographic datasets to investigate and characterize fluvial sinuous ridges (FSRs), found across the Oxia Planum region. The FSRs form segments up to 70 km long, with sub-horizontal layering common in ridge margins. Some FSRs comprise multi-story ridge systems; many are embedded within the phyllosilicate-bearing bedrock. We interpret the FSRs at Oxia Planum as deposits of ancient, episodically active, alluvial river systems (channel-belt and overbank deposits). Thus, the phyllosilicate-bearing bedrock was formed at least partly by ancient alluvial rivers, active across the wider region. Future exploration by the ExoMars rover can verify this interpretation and provides an opportunity to investigate some of the oldest river deposits in the Solar System.