Large-scale hydrodynamic models are vital for flood risk assessment and understanding the global water cycle; however, their results can include uncertainties related to model resolution. Few studies have evaluated hydrodynamic models across a range of spatial resolutions, and these have tended to examine only a few variables (e.g., discharge) or to neglect ungauged sites or parameter optimization. We addressed these limitations by comparing Catchment-based Macro-scale Floodplain (CaMa-Flood) model simulations of Amazon River at different spatial resolutions, using the higher resolution as a benchmark in each comparison. We found that the model performed well in simulating discharge and water depth, with coefficients of determination exceeding 0.84 in > 90% of locations. The normalized Nash–Sutcliffe efficiency coefficients for discharge and water depth were greater than 0.80 and 0.64, respectively, in > 80% of locations, suggesting that most locations had consistent hydrodynamics. We detected large discrepancies in discharge between simulations at ~2.5% of locations due to limited representation of bifurcation flow, floodplain conveyance, and backwater at river confluences in the model. Water depth also differed significantly at ~3% of locations, mainly at headwaters, due to width bottleneck sections. Flood extent patterns differed minimally between simulations around the main stream and large sub-streams, whereas improvements in the downscaling method are required for small sub-streams. Our results demonstrate the need to improve the representation of bifurcation channels and floodplain parameterization for specific locations, although the general river hydrodynamics patterns were well-captured by computationally efficient moderate-resolution (i.e., 6 arcmin) CaMa-Flood simulations.

• Synthetic, holistic review of tracer Green's function techniques in ocean circulation models • Emphasize common underlying theory and ability to customize tracers to address diverse questions • Illustrate power of ocean tracer Green's functions for diagnostics of transport timescales and pathways

Finite fault models using satellite radar interferometry data indicate that the Mw 6.4 Puerto Rico earthquake occurred on a N-dipping fault. Focal mechanism solutions of aftershocks show three trends of strike-slip faults including two parallel WNW-ESE left-lateral faults. The parallel strike-slip faults bound a left-stepping pull-apart basin which localizes the most concentrated area of the swarm.

• Under weak/non-storm substorms, the dawnside SAPS developed on a short timescale in a voltage generator. • Both substorm current wedge (SCW) development and substorm onset occurred on the dawnside. • The fast-time development of dawnside SAPS was triggered by the fast development of dawnside SCW.

Electricity is a basic human necessity. We are highly reliant on continuous access to electricity for our health, well-being, and it remains essential for critical infrastructure, industries, and human development. Yet, there remains a gap in populations with access to electricity across the globe. Mapping where gaps in electrification are currently located is vital to estimate the unmet energy demand to ensure universal access to electricity and modern fuels. To be informative, mapping of electricity access gaps is needed on a global scale but with spatially-disaggregated granularity and it is non-trivial to derive this spatially-explicit data at the global scale. Satellite observations have the unique vantage point of acquiring global observations with frequent updates and are collected in a standardized manner. Specifically, NASA’s Black Marble product derives corrected, global, daily nighttime lights (NTL) that are ideally suited for analyzing urban areas and human settlements with its decade-long records. We utilize this daily dataset to derive neighborhood scale (1km) global maps of electrification using NTL time-series from 2012-2022 and fill in the existing global knowledge gap using highest quality NTL data. We evaluate our analyses with existing global surveys at the national scale and observe high agreement, derive quality flags, and share the results as an open-access dataset. We analyze our dataset to examine the areas with highest access gaps and discuss the potential of the dataset to inform energy transition plans and electricity demand estimations for integrated assessment models that jointly evaluate the effects of climate change and energy transitions.

A document by Lindsay Fitzpatrick. Click on the document to view its contents.

This paper explores machine learning (ML) parameterizations for radiative transfer in the ICOsahedral Nonhydrostatic weather and climate model (ICON) and investigates the achieved ML model speed up with ICON running on graphic processing units (GPUs). Five ML models, with varying complexity and size, are coupled to ICON; more specifically, a multilayer perceptron (MLP), a Unet model, a bidirectional recurrent neural network with long short-term memory (BiLSTM), a vision transformer (ViT), and a random forest (RF) as baseline. The ML parameterizations are coupled to the ICON code that includes OpenACC compiler directives to enable GPU support. The coupling is done with the PyTorch-Fortran coupler developed at NVIDIA. The most accurate model is the BiLSTM with physics-informed normalization strategy, a penalty for the heating rates during training, a Gaussian smoothing postprocessing and a simplified computation of the fluxes at the upper levels to ensure stability of the ICON model top. The presented setup enables stable aquaplanet simulations with ICON for several weeks at a resolution of about 80 km and compares well with the physics-based default radiative transfer parameterization, ecRad. Our results indicate that the compute requirements of the ML models that can ensure the stability of ICON are comparable to GPU optimized classical physics parametrizations in terms of memory consumption and computational speed.

Since the 2011 M9.0 Tohoku-Oki megathrust earthquake, many normal-faulting earthquakes have occurred off northeastern Japan in the upper plate, indicating a trench-normal tensional stress state opposite to that in the inland back-arc area. Determining the spatiotemporal evolution of the stress field is essential for understanding the earthquake occurrence mechanisms in the upper plate of the megathrust. However, the focal depths of normal-faulting earthquakes are not well-constrained due to the lack of observational data directly above the earthquakes. In this study, we first developed a high-frequency waveform modeling method to constrain earthquake depths by reproducing sP depth phases. We then applied the method to M{greater than or equal to}3 earthquakes off southern Tohoku, where intense normal-faulting earthquakes occurred. By comparing the observed waveform envelopes with their synthetic counterparts, we estimated focal depths of 300 events. The estimated focal depths are consistent with those estimated from seafloor seismic observations, supporting the validity of our estimates based solely on inland data. We then conducted relative hypocenter relocation using the events whose focal depths were estimated by sP depth phases as master events to obtain hypocenters of 8,599 events. The results showed that these normal-faulting earthquakes occurred near the surface to a depth of approximately 30 km. This suggests that a tensional stress state prevails from the shallow to deep regions above the megathrust. One possible cause of the tensional stress is gravity force. The effect of plate convergence may not be sufficiently large to make the fore-arc region a compression regime.

A document by Corinne Brevik. Click on the document to view its contents.

In 2023, the biogeographic Amazon experienced temperature anomalies of 1.5°C above the 1991-2020 average from September to November. These conditions were driven by high sea surface temperature in the Atlantic and Pacific oceans, together with reduced moisture advection from the Atlantic, causing large vapor pressure and water deficits in the second semester of 2023. Here, we evaluate the response of the Amazon carbon cycle to this extreme event across different spatial scales. We combined atmospheric CO₂ mole fractions and eddy covariance flux data from the Amazon Tall Tower Observatory (ATTO), near-real-time simulations by Dynamic Global Vegetation Models (DGVMs), an atmospheric inversion, and remote sensing data. We find that in 2023 the Amazon region was, including fires, a net carbon source of 0.01 to 0.17 PgC. Fire emissions (0.15 [0.13-0.17] PgC) were within typical variability of the 2003-2023 period, thus we attribute the weak carbon source to reduced vegetation uptake during the dry season. A stronger-than-normal vegetation uptake early in the year (January to April), consistent across data streams and spatial scales, mitigated the total carbon losses by the end of the year. We find a shift from carbon sink to source in May and a peak source in October. Our findings show a reduced vegetation carbon uptake over the Amazon region, leading to a weak carbon source that contributed 30% of the net carbon loss in the tropical land in 2023.

Urban expansion and the increasing frequency and intensity of extreme precipitation events bring new challenges to stormwater collection systems. One underrecognized issue is the occurence of transient flow conditions that lead to adverse multiphase flow interactions (AMFI): essentially, the formation, collapse, and uncontrolled release of air pockets within stormwater system flows. While the fundamental physics of AMFI have been evaluated in laboratory experiments and idealized modeling studies, much less is known about their development in real or simulated stormwater networks, and about the roles played by rainfall and network properties. A necessary precursor to AMFI is the development of pressurized flow conditions within a network. The goal of this study is to understand how spatiotemporal rainfall variability affects the occurrence of pressurized conditions in a stormwater drainage network in the Richmond district of San Francisco, California. High-resolution bias-corrected radar rainfall fields for 24 recent storms were used as the independent variable of EPA-SWMM simulations. Model analyses indicate that the incidence of pressurized flow increases with storm intensity, and is more sensitive to rainfall temporal variability than spatial variability.

The Amapari Marker Band (AMB) is a layer within the Mount Sharp stratigraphy that has been mapped around Gale crater in orbital images and was recently investigated up close by the Curiosity rover. Symmetric wave ripple marks within the AMB indicate a lacustrine depositional environment in the area investigated along the Curiosity traverse. The wavelength and morphology of the ripples constrain the water depth to a few meters or less. The lateral continuity of the ripple unit defines a minimum extent of the lake during ripple formation. The stratigraphy of the AMB is consistent with an environment of increasing water depth during sedimentation and the lateral correlation of the AMB stratigraphy suggests a transgressive depositional system building upon an eroded surface. The location of the AMB within the surrounding aeolian stratigraphy, coupled with the progression of depositional environments through the Mirador formation, record a pattern of a rising water table relative to sedimentation rates. The potential regional extent of the lacustrine environment, based on orbital mapping of the AMB’s variable elevation, spans at minimum 2.0 km of the lateral AMB deposit in the area around Marker Band Valley and may have extended up to 14 km to the west across northern Gale crater.

To decipher the effects of space-time dynamics of precipitation on the resulting streamflow hydrographs, we herein analyze the controls of timing and shape of the 93,862 hourly streamflow events observed in 199 small German catchments. Using precipitation radar observations, spatially-distributed soil moisture data and landscape properties we derive a comprehensive set of potential controls that apart from standard catchment- and event-averaged precipitation and wetness (i.e., lumped) characteristics represent: the space-time structure and the location of precipitation events within catchments; interaction of precipitation with surface (land use) and subsurface (soil) properties; and interaction of precipitation with antecedent wetness conditions. We find that among considered spatially- and temporally-differentiated controls, particularly the characteristics describing the location of precipitation event relative to catchment outlet and stream network, as well as the interaction of precipitation with the dynamic soil moisture and static soil characteristics have strong effect on the timing of hydrographs. Instead, spatial and temporal structure (i.e., its uniformity or variability in space and time) strongly defines their shapes. We also find that lumped precipitation and wetness characteristics are less relevant for large streamflow events (i.e., magnitudes larger than 95th percentile). Instead, the space-time interaction of precipitation events with antecedent soil moisture is crucial for accurately predicting the timing and shape of large events. The pronounced importance of spatially- and temporally-differentiated precipitation characteristics and their interaction with catchment states for the shape and timing of particularly large events, indicates the need to account for these aspects to improve the accuracy of flood simulations.

Flat slab subduction, exemplified by the Pampean flat slab of the Nazca Plate, exhibits unique geological features such as enhanced seismicity, inboard deformation, and suppressed magmatism. Using thermo-mechanical models, we demonstrate how dehydration dynamics and mantle wedge evolution shape these phenomena. The model replicates landward-migrating dehydration fronts, high seismic coupling, reduced magma production leading to volcanic gaps, and foreland deformation linked to thermal weakening. These findings provide a comprehensive framework to understand the interplay of fluids, magmatism, and tectonics in flat slab subduction systems, consistent with observations in central Chile and western Argentina.

Flat slab subduction, a unique tectonic phenomenon, is characterized by subhorizontal plate motion extending over hundreds of kilometers. Despite its significance, the mechanisms driving flat slab formation remain debated. This study investigates the dynamic effects of mantle wedge hydration on flat slab subduction through advanced numerical modeling, focusing on the Chilean region. Our models incorporate magmatism, hydration, phase transitions, and dynamic pressure variations, revealing that reduced mantle wedge hydration and increased suction forces are critical for slab flattening. Hydration processes, especially serpentinization, create low-viscosity channels that enhance suction forces, while magmatic heat release influences mantle dynamics. The interplay of gravity and suction torques highlights the limited role of slab buoyancy and emphasizes the dominance of suctiondriven dynamics. The results reproduce key geological features, including flat slab geometry, volcanic gaps, and reduced magmatism, consistent with observations in South America. This study provides a comprehensive framework for understanding the geodynamic evolution of flat slab subduction systems worldwide.

This study aimed to evaluate the potential dam breach scenario of the proposed Naumure Dam using the HEC-RAS model. Hydrological and meteorological data from the study area were used to calculate the probable maximum flood, serving as a hydrological input for the model. Geometric data such as reservoir area, inline structure, streamline, riverbank, and flow path were modeled using the HEC-RAS RAS-Mapper tool. Various parametric equations were employed to calculate the breach parameters, which were then input into the HEC-RAS 5.0.7 simulation model along with the input hydrograph. Subsequently, an unsteady flow analysis was conducted to direct the flood through each cross section of the river. The model yielded a maximum flow rate of 141,423.48 m3/s at the dam axis 3.8 hours after the onset of dam failure. The study area, which extended 31.6 km downstream, was analyzed and hydrographs at different cross sections were examined. The results were mapped onto topographic GIS maps to identify affected areas. Approximately 30 km downstream, the settlement area in Bhalubang was inundated with a peak discharge of 48,579.29 m3/s at this location. The research will help relevant authorities devise an emergency response strategy and implement flood mitigation measures.

This study presents basin-wide, full-depth profiles of nitrate δ15N (vs. Air) and δ18O (vs. Vienna Standard Mean Ocean Water, VSMOW) in the Mediterranean Sea. Our results reveal a consistent 15N depletion across the entire Mediterranean Sea in comparison to the global ocean, with significantly lower nitrate δ15N values in the eastern basin (2.2 ± 0.2‰) than in the western basin (2.9 ± 0.1‰). In contrast, there is no significant difference in nitrate δ18O between the two basins (2.2 ± 0.3‰ and 2.1 ± 0.2‰, respectively). These observations point to an external supply of low-δ15N N to the Mediterranean Sea, accumulating as nitrate. This supply is diluted by the Atlantic inflow, creating an east-to-west gradient in nitrate δ15N. Earlier studies have attributed the external low-δ15N N supply to either N2 fixation or atmospheric deposition of anthropogenic N. A four-box model reveals that, given the water residence time of 120–170-years in the Mediterranean, a modest input rate of 1–3 Tg N yr-1 from either of these two sources or their combination is adequate to produce the observed low δ15N of Mediterranean nitrate. Additionally, partial degradation of dissolved organic nitrogen imported from the Atlantic is another possible source of the low-δ15N nitrate in the Mediterranean. Distinguishing among these sources will be aided by reconstruction of Mediterranean nitrate δ15N through time, using either time-series data of nitrate δ15N or paleoceanographic proxies.

Highly productive summer phytoplankton blooms in the central North Pacific Subtropical Gyre (NPSG) are a near annual occurrence that lead to the export of significant amounts of surface particulate carbon being exported to depth. The cause for the formation of these blooms remains unresolved, but the availability iron (Fe) may be a potentially important factor controlling productivity in the central NPSG. From July to October 2022, a large persistent phytoplankton bloom formed around 23.3{degree sign}N, 154.6{degree sign}W that was observable through satellite imagery. We measured elevated Fe concentrations within the bloom that might have stimulated nitrogen (N2) fixation. We estimate that waters that hosted the diazotroph-fueled bloom received up to 20 percent more soluble and total Fe through aerosol deposition than in nearby waters that passed through locations outside the bloom. Even though this moderate increase does not represent incontrovertible evidence that the bloom was stimulated by aerosol Fe deposition, we note evidence of a particularly intense pulse of Fe deposition which occurred roughly 1 month before the bloom. Thus, we suggest a possible role for a lagged Fe stimulation of N2 fixation and blooms and encourage studies which further explore whether Fe deposition might elicit a biological response after approximately 1 month.