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NOAA is forecasting an above-average summer "dead zone" in the Gulf of Mexico covering approximately 5,827 square miles—an area roughly the size of Connecticut. The dead zone, or hypoxic area, is an area of low oxygen that can kill fish and other marine life. It occurs every summer and is primarily a result of excess nutrient pollution from human activities in cities and farm areas throughout the Mississippi-Atchafalaya watershed. The average dead zone measurement is 5,205 square miles over the 37-year period of record.

Abstract

Machine Learning (ML) is having a profound impact in the domain of Weather and Climate Prediction. A recent development in this area has been the emergence of fully data-driven ML prediction models which routinely claim superior performance to that of traditional physics-based models. We examine some aspects of the forecasts produced by three of the leading current ML models, Pangu-Weather, FourCastNet and GraphCast, with a focus on their fidelity and physical consistency. The main conclusion is that these ML models are not able to properly reproduce sub-synoptic and mesoscale weather phenomena and lack the fidelity and physical consistency of physics-based models and this has impacts on the interpretation of their forecasts and their perceived skill. Balancing forecast skill and physical realism will be an important consideration for future ML models.

Abstract

Accurate wildfire forecasting can inform regional management and mitigation strategies in advance of fire occurrence. Existing systems typically use fire danger indices to predict landscape flammability, based on meteorological forecasts alone, often using little or no direct information on land surface or vegetation state. Here, we use a vegetation characteristic model, weather forecasts and a data-driven machine learning approach to construct a global daily ∼9 km resolution Probability of Fire (PoF) model operating at multiple lead times. The PoF model outperforms existing indices, providing accurate forecasts of fire activity up to 10 days in advance, and in some cases up to 30 days. The model can also be used to investigate historical shifts in regional fire patterns. Furthermore, the underlying data driven approach allows PoF to be used for fire attribution, isolating key variables for specific fire events or for looking at the relationships between variables and fire occurrence.

Protecting and effectively managing oceans and seabeds is crucial in the fight against climate change.

Abstract

The long-term memory of the ocean makes sea surface temperature anomalies (SSTAs) become a significant predictor for the subsequent atmosphere, and the tropical ocean is primarily regarded as a major source of atmospheric anomalies. While in North Pacific, the local midlatitude SSTAs also have large contributions but have not been adequately considered yet. We discover a strong connection between the Kuroshio-Oyashio Extension (KOE) SSTAs in spring and the local atmospheric circulation anomalies in following summer at interannual timescale, wherein, the spring KOE SSTAs are generally independent of tropical ocean, and they are primarily induced by the concurrent atmospheric anomalies via surface heat flux and ocean dynamic processes. The spring KOE SSTAs can persist to summer, and then generate nearly reversed whole-layer atmospheric circulation anomalies in their north side through both diabatic heating and atmospheric transient eddy forcing. Consequently, precipitation anomalies in Pan-Pacific regions are distinctly modulated from spring to summer.

Abstract

Rising temperatures entail important changes in the soil hydrologic processes of the northern permafrost zone. Using the ICON-Earth System Model, we show that a large-scale thaw of essentially impervious frozen soil layers may cause a positive feedback by which permafrost degradation amplifies the causative warming. The thawing of the ground increases its hydraulic connectivity and raises drainage rates which facilitates a drying of the landscapes. This limits evapotranspiration and the formation of low-altitude clouds during the snow-free season. A decrease in summertime cloudiness, in turn, increases the shortwave radiation reaching the surface, hence, temperatures and advances the permafrost degradation. Our simulations further suggest that the consequences of a permafrost cloud feedback may not be limited to the regional scale. For a near-complete loss of the high-latitude permafrost, they show significant temperature impacts on all continents and northern-hemisphere ocean basins that raise the global mean temperature by 0.25 K.

Abstract

The trade winds cause strong upwelling in the eastern equatorial Pacific, and create the eastern Pacific Cold Tongue (EPCT) that has far-reaching impacts on global climate. However, large discrepancies persist in quantifying 20th-century EPCT sea surface temperature (SST) changes across different instrumental data sets. Here we synthesize four coral Sr/Ca-SST records from the tropical central-eastern Pacific to develop a Cold Tongue Index (CTI) reconstruction for 1887–1997. The coral CTI record shows a rapid 20th century warming of the EPCT, suggesting an underestimation of warming trends in instrumental CTI records. The decadal to multidecadal changes in reconstructed EPCT SST show an association with the Walker Circulation. Our reconstruction indicates that recent EPCT cooling during the global warming hiatus is not unusual in the context of the 20th century. Our results provide new evidence for 20th century EPCT SST changes and an observational constraint for predicting future tropical climate changes.

Abstract

Central Afar is shaped by the interaction between the Red Sea (RS) and Gulf of Aden (GoA) rifts. While there have been several studies conducted in the region, we know surprisingly little about the mechanism of connection between these two rift branches. Here we use high-resolution 3D lithospheric scale geodynamic modeling to capture the evolution of linkage between the RS and GoA rifts in central Afar. Our results demonstrate that the two rifts initially overlap and interact across a broad zone of faulting and vertical axis block rotation. However, through time, rift overlap is abandoned in favor of direct linkage which generates a series of localized en-echelon basins. The present-day direct linkage between the two rifts is supported by geodetic observations. Our study reconciles previously proposed models for the RS and GoA rift connection by considering spatial and temporal evolution of the rifts.

Abstract

Accurate modeling of snow depth (SD) processes is critical for understanding global energy balance changes, affecting climate change mitigation strategies. This study evaluates the Coupled Model Intercomparison Project Phase 6 (CMIP6) model performance in simulating daily SD across Canada. We assess CMIP6 outputs against observed data, focusing on daily SD averages, snow cover durations, and rates of accumulation and depletion, alongside annual SD peaks for 11 major Canadian catchments. Our findings reveal that CMIP6 simulations generally overestimate daily SD by 57.7% and extend snow cover duration by 30.5 days on average. While three models (CESM2, UKESM1-0-LL and MIROC6) notably align with observed annual SD peaks, simulation biases suggest the need for enhanced model parameterization to accurately capture snow physics, particularly in regions with permanent snow cover and complex terrains. This analysis underscores the necessity of refining CMIP6 simulations and incorporating detailed geographical data for better SD predictions.

Abstract

Bedload sediment transport plays an important role in the evolution of rivers, marshes and deltas. In these aquatic environments, vegetation is widespread, and plant species have unique morphology. However, the impact of real plant morphology on flow and sediment transport has not been quantified. This study used model plants with real plant morphology, based on the aquatic species Phragmites australis, Acorus calamus and Typha latifolia. The frontal area of these species increases away from the bed, which leads to higher near-bed velocity than would be predicted from depth-average frontal area. A plant morphology coefficient was defined to quantify the impact of vertically-varied plant frontal area. Laboratory experiments confirmed that the plant morphology coefficient improved the prediction of near-bed velocity, near-bed turbulent kinetic energy and bedload transport rate in canopies with realistic morphology. Plant morphology can alter transport rates by up to an order of magnitude, relative to the assumption of uniform morphology.

Abstract

Global climate models (GCMs) are unable to produce detailed runoff conditions at the basin scale. Assumptions are commonly made that dynamical downscaling can resolve this issue. However, given the large magnitude of the biases in downscaled GCMs, it is unclear whether such projections are credible. Here, we use an ensemble of dynamically downscaled GCMs to evaluate this question in the Sierra-Cascade mountain range of the western US. Future projections across this region are characterized by earlier seasonal shifts in peak flow, but with substantial inter-model uncertainty (−25 ± 34.75 days, 95% confidence interval (CI)). We apply the emergent constraint (EC) method for the first time to dynamically downscaled projections, leading to a 39% (−28.25 ± 20.75 days, 95% CI) uncertainty reduction in future peak flow timing. While the constrained results can differ from bias corrected projections, the EC is based on GCM biases in historical peak flow timing and has a strong physical underpinning.

Abstract

We examine the newly discovered phenomena of sinuous aurora on the nightside of Mars, using images of 130.4 and 135.6 nm oxygen emission measured by the Emirates Mars Mission EMUS ultraviolet spectrograph, and upstream measurements from the MAVEN and Mars Express spacecraft. They are detected in ∼3% of observations, totaling 73 clear detections. These emissions are narrow, elongated (1,000–6,000 km), cross Mars' UV terminator, and are oriented generally toward the anti-solar point, clustering into north, south, east, and west-oriented groups. Diverse morphologies are observed, though some spatial features, such as broad curves, may in some cases be due to temporal aliasing of aurora motion as each image is built up over 15–20 min. Sinuous aurora form away from Mars' strongest crustal magnetic fields and can be interrupted by moderate crustal fields. Sinuous aurora occurrence increases strongly with solar wind pressure, though brightness shows only a weak positive dependence on pressure. Interplanetary magnetic field (IMF) clock angle affects their occurrence and orientation: sinuous aurora show a broad range of orientations centered on the solar wind convection electric field (E conv) direction and forming in the +E conv hemisphere, although with moderate clockwise and counterclockwise average “twists” for westward and eastward IMF, respectively. From these features we infer a link between sinuous aurora and electron energization in Mars' magnetotail current sheet, where field geometry on the +E conv side of the sheet is more organized and symmetric. Determination of specific triggering conditions for sinuous aurora requires further investigation.

Abstract

Based on correlated magnetosphere-ionosphere (M-I) conjugate observations of seven events, we study the hot zone developed under short-circuiting conditions leading (a) to the development of outward Subauroral Polarization Streams (SAPS) or Subauroral Ion Drifts (SAID) electric (E) field and (b) to the various subauroral arcs' absence or presence. Results show (a) the close relations of the hot zone earthward extent and peak ion temperature (Ti) to the magnitude of outward SAPS/SAID E field and (b) the hot zone's high Ti (∼11,000 eV) developed under enhanced plasma turbulence that was (c) generated by the amplified narrow hot ion and electron plasma density peaks, (d) sometimes in plasmaspheric plumes, and that was (e) sometimes further enhanced by the strong auroral kilometric radiation (AKR) waves (f) leading to the development of enhanced SAPS/SAID E field. From these (a–f) findings we conclude for the seven events investigated that (a) the hot zone's development under short-circuiting conditions was regulated by the kinetic energy of mesoscale plasma flows and that (b) the hot zone created the favorable inner-magnetosphere conditions during short circuiting (c) for stable auroral red (SAR) arc development by plasma turbulence, which is the common source of heat/suprathermal particles accelerated downward, and (d) in the plasmaspheric plume scenario for SAR arc and Strong Thermal Emission Velocity Enhancement (STEVE) arc development by the plumes' enhanced cold plasma populations leading to strong shear flows and thus shear-flow instabilities well-known associated with the SAPS/SAR arc and recently regarded as a potential driver mechanism of the STEVE arc.

Abstract

Observations of far-ultraviolet (FUV) dayglow by the Global-scale Observations of Limb and Disk (GOLD) mission provide an opportunity for quantifying the global-scale response of the thermosphere to solar extreme-ultraviolet variability and geomagnetic activity. Relative temperature changes can be measured by monitoring changes in the rotational structure observed in molecular nitrogen Lyman-Birge-Hopfield (LBH) band emissions. We present a new technique for deriving effective neutral temperatures from GOLD FUV observations using optimal estimation fits to spectra containing LBH band emissions. We provide an overview of the theoretical basis for the GOLD Level 2 TDISK algorithm. Effects on derived effective neutral temperatures from instrument artifacts and particle background are reviewed. We also discuss GOLD Level 1C DAY and Level 2 TDISK data products and present representative examples of each. We show that effective neutral temperatures vary with local time, exhibit a strong dependence on season and solar zenith angle, and correlate strongly with geomagnetic and solar activity. Finally, we present results from a preliminary data product validation that show good agreement with coincident GOLD exospheric temperatures and predictions from a global reference atmospheric model.

Abstract

Eastern North America was constructed over several Wilson cycles, culminating in the breakup of Pangea. Previous seismological imaging lacked the resolution to depict precisely how ancient tectonic boundaries manifest throughout the lithosphere, how continental breakup modified the plate, or how ongoing mantle dynamics shapes the continental margin. We present a high-resolution, plate-scale seismic tomography model of the eastern US by combining an unprecedented suite of complementary data sets in a Bayesian framework. These data provide detailed resolution from crust to asthenosphere, identifying the base of the lithosphere and mid-lithospheric discontinuities. The plate thins in steps that align with ancient orogens. The lithospheric step at the Appalachian front is associated with cells of mantle upwellings, likely edge-driven convection, that erode the base of the plate and shape modern Appalachian topography. Low-velocity structures in the lithospheric-mantle align with the Grenville front and may be remnants of Rodinia assembly.

Abstract

The application of deep-learning-based seismic phase pickers has surged in recent years. However, the efficacy of these models when applied to monitoring volcano seismicity has yet to be fully evaluated. Here, we first compile a data set of seismic waveforms from various volcanoes globally. We then show that the performances of two widely used deep-learning pickers deteriorate systematically as the earthquakes' frequency content decreases. Therefore, the performances are especially poor for long-period earthquakes often associated with fluid/magma movement. Subsequently, we train new models which perform significantly better, including when tested on two data sets where no training data were used: volcanic earthquakes along the Cascadia subduction zone and tectonic low-frequency earthquakes along the Nankai Trough. Our model/workflow can be applied to improve monitoring of volcano seismicity globally while our compiled data set can be used to benchmark future methods for characterizing volcano seismicity, especially long-period earthquakes which are difficult to monitor.

Abstract

Using the latest coupled geospace model Multiscale Atmosphere-Geospace Environment (MAGE) and observations from Jicamarca Incoherent scatter radar (ISR) and ICON ion velocity meter (IVM) instrument, we examine the pre-reversal enhancement (PRE) during geomagnetic quiet time period. The MAGE shows comparable PRE to both the Jicamarca ISR and ICON observations. There appears to be a discrepancy between the Jicamarca ISR and ICON IVM with the later showed PRE about two times larger (∼40 m/s). This is the first time that MAGE is used to simulate the PRE. The results show that the MAGE can simulate the PRE well and are mostly consistent with observations.

Abstract

Seasonal hindcasts have previously been demonstrated to show multi-decadal variability in skill across the twentieth century in indices describing El-Niño Southern Oscillation (ENSO), which drives global seasonal predictability. Here, we analyze the skill of predicting ENSO events' magnitude and spatial pattern, in the CSF-20C coupled seasonal hindcasts in 1901–2010. We find minima in the skill of predicting the first (in 1930–1950) and second (in 1940–1960) principal components of sea-surface temperature (SST) in the tropical Pacific. This minimum is also present in the spatial correlation of SSTs, in 1930–1960. The skill reduction is explained by lower ENSO magnitude and variance in 1930–1960, as well as decreased SST persistence. The SST skill minima project onto surface winds, leading to worse predictions in coupled hindcasts compared to hindcasts using prescribed SSTs. Questions remain about the offset between the first and second principal components' skill minima, and how the skill minima impact the extra-tropics.

Abstract

The minerals carrying the magnetic remanence in geological samples are commonly a solid solution series of iron-titanium spinels known as titanomagnetites. Despite the range of possible compositions within this series, micromagnetic studies that characterize the magnetic domain structures present in these minerals have typically focused on magnetite. No studies systematically comparing the domain-states present in titanomagnetites have been undertaken since the discovery of the single vortex (SV) structure and the advent of modern micromagnetism. The magnetic properties of the titanomagnetite series are known to vary strongly with composition, which may influence the domain states present in these minerals, and therefore the magnetic stability of the samples bearing them. We present results from micromagnetic simulations of titanomagnetite ellipsoids of varying shape and composition to find the size ranges of the single domain (SD) and SV structures. These size ranges overlap, allowing for regions where the SD and SV structures are both available. These regions are of interest as they may lead to magnetic instability and “partial thermal remanent magnetization (pTRM) tails” in paleointensity experiments. We find that although this SD + SV zone occupies a narrow range of sizes for equidimensional magnetite, it is widest for intermediate (TM30-40) titanomagnetite compositions, and increases for both oblate and prolate particles, with some compositions and sizes having an SD + SV zone up to 100s of nm wide. Our results help to explain the prevalence of pTRM tail-like behavior in paleointensity experiments. They also highlight regions of particles with unusual domain states to target for further investigation into the definitive mechanism behind paleointensity failure.

Abstract

Volcano GPS networks can capture vital information during volcanic unrest to aid with hazard assessment and eruption forecasting, but can be hindered by their discrete point locations and possibly miss key spatial information. We show how numerical models can reveal controls on spatial deformation signal intensity compared against GPS network design. Using the GPS network at Soufrière Hills Volcano (SHV), Montserrat, and a range of models, we explore expected surface deformation patterns. Peak horizontal deformation is located offshore, highlighting the difficulties with geodetic monitoring on small ocean-island volcanoes. Onshore areas where the deformation signal is expected to be high are also identified. At SHV, topography plays a greater role in altering the relative distribution of surface displacement patterns than subsurface heterogeneity. Our method, which can be adapted for other volcanoes, highlights spatial areas that can be targeted for effective GPS station placement to help improve deformation monitoring efficiency.