Arctic plants are small in stature and spectrally diverse, which presents challenges to current NASA missions to visualize effects of disturbance or directional vegetation change via mapping. Remotely sensed data having fine spatial (ca. 10 cm pixels) and spectral grain (eg. “hyperspectral”) will therefore help resolve patches of many arctic plant groups, such as dwarf shrubs, bryophytes and lichens and separate them from litter, wood or rock/soil. To address these challenges, in summer 2018 we sampled vegetation at 15 different sites around Fairbanks, Alaska using ground-based and airborne hyperspectral sensors under eight different AVIRIS ng flight lines next gen flight lines (circa 2017-2018). At each AVIRIS flight line, we estimated percent cover of plant functional types in eleven 1m2 quadrats every 10 m along a 100m transect. We then flew our UAV and imaging spectrometer (Headwall Micro A-series VNIR, 400-1000 nm, 330 bands, 10 cm pixels). Spectral signatures of any surfaces were sampled using a field spectroradiometer (PSR+ Spectral Evolution, 400-2500 nm, 1nm bands). We collected 600+ georeferenced scans from 70+ species/plant functional types at 25+ different sites around Alaska. Spectral profiles showed many different plant species have similar to indistinguishable signatures (eg. Paper birch and Alder) while many plant functional types that have been grouped together (eg. Moss) were very spectrally heterogenous. UAV-based hyperspectral imagery (ca. 4-10 cm pixels) resolved pure pixels of many artic plants. Our approach resolves fine grained ecological features, such as networks of circular patches (mostly lichens, brophytes and mineral soil) over very large areas (ca. 10,000 m2), created by small cryoturbation features (frost boils). We explore spectral unmixing and other statistical approaches to compare mapping results using our spectral library with AVIRIS ng (4 m pixels) and our UAV-based VNIR hyperspectral imagery.

Radiative cooling on the lowest atmospheric levels is of strong importance for modulating atmospheric circulations and organizing convection, but detailed observations and a robust theoretical understanding are lacking. Here we use unprecedented observational constraints from subsidence regimes in the tropical Atlantic to develop a theory for the shape and magnitude of low-level longwave radiative cooling in clear-sky, showing large peaks at the top of the boundary layer. A suite of novel scaling approximations is first developed from simplified spectral theory, in close agreement with the measurements. The radiative cooling peak height is set by the maximum lapse rate in water vapor path, and its magnitude is mainly controlled by the ratio of column relative humidity above and below the peak. We emphasize how elevated intrusions of moist air can reduce low-level cooling, by sporadically shading the spectral range which effectively cools to space. The efficiency of this spectral shading depends both on water content and altitude of moist intrusions; its height dependence cannot be explained by the temperature difference between the emitting and absorbing layers, but by the decrease of water vapor extinction with altitude. This analytical work can help to narrow the search for low-level cloud patterns sensitive to radiative-convective feedbacks: the most organized patterns with largest cloud fractions tend to occur in atmospheres below 10% relative humidity and feel the strongest low-level cooling. This motivates further assessment of these favorable conditions for radiative-convective feedbacks and a robust quantification of corresponding shallow cloud dynamics in current and warmer climates.

Land surface phenology (LSP) is associated with climate over space and time, and the monitoring of LSP help understandings of the terrestrial environmental changes. The LSP is often inferred by satellite observation, and long-term and regularly composite satellite imagery is now freely available. In this study, we demonstrate how LSP changes over space and time at the global scale over the last three decades by using GIMMS3g datasets. We focus on the magnitude and the timing of the peak of yearly phenological activity, estimated from a harmonic analysis. The first harmonic curve is regarded as a proxy of the overall productivity of vegetation and the second one is interpreted as a sensitive bimodal system changes. Results show the long-term trend of LSP changes; for example the peak of phenogical activity tend to be earlier in high-latitude regions. Land surface phenology (LSP) is associated with climate over space and time, and the monitoring of LSP help understandings of the terrestrial environmental changes. The LSP is often inferred by satellite observation, and long-term and regularly composite satellite imagery is now freely available. In this study, we demonstrate how LSP changes over space and time at the global scale over the last three decades by using GIMMS3g datasets. We focus on the magnitude and the timing of the peak of yearly phenological activity, estimated from a harmonic analysis. The first harmonic curve is regarded as a proxy of the overall productivity of vegetation and the second one is interpreted as a sensitive bimodal system changes. Results show the long-term trend of LSP changes; for example the peak of phenogical activity tend to be earlier in high-latitude regions.

Serpentinized peridotite is actively reacting with groundwater in the subsurface in the Samail ophiolite in Oman. Although these rocks are partially to completely serpentinized, they are steeped in a groundwater aquifer containing hyperalkaline fluids rich in H production that can continue at low temperature, even after primary olivine and pyroxene are exhausted, thereby sustaining habitable conditions for microbial life.

Das2 describes a collection of cooperating programs originally created to support daily review and analysis activities of the Cassini Radio and Plasma Wave Science (RPWS) investigation. The system proved useful and is now relied on for rapid access to working data sets from many planetary missions including Mars Express and Juno, as well as ground-based radio astronomy results from the Nançay Decameter Array and Long Wave Array 1. As more teams have begun using das2 tools, the need for updates to what was largely an in-house protocol have become apparent. Though Autoplot continues to be the most flexible and commonly used das2 client program, interfacing with other tools would benefit the research community. We will provide an overview of recent updates to the das2 interface definition supporting redundant servers and federated data source catalogs. We will describe a cross site deployment between Southwest Research Institute and the University of Iowa to aid collaboration among ASPERA-3 and MARSIS investigators. We will give an update on the status of new client libraries for NumPy and IDL, as well as das2 stream adapters for HAPI and VOTables. Finally, we will describe how working data sets can be published in-place by registering das2 data sources with a VESPA EPN-TAP service.

Over 95% of volcanism on Earth occurs at mid-ocean ridges (MORs) where tectonic plates diverge. How melt is produced depends on the mineral composition and water content. However, it has proven challenging to understand how melting changes when one or more minerals have completely melted. This project examines differences on MOR melting that come with different assumptions in solidus changes with exhaustion of one of the component minerals, clinopyroxene (cpx). To do this, we constructed 2D numerical models of temperature, mantle flow, and melt production at MORs. We ran several models with different amounts of temperature shift in the solidus with loss of cpx. Using zero shift as a baseline, melting starts around 80km depth and peaks at 35km, exhausting cpx, lowering melt output. A second smaller melting region develops more shallowly where there is no cpx. Additional trials in changing the shift in solidus with loss of cpx were done with varying amounts of mantle hydration. For all trials, total melt decreases with larger shifts in solidus. The shallower melting disappears as greater shifts are made. Increasing hydration allows melting to start at deeper depths, but has little effect on the total amount of melt production.

Large earthquakes that occur away from plate boundaries (i.e., large intraplate earthquakes), though rare, could cause heavy damage. Understanding their causes could help with seismic hazard assessment. In this study, we image the seismogenic structure under the 1969 Ms6.4 Yangjiang intraplate earthquake within the stable South China Block with a high-resolution three-dimensional shear-wave velocity model constructed from ambient noise tomography based on a high-density seismic array. The model images relatively low velocities at a fault intersection region from the surface to at least 13 km depth in the Yangjiang seismogenic zone. Given spatial links among the faults, surface seawater, and low velocities, we interpret the low velocities to reflect the presence of seawater-filled highly-fractured rocks in fault zones. We infer that the seawater infiltration could have elevated pore pressure in the long term and lowered effective stress, as evidenced by low earthquake b values at depths of 8-13 km. This process could explain the generation of the Ms6.4 Yangjiang earthquake. We further hypothesize that the large intraplate earthquakes within stable plates are prone to occur in regional weakening regions that tend to build up stress. Given sufficient tectonic stress accumulation, the long-term hydrologically-driven crustal stress variations via increasing pore pressure could play an essential role in triggering large intraplate earthquakes. This study could help seismic hazard assessment in the Guangdong-Hong Kong-Macao-Greater-Bay-Area, China.

The wintertime Kuroshio sea surface temperature (SST) front have the significant climate effects on southern China. The study demonstrates a close relationship between heavy precipitation over Southern China and Kuroshio SST front in winter. More than half winter heavy rainfall events in Southern China are proved to be resulted from strong High-frequency Variability events of the sea surface Wind Coupled with Precipitation (HV-WCP) over Kuroshio SST front. One day before strong HV-WCP events, the initial precipitation appears over Middle-lower Yangtze River due to the significantly enhanced frontal intensity. Then the precipitation generates low level cyclone and southeasterly wind anomalies, after it moving into Kuroshio front area because of the winter monsoon. The significant marine atmospheric boundary layer (MABL) height gradient over Kuroshio leads to plentiful moisture transporting from MABL into free atmosphere and enhances the local precipitation again. This process further causes the large-scale stratus rainband extending to Southern China and enhancing the heavy rainfall locally. Especially in 2008 winter, several processes of a strong HV-WCP event followed by continuous weak ones are conducive to the low-temperature-precipitation disaster in Southern China

The Chilean subduction zone is one of the most seismically active regions on Earth, due to the shallow depth of the seismogenic zone in combination with the high coupling coefficients and high plate convergence rate. On February 27, 2010, the Maule earthquake, which is one of the strongest instrumentally registered megathrust earthquakes, occurred in Darwin seismic gap – a seismically calm zone existed near the coast of Chile since 1835. We use the keyboard model of generation of strong subduction earthquakes [Lobkovky et al., 1991] to analyze the peculiarities of seismic deformation cycle (SDC) related to the Darwin seismic gap and the 2010 earthquake. Keyboard structure of the South American continental margin near the source zone of the Maule earthquake is confirmed by seismological and geological data. Using of keyboard model allows us to associate interseismic, coseismic and postseismic deformations observed by satellite geodesy with the action of particular geodynamic processes and, therefore, to study their features. To achieve this aim, we analyze the data of almost 10 years of continuous observations at 76 stations of the Chilean GPS network deployed along the source zone of the 2010 Maule earthquake. The analysis of variations in surface deformation fields is based on displacement rates fields of GPS stations estimated over 1-year intervals. On the basis of registered coseismic displacements we construct a model of slip distribution in the source zone of the Maule earthquake and determine the magnitudes of instantaneous shifts of seismogenic blocks towards the ocean, which reached 1-3 meters. In the first two years after the 2010 earthquake GPS stations shift toward the ocean over the whole Central Chile region, which indicates passing of aftershock stage of the SDC. Over the next 7 years of observations, the observed displacements can be mainly explained by the process of restoring the stationary state of stress accumulation for seismogenic blocks in the frontal part of the subduction zone in combination with the continuing displacement of the rear massif by a viscous asthenospheric flow. To assess the time of transition of seismogenic zone to stationary state of accumulation of elastic stresses we construct models of frictional afterslip and viscoelastic relaxation in the asthenosphere. The durations of the afterslip and viscoelastic relaxation processes for the Maule earthquake are according to our estimates about half a year and more than 15 years respectively. Understanding of the features of the SDC plays a significant role in the seismic hazard assessment of the Maule and Biobio regions of Chile.

Realistic simulations of Central California reveal interactions between shoaling internal tidal bores and submesoscale currents on the inner-shelf (30-60 m depth). These interactions comprise collisions between internal tidal upwelling, ‘forward’ bores (FBs) with submesoscale currents (SMCs) in the form of surface layer density fronts or filaments with downwelling secondary circulation. Along-shore oriented FBs collide with both cross-shore (perpendicular interaction) or along-shore (parallel interaction) oriented SMCs. In perpendicular interaction, FBs colliding into cross-shore oriented SMCs refract around the offshore tip of the downwelling front or filament. SMCs generally survive perpendicular interaction, despite partial disruption of downwelling secondary circulation by FBs. An example of parallel interaction demonstrates (1) blocking of FB propagation by elevated mixing and dense filament formation on the inner-shelf and (2) the subsequent destruction of the dense filament coincident with a decrease in vertical mixing and FB propagation underneath it. For both perpendicular and parallel interaction, FB propagation is modulated by a varying medium introduced by SMC density and current structure. The computational evidence of these interactions corroborates recent observations of interactions between small-scale, nearshore currents in the real ocean. This study motivates further exploration of interactions between fronts, filaments, internal tidal bores, and vortices in the nearshore.

High spatial resolution remote sensing and machine learning have improved the accuracy and affordability of high-throughput phenotyping. This paper presents an innovative approach to yield prediction, leveraging multimodal networks and integrating remote sensing data from two sensing technologies. We explore the synergy among different types of remote sensing data, meteorological data, and management practices employing advanced machine learning techniques to enhance accuracy and reliability in yield predictions.This study focuses on three experiments, one in 2021 and two in different environments with distinct management practices in 2022. Hyperspectral, LiDAR and weather-related features served as initial inputs to the LSTM recurrent neural network-based yield prediction models; management practices related categorical variables were concatenated after the time series output from the attention network. In each experiment, 80% of the data was used for training the model and 20% for testing, investigating three deep learning networks:Traditional vanilla stacked LSTM network.Stacked LSTM Network with a temporal attention mechanism.Multi-modal network for the different remote sensing modalities.The attention weights of each time-step were evaluated to determine the importance of each date;All models produced good predictions, but the attention mechanism coupled with the multi-modality network showed the effectiveness of combining multimodal remote sensing data optimally throughout the season and deep learning algorithms in optimizing agricultural decision-making processes. The Attention networks also provided increased interpretability over the growing season, showing flowering time to be the most critical time for the models, which is consistent with field-based trials.

Diapirism is crucial for heat and mass transfer in many geodynamic processes. Understanding diapir ascent velocity is vital for assessing its significance in various geodynamic settings. Although analytical estimates exist for ascent velocities of diapirs in power-law viscous, stress weakening fluids, they lack validation through 3D numerical calculations. Here, we improve these estimates by incorporating combined linear and power-law viscous flow and validate them using 3D numerical calculations. We focus on a weak, buoyant sphere in a stress weakening fluid subjected to far-field horizontal simple shear. The ascent velocity depends on two stress ratios: (1) the ratio of buoyancy stress to characteristic stress, controlling the transition from linear to power-law viscous flow, and (2) the ratio of regional stress associated with far-field shearing to characteristic stress. Comparing analytical estimates with numerical calculations, we find analytical estimates are accurate within a factor of two. However, discrepancies arise due to the analytical assumption that deviatoric stresses around the diapir are comparable to buoyancy stresses. Numerical results reveal significantly smaller deviatoric stresses. As deviatoric stresses govern stress-dependent, power-law, viscosity analytical estimates tend to overestimate stress weakening. We introduce a shape factor to improve accuracy. Additionally, we determine characteristic stresses for representative mantle and lower crustal flow laws and discuss practical implications in natural diapirism, such as sediment diapirs in subduction zones, magmatic plutons or exhumation of ultra-high-pressure rocks. Our study enhances understanding of diapir ascent velocities and associated stress conditions, contributing to a thorough comprehension of diapiric processes in geology.

Relationships between climate variability and climate sensitivity are to be expected where the damping of a climatic anomaly is due to a change in the energy balance of the planet, such that the Fluctuation-Dissipation theorem heuristically applies [Leith, 1975]. A recent attempt to relate Equilibrium Climate Sensitivity (ECS) to global temperature variability over the historical period suggested a surprisingly tight emergent constraint on ECS [Cox et al., 2018]. However, the sensitivity-variability relationship in that study was partially hidden by anthropogenic forcing over the historical period. Here we examine instead CMIP5 control runs. These runs have no external forcing and therefore provide a much cleaner test of proposed links between internal variability and sensitivity. It has been noted before that there is a positive correlation between decadal temperature variability and climate sensitivity across climate models [Colman & Power, 2018]. Questions remained however as to how robust this relationship is across different model ensembles, what mechanisms are responsible for it, and whether it can be used as an emergent constraint on climate sensitivity. We examine the relationship between decadal variability and ECS using models of varying complexity, including CMIP5 control runs and a range of conceptual energy balance models for which analytical solutions are presented. Based on these results, a general mechanism becomes apparent and the shape of the relationship is determined to be more quadratic than linear. The nonlinearity has implications for using this relationship as an emergent constraint, where an incorrect assumption of linearity might lead to biased estimates. A further surprising implication of the study is that a slowdown in global warming does not necessarily imply that climate sensitivity is lower than previously estimated. Models with a higher sensitivity, but which broadly reproduce the long-term record of global warming, are actually more likely to have slow-down periods than models with lower sensitivity.

It is important to perform the quantitative interpretation of the continental margin lithosphere for a more accurate and comprehensive understanding of its tectonic behavior. In this study, we derived the seismic and elastic properties from the 2D seismic data recorded by the Korea Meteorological Administration (KMA) in 2014. In general, most of the previous researches have been based on travel time tomography or Full Waveform Inversion (FWI) methods. However, these methods are not robust to directly apply to the seismic ambient noise data due to its low signal-to-noise ratio (SNR). Therefore, we conducted L2-norm model-based impedance inversion to not only delineate the local geological structures but also suppress the meaningless footprints in the observed data. Moreover, we used FWEA18 models (Tao et al., 2018) as initial velocity and density models to create the inversion result more stable and accurate. Then, we interpreted the lithosphere and asthenosphere from the inverted P-impedance model, which is more obvious than the interpretation of the pre-existing data. The average depths of Moho and Lithosphere-Asthenosphere-Boundary (LAB) are 30 km and 80km, respectively. Furthermore, we estimated the change of bulk density as well as P- and S-wave velocities of the crust, lithospheric mantle, and asthenospheric mantle. Also, we predicted four elastic properties of each layer from the inverted seismic properties, such as bulk modulus, shear modulus, Young’s modulus, and Poisson’s ratio. These model results can help to understand the physical state and elastic behavior variations of the lithospheric and asthenospheric mantle as well as local lithospheric structures beneath the peninsula.

The El Niño Southern Oscillation (ENSO) modulates rainfall amount variability and, by extension, river discharge in the Philippines on seasonal to interannual temporal scales. The El Niño phase (ENP) of ENSO considerably decreases rainfall amounts on a seasonal scale in the western Pacific with varying degrees of heterogeneity expressed across the Philippines. Our understanding of the response in the hydroclimate to ENPs on interannual timescales is still relatively immature. As such, to investigate the hydroclimate response, a composite time series of 29 rainfall and 61 river discharge stations spanning 1901-2020 and 1908-2017 C.E., respectively, and covering the four major climate types in the Philippines were assessed. Our results suggest, regardless of climate type, that river discharge and rainfall data decrease following ENPs. The median response suggests that the decreasing trend can last up to seven years. Further, the hydroclimate response follows either a decreasing trend, if at conception of an ENP, or an increasing trend, if at the termination of an ENP. As water-scarcity becomes an area of immediate concern in an increasingly warming climate, our results have implications for interannual water resource management in this drought-prone tropical archipelago.

Eddies play a crucial role in shaping ocean dynamics by affecting material transport, and generating spatio-temporal heterogeneity. However, how eddies at different scales modulate biogeochemical transformation rates remains an open question. Applying a multi-scale decomposition to a numerical simulation, we investigate the respective impact of mesoscale and submesoscale eddies on nutrient transport and biogeochemical cycling in the California Current System. First, the non-linear nature of biological nutrient uptake results in a 50% reduction in primary production in the presence of eddies. Second, eddies shape the vertical transport of nutrients with a strong compensation between mesoscale and submesoscale. Third, the eddy effect on nutrient uptake is controlled by the covariance of temperature, nutrient and phytoplankton fluctuations caused by eddies. Our results shed new light on the tight interaction between non-linear fluid dynamics and ecosystem processes in realistic eddy regimes, highlighting the importance of both mesoscale and submesoscale variability.

Seismology focuses on the study of earthquakes and associated phenomena to characterize seismic sources and Earth structure, which both are of immediate relevance to society. This article is composed of two independent views on the state of the ICON principles (Goldman et al., 2021) in seismology and reflects on the opportunities and challenges of adopting them from a different angle. Each perspective focuses on a different topic. Section 1 deals with the integration of multiscale and multidisciplinary observations, focusing on integrated and open approaches, whereas Section 2 discusses computing and open-source algorithms, reflecting coordinated, networked, and open principles. In the past century, seismology has benefited from two co-existing technological advancements - the emergence of new, more capable sensory systems and affordable and distributed computing infrastructure. Integrating multiple observations is a crucial strategy to improve the understanding of earthquake hazards. However, current efforts in making big datasets available and manageable lack coherence, which makes it challenging to implement initiatives that span different communities. Building on ongoing advancements in computing, machine learning algorithms have been revolutionizing the way of seismic data processing and interpretation. A community-driven approach to code management offers open and networked opportunities for young scholars to learn and contribute to a more sustainable approach to seismology. Investing in new sensors, more capable computing infrastructure, and open-source algorithms following the ICON principles will enable new discoveries across the Earth sciences.

Extraction of internal tidal (IT) signals is central to the interpretation of Sea Surface Height (SSH) data. The increased spatial resolution of future wide-swath satellite missions poses a challenge for traditional harmonic analysis, due to prominent and unsteady wave-mean interactions at finer scales. However, the wide swaths will also produce spatially two-dimensional SSH snapshots, which allows us to treat IT extraction as an image translation problem for the first time. We design and train TITE, a conditional Generative Adversarial Network, which, given a snapshot of raw SSH from an idealized numerical eddying simulation, generates a snapshot of the embedded IT component. We test it on data whose dynamical regimes are different from the data provided during training. Despite the diversity and complexity of data, it accurately extracts ITs in most individual snapshots considered and reproduces physically meaningful statistical properties. Predictably, TITE’s performance decreases with the intensity of the turbulent flow.