Nitrogen inputs can be an important cost consideration for farmers in terms of economic profit as well as environmental impact. Elucidating genetic regions that are associated with plant phenotype response to nitrogen stress can help in facilitating breeding approaches that can mitigate these costs. A diverse population of 272 maize lines was planted at a field site in Champaign, IL in two consecutive years in reduced nitrogen conditions. 302 phenotypes were recorded including: seed ionomic content, root structural traits derived from 2-dimensional images as well as a 3-dimensional representation generated from x-ray computed tomography (XRT) scans, root traits extrapolated from mini-rhizotron systems, drone images across the growing season and end of season agronomic traits such as biomass and yield. BLUP models were fit to obtain estimates of single year genotypic values as well as across years values both of which took into account year specific spatial variation. Individual years and combined years BLUP values were used as response variables in genome wide association studies (GWAS) to identify loci significantly associated with each set of values. Significant associations were identified for all phenotype categories.

Over the last decades, climate science has evolved rapidly across multiple expert domains. Our best tools to capture state-of-the-art knowledge in an internally self-consistent modelling framework are the increasingly complex fully coupled Earth System Models (ESMs). However, computational limitations and the structural rigidity of ESMs mean that the full range of uncertainties across multiple domains are difficult to capture with ESMs alone. The tools of choice are instead more computationally efficient reduced complexity models (RCMs), which are structurally flexible and can span the response dynamics across a range of domain-specific models and ESM experiments. Here we present Phase 2 of the Reduced Complexity Model Intercomparison Project (RCMIP Phase 2), the first comprehensive intercomparison of RCMs that are probabilistically calibrated with key benchmark ranges from specialised research communities. Unsurprisingly, but crucially, we find that models which have been constrained to reflect the key benchmarks better reflect the key benchmarks. Under the low-emissions SSP1-1.9 scenario, across the RCMs, median peak warming projections range from 1.3 to 1.7{degree sign}C (relative to 1850-1900, using an observationally-based historical warming estimate of 0.8{degree sign}C between 1850-1900 and 1995-2014). Further developing methodologies to constrain these projection uncertainties seems paramount given the international community’s goal to contain warming to below 1.5{degree sign}C above pre-industrial in the long-term. Our findings suggest that users of RCMs should carefully evaluate their RCM, specifically its skill against key benchmarks and consider the need to include projections benchmarks either from ESM results or other assessments to reduce divergence in future projections.

The shape of ice-shelf cavities are a major source of uncertainty in understanding ice-ocean interactions. This limits assessments of the response of the Antarctic ice sheets to climate change. Here we use vibroseis seismic reflection surveys to map the bathymetry beneath the Ekström Ice Shelf, Dronning Maud Land. The new bathymetry reveals an inland-sloping trough, reaching depths of 1100 m below sea level, near the current grounding line, which we attribute to erosion by palaeo-ice streams. The trough does not cross-cut the outer parts of the continental shelf. Conductivity-temperature-depth profiles within the ice-shelf cavity reveal the presence of cold water at shallower depths and tidal mixing at the ice-shelf margins. It is unknown if warm water can access the trough. The new bathymetry is thought to be representative of many ice shelves in Dronning Maud Land, which together regulate the ice loss from a substantial area of East Antarctica.

The role of anthropogenic carbon dioxide (CO2) in global warming is confusing. Experts predict that changes in ocean level and atmospheric temperature will increase considerably in distant future. On the other hand, loss of ices in the World is already dramatic and has increased over the recent years. Anthropogenic CO2-related greenhouse effects may be responsible for the global warming; however ice imbalance remains to be explained in more details. We previously showed that estimated anthropogenic heat released between 1994 and 2017 was energetic enough to have caused the melting of a large part of the global ice lost during the same period. To complement this finding, the present work suggests that water on Earth behaves as a refrigerant and manages solar heat and anthropogenic heat similarly. It is also shown that the combustion of fossil hydrocarbons is releasing a huge amount of water stored for millions years in fossil hydrocarbon sources of energy. As anthropogenic heat is no longer negligible, minimizing CO2 production may not be enough to control climate perturbations. Hydrogen is regarded as a climate-friendly alternative source of energy. The last part suggests that heat-cycle assessment from cradle to grave should be used in addition to life cycle assessment to compare hydrogen with other sources of energy in the search for ways to minimize anthropogenic heat release and its impact on climate changes.

A description and assessment of the first release of the Arctic Subpolar gyre sTate Estimate (ASTE_R1), a data-constrained ocean-sea ice model-data synthesis is presented. ASTE_R1 has a nominal resolution of 1/3o and spans the period 2002-2017. The fit of the model to an extensive (O(10^9)) set of satellite and in situ observations was achieved through adjoint-based nonlinear least-squares optimization. The improvement of the solution compared to an unconstrained simulation is reflected in misfit reductions of 77% for Argo, 50% for satellite sea surface height, 58% for the Fram Strait mooring, 65% for Ice Tethered Profilers, and 83% for sea ice extent. Exact dynamical and kinematic consistency is a key advantage of ASTE_R1, distinguishing the state estimate from existing ocean reanalyses. Through strict adherence to conservation laws, all sources and sinks within ASTE_R1 can be accounted for, permitting meaningful analysis of closed budgets at the grid-scale, such as contributions of horizontal and vertical convergence to the tendencies of heat and salt. ASTE_R1 thus serves as the biggest effort undertaken to date of producing a specialized Arctic ocean-ice estimate over the 21st century. Transports of volume, heat, and freshwater are consistent with published observation-based estimates across important Arctic Mediterranean gateways. Interannual variability and low frequency trends of freshwater and heat content are well represented in the Barents Sea, western Arctic halocline, and east subpolar North Atlantic. Systematic biases remain in ASTE_R1, including a warm bias in the Atlantic Water layer in the Arctic and deficient freshwater inputs from rivers and Greenland discharge.

Investigating basins in light of tectonics provides clues to understanding geological happenings serving a great deal to explore base metal deposits & hydrocarbon reservoirs depending on type of basin & sediment accumulations in different margins. This paper focusses on archiving thoughts in wake of tectonics to understand the interplay of divergent,convergent & strike-slip settings leading to association of different basins on continental & oceanic crusts. Association of intracratonic sag basin, rift basin & passive margin basin is proposed in an extensional set up and a trench,forearc, back-arc & foreland basin is proposed for a collisional set up in active margins.

The South American rainfall Dipole (SAD) is a renowned spatial structure present in the austral summer as part of the South American monsoon system. SAD phases have been related with extreme precipitations and severe droughts across South America, but are yet to be predicted. Here, we reveal $2$ robust and reliable intraseasonal windows in the accumulated SAD index where we can forecast its quantile-state between $5$ to $15$ and $60$ to $70$ days in advance ($99\%$ significance level). These windows are insensitive to variations in the pole’s size and accumulation window, and results are consistent across different quantiles states (median, tercile, and quartile). Our method, which is based on analysing the lagged mutual information between future and present states, could be used in the development of early-warnings for extreme rainfall events. Moreover, it is unrestricted to the present analysis, being applicable to other stationary signals where a forecast is missing.

Deep meteoric waters comprise a key component of the hydrologic cycle, transferring water, energy, and life between the earth's surface and deeper crustal environments, yet little is known about the nature and extent of meteoric water circulation. Using water stable isotopes, we show that maximum circulation depths of meteoric waters across North America vary considerably from 1 to 5 km, with the deepest circulation in western North America in areas of greater topographic relief. Shallower circulation occurs in sedimentary and shield-type environments with subdued topography. The amount of topographic relief available to drive regional groundwater flow and flush saline fluids is an important control on the extent of meteoric water circulation, in addition to permeability. The presence of an active flow system in the upper few kilometers of the Earth's crust and stagnant brines trapped by negative buoyancy offers a new framework for understanding deep groundwater systems.

Ultrasonic transmission is sensitive to the variation in mechanical properties of materials. Wave propagation through fractured media introduces changes in the frequency content, travel time and transmission coefficient of the wave. A workflow based on physics-driven unsupervised learning is developed to process the transmitted ultrasonic-shear waveforms to non-invasively visualize the geomechanical alterations due to hydraulic fracturing of a tight sandstone. Novelty of the work involves the assignment of physically consistent clusters to the measurements of shear waveforms across the axial and frontal planes by incorporating the travel time of the peak of spectral energy and transmission coefficient. The proposed workflow generates maps of geomechanical alterations across the frontal and axial planes of the sample. The outputs of the workflow are in good agreement with independent techniques viz. acoustic emission and X-ray computed tomography. The proposed workflow can be adapted for improved fracture characterization in the subsurface when processing sonic-logging, cross-wellbore seismic or surface seismic waveform data.

The 15 January 2022 eruption of the Hunga volcano provides a unique opportunity to study the reaction of the ionosphere to large explosive events. In particular, this event allows us to study the global propagation of travelling ionospheric disturbances using various instruments. We focus on the detection of the ionospheric disturbances caused by this eruption over Europe, where dense networks of both ionosondes and GNSS receivers are available. This event took place on the day of a geomagnetic storm. We show how data from different instruments and from different observatories can be combined to clearly distinguish the TIDs produced by the eruption from those caused by concurrent geomagnetic activity. By comparing observations obtained from multiple types of instruments, we also show that TIDs produced by various mechanisms are present simultaneously, with different types of waves affecting different physical quantities.

Oceanography has entered an era of new observing platforms, such as biogeochemical Argo floats and gliders, some of which will provide three-dimensional maps of essential ecosystem variables on the North-West European (NWE) Shelf. In a foreseeable future operational centres will use multi-platform assimilation to integrate those valuable data into ecosystem reanalyses and forecast systems. Here we address some important questions related to glider biogeochemical data assimilation and introduce multi-platform data assimilation in a (pre)operational model of the NWE Shelf-sea ecosystem. We test the impact of the different multi-platform system components (glider vs satellite, physical vs biogeochemical) on the simulated biogeochemical variables. To characterize the model performance we focus on the period around the phytoplankton spring bloom, since the bloom is a major ecosystem driver on the NWE Shelf. We found that the timing and magnitude of the phytoplankton bloom is insensitive to the physical data assimilation, which is explained in the study. To correct the simulated phytoplankton bloom one needs to assimilate chlorophyll observations from glider or satellite Ocean Color (OC) into the model. Although outperformed by the glider chlorophyll assimilation, we show that OC assimilation has mostly desirable impact on the sub-surface chlorophyll. Since the OC assimilation updates chlorophyll only in the mixed layer, the impact on the sub-surface chlorophyll is the result of the model dynamical response to the assimilation. We demonstrate that the multi-platform assimilation combines the advantages of its components and always performs comparably to its best performing component.

The Wind spacecraft is a critical element in NASA’s Heliophysics System Observatory (HSO) – a fleet of spacecraft created to understand the dynamics of the sun-Earth system – owing to the combination of its longevity (>25 years in service), its diverse compliment of instrumentation, and high resolution and accurate measurements. Wind has over 55 selectable public data products with over ~1100 total data variables (including OMNI data products) on SPDF/CDAWeb alone. These data have led to paradigm shifting results in studies of statistical solar wind trends, magnetic reconnection, large-scale solar wind structures, kinetic physics, electromagnetic turbulence, the Van Allen radiation belts, coronal mass ejection topology, interplanetary and interstellar dust, the lunar wake, solar radio bursts, solar energetic particles, and extreme astrophysical phenomena such as gamma-ray bursts. This review introduces the mission and instrument suites then discusses examples of the contributions by Wind to these scientific topics that emphasize its importance to both the fields of heliophysics and astrophysics.

We investigated the role of whitesand ecosystems (WSEs) in blackwater formation to develop novel constraints for the terrestrial carbon export from land to ocean. We used Orbitrap mass spectrometry to identify markers in dissolved organic carbon (DOC) from ground- and surface waters of two contrasting WSEs feeding Rio Negro tributaries, and compared them with known Rio Negro markers. Tributaries were fed by a whitesand riparian valley connected to plateau, and a typical upland whitesand . WSE-DOC molecular composition differed by 80% from plateau DOC, which was characterized by reworked, highly unsaturated N- and S-containing molecules. WSE-DOC contained mainly condensed aromatics and polyphenols. WSE samples differed by 10% in molecular DOC composition and also by their isotopic content (C, O, H). Upland WSE-DOC was exported by fresh precipitation and had maximum age of 13 years, being five years older than riparian valley WSE-DOC. Unexpectedly, only markers from the upland WSE, which cover a small proportion of the landscape, were identical to Negro markers. Markers of the riparian valley WSE, which are widespread and known for high DOC export, surprisingly showed lower coverage with Negro markers. Our results suggest that terrestrial DOC from upland WSEs is a main source of specific blackwater molecules missing in the ecosystem C balance, whereas C export from the riparian valley and especially from plateaus represents mainly recycled and transformed carbon not directly affecting ecosystem C balance. Our study highlights the potential of high-resolution techniques to constrain carbon balances of ecosystems and landscapes.

A novel approach to improve seasonal to interannual sandy shoreline predictions is presented, whereby model free parameters can vary in time, adjusting to potential non-stationarity in the underlying model forcing. This is achieved by adopting a suitable data assimilation technique (Dual State-Parameter Ensemble Kalman Filter) within the established shoreline evolution model, ShoreFor. The method is first tested and evaluated using synthetic scenarios, specifically designed to emulate a broad range of natural sandy shoreline behavior. This approach is then applied to a real-world shoreline dataset, revealing that time-varying model free parameters are linked through physical processes to changing characteristics of the wave forcing. Greater accuracy of shoreline predictions is achieved, compared to existing stationary modelling approaches. It is anticipated that the wider application of this method can improve our understanding and prediction of future beach erosion patterns and trends in a changing wave climate.

Large boulders with a diameter of up to several tens of meters are globally observed in mountainous bedrock channel environments. Recent theories suggest that high concentrations of boulders are associated with changes in channel morphology. However, data are scarce and ambiguous, and process-related studies are limited. Here we present data from the Liwu River, Taiwan, showing that channel width and slope increase with boulder concentration. We apply two mass balance principles of bedrock erosion and sediment transport and develop a theory to explain the steepening and widening trends. Five mechanisms are considered and compared to the field data. The cover effect by immobile boulders is found to have no influence on channel width. Channel width can partially be explained by boulder control on the tools effect and on the partitioning of the flow shear stress. However, none of the mechanisms we explored can adequately explain the scattered width data, potentially indicating a long-timescale adjustment of channel width to boulder input. Steepening can be best described by assuming a reduction of sediment transport efficiency with boulder concentration. We find that boulders represent a significant perturbation to the fluvial landscape. Channels tend to adjust to this perturbation leading to a new morphology that differs from boulder-free channels. The general approach presented here can be further expanded to explore the role of other boulder-related processes.

High quality citizen science data can be instrumental in advancing science toward new discoveries and a deeper understanding of under-observed phenomena. However, the error structure of citizen scientist (CS) data must be well-defined. Within a citizen science program, the errors in submitted observations vary, and their occurrence may depend on CS-specific characteristics. This study develops a graphical Bayesian inference model of error types in CS data. The model assumes that: (1) each CS observation is subject to a 5 specific error type, each with its own bias and noise; and (2) an observation’s error type depends on the error community of the CS, which in turn relates to characteristics of the CS submitting the observation. Given a set of CS observations and corresponding ground-truth values, the model can be calibrated for a specific application, yielding (i) number of error types and error communities, (ii) bias and noise for each error type, (iii) error distribution of each error community, and (iv) the error community to which each CS belongs. The model, applied to Nepal CS rainfall observations, 10 identifies five error types and sorts CSs into four model-inferred communities. In the case study, 73% of CSs submitted data with errors in fewer than 5% of their observations. The remaining CSs submitted data with unit, meniscus, unknown, and outlier errors. A CS’s assigned community, coupled with model-inferred error probabilities, can identify observations that require verification. With such a system, the onus of validating CS data is partially transferred from human effort to machine-learned algorithms.

Deep underground water injections induce seismicity. When the seismic fractures coalesce into far-reaching pathways for fluid migration, the migrating fluid may reach pre-existing faults, and by decreasing fault strength, can trigger major seismic events. We assume that the potential for building such pathways depends on closeness of hypocenters, similarity of fracture planes orientations, and closeness of radii taking off from the injection point, on which events locate. We define this potential as the average distance between seismic events in the space of parameters quantifying the above conditions. We show that in the studied case from The Geysers geothermal field, this potential is highly correlated with injection rate. When the overall level of injection rate is high, the higher the injection rate, the more the potential for building far-reaching pathways for fluid migration is reduced.

Geologists have documented at least fourteen occurrences of “giant ooids”, a geologically rare type of carbonate allochem, in Neoproterozoic successions at low paleo-latitudes. Recent experiments and modeling demonstrated that ooid size reflects an equilibrium between precipitation and abrasion rates, such that ooid size could be used as a geological proxy for CaCO3 mineral saturation state (Ω). Here, the documented sizes of Neoproterozoic giant ooids were applied to estimate seawater , which provided a novel approach to constraining temperature, partial pressure of CO2, and alkalinity preceding Neoproterozoic glaciations. The results suggest that giant ooid formation was most plausible with seawater alkalinity elevated over its present value by at least a factor of two, and either much warmer (40C) or much colder (0C) climate than modern tropical carbonate platforms, which have important and divergent implications for climate states and ecosystem responses prior to the initiation of each Neoproterozoic glaciation.