Extreme fluctuations in the horizontal geomagnetic field (dBh/dt) may be generated at the Earth’s surface by electrical currents in the ionosphere and magnetosphere. Using a global database of 125 magnetometers covering several decades we present occurrence statistics for fluctuations exceeding the 99.97th percentile (P99.97) for both ramp changes (Rn) and the root-mean-square (Sn) of fluctuations over periods, τ, from 1 to 60 min and describe their variation with geomagnetic latitude and magnetic local time (MLT). Rates of exceedance are explained by reference to the magneto-ionospheric processes dominant in different latitude and MLT sectors, including ULF waves, interplanetary shocks, auroral substorm currents, and travelling convection vortices. By fitting Generalised Pareto tail distributions above P99.97 we predict return levels (RLs) for Rn and Sn over return periods up to 500 years. P99.97 and RLs increase monotonically with frequency (1/τ) (with a few exceptions at auroral latitudes) and this is well modelled by quadratic functions whose coefficients vary smoothly with latitude. For UK magnetometers providing 1-s cadence measurements, the analysis is extended to cover periods from 1 to 60 seconds and empirical Magnetotelluric Transfer functions are used to predict percentiles and return levels of the geoelectric field over a wide frequency range (2x10-4 to 4x10-2 Hz) assuming a sinusoidal field fluctuation. These results help identify the principal causes of field fluctuations leading to extreme geomagnetically induced currents (GIC) in ground infrastructure over a range of timescales and they inform the choice of frequency dependence to use with dBh/dt as a GIC proxy.

Kinematic finite-fault source inversions aim at resolving the spatio-temporal evolution of slip on a fault given ground motion recorded on the Earth’s surface. This type of inverse problem is inherently ill-posed due to two main factors. First, the number of model parameters is typically greater than the number of independent observed data. Second, small singular-values are generated by the discretization of the physical rupture process and amplify the effect of noise in the inversion. As a result, one can find different slip distributions that fit the data equally well. This ill-posedness can be mitigated by decreasing the number of model parameters, hence improving their relationship to the observed data. In this article, we propose a fuzzy function approximation approach to describe the spatial slip function. In particular, we use an Adaptive Network-based Fuzzy Inference System (ANFIS) to find the most adequate discretization for the spatial variation of slip on the fault. The fuzzy basis functions and their respective amplitudes are optimized through hybrid learning. We solve this earthquake source problem in the frequency domain, searching for independent optimal spatial slip distributions for each frequency. The approximated frequency-dependent spatial slip functions are then used to compute the forward relationship between slip on the fault and ground motion. The method is constrained through Tikhonov regularization, requiring a smooth spatial slip variation. We discuss how the number of model parameters can be decreased while keeping the inversion stable and achieving an adequate resolution. The proposed inversion method is tested using the SIV1-benchmark exercise.

Multispectral imaging with unmanned aircraft systems (UAS) is a promising high-throughput phenotyping technology that has been shown to help understand the causal mechanisms associated with crop productivity. This imaging technology can accurately predict complex agronomic traits like grain yield within a given generation, creating the potential to fast-track selections in plant breeding and increase genetic gains. The objective of this study was to determine the effectiveness and efficiency of prediction on grain yield in an abnormal drought year across locations within a breeding program. Eleven spectral reflectance indices (SRI) including NDRE, NWI, NDVI, and percent canopy cover were used to evaluate Washington State University winter wheat breeding lines between 2018 and 2021. Data was collected using a DJI Inspire 2 drone, equipped with a Sentera Quad Multispectral Sensor, and collected at the heading date. Lines were observed from single location, single replication preliminary yield trials to multi-location, replicated advanced yield trials. Lines advanced in the breeding program were evaluated across 13 different location-year trials. The calculated SRIs and canopy cover were used individually and in combination as fixed effects in mixed model prediction for grain yield under drought conditions. Models were independently validated with 2021 data. Across locations, SRIs are shown to improve the prediction performance for grain yield under abnormal drought conditions by as much as 40% in the case of NDRE. This research is vital for plant breeders to understand the utility of UAS imaging in variety improvement when dealing with abnormal growing seasons.

The field is not always easy for plant phenotyping using conventional phenotyping platforms due to the limited accessibility and regulated aviation area. Smartphone-triggered ground images were collected on wheat field that has a limited access to monitor growth conditions of four wheat varieties, Shinyoung (SY), Joseong (JS), Taewoo (TW), and Cheongwoo (CW). For field mapping during the growing season, six sets of the raw RGB images were acquired by a smartphone camera in an oblique view angle and processed to transform into nadir view images. A series of algorithms were developed to process the skewed tile images to straighten into the nadir images, align the deskewed images, and stitch them into a field image by detecting crop rows using Hough Transformation. Open-source software, iStitch, was developed to automate the algorithms in a batch process. Plot-level metrics were extracted to analyze plant growth of the wheat varieties using a gridding method for vegetation and leaf area indexes. The processed images resulted in the successful transformation and consistency of algorithms on image alignment and stitching. Plot-level analysis indicated that SY variety performed superior to the other varieties in plant quality and quantity and significantly different from TW variety in canopy coverage. The proposed approach of the stitching and gridding was applied on the skewed images acquired by a smartphone camera but can be directly used for other applications of plant phenotyping on images acquired by a camera on a mobile platform or a grid of stationary cameras in greenhouse or outdoor fields.

In the face of ongoing marine deoxygenation, understanding timescales and drivers of past oxygenation change is of critical importance. Marine sediment cores from tiered silled basins provide a natural laboratory to constrain timing and implications of oxygenation changes across multiple depths. Here, we reconstruct oxygenation and environmental change over time using benthic foraminiferal assemblages from sediment cores from three basins across the Southern California Borderlands: Tanner Basin (EW9504-09PC, 1194 m water depth), San Nicolas Basin (EW9504-08PC, 1442 m), and San Clemente Basin (EW9504-05PC ,1818 m). We utilize indicator taxa, community ecology, and an oxygenation transfer function to reconstruct past oxygenation, and we directly compare reconstructed dissolved oxygen to modern measured dissolved oxygen. We generate new, higher resolution carbon and oxygen isotope records from planktic (Globigerina bulloides) and benthic foraminifera (Cibicides mckannai) from Tanner Basin. Geochemical and assemblage data indicate limited ecological and environmental change through time in each basin across the intervals studied. Early to mid-Holocene (11.0-4.7 ka) oxygenation below 1400 m (San Clemente and San Nicolas) was relatively stable and reduced relative to modern. San Nicolas Basin experienced a multi-centennial oxygenation episode from 4.7-4.3 ka and oxygenation increased in Tanner Basin gradually from 1.7-0.8 ka. Yet across all three depths and time intervals studied, dissolved oxygen is consistently within a range of intermediate hypoxia (0.5-1.5 ml L-1 [O2]). Variance in reconstructed dissolved oxygen was similar to decadal variance in modern dissolved oxygen and reduced relative to Holocene-scale changes in shallower basins.

Canopy imaging is a non-invasive phenotyping approach to quantify parameters such as canopy size, stress symptoms, and pigment concentrations. Unlike destructive measurements, canopy imaging is fast and easy. However, analysis of the images can be time consuming. To facilitate large-scale use of imaging, the cost of imaging systems needs to be reduced and the analysis needs to be automated. We developed low-cost imaging systems using a Raspberry Pi microcomputer, equipped with a monochrome camera and filter, at a total hardware cost of ~$500. The latest version of our imaging system takes images under blue, green, red, and infra-red light, as well as images of chlorophyll fluorescence. The system uses a Python-based program to collect and analyze images automatically. The multi-spectral imaging system separates plant from background using the chlorophyll fluorescence image and generates normalized difference vegetation index (NDVI) and anthocyanin content index (ACI) images and histograms, providing quantitative, spatially-resolved information. We verified that these indexes correlate strongly with leaf chlorophyll and anthocyanin concentration. The low cost of the system can make this imaging technology widely available.

Plate reconstruction studies show that the Neotethys Ocean was closing due to convergence of Africa and Eurasia towards the end of the Cretaceous. The period around 75 Ma reflects the onset of continental collision between the two plates, although convergence was still mainly accommodated by subduction, with the Neotethys slab subducting beneath Eurasia. Africa was separated from the rapidly north moving Indian plate by the Owen oceanic transform in the northeast. The rest of the plate was surrounded by mid-ocean ridges. Geologic observations in large basins show that Africa was experiencing continent-wide rifting related to northeast-southwest extension. We aim to quantify the forces and related paleostresses associated with this tectonic setting. To constrain these forces, we use the latest plate kinematic reconstructions, while balancing horizontal gravitational stresses, plate boundary forces and the plate's interaction with the underlying mantle. The contribution of dynamic topography to horizontal gravitational stresses is based on recent mantle convection studies. We model intraplate stresses and compare them with the strain observations. We find that slab pull, horizontal gravitational stresses and transform shear tractions in general acted with the same orientation as the absolute motion of the African plate 75 Ma. Both the balance between these three and the other, resistive, forces, and the fit to strain observations require the net slab pull, as experienced by the plate, to be low, pointing to the absence of a mature continuous Neotethys subduction zone at the time. This corresponds well to reconstructions of micro-continents interfering with the Neotethyan subduction.

Cosegmentation is a recent and rapidly emerging and rapidly growing extension of segmentation, which aims to detect the common object(s) in a group of images. Current cosegmentation methods are ideal and effective only for certain dataset types with limited features that still produce errors making it difficult to obtain detailed metrics of object parts. We propose to build a unified, trainable framework that incorporates multiple features of a high-throughput dataset’s segmented images from multiple algorithms using cosegmentation. Specifically, we propose a novel Cosegmentation for Plant Phenotyping Network (CoPPNet) that utilizes a Fully Convolutional Neural Network with a K-Means Clustering feedback loop for optimal temporal loss. The results from this study will set the benchmark for a novel advancement in computer vision segmentation accuracy and plant phenomics to better understand a plant’s environmental interactions for maximal resilience and yield.

Vertical land motion (VLM) from past and ongoing glacial changes can amplify or mitigate ongoing relative sea level change. We present a high resolution VLM-model for the wider Arctic, that includes both present-day ice loading (PDIL) and glacial isostatic adjustment (GIA). The study shows that the non-linear elastic uplift from PDIL is significant (0.5-1 mm/y ) in most of the wider Arctic and exceeds GIA at 15 of 54 Arctic GNSSsites, including sites in non-glaciated areas of the North Sea region and the east coast of North America. Thereby the sea level change from PDIL (1.85 mm/y) is significantly mitigated from VLM caused by PDIL. The combined VLM-model was consistent with measured VLM at 85% of the GNSS-sites (R=0.77) and outperformed a GIA-only model (R=0.64). Deviations from GNSS-measured VLM can be attributed to local circumstances causing VLM.

Martian meteorites are the only direct samples from Mars, thus far. Currently, there are a total of 262 individual samples originating from at least 11 ejection events. Geochemical analyses, through techniques that are also used on terrestrial rocks, provide fundamental insights into the bulk composition, differentiation and evolution, mantle heterogeneity, and role of secondary processes, such as aqueous alteration and shock, on Mars. Martian meteorites display a wide range in mineralogy and chemistry, but are predominantly basaltic in composition. Over the past six years, the number of martian meteorites recovered has almost doubled allowing for studies that evaluate these meteorites as suites of igneous rocks. However, the martian meteorites represent a biased sampling of the surface of Mars with unknown ejection locations. The geology of Mars cannot be unraveled solely by analyzing these meteorites. Rocks analyzed by rovers on the surface of Mars are of distinct composition to the meteorites, highlighting the importance of Mars missions, especially sample return. The Mars 2020 Perseverance rover will collect and cache --- for eventual return to Earth --- over 30 diverse surface samples from Jezero crater. These returned samples will allow for Earth-based state-of-the-art analyses on diverse martian rocks with known field context. The complementary study of returned samples and meteorites will help constrain the evolution of the martian interior and surface. Here, we review recent findings and advances in the study of martian meteorites and examine how returned samples would complement and enhance our knowledge of Mars.

The Proterozoic Kayad Zn-Pb deposit in Ajmer, Rajasthan is located within the Aravalli-Delhi Fold Belt in western India. Mineralization of sphalerite and galena, commonly associated with chalcopyrite and pyrrhotite, is hosted primarily by graphitic quartz mica schist (QMS) and subordinately by calc-silicate, quartzite and pegmatite. In QMS, both massive ore, evidently formed by remobilization, and laminated ore are present. Calc-silicate and quartzite contain disseminated sulfides while pegmatites contain sulfide veins that cause massive mineralization. Mineral replacement textures such as replacement of albite and muscovite by K-feldspars and biotite by chlorite suggest that Fe-Cu sulfides, represented by chalcopyrite and pyrrhotite, formed during potassic and acidic alteration. Trace element characterization demonstrates that between co-existing chalcopyrite and pyrrhotite, Ag, Zn, Sn, In, Cd, Ga are strongly portioned in chalcopyrite whereas Co and Ni are partitioned in pyrrhotite. High concentration of Ag (up to ~9000 ppm) in chalcopyrite adds to economic potential of the deposit. Barring the exception of massive ore in QMS, the trace element compositions of chalcopyrite and pyrrhotite are host-rock-independent suggesting profound control of the parental hydrothermal fluid on their composition. In laminated QMS, pegmatite and quartzite, higher Co, Cd, Mn and In in sphalerite and higher Ag, Sb, Bi, Se in galena compared to chalcopyrite suggest that these phases co-crystallized during their formation. In contrast in remobilized massive ore in QMS, higher Co, Cd and Mn in sphalerite over chalcopyrite and higher Ga, Sn and In in chalcopyrite over sphalerite and galena possibly indicate co-crystallization followed by recrystallization. Furthermore, constant yet distinct Cd:Zn ratios of chalcopyrite and co-existing sphalerite may indicate involvement of two different fluids. The observed trace element characteristics can be best explained by co-crystallization of chalcopyrite and sphalerite by fluid-mixing and subsequent recrystallization leading to the formation of part of the massive ore.

Urban drainage systems are facing major challenges with rapid urbanization and climate change, especially for developing countries. Green infrastructure (GI) is a natural-based solution expected to reduce flooding and help in water pollution control. Notwithstanding multiple research have discussed the contribution of GI to climate change adaptation. The efficiency of GI to extreme events in the context of the more frequent extreme precipitation events has received limited attention in the literature. This study aims to quantify the impact of historical and future extreme rainfalls on overflow flooding, pollutant transport, and GI’s potential in flood control by taking Phnom Penh City, the capital of Cambodia, as a case study. Firstly, we predicted the history of sub-daily extreme rainfall (1986-2005) by disaggregating outputs of various regional climate models based on the Artificial Neural Network (ANN) method. Secondly, we generated the future intensity-duration-frequency (IDF) curves based on sub-daily extreme rainfall (2026-2045) and input the design rainfall time series (based on the scenarios of RCP4.5 and RCP8.5) into a hydrological model (PCSWMM) to investigate the impact of climate change on urban drainage systems, including the flooding and pollution (suspended solids). The model successfully captured the variation of overflow flooding and transport of pollutants. Thirdly, we introduced four mitigation measures of GI and simulated their effectiveness against climate change with different extreme rainfall events. The results indicate that future climate change will increase the risk of overflow flooding and more pollutants diffuse on urban surfaces. The GI is an effective method to mitigate its impact, but the performance decreases with rainfall intensity. The effect of increased rainfall is consistent for different GI. PP is most effective in relieving the pressure of extreme rainfall for total flood,  peak flow reduction, and pollutant removal. Although GR performs reasonably well in flood control, it is the least effective in pollutant control. It can be seen that more research is needed in the implementation and optimization of GI.

This study presents results from magnetic field line conjunctions between the medium-Earth orbiting Demonstration and Science Experiments (DSX) satellite and the low-Earth orbiting VLF Propagation Mapper (VPM) satellite. DSX transmitted at very low frequencies (VLF) towards VPM, which was equipped with a single-axis dipole electric field antenna, when the two spacecraft passed near the same magnetic field line. VPM did not observe DSX signals in any of the 27 attempted conjunction experiments; the goal of this study, therefore, is to explain why DSX signals were not received. Explanations include i) the predicted power at LEO from DSX transmissions was too low for VPM to observe; ii) VPM’s trajectory missed the “spot” of highest intensity due to the focused ray paths reaching LEO; or iii) rays mirrored before reaching VPM. Different combinations of these explanations are found. We present ray-tracing analysis for each conjunction event to predict the distribution of power and wave normal angles in the vicinity of VPM at LEO altitudes. We find that, for low-frequency (below 4kHz) transmissions, nearly all rays mirror before reaching LEO, resulting in low amplitudes at LEO. For mid- and high-frequency transmissions (~8kHz and 28kHz respectively), the power at LEO is above the noise threshold of the VPM receiver (between 0.5µV/m and 1µV/m). We conclude that the antenna efficiency and plasmasphere model are critical in determining the predicted power at LEO, and are also the two most significant sources of uncertainty that could explain the apparent discrepancy between predicted amplitudes and VPM observations.

Isopycnal mixing of tracers is important for ocean dynamics and biogeochemistry. Previous studies have primarily focused on the horizontal structure of mixing, but what controls its vertical structure is still unclear. This study investigates the vertical structure of the isopycnal tracer diffusivity diagnosed by a multiple-tracer inversion method in an idealized basin circulation model. The first two eigenvalues of the symmetric part of the 3D diffusivity tensor are approximately tangent to isopycnal surfaces. The isopycnal mixing is anisotropic, with principal directions of the large and small diffusivities generally oriented along and across the mean flow direction. The cross-stream diffusivity can be reconstructed from the along-stream diffusivity after accounting for suppression of mixing by the mean flow. In the circumpolar channel and the upper ocean in the gyres, the vertical structure of the along-stream diffusivity follows that of the rms eddy velocity times a depth-independent local energy-containing scale estimated from the sea surface height. The diffusivity in the deep ocean in the gyres instead follows the profile of the eddy kinetic energy times a depth-independent mixing time scale. The transition between the two mixing regimes is attributed to the dominance of nonlinear interactions and linear waves in the upper and deep ocean, respectively, distinguished by a nonlinearity parameter. A formula is proposed that accounts for both regimes and captures the vertical variation of diffusivities better than extant theories. These results inform efforts to parameterize the vertical structure of isopycnal mixing in coarse-resolution ocean models.

The Lightning Imaging Sensor (LIS) was launched to the International Space Station (ISS) in February 2017, detecting optical signatures of lightning with storm-scale horizontal resolution during both day and night. ISS LIS data are available beginning 1 March 2017. Millisecond timing allows detailed intercalibration and validation with other spaceborne and ground-based lightning sensors. Initial comparisons with those other sensors suggest flash detection efficiency around 60% (diurnal variability of 51-75%), false alarm rate under 5%, timing accuracy better than 2 ms, and horizontal location accuracy around 3 km. The spatially uniform flash detection capability of ISS LIS from low-Earth orbit allows assessment of spatially varying flash detection efficiency for other sensors and networks, particularly the Geostationary Lightning Mappers. ISS LIS provides research data suitable for investigations of lightning physics, climatology, thunderstorm processes, and atmospheric composition, as well as realtime lightning data for operational forecasting and aviation weather interests. ISS LIS enables enrichment and extension of the long-term global climatology of lightning from space, and is the only recent platform that extends the global record to higher latitudes (± 55). The global spatial distribution of lightning from ISS LIS is broadly similar to previous datasets, with globally averaged seasonal/annual flash rates about 5-10% lower. This difference is likely due to reduced flash detection efficiency that will be mitigated in future ISS LIS data processing, as well as the shorter ISS LIS period of record. The expected land/ocean contrast in the diurnal variability of global lightning is also observed.

The state and evolution of the North Pacific jet (NPJ) stream strongly influences the character of the downstream synoptic-scale flow pattern over North America. This study employs data from nine models within the Subseasonal-to-Seasonal Reforecast Database hosted by the European Centre for Medium-Range Weather Forecasts to examine the subseasonal (2 weeks–1 month) predictability of the NPJ through the lens of an NPJ phase diagram. The NPJ phase diagram provides a visual representation of the state and evolution of the NPJ with respect to the two leading modes of NPJ variability. The first mode of NPJ variability corresponds to a zonal extension or retraction of the climatological jet-exit region, whereas the second mode corresponds to a poleward or equatorward shift of the climatological jet-exit region. The analysis reveals that ensemble forecasts of the prevailing NPJ regime, as determined from the NPJ phase diagram, are skillful into week 3 of the forecast period. Forecasts initialized during a jet retraction, or verifying during a jet retraction and equatorward shift, generally feature the largest errors during the forecast period. Examination of the worst-performing 21-day forecasts from each model demonstrates that the worst-performing forecasts are uniformly associated with development, maintenance, and decay of upper-tropospheric ridges over the high-latitude North Pacific. These results demonstrate that bias-corrected NPJ phase diagram forecasts have the potential to identify periods that may exhibit enhanced forecast skill at subseasonal lead times based on the anticipated NPJ evolution.

Hydrologic connectivity controls the lateral exchange of water, solids, and solutes between rivers and floodplains, and is critical to ecosystem function, water treatment, flood attenuation, and geomorphic processes. This connectivity has been well-studied, typically through the lens of fluvial flooding. In regions prone to heavy rainfall, the timing and magnitude of lateral exchange may be altered by pluvial flooding on the floodplain. We collected measurements of flow depth and velocity in the Trinity River floodplain in coastal Texas (USA) during Tropical Storm Imelda (2019), which produced up to 75 cm of rainfall locally. We developed a two-dimensional hydrodynamic model at high resolution for a section of the Trinity River floodplain inspired by the compound flooding of Imelda. We then employed Lagrangian particle routing to quantify how residence times and particle velocities changed as flooding shifted from rainfall-driven to river-driven. Our results show that heavy rainfall initiated lateral exchange before river discharge reached flood levels. The presence of rainwater also reduced floodplain storage, causing river water to be confined to a narrow corridor on the floodplain, while rainwater residence times were increased from the effect of high river flow. Finally, we analyzed the role of floodplain channels in facilitating hydrologic connectivity by varying model resolution in the floodplain. While the resolution of floodplain channels was important locally, it did not affect as much the overall floodplain behavior. This study demonstrates the complexity of floodplain hydrodynamics under conditions of heavy rainfall, with implications for sediment deposition and nutrient removal during floods.

The 2016 Amatrice-Norcia seismic sequence in central Italy activated a system of normal faults in the central Apennines and ruptured the surface along the Monte Vettore normal fault. Due to the complex rupture behavior, including antithetic faults and the proposed reactivation of an old thrust front, the Amatrice-Norcia seismic sequence offers a unique opportunity to study the relationship between fault complexity, surface ruptures, and earthquake source properties. Here, we focus on the first two months of the Amatrice-Norcia seismic sequence, including the 30 October 2016 Mw 6.5 mainshock near Norcia and more than 25000 aftershocks. Using continuous waveform data from 94 seismic stations with epicentral distances of up to ~100 km, we estimate source parameters of all cataloged earthquakes that exceed specific quality control criteria in a time period ranging from 24 October – 29 November 2016. Displacement spectral corner frequency and seismic moment values are fit using individual earthquake spectra, and corner frequency estimates are refined using spectral ratios. Constrained spectral parameters then provide input for static stress drop estimates based on a circular crack model. Preliminary results suggest the majority of earthquakes have static stress drop values between 1 and 10 MPa and self-similar scaling. Due to the high quality and quantity of available data, including precise earthquake locations, manually reviewed phase arrivals, and detailed mapping of surface ruptures, the Amatrice-Norcia earthquake sequence represents an opportunity to link earthquake source parameters to geological structures and surface rupture complexity. Preliminary results show correlations between high stress drop values and areas with increasing fault complexity, such as fault intersections at depth (inferred from precise earthquake hypocenters) or the mapped tip of the Monte Vettore normal fault, relative to other fault patches with fewer intersections or mapped surface trace terminations. Future work will examine whether the correlation of stress drop and fault complexity holds using refined stress drop estimates obtained using spectral ratio approaches.