The well recognized constraint of non-linear and non-Gaussian distribution of rainfall observation limits its assimilation in the high-dimensional numerical weather prediction (NWP) model. In this study, rain-gauges’ observed rainfall from Indian Meteorological Department (IMD) over Indian landmass is assimilated in the Weather Research and Forecasting (WRF) model using particle filter. In the framework of imperfect weather model, particles (or ensembles) for rainfall predictions are created with various combinations of model physics (viz. cumulus parameterization, micro-physics, planetary boundary layer schemes). With the help of IMD observed rainfall, weights are provided to various particles using multiple hypotheses, and this is the step in which IMD rainfall observations are used for assimilation. Further, a resampling step is performed to generate new particle from high weight particle using stochastic kinetic-energy backscatter scheme (SKEBS) method in which dynamical variables are perturbed into the model physics. Results based on rainfall verification scores suggest that assimilation of the rain-gauges observed rainfall using particle filter improved prediction of rainfall over CNT runs (unweighted particle; without assimilation). Moreover, surface and vertical profile of temperature, water vapour mixing ratio (WVMR) and wind speed are also improved in 24 h forecasts.

We investigate the 3-D lithospheric thermal and rheological structures beneath Northeast China using detailed P- and S-wave velocity models following mineral physics as well as geothermal methods. Small-scale temperature changes and thermal lithosphere thickness variations between different tectonic blocks are revealed. Our results show that strong lateral heterogeneities exist in the lithospheric thermal structure and rheological structure on both sides of the North-South Gravity Lineament (NSGL). The Changbai volcanic area and the central part of the Songliao Basin in the eastern side of the NSGL exhibit higher temperatures, thinner thermal lithosphere and lower rheological strength, which are closely associated with the western Pacific plate subduction under the Eurasian continent, resulting in upwelling of wet and hot asthenospheric material above the stagnant Pacific slab in the mantle transition zone. The thermo-chemical erosion of the upwelling asthenospheric material may induce delamination of partial lithosphere under the Songliao Basin. In addition, the Songliao Basin edge is characterized by lower temperature, thicker thermal lithosphere and higher rheological strength, which may indicate a relatively stable lithosphere. The Halaha and Abaga volcanic areas in the western side of the NSGL exhibit higher temperature, thinner thermal lithosphere and lower rheological strength, which could be caused by small-scale upwelling of hot asthenospheric material associated with delamination of partial lithosphere beneath the Songliao Basin.

Using a magnetohydrodynamic simulation of magnetotail reconnection, flow bursts and dipolarization we further investigate the current diversion and energy flow and conversion associated with the substorm current wedge (SCW) or smaller scale wedgelets. Current diversion into both Region 1 (R1) and Region 2 (R2) sense systems is found to happen inside (that is, closer to the center of the flow burst) and equatorward of the R1 and R2 type field-aligned currents. In contrast to earlier investigations the current diversion takes place in dipolarized fields extending all the way toward the equatorial plane. An additional FAC system with the signature of R0 (same sense as R2) is found at higher latitudes in taillike fields. The diversion into this system takes place in layers equatorward of the R0 currents, but outside the equatorial plane. Whereas the diversion into R1 and R2 systems is pressure gradient dominated, the diversion into the R0 system is inertia dominated and may persist only during flow burst activity. While azimuthally diverging flows near the dipole contribute to the build-up of R1 and R2 systems, converging flows at larger distance contribute to the build-up of R0 and R1 systems. In contrast to the current diversion regions inside the current wedge, generator regions are found on the outside of the wedge, similar to earlier results. Within the tail domain covered, these regions are overpowered by load regions, such that additional generator regions must be expected closer to Earth, not covered by the present simulation.

Consecutive Rainfall Events (CREs) are important triggers of geological hazards like landslide downhill and mudslide in the Three Gorges Reservoir area (TGR), China. These hazards are not only potential risks for the effective storage capacity of the reservoir but also threats of the safety of the reservoir’s Great Dam. The future changes of CREs’ occurrence and intensity are analyzed by using the projection experiments from twenty models attending the Coupled Model Inter-comparison Project phase 5 (CMIP5) under three different representative concentration pathways (RCP2.6, RCP4.5 and RCP8.5). Spring and fall are focused on, during which CREs are most frequent. Considering a common overestimate of rainy days number in the state-of-the-art models, a new approach is developed to define CREs based on the percentile of rainfall distribution in observations. The approach yields a similar CREs climatology in models to that in observations, and thus is used to identify CREs in models. The results based on multiple model ensemble (MME) and model spread comparison suggest a significant increase in spring and an overall decrease in fall in CREs’ occurrence under all three scenarios. As for the intensity, it is projected to intensify both in spring and fall. Particularly, the higher the emission scenario, the greater the spring accumulated rainfall amount during a single CRE. These results imply an increasing risk of geological hazards in the TGR in the future.

Lakes and reservoirs are important components of freshwater. The expansion and shrinkage of lakes/reservoirs may alter meteorological characteristics and the underlying surface conditions, which would further affect energy and water vapor fluxes in the surrounding area. In this study, the expansion and shrinkage of the Guanting Reservoir during 2013-2017 was analyzed using remote sensing data. Data collected from the Huailai Remote Sensing Experiment Station were used to analyze the energy and water vapor fluxes. The results showed the annual expansion of the Guanting Reservoir from 2013 to 2017, and a seasonal variation characterized by expansion in spring, shrinkage in summer and autumn, and expansion again in winter was exhibited. Meanwhile, the evapotranspiration (ET) in the surrounding area also increased annually. In the growing season, the seasonal shrinkage of the reservoir indirectly affected ET through net radiation, deep soil moisture and vegetation growth conditions, while in the non-growing season, the seasonal expansion directly increased ET by increasing the proportion of water bodies in the source area and increased net radiation and surface soil moisture. In addition, with the reservoir expanding year by year, the difference in ET between the closer site and further site from the reservoir increased obviously, especially in the non-growing season during the seasonal expansion of the reservoir. The results help with the ecosystem restoration and sustainable development of lakes/reservoirs in arid and semiarid areas.

Temporally variable environmental microseismicity and narrowband signals are both demonstrated to reduce the detectability of small seismic events. We investigate the influence of winter wind events on detection thresholds for a 3-sensor seismic network at the terminus of Taylor Glacier, Antarctica. As wind speeds increase, we observe higher spectral amplitudes across the frequency spectrum; however, some frequency bands are preferentially excited. Surprisingly, these spectral peaks shift frequencies through time. To determine detection thresholds, we implement a waveform injection routine wherein we add scaled waveforms to the datastream, and track changes in the size of the smallest scaled event that we can reliably detect. We thereby demonstrate a capability to quantify the size of the smallest detectable event in temporally variable signal environments. Lastly, we propose a method to forecast our ability to detect sources of a threshold size in measured noise conditions.

Trace elements (TE) are tracers of multiple biotic and abiotic processes in the ocean and some of them are essential for marine life. Vertical export by particles is a major removal process of a large fraction of TE from the surface ocean. However, the seasonal export dynamics and its controlling factors, critical for the understanding of the internal TE cycling, remain poorly constrained. Here, we report and discuss the seasonal export of 15 TE in sinking particles collected by a sediment trap deployed in a highly productive region of the Southern Ocean. Basalt material was the main carrier phase for the export flux of 9 TE, and its dynamic was characterised by a strong decrease over time. TE export driven by biological carriers such as diatom spores and vegetative cells added pulsed seasonal dynamics to the lithogenic signal, while the contribution of fecal pellets was less variable over the season. For each TE, we were able to decipher the biological carrier phases that represent the most dominant export pathway. We discuss this partitioning with regards to the known metabolic functions of the different trace metals or TE of biological interest.

The propagation characteristics of near-inertial waves (NIWs) and how mesoscale and submesoscale processes affect the waves’ vertical penetration (i.e., the chimney effect) are investigated using observations from a mooring array located in the northeast Atlantic. The year-long observations show that near-inertial motions are mainly generated by local wind forcing and that they radiate predominantly downward following several strong wind events. Once below the mixed layer, NIWs preferentially propagate equatorward primarily in the form of low modes. High-mode NIWs, however, are most likely dissipated locally near the base of the mixed layer. Enhanced near-inertial kinetic energy and vertical shear are found only in mesoscale anticyclones with Rossby number of O(0.1). By contrast, submesoscale motions with order one Rossby number have little effect on the trapping and vertical penetration of NIWs, due to their smaller horizontal scales and confined vertical extent compared to mesoscale eddies.

Tesserae are some of the most ancient geologic units on Venus and, as such, record the longest history of surface evolution. Their composition and formation mechanisms are still debated, and the degree of variation in their surface properties is not fully characterized. Here we use Magellan synthetic aperture radar data to calculate backscatter coefficient variations throughout 22 tesserae distributed latitudinally and longitudinally across Venus. Statistically significant variations are identified between tesserae, which can be divided into groups smoother (64%) or rougher (36%) than a tessera average. The backscatter coefficient variations of at least one-third of smooth tesserae are controlled by post-emplacement processes, specifically the deposition of fine-grained impact ejecta. It will be critical for upcoming missions to consider both original morphology and post-emplacement processes when evaluating the rock types and diversity of tesserae.

Many waterbodies around the world are adversely impacted by harmful algal blooms (HABs). One primary driver of these blooms is often high concentrations of anthropogenic phosphorus loading. The phosphorus mitigation plans require accurate information on nutrient sources and transport, to and through water bodies, including the stream network. Diffuse sources, are particularly difficult to quantify due to the cost of in situ monitoring, and is often supplemented using various water quality models. SWAT, a comprehensive watershed-scale model, is widely used to assess and improve downstream water quality using QUAL2E equations. EPA developed QUAL2E can model phytoplankton growth but has a limited capacity to model benthic algae. Although SWAT requires a lesser number of parameters while simulating water quality outputs, unlike, HSPF, INCA, SPARROW, WASP, and MIKE-SHE, the water quality algorithm within SWAT needs modifications for simulating phosphorus legacy within the waterbodies. This study reviews the existing water quality models to improve the water quality algorithm within SWAT. Most of the water quality models can simulate processes, including the proliferation of fixed and floating algal biomass and phosphorus cycling (QUAL2E/K, WASP, HSPF). Some water quality models are better in simulating the time-dependent factors, such as light attenuation, form and concentration of nutrients, and water temperature (HSPF, INCA). There are a few water quality algorithms that can simulate both horizontal stream flow and shallow flow (SHETRAN, INCA). Both horizontal and shallow flow takes into account the anisotropy and variable biogeochemistry impacts on the turbulence of water, thus, the water quality. Some water quality models simulate the non-linear relationship between nutrient concentration and discharge timing and magnitude (SPARROW). There are some commercialized models like MIKE-SHE that simulate reasonably good results, but the water quality algorithm/equation/process is not publically available. Our review of the existing water quality models will help in identifying, modifying, and implementing the SWAT source code revisions required to improve and mitigate water quality degradation from a finer spatial scale, including small ditches and streams, to the large-scaled watershed over time.

The evolution of mesoscale eddies is crucial for understanding the ocean energy cascade. Using global reanalysis sea surface velocity data and mesoscale eddy trajectory product tracked by satellite altimeters, this study aims to reveal the coherence of eddy kinetic energy (EKE) variation to the low-frequency ageostrophic energy during the eddy life span. The variation of EKE through the eddy life is highly coherent to that of the 7d low-passed ageostrophic kinetic energy with a correlation coefficient of -0.95. The low-frequency ageostrophic motions supply 43% of the EKE variation at the growing stage of mesoscale eddies, and absorb 45% at the decaying stage, comparing to 7% and 9% of contributions for submesoscale motions. The evolution rate of the EKE during the eddy life span is consistent with the barotropic conversion rate of the low-frequency motions, further confirming the dominant role of the low-frequency motions in the eddy growing and decaying.

The fragile balance of endorheic lakes in highly managed semi-arid basins with transboundary water issues has been altered by the intertwined effects of global warming and long-term water mismanagement to support agricultural and industrial demand. The alarming rate of global endorheic lakes’ depletion in recent decades necessitates formulating mitigation strategies for ecosystem restoration. However, detecting and quantifying the relative contribution of causal factors (climate variability and anthropogenic stressors) is challenging. This study developed a diagnostic multivariate framework to identify major hydrologic drivers of lake depletion in a highly managed endorheic basin with a complex water distribution system. The framework integrates the Soil and Water Assessment Tool (SWAT) simulations with time-series decomposition and clustering methods to identify the major drivers of change. This diagnostic framework was applied to the Salton Sea Transboundary Basin (SSTB), the host of the world’s most impaired inland lake. The results showed signs of depletion across the SSTB since late 1998 with no significant changes in climate conditions. The time-series data mining of the SSTB water balance components indicated that decreases in lake tributary inflows (-16.4 Mm3 yr-2) in response to decline in Colorado River inflows, associated with state water transfer agreements, are causing the Salton Sea to shrink, not changes in the irrigation operation as commonly believed. The developed multivariate detection and attribution framework is useful for identifying major drivers of change in coupled natural-human systems.

Explosive volcanic eruptions radiate seismic waves as a consequence of pressure and shear traction changes within the conduit/chamber system. Kinematic source inversions utilize these waves to determine equivalent seismic force and moment tensor sources, but relation to eruptive processes is often ambiguous and nonunique. In this work, we provide an alternative, forward modeling approach to calculate moment tensor and force equivalents of a model of eruptive conduit flow and chamber depressurization. We explain the equivalence of two seismic force descriptions, the first in terms of traction changes on the conduit/chamber walls, and the second in terms of changes in magma momentum, weight, and momentum transfer to the atmosphere. Eruption onset is marked by a downward seismic force, associated with loss of restraining shear tractions from fragmentation. This is followed by a much larger upward seismic force from upward drag of ascending magma and reduction of magma weight remaining in the conduit/chamber system. The static force is upward, arising from weight reduction. We calculate synthetic seismograms to examine the expression of eruptive processes at different receiver distances. Filtering these synthetics to the frequency band typically resolved by broadband seismometers produces waveforms similar to very long period (VLP) seismic events observed in strombolian and vulcanian eruptions. However, filtering heavily distorts waveforms, accentuating processes in early, unsteady parts of eruptions and eliminating information about longer time scale depressurization and weight changes that dominate unfiltered seismograms. The workflow we have introduced can be utilized to directly and quantitatively connect eruption models with seismic observations.

The Western Ghats region of India and its neighbouring areas are highly susceptible to rainfall-triggered landslides due to the regional geography, extreme rainfall, and anthropogenic intervention like excavation for construction activities etc. Every year in monsoon season, Maharashtra faces a massive loss of properties and life due to rainfall triggered landslides. In the monsoon of 2021, Pune and Konkan divisions in Maharashtra have witnessed severe rainfalls that triggered many landslides, which cause nearly 200 deaths and massive loss of properties. Thus, it is necessary to model an accurate early prediction system to mitigate such natural hazards. In this study, we have analyzed the efficiency of the transient rainfall infiltration and grid-based regional slope-stability (TRIGRS) model in predicting the location and timing of landslides. The case study selected for this analysis is a destructive rainfall-induced landslide triggered at Malin near Mumbai in July 2014, which resulted in 160 deaths, including the burial of an entire village under the debris. The TRIGRS is a widely applied model to analyze the effect of rainfall on pore water pressure fluctuations and related variation in factors of safety. It uses an infinite slope model to estimate the change in the factor of safety for every pixel. The model input data requires topographic properties (slope and elevation), soil layer thickness, material properties, initial water-table depth, and rainfall characteristics (intensity and duration). The preliminary analysis of rainfall data indicated that the study area was affected by 3-days intense rainfall prior to the landslide event. The TRIGRS model results show that the factor of safety of the Malin slope decreases with the increasing rainfall intensity and duration. The present study suggests that this model can also be used at large scale areas to prepare an active early warning system for landslide events. Keywords: Landslide; Rainfall; TRIGRS; Natural hazard; Maharastra

Data science refers to the set of tools, technologies, and teams that alter the paradigm by which data are collected, managed and analyzed. Data science is, therefore, decidedly broader than ‘machine learning,’ and includes instead the full data lifecycle. Never has the need for effective data science innovation been greater than now when at every turn data-driven discovery is both burdened and invigorated by the growth of data volumes, varieties, veracities, and velocities. This growing scale of science requires dramatic shifts in collaborative research, requiring projects to climb the gradations of collaboration from unidisciplinary, to multi-, inter-, and transdisciplinary (Figure 1, [Hall et al., 2014; NRC, 2015]), and perhaps even to an entirely new level that defies any traditional boundary, or antidisciplinary (https://joi.ito.com/weblog/2014/10/02/antidisciplinar.html). We will discuss the cutting-edge efforts advancing collaborative research in Space Physics and Aeronomy, highlight progress, and synthesize the lessons to provide a vision for future innovation in data science for Heliophysics. We will specifically focus on three trail-blazing initiatives: 1) the NASA Frontier Development Laboratory; 2) the HelioAnalytics group at the Goddard Space Flight Center in cooperation with the NASA Jet Propulsion Laboratory’s Data Science Working Group; and 3) an International Space Sciences Institute project. References: Hall, K.L., Stipelman, B., Vogel, A.L., Huang, G., and Dathe, M. (2014). Enhancing the Ef- fectiveness of Team-based Research: A Dynamic Multi-level Systems Map of Integral Factors in Team Science. Presented at the Fifth Annual Science of Team Science Confer- ence, August, Austin, TX. NRC (National Research Council) (2015). Enhancing the Effectiveness of Team Science. Washington, DC: The National Academies Press. https://doi.org/10.17226/19007.

The magnetosphere, ionosphere and thermosphere (MIT) act as a coherently integrated system (geospace), driven in part by solar influences and characterized by variability and complexity. Among the most important and yet uncertain aspects of the geospace system is energy and momentum coupling between regions, which is, in part, accomplished by the transfer of charged particles from the magnetosphere to the ionosphere in a process known as particle precipitation, and in the opposite direction by ion outflow. Both processes are inherently multiscale and manifest the variabilities and complexities of the geospace system. Despite the importance of the transfer of particles, existing models are increasingly ill-equipped to provide the specification necessary for the growing demand for geospace now- and forecasts. Due to recent trends in the availability of data, we now face an exciting opportunity to progress particle transfer in geospace through the intersection of traditional approaches and state-of-the-art data-driven sciences. We reveal novel particle transfer models utilizing machine learning (ML), present results from the models, and provide an evaluation of their capabilities including comparisons with observations and the current ’state-of-the-art’ models (e.g., OVATION Prime for particle precipitation and the Gamera-Ionosphere Polar Wind Model for ion outflow). We detail the data wrangling required to utilize the available geospace observations to make progress on the long-standing challenge of particle transfer and place specific emphasis on the discovery possible when ML models are appropriate and robustly interrogated in the context of physical understanding. Our presentation helps illustrate the trends in the application of data science in space science.

Magmatic structures are well-preserved in a 201.5 Ma diabase sill (PA, USA, equivalent to the Palisades sill) formed as part of the Central Atlantic Magmatic Province during rifting of Pangea. The sill was emplaced at ~6 km depth and tilted ~20° NNW by post-magmatic fault movement. Detailed mush structures are exposed in a dimension stone quarry with walls cut parallel and perpendicular to the strike of the sill. Light gray, plagioclase-rich layers (PLR) a few mm thick contain up to 75% modal plag and are underlain by more pyroxene-rich layers with larger orthopyx antecrysts up to 1 mm length. PLR are sub-parallel to sill margins, have dm-m lateral dimensions, and spaced 0.33 m apart on average. Magma replenishments < 1m thick cross-cut plag-pyx layers at low angles and have basal load-cast-like structures. Since mafic replenishments have PLR at their tops and similar thickness to PLR spacing, we interpret all PLR as having formed by emplacement of small-volume magma pulses bearing ~30% larger pyx and smaller plag antecrysts. This model is similar to Petford and Mirhadizadeh (R Soc Open Sci, 2017) for the Basement sill, Antarctica. Upward migration of mafic melts in pipe-like channels (cm to dm wide) disrupted plag-pyx layers to form dm-scale graben-like and slump-like structures that resemble sediment liquefaction. Channelized flow late in sill development may have been enhanced by seismicity (Davis et al., JVGR, 2007). Diabase micro-structures are similar to published experimental results and numerical simulations of flow and shear-thinning in particle-rich slurries (e.g., Cimarelli et al., G3, 2011; Ishibashi, JVGR, 2009; Deubelbeiss et al., G3, 2011). These include layers such as the plag-pyx couplets and orientations of euhedral plag around pyx phenocrysts. Plag long-axis orientations and tiling indicators in the PLR have strike-parallel and strike-normal components in vertical and plan views consistent with flow alignment in the plane perpendicular to the stress gradient. Plag chemical zoning patterns, limited deformation, and long-axis orientations parallel to inclined layer margins also indicate magmatic flow rather than compaction. Mineral x-ray maps are used to derive initial crystal fraction and aspect ratios for modeling relative viscosity and explore compositional aspects of layer development.

Laboratory reanalysis of paleomagnetic samples from two sets of superposed ~ 4.5 m.y. old lava flows (N=64) collected on Kauai (Hawaii) in the 1960s, when combined with more recently published results from two additional flow sequences (N=59) on the island, yields a mean paleomagnetic pole that differs significantly from the spin axis. The new laboratory work was motivated by the fact the 60% of the published flow mean directions on the old collection derived from measurements of natural remanent magnetization without any demagnetization treatment. In our reanalysis, we subjected all specimens to stepwise alternating field (AF) demagnetization (13 steps; 90 mT peak AF) and modern line-fit analysis. As has been found in many restudies of this sort on young, well-behaved basaltic lavas, modern demagnetization technique produced little change in the flow-mean directions (an average change of just over 2° in this case.) To minimize the bias introduced when rapidly erupted flow sequences sample a single geomagnetic field direction, we thinned the combined data by grouping superposed flows with similar paleomagnetic directions. The procedure requires choosing a minimum angle between directions that will be considered independent samples of the ancient geomagnetic field. Previous studies have commonly used a 6° threshold. We found, however, that much larger values (10° to 16°) were needed to eliminate significant serial correlation (measured in several ways) in the thinned directional sequence. Our conclusion is that the 123 lava flows in this study provide only 33 independent estimate of the ancient field direction. The mean normal polarity paleomagnetic pole resulting from the analysis (Lon=076.8, Lat=82.2, N=13) is almost perfectly antiparallel (179°) to the mean reverse polarity pole (Lon=258.4, Lat=-83.2, N=20). The grand mean of 33 normal and reverse polarity data is Lon=077.3 Lat=82.8 k=31.8 α95=4.5°. The VGP dispersion (without correction for within-site dispersion, of order 0.5° for these very well-behaved paleomagnetic recorders) is 14.3° about the mean pole and 15.9° about the spin axis, comparable to that found in other analyses of Hawaiian paleomagnetic data.