We investigate electron whistler wave activity in the flux pile-up region of an asymmetric reconnection event at the magnetopause. The ~140Hz waves are right-hand polarized with a wave normal angle of ~20 degrees and track the magnetic field strength, consistent with electron whistler waves. Poynting flux direction indicates that the waves were generated at the reconnection site. The waves modulated the flux of 500eV electrons propagating parallel and anti-parallel to the magnetic field, as observed by EDI. Only two of four MMS spacecraft observe similar wave activity, suggesting that the waves are isolated within a narrow flux tube. While it is not possible to use the wave telescope technique, current density produced by 500eV electrons provides a means of estimating the parallel wave vector, k, from a single spacecraft. In addition, we fit the FPI electron parallel energy distribution with a kappa function then use Liouville mapping with 500eV EDI electrons to determine the parallel wave potential, 𝝓, and electric field, E. Combining this with the wave normal angle and Poynting flux direction provides an estimate for the perpendicular components of k and E.

The concept of an Interstellar Probe (ISP) offers an intriguing combination of scientific break-throughs in several disciplines. These include a global view of our heliosphere, unperturbed sampling of the interstellar medium, discoveries of Kuiper Belt Objects, and many others. The current mission concept of the ISP aims at reaching a distance of 1000 au away from the Sun within this century, far beyond the heliopause at roughly 100-200 au. In this presentation, we investigate basic requirements for an Energetic Neutral Atom (ENA) instrument onboard the ISP for the energy range between 10 eV and 5 keV. An ENA is produced when a fast ion exchanges its charge with an ambient neutral atom. The resulting ENA leaves the source region on a straight trajectory, no longer influenced by electromagnetic fields. This allows an ENA camera to image the ion distribution of remote plasma regions. We calculate the energy spectrum of heliospheric ENAs an observer would see from a given vantage point inside or outside the heliopause. Since the global shape of the heliosphere is unknown yet, we use two analytical models to derive proton flowlines for two different heliospheric shapes: the Parker model [Parker 1961] modified with a termination shock and the analytical representation of a full MHD model [Röken et al. 2015, Kleimann et al. 2017]. The ENA intensity then is the line-of-sight integral of proton density times the local density of neutral hydrogen times the charge-exchange cross-section. We disregard any other neutral species inside the heliosphere and we only consider protons as source for ENAs. The proton populations included are the supersonic solar wind and pickup ions inside the termination shock and the shocked solar wind and pickup ions between termination shock and heliopause. The calculated ENA intensities are first compared to the globally distributed ENA flux measured by the Interstellar Boundary Explorer and Cassini in the inner solar system in the energy range from 10 eV to 55 keV. We then proceed to calculate the ENA intensity as seen by an observer at other positions near or beyond the heliopause. These predictions can serve as a rough guideline for the mission concept of ISP: which trajectory offers the most interesting view on the heliosphere in ENAs and which technical requirements should a low-energy ENA imager meet?

A direct comparison of hydrometeor types (HMT) from state-of-the-art hydrometeor classification schemes (HMC) with modelled hydrometeors (ICOL-LAM, operational weather predictions model of the German Weather Service) is challenging, e.g. due to different HMT definitions and numbers and difficulties to identify dominant types in mixtures of hydrometeors. A comparison of published HMCs even revealed significant differences between the membership functions used for the same hydrometeor types (Figure 1), emphasizing again the high uncertainty in scattering simulations for ice hydrometeors because of their complex geometries, dielectric properties, and largely unknown size and orientation distributions. The HMCs were applied to perturbed polarimetric variables observed by the X-band Radar in Bonn (BoXPol) to test their robustness against measurement errors and show that especially in the regions with solid precipitation misclassification in hydrometeor typing occurs often. Thus, a dual strategy to evaluate the hydrometeor type representation in ICON-LAM is presented: i) Classification after clustering of the data is assumed to reduce the sensitivity of the decision to the uncertainty of scattering simulations. First an agglomerative hierarchical clustering of the radar pixels based on their similarity in multi-dimensional polarimetric signatures is applied, and afterwards for each identified cluster a comparison of the distributions of polarimetric moments with scattering simulations or membership functions for different HMT is performed. ii) A direct comparison of multivariate simulated and observed distributions of polarimetric moments. These comparisons will be performed for different heights and/or space-time subsets, and for clusters with similar HMT in the model and the observations as identified with the advanced radar-based hydrometeor classification scheme. Results for a set of case studies observed with the polarimetric X-band radar composite in Bonn, Germany, will be presented.

Sediment fluxes at the estuary-sea interface modulate estuary morphologies and impact particle matter exchanges between marine and continental sources along the land-sea continuum. However, meteorological forcing (e.g., extreme events) and human activities (e.g., estuary deepening) drive pressures on estuary physical functioning, hence threatening estuarine habitats and their ecosystem services. There is an increasing societal need to better predict the potential trajectories of estuarine sediment fluxes resulting from natural and anthropogenic pressures. Nevertheless, it is difficult to derive generalizations from site-specific studies; thus, multi-site approaches appear necessary to move toward a global conceptualization of estuarine sediment transfers. This study explores 10-year numerical hindcasts of three contrasted macrotidal estuaries (Gironde, Loire, and Seine estuaries; France) to disentangle the relative contributions of hydrometeorological and morphological forcing on net sediment fluxes between estuaries and coastal seas. Our results highlight that intense wave events induce fine sediment (≤100 μm) export to the sea but coarser sediment (≥210 μm) import within the estuary. Remarkably, moderate to large river flows support mud import within the estuary. In addition, the Seine Estuary morphological changes due to human activities (i.e., estuary deepening and narrowing) increase fine sediment import within the estuary, shifting the estuary from an exporting to importing system. We propose a conceptualization of mud flux response to river flow and wave forcing, as well as anthropogenic pressures. It provides valuable insights into particle transfers along the land-sea continuum, contributing to a better understanding of estuarine ecosystem trajectories under global changes.

Cyclostratigraphy’s near 100% success rate in statistical cycle identification suggests confirmation bias; absence of cyclicity is not regarded as a possible outcome. Vaughan et al 2011 (VBS) showed that the usual methods of estimating confidence levels (CLs) admit numerous false cycle detections, but in subsequent debate it is asserted that the corrections recommended by VBS do not apply in cyclostratigraphy because they lead to rejection of the expected orbital periods. Is there a deeper problem? VBS particularly criticised universal failure to correct CLs for the unavoidably multiple nature of significance tests of power spectra. However, the multiple-test problem is compounded by assumptions of unlimited freedom to vary procedures to allow for properties of individual datasets. Statistical analysis in cyclostratigraphy operates in a large variable-space, both of target hypotheses (many orbital cycles and combinations thereof), and of procedures (many pre- and syn-processing options). Each of the many data-contingent choices made before and during spectral analysis and significance-testing implies the existence of alternatives: in effect, the reported analysis is only one of many. Given that multiple experiments will eventually achieve a positive result purely by chance, unadjusted significance thresholds will result in large numbers of spurious cycle identifications, a possible explanation for observed success rates. Additional multiplicity is implied by the practice of treating CLs as a guide, rather than as a definitive signal:noise discriminator; treating CLs as movable (or even optional) negates the concept that the particular dataset is just one realisation of many permitted by the noise model; without pre-selection of a CL the statistics are meaningless. Suggestions for practical improvements include: better hypothesis formulation (with attention to the prior probability of signal preservation in an unreliable recording medium); more care in discriminating between the exploratory (hypothesis-setting) and confirmatory (hypothesis-testing) modes of data analysis; advance definition of analytical protocols; and publication of all results whether positive or negative. Reference: Vaughan et al 2011: doi:10.1029/2011PA002195.

Brazil is one of the richest countries in water resources and is currently the second largest global supplier of food and agricultural products. Furthermore, more than 70% of Brazilian energy comes from hydropower. Therefore, to ensure water availability for future generations it is necessary to consider the Nexus thinking (water, food, energy, ecosystem service, and social aspects integrated) in the country. However, few studies have been developed considering the Nexus thinking in Brazil. Understanding the interconnected risks and vulnerability to these sectors under climatic change conditions is crucial for the development of sustainable resources management plans and for mitigating competition among them. Here, we assess the Food-Energy-Water Nexus considering climate and land cover and land use changes (LCLUC) scenarios in the São Francisco river basin. This basin is the third largest basin in Brazil and supplies water to approximately 14 million inhabitants, with the Metropolitan Region of Belo Horizonte being the most populous area. The São Francisco river has been used for water supply, irrigation, agriculture and transportation by waterways, but its preponderant use is for hydroelectric power generation. However, this basin has been suffering from LCLUC and drought that has plagued the region since 2012. In addition, part of the river flow has been diverted due to the transposition of the São Francisco river to supply water to the semi-arid region of Brazil. We will calibrate and evaluate the Soil and Water Assessment Tool (SWAT) using hydrometeorological data from 1972 to 2017. We will also use LCLUC scenarios from the OTIMIZAGRO model and regional climate change models (HadGEM2-ES and MIROC5, RCP 4.5 and 8.5). Then, we will compute the demands of water by different sectors and integrate water availability and demand to reach an optimal water use based on the Nexus thinking. Our results will provide decision-makers with information regarding the risks and trade-offs and will support water resources management decisions in order to allocate scarce water resources toward food or energy.

Understanding spatiotemporal patterns and trends of Indian Summer Monsoon extremes have always been an important task mostly because the impacts of extreme events have an enormous effect on agriculture, economy, life and eco-system. In general, findings from the exploration of extreme events with limited data will have high uncertainty, and it is important to investigate the trends with a high long-term dataset for improved understanding of extreme events. Further, the patterns and interactions become further unusual, unexpected and unpredictable, coupled with the existing challenges of global warming-induced climate change. Hence, the study was primarily prompted by these realizations and an implied aspiration to quantify spatiotemporal patterns and trends of Indian Summer Monsoon extremes. In the present study, Extreme rainfall is defined in three categories, namely severe (99th percentile), very high (95th percentile) and high (90th percentile) during the monsoon season in each year. The temporal changes in extreme rainfall have been detected over the period 1901–2019 using non-parametric Mann-Kendall and Sen’s slope estimator tests, respectively. The analysis revealed significantly intensifying rainfall magnitudes in Jammu and Kashmir, parts of Gujarat, Rajasthan and Peninsular India. The outcomes indicate that the magnitudes of extreme rainfall are likely to increase in future in these regions. On the contrary, Central and some regions of North-eastern India shows deceasing trends in the extreme rainfall significantly. Consistency of the trends, both temporally and spatially has been explored considering three time windows with an overlap of 10 years. The findings of the temporal evolution of extreme rainfall reveal spatiotemporal pattern is not consistent in different periods of the study. The results of the present study will provide an improved understanding of spatiotemporal patterns of the daily rainfall extremes during the Indian summer monsoon.

The Cauca Cluster of seismicity in western Colombia is the most extensive and persistent collection of intermediate (>60 km) depth earthquakes that cannot be easily associated with a subducting slab. The cluster stretches over an area of ~390 km by ~250 km from 2.5°N to 6°N and from 75.5°W to 77.75°W in a wedge-like zone of seismicity thickening from ~25 km in the west to ~125 km in the east. Prior tomographic results suggest that the lower edge of this feature is contained within the subducting Nazca plate’s oceanic lithosphere and corresponds to the Wadati-Benioff zone (WBZ) seen in most slabs, however this cannot explain the full thickness of the cluster. Large earthquakes within the cluster have been reported since at least the 1960s-70s and a great number of smaller events have been reported since the establishment of the Red Sismológica Nacional de Colombia (RSNC)’s regional catalog in 1993. Here, we relocate more than 6,700 events from the RSNC’s catalog beginning in 2010 and extending for ~10 years to dissect the Cauca Cluster’s structure and relationship to seismicity below 10 km depth. We find that while 40% of this seismicity can be associated with the Nazca plate’s WBZ, 35% occurs as features completely or partially within the overlying forearc mantle. These features include: 1) three focused centers of seismicity at ~90, ~100, and ~120 km depth extending ~30 km perpendicular to the WBZ; 2) a feature dipping at an angle shallower than the WBZ between 10 km and ~75 km depth; and 3) a diffuse zone of seismicity extending from the WBZ to ~10 km depth. None of these features extend beneath the active volcanic arc, and as such are limited to the stagnant corner of the mantle wedge. We find that these features are also limited to an area affected by the late Miocene accretion of the Panama-Choco terrane, the top of which we associate with the dipping feature between 10 and 75 km depth. This accretion has likely cooled the deep forearc to a point that allows for seismicity. The occurrence of these mantle wedge earthquakes in an immobile part of the subduction system suggests they are not produced directly by dehydration. They may instead be a result of fracture induced by the upward movement of fluids from the slab or of self-localizing thermal shear runaway triggered by reheating of the cooled forearc along its arc-ward edge.

Geodetic data provide an opportunity to improve our understanding of the processes and parameters controlling the dynamics of deformation during the earthquake cycle at subduction zones. However, the observations contain noise and are temporally and spatially sparse, whereas dynamical models are unequivocally imperfect. Also, the relative contributions from various drivers of surface deformation are poorly constrained by independent observations. Some drivers may be static or vary slowly in time (e.g., plate motion), whilst others vary significantly during the earthquake cycle (e.g., viscoelastic relaxation). Data assimilation combines prior estimates of dynamical models, with the likelihood of observations into posterior estimates of the state evolution and time-independent parameters of a physical process. We explore the usefulness of data assimilation by using a particle filter to estimate the (spatially variable) elastic thickness of the overriding plate and the extent of the locked zone. We assimilate vertical interseismic surface displacements into a 2D elastic flexural model. The particle filter uses a Monte Carlo approach to represent the state probability distribution by a finite number of realizations (“particles”). We use sequential importance resampling to preserve particles statistically close to the observations and duplicate and perturb them. Synthetic experiments demonstrate that the particle filter effectively estimates 1D elastic thickness from synthetic observations. However, elastic thickness estimates for models with a landward increase in plate thickness show larger uncertainty near the coast as the sensitivity of surface displacements reduces with increasing plate thickness. Interestingly, the effectiveness of the elastic thickness estimation is highly sensitive to network aperture, including GPS/A. Assimilation of interseismic vertical velocities prior to the 2011 Tohoku-Oki earthquake yields estimates of upper plate thickness that agree with previous studies. However, results of the locked zone extent are not as expected, which could be due to missing physics in the relatively conceptual model. These results demonstrate the potential of the particle filter to better understand the geodynamic process parameters of the earthquake cycle at subduction zones.

Studying of solar ionizing environment for the interstellar plasma inside the heliosphere is an unavoidable aspect of the interpretation of the full solar cycle of IBEX observations. We present a recent revision of the observation-based model of the ionization rates inside the heliosphere discussed by Sokół et al. 2020 (ApJ 897:179). The solar wind (SW) and the extreme ultraviolet (EUV) radiation affect fluxes of interstellar atoms inside the heliosphere both in time and in space. We present a Sun–Heliosphere Observation-based Ionization Rates (SHOIR) model based on the SW and EUV data available in solar cycle 24. We revised the in-ecliptic variation of the SW parameters, the latitudinal structure of the SW speed and density, and the photoionization rates. The revision most affects the SW out of the ecliptic plane during solar maximum and the estimate of the photoionization rates, the latter because of a change of the reference data. The changes are not constant and vary in time and in latitude. Our study shows that the polar SW is slower and denser during the solar maximum of solar cycle 24, and that the current estimates of the total ionization rates are higher than the previous ones for H, O, and Ne, and lower for He. The changes for the in-ecliptic total ionization rates are less than 10% for H and He, up to 20% for O, and up to 35% for Ne compared to the previous estimates.

River meandering is the natural process that many lowland rivers undergo as a consequence of the alternation of bank erosion and accretion, which leads to the typical shape of the so-called meandering rivers. During the last decades, numerous modelling studies have been developed to reproduce their planform dynamics and to predict their future evolution. Most of these modelling approaches are physics-based, meaning that they solve the mathematical equations of shallow water open channel flow and fluvial sediment transport. Other types of modelling are very rare. Recent advances in artificial intelligence have led to promising results in many fields of science but their potential seems to have been so far rather unexplored in the prediction of meandering rivers morphodynamics. In this study, we have developed machine learning (hereinafter ML) models to compute the meander lateral migration rate based on training dataset: once the model has been trained with known migration rates and curvature values at two consecutive time steps, it is used to predict migration rates at the following time step. To this aim, the train and test dataset is coming from the outputs of a semi-analytical meander morphodynamic model which provides simulated evolving meandering planforms (described through the spatial curvature distribution) and migration rates computed through the excess near bank velocity. Such migration has been considered as the “Target” in the present study. The results for different models such as linear regression, feedforward neural network, SVM, and XGBoost were compared. It indicates that the “XGBoost” model with approximately 80 percent of accuracy in the prediction of the next time step, has the best result among them. This is just an opening chapter for the usage of ML in morphodynamics of meandering rivers and with advanced methods, there will be promising results ahead.

Compound flooding, characterized by the co-occurrence of multiple drivers is a cause of concern in many world river basins. High river flows accompanied by high rain events are responsible for severe flooding events. Many studies in the recent past have analysed rain and river-flow dominated compound floods. In this study, we assessed the rain and river-flow induced compound flooding scenarios in a large tropical river basin, the Mahanadi River basin, located in eastern India. Since, many high floods have occurred in the past decade in the Mahanadi River basin, we analysed how the historical flood (in the year 2000) will unfold in a projected climate change scenario (in the year 2080) under RCP8.5. We used the bias-corrected hydro-meteorological data of nine Global Climate Models (GCMs) as input forcings to a hydrologic model MIKE11 NAM-HD to simulate the river flows at the head of the Mahanadi delta. The mean areal rainfall for the delta region and the river-flow simulations are forced into a calibrated and validated MIKE FLOOD model to simulate the historical and projected flood inundations. Comparison of the compound floods with the rain-induced and streamflow-induced floods indicate increased compound flooding in the projected scenario. Both historical and projected floods are found to be predominantly influenced by the river flows. Also, both the areal extent and flooding depth are found to be increasing the projected period as compared to the historical counterpart.

Previous studies have estimated that 25% to 35% of Amazonian precipitation comes from evapotranspiration (ET) within the basin. However, due to simplifying assumptions of traditional models, these studies primarily focus on large spatial and temporal scales. In this work we use the Weather Research and Forecast (WRF) regional climate model with the added capability of water vapor tracers to track the moisture from Amazonian ET at the native WRF resolution. The tracers reveal that the well-mixed assumption of simpler models does not hold, as local ET is more efficiently rained out of the atmospheric column than remote sources of moisture, particularly in the eastern part of the basin. Recycled precipitation shows a strong annual and semi-annual signal, associated with the passage of the Inter-Tropical Convergence Zone. The tracers also reveal a strong diurnal cycle of Amazonian water vapor related to the diurnal cycle of ET, convective precipitation and advected moisture. ET increases from early morning into the afternoon, some of this moisture is rained out through convective storms in the early evening, while later in the night strong winds associated with the South American Low Level Jet advect moisture downwind. Visualizing the Amazonian water vapor highlights its diurnal beating pattern and suggests that the Amazon has “younger” water than other regions in the globe, with very efficient recycling of local moisture.

All current understanding (theoretical and observational) suggests that the development of the solar wind and CMEs takes place within 10 Rs, particularly below 4 Rs. This seemingly narrow spatial region encompasses the transition of coronal plasma processes through the entire range of physical regimes from fluid to kinetic, and from primarily closed magnetic field structures to primarily open. For these reasons, we refer to it as the Critical Coronal Transition Region (CCTR). Its comprehensive exploration will answer two of the most central Heliophysics questions with repercussions across NASA and society. Here, we outline a path to answer these questions in the next 30 years.

The frequency of extreme weather events depends relatively more on climate variability than on average changes. This makes variability a crucial element to consider in future projections. Stable water isotopes such as δ18O extracted from climate archives, including ice-cores, have been used to reconstruct regional climate and evaluate climate simulations. These archives have shown that variability in the Holocene is much lower than that at the Last Glacial Maximum (LGM, 21 kyr ago). However, state-of-the-art climate models still fail to simulate this shift. Comparison is difficult, since paleoclimate equilibrium simulations are typically run for few centuries and do not yet incorporate water isotope tracers. Volcanic eruptions offer a unique testbed to analyse the link between regional archives and global climate since well reconstructed aerosol data from 800 CE onward allow the investigation of small and large-scale effects in time and space on the climate. Here, millenial simulations from the isotope-enabled version of HadCM3 forced by solar and volcanic reconstructions in pre-industrial, LGM and past-millenium scenarios were evaluated. We then analysed the influence of volcanic eruptions on climate and δ18O values in polar and alpine regions. This allowed us to test the dependency of isotope values on regional shifts in climatology as well as global anomalies using composite analysis of volcanic eruptions. We finally discuss the impact of these results on the climatic representation of polar and alpine ice-cores representing changes in global climate variability.

Surface tension controls all aspects of fluid flow in porous media. Through measurements of surface tension interaction under multiphase conditions, a relative permeability relationship can be determined. Relative permeability is a numerical description of the interplay between two or more fluids and the porous media they flow through. It is a critical parameter for various tools used to characterized subsurface multiphase flow systems, such as numerical simulation for oil and gas development, carbon sequestration, and groundwater contamination remediation. Therefore, it is critical to get a good statistic distribution of relative permeability in the porous media under study. Empirical relationships for determining relative permeability from capillary pressure are already well established but do not provide the needed flexibility in that is required to match laboratory derive relative permeability relationships. By expanding the existing methods for calculating relative permeability from capillary pressure data it is possible to create both two and three-phase relative permeability relationship. Existing laboratory measured relative permeability data along with mercury intrusion capillary (MICP) data coupled with interfacial tension and contact angle measurements were used to determine the efficacy of this approach to relative permeability curve creation. The relative permeability relationships determined with this method were fit to the existing laboratory data to elucidate common fitting parameters that were then used to create relative permeability relationships from MICP data that does not have an associated laboratory measured relative permeability relationship. The study was undertaken as part of the Southwest Regional Partnership on Carbon Sequestration (SWP) under Award No. DE-FC26-05NT42591.

Four transform faults and three intra-transform segments located at Equatorial Atlantic form the Saint Paul Transform System (SPTS), with a long-offset of 630 km. In the northern transform, the 200 km long and 30 km wide Atoba Ridge is a major topographic feature that reaches the sea level at the St. Peter and St. Paul Archipelago island (SPSPA, 00º 55 ‘0’ ‘N and 29º 20 ”43”W). The islets have an average uplift rate of approximately 1.5 mm/year. The southern and northern flanks of the Atobá Ridge are marked by a series of large thrust faults visible in the bathymetry and clearly imaged through seismics and correspond to an exceptionally serpentinized mantle. We have determined the hypocentral location of 62 minor-moderate earthquakes of SPTS, with magnitudes 1.9 ≥ M ≤ 5.3. The earthquakes occurred in 2013 and were recorded by a seismometer installed in SPSPA and three autonomous hydrophones deployed during the COLMEIA cruise. The HYPOCENTER software and Seismic Analysis Code (SAC) were used for data analysis and hypocenter location. The depth range is from 0.2 to 17.5 km and are concentrated in three different zones: the East Shear Zone (ESZ), the Atobá Ridge Zone (ARZ) and the Central Fracture Zone (CFZ). A seismogenic zone with a deep britle-ductile transition was identified in SPTS, with hypocenters reaching 18 km beneath the seafloor. We observed that this lithospheric structure presents relation with the offset age and controls the maximum hypocentral depths of oceanic transform faults. Besides, the earthquakes indicated the existence of a broad serpentinization depth reaching 18 km beneath the ARZ. This was interpreted as the effect of deep water percolation into the mantle in the SPTS, which caused a fluid-mantelic rocks interaction and allowed the expansion of faults into the mantle. Some hypocenters were located in the central fracture zone (CFZ) segment of SPTS and their depths reached 8.8 km beneath the seafloor. We interpreted this seismicity as reactivation of a weakness zone existent in CFZ due to the transpressive load-induced stress originated in Atobá Ridge.

We present a book entitled “Machine Learning, Statistics, and Data Mining for Heliophysics,” an online and open source book available at helioml.org. This book includes a collection of interactive Jupyter notebooks, written in the programming language Python, that walks the reader through the process of applying machine learning, statistics, and data mining techniques on various kinds of solar and space physics data sets to reproduce published results. We consider this book to be a living document with frequent updates. Please contact us if you’d like to submit a chapter!