There have been important criticisms of IPCC recent reports for failing to communicate the dire nature of the current predicament facing civilization – so-called “scientific reticence” – as well as for assuming functional, planetary-effective scale biomass carbon capture and storage in its survivable scenarios [1-3]. In the light of major reports released in 2018 [4,5] which underscore the discrepancy between the current climate trajectory and best-case requirements to maintain global civilization, the current predicament is often described as an “existential” crisis [6]. Part of the confusion appears to stem from the lack of discussion of specific scenarios, such as rapid arctic methane release [7,8], which are not discussed by the IPCC in proportion to their catastrophic potential. This scenario is briefly examined using the Goddard Institute for Space Studies (GISS) ModelE v2 7.50.05 [9]. It is suggested that the results presented here represent a lower bound to climate disruption since in this set-up, neither the oceans nor arctic sea ice (a significant and ongoing runaway feedback [10]) respond to the changes modeled; namely, a sudden release of stored methane gas.

Imagery from the GOES series has been a key element of U.S. operational weather forecasting for four decades. While GOES observations are used extensively by human forecasters for situational awareness, there has been limited usage of GOES imager data in numerical weather prediction (NWP), and operational data assimilation (DA) has ignored cloud and precipitating pixels. The motivation of this project is to bring the benefits of GOES-R Series enhanced capabilities to advance convective-scale DA for improving convective-scale forecasts. We have developed a convolutional neural network (CNN) prototype, dubbed “GOES Radar Estimation via Machine Learning to Inform NWP (GREMLIN)” that fuses GOES-R Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) information to produce maps of synthetic composite radar reflectivity. We find that the ability of CNNs to utilize spatial context is essential for this application and offers breakthrough improvement in skill compared to traditional pixel-by-pixel based approaches. Making use of ABI spatial information potentially provides benefits over radiance assimilation approaches that are limited by saturation of radiances in pixels with precipitation. This presentation will briefly describe the GREMLIN model and characterize its performance across meteorological regimes. We are developing a dense neural network (DNN) to produce vertical profiles of radar reflectivity and latent heating based on the two-dimensional fields output from GREMLIN. The resulting three-dimensional fields of latent heating will be used to initialize NWP simulations of convective-scale phenomena. Another DNN will be developed to produce uncertainty estimates of latent heating for each pixel. Our approach for data assimilation will be described and is innovative in being the first-time machine learning (ML) will be used for the nonlinear latent heating observation operator in the NOAA hybrid Gridpoint Statistical Interpolation (GSI) and/or JEDI systems. The approach will provide all the elements of the Jacobian needed for GSI DA and has the advantage of automatically maintaining the tangent linear and adjoint models through finite difference mathematics.

Global navigation satellite systems (GNSS) or satellite navigation is an important technological advancement; however, it is greatly impacted by the effects of space weather, such as ionosphere scintillation. Ionosphere scintillation is one of the causes of errors in the GNSS signals and also has the potential to cause a loss of access to GNSS. Ionosphere scintillation often impacts the polar region; however, the cause is not always known. One potential source of scintillation is polar cap patches. In Ren et al., [2018], a polar cap patch database was created based on the incoherent scatter radar measurements at Resolute Bay (RISR). Using data provided by the CHAIN Network of ionosphere scintillation detected near Resolute Bay in 2016, it can be determined how polar cap patches impact ionosphere scintillation. A statistical analysis as well as event analysis have been performed. Scintillation data from GNSS satellites with an elevation angle over 40 degrees were collected from each patch in the database and were compared to daily average. It was found that statistically there is no obvious phase scintillation or amplitude scintillation increase associated with patch in the polar cap. For the event analysis, three different patch events with and without enhanced scintillation were chosen for in-depth analysis and cross-comparison. Other datasets, including AMPERE FAC and RISR, are used to understand the plasma characteristics and geomagnetic activity conditions during these events.

Skillful forecasts of daily streamflow on river networks are crucial for flood mitigation, especially in rainfall-driven river basins. This is of acute importance on the Narmada River Basin in Central India, which is driven by the summer monsoon rainfall, and floods lead to heavy loss of life and infrastructure. Physical hydrologic models based on the land surface model – Variable Infiltration Capacity (VIC), have been developed in an experimental mode to model and forecast the hydrologic system, which includes – storage, soil moisture and runoff – by incorporating rainfall data from the India Meteorological Department (IMD). To enhance the forecast skill by model-combination, we propose a coupled physical-statistical modeling framework. In this, we couple the VIC model with a novel Bayesian Hierarchical Network Model (BHNM) for daily streamflow forecasts that uses the network topology to capture the spatial dependence. The daily streamflow at each station is modelled as Gamma distribution with time-varying parameters. The distribution parameters for each day are modeled as a linear function of covariates, which include antecedent streamflow from upstream gauges and, daily 2-day, or 3-day precipitation from the upstream contributing areas - that reflect the antecedent land conditions. The posterior distribution of the model parameters and, consequently, the predictive posterior distribution of the daily streamflow at each station and for each day are obtained. To the BHNM model, we will couple the VIC model by including the hydrologic forecasts – especially soil moisture and storage – as additional covariates. The coupled model will be demonstrated by its application to daily summer (July-August) streamflow at 4 gauges in the Narmada basin network for the period 1978 – 2014. The skill of the probabilistic forecast will be assessed using rank histograms and skill scores such as CRPS and RPS. The model skill will also be tested on five high flooding events on both the timing and magnitude. These model combinations will enable to combine the strengths of the individual models in capturing the hydrologic processes, biases and nonstationary relationships, to provide skillful daily streamflow forecasts. This will be of immense help in flood mitigation.

The solar quiet variation (Sq) observed at observatories near the latitude of the Sq vortex focus is difficult to assess because it is affected by both the geomagnetic activity level and the dynamics of the ionosphere and the upper atmosphere resulting in changes of the Sq ionospheric vortex shape and position. The use of only geomagnetically quiet days (QD) to calculate Sq for a given month can, to a certain extent, remove the effect of geomagnetic disturbances; however, the effect of the atmospheric dynamics still needs to be taken into account. The Sq vortex shape and position can be acquired from the horizontal vector of the geomagnetic field measured at geomagnetic observatories located in the European-African sector between 10ºN and 60ºN using vector rotation or calculating equivalent currents. Here we present results of a comparative analysis of two methods to extract Sq variations from the observations of the earth geomagnetic field. The analyzed data are measurements of the geomagnetic field done between 2007 and 2017 at the Coimbra Geomagnetic Observatory (COI, Portugal) located near 40ºN.The principal component analysis (PCA) based Sq curves are compared with the standard ones obtained using 5 international QD per month. For most of the analyzed years for the X component, the second PCA mode was identified as Sq variation whereas for the Y and Z components for all analyzed data sets the first PCA mode was identified as Sq variation. We studied differences and similarity of the PCA and IQD based Sq in relation to (1) the average geomagnetic activity level and (2) Sq vortex shape and position relatively to COI.

Monitoring stress state in the Earth’s crust plays a crucial role in our understanding of an earthquake’s mechanism, especially how earthquake ruptures nucleate, as well as in calculating the distribution of hazards. Crustal deformation due to the 2019 Ridgecrest earthquakes, which occurred near the town of Ridgecrest, California, that culminated in a preceding earthquake of magnitude (M) 6.4 and a subsequent M7.1 event, caused stress perturbation in nearby regions. However, implications of future seismic activity are still unclear. Here we analyze the occurrence of small earthquakes compared to larger ones—the b-values, showing how the nucleation area for both the M6.4 and M7.1 earthquakes had low b-values before these events occurred, and mid-to-high b-values thereafter. The slip distribution of the M7.1 event is also well correlated with the b-value map. Additionally, the time and local-dependent variations in b-values of the Ridgecrest earthquakes are linked with estimates of changes to Coulomb stress. The main conclusion is that the b-value mapping provide insight into the stress state in the fault zone, which is likely closely related to the nucleation and evolution of earthquakes in the sequence. The combined approach of stress-change and b-value analyses to the post-M7.1-quake sequence shows an area that is currently being stressed near the Garlock fault that hosted past large earthquakes. The b-values are not as low as those immediately before the M6.4 and M7.1 events, but contribute the most recent values in a decreasing trend of the b-value. Together with geodetic and seismological observations, monitoring the spatial and temporal distribution of b-value would contribute to seismic hazards in the Eastern California Shear Zone.

Erma Yulihastin 1,2, Tri Wahyu Hadi1, Nining Sari Ningsih3, Muhammad Ridho Syahputra1 1Atmospheric Sciences Research Group, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, Bandung, 40132, Indonesia 2Center of Atmospheric Sciences and Technology, National Institute of Aeronautics and Space, Bandung, 40175, Indonesia 3Oceanography Research Group, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, Bandung, 40132, Indonesia The diurnal cycles of precipitation over the northern coast of West Java have been studied using the Tropical Rainfall Measuring Mission (TRMM) Real Time Multi-satellite Precipitation Analyses (MPA-RT) products with records spanning from 2000 to 2016, with emphasis on the occurrences of early morning precipitation peaks. Diurnal precipitation over the study area during November to March is basically characterised by precipitation peaks that occur in the afternoon to evening time (15:00–21:00 LT) but secondary peaks in night to morning time (01:00–07:00 LT) are also pronounced in January and February. Harmonic analysis method was then applied on data of January and February to objectively determine the diurnal phase and classify the timing of precipitation for each day into three categories, i.e. afternoon-to-evening precipitation (AEP), early morning precipitation (EMP), and late morning precipitation (LMP) with peaks that occur in the time windows of 13:00–24:00 LT, 01:00–04:00 LT, and 05:00–12:00 LT, respectively. In terms of frequency of occurrence, AEP, EMP, and LMP constitute 55 %, 26.1 %, and 18.9 % of total samples of precipitation events. In spite of the smallest percentage, EMP events are characterised by seaward (as well as landward) propagation, flat phase distribution, and large mean amplitudes. The propagating characteristics of EMP are more prominent, with indications of stronger connectivity between precipitation systems over land and ocean, when data are composited by taking the 99th percentile values in each grid to represent extreme precipitation events. The flat phase distribution of EMP events suggests that the timing of coastal precipitation is not necessarily locked to the phase of land/sea-breezes, thus, allowing precipitation to occur more randomly.

We study the behavior of solar wind (SW) parameters over 21-24 solar cycles (SCs). We take into account that these variation can depend on three reasons: (1) type of SW, (2) phase of SC, and (3) SC number. Our catalog of large-scale SW types for 1976-2018 (see the website ftp://ftp.iki.rssi.ru/pub/omni/ [Yermolaev et al., 2009]) covers the period from the 21st to the 24th SC and allows us to analyze independently these three reasons, since we can select SW parameters for different types of SW (in particularly, slow and fast SW, Sheath, ICME, CIR) and at different phases of different SCs. Preliminary data show that with an increase in the SC number (1) the number of perturbed SW types decreases and (2) the values of plasma and magnetic field parameters decrease in each type of SW, and for each phases of SCs. The most rapid change in parameters was observed during the minimum period between the 22nd and 23rd cycles. The work was supported by the Russian Science Foundation, grant 16-12-10062. References Yermolaev, Y.I., Nikolaeva, N.S., Lodkina, I.G., Yermolaev, M. Y. (2009). Catalog of large-scale solar wind phenomena during 1976–2000. Cosmic Res 47, 81–94 https://doi.org/10.1134/S0010952509020014Yermolaev, Y.I., Nikolaeva, N.S., Lodkina, I.G., Yermolaev, M. Y. (2015). Dynamics of large-scale solar wind streams obtained by the double superposed epoch analysis, JGR, https://doi.org/10.1002/2015JA021274

C-LIFE is a landed camera suite, suitable for Ocean World surfaces, consisting of a color Context Reconnaissance Stereo Imager and an LED flashlight that can also identify biogenic material through fluorescence. The C-LIFE design leverages ongoing work (with industry partners Space Dynamics Lab, SRI International and Ball Aerospace) from our ICEE-2 and COLDTech awards in low-temperature detector qualification, radiation modeling and mechanical design. It takes advantage of our development work on the Descent Imager for Europa Hazard Avoidance and Radiation Durability (DIEHARD) and camera development on other missions. The C-LIFE camera head is mounted on the Europa Lander’s high gain antenna, which provides tilt and pan capability. Minimal electronics in the camera head control and read out the detector and LEDs. Electronics in the lander vault perform most camera functions and image processing. C-LIFE contains no moving parts. In lieu of a focus mechanism, C-LIFE utilizes high F/number optics and a field of view elongated in the vertical direction with progressive focus from top (infinity e.g. imaging horizon) to bottom (close e.g. imaging sample delivery port). Strip filters (that match Europa Clipper’s Europa Imaging System) on the detectors and partly-overlapping images provide color coverage. Heaters warm C-LIFE to operating temperatures, allowing self-heating to take over, but otherwise the camera is unheated in order to conserve energy. We combine two independent eyes into one mechanical housing (Figure 1) with a dual periscope design, which reduces the mechanical envelope, shielding mass, heating energy and total cabling distance. We use LEDs in three bands to illuminate and to excite fluorescence. Fluorescence excited by these three bands can identify the presence of key metabolic biomarkers and discriminate the quantities of live cells, dead cells and spores in a terrestrial setting. Figure 1. A dual-periscope design, with eyes 20 cm apart, folds optical trains (incoming rays in gray) to mutually shield focal planes. Fold mirrors locate LEDs inside the camera for shielding.

Satellite imagery to rapidly develop maps of historical flood hazard and current inundated areas over large spatial coverage is indispensable in supporting situational awareness for improved debris estimation, transportation impacts and damage assessments. However, how best to utilize these maps as actionable information during flood disasters and for flood disaster response assistance is less clear. Furthermore, the integration of any satellite data from an “untrusted” (non-mandated) source into the operations chain and response protocols of a mandated agencies such as FEMA, PDC (PDC is already pulling some DFO-DSS layers) or the UN WFP would be a non-trivial procedure. These agencies desire to prioritize support and resource requirements for community lifelines. (Safety & Security; Food, Water & Shelter; Health & Medical; Energy (Power & Fuel); Communications; Transportation; and Hazardous Materials). The majority of these lifelines can be impacted by floods. The Global Flood Observatory’s (DFO, University of Colorado Boulder) web map server and its associated mobile app (DFO-Floods) is a resource for global extents of floods now delivered as map products via web services. This flood decision support system (DSS) serves flood maps along with other trusted geospatial data to the global disaster response community. However, acceptance of the DFO product line as a trusted information source requires additional tests to assess its performance in combination with the respective response process of agencies around the world. This would allow moving the product from a high Application Readiness Level into an Operational Readiness Level (ORL) for agency trusted data implementation. This paper reviews success examples of the DFO flood layers, illustrates the newly released mobile app and discusses the need for trusted flood map products and services to support the global disaster response community.

Large igneous provinces (LIPs) are often associated with mass extinctions and are thus vital for life evolution on Earth. However, the precise relation between LIPs and their impacts on biodiversity is enigmatic as they can be asynchronous. If the environmental impacts are primarily related to sill emplacement, the structure of LIPs’ magma storage system becomes critical as it dictates the occurrence and timing of mass extinction. Here we use surface wave tomography to image the lithosphere under the Permian Emeishan Large Igneous Province (ELIP) in southwestern China. We find a NE-trending zone of high shear-wave velocity (Vs) and negative radial anisotropy (Vsv > Vsh) in the crust and lithosphere and interpret it as a mafic-ultramafic, dike-dominated magma storage system on the hidden hotspot track of the ELIP. An area of less-negative radial anisotropy, on the hotspot track but away from the eruption center, reflects an elevated proportion of sills emplaced at the incipient stage of the ELIP. Liberation of poisonous gases and mercury by the sills explains why the mid-Capitanian global biota crisis preceded the peak ELIP eruption by 2-3 million years.

Multicollector noble gas mass spectrometry has yielded significant improvements in the precision of 40Ar/39Ar age determinations over the last decade [1,2]. We report initial results from the new Isotopx NGX mass spectometer at the WiscAr Laboratory that is equipped with 9 Faraday detectors and 1 ion counting multiplier. The NGX utilizes Isotopx’s ATONA® amplifier technology, enabling measurements spanning a dynamic range from below 10−16 A to above 10−9 A [3]. Moreover, the WiscAr NGX offers the unique opportunity to evaluate instrument performance using both a conventional, and a newer low temperature, Nier-type ion source, which allows for trap current variation. We have performed a series of tests to: (1) assess optimal measurement and integration times for blanks, baselines, and air aliquots of various sizes, (2) quantify the NGX sensitivity via measurements of first principle 40Ar/39Ar standards fused with a CO2 laser, and (3) compare the sensitivity and effects on instrument background between the conventional and new low temperature Nier-type sources. Initial results suggest that for most samples optimal precision is achieved when using 10 second integration times for measurements lasting 400-600 seconds. Measurements of low 36Ar signals are optimized with longer integration and measurement times. In addition to measurement optimization experiments, we performed a comparative analysis of both fusion and incremental heating data obtained using the WiscAr Nu Instruments Noblesse, MAP 215-50, and the NGX for a variety of geologic materials which range in age from Pleistocene to Permian. Pychron software [4] controls the entire NGX analytical system, including data collection and reduction. Careful experiment design in this automated system, when informed by optimized counting practices and knowledge of collector sensitivity, can lead to high precision 40Ar/39Ar dates. [1] Jicha et al. (2016), Chemical Geology 431, 54–66 [2] Mark et al. (2009), Geochemistry, Geophysics, Geosystems 10 [3] Cox et al. (2020), Geochron. Discuss, 2020-1. [4] Ross J., 2019, NMGRL/pychron v18.2, doi: 10.5281/zenodo.3237834.

Understanding the contribution of the West Antarctic Ice Sheet (WAIS) to past and future sea level has emerged as a scientific priority over the last three decades. In recent years, observed thinning and ice-flow acceleration of the marine-based Pine Island Glacier has demonstrated that dynamic changes are central to the long-term stability of the WAIS. However, significantly less is known about the evolution of the catchment during the Holocene. Internal Reflecting Horizons (IRHs) provide a cumulative record of accumulation, basal melt and ice dynamics that, if dated, can be used to inform ice flow models to project spatial and temporal mass changes. Here, we use airborne radars to trace four consistent IRHs spanning the Holocene across the Pine Island Glacier catchment. We use the WAIS Divide ice-core chronology to assign discrete ages to three IRHs: 4.72 ± 0.08, 6.94 ± 0.11, and 16.50 ± 0.62 ka. We use a 1D model, constrained by observational and modelled accumulation rates, to produce an independent validation of our ice-core-derived ages and provide an age estimate for our shallowest IRH (2.31-2.92 ka). We find that significantly older ice is present below our deepest reflector, but the absence of continuous radar-observed reflectors at depth currently limits our understanding of pre-Holocene ice dynamical history. The clear correspondence between our IRH package and the one previously identified over Institute Ice Stream, altogether representing ~20% of the WAIS, suggests that a unique set of stratigraphic markers spanning the Holocene exist widely across West Antarctica.

Urban Green Spaces (UGSs) are proving to be most important part of urban area of a city. These green spaces not only provide psychological comfort to humans but also affect heat impact on city to a vast level. In a developing country like India, where urban growth is happening in a very fast and haphazard manner a little consideration is given to Green Spaces in city. Such a study has been conducted over Lucknow metro-city of Uttar Pradesh state of India. In this study, the relation between Land Use\Land Cover (LULC) and Land surface temperature (LST) has been tried to find. Using Landsat-8 OLI data (Band 3, 4 & 5) and Maximum Likelihood Classification algorithm, 6 Land Use classes are obtained, which are “Built-up”, “Vegetation”, “Shrub”, “Water”, “Fallow Land” and “Other”. In addition to these 4 Land Cover Indices namely Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI) and Normalized Difference Barren Index (NDBaI) are also generated for same areas. LST is obtained using TIRS data (Band 10 & 11) and Split Window Algorithm by Radiative Transfer Equation. Ancillary data is used for digitization of 5 assembly constituencies (ACs) of Lucknow parliamentary constituency (PC) of Lucknow district namely, Lucknow Cantonment, Lucknow North, Lucknow East, Lucknow West and Lucknow Central has been done. River and Canal passing through these areas, are also considered in Urban Green Spaces as per Urban Atlas code 14100. 250m radius buffer is generated around Built-up pixels for analysis of impact of UGSs on LST. Cantonment and East Lucknow area having highest amount of UGSs in terms of “Vegetation”, “Shrub” & “Water” pixels due to presence of Forest area in both ACs. It is found that LST is positively related with all indices except for NDVI with strong negative correlation and R2 of 0.47 and highest R2 of 0.53 with NDBI. Among all 5 ACs best correlation between all 4 LC and LST values is found in Lucknow East AC with R2 > 0.64 for NDVI, NDWI and NDBI. Lucknow East AC is having least LST but there is very little difference between LST values of Built-up pixels having minimum UGSs present in 250m radius buffer around built-ups and Built-up pixels having no UGSs around. AC Lucknow Central is having 1 °C difference in LST values of such different Built-ups.

For catchment-scale streamflow estimation, recently, the preference is shifting towards the use of innovative remote sensing (RS)-based approaches at the remote gauging stations. In this context, this study evaluates the performances of three RS-based models designed with the near-infrared (NIR) bands of Landsat images at the Jenapur outlet of the Brahmani River basin in eastern India. These RS-based models are designed using the spectral behavior of land (C) and water (M) pixels in the NIR region of the electromagnetic spectrum in the presence and absence of water surrounding the streamflow gauging station. Further, the computed pixel ratio (C/M) is used as a parameter for the discharge estimation, in which four years (2009-2013) of Landsat images are used during calibration and three years (2014-2016) of these images are used during validation. Model-I uses the C/M method in which a box-matrix is conceptualized to analyze the optimal location of the land pixel (C0); and subsequently, the time series of C/M is calibrated with the in-situ discharge (Q) time series. The best pixel ratio (C0/M) time series is preprocessed with an exponential smoothing filter to derive the best filtered-pixel ratio (C0/M*) time series, which is used in the regression model to estimate the river discharge. Model-II corresponds to the multi-pixel ratio (MPR) method, where a 3×3 window is used to calculate the average reflectance of both the C and M pixels within the box-matrix, and subsequently, to obtain the best pixel (C0ʹ/Mʹ) ratio as in the case of Model-I to develop the spectral relationship between C0ʹ/Mʹ and Q time series. Model-III uses both the C/M and water width-based function to estimate the streamflow. The performance evaluation of the models is carried out using the Nash-Sutcliffe efficiency, Percentage bias, and Mean absolute error, which reveals that the model performance varies in the order: Model-III > Model-II > Model-I. This proposed RS-based discharge estimation model framework has the potential to be used in many world- rivers with varying cross-sections.

Material samples are vital across multiple scientific disciplines with samples collected for one project often proving valuable for additional studies. The Internet of Samples (iSamples) project aims to integrate large, diverse, cross-discipline sample repositories and enable access and discovery of material samples as FAIR data (Findable, Accessible, Interoperable, and Reusable). Here we report our recent progress in controlled vocabulary development and mapping. In addition to a core metadata schema to integrate SESAR, GEOME, Open Context, and Smithsonian natural history collections, three small but important controlled vocabularies (CVs) describing specimen type, material type, and sampled feature were created. The new CVs provide consistent semantics for high-level integration of existing vocabularies used in the source collections. Two methods were used to map source record properties to terms in the new CVs: Keyword-based heuristic rules were manually created where existing terminologies were similar to the new CVs, such as in records from SESAR, GEOME, and Open Context and some aspects of Smithsonian Darwin Core records. For example specimen type =liquid>aqueous in SESAR records mapped to specimen type = liquid or gas sample and material type = liquid water. A machine learning approach was applied to Smithsonian Darwin Core records to infer sampled feature terms from record text describing habitat, locality, higher geography, and higher classification fields. Applying fastText with a 600-billion-token corpus in the general domain, we provided the machine a level of “understanding” of English words. With 200 and 995-record training sets, 87%, 94% precision and 85%, 92% recall were obtained respectively, yielding performance sufficient for production use. Applying these approaches, more than 3x106 records of the four large collections have been mapped successfully to a common core data model facilitating cross-domain discovery and retrieval of the sample records.

Conventional engineering measures, such as surge barriers and mobile floodgates, are being adopted in many coastal cities worldwide, threatened by the increasing flooding hazard due to rising sea levels. Famous examples include London, the Netherlands, New Orleans, St. Petersburg and Venice. However, the question of how flood regulation affects the morphodynamic evolution of shallow tidal embayments still lingers. Storm-surge barriers may importantly modify the propagation of tides, surges and wind waves, changing sediment transport and, thus, the morphological evolution of regulated tidal environments, in particular in sediment-starved systems. Combining field data and numerical modelling, we investigate the effect of the Mo.S.E. storm-surge barriers, designed to protect Venice from flooding, on the morphodynamic evolution of the Venice lagoon. Artificial reduction of water levels within the lagoon affects the interaction between tide propagation and wind waves, increasing sediment resuspension on tidal flats. Resuspended sediment hardly accumulates on salt marshes, contributing to their vertical accretion and offsetting the negative effect of relative sea-level rise, owing to the reduction of marsh flooding determined by reduced water levels. Although barrier closures temporarily reduce the sediment export toward the open sea, this does not point to preserve the characteristic lagoonal morphology, hindering salt-marsh accumulation and promoting tidal-flat deepening and channel infilling. We conclude that the operations of flood barriers can promote a significant loss of geomorphological diversity, which will critically impact the ecosystem services provided by the shallow tidal environments they are meant to protect, thus increasing the costs related to their conservation and restoration.

The Malalak Tephra (sourced from Tandikat volcano) is considered one of the youngest and most voluminous tephra deposits (VEI-5) in West Sumatra, Indonesia. However, several constraints such as deposit characteristics and eruption dynamics, remain poorly understood. Therefore, this study focuses on the linkage between temporal variation (stratigraphy) with componentry, bulk density, and juvenile textures such as vesicles and phenocrysts of the Malalak Tephra deposit. This deposit mainly consists of five pumice fall layers (F-1, F-2, F-3, F-4, and F-5) with gradational contact between each layer (repetitions of normal and reverse grading). White and grey pumices occur as the main juvenile phase. White pumice has a higher crystallinity (avg. of 44 %) and more evolved chemical composition of glass (73–78 wt. % SiO2) compared to grey pumice (average crystallinity 37 % with 71–77 wt. % SiO2), suggesting that both pumices originated from different magma chambers and mingled just before and during the eruption. Grey pumice is typically denser than white pumice, with varying bulk density of 0.65–1.78 g/cm3 and 0.48–1.09 g/cm3 for grey pumice and white pumice, respectively. Bulk density was observed to increase (for white and grey pumices) from the main stage (F-1 and F-2) to the closing stage (F-3, F-4, and F-5). Because bulk density is strongly dependent on bulk vesicularity, and bulk vesicularity is controlled by vesicle number density (which is a function of decompression rate), it can be inferred that the main stage was relatively more explosive compared to the closing stage.