On the edge of our continents, oceanic crust meets continental crust. At passive margins, those where there is no active tectonics, subduction or transform faulting, these crustal types are connected as sharp continent-ocean boundaries (COB) or as diffuse continent-ocean transition (COT) zones. Passive margins are hard to explore and consequently relatively little is known about their morphology or the processes of their formation. Here we elicit and analyse seismic image interpretations of the passive margin offshore East India conducted by 17 groups of geoscientists to better understand the differences, or lack therein, of COB or COT interpretations of the margin. The group interpretations provide a wide range of margin models, five of which are abrupt COB based and 11 which are diffuse COT based. However, interpretations within the COB set vary in the placement of the boundary line between continental and oceanic crust, the boundary placement lying within the range of interpreted COT zones, with the average COB location falling in the centre of the interpreted COT zones. These crowd-sourced results are then compared with ten published interpretations across the margin, which show COB and COT zones falling in the same area. These findings raise questions as to the real differences in COB and COT models and the geological processes involved in their formation. Considering this, we discuss the implications for passive margin models and the use of Wisdom of Crowds-type approaches in reflecting on both the range of interpretation-based models and in the value of determining ‘average’ model approaches.

Plate boundary deformation zones represent a challenge in terms of understanding their underlying geodynamic drivers. Active deformation is well constrained by GNSS observations in the SW Balkans, Greece and W Turkey, and is characterized by variable extension and strike slip in an overall context of slow convergence of the Nubia plate relative to stable Eurasia. Diverse, and all potentially viable, forces have been proposed as the cause of the observed surface deformation, e.g., asthenospheric flow, horizontal gravitational stresses (HGSs) from lateral variations in gravitational potential energy, and rollback of the Hellenic slab. We use Bayesian inference to constrain the relative contribution of the proposed driving and resistive regional forces. Our models are spherical 2D finite element models representing vertical lithospheric averages. In addition to regional plate boundaries, the models include well-constrained fault zones like north and south branches of the North Anatolian Fault, Gulf of Corinth and faults bounding the Menderes Massif. Boundary conditions represent geodynamic processes: (1) far-field relative plate motions (2) resistive fault tractions (3) HGSs mainly from lateral variations in topography and Moho topology (4) slab pull and trench suction at subduction zones. The magnitude of each of these is a parameter in a Bayesian analysis of the models in the context of horizontal GNSS velocities. The search yields a probability distribution over all parameters, allowing us to determine mean/median parameter values, robustly estimate parameter uncertainties, and identify tradeoffs. Significant trench suction forces from the Hellenic slab act on the overriding Aegean Sea, including along the Pliny-Strabo STEP Fault. Resistive tractions on most plate boundaries and faults are low. The best-fitting models compare well with paleomagnetic rotations and fault slip rates from previous studies.

The Southern Ocean (SO) is the worlds largest high nutrient low chlorophyll region and has a plentiful supply of underutilised macronutrients due to light and iron limitation. These macronutrients supply the rest of the neighboring ocean basins, and are hugely important for global productivity and ocean carbon sequestration. Vertical mixing rates in the SO are known to vary by an order of magnitude temporally and spatially, however there is great uncertainty in the parameterization of this mixing, including in the specification of a background mixing value in coarse resolutation Earth System Models. Using a biogeochemical-ocean model we show that SO biomass is highly sensitive to altering the background diapycnal mixing over short timescales. Increasing mixing enhances biomass by altering key biogeochemical and physical parameters. An increased surface supply of iron is responsible for biomass increases in most areas, demonstrating the importance of year round diapycnal fluxes of iron to SO surface waters. These changes to SO biomass could potentially alter atmospheric CO2 concentration over longer timescales, demonstrating the importance of accurate representation of diapycnal mixing in climate models.

The Arctic Ocean contains only a 1% of the world’s ocean water, but the rivers that flow out into it account for the 10% of the volume world’s rivers freshwater. The upper layer of fresher water facilitates the creation of sea ice and plays an important role in the position of the jet stream and storms over the northern hemisphere [ISBN, 978-82-7971-097-4]. Remote sensing measurements are of special importance in the Arctic since in situ data is very scarce there. SMOS and SMAP are currently providing sea surface salinity (SSS) measures, but only the product provided by Barcelona Expert Center (BEC) is a dedicated product for the Arctic region. The product that we present in this work is an improvement of the BEC Arctic v2.0. The new version 3.0 has as the primary objective the describing better the river discharges. The spatial grid used is WGS84/NSIDC EASE-Grid 2.0 North for the all stages of the processing chain. This procedure avoids spatial interpolation, favoring the definition of river mouths. The salinity retrieval is based on the Debiased non-bayesian method [doi:10.1016/j.rse.2017.02.023] and similarly to what is done in the processing of altimetric data, SMOS salinity is corrected using a reference calculated from the own SMOS data for each latitude, longitude, pass orientation and antenna measuring position. Arctic v3.0 differs from current method [doi:10.3390/rs10111772] in two important points: the reference is computed for brightness temperature instead of SSS and the antenna has been divided in a more homogeneous grid. Other improvements concern to data filtering and propagation of the radiometric errors to SSS. All these improvements provide level 3 maps less noisy, increasing the effective resolution of salinity gradients. Freshwater gradients are much better resolved than in previous version (Fig. 1). Comparison with JPL SMAP product is also planned as a first step to generate a combined product. This work is funded by ESA Arctic + project and also includes the assimilation of the resulting SSS product in the ocean-sea ice data assimilation system TOPAZ as the next version TOPAZ5. A preliminary study [doi:10.5194/os-2018-163] has been performed concluding that BEC product could be a good candidate to be assimilated by TOPAZ. Moreover, some preliminary tests with a pre-release v3.0 version will start shortly.

The instrument package SEIS (Seismic Experiment for Internal Structure) with the three very broadband and three short-period seismic sensors is installed on the surface on Mars as part of NASA’s InSight Discovery mission. When compared to terrestrial installations, SEIS is deployed in a very harsh wind and temperature environment that leads to inevitable degradation of the quality of the recorded data. One ubiquitous artifact in the raw data is an abundance of transient one-sided pulses often accompanied by high-frequency spikes. These pulses, which we term “glitches”, can be modeled as the response of the instrument to a step in acceleration, while the spikes can be modeled as the response to a simultaneous step in displacement. We attribute the glitches primarily to SEIS-internal stress relaxations caused by the large temperature variations to which the instrument is exposed during a Martian day. Only a small fraction of glitches correspond to a motion of the SEIS package as a whole caused by minuscule tilts of either the instrument or the ground. In this study, we focus on the analysis of the glitch+spike phenomenon and present how these signals can be automatically detected and removed from SEIS’ raw data. As glitches affect many standard seismological analysis methods such as receiver functions, spectral decomposition and source inversions, we anticipate that studies of the Martian seismicity as well as studies of Mars’ internal structure should benefit from deglitched seismic data.

The rapid loss of Arctic Sea Ice (ASI) in the last decades is one of the most evident manifestations of anthropogenic climate change. A transition to an ice-free Arctic during summer would impact climate and ecosystems, both regionally and globally. The identification of Early-Warning Signals (EWSs) for the loss of the summer ASI could provide important insights into the state of the Arctic region. We collect and analyze CMIP6 model runs that reach ASI-free conditions (area below 10^6 km^2) in September. Despite the high inter-model spread, with the range for the date of an ice-free summer spanning around 100 years, the evolution of the summer ASI area right before reaching ice-free conditions is strikingly similar across the CMIP6 models. When looking for EWSs for summer ASI loss, we observe a significant increase in the variance of the ASI area before reaching ice-free conditions. This behavior is detected in the majority of the models, and also averaged over the ensemble. We find no increase in the 1-year-lag autocorrelation in model data, possibly due to the multiscale characteristics of climate variability, which can mask changes in serial correlations. However, in the satellite-inferred observations, increases in both variance and 1-year-lag autocorrelation have recently been revealed.

This paper describes an integrated statistical-hydrodynamic method to estimate tropical cyclone-induced coastal flood inundation hazard, applied to a coastal megacity-Shanghai, China. We identify three “worst-case” scenarios (extracted from over 5000 synthetic storms) that generate unprecedentedly high flood levels in Shanghai. Nevertheless, we find that the mainland Shanghai is relatively safe from coastal flooding under the current climate, thanks to its high-standard seawall protection. However, the city is expected to be increasingly at risk due to future sea level rise, with inundation two times and 20 times more likely to occur by mid-and late-21 st century, respectively, and inundation depth and area to greatly increase (e.g., 60-1360% increase in the inundation area for the “worst cases” by 2100). The low-lying and poorly-protected area (e.g. Chongming island) is likely to be moderately affected by flood events with long return periods at the current state but could be largely inundated in future sea-level-rise situations.

We explore the sensitivity of Southern Ocean surface and deep ocean temperature and salinity biases in the FOCI coupled climate model to atmosphere-ocean coupling time step and to lateral diffusion in the ocean with the goal to reduce biases common to climate models. The reference simulation suffers from a warm bias at the sea surface which also extends down to the seafloor in the Southern Ocean and is accompanied by a too fresh surface, in particular along the Antarctic coast. Reducing the atmosphere-ocean coupling time step from 3 hours to 1 hour results in increased sea-ice production on the shelf and enhanced melting to the north which reduces the fresh bias of the shelf water while also strengthening the meridional density gradient favouring a stronger Antarctic Circumpolar Current (ACC). With the shorter coupling step we also find a stronger meridional overturning circulation with more upwelling and downwelling south and north of the ACC respectively, as well as a reduced warm bias at almost all depths. Tuning the lateral ocean mixing has only a small effect on the model biases, which contradicts previous studies using a similar model configuration. We note that the latitude of the surface westerly wind maximum has a northward bias in the reference simulation and that this bias is unchanged as the surface temperature and sea-ice biases are reduced in the coupled simulations. Hence, the surface wind biases over the Southern Hemisphere midlatitudes appear to be unrelated to biases in sea-surface conditions.

A document by Xiaoting Ji. Click on the document to view its contents.

Particle sinking velocity is an important determinant of carbon transport and sequestration to the deep-sea. It is however technically challenging to measure in situ particle sinking velocities. Recently, methods based on the radioactive pairs, (234Th-238U and 210Po-210Pb) were developed to estimate average sinking velocity (ASV), along the classical carbon export flux estimates. The influence of ASVs on key metrics of the biological carbon pump such as (i) the particle export efficiency (defined as the proportion of PP being exported below the surface ocean) (ii) carbon export fluxes and attenuation, still remain uncertain and need to be further evaluated. ASVs are calculated in five biogeochemically contrasting sites: high latitude (Irminger Basin; Scotia Sea), temperate (PAP site) and oligotrophic (BATS, Equator) North Atlantic. ASVs are also calculated for different bloom stages (bloom - post bloom) in the North Atlantic and at the start of the bloom in two contrasting sites in the Southern Ocean (Scotia Sea). A systematic increase of ASVs with depth, inversely correlated to carbon flux attenuation, is detected. We assess whether the increase in ASV with depth is correlated with either temperature or community structure (phytoplankton and/or zooplankton). Evidences of ASV correlation with carbon export efficiency are detected, but they vary strongly with season and location, e.g. very distinct relationships are found for the results from Scotia Sea, likely driven by zooplankton abundance.

Interaction between surface gravity waves and sea-ice in the marginal ice zone is complex, and most of the prior research focus has been in deeper oceans. Here, the regional wave model Simulating WAves Nearshore (SWAN) is configured to simulate reduced wind-generation and wave dissipation in the presence of sea-ice. The wind-generation process is modified by scaling the generation terms with the open-water fraction, while wave dissipation in the presence of sea-ice is simulated as an exponential energy decay as function of ice concentration, wave frequency and empirical coefficients determined from prior experiments. Modified SWAN is used to simulate interaction between regional sea-ice and a swell event in the Barents Sea. The simulation accounting for wave-ice interaction reasonably agrees with field measured significant wave height and the energy spectral density. Additional simulations are conducted for the shallow seas of Gulf of Bothnia, located in the northernmost reach of the Baltic sea. Modeled wave dynamics in this region agrees well with satellite altimetry based measurements. This model setup is further investigated to understand fetch scaling in the marginal ice zone, and non-dimensional energy scales well with a non-dimensional fetch determined from a cumulative fetch dependent on ice concentration. Additional implications for Stokes drift and Stokes drift shear are also discussed for the Bothnian bay. Finally recommendations for including dissipation due to ice thickness, and plans for future model coupling are considered.

Several studies suggest that magnetic reconnection plays an essential role to generate and accelerate most of the erupting coronal magnetic flux ropes such as coronal mass ejections (CMEs). We explore the connection between magnetic properties (magnetic flux and helicity) of interplanetary coronal mass ejection (ICME) flux-ropes (magnetic clouds [MCs]) and those of associated near-sun CME flux-ropes formed in situ by low corona magnetic reconnection. We identify the progenitor CMEs and their solar sources and derive the source region reconnection flux using the post-eruption arcade (PEA) method. Combining the reconnection flux and the geometrical properties of associated CMEs obtained by forward-modeling, we extract the magnetic properties of CME flux ropes at their source. To measure the magnetic properties of 1 AU ICME we use constant-α force-free cylindrical flux rope model fit to in situ observations and directly from the observed magnetic time series rotated to the cloud frame. We investigate whether a significant difference exists in magnetic properties of ICMEs if their solar source is composed of pre-existing flux-ropes (filaments). This study has significant implications in finding the role of reconnection in the formation of twisted flux ropes during a solar eruptive process that transport solar magnetic flux and helicity into interplanetary space.

Due to global warming, heat stress is becoming a major challenge especially in cities where an intensification of the urban heat island effect is observed and further expected. Climate change adaptation measures are a key strategy to mitigate heat stress and health consequences. Successful adaptation should cool down both indoor and outdoor conditions. As indoor heat is mainly caused by wall heat flux, measures like green, blue or blue-green roofs or facades are a promising approach. These measures on buildings can also easily be scaled as they do not require additional space. However, cooling effects of evaporation-based measures are largely limited by water availability to enable latent heat flux and reduce wall heat flux at extreme heat events or prolonged drought periods. Rainfed water storage systems at buildings like cisterns with a PV-driven pumping mechanism not only supply water for greenings or wet roofs during hot days, but also store storm water to reduce flooding risks. This research aims to simulate heat mitigation effects of rainfed nature-based and technical solutions on buildings using the physically-based high-resolving microclimate model ENVI-met in contrasting climatic conditions. A 3D gridded 16 ha model domain of an urban high-density area in the mid-latitude city of Cologne/Germany and monsoon driven city of Pune/India was parameterised using field observations and remote sensing data. Both models are validated based on a setup quality-controlled, densely-distributed microclimate sensor network. Scenario analyses are performed to quantify cooling effects of intensive/extensive roof greenings, (non-)ground-based facade greenings, wet roofs and combinations. Specific water demands for irrigation of greenings or blue roofs from a managed local rainfed storage are determined to analyse how often and effectively the systems can be operated. Simulation results show significant potential cooling effects in both study areas which are stronger for Pune. Due to water scarcity in the Indian pre-monsoon season, actual heat mitigation potentials are significantly lower than in Cologne as measures can rarely be operated for extreme heat waves at the end of the season. To effectively improve thermal comfort in monsoon conditions, potentials of other measures will be simulated in further research.

The Hawaiian Island chain in the middle of the Pacific Ocean is a well-studied example of hotspot volcanism caused by an underlying upwelling mantle plume. However, the thermal and compositional nature of the plume is still uncertain. The depth and amplitude of seismic discontinuities can show how the plume effects phase transitions in mantle minerals, providing insights into the plume’s thermo-chemical properties. This study utilises >5000 high quality receiver functions from Hawaiian island stations to detect P-to-s converted phases. These receiver functions are stacked in a variety of ways in order to image seismic discontinuities between 200 to 800 km depth. In the mantle transition zone, we find that to the southwest of the Big Island the 660 discontinuity is split. This is inferred to represent the position of the hot plume at depth, with the upper discontinuity caused by an olivine phase transition and the lower by a garnet phase transition. In the upper mantle, the so-called X-discontinuity, which has an enigmatic origin, is found across the region at depths varying between 290 to 350 km. To the east of the Big Island the X-discontinuity lies around 336 km and is particularly strong in amplitude, to such an extent that the discontinuity around 410 km disappears. Synthetic modelling reveals that such observations can be explained by a silica phase transition from coesite to stishovite. This suggests there is widespread ponding of silica-saturated material (such as eclogite, which is silica-rich relative to pyrolite) spreading out from the plume to the east, a hypothesis which is consistent with dynamical models. We suggest that this seemingly thermochemical plume could be sampling recycled basalt, now in the form of eclogite, from lower in the mantle. Therefore these results support the presence of a significant garnet and eclogite component within the Hawaiian mantle plume. We will briefly highlight further work comparing Hawaii with other hotspot locations around the world to consider whether this is also occurring in other plumes and what heterogeneous plumes may imply about the recycling of material in the mantle.

Efforts to stem the spread of COVID-19 in China hinged on severe restrictions to human movement starting January 23rd, 2020 in Wuhan and subsequently to other provinces. Here, we quantify the ancillary impacts on air pollution and human health using inverse emissions estimates based on multiple satellite observations. We find that Chinese NOx emissions were reduced by 36% from early January to mid-February, with more than 80% of reductions occurring after their respective lockdown in most provinces. These emissions declines increased surface ozone by up to 16 ppb over northern China but decreased PM2.5 by up to 23 µgm nationwide. Air pollution appears to have substantially offset hospital admissions related to COVID-19, augmenting mitigation efforts, such as in the Hubei province with ~400 reduced admissions. Changes in human exposure are associated with about 2,100 increased ozone-related morbidity incidences and avoidance of at least 60,000 PM2.5-related morbidity incidences.

The approach of direct inversion of surface wave dispersion data to obtain shallow earth structure becomes popular compared with the traditional two-step surface wave tomographic method. However, some fundamental problems still exist on selecting proper grids to parameterize model. In this study, we apply model parameterization with a multiplegrid scheme to the direct inversion method. A multiple-grid scheme represents a combination of several collocated grids, such as staggered grids, multiscale grids and multiscale-staggered grids. At each iteration, direct inversion is applied to each individual collocated grid to invert for S-wave velocity perturbations that is then interpolated to a predefined base grid using a 3-D B-spline interpolation method. At the end of each iteration, the S-wave velocity perturbations of all collocated grids are averaged together. The averaged perturbations are used to update the 3-D S-wave velocity model that is then used as an initial model for the next iteration. The efficiency of the multiple-grid direct inversion method is demonstrated by applying it to a dense array in Chaohu lake, a special area with the Tanlu fault zone (TFZ) passed through. Synthetic examples confirm a better performance of the multiple-grid direct inversion method than the traditional one. A detailed shallow 3-D S-wave velocity model of the Chaohu lake is obtained after applying the multiple-grid direct inversion method to real data. The velocity model reveals a staggered pattern of velocity variations with low-velocity anomalies in the Hefei basin and eastern Chaohu lake and prominent deep rooted and high-velocity anomalies beneath the TFZ and Yinping mountain, which may associated with the multi-stage tectonic activities in the Tanlu fault. The multiple-grid scheme of this study can further be applied to other tomographic approaches in the near future.

Hydroclimatic flood generating processes, such as excess rain, short rain, long rain, snowmelt and rain-on-snow, underpin our understanding of flood behaviour. Knowledge about flood generating processes helps to improve modelling decisions, flood frequency analysis, estimation of climate change impact on floods, etc. Yet, not much is known about how climate and catchment attributes influence the distribution of flood generating processes. With this study we aim to offer a comprehensive and structured approach to close this knowledge gap. We employ a large sample approach (671 catchment in the conterminous United States) and test attribute influence on flood processes with two complementary approaches: firstly, a data-based approach which compares attribute probability distributions of different flood processes, and secondly, a random forest model in combination with an interpretable machine learning approach (accumulated local effects). This machine learning technique is new to hydrology, and it overcomes a significant obstacle in many statistical methods, the confounding effect of correlated catchment attributes. As expected, we find climate attributes (fraction of snow, aridity, precipitation seasonality and mean precipitation) to be most influential on flood process distribution. However, attribute influence varies both with process and climate type. We also find that flood processes can be predicted for ungauged catchments with relatively high accuracy (R2 between 0.45 and 0.9). The implication of these findings is that flood processes should be taken into account for future climate change impact studies, as impact will vary between processes.

Preventing leakage of CO2 along wellbore cement sheaths is a key factor for ensuring success of geologic carbon storage (GCS) operations. Here, we examine a potential alternative cementing material, engineered cementitious composites (ECC), for use in GCS wellbore cementing applications. ECC is a novel fiber-reinforced cementitious composite that exhibits strain hardening and improved tensile ductility in comparison to conventional cement. Improved ductility may prevent wellbore damage caused by CO2 injection pressures and casing expansion/contraction associated with thermal swings. Earlier work examining physical alterations of ECC exposed to CO2 at 10 MPa and 50°C found that damage to ECC was limited to microcracks with apertures less than 60 µm after several weeks of reaction. However, microstructural analysis revealed densification of the fiber/matrix interphase due to calcite precipitation, which could alter the engineered bonding properties between the matrix and fibers. Such alteration following carbonation could negatively impact the long-term ductility of ECC used for GCS wellbore cementing applications. This presentation will discuss recent results from static batch studies investigating the impact of CO2-acidified water on tensile ductility of ECC. Several ECC and ordinary Portland cement (OPC) coupons were exposed to CO2-saturated water under temperature and pressure conditions of 50oC and 10 MPa, respectively, and samples were retrieved after 2, 7, 14, and 28 days. Four-point flexural test and micro-CT analysis were carried out to investigate the impact of carbonation on the ductility and microstructural properties of ECC. Replicate experiments were also conducted under the same conditions but with a N2 headspace to isolate impacts associated with CO­2 exposure. While the samples exposed to N2 continued to exhibit a multiple microcracking behavior with no observable change in tensile ductility, the ductility of the composite exposed to CO2-acidified water showed an increase in the ultimate flexural strength and significant decrease in ductility as the duration of reaction increased. OPC coupons exhibited brittle behaviors under all test conditions. This suggests that the densification of the fiber matrix interface after exposure to CO2 can compromise ECC’s overall ductility.