bluuebunny/crossref_metadata_2025 huggingface dataset:
The state of stress in the shallow crust of the Hikurangi Subduction Margin hangingwall, New Zealand
Authors: Behboudi Effat , McNamara David , Lockmer Ivan , Wallace Laura , Manzocchi Tom
Published: March 2021

Knowledge of in situ stress fields is critical for a better understanding of deformation, faulting regime, and earthquake processes in seismically active margins such as the Hikurangi Subduction Margin (HSM), North Island, New Zealand. In this study, we utilize Leak-off Test (LOTs) data, borehole breakout widths measured from borehole image logs, and rock unconfined compressive strengths (UCS) derived from empirical P-wave velocity log relationships to estimate vertical (Sv), minimum (Shmin), and maximum horizontal stress magnitudes (SHmax) and interpret the likely faulting regime experienced in four boreholes (Kauhauroa-2, Kauhauroa-5, Titihaoa-1, and Tawatawa-1). Using the standard Anderson’s stress regime classification, relative stress magnitudes in Kauhauroa-5 at 1200-1700 m depth and Kauhauroa-2 at 1800-2100 m and  indicate that the stress state in the shallow crust of the central and northern part of HSM is predominantly strike-slip (SHmax≥Sv≥Shmin) and normal Sv≥SHmax> Shmin respectively. Moving to the offshore, southern HSM a dominant compressional stress regime (SHmax> Shmin >Sv), with some possible strike slip stress states are observed in Titihaoa-1 from 2240-2660 m and Tawatawa-1 from 750-1350 m. The observed normal/strike-slip stress state in Kauhauroa-2 and Kauhauroa-5 is consistent with the average SHmax orientation of 64° ± 18° (NE-SW) determined from borehole breakouts and dominantly NE–SW striking normal faults interpreted from seismic reflection data. The normal/ strike-slip regime in this area suggests that the stress regime here is probably influenced by the effect of the clockwise rotation of the HSM hangingwall associated with oblique Pacific-Australia plate convergence (ENE-WSW). Alternatively, these stress states could be the result of gravitational collapse due to rapid uplift of the subducting plate during the mid-Miocene. The compressional stress regime in the southern HSM in Titihaoa-1 and Tawatawa-1 is in agreement with the SHmax orientations of 148° ± 14° (NW-SE ) and 102° ± 16° (WNW-ESE) obtained from image logs and mapped NE–SW striking reverse faults in this region. This observation suggests that the tectonics here are strongly linked to the subduction of Hikurangi plateau under Australian Plate (NW-SE) or active frontal thrusts in the overriding plate. 
Morphometric analysis of the terrain over time to characterize subsidence. Case study: Mexico City, Mexico.
Authors: Vidal Gabriela , Nieto Butrón Jacob , Hernández Hernández Mario Alberto , Herrera Zamarrón Graciela , Cabral Cano Enrique , Yépez Rincón Fabiola Doracely , Ramírez Serrato Nelly Lucero
Published: March 2021

It is well known that groundwater overexploitation can generate land subsidence due to the compaction of compressible aquitards. Mexico City's soils are an important example of highly compressible lake sediments in compaction due to groundwater extraction that have significantly damaged the urban and commercial building structures. Previous studies indicate that there is annual subsidence of 15 to 25 cm in the Mexico City International Airport, 10 cm in downtown, and between 10 to 15 cm in the Southeast Mexico City area. Soil fracturing is an indicator of differential subsidence that has damaged buildings and infrastructure, including hydraulic pipes, sidewalks, and pavements. For this reason, it is necessary to carry out specific studies related to topographic deformation. This talk presents a characterization of the terrain changes over time and a zoning map for Mexico City subsidence susceptibility. To this end, free access elevation models generated from 2000 to 2018 by different sensors and methodologies were compared. The resulting model is validated by mapping information from active GPS stations, whose data is also freely available. Besides, a spatial comparison of land subsidence areas and sites previously identified as flooding and aquifer overexploitation areas is presented. The results will serve as a basis for future monitoring to be carried out in the area with high-resolution tools.
Indian Ocean mediates the ENSO teleconnections to the Central Southwest Asia during the wet season 
Authors: Abid Muhammad Adnan , Ashfaq Moetasim , Kucharski Fred , Evans Katherine J. , Almazroui Mansour
Published: March 2021

Central Southwest Asia (CSWA) is a region with the largest number of glaciers, outside the polar regions in its northeast and the Arabian desert to its southwest. The region receives precipitation from November to April period also known as the wet season, which contributes to the regional freshwater resources. Mainly, El Niño–Southern Oscillation (ENSO) modulates the wet season precipitation over CSWA, with a positive relationship. However, the intraseasonal characteristics of ENSO influence are largely unknown, which may be important to understand the regional sub-seasonal to seasonal hydroclimate variability. We noted that the ENSO‐CSWA teleconnection varies intraseasonally and is a combination of direct and indirect positive influences. The ENSO direct influence is through a Rossby wave‐like pattern in the tail months of the wet season, while the indirect influence is noted through an ENSO‐forced atmospheric dipole of diabatic heating anomalies in the tropical Indian Ocean (TIO), which also generates a Rossby wave‐like forcing and persists throughout the wet season. The stronger ENSO influence is found when both direct and indirect modes are in phase, while the relationship breaks down when the two modes are out of phase. Moreover, the idealized numerical simulations confirm and reproduce the observed circulation patterns. This suggests that improvements in sub-seasonal to seasonal scale predictability requires the better representation of intraseasonal variability of ENSO teleconnection, as well as the role of interbasin interactions in its propagation.
The information content of skylight polarisation in MAX-DOAS trace gas- and aerosol profiling applications 
Authors: Tirpitz Jan-Lukas , Frieß Udo , Platt Ulrich
Published: March 2021

Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) is a well-established measurement technique for the detection of atmospheric aerosol and trace gases: ultra-violet and visible radiation spectra of skylight are analyzed to obtain information on different atmospheric parameters. An appropriate set of spectra recorded under different viewing geometries ("Multi-Axis") allows retrieval of aerosol and trace gas vertical distributions as well as aerosol properties by applying numerical inversion methods. Currently one of the method’s major limitations in ground-based applications is the limited information contained in the measurements that reduces the sensitivity, particularly at higher altitudes.

It is well known but not yet used in MAX-DOAS profile retrievals that measuring skylight of different polarisation directions provides additional information: The degree of polarisation for instance strongly depends on the atmospheric aerosol content and the aerosol properties and – since the light path differs for the light of different polarisation -  the set of geometries available for the inversion is extended. We present a novel polarization-sensitive MAX-DOAS instrument (PMAX-DOAS) and a corresponding inversion algorithm, capable of using polarimetric information to significantly extend the information content of the measurements. The improvement over conventional “unpolarised” MAX-DOAS approaches will be discussed, based on both, synthetic data and real measurements.
Double-scale diffusive wave model dedicated to spatial river observation and associated covariance kernel for variational data assimilation 
Authors: Malou Thibault , Monnier Jérome
Published: March 2021

The spatial altimetry provides an important amount of water surface height data from multi-missions satellites (especially Jason-3, Sentinel-3A/B and the forthcoming NASA-CNES SWOT mission). To exploit at best the potential of spatial altimetry, the present study proposes on the derivation of a model adapted to spatial observations scale; a diffusive-wave type model but adapted to a double scale [1].

Moreover, Green-like kernel can be employed to derived covariance operators, therefore they may provide an approximation of the covariance kernel of the background error in Variational Data Assimilation processes. Following the derivation of the aforementioned original flow model, we present the derivation of a Green kernel which provides an approximation of the covariance kernel of the background error for the bathymetry (i.e. the control variable) [2].

This approximation of the covariance kernel is used to infer the bathymetry in the classical Saint-Venant’s (Shallow-Water) equations with better accuracy and faster convergence than if not introducing an adequate covariance operator [3].

Moreover, this Green kernel helps to analyze the sensitivity of the double-scale diffusive waves (or even the Saint-Venant’s equations) with respect to the bathymetry.

Numerical results are analyzed on real like datasets (derived from measurements of the Rio Negro, Amazonia basin).

The double-scale diffusive wave provide more accurate results than the classical version. Next, in terms of inversions, the derived physically-based covariance operators enable to improve the inferences, compared to the usual exponential one.

[1] T. Malou, J. Monnier "Double-scale diffusive wave equations dedicated to spatial river observations". In prep.

[2] T. Malou, J. Monnier "Physically-based covariance kernel for variational data assimilation in spatial hydrology". In prep.

[3] K. Larnier, J. Monnier, P.-A. Garambois, J. Verley. "River discharge and bathymetry estimations from SWOT altimetry measurements". Inv. Pb. Sc. Eng (2020).
Supraglacial lake bathymetry automatically derived from ICESat-2 constraining lake depth estimates from multi-source satellite imagery
Authors: Wouters Bert , Datta Rajashree Tri
Published: March 2021

We introduce an algorithm (Watta), which automatically calculates supraglacial lake bathymmetry and potential ice layers along tracks of the ICESat-2 laser altimeter. Watta uses photon heights estimated by the ICESat-2 ATL03 product and extracts supraglacial lake surface, bottom, corrected depth and (sub)surface ice cover in addition to producing surface heights at the native resolution of the ATL03 photon cloud. These measurements are used to constrain empirical estimates of lake depth from satellite imagery, which were thus far dependent on sparse sets of in-situ measurements for calibration. Imagery sources include Landsat OLI, Sentinel-2 and high-resolution Planet Labs PlanetScope and SkySat data, used here for the first time to calculate supraglacial lake depths.

The Watta algorithm was developed and tested using a set of 46 lakes near Sermeq Kujalleq (Jakobshavn) glacier in Western Greenland, and we use multiple imagery sources to assess the use of the red vs green band to extrapolate depths along a profile to full lake volumes. We use Watta-derived estimates in conjunction with high-resolution imagery from both satellite-based sources (tasked over the season) and nearly-simultaneous Operation IceBridge CAMBOT imagery (on a single airborne flight) for a focused study of the drainage of a single lake over the 2019 melt season.   Our results suggest that the use of multiple imagery sources (both publicly-available and commercial) in combination with altimetry-based depths, can move towards capturing the evolution of supraglacial hydrology at improved spatial and temporal scales.
Improving Ocean Circulations Using Lagrangian Data Assimilation of Surface Drifters During Grand Lagrangian Deployments
Authors: Sun Luyu , Penny Stephen , Harrison Matthew
Published: March 2021

Accurate forecast of ocean circulation is important in many aspects. A lack of direct ocean velocity observations has been one of the overarching issues in nowadays operational ocean data assimilation (DA) system. Satellite-tracked surface drifters, providing measurement of near-surface ocean currents, have been of increasing importance in global ocean observation system. In this work, the impact of an augmented-state Lagrangian data assimilation (LaDA) method using Local Ensemble Transform Filter (LETKF) is investigated within a realistic ocean DA system. We use direct location data from 300 surface drifters released in the Gulf of Mexico (GoM) by the Consortium for Advanced Research on Transport of Hydrocarbon in the Environment (CARTHE) during the summer 2012 Grand Lagrangian Deployment (GLAD) experiment. These drifter observations are directly assimilated into a realistic eddy-resolving GoM configuration of the Modular Ocean Model version 6 (MOM6) of the Geophysical Fluid Dynamics Laboratory (GFDL). Ocean states (T/S/U/V) are updated at both the surface and at depth by utilizing dynamic forecast error covariance statistics. Four experiments are conducted: (1) a free run generated by MOM6; 2) a DA experiment assimilating temperature and salinity profile observations from World Ocean Database 2018 (WOD18); and 3) a DA experiment assimilating both drifter and the profile observations. The LaDA results are then compared with the traditional assimilation using the drifter-derived velocity field from the same GLAD database. In addition, we evaluate the impact of the LaDA algorithm on different eddy-permitting and eddy-resolving model resolutions to determine the most effective horizontal resolutions for assimilating drifter position data using LaDA.
Accelerating Climate Model Computation by Neural Networks: A Comparative Study
Authors: Mdini Maha , Miyoshi Takemasa , Otsuka Shigenori
Published: March 2021

In the era of modern science, scientists have developed numerical models to predict and understand the weather and ocean phenomena based on fluid dynamics. While these models have shown high accuracy at kilometer scales, they are operated with massive computer resources because of their computational complexity.  In recent years, new approaches to solve these models based on machine learning have been put forward. The results suggested that it be possible to reduce the computational complexity by Neural Networks (NNs) instead of classical numerical simulations. In this project, we aim to shed light upon diﬀerent ways to accelerating physical models using NNs. We test two approaches: Data-Driven Statistical Model (DDSM) and Hybrid Physical-Statistical Model (HPSM) and compare their performance to the classical Process-Driven Physical Model (PDPM). DDSM emulates the physical model by a NN. The HPSM, also known as super-resolution, uses a low-resolution version of the physical model and maps its outputs to the original high-resolution domain via a NN. To evaluate these two methods, we measured their accuracy and their computation time. Our results of idealized experiments with a quasi-geostrophic model [SO3] show that HPSM reduces the computation time by a factor of 3 and it is capable to predict the output of the physical model at high accuracy up to 9.25 days. The DDSM, however, reduces the computation time by a factor of 4 and can predict the physical model output with an acceptable accuracy only within 2 days. These ﬁrst results are promising and imply the possibility of bringing complex physical models into real time systems with lower-cost computer resources in the future.
Assimilation of Nonlinear Observations with the Maximum Likelihood Ensemble Filter
Authors: Nakashita Saori , Enomoto Takeshi
Published: March 2021

Satellite observations have been a growing source for data assimilation in the operational numerical weather prediction. Remotely sensed observations require a nonlinear observation operator.  Most ensemble-based data assimilation methods are formulated for tangent linear observation operators, which are often substituted by nonlinear observation operators. By contrast, the Maximum Likelihood Ensemble Filter (MLEF), which has features of both variational and ensemble approaches, is formulated for linear and nonlinear operators in an identical form and can use non-differentiable observation operators. 

In this study, we investigate the performance of MLEF and Ensemble Transform Kalman Filter (ETKF) with the tangent linear and nonlinear observation operators in assimilation experiments of nonlinear observations with a one-dimensional Burgers model.

The ETKF analysis with the nonlinear operator diverges when the observation error is small due to unrealistically large increments associated with the high order observation terms. The filter divergence can be avoided by localization of the extent of observation influence, but the analysis error is still larger than that of MLEF. In contrast, MLEF is found to be more stable and accurate without localization owing to the minimization of the cost function. Notably, MLEF can make an accurate analysis solution even without covariance inflation, eliminating the labor of parameter adjustment. In addition, the smaller observation error is, or the stronger observation nonlinearity is, MLEF with the nonlinear operators can assimilate observations more effectively than MLEF with the tangent linear operators. This result indicates that MLEF can incorporate nonlinear effects and evaluate the observation term in the cost function appropriately. These encouraging results imply that MLEF is suitable for assimilation of satellite observations with high nonlinearity.
The effect of preservation on diversity in a Triassic reef basin assemblage
Authors: Roden Vanessa Julie , Nützel Alexander , Kiessling Wolfgang
Published: March 2021

Taphonomic effects complicate the assessment of variations in biodiversity over time. Most pre-Cenozoic fossil assemblages have been altered through taphonomic effects, such as lithification and aragonite dissolution. Several studies have found alpha (local) and gamma (global) diversity in marine ecosystems to be low in the early Mesozoic and then increase throughout the Mesozoic, reaching a maximum in the Cenozoic.

The Middle to Late Triassic Cassian Formation, exposed in the Dolomites, Southern Alps, northern Italy, comprises tropical reef basin and transported platform assemblages characterized by high diversity and commonly excellent preservation of fossils. The Cassian Formation yields high alpha (mean species richness per locality: 96), beta (mean Jaccard dissimilarity: 0.95), and gamma (1421 invertebrate species) diversity. The high primary diversity is probably due to the tropical reef-associated setting, and its reduced taphonomic alteration caused 4.5 times higher biodiversity to be preserved than in comparable pre-Cenozoic settings. High beta diversity can be explained by the presence of various habitat types and may also have been driven by priority effects. The Cassian fauna, like most comparable modern ecosystems, features a large number of gastropods (39% of all invertebrates, 58% of mollusks are gastropods). Especially small species in the millimeter size range contribute to the large number of gastropod species in the Cassian Formation. Our results support the assumption that the Modern Evolutionary Fauna was already established early in the Mesozoic and that the scarcity of small gastropods in many fossil assemblages is a taphonomic phenomenon. This contradicts the view that the major radiation of gastropods and the generally very strong increase in biodiversity largely took place in the Cenozoic. We suggest that highly complex, gastropod-dominant marine benthic ecosystems are as old as Middle/Late Triassic, pointing to an earlier establishment of the Modern Evolutionary Fauna than previously assumed. An improved eco-space utilization by infaunalization and increased biotic interactions such as a predator/prey escalation may have contributed to the high biodiversity and may reflect early aspects of the Marine Mesozoic Revolution.
An adaptive inversion algorithm for one-dimensional magnetotelluric problems
Authors: Chen Huang , Ren Zhengyong , Tang Jingtian
Published: March 2021

      As we know, the traditional one-dimensional (1-D) magnetotelluric (MT) regularization inversion needs the geometry model of the 1-D Earth conductivity model, i.e., the number of layers and the thickness of each layer to be given in advance and cannot be changed during the inversion. In this way, too few layers cannot approximate the 1-D conductivity model accurately, while too many layers will increase the non-uniqueness of the inversion problem and hence may result in unreasonable results. Aiming to solve this issue, an adaptive inversion algorithm has been proposed for 1-D MT problems, where the layer number and the thickness of each layer can be adjusted automatically during the inversion process. To this end, three pseudo a-posterior error estimators has been proposed to guide the adjustment of the 1D geometry model, which are based on the gradient of the data misfit term of the penalty function, the diagonal elements of the model resolution matrix, and the weighted elements of the sensitivity matrix, respectively. The inversion results of the synthetic and field data by using our proposal adaptive inversion algorithm and the traditional regularization inversion not only validate the proposed algorithm, but also show that our proposed algorithm can obtain more accurate and reasonable results than traditional one. Subsequently, the proposed algorithm will be extended for 3-D magnetotelluric inversion problems soon.
Large-sample based evaluation of the spatial resolution discretization of the wflow_sbm model for the CAMELS dataset
Authors: Aerts Jerom , Weerts Albrecht , van Verseveld Willem , Hazenberg Pieter , Drost Niels , Hut Rolf , van de Giesen Nick
Published: March 2021

In this study, we investigate the effect of spatial resolution discretization at 3km, 1km, and 200m by evaluating the streamflow estimation of the model. A hypothesis driven approach is used to investigate why changes in states and fluxes are taking place at different spatial resolutions and how they relate to model performance. These changes are evaluated in the context of landscape and climate characteristics as well as hydrological signatures. Answering the research question: can landscape, climate and hydrological characteristics dictate appropriate spatial modelling resolution a priori?

We use a spatially distributed wflow_sbm model (Imhoff et al., 2020, code: https://zenodo.org/record/4291730) together with the CAMELS dataset (Addor et al., 2017), covering the Continental United States. The wflow_sbm model is chosen due to flexibility in the spatial resolution of the watershed discretization while maintaining run time performance suitable for large-sample studies. The flexibility in spatial resolution is achieved by the use of point-scale (pedo)transfer functions (PTFs) with upscaling rules to global datasets to ensure flux matching across scales (Imhoff et al., 2020; Samaniego et al., 2010, 2017). The model relies on open datasets for parameter estimation and requires minimal calibration efforts as it is most sensitive to two model parameters, rooting depth and horizontal conductivity .

This study is carried out within the eWaterCycle framework; allowing for a FAIR by design research setup that is scalable in terms of case study areas and hydrological models.
An efficient and accurate method for obtaining regional scale rice growth conditions based on WOFOST model and satellite images
Authors: Zhao Bingyu , Liu Meiling , Wu Jiianjun , Liu Xiangnan , Liu Mengxue , Wu Ling
Published: March 2021

It is very important to obtain regional crop growth conditions efficiently and accurately in the agricultural field. The data assimilation between crop growth model and remote sensing data is a widely used method for obtaining vegetation growth information. This study aims to present a parallel method based on graphic processing unit (GPU) to improve the efficiency of the assimilation between RS data and crop growth model to estimate rice growth parameters. Remote sensing data, Landsat and HJ-1 images were collected and the World Food Studies (WOFOST) crop growth model which has a strong flexibility was employed. To acquire continuous regional crop parameters in temporal-spatial scale, particle swarm optimization (PSO) data assimilation method was used to combine remote sensing images and WOFOST and this process is accompanied by a parallel method based on the Compute Unified Device Architecture (CUDA) platform of NVIDIA GPU. With these methods, we obtained daily rice growth parameters of Zhuzhou City, Hunan, China and compared the efficiency and precision of parallel method and non-parallel method. Results showed that the parallel program has a remarkable speedup (reaching 240 times) compared with the non-parallel program with a similar accuracy. This study indicated that the parallel implementation based on GPU was successful in improving the efficiency of the assimilation between RS data and the WOFOST model and was conducive to obtaining regional crop growth conditions efficiently and accurately.
Quantifying the lobe reconnection rate during dominant IMF By periods
Authors: Reistad Jone Peter , Laundal Karl Magnus , Ohma Anders , Østgaard Nikolai , Hatch Spencer , Haaland Stein , Thomas Evan
Published: March 2021

Lobe reconnection is usually considered to play an important role in geospace dynamics only when the Interplanetary Magnetic Field (IMF) is mainly northward. This is because the most common signature of lobe reconnection is the strong sunward convection in the polar cap ionosphere observed during these conditions. During more typical conditions, when the IMF is mainly in a dawn-dusk direction, plasma flows initiated by dayside as well as lobe reconnection map to high latitude ionospheric locations in close proximity to each other. This has been emphasized in the literature earlier, mainly on a conceptual level, but quantifying the relative importance of lobe reconnection to the observed ionospheric convection is highly challenging during these IMF By dominated conditions, since one has to identify and distinguish these regions. By normalizing the ionospheric convection (observed by SuperDARN) to the polar cap boundary (inferred from simultaneous AMPERE observations), we are able to do this separation, allowing us to quantify the relative contribution of both lobe reconnection and dayside/nightisde reconnection to the ionospheric convection pattern. Using this segmentation technique we can get new quantitative insights into the importance of the various mechanisms that affect the lobe reconnection rate. In this presentation we will describe the technique and show results of analysis of periods when the IMF is mainly in the dawn-dusk direction. Our quantification of the average lobe reconnection rate during various conditions yields quantitative knowledge of the importance of the lobe reconnection process, which can act independently in the two hemispheres. We will specifically constrain the influence from parameters such as the dipole tilt angle and the product of IMF transverse component and solar wind velocity.
The early postseismic phase of Tohoku-Oki earthquake (2011) from kinematics solutions: implication for subduction interface dynamics
Authors: Periollat Axel , Radiguet Mathilde , Weiss Jérôme , Twardzik Cédric , Marill Lou , Cotte Nathalie , Socquet Anne
Published: March 2021

Earthquakes are usually followed by a postseismic phase where the stresses induced by the earthquakes are relaxed. It is a combination of different processes among which aseismic slip on the fault zone (called afterslip), viscoelastic deformation of the surrounding material, poroelastic relaxation and aftershocks. However, little work has been done at the transition from the co- to the postseismic phase, and the physical processes involved.

We study the 2011 Mw 9.0 Tohoku-Oki earthquake, one of the largest and most instrumented recent earthquake, using GEONET GPS data. We focus on the few minutes to the first month following the mainshock, a period dominated by afterslip.

Based on the method developed by Twardzik et al. (2019), we process 30-s kinematic position time series and we use it to characterize the fast displacements rates that typically occur during the early stages of the postseismic phase. We quantify precisely the co-seismic offset of the mainshock, without including early afterslip, and we also characterize the co-seismic offset of the Mw 7.9 Ibaraki-Oki aftershock, which occurred 30 minutes after the mainshock. We analyze the spatial distribution of the co-seismic offsets for both earthquakes. We also use signal induced by the postseismic phase over different time windows to investigate the spatio-temporal evolution of the postseismic slip. We determine the redistribution of stresses to estimate the regional influence of the mainshock and aftershock on postseismic slip.

From a detailed characterization of the first month of postseismic kinematic time series, we find that the best-fitting law is given by an Omori-like decay. The displacement rate is of the type v0/(t+c)p with spatial variation for the initial velocity v0 and for the time constant c. We find a consistent estimate of the p-value close to 0.7 over most of the studied area, apart from a small region close to the aftershock location where higher p values (p~1) are observed. This p value of 0.7 shows that the evolution of the Tohoku-Oki early afterslip is not logarithmic. We discuss about the implications of these observations in terms of subduction interface dynamics and rheology. We also discuss about the different time-scales involved in the relaxation, and how this model, established for the early postseismic phase over one month, performs over longer time scales (by comparison with daily time series lasting several years).

Twardzik Cedric, Mathilde Vergnolle, Anthony Sladen and Antonio Avallone (2019), doi.org/10.1038/s41598-019-39038-z

Keywords: Early Postseismic, Afterslip, GPS, Kinematic, Omori Law
Spatial estimation of snow water equivalent by modeling of the melting of seasonal snow and glacier in Iceland
Authors: Gunnarsson Andri , Garðarsson Sigurður M. , Jóhannesson Tómas , Pálsson Finnur
Published: March 2021

Runoff from seasonal snow- and glacier melt is critical for hydropower production and reservoir storage in Iceland as the energy system is strongly dependent on summer inflow. The isolation and high natural climate variability can pose a risk to the energy security of the power system as drought conditions and low-flow periods are usually not foreseen in great advance. Forecasting the timing, spatial distribution and magnitude of seasonal melt is a challenge and influences the operational control of energy infrastructure and long-term resource planning. As hydropower generation provides over 72% of the total average energy produced in Iceland, accurate forecasting of seasonal melt is essential for the operation of the national power system.

In this study, we present results from a spatially-distributed energy-balance model combined with gap-filled satellite-based time series of fractional snow cover and surface albedo from MODIS. The model reconstructs seasonal snow and glacier melt for the Icelandic highlands providing insight into the spatio-temporal distribution of snow water equivalent over the study period.  The reconstruction method uses daily, satellite-derived estimates of fractional snow cover and albedo to scale the melt flux at every pixel. Modeled snow melt was integrated over time, reconstructing the maximum snowpack/glacier melt for each year. The model runs at a 500 m spatial resolution, with a daily timestep from 1 March to 30 September during 2000 to 2019 spanning the general seasonal snow and glacier melt period.

Energy-balance components were validated with in-situ observations from the Icelandic highlands and a network of stations operated annually at various Icelandic glaciers. Ground-based measurements of snow water equivalent (snow pits, surface mass balance) were used to validate the model performance as well as discharge observations. Simulations indicate a good performance compared with summer glacier mass balance records from Vatnajökull, Hofsjökull, Langjökull and Mýrdalsjökull. Sparse and discontinuous measurements of seasonal snow water equivalent from snow pillows or transects from snow courses were available from a few location, providing limited capabilities for direct validation for seasonal snow. Discharge observations in highland catchments indicate acceptable performance.

The results allow for quantification of the spatial distribution of snow water equivalent, relationships to elevation and other topographical parameters as well as between basins and years. Discrimination between seasonal snow and glacier melt on a catchment scale is valuable to analyze the annual variability in these two critical hydrological water sources and how they are related.
European-Adriatic plate collision in teleseismic tomography of the Eastern Alps
Authors: Plomerova Jaroslava , Zlebcikova Helena , Hetenyi Gyorgy , Vecsey Ludek , Babuska Vladislav , Working Group AlpArray
Published: March 2021

We present potential scenarios of the European and Adriatic plates’ collision that formed the Alps and the neighbouring mountain belts. Our results are based on teleseismic body-wave data from the AlpArray-EASI complementary experiment (2014-2015, Hetényi et al., Tectonophysics 2018) and the AlpArray Seismic Network (Hetényi et al., Surv. Geophys. 2018).  Tomography of seismic velocities in the upper mantle along a ca. 200 km broad and 540 km long north-south transect images steady southward thickening of the lithosphere beneath the Bohemian Massif  and northward dipping East-Alpine lithospheric keel. Thanks to the dense spacing of the AlpArray Seismic Network stations and high-quality data, the high-resolution tomography resolves for the first time two sub-parallel down-going high-velocity heterogeneities beneath the Eastern Alps, instead of a single, thick anomaly. The southern heterogeneity, which we relate to the subducted Adriatic plate, is more distinct than the northern one, which loses its connection with the shallow parts. Moreover, amplitudes and size of this heterogeneity decrease in cross-sections perpendicular to the strike of the Alps when shifting towards the Central Alps. The presented collision scenarios consider the smaller northern heterogeneity as (1) a remnant of a delaminated early phase subduction of the European plate with the reversed polarity relative to that in the Western Alps, (2) a piece of continental and oceanic lithosphere together, or, (3) a fragment of a quite extended lithosphere margin foundering in a preceding phase of the Adriatic subduction.
Changing spatial patterns of deep convection in the subpolar North Atlantic
Authors: Rühs Siren , Oliver Eric , Biastoch Arne , Böning Claus W. , Dowd Michael , Getzlaff Klaus , Myers Paul G.
Published: March 2021

Deep convection and associated deep water formation are key processes for climate variability, since they impact the oceanic uptake of heat and trace gases and alter the structure and strength of the global overturning circulation. For long, deep convection in the subpolar North Atlantic was thought to be confined to the central Labrador Sea in the western subpolar gyre (SPG). However, there is increasing evidence that deep convection also occurs in the eastern SPG south of Cape Farewell and in the Irminger Sea. In particular, observations indicate gyre-scale intensified convection in 2015-2018. Here we assess this recent event in the context of the temporal evolution of the spatial deep convection pattern in the SPG since the mid-twentieth century, using realistic eddy-rich ocean model simulations. These reveal large interannual variability, including several periods with intensified deep convection in the eastern SPG. Notably, this happened in 2015-2018, but to a lesser degree in the late 1980s to early 1990s, the period with highest deep convection intensity in the Labrador Sea related to a persistent positive phase of the North Atlantic Oscillation. Our analyses further suggest that deep convection in 2015-2018 occurred with an unprecedented high (low) relative contribution of the eastern (western) SPG to the total deep convection volume. This is partly linked to a considerable smaller north-westward extent of deep convection in the Labrador Sea compared to previous periods of intensified deep convection, and may be a first fingerprint of strong near-surface freshening in the Labrador Sea associated with Greenland melting.
Scalings for subglacial discharge driven circulation in Greenland's proglacial fjords
Authors: Stanway Adam , Wells Andrew , Johnson Helen , Ridley Jeff
Published: March 2021

Around Greenland, the transport of heat and fresh meltwater between the ocean and Greenland's Ice Sheet is mediated by circulation in several hundred proglacial fjords. These fjords are long and narrow, with circulation controlled by a variety of processes. This circulation, and the resultant heat transported to the ice sheet has global implications. However, the spatial scales of these fjords means that they cannot be directly represented in global scale climate models, as currently achievable horizontal resolutions are too coarse to resolve fjords directly. Therefore, a subgrid-scale parameterization scheme is required, to include the impact of fjord circulation on Greenland's Ice Sheet in these models. The development of such a scheme requires increased theoretical understanding, with the aim of capturing the circulation response simply, over a relevant range of the parameter space.

Current climate models add freshwater runoff from Greenland's Ice Sheet into the ocean model in the surface grid cell, and do not account for the impacts of fjord circulation on melt rates at glacial termini. Therefore, we focus on predicting the depth at which fresh meltwater enters the wider ocean, and the flow structure at the ice face itself, to understand the feedback on ice melt rates. We consider a subglacial discharge driven regime, with a localised source of subglacial discharge into the fjord at the glacial grounding line. We employ a combination of computational modelling using idealised configurations in MITgcm, and theoretical explorations, to capture this circulation as simply as possible. For fjords without sills, we find that the cross-fjord integrated velocity profile at the fjord mouth echoes that at the ice face. Further, we find that a horizontal recirculation cell develops at the ice face, as the fjord responds to horizontal velocities driven by the plume itself, generating flow across the entire ice face. We use scaling laws previously developed for turbulent plumes to provide a simple prediction of the cross-fjord integrated velocity structure at the fjord mouth, predicting the depth level at which meltwater enters the wider ocean. We develop theoretical predictions for the cross-fjord flow at the ice face, as a consequence of the flow directly induced by a buoyant plume and the circulation response in the fjord, allowing prediction of the pattern of melt across the ice face.
Development of debris cover and changes in fluvial sediments at Eastern Alpine glaciers
Authors: Helfricht Kay , Hiller Clemens , Hohensinner Severin , Schwaizer Gabriele , Haas Florian , Fischer Andrea , Achleitner Stefan
Published: March 2021

High mountain environments showed substantial geomorphological changes forced by rising temperatures over the past 150 years. Glacier retreat is the most visible manifestation of climate change in alpine areas and has a significant impact on glacier land systems, high mountain runoff and, thus, on sediment transport in headwaters. Downwasting glaciers face an increase debris cover due to sediment flux onto glacier surfaces and melt out of englacial debris. Continuous debris transport from the glacier to the glacier forefield enhances its sediment available for being mobilized in case of higher or extreme runoff events.

The presented results arise from the Hidden.Ice project, which serves to investigate the hydrological impact of supraglacial debris deposits in the transition zone from glacier ice to the proglacial area. A detailed study focusses on the debris connectivity to bed load transport at the LTER site Jamtalferner (Silvretta mountains, Austria) and the evolution of the debris cover on glaciers in Austria.

A first spatio-temporal analysis of the long-term land cover evolution along the river channel from historical maps and remote sensing data shows increasing shares of fluvial sediments to about 12% of the area deglaciated after the LIA glacier maximum until the 1920s. However, the ongoing exposure of additional sediment plains is compensated by sediment export and covering of former stream banks by vegetation at decadal scale. Vegetation developed on up to 20% of the area in a 50 m buffer around the present glacier stream. This complementary documentation increases our knowledge on the temporal evolution of the sediment-rich proglacial zone evolved with glacier retreat.

To tackle the present interaction of the debris-covered glacier tongue with the runoff, the connectivity of supraglacial debris to bed load transport is estimated based on multi-annual and sub-seasonal high-resolution surface information. The underlying point cloud analysis employs Structure-from-Motion photogrammetry from UAV surveys and airborne laser scanning acquisitions. The deposition and renewed movement of debris in the glacier forefield is calculated from sediment volume changes. Strong variations in the stream position suggest high connectivity of the entire proglacial sediment body to bed load transport, and considerable shifts of the main channel have been documented from year to year. Multi-spectral analysis of Landsat and Sentinel-2 optical satellite data time series from 1985 to 2020 show the development of debris cover on glaciers in the study region with increasing relative share of total glacier area over the past decades.
Development of a Next Generation Drought Index: combining multiple global and local data sources to enable detection of sector-specific drought impacts
Authors: Hendriks Dimmie , Hazenberg Pieter , Gotte Jonas , Trambauer Patricia , Haag Arjen , Donchyts Gennadii , Sperna Weiland Frederiek
Published: March 2021

An increasing number of regions and countries are confronted with droughts as well as an increase in water demand. Inevitably, this leads to an increasing pressure on the available water resources and associated risks and economic impact for the water dependent sectors. In order to prevent big drought impacts, such as agricultural damage and food insecurity, timely and focused drought mitigation measures need to be carried out. To enable this, the detection of drought and its sector-specific risks at early stages needs to be improved. One of the main challenges is to develop compound and impact-oriented drought indices, that make optimal use of innovative techniques, satellite products, local data and other big data sets.

Here, we present the development of a Next Generation Drought Index (NGDI) that combines multiple freely available global data sources (eg. ERA5, MODIS, PCR-GLOBWB) to calculate a range of relevant drought hazard indices related to meteorological, hydrological, soil moisture and agricultural drought (eg. SPI, SPEI, SRI, SGI, VCI). The drought hazard indices are aggregated at district level, while considering the percentage area exposure of the drought impacted sector (exposure). In addition, the indices are enriched with local and national scale drought impact information (eg. online news items, social media data, EM-DAT database, GDO Drought news, national drought reports). Results are presented at sub-national scales in interactive spatial and temporal views, showing the combined drought indices and impact data.

The NGDI approach is being tested for the agricultural sector in Mali, a country with a vulnerable population and economy that faces frequent dry spells which heavily impact the functioning of the important agricultural activities that sustain a large part of the population. The computed drought indices are compared with local drought data and an analysis is made of the cross-correlations between the indices within the NGDI and collected impact data.

We aim at providing the NGDI information to a broad audience as well as co-creation of further NGDI developments. Hence, we would like to reach out to interested parties and identify collaboration opportunities.
The HYPOS project as a support to the hydroelectric sector
Authors: Matta Erica , Bresciani Mariano , Giardino Claudia , Amadori Marina , Heege Thomas , Schenk Karin , Knauer Kim , Bartosovar Alena , Pechlivanidis Ilias , Ribeiro Marcelo Leite , Launay Marina , Matos José Pedro , Kelleher Declan , Rüther Nils , Schwarzwälder Kordula Valerie Anne
Published: March 2021

The EC HYPOS (HYdro-POwer-Suite) project (https://hypos-project.eu/) has the main goal of assessing the environmental impact of existing and future hydropower systems. The project will provide a suite of data analysis applications which integrates Earth Observation (EO) technologies and hydrological modelling. These include an online Decision Support Tool (DST) for investment planning and monitoring, as well as a subscription portal combining satellite data over time, current measurements and detailed estimates for present and near future assessments. A dedicated analysis on the “blue footprint” (i.e. the amount of water used to produce a service) of reservoirs is included for addressing sustainable monitoring solutions. Such analysis comprises the evaluation of the climate change effects on reservoirs management and hydropower production. For instance, extreme weather events like short-term heavy precipitations are connected with flooding and transport of large amounts of sediments in dammed reservoirs, with critical consequences for their management. Similarly, global warming can heat the surface of water bodies and induce higher evaporation rates, thus decreasing the amount of water available for energy production.  

In this study we present the first products from HYPOS project. These products are representative of what can be generated within the DST using elaboration techniques of EO data. Gridded products of water quality parameters (e.g. water turbidity, Chlorophyll-a concentration, suspended sediments concentration) are generated for the test sites of the project, which are small dammed reservoirs located in Switzerland, France, Albania and Georgia. These products are obtained using the Modular Inversion and Processing System (MIP), a sensor independent image processing chain based on radiative transfer models, which works in a multi-layer system, solving the light transfer in the atmosphere, at the water surface and inside the waterbody.

For the assessment of the “blue footprint” of a reservoir, the water loss due to evaporation is computed by applying a consolidated mass transfer evaporation method to EO data. The resulting evaporation rates are first compared with the outputs of semi-automatic evapotranspiration EO-based models (e.g. SEBAL), and then with the estimates ​​obtained from two different numerical models: a hydrological model (E-Hype) and a 3D hydrodynamic model (Delft3D). The key parameters influencing water evaporation rates, their behavior and the issues related to each approach are analyzed. The first comparison results are made for lake Garda, where a complete set of data is available for the production of evaporation maps.