Man-made terraces for agricultural purposes are a quite diffuse and ancient anthropogenic landscape modification in mountainous areas. The original slope alteration, obtained through a sequence of sub-vertical and sub-planar surfaces, represents a human interference with the geomorphic system, altering the original balance of geomorphological and geo-hydrological factors. Stone walls and soil formed by human activity have been artificially immobilized on the slopes and are available again to gravitative processes once in abandonment and may be subject to deep degradation in case of intense rain events. However, socio-economic conditions play often a crucial role in the abandonment of terraces, indirectly contributing to increase gully erosion and walls failure. The modification of the original slope profile, due to its regular geometry in respect to the typical more complex natural surface, is rather suitable to be detected through remote sensing, particularly LIDAR, as many authors have recently demonstrated. In the present research the attention has been focused on the assessment of terraces and of the volume of stones and soil that have been involved by human activity. The research area is among the most deeply modified by terraces in the Mediterranean area and internationally famous for this landscape anthropogenic alteration: The Cinque Terre in Italy is a National Park intensively visited by tourists all over the year. Then terraces represent an important economic asset that need to be preserved from degradation and collapse as partially occurred in 2011 after the intense rain event that caused flood, hundreds of landslides and consequently damage. During the 2011 event many terraced slopes have collapsed with significant loss of soil and stone walls: the research allowed to evaluate the lost volumes and to estimate the remaining ones in the Vernazza catchment.

The quality of groundwater (GW) has deteriorated rapidly, which causes many serious threats owing to the exposure of many contaminants to the environment and living creatures. In the last three decades, Permeable Reactive Barrier (PRB) has been proven an efficient and well-established in-situ GW remediation technology for treating various contaminated sites around the world. In this study, the long-term performance of an in-situ PRB has been evaluated by three-dimensional numerical modelling using Visual MODFLOW for the simultaneous treatment of three different contaminants, nitrate (NO3-), phosphate (PO43-) and hexavalent chromium Cr(VI), from GW. The selected materials for PRB are considered as a mixture of five different low cost-reactive materials, i.e., rise husk (RH), fly ash (FA), quartz sand (QS), activated charcoal (AC), and activated alumina (AA), in an optimized proportion. Initially, the model has been simulated for a period of 10 years to obtain the natural attenuation of contaminant plume, with NO3-, PO43-, Cr(VI) contaminants, with the aquifer. Further, multiple continuous PRBs have been installed with optimized design and selected material properties. The simulation results show that the PRB is able to remediate the continuous multi-contaminant plume effectively. The interference of contaminants in the PRB performance also indicates a significant factor in the decline or enhancement of PRB performance in the long run. Similarly, the pumping rate in the proximity of PRB emplacement and the ratio of PRB to surrounding aquifer hydraulic conductivity also played a significant role in enhancing PRB performance. The higher the ratio, the larger the plume contaminant passes through the aquifer, which increases the overall removal efficiency of the PRB system. Therefore, the three-dimensional numerical modelling simulation results of the flow and solute transport model following the PRB performance for simultaneous removal of multi contaminants pave the way for opting for an efficient PRB design for the effective and sustainable performance for a variety of aquifers remediation. The model also provides support to build the understanding for avoiding any potential failure after the emplacement of PRB in the field.

Arctic cyclones are key drivers of sea ice and ocean variability. During the 2019-2020 Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, joint observations of the coupled air-ice-ocean system were collected at multiple spatial scales. Here, we present observations of a pair of strong mid-winter cyclones that impacted the MOSAiC site as it drifted in the central Arctic pack ice, with analytic emphasis on the second cyclone. The sea ice dynamical response showed spatial structure at the scale of the evolving atmospheric wind field. Internal ice stress and the ocean stress play significant roles, resulting in timing offsets between the atmospheric forcing and the ice response and post-cyclone inertial ringing in the ice and ocean. A structured response of sea ice motion and deformation to cyclone passage is seen, and the consequent ice motion then forces the upper ocean currents through frictional drag. The strongest impacts to the sea ice and ocean from the passing cyclone occur as a result of the surface impacts of a strong atmospheric low-level jet (LLJ) behind the trailing cold front. Impacts of the cyclone are prolonged through the coupled ice-ocean inertial response. The local impacts of the approximately 120 km wide LLJ occur over a 12 hour period or less and at scales of a kilometer to a few tens of kilometers, meaning that these impacts occur at smaller spatial scales and faster time scales than many satellite observations and coupled Earth system models can resolve.

This paper presents a statistical analysis to investigate the day-to-day variability of field-aligned irregularities (FAI) occurrence in nighttime F-region ionosphere over the Equatorial Atmosphere Radar (EAR), West Sumatra, Indonesia. FAI echoes were identified based on signal intensity of backscatter radar observations. We analyzed nighttime F-region FAI during 3 years starting in January 2011 to December 2013. For the first time, a combinatorics analysis was applied to examine the statistical likelihood of various day-to-day FAI occurrence patterns. The empirical day-to-day combinatorics analysis was performed based on binary classification of EAR observation data into either FAI occurrence (+) or absence (-) for each calendar date. Permutations of various day-to-day occurrence patterns, from 1-day to 6-day patterns, were sorted into histograms. The combinatorics analysis was performed in 4 separate time intervals to account for seasonal variation: two equinoxes (March and September) and two solstices (June and December). EAR data show that FAI occurrence probability is maximum for the two equinoxes, and that it is minimum for the two solstices. Our analysis shows that certain day-to-day patterns are more likely to occur than others, and such “combinatorics fingerprints” depend on season. During the solstices, persistent absence of FAI over several consecutive days far outweighed persistent FAI occurrence over an equivalent grouping of days with the same length. Meanwhile, during the equinoxes, we found a generally more equitable distribution between persistent day-to-day FAI occurrence and persistent day-to-day FAI absence. These findings may open new ways to help forecast FAI occurrence on a regional basis.

We present evidence of volcano-tectonic interactions at Sabancaya volcano that we relate to episodic magma injection and high regional fluid pore pressures. We present a surface deformation time series at Sabancaya including observations from ERS-1/2, Envisat, Sentinel-1, COSMO-SkyMed, and TerraSAR-X that spans June 1992 - February 2019. These data show deep seated inflation northwest of Sabancaya from 1992-1997 and 2013-2019, as well as creep and rupture on multiple faults. Afterslip on the Mojopampa fault following a 2013 Mw 5.9 earthquake is anomalously long-lived, continuing for at least six years. The best fit fault plane for the afterslip is right-lateral motion on an EW striking fault at 1 km depth. We also model surface deformation from two 2017 earthquakes (Mw 4.4 and Mw 5.2) on unnamed faults, for which the best fit models are NW striking normal faults at 1-2 km depth. Our best fit model for a magmatic inflation source (13 km depth, volume change of 0.04 to 0.05 km^3 yr^-1), induces positive Coulomb static stress changes on these modeled fault planes. Comparing these deformation results with evidence from satellite thermal and degassing data, field observations, and seismic records, we interpret strong pre-eruptive seismicity at Sabancaya as a consequence of magmatic intrusions destabilizing tectonic faults critically stressed by regionally high fluid pressures. High fluid pressure likely also promotes fault creep driven by static stress transfer from the inflation source. We speculate that strong seismicity near volcanoes will be most likely with high pore fluid pressures and significant, offset magmatic inflation.

Precision yield data is commonly recorded by modern combine harvesters and can be used to help growers optimize their operations. However, there have been very few attempts to predict variation in yield within a given field using multispectral satellite data. We used a precision yield dataset gathered in canola (Brassica napus L.) crops in central Alberta, Canada, and a time series of medium-resolution Sentinel-2 data collected over the growing season. Using two mapping methods, random forest regression and functional data analysis, we were able to predict crop yield to within 12-16% accuracy of actual yield, and to capture within-field variation. Our results demonstrate that time series of medium-resolution multispectral imagery is capable of mapping small-scale variation in crop yields, presenting new research and management applications for these techniques.

We present a new high resolution empirical model for the ionospheric total electron content (TEC). TEC data are obtained from the global navigation satellite system (GNSS) receivers with a 1 x 1 spatial resolution and 5 minute temporal resolution. The linear regression model is developed at 45N, 0E for the years 2000 - 2019 with 30 minute temporal resolution, unprecedented for typical empirical ionospheric models. The model describes dependency of TEC on solar flux, season, geomagnetic activity, and local time. Parameters describing solar and geomagnetic activity are evaluated. In particular, several options for solar flux input to the model are compared, including the traditionally used 10.7cm solar radio flux (F10.7), the Mg II core-to-wing ratio, and formulations of the solar extreme ultraviolet flux (EUV). Ultimately, the extreme ultraviolet flux presented by the Flare Irradiance Spectral Model, integrated from 0.05 to 105.05 nm, best represents the solar flux input to the model. TEC time delays to this solar parameter on the order of several days as well as seasonal modulation of the solar flux terms are included. The Ap_3 index and its history are used to reflect the influence of geomagnetic activity. The root mean squared error of the model (relative to the mean TEC observed in the 30-min window) is 1.9539 TECu. A validation of this model for the first three months of 2020 shows excellent agreement with data. The new model shows significant improvement over the International Reference Ionosphere 2016 (IRI-2016) when the two are compared during 2008 and 2012.

Climate variability, in terms of the climatic fluctuations in precipitation and potential evapotranspiration, impacts the variability of runoff at different timescales. This paper developed a new daily water balance model which unifies the probability distributed model and the SCS curve number method, and provides a unified framework for water balances across different timescales. The model uses a daily step but can be forced with climate inputs varying at different timescales. The model is applied to 82 MOPEX catchments, and the runoff at a coarser timescale is aggregated from the daily runoff. For runoff at each timescale, the relative role of each climate variability (daily, monthly, or inter-annual variability) is evaluated by comparing the modeled runoff forced with the climate variability at two consecutive timescales. It is found that the runoff variability at the daily, monthly, and annual scale is primarily controlled by the climate variability at the same timescale. The monthly climate variability significantly contributes to both the daily and inter-annual runoff variability. However, both daily and inter-annual climate variability play much smaller roles in monthly runoff variability. Besides monthly climate variability, mean annual runoff receives considerable contribution from the inter-annual climatic variability, which is often disregarded in previous studies. The quantitative evaluation of the roles of climate variability reveals how climate controls runoff across different timescales.

Current changes in tropical South America due to atmospheric warming, deforestation, and glacier retreat impact moisture and water exchange between the Amazon basin and the Andes. Thus, a deeper understanding of past atmospheric variability is crucial for developing strategies for climate and environmental change scenarios in this region. Within this context, we investigated an 18-year firn core drilled at the Illimani to interpret its aerosol composition (trace elements and major ions) in relation to seasonal processes, particularly atmospheric circulation over the Amazon basin. The resulting 21st-century record showed reduced Cr contamination over the Altiplano in comparison to the late 20th century, which was probably related to reduced emissions from mining activities. Sulfur records suggest the influence of volcanic eruptions in 2006 (Rabaul) and 2014 (Nyamuragira-Nyiragongo). Overall, the aerosol composition was mainly modulated by precipitation variability over the Altiplano at both annual and seasonal timescales. However, Mn was enriched due to strengthened low-level jets in the Amazon basin during the dry season, especially in 2015. This was corroborated by the reanalysis data. Furthermore, Mn, Co, and Fe showed an unprecedented peak in the record during the wet season of 2014, which was consistent with the arrival of a dust plume from Africa over Amazonia. Therefore, the Mn enrichment record can be used as a new proxy for obtaining information about the South American Low-Level Jet, and, when considered together with more elements, might also indicate snow layers that were possibly loaded with aerosols from Africa.

This study used data of 165 rain stations for mapping SPI index for winter season at the base of 7 months period (from November to next April). For compensating the lost measurements in stations, we used the Kriging method in ArcGIS10.1 for producing precipitation maps for each period of the year. We used a simple equation for calculating SPI 7 , and modeled the process by using Model Maker tool within the ERDAS 2014. The application of this model over the period from 1992 to 2018 produced twenty-seven annual maps of the SPI 7 in Syria. By plotting the general trend of precipitation changes according to this index, we observed that the entire study area is stable on a normal climatic state close to the annual average during the most of years. By analyzing precipitation and SPI maps using statistical zonal methods, based on agricultural stabilization zones, we found different behaviors of drought in every zone and between these zones.

In order to determine particle velocities and electric field in the frame of the magnetic structure, one first needs to determine the velocity of the magnetic structure in the frame of the spacecraft observations. Here, we show how to determine a two dimensional magnetic structure velocity for the magnetic reconnection event observed in the magnetotail by the Magnetospheric Multiscale (MMS) spacecraft on 11 July 2017. We use two different multi-spacecraft methods, Spatio-Temporal Difference (STD) and the recently developed polynomial reconstruction method. Both of these methods use the magnetic field measurements, and the reconstruction technique also uses the current density measured by the particle instrument. We find rough agreement between the results of our methods and with other velocity determinations previously published. We also explain a number of features of STD and show that the polynomial reconstruction technique is only likely to be valid within a distance of two spacecraft spacings from the centroid of the MMS spacecraft. Both of these methods are susceptible to contamination by magnetometer calibration errors.

The timescale over which magma rises to the surface during a volcanic eruption is a critical parameter that controls eruption style but is challenging to determine. Melt embayments, which are pockets of magma trapped within crystals but are still open to the host magma, tend to develop volatile (e.g., H2O, CO2) concentration gradients during ascent through the process of diffusion. These gradients are increasingly used as output constraints for diffusion models to calculate total ascent time. However, there are two main assumptions associated with the method that have yet to be properly evaluated. First, the diffusion models tend to be carried out in 1D, which may be less accurate than 3D models if the embayment narrows near the opening. This geometry has more complicated volatile flux pathways that 1D models cannot account for. Second, the models typically assume that volatile contents follow equilibrium saturation trends defined by depth below the surface, which may not be accurate for high silica magmas. For these compositions, a significant supersaturation of volatiles may be needed for volatile exsolution to start, depending on the availability of suitable crystal phases for bubble nucleation. This nucleation lag delays the start of diffusion as well and could influence modeled timescales. We developed 3D diffusion models to evaluate the degree of inaccuracy in calculated timescales introduced by these assumptions for high silica magmas. We built synthetic embayments with variable 3D geometries and imposed both equilibrium and disequilibrium ascent conditions in our models. Our results indicate that the inaccuracy introduced by embayment geometry in 1D diffusion models increases as the diameter of the embayment opening decreases. This degree of inaccuracy is also tied to diffusion duration – as it increases, so does the relative error in timescales retrieved by 1D models fitting 3D-generated profiles. Once the diffusion front extends beyond the narrow, “necked” region of the embayment, relative error increases with increasing diffusion time. However, volatile disequilibrium behavior does not appear to significantly impact modeled timescales. These results indicate that embayment geometry is a critical variable that must be accounted for whereas delayed nucleation is of secondary influence.

Lower atmosphere variations in the martian water vapour and hydrogen abundance during the Mars Year (MY) 34 C storm from LS=326.1◦-333.5◦ and their associated effect on hydrogen escape are investigated using a multi-spacecraft assimilation of atmospheric retrievals into a Martian global circulation model. Elevation of the hygropause and associated increase in middle atmosphere hydrogen at the peak of the MY 34 C storm led to a hydrogen escape rate of around 1.4×109 cm−2s−1 , meaning the MY 34 C storm enhanced water loss rates on Mars to levels observed during global-scale dust storms. The water loss rate during the MY 34 C storm (a loss of 15% of the total annual water loss during only 5% of the year) was three times stronger than the weak MY 30 C storm assimilation, demonstrating that interannual variations in C storm strength must be considered when calculating the integrated loss of water on Mars.

Departures from standard spherically symmetric solar models, in the form of perturbations such as global and local-scale flows and structural asphericities, result in the splitting of eigenfrequencies in the observed solar spectrum. Here we describe new theoretical developments that enable the computation of sensitivity kernels for frequency splittings (a coefficients) due to general Lorentz stresses in the Sun. We draw from theoretical ideas prevalent in normal-mode coupling theory in geophysical literature to build these kernels. We plot the Lorentz-stress kernels and estimate the a-coefficients arising from a combination of deep-toroidal and surface-dipolar fields (although we note that this could equally well be substituted by another choice of Lorentz stresses). These results pave the way to formally pose an inverse problem, and infer magnetic fields from the measured even a-coefficients.

InSAR time-series (InSAR-TS) analysis enables us to obtain the displacement time-series by using a number of SAR images repeatedly acquired on the area. Among the factors affecting the accuracy of the InSAR-TS analysis, this study focuses on three factors that may severely affect the signal detection limit: 1) the selection of the reference point (determining the offset in each interferogram), 2) ramp-type artifact that originate from inaccuracy in the orbit data or ionospheric disturbance, and 3) altitude-correlated tropospheric noise. Fukushima et al. (2019, Earth, Planets and Space) proposed an InSAR-TS analysis method to simultaneously solve for the displacement time-series and the error terms mentioned above as well as the error in the digital elevation model. In the proposed method, the unwrapped phase in interferograms is assumed to be composed of a linear combination of the LOS displacement, offset, planar ramp, altitude-correlated phase, and error in the used digital elevation model. A set of unwrapped small-baseline interferograms is then inverted to simultaneously obtain the displacement time-series and the parameters describing the error terms under the minimum norm condition on the displacement time-series. In this study, I applied the above-mentioned method after some updates such as introduction of the temporal constraint adopted by the NSBAS algorithm (Doin et al., 2011) and data masking, on the ALOS-2 data acquired around the Arima-Takatsuki fault zone in western Honshu, Japan. Data of four different Paths (20 and 21 from descending orbit, 127 and 128 from ascending orbit) obtained between August 2014 and March 2021 were analyzed. Some of the original interferograms contained severe noise such as a phase ramp equivalent to approximately 25 cm of LOS displacements. The average velocity field obtained by applying the method captured a relative range decrease of a few mm/year on the southern side of the fault, consistent with the results obtained from Sentinel-1 data analysis. Given the fact that the Sentinel-1 dataset had much favorable conditions (much larger number of data and much smaller ionospheric noise), the consistency in the average velocity field suggests the effectiveness of the proposed approach.

We present a characterization of large amplitude, short-timescale geomagnetic disturbances that we refer to as transient induced current (TIC) events. TIC events are defined as one or more short-timescale (< 60 seconds) dB/dt signature with magnitude ≥ 6 nT/s. We identified 40 TIC events that occurred at six stations of the Magnetometer Array for Cusp and Cleft Studies throughout 2015 and we demonstrate the existence of large-amplitude dB/dt with timescale less than 10 seconds in nine of the events. The association of these events to sudden commencements is weaker than expected, rather the events are more likely to occur in relation to substorm onsets. However, 15% of TIC events show no direct association to geomagnetic storms, substorms or nighttime magnetic impulse events. Our findings suggest that the TICs have different properties than typical geomagnetically induced currents and may be hazardous to conductive components of the Internet of Things network.

In preparation for future human habitats on Mars, it is important to understand the Martian radiation environment. Mars does not have an intrinsic magnetic field and Galactic cosmic ray (GCR) particles may directly propagate through and interact with its atmosphere before reaching the surface and subsurface of Mars. However, Mars has many high mountains and low-altitude craters where the atmospheric thickness can be more than 10 times different from one another. We thus consider the influence of the atmospheric depths on the Martian radiation levels including the absorbed dose, dose equivalent and body effective dose rates induced by GCRs at varying heights above and below the Martian surface. The state-of-the-art Atmospheric Radiation Interaction Simulator (AtRIS) based on GEometry And Tracking (GEANT4) Monte Carlo method has been employed for simulating particle interactions with the Martian atmosphere and terrain. We find that higher surface pressures can effectively reduce the heavy ion contribution to the radiation, especially the biologically weighted radiation quantity. However, enhanced shielding (both by the atmosphere and the subsurface material) can considerably enhance the production of secondary neutrons which contribute significantly to the effective dose. In fact, both neutron flux and effective dose peak at around 30 cm below the surface. This is a critical concern when using the Martian surface material to mitigate radiation risks. Based on the calculated effective dose, we finally estimate some optimized shielding depths, under different surface pressures (corresponding to different altitudes) and various heliospheric modulation conditions. This may serve for designing future Martian habitats.

Diapycnal mixing in the ocean interior is largely fueled by internal tides. Mixing schemes that represent the breaking of internal tides are now routinely included in ocean and earth system models applied to the modern and future. However, this is more rarely the case in climate simulations of deep-time intervals of the Earth, for which estimates of the energy dissipated by the tides are not always available. Here, we present and analyze two IPSL-CM5A2 earth system model simulations of the Early Eocene made under the framework of DeepMIP. One simulation includes mixing by locally dissipating internal tides, while the other does not. We show how the inclusion of tidal mixing alters the shape of the deep ocean circulation, and thereby of large-scale biogeochemical patterns, in particular dioxygen distributions. In our simulations, the absence of tidal mixing leads to a deep North Atlantic basin mostly disconnected from the global ocean circulation, which promotes the development of a basin-scale pool of oxygen-deficient waters, at the limit of complete anoxia. The absence of large-scale anoxic records in the deep ocean posterior to the Cretaceous anoxic events suggests that such an ocean state most likely did not occur at any time across the Paleogene. This highlights how crucial it is for climate models applied to the deep-time to integrate the spatial variability of tidally-driven mixing as well as the potential of using biogeochemical models to exclude aberrant dynamical model states for which direct proxies do not exist.