The uncontrolled rapid population growth in our regions and strong industrialization are putting pressure on natural resources, accelerating climate change and desertification. This study aims to follow the evolution of land use in the N’ZI watershed. Three images from Landsat 4 & 5 (1986), Landsat 7 (2000), and Landsat 8 (2020) made it possible to carry out this study. Remote sensing and geographic information systems (GIS) have been used to monitor land cover as a whole. The software Envi 5.1 and ArcGIS 10.4.1 have made it possible to do various treatments. The supervised classification method was used in this work in addition to the calculation of the spectral indices. The land-use analysis showed the changes that took place during the periods 1986-2000, 2000-2020, and 1986-2020. The results of this analysis showed regression of water surfaces (-64.95% and-52.47%) over the period (2000-2020 and 1986-2020) on the other hand, there is a great increase in bare-ground dwellings (373.63%) and low-cover soils (10.60%). These progressions are at the expense in particular of forests (-86.93%), savannas (-3.97%), and agricultural areas (-9.30%) between 1986-2020.

The Amazon River has the largest volume on earth, making up 15–20% of the annual fluvial discharge into oceans. The neighboring Pará River mixes with the Amazon River waters in the Amazon Estuary before forming a plume that extends into the Atlantic. Despite the global importance of these rivers, dissolved trace metal fluxes from this estuary remain unknown. Here we present data for dissolved (<0.2 µm) trace metals (Al, Mn, Fe, Co, Ni, Cu, Zn, Cd, Pb and U) in the Amazon Estuary during the high discharge season (April–May 2018). We observed distinct trace metal signatures for the Amazon and Pará Rivers, reflecting different catchment areas. Concentrations of the particle-reactive elements (Mn, Fe and Pb) decreased rapidly at low-salinity (S≤2), resulting in the highest estuarine removal (86–94% in the Amazon; 61–70% for the Pará). Co, Ni and Cu removal was comparatively low in both river transects (6–39%), while Cd was the only element with a consistent net input. Chemical fluxes were estimated using (a) endmember concentrations and estuarine removal and (b) combining trace element concentrations with 228Ra fluxes. Relative to global total river fluxes, the Amazon and Pará Rivers combined contribute 21% of dissolved Cu and 18% of dissolved Ni during the high discharge season, but account for comparatively low fractions of Mn, Fe, Co and Zn. These data quantify, for the first time, the trace metal output from the world’s largest and 5th largest river into the Atlantic Ocean, filling a critical gap in knowledge of this globally-important region.

Highlights: • Evidence for a 175 km thick lithosphere beneath the Archean Eastern Dharwar craton. • The lithosphere has a shear wave velocity of 4.7-4.8 km/s, typical for a craton. • Moderate coupling between the Dharwar craton lithosphere and asthenosphere. • Collocated seismological and kimberlite xenolith data reveal undisturbed craton root.

AbstractFeature interaction is a crucial concept when it comes to machine learning interpretability. These interactions make it easier for the person using a machine learning tool to know how the model made its prediction. Intrinsic models such as the Generalized linear models pull their interpretability aspects from detecting feature interactions on the data. However, these models do not search the whole sample space for interactions and assume all interactions to the target feature are identical. A hybrid model combining Rough Set and Generalized linear models is proposed. Rough Set uses the concept of information granulation and approximations of regions with meaningful information to find feature interactions in the whole sample space. The detected features will then be modeled onto a Generalized linear model for prediction purposes. The dataset used in the experiment was drawn from wunderground.com online weather site, specifically the Kariki Farm online weather station. The proposed methodology for the research is the CRISP-DM method.Keywords: Machine interpretability, Rough Set, Generalized linear model, weather prediction.

Media propagation delay and delay-rate induced by the water vapor within the Earth's troposphere represent one of the main error sources for radiometric measurements in deep space. In preparation for the BepiColombo and JUICE missions, the European Space Agency has installed and operates the prototype of a tropospheric delay calibration system (TDCS) at the DSA-3 ground station located in Malargüe, Argentina.An initial characterization of the TDCS performance was realized using two-way Doppler measurements at X-band to perform the orbit determination of the Gaia spacecraft. This work will further characterize the system by analyzing two-way Doppler and range data at X- and Ka-band for 31 tracking passes of the BepiColombo spacecraft, which were recorded between March 2021 and February 2022 during the first two solar conjunction experiments. The performance exceeds the expectations based on the previous analysis, with a reduction of the Doppler noise of 51% on average and up to 73% when using the TDCS measurements in place of standard calibrations based on global navigation satellite system data. Furthermore, the campaign serves as validation of the TDCS operations during superior solar conjunctions, with most of the tracking passes at low elongation now satisfying the Mercury orbiter radioscience experiment requirements on two-way Doppler stability. These results, which are in line with those of similar instruments installed at other Deep Space Network antennas, are obtained using a commercial microwave radiometer with significantly lower installation and maintenance costs.

The Solar Dynamics Observatory (SDO) is a solar mission in an inclined geosynchronous orbit. Since commissioning, images acquired by Atmospheric Imaging Assembly (AIA) instrument on-board the SDO have frequently displayed “spikes”, pixel regions yielding extreme number of digital counts. These are theorized to occur from energetic electron collisions with the instrument detector system. These spikes are regularly removed from AIA Level 1.0 images to produce clean and reliable data. A study of historical data has found over 100 trillion spikes in the past decade. This project correlates spike detection frequency with radiation environment parameters in order to generate an augmented data product from SDO. We conduct a correlation study between SDO/AIA data and radiation belt activity within the SDO’s orbit. By extracting radiation “spike” data from the SDO/AIA images, we produce a comprehensive data product which is correlated not only with geomagnetic parameters such as Kp, Ap and Sym-H but also with the electron and proton fluxes measured by the GOES-14 satellite. As a result, we find that AIA spikes are highly correlated with the GOES-14 electrons detected by the MAGED and EPEAD instruments at the equator (where the two satellites meet) with Spearman’s Correlation values of ρ=0.73 and ρ=0.53 respectively, while a weaker correlation of ρ=0.47 is shown with MAGPD protons for the two year period where both missions returned data uninterruptedly. This correlation proves that the SDO spike data can be proven useful for characterizing the Van Allen radiation belt, especially at areas where other satellites cannot.

We describe new publicly-available, multi-year formaldehyde (HCHO) data records from the Ozone Mapping and Profiler Suite (OMPS) nadir mapper (NM) instruments on the Suomi NPP and NOAA-20 satellites. The OMPS-NM instruments measure backscattered UV light over the globe once per day, with spatial resolutions close to nadir of 50 × 50 km² (OMPS/Suomi-NPP) and 17 × 17 km² or 12 × 17 km² (OMPS/NOAA-20). After a preliminary instrument line shape and wavelength calibration using on-orbit observations, we use the backscatter measurements in a direct spectral fit of radiances, in combination with a nadir reference spectrum collected over a clean area, to determine slant columns of HCHO. The slant columns are converted to vertical columns using air mass factors derived through scene-by-scene radiative transfer calculations. Finally, a correction is applied to account for background HCHO in the reference spectrum, as well as any remaining high-latitude biases. We investigate the consistency of the OMPS products from Suomi NPP and NOAA-20 using long-term monthly means over 12 geographic regions, and also compare the products with publicly-available TROPOMI HCHO observations. OMPS/Suomi-NPP and OMPS/NOAA-20 monthly mean HCHO vertical columns are highly consistent (r = 0.98), with low proportional (2 %) and offset (2×10¹⁴ molecules cm⁻²) biases. OMPS HCHO monthly means are also well-correlated with those from TROPOMI (r = 0.92), although they are consistently 10±16 % larger in polluted regions (columns >8×10¹⁵ molecules cm⁻²). These differences result primarily from differences in air mass factors.

The 2019 Museum Fire burned in a mountainous region near the city of Flagstaff, AZ, USA. Due to the high risk of post-wildfire debris flows and flooding entering the city, we deployed a network of seismometers within the burn area and downstream drainages to examine the efficacy of seismic monitoring for post-fire flows. Seismic instruments were deployed during the 2019, 2020, and 2021 monsoon seasons following the fire and recorded several debris flow and flood events, as well as signals associated with rainfall, lighting and wind. Signal power, frequency content, and wave polarization were measured for multiple events and compared to rain gauge records and images recorded by cameras installed in the study area. We use these data to demonstrate the efficacy of seismic recordings to (1) detect and differentiate between different energy sources, (2) estimate the timing of lightning strikes, (3) calculate rainfall intensities, and (4) determine debris flow timing, size, velocity, and location. This work confirms the validity of theoretical models for interpreting seismic signals associated with debris flows and rainfall in post-wildfire settings and demonstrates the efficacy of seismic data for identifying and characterizing debris flows.

A supermodel connects different models interactively so that their systematic errors compensate and achieve a model with superior performance. It differs from the standard non-interactive multi-model ensembles (NI), which combines model outputs a-posteriori. We formulate the first supermodel framework for Earth System Models (ESMs) and use data assimilation to synchronise models. The ocean of three ESMs is synchronised every month by assimilating pseudo sea surface temperature (SST) observations generated from them. Discrepancies in grid and resolution are handled by constructing the synthetic pseudo-observations on a common grid. We compare the performance of two supermodel approaches to that of the NI for 1980—2006. In the first (EW), the models are connected to the equal-weight multi-model mean, while in the second (SINGLE), they are connected to a single model. Both versions achieve synchronisation in locations where the ocean drives the climate variability. The time variability of the supermodel multi-model mean SST is reduced compared to the observed variability; most where synchronisation is not achieved and is bounded by NI. The damping is larger in EW than in SINGLE because EW yields additional damping of the variability in the individual models. Hence, under partial synchronisation, the part of variability that is not synchronised gets damped in the multi-model average pseudo-observations, causing a deflation during the assimilation. The SST bias in individual models of EW is reduced compared to that of NI, and so is its multi-model mean in the synchronised regions. The performance of a trained supermodel remains to be tested.

The mineral dolomite (CaMg(CO3)2) forms in only small quantities in modern oceans, cannot be precipitated abiotically from unmodified seawater in laboratory experiments, yet comprises much of the carbonate rock record. The challenge of explaining the apparent temporal discrepancy in dolomite, the “dolomite problem,” has fascinated carbonate sedimentologists for centuries. Yet, this pursuit has lacked a quantitative tabulation of dolomite in the rock record. Here, we use the North American rock record, as archived in Macrostrat, to assemble a record of dolomite abundance through geologic time. The completeness and age resolution of our dataset allow us to compare dolomite abundance with environmental variables, including stromatolite abundance, evaporite occurrences, sea level, glaciation, and temperature. We use these comparisons to test the assumption that the bulk of the geologic dolomite record was formed via secondary diagenetic processes. We find no monotonic decrease in abundance with age-the expected result if late diagenesis affects the bulk of the record. Dolomite was just as abundant during the first half of the Paleozoic as it was during most of the Neoproterozoic, a challenge to canonical thinking. We show that a number of dolomite precipitation mechanisms known from modern environments and experimentally grown dolomite can explain many of the patterns we observe in the North American dolomite record. Perhaps dolomite is not such a problem after all.

It is widely acknowledged that distributed water systems (DWSs), which integrate distributed water supply and treatment with existing centralized infrastructure, can mitigate challenges to water security from extreme events, climate change, and aged infrastructure. However, there is a knowledge gap in finding beneficial DWS configurations, i.e., where and at what scale to implement distributed water supply. We develop a meso-scale representation model that approximates DWSs with reduced backbone networks, which enable efficient system emulation while preserving key physical realism. Moreover, system emulation allows us to build a multi-objective optimization model for computational policy search that addresses energy utilization and economic impacts. We demonstrate our models on a hypothetical DWS with distributed direct potable reuse (DPR) based on the City of Houston’s water and wastewater infrastructure. The backbone DWS with greater than 92% link and node reductions achieves satisfactory approximation of global flows and water pressures, to enable configuration optimization analysis. Results from the optimization model reveal case-specific as well as general opportunities, constraints, and their interactions for DPR allocation. Implementing DPR can be beneficial in areas with high energy intensities of water distribution, considerable local water demands, and commensurate wastewater reuse capacities. The meso-scale modeling approach and the multi-objective optimization model developed in this study can serve as practical decision-support tools for stakeholders to search for alternative DWS options in urban settings.

We present partial ring distributions of solar wind protons observed by the Rosetta spacecraft at comet 67P/Churyumov-Gerasimenko. The formation of ring distributions is usually associated with high activity comets, where the spatial scales are larger than multiple ion gyroradii. Our observations are made at a low-activity comet at a heliocentric distance of 2.8 AU on April 19th, 2016, and the partial rings occur at a spatial scale comparable to the ion gyroradius. We use a new visualisation method to simultaneously show the angular distribution of median energy and differential flux. A fitting procedure extracts the bulk speed of the solar wind protons, separated into components parallel and perpendicular to the gyration plane, as well as the gyration velocity. The results are compared with models and put into context of the global comet environment. We find that the formation mechanism of these partial rings of solar wind protons is entirely different from the well-known partial rings of cometary pickup ions at high-activity comets. A density enhancement layer of solar wind protons around the comet is a focal point for proton trajectories originating from different regions of the upstream solar wind. If the spacecraft location coincides with this density enhancement layer, the different trajectories are observed as an energy-angle dispersion and manifest as partial rings in velocity space.

Surface charging properties of a non-conducting surface that has a deep cavity and is in contact with the solar wind plasma are investigated by means of the particle-in-cell plasma simulations. The modeled topography is intended with a portion of irregular surfaces found on solid planetary bodies. The simulations have revealed unconventional charging features in that the cavity bottom is charged up to positive values even without any electron emission processes such as photoemission, provided that the surface location is accessible to a portion of incoming solar wind ions. The major driver of the positive charging is identified as drifting ions of the solar wind plasma, and an uncommon current ordering where ion currents exceed electron currents is established at the innermost part of the deep cavity. This also implies that the cavity bottom surface may have a positive potential of several hundred volts, corresponding to the kinetic energy of the ions. The present study also clarifies the role of photoelectrons in developing the distinctive charging environment inside the cavity. The photoemitted electrons can no longer trigger positive charging at the cavity bottom, but rather exhibit the effect of relaxing positive potentials caused by the solar wind ions. The identified charging process, which are primarily due to the solar wind ions, are localized at the depths of the cavity and may be one possible scenario for generating intense electric fields inside the cavity.

We present a statistical study of Jupiter’s disk X-ray emissions using 19 years of Chandra X-Ray Observatory (CXO) observations. Previous work has suggested that these emissions are consistent with solar X-rays elastically scattered from Jupiter’s upper atmosphere. We showcase a new Pulse Invariant (PI) filtering method that minimises instrumental effects which may produce unphysical trends in photon counts across the nearly-two-decade span of the observations. We compare the CXO results with solar X-ray flux data from the Geostationary Operational Environmental Satellites (GOES) X-ray Sensor (XRS) for the wavelength band 1-8 Å (long channel), to quantify the correlation between solar activity and jovian disk counts. We find a statistically significant Pearson’s Correlation Coefficient (PCC) of 0.9, which confirms that emitted jovian disk X-rays are predominantly governed by solar activity. We also utilise the high spatial resolution of the High Resolution Camera Instrument (HRC-I) on board the CXO to map the disk photons to their positions on Jupiter’s surface. Voronoi tessellation diagrams were constructed with the JRM09 (Juno Reference Model through Perijove 9) internal field model overlaid to identify any spatial preference of equatorial photons. After accounting for area and scattering across the curved surface of the planet, we find a preference of jovian disk emission at 2-3.5 Gauss surface magnetic field strength. This suggests that a portion of the disk X-rays may be linked to processes other than solar scattering: the spatial preference associated with magnetic field strength may imply increased precipitation from the radiation belts, as previously postulated.

Interaction between ocean waves and sea ice may play an important role in sea ice retreat in the Arctic. However, it is difficult to quantify the change of ocean waves propagating in ice as nearly no available measurements. Although SAR has shown the capability of imaging ocean waves in ice-covered areas, there are few attempts to retrieve two-dimensional ocean wave spectra (OWS) by SAR. In this study, we applied the previously developed nonlinear inversion scheme, i.e., the MPI scheme, to retrieve OWS by the Sentinel-1 SAR data acquired in the Barents Sea, where waves penetrate deeply in ice. We compared the retrieved spectra by different combinations of modulation transfer functions (MTFs) used in the MPI scheme, i.e., the same MTFs as those used in retrievals in open water, neglecting both the hydrodynamic and tilt modulations in the MTFs, and neglecting the hydrodynamic modulation but remaining the tilt modulation (a new one fitted in this study for HH-polarized SAR data over ice) in the MTFs. As no in situ measurements (e.g., by directional buoys) available, we compared the simulated SAR image spectra based on the retrievals with the observational SAR image spectra to quantify their respective performances. The comparisons suggest that neglecting hydrodynamic modulation can significantly improve the retrievals. Remaining tilt modulation can further improve the retrievals, particularly for range-travelling waves. The study enhances the understanding of principles of SAR imaging waves in ice and provides basics for retrievals of ocean wave spectra by SAR data in ice-covered areas.

Volcanism is the dominant natural source of mercury (Hg) to the atmosphere, biosphere, ocean and sediments. In recent years, sedimentary Hg contents have emerged as a tool to reconstruct volcanic activity, and particularly activity of (subaerially emplaced) large igneous provinces (LIP) in geological deep time. More specifically, Hg has shown potential as a useful proxy to illuminate the previously elusive impact of such large-scale volcanism on marine and terrestrial paleo-environments. While Hg is now widely applied as volcanism tracer, non-volcanic factors controlling sedimentary Hg content are generally not well constrained. Part of this uncertainty stems from our inability to directly observe a natural unperturbed “steady-state” environment as a baseline, as the modern Hg cycle is heavily influenced by anthropogenic activity. Here we focus on the effects of ambient redox conditions in the water column and shallow sediments (early diagenesis), quantify their influence on the geological Hg record and thereby constrain their potential impact on the use of Hg as a proxy for deep-time volcanic activity. Constraining these factors is of critical importance for the application of Hg as a proxy. Many periods in the geological past for which records have been generated, such as the Mesozoic Oceanic Anoxic Events, are marked by a variety of high-amplitude environmental perturbations, including widespread deoxygenation and deposition of organic-rich sediments. We estimate the impact of redox changes and early diagenesis on the geological Hg record using a suite of (sub)recent–Pleistocene and Upper Cretaceous sediments representing oxic to euxinic marine conditions. Our sample set includes a transect through an oxygen minimum zone and cores that record transient shifts in oxygenation state, as well as post-depositional effects – all unrelated to volcanism, to the best of our knowledge. We find substantial alterations to the Hg record and the records of organic carbon and total sulfur, which are typically assumed to be the most common carrier phases of Hg in marine sediments. Moreover, these biases can lead to signal-alterations on a par with those interpreted to result from volcanic activity. Geochemical modifications are ubiquitous and their potential magnitude implies that the factors leading to biases in the geological record warrant careful consideration before interpretation. Factors of particular concern to proxy application are (1) the disproportionate loss of organic carbon and sulfur compounds relative to Hg during oxidation that strongly modulates normalized Hg records, (2) the evasion of Hg in anoxic and mildly euxinic sediments and (3) sharp focusing of Hg during post-depositional oxidation of organic matter.

This work uses the Specified Dynamics-Whole Atmosphere Community Climate Model with Ionosphere/Thermosphere eXtension (SD-WACCM-X) to determine and explain the seasonality of the migrating semidiurnal tide (SW2) components of tropical upper mesosphere and lower thermosphere (UMLT) temperature, zonal-wind and meridional-wind. This work also quantifies aliasing due to SW2 in satellite-based tidal estimates. Results show that during equinox seasons, the vertical profile of tropical UMLT temperature SW2 and zonal wind SW2’s amplitudes have a double peak structure while they, along with meridional wind SW2, have a single peak structure in their amplitudes in June solstice. Hough mode reconstruction reveals that a linear combination of 5 SW2 Hough modes cannot fully reproduced these features. Tendency analysis reveals that for temperature, the adiabatic term, non-linear advection term and linear advection term are important. For the winds, the classical terms, non-linear advection term, linear advection term and gravity wave drag are important. Results of our alias analysis then indicate that SW2 can induce an ~60% alias in zonal-mean and DW1 components calculated from sampling like that of the Thermosphere Ionosphere Mesosphere Energetics and Dynamics satellite and the Aura satellite. This work concludes that in-situ generation by wave-wave interaction and/or by gravity waves play significant roles in the seasonality of tropical UMLT temperature SW2, zonal wind SW2 and meridional wind SW2. The alias analysis further adds that one cannot simply assume SW2 in the tropical UMLT is negligible.

We argue that ocean general circulation models and observations based on Ekman or geostrophic balance provide estimates of the Lagrangian-mean ocean velocity field averaged over surface waves — the total time-averaged velocity that advects oceanic tracers, particles, and water parcels. This interpretation contradicts an assumption often made in ocean transport studies that numerical models and observations based on dynamical balances estimate the Eulerian-mean velocity — the velocity time-averaged at a fixed position and only _part_ of the total ocean velocity. Our argument uses the similarity between the wave-averaged Lagrangian-mean momentum equations appropriate at large oceanic scales, and the momentum equations solved by “wave-agnostic” general circulation models that neglect surface wave effects. We further our case by comparing a realistic, global, “wave-agnostic” general circulation ocean model to a wave-averaged Lagrangian-mean general circulation ocean model at eddy-permitting 1/4-degree resolution, and find that the wave-agnostic velocity field is almost identical to the wave-averaged Lagrangian-mean velocity.