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Digital surface model (DSM) is the fundamental data in various geoscience applications, such as city 3-D modeling and urban environment analysis. The freely available DSM often suffers from limited spatial resolution. Super-resolution (SR) is a promising technique to increase the spatial resolution of DSM. However, most existing SR models struggle to reconstruct spatial details, such as buildings, valleys, and ridges. This article proposes a novel DSM super-resolution (DSMSR) model that integrates high-resolution remote sensing imagery using generative adversarial networks. The generator in DSMSR contains three modules. The first DSM feature extraction module uses the residual-in-residual dense block to extract features from low-resolution DSM. The second multiscale attention feature extraction module employs the pyramid convolutional residual dense blocks to capture the spatial details of ground objects at multiple scales from remote sensing imagery. The third DSM reconstruction module uses a squeeze-and-excitation block to fuse the extracted features from low-resolution DSM and high-resolution remote sensing imagery for generating SR DSM. The discriminator of DSMSR uses the relativistic average discriminator for adversarial learning. The slope loss is further introduced to ensure the accurate representation of topographic features. We evaluate DSMSR on four different terrain regions in the U.K. to downscale the 30-m AW3D30 DSM to 5-m DSM. The experimental results indicate that DSMSR outperforms the traditional interpolation algorithms and four existing deep-learning-based SR models. The DSMSR restores more spatial detail of topographic features and generates more accurate image quality, elevation, and terrain metrics.

Abstract Blue carbon in mangrove ecosystems contributes significantly to the global carbon cycle. However, large uncertainties maintain in the soil organic carbon (SOC) storage throughout the tide-induced salinity and alkalinity transect in the mangrove restoration region in Southern China. Total 125 soil samples were obtained to detect the SOC content and physicochemical properties. The mean SOC content of each layer ranged from 6.82 to 7.86 g kg−1, while the SOC density ranged from 2.99 to 11.41 kg m−2, increasing with soil depths. From different land covers in the study region, the SOC content varied from 4.63 to 9.71 g kg−1, increasing across the salinity and alkalinity transect, while the SOC density fluctuated from 3.01 kg m−2 in mudflats to 10.05 kg m−2 in mangrove forests. SOC concentration was favorably linked with total nitrogen (r = 0.95), and total phosphorus (r = 0.74), and negatively correlated with Cl− (r = − 0.95), electrical conductivity (r = − 0.24), and total dissolved solids (r = − 0.08). There were significant logarithmic relationships between SOC content and the concentrations of clay (r = 0.76), fine silt (r = 0.81), medium silt (r = − 0.82), and coarse silt (r = − 0.78). The spatial patterns of SOC concentration were notably affected by soil texture, physicochemical properties, and land-cover type, providing essential reference for future investigations of blue carbon budget in restored mangrove forests.

With a view to understanding the dynamics of ancient trade and agrobiodiversity, archaeobotanical remains provide a means of tracing the trajectories of certain agricultural commodities. A prime example is cotton in Arabia, a plant that is non-native but has been found in raw seed and processed textile form at Hegra and Dadan, in the region of al-ʿUlā, north-western Saudi Arabia—sites of critical importance given their role in the trans-Arabian trading routes during Antiquity. Here, we demonstrate that the measurement of strontium isotopes from pre-cleaned archaeological cotton is methodologically sound and is an informative addition to the study of ancient plant/textile provenance, in this case, putting forward evidence for local production of cotton in oasis agrosystems and possible external supply. The presence of locally-grown cotton at these sites from the late 1st c. BCE–mid 6th c. CE is significant as it demonstrates that cotton cultivation in Arabia was a Pre-Islamic socio-technical feat, while imported cotton highlights the dynamism of trade at that time.

The study of paleo shorelines, particularly of those formed during the late Quaternary, provides robust insights into past climate variability. Advances in surveying techniques and chronological methodologies have dramatically improved the inter-comparability of regional and basin-wide paleo shoreline surveys. However, these advances have been applied unevenly across the globe. This is especially true in southwestern Madagascar, where, in the 1960s and 1970s, emerged Pleistocene beach and reef facies were first described in detail and dated to Marine Isotope Stage (MIS) 5a using U–Th alpha activity counting by french geologist René Battistini. Now, 50 years on, no further analysis of the coastal sequence has been made. In this study, we present an updated late Pleistocene coastal evolution model for the southwestern Madagascar coast. Utilizing a combination of Structure-from-Motion/Multi-View Stereo techniques and differential Global Navigation Satellite System surveys, we have created five high-resolution 3D outcrop reconstructions that have, in turn, been chronologically constrained using 10 U-series ages from both in situ and reworked coral samples. Our data suggest that the emerged reef was deposited during MIS 5e (∼125 ka), then was covered by intertidal and beach sediment (including redeposited coral clasts of MIS 5e age), and finally capped off by thick eolianites. This sequence would suggest that the local sea level must have remained stable throughout MIS 5e in order to allow for the progradation of both the beach and reef environments.

Abstract In the context of increasing evidence of plate interface coupling variability in subduction zones, there is a need to extend the short time window given by instrumental data and to gather data over multiple time and spatial scales. We hence investigated the long‐term topography on Barbuda island, located in the northern part of the Lesser Antilles, west of the Caribbean subduction zone. Following pioneering work using a set of marine terraces on the eastern side of the island, we performed the first U‐Th dating on 10 corals in growth position from the lowest terrace, for which the highest relative sea‐level (RSL) indicator is found at 9 ± 1 m above the mean sea level. We find that this terrace corresponds to the Last Interglacial (LIG) (ages between 122.8 ± 0.3 ka and 128.1 ± 0.3 ka) and we estimate a paleo RSL of 7 ± 2 m above the current mean sea level. The present elevation of the LIG shoreline on Barbuda might imply tectonics as an additional mechanism to eustatic sea level, mantle dynamic topography and glacial isostatic adjustment. East‐west morphological asymmetry of Barbuda and difference in LIG shoreline elevation between Barbuda and Antigua suggest a regional tectonic process. As with the proposed westward tilting from the forearc to the volcanic arc of the Guadeloupe archipelago, vertical deformation on Barbuda could be related to plate‐scale subduction processes. Long‐term uplift of Barbuda might be related to the accumulation of residual coseismic deformation not fully recovered by interseismic subsidence and the corresponding seismogenic segment would extend below the Moho.

Lake Maryut (northwestern Nile Delta, Egypt) was a key feature of Alexandria's hinterland and economy during Greco-Roman times. Its shores accommodated major economic centers, and the lake acted as a gateway between the Nile valley and the Mediterranean. It is suggested that lake-level changes, connections with the Nile and the sea, and possible high-energy events considerably shaped the human occupation history of the Maryut. To reconstruct Lake Maryut hydrology in historical times, we used faunal remains, geochemistry (Sr isotopic signature of ostracods) and geoarcheological indicators of relative lake-level changes. The data show both a rise in Nile inputs to the basin during the first millennia BCE and CE and a lake-level rise of ca. 1.5 m during the Roman period. A high-energy deposit, inferred from reworked radiocarbon dates, may explain an enigmatic sedimentary hiatus previously attested to in Maryut's chronostratigraphy.

Gridded gross domestic product (GDP) data are a crucial land surface parameter for many geoscience applications. Recently, machine learning approaches have become powerful tools in generating gridded GDP data. However, most machine learning approaches for gridded GDP estimation seldom consider the geographical properties of input variables. Therefore, in this study, a geographically weighted stacking ensemble learning approach was developed to generate gridded GDP data. Three algorithms—random forest, XGBoost, and LightGBM—were used as base models, and the linear regression in stacking ensemble learning was replaced by geographically weighted regression to locally fuse the three predictions. A case study was conducted in China to demonstrate the effectiveness of the proposed approach. The results showed that the proposed GDP downscaling approach outperformed the three base models and traditional stacking ensemble learning. Meanwhile, it had good predictive power on county-level GDP test data with R2 of 0.894, 0.976, and 0.976 for the primary, secondary, and tertiary sectors, respectively. Moreover, the predicted 1 km gridded GDP data had a high accuracy (R2 = 0.787) when evaluated by town-level GDP data. Hence, the proposed GDP downscaling approach provides a valuable option for generating gridded GDP data. The generated 1 km gridded GDP data of China from 2020 are of great significance for other applications.

In the Western Alps, the Penninic frontal thrust (PFT) is the main crustal-scale tectonic structure of the belt. This thrust transported the high-pressure metamorphosed internal units over the non-metamorphosed European margin during the Oligocene (34–29 Ma). Following the propagation of the compression toward the European foreland, the PFT was later reactivated as an extensional detachment associated with the development of the High Durance extensional fault system (HDFS). This inversion of tectonic displacement along a major tectonic structure has been widely emphasized as an example of extensional collapse of a thickened collisional orogen. However, the inception age of the extensional inversion remains unconstrained. Here, for the first time, we provide chronological constraints on the extensional motion of an exhumed zone of the PFT by applying U–Pb dating on secondary calcites from a fault zone cataclasite. The calcite cement and veins of the cataclasite formed after the main fault slip event, at 3.6 ± 0.4–3.4 ± 0.6 Ma. Cross-cutting calcite veins featuring the last fault activity are dated at 2.6 ± 0.3–2.3 ± 0.3 Ma. δ13C and δ18O fluid signatures derived from these secondary calcites suggest fluid percolation from deep-seated reservoir at the scale of the Western Alps. Our data provide evidence that the PFT extensional reactivation initiated at least ∼ 3.5 Myr ago with a reactivation phase at ∼ 2.5 Ma. This reactivation may result from the westward propagation of the compressional deformation toward the external Alps, combined with the exhumation of external crystalline massifs. In this context, the exhumation of the dated normal faults is linked to the eastward translation of the HDFS seismogenic zone, in agreement with the present-day seismic activity.

The Humboldt Large Marine Ecosystem (HLME) and Patagonian Large Marine Ecosystem (PLME) are the two largest marine ecosystems in the Southern Hemisphere and are respectively located along the Pacific and Atlantic coasts of southern South America. This work investigates the exchange between these two LMEs and its seasonal and interannual variability by employing numerical model results and offline particle-tracking algorithms. Our analysis suggests a general poleward transport on the southern region of the HLME, a well-defined flux from the Pacific to the Atlantic, and equatorward transport on the PLME. Lagrangian simulations show that the majority of the southern PS waters originate from the upper layer in the southeast South Pacific ( m), mainly from the southern Chile and Cape Horn shelves. The exchange takes place through the Le Maire Strait, Magellan Strait, and the shelf break. These inflows amount to a net northeastward transport of 0.88 Sv at 51∘ S in the southern PLME. The transport across the Magellan Strait is small (0.1 Sv), but due to its relatively low salinity it greatly impacts the density and surface circulation of the coastal waters of the southern PLME. The water masses flowing into the Malvinas Embayment eventually reach the PLME through the Malvinas Shelf and occupy the outer part of the shelf. The seasonal and interannual variability of the transport are also addressed. On the southern PLME, the interannual variability of the shelf exchange is partly explained by the large-scale wind variability, which in turn is partly associated with the Southern Annular Mode (SAM) index (r=0.52).

This paper describes the next-generation ocean forecast model for the European north-west shelf, which will become the basis of operational forecasts in 2018. This new system will provide a step change in resolution and therefore our ability to represent small-scale processes. The new model has a resolution of 1.5 km compared with a grid spacing of 7 km in the current operational system. AMM15 (Atlantic Margin Model, 1.5 km) is introduced as a new regional configuration of NEMO v3.6. Here we describe the technical details behind this configuration, with modifications appropriate for the new high-resolution domain. Results from a 30-year non-assimilative run using the AMM15 domain demonstrate the ability of this model to represent the mean state and variability of the region.Overall, there is an improvement in the representation of the mean state across the region, suggesting similar improvements may be seen in the future operational system. However, the reduction in seasonal bias is greater off-shelf than on-shelf. In the North Sea, biases are largely unchanged. Since there has been no change to the vertical resolution or parameterization schemes, performance improvements are not expected in regions where stratification is dominated by vertical processes rather than advection. This highlights the fact that increased horizontal resolution will not lead to domain-wide improvements. Further work is needed to target bias reduction across the north-west shelf region.

It is hypothesized that more accurate prediction and warning of natural hazards, such as of the impacts of severe weather mediated through various components of the environment, require a more integrated Earth System approach to forecasting. This hypothesis can be explored using regional coupled prediction systems, in which the known interactions and feedbacks between different physical and biogeochemical components of the environment across sky, sea and land can be simulated. Such systems are becoming increasingly common research tools. This paper describes the development of the UKC2 regional coupled research system, which has been delivered under the UK Environmental Prediction Prototype project. This provides the first implementation of an atmosphere–land–ocean–wave modelling system focussed on the United Kingdom and surrounding seas at km-scale resolution. The UKC2 coupled system incorporates models of the atmosphere (Met Office Unified Model), land surface with river routing (JULES), shelf-sea ocean (NEMO) and ocean waves (WAVEWATCH III). These components are coupled, via OASIS3-MCT libraries, at unprecedentedly high resolution across the UK within a north-western European regional domain. A research framework has been established to explore the representation of feedback processes in coupled and uncoupled modes, providing a new research tool for UK environmental science. This paper documents the technical design and implementation of UKC2, along with the associated evaluation framework. An analysis of new results comparing the output of the coupled UKC2 system with relevant forced control simulations for six contrasting case studies of 5-day duration is presented. Results demonstrate that performance can be achieved with the UKC2 system that is at least comparable to its component control simulations. For some cases, improvements in air temperature, sea surface temperature, wind speed, significant wave height and mean wave period highlight the potential benefits of coupling between environmental model components. Results also illustrate that the coupling itself is not sufficient to address all known model issues. Priorities for future development of the UK Environmental Prediction framework and component systems are discussed.

River freshwater contribution in the European Atlantic margin and its influence on the sea salinity field are analyzed. The impacts of using a new river discharge database as part of the freshwater forcing in a regional ocean model are assessed. Ocean model scenarios, based on the CMEMS (Copernicus Marine Environment Monitoring Service) operational IBI-MFC (Iberia Biscay Ireland Monitoring Forecasting Centre) model set-up, are run to test different (observed, modeled and climatological) river and coastal freshwater forcing configurations throughout 2018. The modelled salinity fields are validated, using as a reference all known available in-situ observational data sources. The IBI model application is proven to adequately simulate the regional salinity, and the scenarios showcase the effects of varying imposed river outflows. Some model improvement is achieved using the new forcing (i.e., better capture of salinity variability and more realistic simulation of baroclinic frontal structures linked to coastal and river freshwater buoyancy plumes). Major impacts are identified in areas with bigger river discharges (i.e., the French shelf or the northwestern Iberian coast). Instead, the Portuguese shelf or the Gulf of Cadiz are less impacted by changes in the imposed river inflows, and other dynamical factors in these areas play a major role in the configuration of the regional salinity.