bluuebunny/crossref_metadata_2025 huggingface dataset:
Mass-Independent Fractionation Reveals the Sources and Transport of Atmospheric Particulate Bound Mercury
Authors: Qin Xuechao , Dong Xinyuan , Liu Congqiang , Wei Rongfei , Tao Zhenghua , Zhang Hua , Guo Qingjun
Published: March 2024

Mercury (Hg) is highly toxic and the only heavy metal that can exist in the atmosphere in gaseous form. When atmospheric Hg mixes with aerosols, it forms particulate-bound mercury (PBM). PBM can be transported and settle down quickly across regions, posing serious threats to ecosystems globally. Despite these concerns, tracking the sources and transport of atmospheric Hg remains challenging due to its global dispersal nature. However, the three-dimensional fractionation of Hg isotopes provides a feasible approach for addressing this issue. In this study, PBM2.5 and PBMTSPsamples were collected simultaneously in rural, suburban, urban, industrial, and coastal areas of the Beijing-Tianjin-Hebei (BTH) region, which is influenced by severe atmospheric pollution and the East Asian monsoon. Due to the significant influence of anthropogenic sources, the concentrations of PBM2.5 and PBMTSP were highest in the industrial and coastal areas, followed by the urban, suburban, and rural areas. The δ202Hg values of PBM2.5 and PBMTSP at the five sites were negative, overlapping with the values of most anthropogenic sources. However, most PBM2.5 and PBMTSP samples showed significantly positive Δ199Hg, significantly higher than the values of emission sources,especially for PBM2.5. The mass-independent fractionation (MIF) of Hg and sulfur isotopes showed that strong photochemical reduction happened during long-distance transport, making Δ199Hg have a positive shift. The positive changes in Δ200Hg may be due to ozone-mediated oxidation during the transport process, as shown by the interesting relationships between O3, Δ199Hg, and Δ200Hg in PBM2.5. Additionally, the analysis of backward trajectories unveiled the influence of air masses originating northwest of the BTH region through high-altitude transport. The cross-border transport of PBM, influenced by westerly and northwesterly air masses from Central Asia and Russia, markedly impacted  PBM pollution in the BTH region. Furthermore, these air masses, upon reaching the BTH area, would transport heightened PBM concentrations to the ocean through the winter monsoon. Conversely, during the summer, southeastward air masses transported from the ocean by the summer monsoon acted to mitigate the inland PBM pollution. The study results show that significant positive odd-MIF of PBM can occur in places with intensive anthropogenic emissions rather than being limited to remote areas. It implies that the odd-MIF resulting from atmospheric transport has likely been significantly undervalued. Our research offers valuable perspectives on the transport, transformation, and circulation of Hg in the environment.
Accurate calculation of Land Surface Heat Flux Based on Soil Observations over the Tibetan Plateau
Authors: He Jianan , Ma Weiqiang , Ma Longtengfei , Ma Weiyao , Shi Lele
Published: March 2024

The land surface heat flux is a crucial parameter that plays a significant role in the transformation and cycling of energy and matter between the atmospheric and land surface layers. This parameter serves as an essential input for various numerical models. Most land surface schemes deduce soil heat flux by amalgamating the heat conduction equation and residual method of energy balance. However, substantial discrepancies could be observed in soil heat flux simulations. These occurred among different Numerical Weather Prediction and offline Land Surface models, even though they were driven by the same atmospheric processes. The presence of discrepancies in models necessitated the accurate calculation of soil heat flux in order to reduce uncertainty in the allocation of sensible and latent heat flux at the surface. By reducing this uncertainty, we could decrease uncertainties in surface energy partitioning, achieved through diminishing the bias in simulated precipitation. However, in the Tibet plateau, soil heat flux observations were sparsely distributed, and the coverage period was different and limited, primarily used for model and remote sensing validation. There was a notable gap in research on the precise variations in soil heat flux in the Tibet plateau, particularly in studies employing sampled soil observations to accurately calculate soil heat flux. This study addressed these aforementioned deficiencies by focusing on soil attributes in the Tibet plateau to accurately calculate soil heat flux. In calculating soil heat flux precisely, factors like topography, land use, and vegetation type were considered. To ensure stability, representative soil cores were carefully observed and selected, obtaining samples through a layer-by-layer sampling approach. All sampling work had currently been completed.Utilizing comprehensive, synchronous, and continuous soil heat flux observations at the BJ site, in conjunction with long-term observational data and soil samples, we employed sampled soil attributes and soil heat flux plate observations to ascertain the requisite parameters for accurate soil heat flux calculation. These parameters, including the physical properties and porosity of soil profiles, enabled us to precisely determine the surface soil heat flux fluctuations at the BJ site. As a result of global warming, the Nagqu region had experienced elevated temperature, augmented precipitation, and amplified soil heat flux. In summary, accurately calculating soil heat flux is vitally important for allocating sensible and latent heat flux at the surface, which in turn diminishes uncertainty in the surface energy balance within models. This reduction in uncertainty is crucial for establishing a foundation to mitigate biases in local precipitation simulations within existing models.
Magnetosheath jets at jupiter and across the solar system
Authors: Zhou Yufei , Raptis Savvas , Wang Shan , Shen Chao , Ren Nian , Ma Lan
Published: March 2024

The study of jets downstream of Earth's bow shock has been a subject of extensive investigation for over a decade due to their close connection with shock dynamics and their profound impact on the geomagnetic environment. While the variability of the solar wind and its interaction with Earth's magnetosphere provide valuable insights into jets across a range of parameters, a broader parameter space can be explored by examining the downstream of other planetary bow shocks. Here we report the existence of anti-sunward and sunward jets downstream of Jovian bow shock and show their close association to magnetic discontinuities. The anti-sunward jets are possibly generated by a shock--discontinuity interaction. Finally, through a comparative analysis of jets observed at Earth, Mars, and Jupiter, we show that the size of jets scales with the size of bow shock.
Research on Machine Learning Hybrid Framework for Flood Forecasting by Integrating Physical Processes of Runoff Generation and Vectorized Flood Processes
Authors: Chengshuai Liu , Caihong Hu
Published: March 2024

One of the important non-engineering measures for flood forecasting and disaster reduction in watersheds is the application of machine learning flood prediction models, with Long Short-Term Memory (LSTM) being one of the most representative time series prediction models. However, the LSTM model has issues of underestimating peak flows and poor robustness in flood forecasting applications. Therefore, based on a thorough analysis of complex underlying surface attributes, this study proposes a framework for distinguishing runoff models and integrates a Grid-based Runoff Generation Model (GRGM). Additionally, a GRGM-K-LSTM hybrid flood forecasting model is constructed by coupling the flood process line vectorization method and LSTM. Taking the Jialu River in the Zhongmu station control basin as an example, the model is validated using 18 instances of measured floods and compared with the LSTM and GRGM-LSTM models. The study shows that the GRGM model has a relative error and average coefficient of determination for simulating runoff of 8.41% and 0.976, respectively, indicating that considering the spatial distribution of runoff patterns leads to more accurate runoff calculations. Under the same lead time conditions, the GRGM-K-LSTM hybrid forecasting model has a Nash efficiency coefficient greater than 0.9, demonstrating better simulation performance compared to the GRGM-LSTM and LSTM models. As the lead time increases, the GRGM-K-LSTM model provides more accurate peak flow predictions and exhibits better robustness. The research findings can provide scientific basis for coordinated management of flood control and disaster reduction in watersheds.
Observed climate extreme indices trends and variation in Gandhinagar, Gujarat
Authors: Kumar Sandeep , Pathak Bhawana
Published: March 2024

Climate change is very evident and transformative in the 21st century. Variations in rainfall and temperature define the ecosystem services, extreme events (flood, drought, heatwave etc.) and agricultural activities, especially in developing countries such as India where the majority of the population is agricultural dependent. Apart from global variability in rainfall and temperature, a significant change has been also observed at the regional level. Thus it’s also very important to study regional variation in climate extreme indices. In this paper historical variation (1991-2022) in rainfall and temperature extreme indices has been computed over the Gandhinagar district, Gujarat. Daily rainfall and temperature gridded data from the Indian Meteorological Department (IMD) have been acquired and used for the Expert Team on Climate Change Detection and Indices (ETCCDI) extreme indices calculation. A data homogenization technique was applied for the quality control and outliers were removed. As recommended by ETCCDI core rainfall (CDD, CWD, PRCPTOT, R30mm) and temperature (CSDI, WSDI, DTR) extreme indices were calculated. The trend was calculated using Mann-Kendall (M-K) and Sen’s slope estimator. It was observed that Consecutive Dry Days (CDD) are decreasing (R2 = 0.05) as the days having a minimum rainfall of 10mm are increasing (R2 = 0.02). Cold Spell Duration Indicator (CSDI) suggests that the period having minimum temperature is decreasing (R2 = 0.3) which is also supported by the decreasing Diurnal Temperature Range (DTR) (R2 = 0.25). The observed change in CSDI and DTR is more influenced by the minimum rather than maximum temperature as a continuous rise in minimum temperature has been observed since 1991. Since Gandhinagar district is developing at a very rapid pace the results of this study could be used for the climate change policy framework and better sustainable developmental strategies for the region.
Microtextures of modern tufa stromatolites from the peritidal zone near Schoenmakerskop, Eastern Cape, South Africa: investigating the relative contributions of microbes, algae and chemical precipitation to microbialite growth   
Authors: McLoughlin Nicola , Mahlapha Karabo
Published: March 2024

At Schoenmakerskop on the coast near Gqeberha (Port Elizabeth), modern microbialite deposits are forming where CaCO₃-supersaturated groundwater emerges at the contact between Pleistocene aeolianites and the underlying Cape Supergroup bedrock (Edwards et al. 2017). Two different systems were investigated: well-laminated spring line tufa deposits above intertidal beachrocks, and a series of barrage pools with active and remnant rimstone deposits showing thrombolitic and laminated mesofabrics. Petrographic light-microscopy and scanning electron microscopy (SEM) were used to investigate the relative contributions of biotic and abiotic processes in the formation of these microbialites.Light-microscopy identified isopachous light-brown sparry crusts consisting of tabular or platy carbonate, interpreted to have formed predominantly by chemical precipitation. Hybrid crusts were also found comprising alternating organic-rich layers and sparry crusts, along with colloform and micritic microtextures. Fossilised algal filaments were identified and SEM observations revealed both densely and loosely packed layers of hollow, unbranched filaments encrusted by microcrystalline carbonate. Exceptionally well-preserved draping biofilms were also found in some samples. Evidence for trapping and binding of clastic material was very limited, with only occasional diatom fragments. Taken together our observations point to a system dominated by chemical precipitation of carbonate with rapid precipitation leading to exceptional preservation of biofilms in submerged samples, and entombment of algal and sometimes microbial filaments. Evidence for biologically induced extracellular mineralisation of the algal filaments and microbial biofilms is recorded in these microbialites. The potential of these deposits to serve as analogues for chemical stromatolites in the fossil record is explored.Edwards et al. (2017). Macro- and Meso-fabric structures of peritidal tufa stromatolites along the Eastern Cape coast of South Africa. Sedimentary Geology 359: 62-75.
Two Physics-informed Enso Deep Learning Forecasting Models: ENSO-ASC and ENSO-GTC
Authors: Qin Bo
Published: March 2024

El Niño-Southern Oscillation (ENSO) events have significant impacts on global climate change, and the research on their accurate forecasting and dynamic predictability holds remarkable scientific and engineering values. Recent years, we have constructed two ENSO deep learning forecasting models, ENSO-ASC and ENSO-GTC, which are both incorporated with prior ENSO dynamic mechanisms. Specifically, the former possesses the multivariate air-sea coupler (ASC), which can simulate the occurrence and decay of ENSO events, accompanied by concurrent energy interactions among multiple physical variables in the Pacific Ocean. The latter possesses the global teleconnection coupler (GTC), which can modulate the significant teleconnections of global ocean basins rather than the isolated interactions in the Pacific Ocean. From the perspective of forecasting skill, the Niño 3.4 index correlation skills of these two models can reach 0.78/0.65/0.50 (0.79/0.66/0.51) in 6/12/18 lead-month prediction, which means they exhibit an effective forecasting lead month of more than 18, outperforming the Ham et al.'s Nature-published ENSO forecasting model. The test of the past year's (2022) forecast results shows that the average forecast error of these two models is 0.156, which is less than 10% of the actual ENSO amplitudes. It is worth noting that these two models also encounter the spring presistence barrier (SPB), but indicates a profound improvement compared to the numerical models. From the perspective of ENSO predictability, zonal and meridional winds are two sensitive predictors for ENSO forecasting besides sea surface temperature (SST), which greatly contribute to the Bjerknes positive feedback mechanism and WES mechanism. Walker circulation, acting as the "atmpsphric bridge", induces the teleconnections of the three oceans, which can derive the easterly wind anomalies in the equatorial western Pacific from the Indian Ocean and North Pacific meridional mode in the northeastern Pacific from the Atlantic Ocean, promoting ENSO event development and decay.
Spatio-temporal evolution of glacial lakes in the Upper Ganga basin, Central Himalayas
Authors: Kumar Atul , Mal Suraj , Schickhoff Udo
Published: March 2024

The rise in annual mean temperature due to anthropogenic climate change is causing faster melting and thinning of glaciers leading to the formation of new glacial lakes and the expansion of existing ones in the Himalayan region. This exponential growth of glacial lakes increases the availability of freshwater resources and escalates the risk of future Glacial Lake Outburst Floods (GLOFs).In the present study, Glacial lake inventories for the Upper Ganga basin were generated at the sub-basin level for 1990, 2000, 2010 and 2020 using Landsat (TM and OLI) images and semi-automated methods to understand the evolution of glacial lakes, altitudinal, orientational and typology changes. We were able to map 2,554 (area: 170.15 sq. km) glacial lakes in 1990, 2,783 (area: 191.03 sq. km) in 2000, 2,834 (area: 201.44 sq. km) in 2010, and 3,118 (area: 210.87 sq. km) in 2020. Between 1990 and 2020, the total number of glacial lakes increased by 564 (22.08%) and the total area increased by 40.72 sq. km (23.93%). In the year 2020, glacial lakes were found in 31 sub-basins of the Upper Ganga basin, out of 31 sub-basins, Arun sub-basin had the maximum number of glacial lakes (n: 734 & area: 61.66 sq. km).The mean elevation of glacial lakes increased from 5,044.81 m asl (1990) to 5,052.30 m asl (2020), showing an increase of 7.49 m asl. In 2020, the majority of the glacial lakes were distributed in the elevation zone of 5,000-5,500 m asl (n:1,404 & area: 113.79 sq. km). In the upper Ganga basin, majority of the glacial lakes were south-facing (491) in 2020.End moraine-dammed (M(e)) lakes dominate among differnt types of glacial lakes. In 1990, there were 2,081 (M(e)) lakes, which increased to 2,413 in 2020, indicating towards increasing risk of future Glacial Lake Outburst Floods (GLOFs) in the Upper Ganga basin. Therefore, the present study provides vital insights into the glacial lake dynamics of the Upper Ganga basin at the sub-basin level and will help in identifying potentially dangerous glacial lakes and developing robust policies to mitigate the impact of future GLOF events.
Multilayer HySEA granular flow and tsunami model improves results over single layer models: sensitivity analysis, benchmarking against flume experiments, and implications for field scale models.
Authors: Silver Maxwell M. W. , Marboeuf Alexis , Mangeney Anne , Le Friant Anne , Fernandez Nieto Enrique D. , Belieres-Frendo Amaury , Bougouin Alexis , Roche Olivier , Paris Raphael , Moatty Annabelle
Published: March 2024

     Granular avalanches that enter a body of water present a hazard to coastal communities via their ability to generate tsunami waves. By improving the accuracy of model estimates of tsunami severity and quantifying the error of said models, we can improve the accuracy of tsunami hazard assessments. Sensitivity analyses were performed of the hybrid finite-difference finite-element model HySEA to changes in the number of vertical layers used to discretize the water column (from a single layer up to 5 layers), non-hydrostatic vs hydrostatic fluid pressures, different friction rheological laws (Pouliquen and μ(I)), and various friction coefficients. Flume experiments with matching conditions were used to benchmark simulations. An improved fit between simulation and experiment wave heights and wave frequencies, as well as improved model stability was found with 3 to 5 vertical water discretization layers compared to using a single water layer. We also demonstrate an improved fit between simulation and experiment wave heights, speeds, and form with non-hydrostatic versus hydrostatic conditions, although most simulations performed here did not accurately estimate wave speeds. Only minor changes in fit were observed between the Pouliquen and μ(I) friction laws. We demonstrate that multilayer HySEA can reliably estimate tsunami wave heights with a reasonable certainty (< 38% error) without any fitting across different granular mass volumes, grain sizes, and slopes of flow and can reach errors < 2% with only limited fitting. Furthermore, we detail how to improve model fit using additional rheological information (e.g., grain size, slope, volume of mass) and friction coefficients.
Leaching potential of coal waste organic compounds; a simulation study with fresh and saline water (Upper Silesia Coal Basin, Poland)
Authors: Fabiańska Monika , Goleniak Arkadiusz , Misz-Kennan Magdalena , Ciesielczuk Justyna
Published: March 2024

The vast amount of waste rocks excavated during coal mining and stored in dumps presents a significant environmental problem as they readily undergo spontaneous heating. The process produces large amounts of organic compounds, relatively well-soluble in water. The problem is severe because self-heating has been registered in many coal mining regions. The brine application as an anti-pyrogenic agent to prevent self-heating is a method that is still being developed. Its advantages are the ignition temperature increase, rock pores sealing by crystallizing salt, and permeability decrease, preventing contact with oxygen. Since there is no knowledge about the brine potential to leach organic compounds from coal wastes, this project aims to characterize components leached by rainwater and brine applied as an anti-pyrogen.The Starzykowiec dump has stored coal wastes since the beginning of the 20th century. They consist of mudstones, siltstones, claystones, and arcosic sandstones. Most self-heating occurred from the 1940-60s. For the procedure, samples representing six rock types were selected, all thermally affected to different degree. Maceral composition and mineral content were determined at 500 points, and random reflectance was measured on vitrinite particles at 5-100 points. Two rock portions (ca 60g) powdered to
3D Hybrid simulation of the self-consistent propagatinginterplanetary shock wave in the Solar Wind
Authors: Ginisty François , Fontaine Dominique , Savoini Philippe , Cazzola Emanuele
Published: March 2024

Interplanetary shocks propagate in the interplanetary medium alone or as part of solar tran-sients as interplanetary coronal mass ejections, stream interaction regions, etc. . . Their interactionwith the terrestrial environment may trigger geomagnetic activity in the magnetosphere which mayeven cause damages of man-made devices for the most severe events. The common feature of theseshocks and front shocks is their large velocity relative to the ambient plasma.By means of a 3D hybrid PIC code, we simulate a steady solar wind and introduce a shock witha larger velocity at the entrance of the simulation box. We then let it self-consistently propagatein the interplanetary medium. As expected, we observe that the shock front is characterized bya jump of the plasma parameters. Immediately following the shock, a denser and more turbulentlayer is progressively forming and growing. We analyze the time evolution of the characteristicparameters of the shock and his following plasma layer. We discuss these results by comparison toobservations in the interplanetary medium upstream of Earth.
Re-visiting the dip-slip rate of the North Tehran Fault at the northern megacity of Tehran (Iran) using luminescence dating 
Authors: Heydari Maryam , Ghassemi Mohammad R. , Grützner Christoph , Preusser Frank
Published: March 2024

The North Tehran Fault (NTF) is the most active tectonic structure crossing the northern fringe of the densely populated megacity of Tehran (Iran). It extends over 68 km and juxtaposes the southern piedmonts of the Central Alborz Mountains (volcanic rocks associated with the Karaj Formation) from the Neogene-Quaternary Tehran Alluvium. The NTF is an oblique-slip fault in which the left-lateral strike-slip faulting accompanies the dominant reverse motion.The geomorphic features affected by the NTF’s activity appear to be limited and concealed during the past few decades due to the rapid northward expansion of the Tehran metropolitan area. Nevertheless, numerous evident fault outcrops, displaying stratigraphic offsets in various locations along the megacity, are still accessible.This study selects two fault outcrops inside the city in the western segment of the NTF and a third one in the eastern termination of the NTF close to its junction with the Mosha Fault. These sites were already studied in previous works, however, no reliable geochronological data have been available so far for them. In the first two western sites, the Eocene Karaj Formation rocks were thrust over Quaternary alluvial-colluvial deposits. The subsidiary fault is almost parallel to the main NTF in the second site at Kan, which separates the old alluvial-colluvial deposits in the hanging wall from the younger deposits in the footwall. The third site is located close to the termination of the NTF in the Kond region. Here, remnants of Quaternary fluvial terraces are uplifted by the NTF and form elevated landforms identified in its hanging wall.To estimate the dip-slip rate for the NTF, we applied luminescence dating to the alluvial-colluvial deposits and fluvial terraces to constrain the deposition time. By incorporating the measured vertical offset for each site, the dip-slip rates of the NTF were established at different locations.
Quantifying the impact of near-surface winds on the occurrence of extreme sea level rises along the Swedish Baltic coastline: A statistical analysis
Authors: Minola Lorenzo , Re Alice , Bedoya-Valestt Shalenys , Motta Corrado , Azorin-Molina Cesar , Pezzoli Alessandro , Chen Deliang
Published: March 2024

Sea level rises pose significant risks to densely populated coastal regions, threatening human lives and vital infrastructures. Coastal societies, economies, and properties face acute vulnerability from saltwater intrusion, coastal erosion, and flooding resulting from extreme sea level variations. These occurrences are a confluence of factors, including local sea level rises, tidal changes, storm surges, waves, and shifts in coastal morphology.In the Baltic Sea basin, where tides and North Atlantic storm surges are mitigated by the Danish Straits due to its semi-enclosed nature, coastal extreme sea levels are primarily driven by storm surges propelled by atmospheric pressure and surface winds from extratropical cyclones. Consequently, the surge in extreme sea levels here is predominantly wind-induced, regulated by meteorological processes.This research focuses on the meteorological conditions, specifically wind patterns, that contribute to sudden sea level rises along the Swedish Baltic coastline. By integrating observations and model data like the ERA5 reanalysis, the study correlates the rapid increase in relative sea levels across 14 tide-gauge stations with wind and wave data. The aim is to exclusively utilize meteorological information for identifying extreme sea level occurrences, thereby enhancing the prediction of such events through weather forecasting.
Integration of data from agricultural practice into the Swiss agri-environmental monitoring project MAUS
Authors: Blaser Silvio , Baumgartner Simon , Schneuwly Jérôme , Gilgen Anina
Published: March 2024

In order to fulfil the requirements of the Agriculture Act and the Ordinance on the Assessment of Sustainability, the Swiss Federal Research Centre Agroscope assesses the quantitative and qualitative impacts of agriculture on the environment using regional and farm-related eco-indicators. This is done by the monitoring of the Swiss agri-environmental system (MAUS).Thematically, these indicators cover a wide range of agroecological hotspots, such as humus, heavy metal and nutrient balances, use and risks of plant protection products, potential impact on biodiversity, greenhouse gas emissions and others. Agroscope bases the calculation of the indicators largely on existing data. To supplement and improve the quality of this data, MAUS is currently launching projects to acquire and integrate data from remote sensing, online surveys and farm management information systems (FMIS).Integrating FMIS data essentially means requesting data that is already collected by farmers for their farm management and in order to receive direct payments. A large part of this is field calendar data, which describes what happened in a field after the previous crop was harvested: e.g., how was the seedbed prepared, what fertilisation and plant protection measures were carried out before the crop was harvested, etc.There are various large gaps in the level of detail and scope of the FMIS available on the market compared to what is needed to calculate the indicators. Therefore, solutions are needed that allow the farms providing data to supplement missing information and, where necessary, to specify the entries for MAUS.As part of a pilot project, a technical solution was developed with one of the Swiss providers and is currently being implemented. This has shown that, in addition to a precise definition of requirements, constant and lively dialogue is important. A comprehensive data set that exemplifies how operating data must arrive at MAUS not only helps with final testing, but also with understanding the implementation.In the near future, other interested FMIS are to supplement their platforms so that data can be supplied to MAUS. In the collaboration between Agroscope and the interested providers, both parties will benefit from the preliminary work and the findings of the pilot project.
Simulating two-phase flow using Physics-informed neural networks with capillary heterogeneity and hydraulic discontinuities
Authors: Chakraborty Anirban , Moreno Ziv
Published: March 2024

Simulations of two-phase flow in heterogeneous porous media are crucial for several applications, such as CO2 sequestration, efficient oil and gas recovery, and groundwater pollution remediation. Modeling of two-phase flow systems becomes very challenging when capillary heterogeneity and hydraulic discontinuities are considered. Traditional models use numerical techniques such as finite difference, finite element, and finite volume for solving the partial differential equations of the system. Although numerical methods have been shown to produce reliable solutions for complex flow problems, they can become computationally expensive. This emphasizes the high computational demand for solving the inverse problem. The use of DNNs (deep neural networks) has become more common in predicting subsurface flow behavior. DNNs is a data-driven approach that enables the learning of a system by linking input and output parameters and provides fast predictions of dynamic, complex systems. Nevertheless, when data is extremely scarce, particularly in subsurface systems, standard DNNs are unable to yield robust results. Recent advancements enable the integration of physical constraints as partial differential equations (PDEs) into the DNNs scheme. Such a class of deep learning techniques is generally referred to as physics-informed neural networks (PINNs). PINNs are also capable to provide forward solutions for PDEs.  In this work, we examined PINNs' capabilities to provide forward solutions of a 1D steady-state two-phase flow with capillary heterogeneity at the sub-core scale. Here, we trained a PINNs system that incorporates high variability in the hydraulic properties and boundary conditions implemented as input parameters. We compared the PINNs results with numerical solutions to test the efficiency of the developed PINNs system. Results have shown that the trained PINNs system could reproduce both capillary pressure and phase saturation profiles for altering fractional flows, injection rates, hydraulic properties, and domain lengths with high accuracy and within a single training. Training the extended PINNs system was obtained in a few hours, and the post-trained system provided unlimited solutions for variable structures and boundary conditions within a few seconds. 
The atmospheric circulation anomalies associated with the formation of marine heatwaves in the Northeast Pacific
Authors: Tang Cong , Lu Riyu
Published: March 2024

Extreme and persistent marine heatwaves (MHWs) occur frequently in the Northeast Pacific, with huge impacts on climate, ecosystem and socio-economic. This study investigates the atmospheric circulations associated with the 33 MHWs since 1951 in observations. The composite results reveal that the MHWs in the Northeast Pacific can be triggered by a couple of anticyclonic and cyclonic anomalies, i.e., the anticyclonic anomaly to the northeast of the MHW region and cyclonic anomaly to the southwest.  This atmospheric circulation pattern can be detected as the dominant mode through EOF analysis on 500-hPa geopotential height anomalies over the Northeast Pacific-North America region, following the Pacific–North American teleconnection. These observational results are verified by using the outputs of 34 models in the historical simulation from phase 6 of the Coupled Model Intercomparison Project (CMIP6). Further diagnosis of the heat budget is performed, in attempt to illustrate the processes of MHW formation and maintenance.
Temperature trends  in olive growing season in producing areas of Extremadura (Spain)
Authors: Paniagua Luis L. , García-Martín Abelardo , García García Dolores , Aguirado Cristina , Rebollo F. Javier , Moral Francisco J. , Honorio Fulgencio
Published: March 2024

The olive tree is mainly cultivated in the temperate zones of the Mediterranean area. Temperature is the main factor to evaluate the climatic suitability for olive cultivation. The study of the spatial and temporal variations of temperatures in a territory is necessary to define the most appropriate areas for production, as well as to evaluate different varieties. Extremadura has more than 269,000 ha of olive trees with a production of 884,960 tonnes, the third-largest surface area, and the second-largest olive-growing production in Spain. In this study the number of olive active days (OAD), the growing degree-days (GDD), and the average temperature of the olive growing period (OGST) index are analysed. The active days for the olive tree have been defined as those in which the average daily temperatures are above 14.4 °C between April and October. The minimum and maximum daily temperatures, from the meteorological data base of the Spanish government (AEMET), located in the main olive growing areas have been used, considering a period from 1991 to 2020. Mann-Kendal test and Sen's slope have been used to determine trends and their magnitude. The results show 200 active days per year, between 185 in Ibores and 215 in Vegas del Guadiana. The mean GDD value was 1514°C, varying between 1363°C in the Ibores area and 1685°C in La Serena whith a significant increasing trend in five areas. Growing degree-days have increased by an average of 4.9°C per year. The mean OGST value was 22.0°C, varying between 21.7°C in the Logrosan-Guadalupe area and 22.4°C in La Siberia. It has also shown a significant increasing trend in the index in four areas. Temperatures in the olive tree growth period have increased by an average of 0.21°C per decade, which represents an average increase of 0.67°C between 1991 and 2020.Keywords: olive, active days, degree-days, temperature, trends, Spain.
High-resolution volcanic SO2 emissions in WACCM produce more realistic AODs
Authors: Axebrink Emma , Friberg Johan , Sporre Moa K.
Published: March 2024

Volcanic climate impact is strongly correlated with how high its effluents reach in the atmosphere. Volcanic SO2 injected into the stratosphere can have a residence time of several years, whereas injections in the troposphere only have a residence time of weeks.We have performed simulations of the 2009 Sarychev eruption with the Community Earth System Model version 2 (CESM2), Whole Atmosphere Community Climate Model version 6 (WACCM6). We have compared the standard model dataset with two high-resolution datasets developed in our group to investigate the importance of utilizing highly vertically and horizontally resolved SO2 datasets. The default dataset M16 [1] used in WACCM has a vertical resolution of 1 km and is released in one latitude longitude gridbox. Our two high-vertical resolution datasets, S21-3D, and S21-1D, were created from the dataset of Sandvik et al. [2]. These datasets have a vertical resolution of 200 m, spanning from 7.6 to 18.6 km. S21-3D is distributed over several latitudes and longitudes, whereas S21-1D releases all SO2 in one latitude longitude gridbox to mimic the default dataset in WACCM.The SO2 from S21-3D, and S21-1D is injected at a higher altitude than the M16, leading to a longer residence time for both the SO2 and the formed stratospheric aerosol. The S21-3D dataset has the highest stratospheric SO2 and SO4 concentrations of the three simulations and the concentrations peak later than the other two simulations. The results from the S21-1D dataset are similar to those from the S21-3D simulation but with slightly lower concentrations.The simulated S21-3D AOD agrees with AOD from the space-borne lidar instrument CALIOP. In the simulation with the M16 dataset, the AOD is underestimated by >50%. The volcanic radiative forcing from the Sarychev eruption was 31% lower at the end of 2009 in the simulation with M16 compared to the simulation with S21-3D.Our results show that the vertical resolution of SO2 injections substantially impacts the model’s ability to correctly simulate the climate effects of volcanic eruptions, especially if the SO2 is injected in the vicinity of the tropopause.Future work will involve simulating a high vertically resolved dataset of SO2 of other volcanic eruptions since 2006.References [1] Mills, M. J., A. Schmidt, R. Easter, S. Solomon, D. E. Kinnison, S. J. Ghan, R. R. III Neely, D. R. Marsh, A. Conley, C. G. Bardeen, et al. (2016), Global volcanic aerosol properties derived from emissions, 1990–2014, using CESM1(WACCM), J. Geophys. Res. Atmos., 121, 2332–2348, doi:10.1002/2015JD024290.[2] Sandvik, O. S., Friberg, J., Sporre, M. K., and Martinsson, B. G.: Methodology to obtain highly resolved SO2 vertical profiles for representation of volcanic emissions in climate models, Atmos. Meas. Tech., 14, 7153–7165, https://doi.org/10.5194/amt-14-7153-2021, 2021.
Taylor’s law predicts unprecedented pulses of forest disturbance under global change
Authors: Senf Cornelius , Seidl Rupert , Knoke Thomas , Jucker Tommaso
Published: March 2024

Climate extremes are causing increasingly large pulses of forest disturbance across biomes, raising concerns that forests are pushed beyond their safe operating space. Predicting future disturbance pulses remains, however, a major challenge, because disturbance pulses are stochastic and driven by complex ecological and socio-economic processes. Here, we provide a tractable solution to this problem using Taylor's law, which relates the mean and variability of a system through a power law relationship (variance ~ meanb). We test the hypothesis that forest disturbance dynamics can be described through Taylor’s law using high-resolution (30 m) annual disturbance maps of Europe’s forests going back 35 years and covering more than 1.6 million km2 of forests. We find strong evidence for a positive power law relationship between mean disturbance rates and their temporal variability (R2 of 0.95), indicating that increasing mean disturbance rates – as observed for Europe and many other parts of the globe – significantly amplify the probability of large pulses of tree mortality. The power law relationship was consistent across natural disturbance agents (bark beetle, fire, wind), spatial scales (100-25,600 km2) and biomes (boreal, temperate, Mediterranean) with a power law coefficient of b = 2.35, and also applied to human-dominated disturbances (R2 of 0.84 but a lower power law coefficient of b = 1.86). Simulations based on the power law model illustrate how increasing mean disturbance rates cause annual disturbance rates to quickly become more variable, and thus more likely to include extremely large disturbance pulses: A long-term mean disturbance rate of 1 % yr.-1 will lead to disturbance pulses with > 5 % annual mortality once every 112 years (0.9 % probability). Increasing disturbance rates to 1.5 % yr.-1, however, we would expect a disturbance pulses of the same magnitude already every five years (19 % probability). Our findings thus challenge the assumption that extreme disturbance pulses as observed recently were unexpected or inherently unpredictable, providing a framework for the integration of future disturbance pulses into forest policy and management.
Typology of world’s river basins regarding socio-ecological resilience to ten major water related risks
Authors: Varis Olli
Published: March 2024

Risks to the planet's freshwater systems are currently subjected to soaring concern worldwide. We applied the coupled Social-Ecological Systems approach to study and systematize the risks due to ten major water related stressors (variability, overuse, groundwater, floods, droughts, organic pollution, salinity, eutrophication, drinking water, sanitation). We used gridded socioeconomic indicator data for the analysis of human exposure and its vulnerability (adaptive capacity) to these stressors in 540 river basin units covering the whole world. Among the stressors, lack of appropriate sanitation scored highest, followed by droughts and eutrophication. The large and densely populated Asian basins, Ganges-Brahmaputra-Meghna, Indus, and Yangtze, topped, followed with the largest African basins (the Nile, Niger, and Congo/Zaire). The other top-ten basins were Rajasthan Inner Basins, Huang, Hai, and Myanmar South Coastal Basins. The ranking changed when weighting the stressor data (on physical entities) with socioeconomic vulnerability data (on societal ones). Each included basin unit manifested a specific risk profile. For the basin units, we developed a typology using principal component and cluster analyses. This allowed us identification of the roles of vulnerability and population exposure in worldwide river basin risk framework and revealed distinctive basin clusters associable with the following characterizations: (1) too little water – high salinity – high variability – overexploited, (2) high organic pollution, eutrophic, flood prone – highly populated, (3) water abundant, (4) lacking infrastructure – low socioeconomic development. These clusters largely form a sequence as for instance there are basins that fall at the edge of (1), with many similarities already to (2), etc. The analysis provides a new perspective to comparison of world’s river basins and looking for novel learning opportunities for river basin management and risk reduction policies, especially in a multihazard-multirisk setting allowing the identification of the basin-specific risk profile and the roles of vulnerability and exposure.
Patterns of deformation and connectivity at Western Galápagos Volcanoes
Authors: Ebmeier Susanna , Reddin Eoin , Rivalta Eleanora , Bagnardi Marco , Baker Scott , Bell Andrew , Mothes Patrica , Aguaiza Santiago
Published: March 2024

The Western Galápagos volcanoes of Alcedo, Cerro Azul, Darwin, Fernandina, Sierra Negra, and Wolf have exceptionally high rates of eruption and unrest.  Deformation rates measured using Interferometric Synthetic Aperture Radar are high magnitude during eruptions and episodes of magmatic intrusion, but also significant during inter-eruptive periods.  There are characteristic differences in deformation and unrest styles between the volcanoes that have persisted for at least three decades, indicative of the impact of topography, magmatic zone maturity and magmatic flux.   Here, we focus on analysing the trends in displacements at these six volcanoes over the past three decades. These show correlations not only in long-term uplift and subsidence, but also in short term fluctuations in displacement rate.  Correlation is especially high during episodes of high melt flux into the shallow crust, indicating some degree of connectivity in the subsurface. We are able to rule out static stress changes, shallow hydraulic connections and radar processing artefacts, and suggest that the mechanism for connectivity lies in pore pressure diffusion at the base of the crust, as inferred at Hawai’i.Volcanic deformation is generally interpreted in the context of shallow magmatic reservoirs treated as discrete independent systems.  However, in the Western Galápagos, and potentially many other places around the world, they are actually the most accessible expression of vertically extensive, heterogeneous magmatic systems.
Machine Learning for Nonorographic Gravity Waves in a Climate Model
Authors: Hardiman Steven , Scaife Adam , van Niekerk Annelize , Prudden Rachel , Owen Aled , Adams Samantha , Dunstan Tom , Dunstone Nick , Madge Sam
Published: March 2024

Use of machine learning algorithms in climate simulations requires such algorithms to replicate certain aspects of the physics in general circulation models.  In this study, a neural network is used to mimic the behavior of one of the subgrid parameterization schemes used in global climate models, the nonorographic gravity wave scheme.  Use of a one-dimensional mechanistic model is advocated, allowing neural network hyperparameters to be chosen based on emergent features of the coupled system with minimal computational cost, and providing a testbed prior to coupling to a climate model. A climate model simulation, using the neural network in place of the existing parameterization scheme, is found to accurately generate a quasi-biennial oscillation of the tropical stratospheric winds, and correctly simulate the nonorographic gravity wave variability associated with the El Niño–Southern Oscillation and stratospheric polar vortex variability. These internal sources of variability are essential for providing seasonal forecast skill, and the gravity wave forcing associated with them is reproduced without explicit training for these patterns.
In-flight GNSS phase map calibration modelling with Zernike polynomials
Authors: Baños Garcia Adrian
Published: March 2024

GNSS processing for POD suffers from systematic errors when the location of the instantaneous phase center is not knownwith a few millimeter accuracy. The traditional approach to model the GNSS phase center origin and variations is todetermine antenna phase maps iteratively from the residuals. A more direct approach consists in modeling the antennaphase map through an expansion in well-chosen Zernike polynomials, in order to reduce potential correlations with dynamicmodeling errors. This strategy has been applied to derive the GNSS antenna phase maps of several altimetry missions suchas Sentinel-3A, Jason-3, Sentinel-6 MF and SWOT. The derived phase corrections were tested on CNES POE-G GNSS-onlyreduced-dynamic orbit solutions to assess their impact and validate their benefits owing to independent SLR observations. 