bluuebunny/crossref_metadata_2025 huggingface dataset:
Global automatic detection of methane emissions in Sentinel 2 data using deep learning
Authors: Rouet-Leduc Bertrand , Hulbert Claudia
Published: March 2024

Methane is one of the most potent greenhouse gases, and its short atmospheric half-life makes it a prime target to rapidly curb global warming. However, current methane emission monitoring techniques primarily rely on approximate emission factors or self-reporting, which have been shown to often dramatically underestimate emissions.Although initially designed to monitor surface properties, satellite multispectral data has recently emerged as a powerful method to analyze atmospheric content. However, the spectral resolution of multispectral instruments is poor, and methane measurements are typically very noisy. Methane data products are also sensitive to absorption by the surface and other atmospheric gases (water vapor in particular) and therefore provide noisy maps of potential methane plumes, that typically require extensive human analysis.Here we show that the image recognition capabilities of deep learning methods can be leveraged to automatize the detection of methane leaks in Sentinel-2 satellite multispectral data, with dramatically reduced false positive rates compared with state-of-the-art multispectral methane data products, and without the need for a priori knowledge of potential leak sites.Our proposed approach is validated on thousands of catalogued leaks from AVIRIS-NG and GAO airborne detection campaigns, and paves the way for the automated, high-definition and high-frequency monitoring of point-source methane emissions across the world.
Sources of S2S and MJO predictability
Authors: Zhang Chidong
Published: March 2024

One main justification for subseasonal-to-seasonal (S2S) prediction is its identified sources of predictability. These sources include slowly varying phenomena, such as the MJO, stratospheric conditions, upper-ocean heat content, soil moisture, and sea ice. In practice, however, these presumed sources of S2S predictability have become the main targets of S2S prediction. For example, predicting the MJO, especially its propagation over the Indo-Pacific Maritime Continent, has been challenging. This raises a fundamental question: What are the predictability sources of the MJO? For global coupled prediction models, the primary sources of predictability are initial conditions and the governing laws. It is unclear, however, what elements in the initial conditions are more important to MJO prediction than others. It can be argued that the current practice of initializing forecasts using a single state of the system may not be optimal. Embedded initial conditions may provide an additional source of predictability that has yet to be fully explored.
Advancements in the Ongoing Development of the Black Sea Physical Analysis and Forecasting System
Authors: Ilicak Mehmet , Azevedo Diana , Jansen Eric , Causio Salvatore , Lima Leonardo , Sozer Adil , Maslo Aljaz , Creti Sergio , Trotta Francesco , Coppini Giovanni , Pinardi Nadia
Published: March 2024

The Black Sea Physical Analysis and Forecasting System (BSFS) operates within the Black Sea Monitoring and Forecasting Centre (BLK-MFC) as part of the Copernicus Marine Service (CMEMS). Here we present ongoing research and development activities for the future generations of the BSFS. The current system has the 1/40-degree horizontal grid NEMO ocean model featuring 121 vertical levels. Significant enhancements encompass the integration of biharmonic horizontal viscosity instead of the traditional Laplacian constant viscosity. This adaptation effectively mitigates small-scale grid noise, thereby elevating accuracy in representing mesoscale eddies.A notable advancement includes the implementation of a two-way nested domain surrounding the Bosphorus Strait, employing the NEMO-AGRIF mesh refinement algorithm. This newly constructed high-resolution Bosphorus Strait domain has a 1/200-degree horizontal resolution, facilitating much better resolution of the strait's bathymetry.Further refinements encompass recent developments targeting improvements in the model's eddy kinetic energy (EKE), relative vorticity fields, and minimized drift below the thermocline which is crucial for longer integration in a reanalysis scope. A concurrent effort involves the ongoing development of a new domain encompassing the Azov Sea, coupled with a sea-ice model. This initiative involves the utilization of different bulk formulas, enabling the incorporation of sea ice fluxes and AGRIF mesh refinement capabilities.Testing of the enhanced domain configuration involves rigorous assessments aimed at validating the efficacy of these updates, ensuring a comprehensive evaluation of the system's performance.
InSAR Phase Bias Correction Processor: Recent Developments
Authors: Maghsoudi Yasser , Hooper Andrew , Wright Tim , Lazecky Milan , Pinheiro Muriel
Published: March 2024

The Sentinel-1 satellite's short revisit time is advantageous for maintaining better coherence in interferograms over short intervals, resulting in more accurate assessments of rapid deformation. However, the use of shorter-interval, multilooked interferograms may introduce a bias, known as a "fading signal," in the interferometric phase, leading to unreliable velocity estimates.In the first part of our research, funded by the European Space Agency (ESA), we explore characterizing phase bias, focusing on one of its primary indicators—the closure phase. We explore loop closure time-series across various datasets, considering different look directions (ascending and descending), evaluating the impact of filtering and multilooking on closure phases, investigating loop closures across diverse landcovers, and examining the polarization dependency of closure phases. Additionally, we establish correlations between the time series of phase closures and various environmental proxies.In the second stage, we present our progress on developing a universally applicable phase bias correction. We previously developed an empirical mitigation strategy that corrects the phase bias based on the assumption that the change in strength of the bias in interferograms of different length has a constant ratio (Maghsoudi et al. 2022). In this presentation, we investigate the applicability of the proposed method across various scenarios and compare it with alternative approaches.Correcting for the phase bias is particularly important for InSAR processing systems, such as the COMET LiCSAR system (Lazecký et al. 2020), which aims to study geohazards over large areas. ReferencesMaghsoudi, Y., Hooper, A.J., Wright, T.J., Lazecky, M., & Ansari, H. (2022). Characterizing and correcting phase biases in short-term, multilooked interferograms. Remote Sensing of Environment, 275, 113022Lazecký, M., Spaans, K., González, P.J., Maghsoudi, Y., Morishita, Y., Albino, F., Elliott, J., Greenall, N., Hatton, E., Hooper, A., Juncu, D., McDougall, A., Walters, R.J., Watson, C.S., Weiss, J.R., & Wright, T.J. (2020). LiCSAR: An Automatic InSAR Tool for Measuring and Monitoring Tectonic and Volcanic Activity. Remote Sensing, 12 
Detecting the heaviness of daily rainfall probability distributions in Europe through an expeditious method, the Obesity Index
Authors: Marconi Flavia , Moccia Benedetta , Ridolfi Elena , Russo Fabio , Napolitano Francesco
Published: March 2024

Extreme precipitation events have a significant impact on hydraulic infrastructure design and risk management. The World Climate Research Programme (WCRP) Grand Challenges highlights the need for further investigation in analyzing and modeling weather and climate extremes due to their substantial effects. These rare meteorological occurrences represent the upper tail of the probability distribution, which can be effectively defined as heavy or light. The Obesity Index (OB) represents a user-friendly, non-parametric, empirical method capable of quantitatively assessing the heaviness of probability distribution tails directly from the original dataset, without the need to extract only extreme values. Our assessment of OB involves two distinct gridded datasets: one specific to Italy (SCIA) and another covering the entire Europe (E-OBS). The analysis shows a robust correlation between OB and L-moment ratios (L-variation, L-skewness, L-kurtosis), along with the Coefficient of Variation (CV). It is interesting to note that the tail heaviness in a specific region may vary depending on the dataset employed. For instance, OB indicates a prevalence of heavy tails across Italy or lighter tails in specific areas of the peninsula when employing SCIA or E-OBS dataset, respectively. This divergence could be attributed to an excessive smoothing of rainfall observations during the interpolation procedures used in generating E-OBS dataset. Thus, our findings reinforce the thesis of using light-tail probability distributions with caution when addressing rainfall extremes.
Analysis of Primary Productivity Variability in the Transitional Zone of the Mexican Pacific during the Late and Middle Holocene
Authors: Acevedo Thalia , Sánchez Alberto
Published: March 2024

The transitional zone of the Mexican Pacific is a complex region in terms of its oceanographic conditions. This leads to changes in primary and exported productivity over various time scales. This study employs geochemical tracers—organic carbon (CO), biogenic opal, and calcium carbonate—to assess sedimentary records' primary and exported productivity. Analyzing responses to past warm periods is crucial for understanding marine productivity in future climate change scenarios. The objective of the present study was to quantify organic carbon content and to infer changes in primary and exported productivity in the transitional zone of the Mexican Pacific for the late Holocene and the final part of the middle Holocene. The sediment core, collected at a depth of 680 meters on the southwestern margin of Baja California Sur. It has a length of 137 cm and was sectioned at intervals of 1 cm, representing 137 samples. The estimated age from ¹⁴C was 5466 years. Each one-centimeter interval denotes 33 years. CO analysis used a COSTECH 4010 elemental analyzer with 0.2% analytical accuracy, employing BBOT and Urea certified standards. Biogenic opal determination follows the molybdenum blue spectrophotometric method by Mortlock and Froelich (1989). CO content ranged from 8% and 14%, showing periodic changes at ~300, ~170, and ~100 years. Biogenic opal ranged from 0.2 to 19.3%, with abrupt changes at ~310, ~270, and ~70 years. Organic carbon and biogenic opal exhibited a positive correlation, indicating increased productivity during warm periods like the Roman Warm Period (1800 to 2200 years ago) and the Medieval Warming Period (700 to 1100 years ago). This suggests responsiveness to oceanographic conditions across various time scales.
Helium diffusion systematics in apatites: lessons from Continuous Ramped Heating analysis
Authors: Guo Hongcheng , Zeitler Peter , Idleman Bruce , Tremblay Marissa
Published: March 2024

There is now a growing body of literature that reports over-dispersed (U-Th)/He ages from apatites. To address this challenge, we have performed continuous ramped heating (CRH) experiments on apatites from various geologic settings to characterize grain-specific helium (4He) diffusion behavior. Several first-order results emerge from our CRH analyses. (1) It became clear that simple volume diffusion, even accounting for radiation damage, cannot completely describe the diffusion of 4He in apatite. Two major types of 4He degassing behavior were broadly observed. Apatites with good (U-Th)/He age reproducibility show simple and unimodal incremental degassing curves that are similar to those predicted by volume diffusion, whereas samples exhibiting greater age dispersion, often accompanied by anomalously old ages, have complex gas-release curves that feature secondary gas-release peaks deferred to higher temperatures. (2) In practice, CRH can serve as a screening tool to reduce the dispersion of apatite (U-Th)/He ages, especially for those obtained from samples that have experienced slow-cooling. (3) Even among apatites in which 4He does show broad volume diffusion behavior (i.e., size and radiation-damage modulated volume diffusion), CRH analysis reveals kinetic variability of 4He diffusion. (4) Diffusion sinks, which are capable of trapping radiogenic 4He during both geologic processes and laboratory heating, can explain the observed high-temperature gas release during CRH analyses. CRH results of a sample suite from an active helium partial retention zone demonstrate that the release of sink-trapped 4He is temperature dependent rather than being controlled by a threshold mechanism. The results from our CRH analyses carry two critical implications. First, CRH is suitable for routine implementation that enables thermochronology practitioners to focus their measurement and interpretation on apatites in which 4He diffusion obeys volume diffusion. Second, diffusion sinks provide opportunities to extract additional thermal-history information providing a description of grain-specific trapping dynamics. Work in this area is ongoing via 4He/3He diffusion experiments, through which degassing of proton-irradiated 3He in a sample provides information trapping dynamics and degassing of radiogenic 4He constrains the sample’s thermal history.
High-resolution geochemical and petrographic study of a last glacial Cook Islands flowstone and the hydrological significance of calcite optical properties
Authors: Borsato Andrea , Frisia Silvia , Sinclair Daniel , Hellstrom John , Drysdale Russell , Faraji Mohammadali
Published: March 2024

The South Pacific Convergence Zone (SPCZ), the largest component of tropical circulation on our planet, extends diagonally across the South Pacific and its displacement controls rainfall variability and tropical cyclone activity. Speleothems that formed during the last glacial period in the Cook Islands offer the opportunity to investigate the strength and position of the SPCZ across both the last glacial termination, and during rapid climate fluctuations (e.g. the Dansgaard-Oeschger Events). We present a high-resolution, multiproxy study of an 80 cm-thick flowstone retrieved in Atiu (Southern Cook Islands) covering the period from 10 to 80 ka. Optical and fluorescence microscopy, synchrotron X-ray fluorescence mapping, stable isotope ratios and LA-ICP-MS trace elements analyses allowed us to characterise the geochemical and optical properties of different calcite fabrics and speleothem facies. The geochemical and textural properties of the flowstone are directly controlled by prior calcite precipitation (PCP), which caused large positive shifts in δ13C and δ18O values, and synchronous peaks in Mg concentration and other hydroclimate-sensitive elements. These rapid shifts are particularly marked between 35 and 45 ka and coincide with several Dansgaard-Oeschger events recorded by the Greenland Ice Cores. The positive shifts in δ13C and δ18O values and Mg concentration are commonly recorded within compact, translucent fabric characterized by low greyscale values. By contrast, shifts to more negative δ13C and δ18O values and low Mg concentrations are associated with a porous, open fabric with a high density of fluid inclusions and high greyscale values. This confirms previous findings from modern Atiuan stalagmites and cave-farmed calcite (Faraji et al., 2022, 2023), thus opening the possibility to utilise greyscale mapping and fabric logs as novel, high-resolution hydroclimate proxies.References:  Faraji, M., Borsato, A., Frisia, S., Hartland A., Hellstrom, J. (2023). High-resolution and quantitative records of infiltration in the Southern Cook Islands based on multi-element stalagmite data. Quaternary Research, 1-21. https://doi.org/10.1017/qua.2023.51. Faraji, M., Borsato, A., Frisia, S., Mattey, D.P., Drysdale R.N., Verdon-Kidd, D.C., Malcolm, R., Marca, A. (2022). Controls on rainfall variability in the tropical South Pacific for the last 350 years reconstructed from oxygen isotopes in stalagmites from Cook Islands. Quaternary Science Reviews, 289, 107633.
Geology, petrography and emplacement conditions of the Esenköy Pluton (NW Anatolia)
Authors: Bayram Gökçenur , Tükel Esra , Güraslan Işıl Nur , Ünal Alp , Altunkaynak Şafak
Published: March 2024

One of the least studied plutons in NW Anatolia, the Esenköy pluton intruded into the Palaeozoic Armutlu metamorphics. Along its southwestern boundary with the Esenköy pluton, basement rocks are found as "roof pendants". Both the Esenköy pluton and the Armutlu metamorphics are cut by aplite and diorite porphyry dykes. The pluton is mainly granodioritic in composition and is made up of 45-50% plagioclase, 25-30% quartz, 12-15% alkali feldspar, 6-9% hornblende, and 3-5% biotite. It exhibits predominantly holocrystalline porphyritic texture, and graphic-granophyric textures are also widespread throughout the main plutonic body. Diorite porphyry dykes display micro-granular porphyritic texture, while aplite dykes commonly show micro-granular texture.Chemical analyses of plagioclase and amphibole minerals in granodiorite samples reveal that plagioclases are predominantly andesine (An35-50) in composition. Zoned plagioclases generally show normal zoning with a decrease in calcium ratios from the core to the rims of the crystals. Amphiboles are all calcic in composition and are represented by magnesio-hornblende. Geothermobarometric calculations, using the chemistry of amphiboles and plagioclases from the same samples, yield pressure values ranging from 1.12 to 1.41 kbar and temperature values ranging from 741 to 787 °C. These temperature and pressure conditions suggest that the Esenköy pluton is emplaced at depths of 3.37-4.23 km within the crust. Contact relationships, textural properties and geothermobarometric calculations collectively indicate that the Esenköy pluton is an epizonal pluton that was emplaced into shallow levels of NW Anatolian crust.
Temporal deceleration of fluvial incision since the Middle Pleistocene along the Salween-Nu River in southeast Tibet
Authors: Zhang Jinyu , Wang Wei , Yang Huili , Zeng Xianyang , Guo Zhaowu
Published: March 2024

Fluvial terraces record intermittent river aggradation and down cutting regulated by the competition between stream power and sediment supply. Therefore, reconstructing the magnitude and rate of fluvial incision can provide insights into the interaction of tectonics, surface processes and climate change in shaping the landscape. The southeast Tibetan plateau is characterized by gently-dipping topography and deeply incised valleys with inset levels of fluvial terraces along the Salween, Mekong, and Yangtze Rivers. In this study, we focused on fluvial terraces well preserved at the two steeper segments of the Salween-Nu River (Bingzhongluo and Exi) to reconstruct the aggradation and incision history by integrating field investigation, unscrewed aerial vehicle (UAV) photogrammetric survey, and K-feldspar post-infrared infrared stimulated luminescence (pIRIR) dating. For the downstream Bingzhongluo reach with higher steepness, three levels of strath terraces at 20-160 m above the trunk river are overlain by three episodes of fluvial deposits at 370 ka, 275 ka, and 130 ka, and this yield the incision rates decreasing from 0.4 to 0.2 mm/yr with time. For the upstream Exi reach with lower steepness, five levels of strath terraces occurs at 10-350 m high, and the middle three terrace deposits are dated at 430 ka, 380 ka, and 300 ka. The corresponding incision decelerated from 0.6 mm/yr to 0.1 mm/yr. To summarize, fluvial terraces along two steeper reaches of the Salween-Nu River reveal temporal deceleration of river incision since the Middle Pleistocene varying at 0.6-0.1 mm/yr. Field investigation for terrace deposits revealed that there occur thick alluvial deposits overlying fluvial deposits by the Salween-Nu River, either tributary-derived boulder conglomerates or hillslope-derived angular conglomerates. We tend to believe that the large amounts of sediment supply may protect the underlying bedrock strath from erosion for a certain interval of time, and therefore slow the pace of river incision and regional landscape evolution in southeast Tibet.
Soil structure determined from interrelationships in hydraulic, thermal and electrical properties
Authors: Heitman Josh , Fu Yongwei , Horton Robert
Published: March 2024

The presentation will focus on the interrelationships of soil hydraulic, thermal and electrical transport properties. We will highlight how some more easily measured transport properties can be used as surrogates for others, which cannot be readily measured. We will specifically illustrate how the thermo-TDR sensing platform can be used to collect detailed in situ thermal and electrical property measurements at millimeter to profile scale. We will utilize the interrelationships between hydraulic, thermal and electrical properties together with thermo-TDR measurements in order to demonstrate how soil density and structure can be determined in situ. We will also highlight opportunities for extending such approaches to other sensing platforms at other scales.
Utilising a system dynamics framework to investigate socio-environmental impacts of hydropower in the upper Brahmaputra basin 
Authors: Thakur Isha Smiti , Hegarty Susan , O'Keeffe Jimmy
Published: March 2024

Emerging economies are increasingly constructing large hydropower projects to meet growing energy demand. The Yarlung Tsangpo-Brahmaputra transboundary basin shared by China, India, and Bangladesh holds enormous untapped hydropower potential, attracting ambitious hydropower development plans in the region. The transboundary basin is a highly biodiverse region sensitive to environmental and anthropogenic stressors. Hydropower projects are advertised as powerful development infrastructure that can provide greater access to clean water and clean energy. However, these projects also present grave environmental challenges including the degradation of ecosystems and their services, biodiversity loss and increased risk of natural hazards like earthquakes, landslides and floods. Further, dams have social and economic effects like population displacement and loss of livelihoods. Such effects are gendered: women are often disproportionately impacted. Stakeholder engagement with indigenous and other local communities is often absent or negligible in planning these hydropower projects. The projects usually export the electricity produced to far-away urban centres, leaving basin populations energy-poor, further aggravating existing inequities in resource access.This paper presents a systems model examining the interactions between the socio-economic, ecological, hydrological, and institutional structures operating in the river basin to investigate the socio-environmental impacts of hydropower development in the region. The systems model has been conceptualised using stakeholder inputs gathered through fieldwork in the upper Brahmaputra basin. The model will especially examine interlinkages between hydropower development-induced systemic changes and socio-ecological well-being. 
Comprehensive Analysis of Atmospheric Microplastic Deposition: Insights from North Wales, UK, and Global Collaborations.
Authors: Florent Perrine J. , Collins Benjamin I. , Graf Martine , Reay Michaela K. , Chadwick Dave R. , Jones Davey L.
Published: March 2024

Microplastic contamination poses a significant environmental threat with far-reaching consequences for ecosystems and human well-being. This study addresses this concern by conducting an extensive analysis of atmospheric microplastic (MP) deposition, with a focus on fostering international collaboration across countries. While significant research has focused on microplastics in aquatic environments, their presence in the atmosphere remains relatively unexplored. This research seeks to fill this gap by evaluating atmospheric MPs, providing crucial insights into their distribution and transport mechanisms. The main objective of this study is twofold: first, to assess the characteristics and prevalence of atmospheric MPs in North Wales, UK; and second, to establish collaborative partnerships with countries such as China, Vietnam, Egypt, Sri Lanka and Brazil. Simultaneously, the research identifies MPs in the soil, facilitating a comprehensive comparison between these two environments. This comparative analysis not only contributes to our understanding of potential atmospheric MP deposition onto the soil but also emphasises the importance of collaborative efforts in addressing this global issue. The sampling approach involves collecting both rainfall and soil samples over a year. Fluorescence microscopy is employed to assess the quantity, shape, and size of MPs, while Laser Direct Infrared Imaging (LDIR) is utilised to identify their polymer composition. Preliminary findings reveal a significant prevalence of small MPs (20-40 microns), with abundance diminishing as MP size increases. Temporal variations in MPs align primarily with rainfall patterns, with wind emerging as a crucial factor during periods of low-intensity precipitation. Additionally, the presence of MPs in the soil is expected to be influenced by vegetation coverage, with deposition anticipated to rise with increased precipitation. This comprehensive examination not only enhances our understanding of the environmental fate of MPs but also underscores the need for collaborative approaches to address atmospheric MP pollution globally. By establishing partnerships, the research aims to create a framework for shared knowledge and resources, enabling the comparison of atmospheric MP deposition across different climate zones. This international collaboration not only expands the study's scope but also fosters a collective understanding of the impact of atmospheric MPs on diverse environments. 
Why all emergent constraints are wrong but some are useful - a machine learning perspective
Authors: Nowack Peer , Watson-Parris Duncan
Published: March 2024

Global climate change projections, such as those from the Coupled Model Intercomparison Project phase 6 (CMIP6), are still subject to substantial modelling uncertainties. A variety of Emergent Constraints (ECs) have been suggested to address these uncertainties, but remain heavily debated in the scientific community. Still, the central idea behind ECs to relate future projections to already observable quantities has no real substitute.Here we discuss machine learning (ML) approaches for new types of controlling factor analyses (CFA) as a promising alternative. The principal idea is to use ML to find climate-invariant relationships in historical data, which also hold approximately under strong climate change scenarios. On the basis of existing big data archives such as those from the CMIPs, these climate-invariant relationships can be validated in perfect-climate-model frameworks.From a ML perspective, we argue that CFA are promising for three reasons: (a) they can be objectively validated both for present-day data and future data and (b) they provide more direct - by design physically-plausible - links between historical observations and potential future climates compared to ECs and (c) they can take higher dimensional relationships into account that better characterize the still complex nature of large-scale emerging relationships. We highlight these advantages for three examples in the form of constraints on climate feedback mechanisms (clouds [1], stratospheric water vapour [2]) and forcings (aerosol-cloud interactions).References:1. Ceppi P. and Nowack P. Observational evidence that cloud feedback amplifies global warming, Proceedings of the National Academy of Sciences 118 (30), e2026290118 (2021). https://doi.org/10.1073/pnas.20262901182. Nowack P., Ceppi P., Davis S.M., Chiodo G., Ball W., Diallo M.A., Hassler B., Jia Y., Keeble J., and Joshi M. Response of stratospheric water vapour to warming constrained by satellite observations, Nature Geoscience 16, 577-583 (2023). https://doi.org/10.1038/s41561-023-01183-
The effect of commercial export farms on drought risk and adaptation of agropastoral communities in the drylands of Kenya
Authors: Streefkerk Ileen , Aerts Jeroen , de Bruijn Jens , Hassaballah Khalid , Odongo Rhoda , Schrieks Teun , Wasonga Oliver , Van Loon Anne
Published: March 2024

Drought poses a thread in the already existing water challenges in dryland regions. Drought hazard and risk are, however, not merely a natural phenomenon. Instead they are shaped and influenced by human behaviour and interventions. This raises questions about how to distribute the limited available water in an equitable manner, especially in drought prone areas such as drylands where water is key to people’s livelihood and fragile ecosystems.In the Horn of Africa Drylands (HAD) conflict over water and vegetation is prominent. On top of that, large-scale land acquisitions (LSLAs) are increasing the competition of water, putting local communities at increased risk. A key impact of increasing LSLA's is the decrease in water and land availability for vulnerable agropastoral communities. For such communities, drought adaptation is key to reduce drought risk, especially under climate change. Despite these recent studies, there is still a lack of research that includes the influence of upstream-downstream dynamics on drought risk and adaptation behaviour with a focus on the impacts of agropastoralists.This study, therefore, further develops an agent-based model (ADOPT-AP) to investigate how upstream large scale commercial farms influence downstream drought risk and adaptation of agropastoralists. We apply and test the ADOPT-AP model for the Ewaso N’giro north catchment in Kenya. Main novelties of our method are the ability to capture heterogeneous and dynamic drought-human interactions (including different water users) in a spatially-explicit manner. After the model has been calibrated and validated, we test how commercial exporting farms affect drought risk and impact of downstream communities by simulating different scenarios. We show for various drought periods how both drought characteristics (soil moisture, discharge and groundwater levels) and impacts (milk production, crop production, distance to water) differ among the scenarios.
Impact of river engineering drivers on denudation processes in a small catchment
Authors: Piasecka-Rodak Joanna , Święchowicz Jolanta , Najwer Alicja , Zwoliński Zbigniew
Published: March 2024

Human influence in the form of hydraulic engineering causes disruption to unconfined channel transport in catchments. Hydrotechnical construction includes, among others: weirs, dams, retention reservoirs, river bank supports, bridges, etc. Each of these structures causes disruptions in the flow of trailed and suspended sediments originating from denudation in the river catchment. It is widely known that the dynamic balance of the river bed is disturbed by sediment accumulation upstream of the reservoir's dam, limited sediment outflow from the reservoir, and increased downcutting downstream of the dam. The aim of the study was to investigate the influence of reservoir and additional river regulation facilities on selected rivers in Poland on the structural and functional connectivity of the river channel in terms of sediment transfer from slope denudation in the catchment areas. The study examined a high-resolution digital elevation model together with survey data on sediment accumulation sites along the river. It was shown that a more detailed and realistic connectivity pattern for hillslopes and river channels can be obtained by applying several tools and parameters simultaneously (i.e. field surveys, modelling, etc.).The study uses the concept of connectivity. A spatial examination of catchment linkages enables a determination of the degree to which a catchment participates in the transfer of sediment in suspended form and the pathways used to facilitate this. A detailed analysis of such pathways is needed to plan appropriate river engineering work and efforts designed to reduce sedimentation in reservoir and downstream erosion as well as efforts to remove dams in situations where this is deemed to be the most appropriate solution.We observed in the study area, the highest values of the IC were noted for valleys of streams where suspended sediment transfer occurs through multiple pathways found in the vicinity of streams. Conversely, the lowest index values were noted for mouth section areas found near the studied reservoir, where sediment deposition occurs in the form of alluvial fans. In foothill areas sediment transported in stream channels usually comes from lateral bank erosion as well as stream bed erosion in the Wapienica. In foreland basins part of the catchment, the influx of sediment occurs at select sites, mostly via drainage ditches. The presence of levees along rivers and concrete lining of channels effectively prevents sediment influx from area hillslopes. On the other hand, the use of rubble in the channel bed impedes channel floor erosion and channel bank erosion. The largest number of sites where suspended material is supplied to fluvial transport pathways are found in middle mountain areas, followed by foothill areas, and finally foreland basins.
Importance of ocean observations to the ECCC global ocean analysis system, GIOPS
Authors: Peterson K Andrew , Smith Gregory C , Surcel-Colan Dorina , Chikhar Kamel , Zheng Brayden
Published: March 2024

The Synergistic Observing Network for Ocean Prediction (SynObs) project (https://oceanpredict.org/synobs) seeks to find synergies between ocean observations and ocean prediction through a multi-system approach to an Observing System Experiment (OSE). Best estimates and predictions for locations of eddies, shape of ocean sound speed profiles, ocean currents, sea surface temperature and ocean water masses are important ocean diagnostics for a variety of ocean and/or coupled NWP applications. Skillful estimates of these diagnostics is presumably determined by the quantity and quality of ocean observations used in the ocean state estimation, but the exact value of the observations, and in particular, which observations are most crucial is unknown. In the context of the SynObs project, Environment and Climate Change Canada's (ECCC's) system the Global Ice Ocean Prediction System (GIOPS) has performed several observation withholding experiments.  The importance of each withholding experiment will be studied by looking first at our standard innovation metrics of observation minus model misfits in the context of both assimilated observations and withheld profile observations.    Further analysis against novel observation metrics, such as an eddy tracking diagnostic comparison, drifting buoy current velocity measurements and sound profile (from T/S profile) comparisons will be detailed.  Finally, preliminary results from a set of short lead (10d) coupled forecast runs may also be presented.  
Englacial shearing in the context of old ice preservation
Authors: Manos John-Morgan , Gräff Dominik , Lipovsky Brad
Published: March 2024

Old ice (>1 million years) has been discovered in blue ice areas in the Allan Hills, Antarctica, and ice cores have been retrieved from shallow boreholes less than 200 m depth (Higgins et al., 2015 and Yan et al., 2019). However, it remains unclear what ice properties, mechanisms, and conditions allow for the preservation of old ice in blue ice areas. A high-resolution distributed temperature sensing (DTS) deployment was carried out in the COLDEX 22/23 and 23/24 field seasons. A temperature sensitive fiber optic cable was deployed into five air-filled boreholes, one for two consecutive seasons. Temperature was recorded every ~25 cm along the fiber length at a temperature resolution of 10 mK. Borehole temperature profiles reveal both the seasonal temperature signal shallow in the ice column and recent climate temperature trends below the seasonal signal due to ground surface temperature diffusion. Discrete temperature anomalies, unrelated to ground surface temperature signals, were identified at multiple depths. The temperature anomalies appear to coincide with points of ice crystal c-axis transitions in the ice fabric, suggesting possible shear horizons at transitions between ice layers at these depths. 23/24 field season efforts aim to confirm the presence of transient shear heating events and elucidate the horizontal distribution of shear heating events as they relate to the presence of old ice.
Predicting soil erosion under climate change: Using climate data to forecast future climate change scenarios and RUSLE2 modeling to estimate soil erosion on agricultural lands in the United States
Authors: Ghorbani Mahsa , El Kadiri Racha , Momm Henrique , Yoder Daniel , Dalmo Vieira , Bingner Ronald , Wells Robert , Ferruzzi Giulio , Darnault Christophe
Published: March 2024

Soil erosion is one of the major processes of land degradation. Climate change, marked by alterations in the precipitation spatial and temporal patterns as well as rainfall amounts projected to increase, is expected to exacerbate soil erosion and loss of soil in the agricultural landscape. Understanding soil loss using physically-based water erosion prediction models and improving knowledge of soil erosion of agricultural lands under future climate change scenarios is critical to developing best management practices for the conservation of soil resources as well as to inform decision and policy makers. This study aims at investigating the impacts of future climate changes on soil erosion in the United States. By integrating up-to-date climate datasets this study characterized differences and current trends in precipitation with respect to climate change and applied a climate model ensemble based on the CMIP6 climate scenarios to predict the future climate. These data are downscaled with machine learning algorithms. It also estimates soil erosion in different soil-climate-agricultural management systems from predicted precipitation under future climate change scenarios using the Revised Universal Soil Loss Equation, Version 2 (RUSLE2). Research findings on the impacts of future climate change scenarios on soil erosion in agricultural landscapes will allow the development of climate-driven best management practices and conservation agriculture techniques as well as inform decision and policy makers to reduce soil loss, therefore protecting the limited soil and water resources, and contributing to a sustainable agricultural production and food security.
Spatio-temporal probability prediction of rainfall-induced landslides based on deep learning under climate change
Authors: Zhao Yu , Chen Lixia
Published: March 2024

In recent years, with the frequent occurrence of extreme climate, rainfall-induced landslide (RIL) has become one of the main geological hazards that endanger human life and property safety. Understanding the relationship between meteorological factors and RIL is essential for promoting safety. Although the research community has been studying the spatial or temporal probability relationship between climate variability and RIL using quantitative and qualitative methods at different spatial or temporal scales for decades, the spatio-temporal probability of synchronous hazard prediction has rarely been studied. Here, we constructed a hybrid model of Convolutional Neural Network (CNN) and Long-Short Term Memory (LSTM) and utilized the spatial feature extraction capability of the CNN model and the temporal feature extraction capability of the LSTM model to infer the causal relationship of RIL and simulate the risk of RIL from the meteorological data from 1980 to 2015. In this study, the Wanzhou District of Chongqing, China was used as the research area to train and test the model, in order to provide a new idea to synchronously predict the spatial probability and temporal probability of RIL. Our results reveal that the spatio-temporal probability prediction model has higher prediction accuracy than the single spatial probability or temporal probability prediction model, and it is more consistent with the actual occurrence of RIL. The predicted results of our model show that the occurrence of RIL is mainly affected by the geological environment, followed by the intensity and duration of rainfall in extreme climates. The inferred patterns show that precipitation extremes are associated with an increased risk of RIL. Therefore, in addition to understanding the geological factors that trigger the hazards themselves, a better understanding of climate-hazard linkages enhances the spatio-temporal modeling capacity for the risk of RIL. In the future, it can be used to analyze the world's risks of RIL caused by climate change.
An assessment of prediction and predictability through the state-of-the-art global ensemble forecast systems
Authors: Zhu Yuejian
Published: March 2024

Ensemble forecasts play a pivotal role in weather prediction, providing valuable insights into the inherent uncertainty of atmospheric processes. Strategies in ensemble construction involve generating multiple simulations by perturbing initial conditions, model parameters, or both. This diverse set of forecasts allows meteorologists to capture a range of possible future scenarios, acknowledging the inherent complexity of the atmosphere. Model resolution is a critical factor, influencing the representation of small-scale features and improving the overall accuracy of ensemble predictions. Additionally, forecast range-related issues address the challenge of extending predictions beyond a few days, where uncertainties tend to grow. Combining advanced statistical techniques with cutting-edge modeling technologies helps refine ensemble forecasts, enhancing our ability to anticipate and mitigate the impacts of weather-related events on society and the environment.The investigation based operational global ensemble forecast system from NCEP, CMC, ECMWF and CMA to focus on the analyses of ensemble design that combined to the data assimilation for initial condition perturbation and various stochastic physical perturbations. The impact of model resolutions (both horizontal and vertical) will be addressed to the different atmospheric characteristics, such as forecast uncertainty, reliability and resolution. The forecast capability and predictability to the extreme events will be discussed from single model ensemble and multi-model ensemble. Finally, the 1st-moment and 2nd-moment ensemble forecast calibration will be demonstrated from traditional statistical method and machine learning based ensemble reforecasts
Reconstructing vertical velocities and heat fluxes in the Southern Ocean from SWOT SSH fields
Authors: Carli Elisa , Siegelman Lia , Morrow Rosemary , Legresy Benoit , Vergara Oscar
Published: March 2024

Accessing vertical velocities and heat fluxes globally represents today a major gap in our understanding of the 3D ocean dynamics. SWOT is showing a great advance, namely a sea level resolution up to ten times better than traditional nadir-looking altimeters, allowing for the observation of fine-scale ocean dynamics. Mesoscale dynamics account for 80% of the total kinetic energy in the ocean and smaller mesoscales and sub-mesoscales contribute 50% of the total vertical velocity variance in the upper ocean. In this work, we explore the potential of using SWOT 2D surface topography data to reconstruct vertical velocities and vertical heat fluxes below the Southern Ocean mixed layer using surface Quasi-Geostrophic (sQG) theory for the vertical projection. The upper ocean 3D circulation is calculated from SWOT’s science phase 2D sea surface height (SSH) observations and validated with multi-sourced in-situ data (high-resolution XBT and CTD sections from the SURVOSTRAL and ACC-SMST SWOT CalVal campaigns in the Southern Ocean south of Tasmania). The performance of the SQG methodology, in terms of spatial and temporal correlation, is first assessed using the COAS coupled ocean-atmosphere simulation,  and we find that the SQG reproduces both the spatial distribution and the overall regional variability of the mesoscale structures below the Southern Ocean mixed layer. We then apply the SQG methodology to a high-resolution SSH regional mapping of 3 to 5 days of SWOT science phase data to obtain reconstructed vertical velocities and vertical heat fluxes. The results are validated over the in-situ XBT and CTD data collected in the same time period. The observable structures, resolved dynamics and errors involved in this fine-scale reconstruction are discussed.
Identification of forced response and internal climate variability using ensemble linear dynamical modes
Authors: Gavrilov Andrey , Kravtsov Sergey , Buyanova Maria
Published: March 2024

The problem of accurate detection of climate response to slow external forcing in 19-21 centuries is complicated by the presence of internal climate variability, which can also exhibit slow (decadal and multidecadal) large-scale dynamics, and also by the fact that there is only one observed climate realization available. At the same time, state-of-the-art Earth system models (ESMs) exhibit different spatiotemporal content on slow time scales, and their ability to estimate forced and internal climate variability needs further verification, especially given a relatively poor (short) observational statistics with respect to slow time scales.Here we present a method called ensemble linear dynamical mode (E-LDM) decomposition [1] which addresses the problem of forced signal and internal variability detection from small ensembles of ESM simulations. The method is based on the general assumption that the forced response is the same in all ensemble members and the internal variability is uncorrelated, while both of them can be essentially represented by a low-dimensional set of spatial patterns and corresponding forced and internal time series with certain time scales; the patterns, the time series and their time scales are optimized via the Bayesian framework. We compare the E-LDM method with other state-of-the-art methods of forced signal detection on synthetic and ESM-simulated data, and also discuss its applicability to the problem of intercomparison of ESMs and their verification with respect to real data. This research was supported by the state assignment of the Institute of Applied Physics of the Russian Academy of Sciences (Project No. FFUF-2022-0008). 1. Gavrilov, A., Kravtsov, S., Buyanova, M., Mukhin, D., Loskutov, E., & Feigin, A. (2023). Forced response and internal variability in ensembles of climate simulations: identification and analysis using linear dynamical mode decomposition. Climate Dynamics, 1–28. https://doi.org/10.1007/S00382-023-06995-1.