bluuebunny/crossref_metadata_2025 huggingface dataset:
Implementing Gaussian Probability Density Function cloud fraction scheme in WRF much reduces the wet bias over the Tibetan Plateau in high-resolution simulations
Authors: Liu Jiarui , Yang Kun , Zhao Dingchi , Wang Jiamin , Zhou Xu , Lin Yanluan
Published: March 2024

A noticeable wet bias persists over the Tibetan Plateau (TP) during summer in both global and regional climate models, despite numerous advancements and ongoing efforts to lower it. This study investigates the performance of the Gaussian Probability Density Function (GPDF) cloud fraction scheme in the Weather Research and Forecasting (WRF) model over the TP during July and August 2018. The evaluation reveals that the GPDF scheme mitigates the wet bias over the TP in simulations at two resolutions (0.1° and 0.05°), with a significant reduction in the bias. This scheme also reduces the overestimation of downward surface shortwave radiation, indicating an improvement in cloud simulations. We propose that the GPDF scheme alleviates the wet bias through both local moisture process and dynamic process. Specifically, an increase in cloud water/ice content leads to a reduction in surface net radiation and subsequent decrease in surface sensible heat flux and evapotranspiration. This diminished surface heating lessens the thermal effect of the TP, causing a weakened monsoon circulation and decreased moisture flux convergence over the TP. Both the decreases in local evapotranspiration and remote moisture flux convergence contribute to the alleviation of the wet bias, and the latter plays a dominant role, contributing to approximately 70% of the precipitation decrease.
Global Ionospheric Total Electron Contents Modeling with Air-borne Observables and GAN Frameworks
Authors: Liu Yang , Yang Kunlin
Published: March 2024

The ionosphere services as an important medium for radio wave propagation, and the refraction phenomenon occurs for trans-ionosphere signals, resulting in propagation delay.  When the distribution of electron density in the ionosphere is uneven, amplitude attenuation and phase jitter will occur in trans-ionospheric signals, which are particularly prominent for global satellite navigation signals.  This coupling mechanism makes it possible to use radio waves for ionosphere remote sensing.
Currently, international GNSS services use nearly 500 observation stations globally to derive the spatial and temporal feature of global ionospheric total electron content. The resulting product, global ionospheric map has become the major data source for ionosphere study. Moreover, the University Corporation for Atmospheric Research in America took the lead in the use of Low Earth Orbit occultation observations to measure the vertical profile of ionospheric electron density and scintillation effects in the ionosphere.
Although existing ionosphere remote sensing techniques have been developed, the fundamental problem is still difficult to solve. For ground-based sensing, there are blind zones that ground stations cannot reach. For instance, it is difficult to deploy ground receivers in deserts and oceans. For space-borne techniques, such as radio occultation, it is mainly applied in middle to low latitude areas, and the observations cannot be continuously in both spatial and temporal domains.  
To address the problem, it is helpful to get more sources of ionospheric observations. It is clear that with dual frequency measurements, the accurate ionospheric total electron content can be solved at the pierce point. Therefore, with comprehensive satellite signals, the development of multiple constellations in satellite navigation can make benefits for accurate ionosphere sensing and modeling.
In this work, we focus on the application and contribution of air-borne observations in ionosphere sensing and modeling. Supposing the air-borne dual-frequency GNSS receivers can derive accurate total electron content, more ionospheric pierce points are obtained with global air flights. The feasibility of air-borne ionospheric sensing and modeling are further investigated. We apply Generative Adversarial Networks to reconstruct the regional ionospheric TEC map with plentiful air-borne ionospheric observables from airlines equipping dual frequency GNSS receivers. The proposed ionospheric TEC maps are verified by comparison with the IGS global ionospheric map. Several GAN-based deep learning networks are applied, such as DCGAN and SNP-GAN.
This study is benefit for exploring the feasibility of air-borne ionospheric sensing and modeling, as supplement for ground and space-borne ionospheric sensing systems. 
Evaluations of Temperature Lapse Rate in and Around the East-West Himalayan Chain: An Implication for Climate Understanding and Modeling
Authors: Kattel Dambaru Ballab , Yao Tandong , Ullah Kalim
Published: March 2024

This study evaluated the monthly characteristics of TLRs based on the results derived from 18 observation stations in Bhutan (1996–2009), 56 stations in Nepal (1985–2004), and 53 observation stations in Pakistan (1971–2000). The study covers an elevation range of 5–3920 m above sea level, with various topography, climatic regimes, and geographical coordinates. Various empirical analysis techniques, including thermodynamics and hydrostatic systems, have been used to obtain the results. The annual cycle of TLR, such as a bi-modal pattern (two minima in the winter and summer and two maxima in the pre- and post-monsoon seasons), is a typical pattern throughout the study area. However, the forcing strengths, mechanisms, and processes for the monthly variations in TLR magnitude and diurnal range differed. Monsoon, orographic controls, and mountain barrier effects on TLR are more robust in summer, especially during the day, while the influences of inversions and mountainous microclimates are higher during the non-monsoon period, particularly in the winter and at night. A shallower TLR occurs in summer throughout the study area because of the intense heat exchange process within the boundary layer, corresponding to warm and moist monsoonal atmospheric conditions. Steeper values of TLR in the non-monsoon period, especially in the pre- and post-monsoon seasons, result from strong dry convective cooling at higher elevations owing to high thermal forcing effects at lower elevations. The winter shallower TLR is associated with westerly-driven cold air flow towards the lower elevations and radiative cooling, especially at night, excluding Bhutan. There are systematic differences in TLRs monthly and diurnal variations in magnitudes, such as the lowest gradient value in Pakistan observed in August and the highest in May, one month later than observed in Nepal and Bhutan, due to the late arrival of monsoon moisture in summer and intense thermal forcing effects following the wet early pre-monsoon months. In addition to the variation in magnitudes, the variation in the diurnal range from one place to another is also due to distinct differences in topoclimate, in addition to the effects of the synoptic regime, moisture amounts, elevations, geographical coordinates, variations in net radiation, surface roughness, vegetation coverage, and distance from the sea coast. The results of this study are useful for determining the local or regional climatic behavior or interactions, climate reconstruction, and temperature field in various glacial-hydro-climatic, ecological, and agricultural modeling.
Benthic foraminiferal morphogroups track the recovery of the deep-marine ecosystem after the K/Pg boundary
Authors: Kaminski Michael , Hikmahtiar Syouma , Cetean Claudia
Published: March 2024

Morphogroup analysis of benthic foraminifera is a useful tool that reflects the nature of the trophic continuum, and in particular the flux of organic matter to the sea floor and its source. In broad terms, agglutinated benthic foraminifera can be placed in four morphotypes based on their test morphology and feeding preference. Morphotype M1 constitutes tubular suspension feeders that trap food particles carried in suspension. Morphotypes M2 and M3 are the coiled multichambered forms, which are epifaunal detritivores, and M4 is the group of elongated and rectilinear infaunal deposit feeders. Their relative proportions tell us something about flux of particulate organic carbon (POM) to the sea floor and its mode of delivery, which is ultimately a function of water depth, currents, and the amount of surface-water phytoplankton production.To assess the trophic structure of the benthic foraminiferal community across the Cretaceous/Paleogene boundary in the western Tethys, we examined >70 samples from the Scaglia Rossa Formation in Gubbio, Italy. Samples were mostly collected at 10 cm spacing. We also recalibrated the age model for the Scaglia Rossa Formation in Gubbio using the 2020 geologic time scale. In the top two meters of the Maastrichtian, a gradual increase in the proportion of M4 is observed (to ca. 20%) leading up to the K/Pg boundary. These values fall abruptly to 7% in the beds immediately above the boundary clay, with more variable values in the lower Paleocene. This pattern can be interpreted as reflecting a modest but short-lived reduction in the total sea-floor organic flux following the boundary event (but not a “Strangelove Ocean”). Morphotype M1 shows a major reduction above the boundary, and there is a concurrent increase in the M2 morphotype. This implies a reduction in the amount of POM arriving at the sea floor from suspension. The increase in M2 suggests that there was greater influence of organic matter from bacterial sources in the early Paleocene.The recovery of the deep-marine ecosystem was prolonged, with M1 returning to Maastrichtian values approximately 3.4 m above the K/Pg boundary clay. Using our new age model, this is equivalent to 1.8 m.y. after the event. Our findings of a prolonged recovery are in line with the conclusions of nannofossil workers, who estimated that it took approximately 2 m.y. for the marine food web to fully reestablish itself after the K/Pg boundary event.
A 1000-year extreme flooding record from NE Asia reveals the roles of climatic and anthropogenic changes in driving basin erosion and sedimentation
Authors: Sun Shuang , Dong Xianliang , Nie Yunfeng , Li Yang , Zhu Liya , Cao Xianyong , Ma Hongwei , Li Yan , Wang Hong , Hu Ke , Lu Yin
Published: March 2024

Short-term hydrological monitoring has limited our understanding of how climate and human activities affect flood erosion and deposition. Here, we reconstruct a 1000-year-long extreme flooding record by analyzing drill cores from the Daling River estuary (NE China), NE Asia, based on the observation that instrumental floods normally cause coarse particle enrichment in the estuary. Our data reveal that (1) centennial-scale climate aridification coupled with vegetation coverage reduction has enhanced flood erosion and estuarine sedimentation; (2) accelerated reservoir construction and reforestation and grass planting since 1960 have consistently reduced sediment flux and coarse particles reaching the estuary. Our findings promote our understanding of basinal erosion and estuarine sedimentation under climate aridification and human pressure.
Laboratory earthquake prediction via multimodal features
Authors: Gao Ke
Published: March 2024

With earthquake disasters inflicting immense devastation worldwide, advancing reliable prediction models utilizing diverse data paradigms offers new perspectives to unlock practicable prediction solutions. As reliable earthquake forecasting remains a grand challenge amidst complex fault dynamics, we employ combined finite-discrete element method (FDEM) simulations to generate abundant laboratory earthquake data. We propose a multimodal features fusion model that integrates temporal sensor data and wavelet-transformed visual kinetic energy to predict laboratory earthquakes. Comprehensive experiments under varied stress conditions confirm the superior prediction capability over single modal approaches by accurately capturing stick slip events and patterns. Furthermore, efficient adaptation to new experiments is achieved through fine-tuning of a lightweight adapter module, enabling generalization. We present a novel framework leveraging multimodal features and transfer learning for advancing physics-based, data-driven laboratory earthquake prediction. As increasing multi-source monitoring data becomes available, the established modeling strategies introduced here will facilitate the development of reliable real world earthquake analysis systems.
Nature-based solutions to capture atmospheric pollutants in urban ecosystems
Authors: Azpeitia García Angélica Montserrat , Eggermont Marjan Jose , Rivera Cárdenas Claudia Inés
Published: March 2024

Atmospheric pollution is a social problem reflected in cities due to pollutants contributing to various adverse effects on society.Over the last few years, experts have been arguing that cities may play a positive role in the resilience and adaptation strategies against atmospheric pollutants and climate change effects. Recently, Nature-based Solutions (NBS) started to be implemented, focusing on solving environmental problems in place of sole human intervention. The main purpose of this contribution is to apply NBS solutions in Mexico City and the City of Calgary, as well as to compare their effectiveness in both countries.Our contribution begins with previous research conducted about the most feasible NBS to be applied to those cities. The selected solution was the Ecosystem-based adaptation through pocket parks. Consequently, six pocket parks were visited in both cities and a database was created with descriptions of each park. In addition, a historical air quality database of those cities was created too, with the purpose of studying if NBS positively contributes to the decrease of atmospheric pollutant concentrations especially in the areas where pocket parks are placed.These databases were processed through data visualization software, which concluded that the area of the pocket parks, the quantity, and the species of trees in each park may have an important influence on pollutant reduction through the studied NBS.On the other hand, pocket parks have additional features that maintain their importance on the NBS since they have social benefits and contribute against the effects of climate change on cities. This study concludes by recognizing the importance of creating as many recreational spaces as possible that include features that address the needs of cities and citizens in building a better urban environment.
Comparing the interaction of differently shaped Microplastics with the Hyporheic zone
Authors: La Capra Marco , Frei Sven
Published: March 2024

Microplastics (MPs) are a major pollutant of the modern world, being dubbed “the lead of our generation”. Even though their potential danger to life on Earth is understood, their transport in water bodies remains an area with open questions, specifically their transport in rivers and streams. Such contaminants can be divided into three categories: spherical, irregular and fiber MPs. While research has been done on the fluvial transport of spherical MPs and their interaction with the hyporheic zone, the transport mechanisms that govern Microplastic Fibers (MPFs) are still unknown. State of the art models suggest a marked difference between the transport and settling of MPFs compared to spherical and irregular MPs, thus the need to confirm these models in a laboratory setting. The difference between the fluvial transport of spherical MPs, irregular MPs and MPFs is thereby researched here. Similarly sized fluorescent MPs and MPFs will be compared in an experimental flume, continuously logging the concentration in the water head and that in the hyporheic zone at the flume interface.
Generalizability evaluation of heterogeneous ensembles models for benthic macroinvertebrate index predictions
Authors: Park Taeseung , Shin Jihoon , Cha YoonKyung
Published: March 2024

Predictive models, which leverage the relationship between environmental variables and river health, serve as a valuable tool for predicting the river health at unmonitored sites. Such models should be generalizable to unseen data. However, predictions derived from machine learning (ML) models can exhibit large variability even with minor changes in the training dataset. The potentially unstable behaviors of a ML model decrease the model’s generalizability to unseen data, likely limiting its applicability as an assistant tool for decision making. Heterogeneous ensemble models are recognized to achieve greater generalizability compared to single models owing to their structural diversity. In this study, various machine learning (ML) models are employed to understand the relationship between environmental factors and benthic macroinvertebrate health. To obtain a model with better generalizability, the present study compares the generalizability of heterogeneous ensembles with those of homogeneous ensembles and single models by using the bias–variance decomposition. The models classified five grades (very good to very poor) of benthic macroinvertebrate index (BMI). The models incorporated diverse environmental factors, including water quality, hydrology, meteorological conditions, land cover, and stream properties, as input variables. The data were monitored at 2,915 sites in the four major river watersheds in South Korea during the 2016–2021 period. The results indicated better generalizability of the heterogeneous and homogeneous ensembles than single models. Moreover, heterogeneous ensembles tended to show higher generalizability than homogeneous ensembles, although the differences were marginal. Weighted soft voting was the most generalizable of the heterogeneous ensembles, with loss of 0.49. Weighted soft voting also delivered acceptable classification performance on the test set, with accuracy of 0.52. The identified contributions of the environmental factors to BMI predictions and the directions of their effects agreed with established knowledge, confirming the reliability of the predictions. These results demonstrate the usefulness of the heterogeneous ensemble models for increasing the generalizability of ML model predictions. Furthermore, despite the slightly lower generalizability than voting-based ensembles, homogeneous ensembles demonstrated comparable levels of generalizability to heterogeneous ensembles.
3D reflection seismic surveying and borehole DAS measurements to image the sedimentary structure in the Sudret area of Gotland, Sweden
Authors: Juhlin Christopher , Brodic Bojan , Erlström Mikael , Hedin Peter , Sopher Daniel , Wang Zhihui , Wilczynski Zbigniew
Published: March 2024

Reflection seismic data were acquired in the Sudret area of Gotland in the time window 6 to 13 November, 2023. Objectives of the survey were to obtain images of the subsurface down to the Precambrian basement in the vicinity of two coreholes that had been drilled earlier down to about 800 m. These images would provide a better understanding of the sedimentary strata and local structure near these holes. For these purposes a sparse 3D survey was acquired that covered a c. 300 m by 700 m rectangular area with high fold, including the locations where the boreholes were drilled. A longer c. 2.8 km 2D profile was also acquired adjacent to the 3D survey that ran roughly in the N-S direction. In addition, distributed acoustic sensing (DAS) measurements were performed in the two coreholes. We report here on some results from the 3D survey and from the DAS measurements.A Bobcat source with a 500 kg weight drop hammer with base plate was used as a source and 410 5Hz nodal units were available for recording. In total, 704 receiver locations were occupied with acquisition along 19 source lines, implying that 294 units had to be moved during the survey and that the source lines had to be shot twice. DAS data were recorded over the depth interval 17 m above sea level to 475 m below sea level in the Nore-1 corehole. In Nore-2 the depth interval was 17 m above sea level to 720 m below sea level. The fiber optic cable was sampled at 2.45 m intervals and data were recorded at a sampling frequency of 4000 Hz. Due to borehole irregularities it was not possible to get the fiber optic cables all the way to the bottom of the coreholes.Numerous semi-continuous reflection horizons are observed in the c. upper 500 ms after stacking. A particularly strong reflection at 350 ms likely originates from the top of the Ordovician. Cambrian sandstones are also reflective, as well as shallow sandstone layers in the upper 150 ms. Normal moveout (NMO) velocities are relatively constant at about 3500 m/s. However, depth conversion using this velocity places the reflectivity deeper than what is expected from the cores. The DAS data allow the vertically propagating P-wave velocity to be measured at 3100 m/s. Using this velocity for depth conversion provides more reasonable depths to the main horizons. Since the NMO velocities are largely controlled by the horizontal velocity of the rock the difference between these and the DAS velocity can be explained by the rocks in the area having significant anisotropy (about 10%).
Characterizing changing stream flow components and hydroclimate interactions in cities – implications for future management and restoration of urban ecosystems
Authors: Warter Maria Magdalena , Tetzlaff Dörthe , Marx Christian , Soulsby Chris
Published: March 2024

In urbanized areas the natural flow paradigm from river management is being increasingly challenged by hydroclimatic changes and marked anthropogenic influences on flow regulation. Although the impacts of urbanization, increased runoff and reduced baseflow are increasingly well quantified; the characteristics of flow regimes that are sustainable and wanted for urban streams to preserve or restore their hydrologic and ecological integrity in the face of future climate change and rapid urbanization, remain less well understood.To that end, we conducted a paired catchment study of two streams, both sub-catchments of the Spree catchment – a more natural intermittent rural agricultural stream in Brandenburg (Demnitzer Mill Creek) and an anthropogenically impacted urban stream in Berlin (Panke).  We characterized contrasts in inter- and intra-annual streamflow variability, storm period responses, water ages and mixing processes. Through tracer-based analyses, using stable water isotopes, we identified the physical processes (sources, flow paths and age) sustaining stream flow over multiple years (2018-2023), and broadly linking them to biological dynamics obtained through environmental DNA, in order to estimate resilience to future hydroclimate interactions and land use changes. The higher specific discharge of the urban stream emerges as a clear artefact of artificially increased baseflow due to discharge of wastewater, while reacting primarily to convective summer storms with strong runoff reactions and short discharge peaks. In contrast, the rural stream shows a characteristically intermittent behavior with longer periods without baseflow and only limited runoff reactions with only temporary superficial accumulation of water after heavy rainfall. Water ages reflected the respective runoff contributions and mixing processes, with a low contribution of young water observed in the urban stream and a higher, more variable contribution of young water in the rural stream. The strong dichotomy of runoff responses and unmistakable influence of baseflow manipulation on streamflow dynamics and biological processes point to major uncertainties in the suitability of different approaches for the restoration of urban and management of naturally intermittent rivers. Effective stakeholder engagement will be necessary in seeking to manage flow regimes to maintain ecohydrological connectivity and future resilience in the face of urban growth and climate change.
Satellite-based monitoring of irrigated cropland dynamics in data-sparse environments
Authors: Foster Timothy , Higginbottom Thomas , Adhikari Roshan , Redicker Sarah
Published: March 2024

Water scarcity is a major constraint to agricultural productivity, food security, and economic development, in particular in low- and middle-income countries in regions such as Sub-Saharan Africa (SSA). However, our ability to effectively design, target, and implement interventions to reduce agricultural water insecurity is limited by a lack of data on the locations, dynamics, and outcomes of irrigated croplands in these regions. In this talk, we demonstrate how satellite remote sensing can be combined with machine learning methods to develop continuous fine-resolution maps of irrigated cropland areas in data-sparse environments distributed across SSA. Our results demonstrate that past large-scale irrigation projects initiated by governments and donors in SSA have failed to deliver on promises of agricultural expansion and intensification. In contrast, our mapping shows a more rapid recent growth in small-scale informal irrigation in SSA, typically initiated by farmers themselves and outside of official irrigation infrastructure and monitoring systems. We contextualise the economic, political, and social drivers of these historic irrigated cropland dynamics in SSA, while also discussing some of the opportunities and challenges that exist for mainstreaming use of satellite-based monitoring in future water management and policy in SSA.
Probabilistic delineation of debris-flow routing pathways in cones and fans within a Monte Carlo framework
Authors: Schiavo Massimiliano , Bernard Martino , Barbini Matteo , Boreggio Mauro , Lopez Sandy , Gregoretti Carlo
Published: March 2024

Debris flow phenomena are difficult to predict because their occurrence depends on multiple factors (e.g. availability of sediment, volume, and rainfall intensity, as well as slope conditions before an intense rainfall event, etc.). When they occur, debris flows can significantly modify the topographic surface of conical-shaped fans and cones via erosion and deposition phenomena.This contribution aims, for the first time, to use a Monte Carlo approach to simulate the most probable avulsion paths of debris flows and define those conveying a certain drainage area with a minimum occurrence probability. We rely upon various digital terrain models (DEM) available for the Fiames area (Cortina d'Ampezzo, BL), covering approximately 1.6 km2 , and the average local elevation and the standard deviation of each cell of the domain are evaluated. We then generate N=2000 Monte Carlo realizations of possible topographic (equiprobable) surfaces, according to the geostatistical procedure known as Sequential Gaussian Simulations (SGSIMs). On each topographic surface obtained, the optimal drainage network is extracted using algorithms that guide the flow, by gravity, along the directions of maximum slope, as commonly used in hydrology. It is therefore possible to obtain as many drainage networks as there are simulated topographies. The ensemble of drainage networks (networks) is used to obtain the most probable network, extracted from the average topographic surface among the simulated ones.Furthermore, we set a threshold on the drainage area variable, thus it is possible to calculate the probability of having, in a domain's location, a flow conveyance (per unit of area) higher than the threshold one. Finally, it is possible to (at least preliminarily) evaluate the probability of existing infrastructure vulnerability by appraising the probability that they are located along possible drainage routes or not. The presented approach moves the analysis of avulsion paths within the probability space. It can be validated by verifying the correspondence between a part of the probable (synthetic) pathways with those that historically occurred. Furthermore, it allows us to define routes and (synthetic) triggering points different from the historical ones.
Microbial assemblies with distinct trophic strategies drive changes in soil microbial carbon use efficiency along vegetation primary succession in a glacier retreat area of the southeastern Tibetan Plateau
Authors: Ma Shenglan , Zhu Wanze , Wang Wenwu , Li Xia , Sheng Zheliang , Wanek Wolfgang
Published: March 2024

Microbial carbon use efficiency (CUE) is a vital physiological parameter in assessing soil carbon turnover. Yet, how microbial communities with distinct trophic strategies regulate soil microbial CUE has remained elusive. Based on the oligotrophic: copiotrophic framework, we here explored the role of microbial taxa with different trophic strategies in mediating microbial CUE (determined by a 13C-labeling approach) along the vegetation primary succession in the Hailuogou glacier retreat area of the southeastern Tibetan Plateau. Soil microbial CUE ranged from 0.54 to 0.72 (averaging 0.62 ± 0.01 across all samples), increasing markedly along the vegetation succession. Microbial assemblies with distinct trophic strategies were crucial regulators of soil microbial CUE. Specifically, microbial CUE increased with microbial oligotroph: copiotroph ratios, with oligotroph-dominated stages having a higher microbial CUE than copiotroph-dominated ones. The prevalence of oligotrophic members would therefore be linked to the high soil microbial CUE at late successional stages. Given that oligotrophs predominate in soils with more recalcitrant carbon and because of their higher microbial CUE, we speculate that oligotrophs are likely to promote carbon sequestration in soils. In addition, the responses of soil microbial CUE to fungal oligotroph: copiotroph ratios were stronger than to bacterial ones. Fungal taxa may play a particularly pronounced role in shaping microbial CUE relative to bacterial members. Overall, our results highlighted close associations between microbial trophic strategies and CUE and provide direct evidence regarding how microbial trophic strategies regulate soil microbial CUE. This study is a significant step forward for elucidating the physiological mechanisms regulating microbial CUE and has significant implications for understanding microbial-mediated carbon cycling processes.
Extreme surface solar radiation events and implications for PV energy generation
Authors: Folini Doris , Senger Guillaume , Chtirkova Boriana , Wohland Jan , Wild Martin
Published: March 2024

In the context of climate science and climate change, extreme events take a prominent place because of their potentially devastating impacts on various aspects of society, from economic losses to premature deaths. Much effort has gone, in particular, into the study of heat waves and droughts. Extreme events in surface solar downwelling radiation (SSR) have, by contrast, gained little interest so far. This neglect is at odds with the prominent role that photo-voltaic (PV) energy production, which feeds on SSR, is to play in the future.Based on daily-mean data from nine global climate models participating in the pre-industrial control experiment (piControl) of the Coupled Model Intercomparison Project-Phase 6 (CMIP6), we provide a descriptive analysis of extreme events in surface solar radiation (SSR) arising from internal variability of the climate system, with a geographical focus on central Europe, where we also anchor our analysis in 38 years of observed daily mean SSR data. Two kinds of extreme events are investigated: sustained radiation events (SREs, periods of L consecutive days with extremely high or low SSR on each single day) and cumulative radiation events (CREs, yearly minimum mean SSR over a period of L days). To explore the role of extreme SSR events in PV energy generation, we use the Global Solar Energy Estimator (GSEE, https://github.com/renewables-ninja/gsee).Selected findings from our analysis include the following. In central Europe, the frequency of SREs shows an exponential dependence on L, their duration in days. High SREs are more frequent than low SREs over global land. CREs in central Europe are well described by Generalized Extreme Value statistics with a negative shape parameter, similar to wind and temperature extremes. PV production associated with low SREs in central Europe is roughly linear in SSR with little sensitivity to panel orientation, while for high SREs PV production depends non-linearly on SSR and sensitivity to panel orientation is pronounced. PV production of high SRE events in winter greatly exceeds PV production of low SRE events in summer. Our results are a first step in examining the characteristics and relevance of SSR extreme events, highlighting the need for further studies.
Exploring landscape persistence and erosion dynamics in mountain catchments: A morphometric approach in the Swiss Alps and Blue Ridge Mountains, USA
Authors: Orr Elizabeth , Oien Rachel
Published: March 2024

In recent years, increased theoretical and modelling-based research has explored the persistence of mountain topography and the processes and timescales over which landscapes achieve a stable or ‘steady state’ form. Across various sub-disciplines of geomorphology, amphitheatre or arm-chair-shaped topography has been recognised as a more persistent landscape form, attainable through glacial, periglacial and/or fluvial processes. Once achieved, rates of landscape change may be subdued, or a higher magnitude forcing or event is needed to significantly alter the form. This has yet to be empirically tested in the headwaters of mountain catchments.This study evaluates the extent to which the morphometrics of catchment headwaters can provide insight into the persistence of mountain landscapes. This is achieved by exploring the dynamic relationships between topographic form and erosion in the Swiss Alps and Blue Ridge Mountains, USA.  We focus on two distinct mountain regions to capture a range of tectonic, climatic, and glacial settings. We use the novel ACME 2.0 GIS tool and high-resolution LiDAR data to characterise the morphometrics (inc. circularity, relief, hilltop curvature, hillslope length) of more than 50 catchments. We introduce a new Headwaters Topographic Form Index (HTFI) derived from these data, which allows us to compare topographic form between diverse mountain environments. To explore the links between form and rates of landscape change, we compare the HTFI and morphometric data with published catchment-averaged erosion rates.This study aims to explore some of the factors influencing landscape persistence in mountain catchment headwaters, providing new insights into how vulnerable mountain landscapes may respond to ongoing and future climate change. This work has implications for research focused on hillslope stability, mountain hazards (e.g., landsliding), and landscape evolution modelling.
Detection of a corotating interaction region in solar wind using RPW and SWA instruments of the Solar Orbiter mission.
Authors: Chechotkin Dmytro , Yakovlev Oleksandr , Bilokon Oleksandr
Published: March 2024

The study of characteristics, size, and shape variations of corotating interaction region (CIR) with changes in heliocentric distance is of scientific interest. The unique orbit parameters of the Solar Orbiter spacecraft (SOLO) and its set of equipment provide an opportunity to address the posed question. In our study, an attempt has been made to identify CIR regions using only data from the SOLO instruments.The methodology for identifying CIR is well-developed. It involves in-situ observations of solar wind parameters, such as those proposed in the works of Hajra and Sunny, and verifies the potential presence of high-speed streams (HSS) from coronal holes. Such verification can be performed using SDO/AIA extreme ultraviolet observation data. This methodology can be easily implemented considering the near-Earth satellite constellation. Often, the trajectory of the SOLO passes out of the visibility range of near-Earth solar observation facilities, and there is no opportunity to verify the presence of coronal holes on the solar disk, which could be sources of HSS. In such cases, it is necessary to rely solely on the data from the SOLO instruments.During the analysis of RPW instrument data, it was observed that sometimes the instrument registers shock events not confirmed by SWA instrument data. However, these events demonstrate an intense increase in solar wind speed and other parameters. The hypothesis has been put forward that multiple activations of the RPW instrument's SBM1 algorithm within a day can be used as a marker for the spacecraft's presence in the CIR zone. To validate this hypothesis, a comparative analysis of RPW data at the time of SBM1 events is conducted, comparing it with data from the SWA-PAS instrument. Based on the examples considered, a conclusion is drawn regarding the ability to track the spacecraft's entry and exit moments from the CIR region and assess the changes in CIR parameters when the spacecraft is within it.This work is supported by the “Long-term program of support of the Ukrainian research teams at the Polish Academy of Sciences carried out in collaboration with the U.S. National Academy of Sciences with the financial support of external partners”.
Progress towards a calibration facility for non-catching disdrometers
Authors: Kjeldsen Henrik , Østergaard Peter Friis , Nielsen Jan
Published: March 2024

Precipitation is among the most important meteorological variables for meteorological, hydrological and climate studies. From an operational point of view, non-catching precipitation gauges are attractive, because they require less maintenance compared to the more traditional catching types (e.g. gravimetric or tipping-bucket). For that reason, in recent years non-catching precipitation gauges are increasingly adopted in meteorological networks.
Despite the growing number of such gauges, calibration procedures and dedicated setups are missing. The result is that sensors are not calibrated, and this has a negative influence on the accuracy and reliability of the measured data. Therefore, Danish Technological Institute (DTI) is currently developing at setup for test and calibration of non-catching rain gauges. The setup is intended to simulate real rain, i.e. it will produce water drops that are similar in both size and velocity to those found in real rain. The setup can produce drops with diameters from about 0.2 mm to several mm. Traceability to the SI-unit system is obtained by flow and area measurements. In this context a volumetric pump is employed and calibrated gravimetrically in the DTI micro-flow laboratory. The drop velocity is determined using a photographic system. A key advantage of the setup is that the non-catching gauges can be calibrated under well-controlled, stable laboratory conditions.
The presentation describes the design principle and summarizes recent progress of the setup at DTI.
GTWS-MLrec: global terrestrial water storage reconstruction by machine learning from 1940 to present
Authors: Yin Jiabo , Slater Louise , Khouakhi Abdou , Liu Pan , Pokhrel Yadu , Liu Dedi , Gentine Pierre
Published: March 2024

Terrestrial water storage (TWS) includes all forms of water stored on and below the land surface, and is a key determinant of global water and energy budgets. However, TWS data from measurements by the Gravity Recovery and Climate Experiment (GRACE) satellite mission are only available from 2002, limiting global and regional understanding of the long-term trends and variabilities in the terrestrial water cycle under climate change. This study presents long-term (i.e., 1940-2022) and relatively high-resolution (i.e., 0.25°) monthly time series of TWS anomalies over the global land surface. The reconstruction is achieved by using a set of machine learning models with a large number of predictors, including climatic and hydrological variables, land use/land cover data, and vegetation indicators (e.g., leaf area index). The outcome, machine learning-reconstructed TWS estimates (i.e., GTWS-MLrec), fits well with the GRACE/GRACE-FO measurements, showing high correlation coefficients and low biases in the GRACE era. We also evaluate GTWS-MLrec with other independent products such as the land-ocean mass budget, atmospheric and terrestrial water budget in 341 large river basins, and streamflow measurements at 10,168 gauges. The results show that our proposed GTWS-MLrec performs overall as well as or is more reliable than previous TWS datasets. Moreover, our reconstructions successfully reproduce the consequences of climate variability, such as strong El Niño events. GTWS-MLrec dataset consists of three reconstructions based on JPL, CSR and GSFC mascons, three detrended and de-seasonalized reconstructions, and six global average TWS series over land areas, both with and without Greenland and Antarctica. Along with its extensive attributes, GTWS_MLrec can support a wide range of geoscience applications such as better understanding the global water budget, constraining and evaluating hydrological models, climate-carbon coupling, and water resources management.GTWS-MLrec is available on Zenodo through https://zenodo.org/records/10040927.
Multi-day precipitation extremes ranking and their association with atmospheric moisture fluxes over India
Authors: Gaspar Tomás , M. Trigo Ricardo , M. Ramos Alexandre , Singh Raghuvanshi Akash , Russo Ana , M.M. Soares Pedro , Ferreira Tiago , Agarwal Ankit
Published: March 2024

The Indian subcontinent is characterized by a pronounced summer monsoon season with substantial rainfall from June to September and a less intense autumn monsoon, albeit both posing major challenges to the densely populated regions through flash floods and landslides. During monsoons, different regions of India are affected by extreme precipitation events with distinct durations and triggered by several mechanisms. Here, considering 10 different regions of India characterized by different climatic regimes, we apply an objective ranking of extreme precipitation events, across various time scales, ranging from 1 to 10 days, making use of a high-resolution daily precipitation dataset covering the entire Indian territory from 1951 to 2022. The results confirm that the method accurately detects and ranks the most extreme precipitation events in each region, providing information on the daily evolution of the magnitude (and spatial extent affected) of high precipitation values in each region. Moreover, results show that top rank events can be associated with different types of storms affecting the four main coastal regions of India. In particular, some top rank events can be critically linked to long duration events (e.g., 10 days), which can be missed in ranks for shorter duration (e.g., 1-3 days) periods, thus stressing the need to employ multi-day precipitation extremes ranking. Finally, an in-depth analysis of the large-scale atmospheric circulation and moisture transport is presented for the top 10-day events affecting four coastal regions of India. Overall, we are confident that our findings are valuable in advancing disaster risk reduction strategies, optimizing water resource management practices, and formulating climate change adaptation strategies specifically tailored for the Indian subcontinent. R.M.T., A.R., S.P. and A.T.M. thank Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020 (https://doi.org/10.54499/UIDP/50019/2020) and LA/P/0068/2020 (https://doi.org/10.54499/LA/P/0068/2020). A.R. and R.M.T. thank also FCT (https://doi.org/10.54499/2022.09185.PTDC, http://doi.org/10.54499/JPIOCEANS/0001/2019, https://doi.org/10.54499/DRI/India/0098/2020). A.R. was supported by FCT through https://doi.org/10.54499/2022.01167.CEECIND/CP1722/CT0006. 
Arctic Wintertime Sea Ice Lead Detection from Sentinel-1 SAR Images
Authors: Chen Shiyi , Shokr Mohammed , Zhang Lu , Zhang Zhilun , Hui Fengming , Cheng Xiao , Qin Peng
Published: March 2024

Leads in sea ice cover are almost linear fractures within the pack ice, and are commonly observed in the polar regions. In winter, leads promote energy flux from the underlying ocean to the atmosphere. Synthetic aperture radar (SAR) can monitor leads with a fine spatial resolution, regardless of solar illumination and atmospheric conditions. In this paper, we present an approach for automatic sea ice lead detection (SILDET) in the Arctic wintertime using Sentinel-1 SAR images. SILDET is made up of four modules: 1) a segmentation module; 2) a balance module; 3) an optimization module; and 4) a mask module. The validation results presented in this paper show that SILDET has the capability of detecting open and frozen leads at different stages of freezing. The lead map obtained from SILDET was compared to a lead dataset based on Moderate Resolution Imaging Spectroradiometer (MODIS) data and validated by the use of Sentinel-2 images. This shows that SILDET can provide a more detailed distribution of leads and better estimation of lead width and area. Compared with visual interpretation of Sentinel-1 images, the overall detection accuracy is 97.80% and the Kappa coefficient is 0.88 (for all types). The pyramid scene parsing network (PSPNet) in the segmentation module shows a better performance in detecting frozen leads, compared with the deep learning methods of UNet and DeepLabv3+. The optimization module utilizing shape features also improves the precision in detecting frozen leads. SILDET was applied to present the Arctic lead distribution in January and April 2023 with a spatial resolution of 40 m. The Arctic-wide lead width distribution follows a power law with an exponent of 1.64 ± 0.07. SILDET can be expected to provide long-term high-resolution lead distribution records.
The role of graphite in the formation of thrust faults on Mercury
Authors: Vergara Sassarini Natalia Amanda , Massironi Matteo , Giacomini Lorenza , Bistacchi Andrea
Published: March 2024

Globally, the most widespread contractional landforms on Mercury are lobate scarps. Lobate scarps are linear or curvilinear topographic features interpreted as the surface expression of thrust faults, formed as a consequence of planetary cooling and contraction. These features have been studied extensively, from the initial images captured by Mariner-10 to the more recent data acquired by MESSENGER's Mercury Dual Imaging System (MDIS). However, although several works have analyzed the global tectonics of the planet (e.g., Klimckzak et al. 2015; Watters et al., 2015), a comprehensive interpretation of thrust faults geometry and their mechanical behavior on a global scale has not yet been fully constrained. Here we show that the formation and growth of large-scale lobate scarps is facilitated by the presence of a graphite-rich layer(s), acting as fault lubricant. We studied thrust faults from seven different Mercury quadrangles and derived their geometric characteristics (relief height, amount of shortening, detachment depth) considering a fault-propagation geometry for a range of possible dip angles on isolated thrusts. Using a critical taper theory-based model (iterative mechanical model) we then estimated the basal friction coefficient for thrust-belts located in the same quadrangles. The low friction coefficients obtained under three different lithospheric initial conditions indicate the presence of a weak material that allows fault slip. Our results demonstrate the crucial role that graphite possibly plays in shaping Mercury’s lithosphere, providing new understanding on thrust faults nucleation and growth and establishing a possible connection between surface deformational processes and Mercury’s early crust composition.