bluuebunny/crossref_metadata_2025 huggingface dataset:
Characterization of different crop types using biophysical indicators derived from Sentinel-2 MSI multi-temporal data in Sudurpashchim Province, Western Nepal
Authors: Sahbeni Ghada , Székely Balázs , Sahajpal Ritvik
Published: February 2023

Consistent information on agricultural land use provides a fundamental basis for sustainable land management, achieving zero hunger (SDG2) and maintaining life on land (SDG15) in South Asia and Nepal in particular due to its high vulnerability to natural disasters caused by its diverse geo-climatic system. The present study aims to characterize different crop types (i.e., Maize, Sugarcane, and Wheat) cultivated in Sudurpashchim Province, one of Nepal’s most heavily cultivated areas, and identify their spectral behavior using Sentinel-2 MSI multitemporal data acquired between January and December 2021. In this regard, forty crop profiles were identified based on a 250-m crop-type map provided by the National Soil Science Research Center (NSSRC). Leaf Area Index (LAI), Fractional Vegetation Cover (FVC), and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), in combination with Normalized Difference Vegetation Index (NDVI) and Shortwave Infrared bands (SWIR1 and SWIR2), were derived for each crop profile, then averaged per crop type to assess the overall trend. The results revealed the efficiency of biophysical indicators in crop type identification during their growing season. While shortwave infrared bands partially failed to characterize different cropping systems, LAI and FVC performed well in terms of separating wheat from other crops in the February-March period, revealed by maximum values reaching 1.2 and 0.4; then a sudden drop to 0.5 and 0.17 for LAI and FVC, respectively, during the harvesting season. For sugarcane, peak values have been observed during the July-September period, with LAI between 0.8 and 1 and FVC of approximately 0.4. Although a less unusual behavior has been registered for maize, local maxima for LAI, FVC, NDVI, and FAPAR around the July-August period have been found. This was followed by a notable decrease in September, which is contemporary with the harvesting season. Despite the fact that the increasing and decreasing trends of biophysical parameters are relatively synchronous with crop calendars, the distinction between different crop profiles can be robustly improved by adding more profiles and using Sentinel-1 SAR to take advantage of weather insusceptibility, which was a limiting factor for Sentinel-2 MSI.
Constraining the tropical anvil cloud "iris" feedback
Authors: McKim Brett , Bony Sandrine , Saint-Lu Marion , Dufresne Jean-Louis
Published: February 2023

An outstanding question in climate science is how much the change in tropical anvil cloud clover with warming influences Earth's climate sensitivity. Here, we construct a simple model of cloud radiative effects to obtain an analytical equation for the tropical anvil area “iris” feedback. Our equation shows how the feedback is constrained by the fractional change in anvil cloud area, the anvil cloud radiative effect, and the radiative masking of low clouds that live beneath anvils.  We then look at satellite observations to diagnose these quantities. We find that the inferred values of anvil cloud radiative effect and low cloud masking effects sum to 1 Wm-2. Owing to this small radiative effect, the observed changes in anvil cloud cover in interannual variability implies an iris feedback that is wholly insufficient to strongly influence climate sensitivity. We then extend our equation to address whether anvil clouds might affect climate sensitivity through their masking of other forcings  or feedbacks.
Enhancing the spatial and temporal resolution of air quality monitoring in low – and middle-income countries using low-cost sensors
Authors: Hodoli Collins Gameli , Amoah Anthony , Buer Boyetey Dominic , Mead Iq , Coulon Frederic , Pant Pallavi , Ivey Cesunica E. , Owusu Tawiah Victoria , Nimoo James , Morladza John-Terry , Raheja Garima , Amedofu Mawuli , Allison Hughes Felix , Kowu Nelson , Appoh Emmanuel , Essien Benjamin , Malings Carl , Westervelt Daniel M.
Published: February 2023

Air pollution is one of the leading risk factors for poor health in Africa, resulting in millions of premature deaths and economic losses. Of particular interest is exposure to fine particulate matter (PM2.5) which is the driver for a majority of deaths across the continent. However, PM monitoring, and by extension, ground-level data on PM2.5 is very limited; this limits our understanding of the widespread societal and health impacts linked to PM pollution. The robustness of low-cost PM sensors and their ability to report in situ data in tropical environments via internet-based platforms as well as relative affordability has created the opportunity to employ low-cost sensors (LCS) for air quality monitoring but calibration methodologies and the usefulness of the high-temporal resolution data for source identification remain a challenge. Increasingly, local governments in African countries are also turning to low-cost sensors to monitor air quality. In this study, two Airnote PM monitors were colocated with reference-grade Teledyne PM mass monitor T640 for ~4 weeks at the University of Ghana, Accra to establish their performance using a simplified data correction methodology - multiple linear regression (MLR) model. A split ratio of 80% and 20% was used to train and test the populated Airnote PM2.5 data respectively based on measurements from Teledyne T640 with temperature and relative humidity values from the Airnote monitor. Sectoral and calendar analysis with wind component data were used to triangulate the sources of PM2.5. We observed a high consistency between the two Airnote monitors. Hourly and 24-hour average PM2.5 values ranged from 25 to 95 μg/m3, and 29 to 54 μg/m3 respectively, and in most cases, were significantly higher than the WHO Air Quality Guideline. MLR using Pearson’s correlation analysis improved the out-of-the-box quality of low-cost Airnote PM2.5 data; the R2 improved from 0.69 to 0.84 and the mean absolute error from 11.75 to 4.20 μg/m3 respectively. Also, the MLR correction model was found to improve the Airnote PM2.5 data quality for higher relative humidity (between 50 and 90%) but not lower. PM2.5 pollution was local and from N, NE and SW winds for the raw, corrected and Teledyne PM mass monitor T640 measurements. Together, these results indicate that with appropriate corrections, low-cost PM sensors can generate the much needed data for air pollution research and mitigation in areas with limited air quality monitoring and data.
Evaluation of external spherical harmonic series inside the minimum Brillouin sphere: examples for the lunar gravitational field
Authors: Šprlák Michal , Han Shin-Chan , Pitoňák Martin , Novák Pavel
Published: February 2023

Spherical harmonic expansions are routinely used to represent the gravitational potential and its higher-order spatial derivatives in global geodetic, geophysical, and planetary science applications. The convergence domain of external spherical harmonic expansions is the space outside the minimum Brillouin sphere (the smallest sphere containing all masses of the planetary body). Nevertheless, these expansions are commonly employed inside this bounding surface without any corrections. Justification of this procedure has been debated for several decades, but conclusions among scholars are indefinite and even contradictory.In this contribution, we examine the use of external spherical harmonic expansions for the gravitational field modelling inside the minimum Brillouin sphere. We employ the most recent lunar topographic LOLA (Lunar Orbiter Laser Altimeter) products and the measurements of the lunar gravitational field by the GRAIL (Gravity Recovery and Interior Laboratory) satellite mission. We analyse selected quantities calculated from the most recent GRAIL-derived gravitational field models and forward-modelled (topography-inferred) quantities synthesised by internal/external spherical harmonic expansions. The comparison is performed in the spectral domain (in terms of degree variances depending on the spherical harmonic degree) and in the spatial domain (in terms of spatial maps). To our knowledge, GRAIL is the first gravitational sensor ever, which helped to resolve the long-lasting convergence/divergence problem for the analytical downward continuation of the external spherical harmonic expansions, see (Šprlák and Han, 2021). ReferencesŠprlák M, Han S-C (2021) On the Use of Spherical Harmonic Series Inside the Minimum Brillouin Sphere: Theoretical Review and Evaluation by GRAIL and LOLA Satellite Data. Earth-Science Reviews, 222, 103739, https://doi.org/10.1016/j.earscirev.2021.103739.
Assessing the value of Digital Soil Assessment: a bridge too far?
Authors: Corstanje Ron , Hannam Jack
Published: February 2023

Digital Soil Mapping (DSM) is a demonstrated viable approach to generate spatial predictions of soil properties but Digital Soil Assessment (DSA) methods are not widely applied as the translational step from DSM to DSA remains challenging. The purpose, in generic terms, of DSA is the conversion of quantitative data on soil properties obtained through DSM to a spatial assessment of the capacity of a soil to fulfil a particular function. However, the interpretation and value of soil information to users for effective decision making is often qualitative rather than quantitative, expressing the capacity and capability of soil to deliver particular services or perform particular functions. We identify three challenges to implementing DSA for decision making and illustrate these with several case studies: 1) Bridging the gap between quantitative DSM to qualitative DSA.  Soil Quality and Health (SQH) are general terms for indicators that are associated with soil security which are neither easy to define, nor easy to quantify. Through combining the UK national soils datasets, and the SQH Bayesian inference, we were then able to predict SQH for soils across Great Britain.  We show that we are able to describe both aleatoric uncertainty and, equally important, epistemic uncertainty through a description of the experts confidence and through using multiple experts. 2) Cascading the uncertainty generated from DSM into DSA. We demonstrate using a stochastic simulation technique and specified threshold values for soil constraints for crop growth that the uncertainty can be incorporated into the resulting value assessments. We show that DSA can be used to quantify the potential contributions of soil constraints versus socio-economic, farm management and other factors, and the importance of allowing for uncertainties and having appropriate constraint criteria is illustrated by the sensitivity of our constraint estimates to the various criteria we tested. 3) Incorporating temporally dynamic environmental data. We developed a DSA that integrated a dynamic modelling approach to determine land suitability under future climatic variability.  The DSA outputs highlighted where best to grow food in the future based on soil and climate interactions, however decision making needs to address potential trade-offs in other soil services before deciding when and where to protect the best quality land. Although we illustrate, through these examples, that informative and useful spatial data about the soil can be obtained through DSA, in each case the process is elaborate and complex, with significant modelling challenges. Unlike DSM, DSA introduces a value judgement on the soil which can be difficult to capture through quantitative modelling processes.
Scale Heterogeneity Avoided Dasymetric Mapping for the Gridded Population
Authors: Lu Weipeng , Weng Qihao
Published: February 2023

The gridded population, crucial for resource allocation and emergency support, is mainly downscaled from the census data with administrative divisions. A common dasymetric mapping approach is building a regression model between aggregated geospatial properties and population potential at the administrative level and then applying this model directly to the grid level. The aggregation of geospatial properties often relies on statistical methods like averaging. However, the difference in scale between the two levels can lead to the heterogeneity of geospatial properties, which causes a gap between the training domain and the target domain and makes these methods fail to preserve the physical meaning of geographic properties. To address this issue, we propose a deep learning-based approach, in which a sophisticated loss function involving tripartite elements, gridded geospatial properties, gridded population potential, and administrative population potential, is designed. In this way, scale heterogeneity both in aggregation and domains can be avoided. In this study, a 30-meter resolution population density map of Hong Kong is produced through the proposed approach. The validation result shows that compared with both the machine learning-based or the artificial neural network-based one, the proposed approach gets a lower RMSE and potentially provides a more accurate reference for detailed urban management.
Evolution of tunnel valleys – contrasting examples from western Poland (Scandinavian Ice Sheet)
Authors: Lipka Ewelina , Kalita Jakub
Published: February 2023

Tunnel valleys are commonly found in beds of palaeo-ice sheets. They indicate subglacial meltwater pathways in near marginal environment. Their formation mechanisms are still debated, with hypotheses ranging from gradual, time-transgressive origin to catastrophic. The aim of the study is to contribute to the discussion by comparative analysis of tunnel valleys footprint that was formed during the deglaciation of Scandinavian Ice Sheet from its southernmost sector.The context of the study area comprises quasi-regular set of tunnel valleys located in close proximity to anastomosing network of tunnel valleys. From the former pattern, two neighbouring tunnel valleys (eastern and western) located ca 7 km away were selected for detailed landform analysis, performed using a Digital Elevation Model (DEM) based on high-resolution LiDAR data.Both tunnel valleys are ca 12-14 km long. The proximal parts of both valleys have similar width as well – ca 1 km, though the western tunnel valley gets much wider in the distal part, compared to the eastern one. The depth of incision of the western tunnel valley is smaller ( >20 m) compared to the eastern one ( >40 m). The eastern one ends with an extensive outwash fan, the other, western one, not – its southern (distal) part gets wider and shallower down-ice, with an array of landforms related to glacial meltwater flow. The western tunnel valley seems only half-developed, with its southern part much wider, shallower and less pronounced: the valley gets less sharply defined down-ice.  The distal part of the western valley contains an array of landforms formed under high energy turbulent flow, possibly evidence of subglacial flood: mega-scale current ripples (giant current ripples - several ridges with arcuate crests arranged more-less perpendicular to the tunnel valley axis), circular incision, scours/furrows, and potholes.The composite sequence of landforms comprising the tunnel valleys suggest they were forming in highly dynamic environment and switching between steady-state conditions to catastrophic basal flooding events. Both tunnel valleys analysed here reveal similar evolution history to an extent - with a different ending.This contribution presents the findings of an initial study, which will be continued and complemented with sediment lithofacies analysis.  
Open Magnetic Flux in the Time-Evolving Corona
Authors: Linker Jon A. , Mason Emily , Lionello Roberto , Downs Cooper , Caplan Ronald , Titov Viacheslav , Riley Pete , DeRosa Marc
Published: February 2023

Models of the Solar Corona, ranging from potential field source surface (PFSS) to magnetohydrodynamic (MHD), typically provide a steady-state representation for a given time period, based on a single photospheric magnetic map.  However, the Sun's magnetic flux is in truth constantly evolving, and these changes in the flux affect the structure and dynamics of the corona and heliosphere.  The dynamics may be crucial to understanding solar wind properties.  A key question in the "Open Flux Problem" is whether the nature of open magnetic flux is adequately captured by steady-state PFSS and MHD models.  We describe an approach to evolutionary models of the corona and solar wind, using time-dependent boundary conditions.  We use the Lockheed Surface Flux Transport (SFT) model to evolve the surface magnetic fields, which in turn drive the coronal evolution.  The simulations are performed with the MAS thermodynamic Wave-Turbulence Driven (WTD) model for a month of simulated time.  We use the simulated observables derived from the simulation to explore the evolution of coronal structure (e.g., coronal hole boundaries).  We investigate the open magnetic flux in the model and contrast the results with MHD solutions using static magnetic flux boundaries at selected times.
Persistent anomalies of the North Atlantic jet stream and associated surface extremes over Europe
Authors: Galfi Vera Melinda , Messori Gabriele
Published: February 2023

Persistent unusual configurations of the North Atlantic jet stream affect the weather and climate over Europe. We focus on winter and on intraseasonal and seasonal time scales, and study persistent jet anomalies through the lens of large deviation theory using CMIP6 simulations of the MPI-ESM-LR model and ERA5 reanalysis data. Our results show that persistent temperature and precipitation extremes over large European regions are anomalously frequent during the unusual, persistent jet configurations we identify. Furthermore, the relative increase in frequency of surface extremes is larger as we consider more intense surface extremes and/or more extreme jet anomalies. The highest extreme event frequencies at the surface are observed in case of precipitation over the Mediterranean and Western Europe during anomalously zonal and/or fast jet events, pointing to these jet anomalies matching rather homogeneous large-scale atmospheric configurations with a clear surface footprint. Additionally, our results emphasise the usefulness of large deviation rate functions to estimate the frequency of occurrence of persistent jet anomalies, and more generally of unusual, persistent atmospheric circulation patterns.
Internal structure and present-day activity of deep-seated gravitational slope deformation (Chingjing, Taiwan)
Authors: Lin Cheng-Han , Lin Ming-Lang
Published: February 2023

Deep-seated gravitational slope deformation (DSGSD) is a rock mass wasting process of high mountain slopes, featuring slow movement rate. Although DSGSD movement is slow, it can continue for a long period, producing large cumulative displacements and could transform to catastrophic rockslides. In Taiwan, DSGSD has often been reported in the slate belt of the Taiwan’s backbone Range because of the inherent cleavage characteristic. When the slate slope undergoing DSGSD, the geometry of cleavage structures will interact with topographic slope and manifest by different internal structures such as toppling features and flexural folding. This study investigates how the DSGSD influences the internal structures and present-day activity of slate slopes in the Chingjing region, Taiwan. We focus on where the cleavage dip direction is parallel to the topographic downslope direction. To describe the relationship between cleavage structure and DSGSD movement, we present 2D numerical simulation of simplified slopes using the distinct element modeling approach. The slope topography and cleavage geometry are based on the typical values of slate slope in the study area. The simulation shows that the rotation of the cleavage dip angle has correlated with the slope deformation mechanics at different locations. The toppling structure appears to the slope toe, and the cleavage remains the same dip angle at the crest. Three hinge lines can be identified at different depths of the slope, which suggests the location of potential basal shear bands within the slope. We also observe the distribution of the shear bands emerging at higher elevation as the deformation velocity decreases. Parametric study shows that deformation of internal structures can exist at depths of 60 m and more as a result of slope height, slope steepness and cleavage dip angle. On the other hand, this study retrieves slope kinematics by performing 2D decomposition of PS-InSAR products derived from Sentinel-1 data acquired in ascending and descending orbits. The result shows that surface displacement ranges in 5 - 10 mm/year in the period of 2015 - 2017, and the displacement rate increases to 10 - 30 mm/year in the period of 2018 - 2020. By detecting velocity change and identifying deformation dip vector, we explain the present-day activity of DSGSD and driving mechanisms in the study cases. Overall, based on mechanical modeling, our analyses demonstrate that a cataclinal slate slope can exhibit different internal structure patterns in different sectors during DSGSD. We also highlight the need for InSAR-assisted monitoring in the region lack of surface displacement data for deeper understanding of this long-term process and interactions between slope activity and potential driving force.
A Resource Nexus concept - Definition, design, and practice
Authors: Brouwer Floor
Published: February 2023

The nexus has gained importance in assessing interlinkages between related resources and is critical to achieving broader policy goals such as the Sustainable Development Goals (SDGs) or targeted objectives related to biodiversity and climate. Creating awareness of such interactions offers a basis to seek synergies that might be created. Guided by an extensive literature review and a consultation of nexus experts, the presentation will summarize the main features of the nexus and an overview of essential resources that are critical for consideration in a Resource Nexus concept. Definitions of the nexus provided in the literature typically relate to focused and often limited approaches. Moreover, some steps are presented to advance the concept in Resource Nexus assessments. In light of the latter, an effort is made to propose a more robust definition of the Resource Nexus for its application and operationalization for policy support. 
Ecosystem impacts due to thermocline depression by the 2019 extreme Indian Ocean Dipole event
Authors: Robinson Edward , Hosegood Philip , Vlasenko Vasiliy , Stashchuk Nataliya , Diaz Clara , Foster Nicola , Harris Joanna , Embling Clare , Howell Kerry
Published: February 2023

Tropical atoll habitats are often key conservation targets due to being inhabited by several vulnerable species such as reef manta rays and tropical coral species. These atolls are subject to both basin scale forcing through the Indian Ocean Dipole (IOD), monsoonal variation, and local processes. The steep slopes surrounding these atolls support highly dynamic, energetic nearshore ecosystems which vary over sub-kilometre spatial scales that are poorly resolved in general circulation models. Improving our understanding of how physical oceanographic processes control these local ecosystems, through both in-situ observations, and fine scale models, is critical for enabling informed policy decisions and efficient use of conservation resources. Here we summarise the impact of the local fine scale processes, which are heavily modulated by the monsoon and Indian Ocean Dipole (IOD), on a tropical atoll ecosystem in the central Indian Ocean (IO).The IOD is experiencing increasingly extreme fluctuations with direct impacts on the depth of the thermocline throughout the western IO. In our observations from 2019, the IOD deepened the thermocline to an unprecedented depth of 100 m, subjecting mesophotic corals to temperatures typical of surface waters and causing significant bleaching. High resolution numerical modelling shows that internal waves, rather than alleviating bleaching, further exacerbate the heating effects preferentially advecting high temperature surface water to increased depths. The wave influence is, however, highly localised, necessitating designated studies at individual sites to understand the spatial heterogeneity in internal wave impacts.At smaller sub-atoll scales, the IOD also influences the feeding behaviour of reef manta rays, which are more frequently detected in the presence of tidally forced surface-to-bottom temperature gradients. The site of most manta ray detections in the study area is a lipped gully, situated at 60-70 m depth, and colloquially named 'Manta Alley'. During deeper thermoclines, the cooling events within Manta Alley, with which increased reef manta presence is associated, are precluded from occurring due to the deep thermocline, impacting feeding behaviour.Our results highlight the inherent dynamical complexity in these environments, with the impacts of basin scale processes cascading down to local scales. Improving our understanding of how these dynamics cross-interact with each other, as well as the local ecosystem, enhances the value of biological observations, presenting the opportunity for better informed and more effective conservation strategy.
Sensitivity Analysis of the SUMMA Model on the Global Scale
Authors: Liu Hongli , Clark Martyn , Tang Guoqiang , Knoben Wouter , Gharari Shervan , Freer Jim , Arnal Louise , Casson Dave
Published: February 2023

Despite the recent advances, the identification of influential hydrologic processes and parameters of the process-based hydrologic model is still challenging. Part of the reason is the uncertain and interacting hydrologic process and the high dimensional parameter space. The motivation for this work is to effectively select an appropriate set of hydrologic processes and parameters for each basin on the globe, which is not necessarily the same everywhere. Here we evaluate the applications of the Structure for Unifying Multiple Modeling Alternatives (SUMMA) model to a large number of representative areas on the globe. Our objective is to identify the dominant hydrologic processes and sensitive model parameters for each representative area. First, sensitivity indices of the SUMMA parameters are computed using the VISCOUS global sensitivity analysis method. VISCOUS is the abbreviation of Variance-based Sensitivity Analysis using Copulas. Second, the sensitivity values are summarized per hydrologic process (e.g., snowmelt, surface runoff, infiltration, soil moisture, evapotranspiration, baseflow, and runoff) and per simulation statistic (e.g., mean, coefficient of variance, and autoregressive lag 1). The summarized sensitivity indices enable modelers to identify the most dominant hydrologic processes in each representative area. The results of this study will provide a foundation to estimate parameters in large-domain applications of process-based hydrologic models.
Decoding downstream trends in stratigraphic grain size distribution: examples from the Kerinitis Gilbert type delta, Greece.
Authors: Rezwan Nahin , Whittaker Alexander , Gupta Sanjeev , Castelltort Sébastien , Schlunegger Fritz , Braun Jean , Sømme Tor , Mcleod Jonah , Hook Joel
Published: February 2023

Stratigraphy represents a physical record of the behavior of source to sink sedimentary systems in the geological past. Grain-size fining in stratigraphy toward the downstream direction is driven by the sediment supply, subsidence rate and accommodation space generation. In principle these grain size trends can be inverted to quantify the temporal and spatial variation in these driving forces. This work addresses this challenge to understand how stratigraphic grain size fining reflects sediment flux and accommodation space generation in a normal fault bounded sedimentary system in the Gulf of Corinth, Greece. A SW to NE 2.6 km exposed natural cliff cut section of the middle Pleistocene Kerinitis Gilbert type delta has been selected for its accessibility, where the stratigraphic units are traceable, and where the timing of sediment deposition is well constrained (500 to 800 ka). The qualitative evolution of the fault is also understood as the three mapped depositional packages (lower part, middle part and the upper part) in the Kerinitis delta are thought to represent the initiation, development, and termination of the Pirgaki-Marmoussia fault. Down-system grain size data has been collected using the Wolman point count method at 25 measurement stations, predominantly from fluvial top-sets following for several timelines. Furthermore, high-resolution grain size photographs have been captured to study the inaccessible higher stratigraphic units. Paleoflow direction is reconstructed using a pebble imbrication dataset, which indicates the source to sink direction. For the grain size datasets, we have applied several self-similarity tests to evaluate the mutual relationship among the datasets. Our result shows that almost all the datasets exhibit significantly self-similarity with each other. We reconstruct grain size fining trends for each of the units, which we quantitatively relate to the spatial distribution of subsidence and sediment flux using a self-similarity based fining model. Our analysis gives new insights into the evolution of the delta bounding Pirgaki-Marmoussia fault and show how grain size data can be used to reconstruct landscape dynamics in the past.
The Time-Frequency Analysis (TFA) toolbox: a versatile processing tool for the recognition of magnetospheric and ionospheric signals in Swarm time series
Authors: Balasis Georgios , Papadimitriou Constantinos , Boutsi Adamantia Zoe , Vasalos Georgios , Antonopoulou Alexandra , Giannakis Omiros , Smith Ashley
Published: February 2023

The ongoing Swarm mission of the European Space Agency (ESA) provides an opportunity for a better knowledge of the near-Earth electromagnetic environment, including investigations of ultra-low frequency (ULF) wave events. The Time-Frequency Analysis (TFA) tool is a processing tool established for deriving Pc1 (0.2–5 Hz) and Pc3 (20–100 mHz) wave indices. The tool includes both a graphical interface as well as a dedicated back-end that can be used to perform wavelet analysis and visualize the results for both Pc1 and Pc3 waves, using both Swarm magnetic Level 1b 50 Hz and 1 Hz data. Following recommendations from the Advisory Board of the Swarm Data, Innovation and Science Cluster (Swarm DISC) the tool has been further developed and generalized so as to accommodate analysis of other types of time series from both satellite and ground station measurements. In particular, the resulting TFA toolbox provides users with the capabilities of studying different wave types (e.g. compressional waves, Alfvén waves, etc.), various magnetic field components (e.g. in Mean Field Aligned – MFA coordinates), and other geophysical measurements (e.g. electric field, plasma parameters). The TFA toolbox is also able to detect external source signals, e.g. due to plasma instabilities, and artificial disturbances (anomalies), e.g. spikes, jumps. It is possible also to use data from ground stations in a consistent format, e.g. 1 Hz magnetic observatory data as available in the virtual research service - VirES for Swarm. Moreover, integration of the TFA toolbox into the VirES platform is currently under development. This presentation aims to demonstrate the unique capabilities of the Swarm DISC TFA toolbox.
Hysteresis of idealized marine outlet glaciers under variation of pinning-point buttressing
Authors: Feldmann Johannes , Winkelmann Ricarda , Levermann Anders
Published: February 2023

Ice-shelf pinning points such as ice rises or ice rumples can have an important role in regulating the ice discharge of marine outlet glaciers. For instance, the observed gradual ungrounding of the ice shelf of West Antarctica's Thwaites Glacier from its last pinning points diminishes the buttressing effect of the ice shelf and thus contributes to the destabilization of the outlet. Here we use an idealized experimental setting to simulate the response of an Antarctic-type marine outlet glacier to a successive ungrounding of its ice shelf from a pinning point. This is realized by perturbing steady states by a step-wise lowering of the pinning point, which induces a buttressing reduction. After the complete detachment of the ice shelf from the pinning point the perturbation is reversed, i.e., the pinnning point is incrementally elevated toward its initial elevation. First results show that the glacier retreat down the landward down-sloping (retrograde) bed, induced by the loss in buttressing, can be reversible in case of a relatively flat retrograde bed slope. For steeper slopes, glacier retreat and re-advance show a hysteretic behavior. Thus, if the bed depression is sufficiently deep, the glacier does not recover from its fully retreated state even for pinning-point elevations that are higher than the initial elevation.
Impact of the MJO on the extreme precipitations in the Mexican Valley
Authors: Proveyer Liset V. , Jaramillo Alejandro
Published: February 2023

This research aims to determine how the Madden-Julian oscillation (MJO) influences extreme summer precipitation events in the Metropolitan Area of the Mexican Valley (MAMV). Using the Real-time Multivariate MJO Index (RMM), we found a higher frequency of days with extreme events during phases 1 and 2 of the MJO (wet phases), with the lowest occurrence during phases 6, 7, and 8 (dry phases). These frequencies are associated with positive (negative) humidity anomalies in the whole atmospheric column of the study region during the wet (dry) phases. The interaction of a humid flow from the Caribbean Sea with the mountain systems of the region plays a fundamental role in the occurrence of deep convection. Also, the formation of mesoscale convective systems in the central region of the Mexican territory contributes to the moisture content in the Mexican Valley. We used the Dynamic Recycling Model to quantify the relative contributions of different source regions to the atmospheric humidity in MAMV. We found that the greatest contributions to the humidity anomalies are from the Caribbean Sea and Central Mexico during the wet phases of the MJO. During the remaining phases, we observe a weakening of the humid flow from the east as the Caribbean low-level jet intensifies. Additionally, during phases 7 and 8, the mountainous systems that limit the MAMV constitute natural barriers to the flow of humidity that tends to be predominantly from the eastern Pacific. The MAMV is highly vulnerable to extreme precipitation events and their effects, such as pluvial floods and landslides. Therefore, studying the phenomena that modulate these extreme events is essential to improve their predictability and perform better risk management.
Application of Soil moisture in Regionalization framework for Predictions in Ungauged Basin and its Uncertainty quantification
Authors: Vema Vamsikrishna , Pattabiraman Balasundaram
Published: February 2023

Continuous streamflow prediction in ungauged basin and the quantification of its uncertainty has been challenging over the decades. Regionalization of parameters from gauged basin has been the most promising approach adopted by the researchers. However, the improvement of hydrological model prediction in regionalization with proper alternative observed data has been constantly explored. Various researchers have used remote sensing based products such as soil moisture and evapotranspiration as variables for calibration of hydrological models. While the regionalization based approach result in higher predictive uncertainty, performance of models calibrated using remote sensing products have been found to be sub-optimal. In this context, a combined approach of regionalization and remote sensing data may result in reduced predictive uncertainty and enhanced accuracy. In this study the predictive uncertainty quantification in ungauged basin is proposed using the regression-based regionalization framework between the catchment attributes and probability distribution function (PDF) of hydrological model parameters. The PDF of the hydrological model parameters is derived using the MCMC procedure in the DREAM algorithm. The proposed approach is evaluated using the data pertaining to 12 watersheds in the MOPEX database and assuming one of the catchments as pseudo-ungauged catchment. The uncertainty quantification in regionalization for streamflow prediction analysed by average of the prediction is better performing with NSE of 0.77 in pseudo ungauged basin (Sugar Creek EdinBurgh watershed). Further, the remote sensing soil moisture from GLDAS was compared with the model simulated soil moisture analysed using NSE to sub sample the regionalization parameter space in ungauged basin. The regionalization of the reduced parameter set to assess the change in uncertainty quantification is performed and found to have same performance NSE of 0.77 in ungauged basin for streamflow prediction with reduction in average width of 0.23 mm/day in ensembles of streamflow prediction. The ensemble of the simulations has similar performance compared to the model calibrated using streamflow (NSE 0.77). The outcome of the study indicates that the calibration of hydrological model using remote sensing soil moisture product as simulating variable have improved performance the model prediction in the parameter range obtained from the regionalization framework in the ungauged basin. Thus, the integration of regionalization approach with simulation of hydrological model using remote sensing products in the ungauged basin is recommended to apply in the real time applications of water resources management.
Variation characteristics of mesoscale lakes in the Tibetan Plateau
Authors: Ma Weiyao , Bai Lin , Ma Weiqiang , Hu Wei , Xie Zhipeng , Su Rongmingzhu , Wang Binbin , Ma Yaoming
Published: February 2023

Known as “Water Tower of Asia”, the Tibetan Plateau (TP) is widely distributed with numerous inflow lakes. Lakes on the TP are less affected by human actives and can be considered as a sensitive indicator of climate change, changes of lakes can well reflect the change of regional climate. However, due to the harsh environment, data acquisition is not easy, studies on the response of lake change to climate mainly focus on several typical lakes (Nam Co, Selin Co Ngoring lake, etc.), but less attention is paid to variation characteristics of mesoscale lake (~100km2). To compensate for this deficiency, we selected three typical mesoscale lakes (Bamu Co, Langa Co and Longmu Co) in different climate zones and studied the lake changes and their responses to climate change using in-situ observations data and remote sensing data. By using multisource remote sensing and water level observation data, this study systematically analyzed inter-annual changes from 1970 to 2021 and monthly changes from 2019 to 2021. The main conclusions are as follows: (1) The changes to lakes in different climatic regions are different: lakes in the monsoon-dominated region showed a significant trend of expansion from 2000 to 2014, but the trend slowed down and stabilized after 2014; lakes in the westerlies-dominated region showed a small expansion trend; lakes in the region affected by both westerlies and the monsoon showed an overall shrinking trend. (2) The monthly variation of lake water volume showed a periodical trend of first increasing and then decreasing, with the largest relative change of lake water volume in August and September. (3) Temperature and precipitation are dominant meteorological elements affecting the variation of lakes, and with the warming of the TP, temperature plays an increasingly important role. Combining observational data and remote sensing data, the study of mesoscale lakes changes can increase the understanding of relationship between lake change and climate change, provide help for further study of lake - atmosphere interaction and climate effect and climate change in the TP.Key words: Tibetan Plateau; mesoscale lakes; change of lake water volume; multisource altimetry data; in-situ observation; climate zones
UNITE: A toolbox for unified diagnostic evaluation of physics-based, data-driven and hybrid models based on information theory
Authors: Álvarez Chaves Manuel , Guthke Anneli , Ehret Uwe , Gupta Hoshin
Published: February 2023

The use of “hybrid” models that combine elements from physics-based and data-driven modelling approaches has grown in popularity and acceptance in recent years, but these models also present a number of challenges that must be addressed in order to ensure their effectiveness and reliability. In this project, we propose a toolbox of methods based on information theory as a step towards a unified framework for the diagnostic evaluation of “hybrid" models. Information theory provides a set of mathematical tools that can be used to study input data, model architecture and predictions, which can be helpful in understanding the performance and limitations of “hybrid” models.Through a comprehensive case study of rainfall-runoff hydrological modelling, we show how a very simple physics-based model can be coupled in different ways with neural networks to develop “hybrid” models. The proposed toolbox is then applied to these “hybrid” models to extract insights which guide towards model improvement and refinement. Diagnostic scores based on the entropy (H) of individual predictions and the Kullback-Leibler divergence (KLD) between predictions and observations are introduced. Mutual information (I) is also used as a more all-encompassing metric which informs on the aleatory and epistemic uncertainties of a particular model. In order to address the challenge of calculating quantities from information theory on continuous variables (such as streamflow), the toolbox takes advantage of different estimators of differential entropy, namely: binning, kernel density estimation (KDE) and k-nearest neighbors (k-NN).
Simulating the field-scale potential of natural variation in soybean leaf optical properties on carbon assimilation and water use
Authors: Drewry Darren
Published: February 2023

Agricultural lands provide a near-term opportunity to address climate change, food, and water security challenges. Addressing these complex challenges will require the integration of empirical data on the natural variation of vegetation traits with computational approaches that can integrate this empirical information toward an understanding of canopy-scale impacts. The relationships between leaf chlorophyll content, leaf optical properties, and biochemical photosynthetic capacity were measured in a collection of soybean (Glycine max) accessions showing large variations in leaf chlorophyll content (Chl). These relationships were integrated into a biophysical model of canopy-scale photosynthesis to simulate the within-canopy light environment, carbon dioxide assimilation and water use. Simulations were conducted for each accession to identify possible opportunities for improving canopy photosynthesis through foliar chlorophyll modification. These simulations demonstrate that canopy photosynthesis may not increase as Chl is reduced due to increases in leaf reflectance and nonoptimal distribution of canopy nitrogen. However, similar rates of canopy photosynthesis can be maintained with a 9% savings in leaf nitrogen resulting from decreased Chl. Additionally, analysis of these simulations indicates that the inability of Chl reductions to increase photosynthesis arises primarily from the connection between Chl and leaf reflectance and secondarily from the mismatch between the vertical distribution of leaf nitrogen and the light absorption profile. These simulations motivated the use of numerical optimization to quantify the extent to which low Chl mutations can be used to improve canopy performance by adapting the distribution of the “saved” nitrogen within the canopy to take greater advantage of the more deeply penetrating light. We conclude with a discussion of the impact of the re-distribution of nitrogen vertically through the canopy to improve photosynthesis and canopy water use.
Comparison of coverage obtained by land use classification using landsat and RapidEye. Case study: Tenosique, Tabasco, Mexico.
Authors: Nieto Jacob , Ramírez Serrato Nelly Lucero , Jácome Paz Mariana Patricia , Ruiz Santos Tania Ximena
Published: February 2023

Land use classification studies help to quantify the changes in forest cover that may occur at a given site over time. This quantification helps us understand the effect of the natural and anthropogenic processes over the study site. Activities such as agriculture, cattle ranching and illegal logging, which in turn are related to the evolution of the site's public policies, can be evaluated through classification studies. Tenosique area, in the southeast of Mexico, is a clear example of the consequences of these programs, being largely benefited by economic consent for agriculture and more for cattle ranching, and, suffering,  in 1974, a complete  turn in productivity activities because it was given full support in exploration and obtainment of hydrocarbons. This led to a crisis that left the area devastated and later became a protected area in 2008, which resulted in illegal logging, and land use for agriculture within the tropical forest, among others. With remote sensing, the task of quantifying the effect of public policies has become increasingly influential and many studies are being carried out to evaluate the current state of Tenosique. However, the results are known to depend directly on the images and methodologies used for this task.Because of this, this project, proposes, in a practical exercise, to determine how much these results may vary with respect to the images used as input for the supervised classification, and if this variation is significant enough to establish rules of operation on methodologies and determine ranges of the parameters of the images to perform a better land use classification. The aim of this project is to determine the margin of variability in the classification result over a given study area, using images from different satellite platforms, Landsat and RapidEye, together with the analysis of the properties of each image, when acquired by the satellite. In addition, the degree of affectation in the image by meteorological changes such as tropical haze in the source image and its respective corrected image was evaluated. The main results are:  individualization of complications and advantages derived from the resolution of the images, identification of the main steps for the possible corrections that can be needed for the images, advantages that are used for analyzing the metadata before doing some process to the images and finally, presenting a decision tree based on this information. It is important to emphasize that this study allows us to delimit the scope and limitations of the land use classifications made in the study area. Acknowledgments: Tania Ximena for the Planet images and Humberto Abaffy-Castillo, Ulises Gracía-Martínez and Mario Seinos-Jiménez for technical help in the project.
Use of Scaling to Describe Temporal Variability of Soil Hydraulic Properties
Authors: Kumar Saurabh , Ojha Richa
Published: February 2023

Soil hydraulic properties exhibit spatio-temporal variability and are affected by both natural and human factors. Their knowledge is essential for assessing soil water regimes. Scaling methods based on similar media concept have been widely used to model the surface spatial and temporal variation of vadose zone processes while assuming that similarity conditions are preserved. Soil heterogeneity, changes in field conditions due to rainfall or irrigation and other factors lead to changes in boundary conditions which makes analysis based on similitude analyses or functional normalization difficult. However, inspectional analysis method can reduce known physical laws along with corresponding initial or boundary conditions to non-dimensional form while eliminating as many physical constants and variables as possible which is then used to obtain scale factors and similarity requirements. The objective of this study is to obtain scaling factors based on inspectional analysis to describe the temporal variability of soil hydraulic properties.