bluuebunny/crossref_metadata_2025 huggingface dataset:
Differences in the superficial storage of organic carbon in soils from different olive orchard cultivation systems and ecosystem service implications (Sierras Subbéticas Natural Park, southern Spain).
Authors: Martinez-Murillo Juan F. , Menjíbar-Romero Mario
Published: February 2023

According to Pereira et al. (2018) soils provide and regulate many ecosystem services and play an important role in sustaining humanity. The benefits we receive from soils are directly or indirectly linked to clean air and water and food production, among others. The type, quantity or quality of soil ecosystem services depends on the specific environmental characteristics that will determine soil properties and functions. The valuation of soil ecosystem services depends on natural features and management type. Non-sustainable practices induce soil degradation/devaluation and many disservices, while sustainable practices can maintain and improve soil ecosystem services. Overall, soil ecosystem services quality and quantity over the long-term will depend on how sustainably we manage our land. 

In this study, the aim is the assessment of differences between the carbon storage in soils from different olive orchard cultivation systems for a preliminary evaluation of this regulating soil ecosystem service. To do this, we selected four different olive orchard cultivation systems: traditional (no sustainable practices), intensive (no sustainable practices and irrigation), ecological (sustainable practices: no chemical amendments, no tillage, and grass cover), and abandoned (abandoned at least 60-70 years ago and recolonised with shrubs). Soils were sampled following a longitudinal transect from the bottom of the cultivated/abandoned hillslopes to the top: every 10 m disturbed and undisturbed samples were taken in the upper 0-10 cm of soil profile. Once the soil samples were dried in laboratory conditions and sieved to 2 mm, the bulk density and organic carbon content were determined as follows: I) bulk density by the core method (Blake and Hartge, 1986); ii) organic carbon content with the application of the 1.74 factor to the organic matter content obtained by means of calcination. Both parameters let calculate the carbon storage (Ruiz-Sinoga and Romero-Díaz, 2010).   

References: 

Blake, G.R., Hartge, K.H. 1986. Bulk density, In: Klute, A. (Ed.), Methods of Soil Analysis, Part 1, Physical and Mineralogical Methods, 2nd Ed. Agronomy Monograph, 9. American Society of Agronomy and Soil Science, Madison, W, pp. 363–375. 

Pereira, P., Bogunovic, I., Muñoz-Rojas, M., Brevik, E.C. 2018. Soil ecosystem services, sustainability, valuation and management. Current Opinion in Environmental Science & Health, 5:7–13. 

Ruiz-Sinoga, J.D, Romero-Díaz, A. 2010. Soil degradation factors along a Mediterranean pluviometric gradient in Southern Spain. Geomorphology, 118:359–368. 
Investigating zonal asymmetry in stratospheric ozone trends at northern high latitudes using satellite limb observations and CTM simulations
Authors: Arosio Carlo , Chipperfield Martyn P. , Rozanov Alexei , Weber Mark , Dhomse Sandip , Feng Wuhu , Burrows John P.
Published: February 2023

Observations in limb geometry from satellite platforms are very valuable for monitoring the stratospheric ozone layer on a global scale, as they provide information with high spatial and temporal coverage and good vertical resolution. At the University of Bremen, ozone profiles were retrieved from observations from two limb sounders, SCIAMACHY (2002-2012) and OMPS-LP (2012-present), using similar retrieval algorithm setups. These two data sets were merged to obtain a consistent time series of longitudinally resolved global ozone distribution, referred to below as SCIA+OMPS. Recently, the OMPS-LP data set has been re-processed by using improved L1 data produced by the NASA team, with the main aim to mitigate the long-term drift affecting the OMPS-LP time series. The results of this re-processing will be presented; the use of the updated data set gives more confidence in the trend studies from the SCIA+OMPS time series.The overarching aim of this study is the investigation of vertically consistent patterns in the longitude-resolved trends, particularly at northern mid- and high-latitudes above 30 km altitude, detected in the SCIA+OMPS data set. Large positive trends are found over the Atlantic sector, whereas close-to-zero changes are detected over the Siberian/Pacific sector. To investigate the origin of this behaviour, we performed full chemistry simulations of the TOMCAT global 3-D chemistry transport model (CTM), forced by ERA5 reanalysis, for the 2003-2020 period. We then applied a multi-linear regression model including dynamical proxies to both the satellite observations and TOMCAT simulations. First, we compare the trend resulting from the merged data set with those from the model simulations to check the consistency of the detected zonal and longitudinally resolved patterns. Then, seasonally and monthly resolved trends are studied as they provide valuable insight into the observed zonal asymmetry of the trends. We find the largest variability with longitude occurring in winter- and springtime, and a good consistency between observations and the CTM.By comparing ozone changes, with trends in temperature and meridional wind fields from ERA5, we investigated potential mechanisms driving the observed asymmetry. Dedicated TOMCAT simulations showed the negligible role of photochemical processes for the observed pattern. We therefore consider the behaviour to be mainly dynamically driven. A composite analysis supports the hypothesis that the long-term change in the position of the polar vortex has influenced the winter- and springtime ozone concentrations and has led to the zonal asymmetry identified in the data and model.
Imagery and Terrain Data Fusion with the Flood Inundation Surface Topology (FIST) Model
Authors: Dobbs Kevin , Phillips James
Published: February 2023

Satellite imagery provides a unique reference for estimating flood inundation extent that can help characterize flood magnitudes and impacts in support of scientific studies and for operational disaster response. All imagery modalities (multispectral/hyperspectral, panchromatic, synthetic aperture radar (SAR)) suffer from factors that confound accurate spatial representation of flood extent, whether using traditional image classification methods or machine learning-based approaches. Clouds, cloud shadows, tree canopy, tall vegetation, and other factors either obscure the water surface or confuse the classifiers. These can yield results that vary widely when compared to actual flood extents, whether referencing observed data like high-water marks or high-quality hydrodynamic models. In addition, opportunities for imagery collection often do not coincide with maximum flood extent due to satellite access windows, cloud cover impacting optical sensors, or a combination of both. That said, the proliferation of existing and planned commercial and civil sensors across all modalities presents increasing opportunities for timely collection.In recent years, the quality of terrain data at regional, country, continental, and global scales has continued to rapidly improve. The data include WorldDEM, NASADEM, MERIT DEM, EarthDEM, among others, and many regional to country-scale lidar-derived datasets. The availability of this high-quality data allows for new methods that integrate terrain data with remotely sensed imagery data, to yield accurate and timely representations of flood extent in new ways to support both scientific investigations and disaster response.However, few methods have been developed that integrate satellite and/or aerial imagery data with terrain data to improve imagery-derived flood products. This paper will present new methods, based on the novel Flood Inundation Surface Topology (FIST) Model, for integration of terrain data with the limited data derived from imagery to provide a more accurate representation of maximum flood extents that overcomes many of the aforementioned limitations of using imagery alone. In addition, The FIST model also produces flood depth grids at the resolution of the native terrain data, which represents a major advance in imagery-derived flood products. We present the fundamental directed graph algorithm that is unique to the FIST model; the data architectures that support a range of applications; and case studies for the use of active flood and post-peak flood imagery to generate inundation extents and depth grids for peak-flood conditions.
Process-based water balance modelling with explicit ice-flow dynamics and multi-data set calibration: the WaSiM-OGGM coupling scheme
Authors: Pesci María Herminia , Förster Kristian
Published: February 2023

The water balance of high-alpine glacierized catchments is largely dominated by snow and ice processes. When modelling the hydrological response of such catchments, a reliable representation of snow/ice accumulation and melt should be ensured, especially when studying the effects of climate change. Even though numerous state-of-the-art hydrological models are able to adequately represent the contribution of snow melt into the total runoff with the use of complex approaches (e.g. energy balance models), glacier dynamics are still based on conceptual or empirical methods, which exhibit some limitations compared to more sophisticated models (e.g. explicit ice-flow dynamics).The Water Flow and Balance Simulation Model (WaSiM) is a process-based hydrological model that includes an empirical volume-area scaling approach for describing the glacier’s evolution. Although acceptable estimates can be obtained with this approach, an integration to a more complex glacier representation is still missing. For this reason, a coupling scheme between WaSiM and the Open Global Glacier Model (OGGM) is developed, hence accounting for explicit ice-flow dynamics.The workflow consists mainly on three steps: i) a first WaSiM run to obtain monthly values of temperature and precipitation that serve as input for the ii) second step, which is running OGGM. Finally, iii) a dynamic model run of WaSiM with the updated output from OGGM (annual glacier outlines and ice thickness) is performed. Within this last step, the glacier’s volume internally calculated by WaSiM (i.e. with the VA-scaling approach) is replaced by OGGM’s output, while performing a simultaneous multi-data set automatic calibration. In this calibration, only WaSiM parameters are adjusted and simulation results are compared against glacier mass balances (OGGM) and observed runoff. The performance of the calibration is then evaluated in terms of a weighted multi-objective function. Although the best fit between observed and simulated runoff is achieved when considering only runoff observations (single-data calibration), glacier components are better represented when calibrating the coupled model with the multi-data set (i.e. also including glacier mass balances). Therefore, a trade-off is made between general model performance and accurate runoff prediction. This coupling scheme is aimed for hydrological modellers with no additional expertise on glacier modelling, since OGGM is set up according to its default parameters. Finally, it could serve as a tool not only to predict the hydrological response of any glacierized catchment (even without any available glacier data), but also to make predictions under future climate projections with a more reliable representation of glaciers. 
The Search-Coil Magnetometer (SCM) of the Radio and Plasma Waves Investigation (RPWI) onboard the ESA JUICE mission
Authors: Retinò Alessandro , Mansour Malik , Canu Patrick , Chust Thomas , Hadid Lina , Le Contel Olivier , Sahraoui Fouad , Zouganelis Ioannis , Alison Dominique , Ba Nadjirou , Jeandet Alexis , Mehrez Fatima , Mirioni Laurent , Piberne Rodrigue , Berthod Christophe , Geyskens Nicolas , Sou Gerard , Cecconi Baptiste , Bergman Jan , Wahlund Jan-Erik
Published: February 2023

The JUpiter ICy moons Explorer (JUICE) mission is the first large-class (L1) mission of ESA Cosmic Vision. JUICE will be launched in April 2023 with an arrival at Jupiter in 2031 and at least four years making detailed observations of Jupiter’s magnetosphere and of three of its largest moons (Ganymede, Callisto and Europa). The Radio and Plasma Wave Investigation (RPWI) consortium will carry the most advanced set of electric and magnetic fields sensors ever flown in Jupiter’s magnetosphere, which will allow to characterize the radio emission and plasma wave environment of Jupiter and its icy moons. Here we present the scientific objectives and the technical features of the Search Coil Magnetometer (SCM) of RPWI. SCM will provide for the first time three-dimensional measurements of magnetic field fluctuations in the frequency range 0.1 Hz – 20 kHz within Jupiter’s magnetosphere. High sensitivity (~10 fT / √Hz at 1 kHz) will be assured by combining an optimized (20 cm long) magnetic transducer with a low-noise (4 nV / √Hz) ASIC pre-amplifier. Perturbations by the spacecraft are strongly reduced by accommodating SCM at about 10 m away from the spacecraft on the JUICE magnetometer boom. The combination of high sensitivity and high cleanliness of SCM measurements will allow unpreceded studies of electromagnetic fluctuations down to plasma kinetic scales, in particular in key regions such as the magnetopause, the auroral region and the magnetotail current sheet of Ganymede’s own magnetosphere which JUICE will orbit for many months. This will lead to important advances in understanding how fundamental plasma processes such as magnetic reconnection, turbulence and particle energization occur in Jupiter’s plasma environment.
Validation of a 2D modelling approach for urban microclimatic conditions
Authors: König Albert , Pichler Markus , Muschalla Dirk
Published: February 2023

The mitigation of urban microclimatic deficiencies as a result of the urbanized environment receives increasing attention by cities, municipalities and the planning community. Priority areas for the implementation of multi-beneficial climate change adaptation measures and the development of mitigation plans need to be identified. Therefore modelling methods producing good results while only requiring moderate data input and computational effort are needed for the widespread application in planning processes. In this study, we test the rapid fine-scale methodology for simulating urban bioclimatic conditions in a 2D environment that was previously introduced by Back et al. (Back et al., 2021). The original methodology uses high resolution land cover classification (Hiscock et al., 2021) from multi-spectral aerial imagery, digital elevation data, and a vector layer of buildings to calculate land surface temperature (LST), mean radiant temperature (MRT), and the Universal Thermal Climate Index (UTCI). We apply this methodology to the rural municipality of Feldbach, Austria, using commercially and openly available satellite imagery. The simulated data is validated against the publicly available monitoring data from the WegenerNet climate station networks (Fuchsberger et al., 2022), which provides high spatial and temporal resolution measurements. The results are evaluated regarding the agreement of relative spatial differences of the simulated variables with the observed data. To be suitable for the identification of priority areas for the implementation of climate change adaptation measures, the methodology is expected to accurately reflect the spatial variability of the simulated variables.Project supported by ESA Network of Resources Initiative.Back, Y., Bach, P. M., Jasper-Tönnies, A., Rauch, W., & Kleidorfer, M. (2021). A rapid fine-scale approach to modelling urban bioclimatic conditions. Science of The Total Environment, 756, 143732. https://doi.org/10.1016/j.scitotenv.2020.143732Fuchsberger, J., Kirchengast, G., Bichler, C., Leuprecht, A., & Kabas, T. (2022). WegenerNet climate station network Level 2 data [Text/csv,application/x-netcdf]. Wegener Center for Climate and Global Change, University of Graz. https://doi.org/10.25364/WEGC/WPS7.1:2022.1Hiscock, O. H., Back, Y., Kleidorfer, M., & Urich, C. (2021). A GIS-based Land Cover Classification Approach Suitable for Fine‐scale Urban Water Management. Water Resources Management, 35(4), 1339–1352. https://doi.org/10.1007/s11269-021-02790-x
Pesticide transformation product occurrences in surface waters as ground water pollution risk indicators in the context of an extended residence time aquifer
Authors: Gallé Tom , Bayerle Michael , Pittois Denis , Huck Viola , Farlin Julien
Published: February 2023

Luxembourgish groundwater aquifers have recently been impacted by high concentrations of several pesticide transformation products (TP) that led to regulatory issues for about 1/3 of the drinking water supplies (Luxembourg considers all transformation products to be relevant and applies the 100 ng/L legal threshold). The consequent application restrictions or complete bans of certain pesticides triggered switches in compound uses in several cultures. A leaching risk analysis had been conducted to orient agricultural counselling on the least impacting parent compounds and transformation products. However, since the leaching simulations relied on literature environmental property data of the pesticides (like fraction of TP generated), there was some uncertainty on the true impact of the identified TPs. Residence times of groundwaters in the main aquifer spanning on average between 10 and 20 years (with proportional recovery times once these waters are contaminated), a faster validation approach was needed. The hypothesis was established that the interflow component in surface waters would be a good indicator to estimate the amount of transformation products available for groundwater leaching. In that perspective passive sampling campaigns were established on four river basins of distinct hydrogeology to quantify the masses of parent compounds and transformation products transported during an entire year and supported by grab sampling in the descending limbs of seasonal flood waves. Additional parameters included conductivity, DOC, Abs280 and macro-anions. All the predicted transformation products were identified and their occurrence varied in amount and timing in the different catchments according to their application, metabolization in soils and hydrogeological setting. This contribution discusses the influences of spatial use variability and hydrological connectivity of agricultural source plots to the magnitude of the occurrences as well as its potential link to the leaching modelling and its parametrization.
Improved flush detection and classification in combined sewer monitoring
Authors: Pichler Markus , Muschalla Dirk
Published: February 2023

During rain events, rainwater reaches the combined sewer system and causes additional hydraulic and pollutant load. Due to the limited capacity of the sewer system and the wastewater treatment plant, overflow structures are constructed to reduce the discharge and thus create a potential hazard for the environment. For optimal management of these structures, it is necessary to know the runoff and pollutant load of the events and their distribution over time. When these distributions have a significant peak, they are often referred to as a flush, the best-known phenomenon being the first flush at the beginning of a rainfall event. This knowledge can be used for the design of retention facilities and the calibration of sewer models. The flush phenomena are mainly caused by the erosion of contaminants on the surface as well as the remobilisation of sediments in the sewer network.Although many papers have investigated the first flush, no common pattern for the occurrence of these flushes has been identified. While the concentration of the flushes in rainwater sewers can be measured directly, the rain flushes in combined sewers are mixed with more polluted wastewater, which leads to a reduction in signal strength.The sensor site for the used measurement data is located in a combined sewer overflow in the western part of Graz, Austria with a catchment area of 460 ha, consisting mainly of residential areas and with about 19500 inhabitants.This work aims to separate and classify pollution flush signals from rainfall events in combined sewer systems to better understand the relationship between these signals and rainfall event characteristics.For this reason, the continuous hydraulic and pollution data are first analysed to determine the representative dry weather contribution. By subtracting the dry weather contribution from the combined wastewater volume and the mass flux, the stormwater contribution and thus the flushes can be estimated. In addition, automatic event detection of combined sewer events was done.Next, the wet weather events are classified by clustering the stormwater runoff-induced pollutant distribution (flush signals) and the event parameters. For the clustering of the temporal pollutant load distribution of events of different duration, the events are normalised by the mass-volume curves. To obtain the best possible clustering result, the dimension of the mass-volume curves is reduced by a principal component analysis. Different clustering methods, such as partitioning or hierarchical methods, are applied and compared.
Cloud native OpenScienceLabs for HPC : Easing the road to FAIR collaboration and OpenSource
Authors: Roedig Constanze , Sorathia Kareem
Published: February 2023

We present a method for publishing high performance compute (HPC) code and results in a scalable, portable and ready-to-use interactive environment in order to enable sharing, collaborating, peer-reviewing and teaching. We show how we utilize cloud native elements such as kubernetes, containerization, automation and webshells to achieve this and demonstrate such an OpenScienceLab for the MAGE (Multiscale Atmosphere Geospace Environment) model, being developed by the recently selected NASA DRIVE Center for Geospace Storms. We argue that a key factor in the successful design of such an environment is its (cyber)-security, as  these labs require non-trivial compute resources open to a vast audience. Benefits as well as implied costs of different hosting options are discussed, comparing public cloud, hybrid, private cloud and even large desktops.We encourage HPC centers to test our method using our fully open source blueprints. We hope to thus unburden the research staff and scientists to follow FAIR principles and support open source goals without needing a deep knowledge of cloud computing.
Flank collapse and magma dynamics interactions on stratovolcanoes: InSAR and GNSS observations at Mt. Etna (Italy)
Authors: Pezzo Giuseppe , Palano Mimmo , Beccaro Lisa , Tolomei Cristiano , Albano Matteo , Atzori Simone , Chiarabba Claudio
Published: February 2023

Spatial-temporal ground deformation patterns of volcanoes is one of the major and more impressive observations of the volcanic dynamic. Cause of his numerous volcanic, seismic, and gravitational phenomena, Mt. Etna is one of the more studied volcanoes worldwide. We processed and analyzed GNSS and InSAR dataset from January 2015 - March 2021 period. In addition to inflation and deflation displacement pattern, we observe a spectacular velocity modulation of the superfast seaward motion of the eastern flank. Rare flank motion reversal indicates that short-term contraction of the volcano occasionally overcomes the gravity-controlled sliding of the eastern flank. On the other hand, fast dike intrusion guided the acceleration of the sliding flank, potentially evolving into sudden collapses, fault creep, and seismic release. These observations can be of relevance for addressing short term scenarios and forecasting of the quantity of magma accumulating within the plumbing system.
A modelling framework to assess urban flood risk on the city scale
Authors: Reinstaller Stefan , König Albert , Muschalla Dirk
Published: February 2023

A city-wide approach to reduce the uncertainty regarding the spatial variability of urban flooding events is required in urban catchments. The goal of this study is the development of a modelling framework independent of the spatial scale to address the most hazardous areas in the current state and the future. The framework starts with the definition of the study objectives (e.g. reducing flood risk), which have a direct impact on the spatial and temporal scale, the used model approach, the data requirement and the level of detail. Furthermore, potentially hazardous areas will be identified with the potential flood risk index (PFRIi). The determination of this is a risk-based approach (R=E*V*H) which combines the exposition (E) with the vulnerability (V) and the hazard (H). The population density of each object and the total number of persons in the catchment will quantify the exposition. The vulnerability includes the number of past damage events and the object use. How accurate the modelled hazard is considered, depends on the used model approach: i) GIS-based; ii) only 1D; iii) only 2D; iv) 1D/2D models. The combination of H and V resulted in the risk factor (RFi) in four levels of detail depending on the used model approach. This allows both, the quantification of hazardous areas at the current state and the change of the PFRIi by future scenarios such as climate change and urbanization.PFRIi = nP,k * RFi / (Ak * ∑P)                                                                                                                                                                                     PFRIi=Potential Flood Risk Index; nP,k= number of Persons on a private ground k; Ak=total object area; =total number of persons in the catchment; Rfi= risk factor depending on the used model approach kThe GIS-based flow path analysis as the first level of detail can be used to identify the urban flooding hot spots. This allows the identification of hazardous sub-catchments in a city or high-risk private ground in a catchment quantified by the PFRIGIS. This is useful for further detailed analysis with other model approaches (e.g. 1D/2D model). The next steps are the implementation of the demonstrated framework for each level of detail in the city of Graz in Austria. Furthermore, the framework will integrate different climate scenarios based on a high-resolution climate model to address the impact of climate change on the urban drainage system quantified by the PFRIi.Keywords: urban flooding, urban flood modelling, risk assessment, future changes
New Interpretations of the Deep Structure of the Alps based on 3D Anisotropy
Authors: Pondrelli Silvia , Confal Judith M. , Baccheschi Paola
Published: February 2023

In a recent study, a large amount of splitting intensity measurements of the seismic anisotropy for the Central Mediterranean region has been made available, to retrieve an anisotropy tomography (see Baccheschi et al. and Confal et al. posters of session GD7.1). Here we focus on the images obtained for the Alpine region, that strongly benefit of AlpArray and Cifalps1 and 2 data. The 3-D distribution of seismic anisotropy, from 70 to 300 km of depth, has been compared with previous SKS shear wave splitting measurements and has been interpreted taking into account remnant and active pieces of slabs. Most of previously defined mantle flows are confirmed, as the asthenospheric toroidal flow around the tip of the slab beneath the Western Alps. Shallower anisotropy pattern show strong relation with main tectonic structures, from the Rhine Graben to the Western Alps arc and so on. However, the no uniqueness of available seismic velocity anomalies mapping keep some part of the interpretation open, as for instance the detectability of proper slab anisotropy. Out of the directional patterns, this splitting intensity tomography gives a map of anisotropy intensity and its variations with depth, with some strong heterogeneities corresponding to regions where previous seismic anisotropy studies described the presence of complex structure, as for the upper mantle beneath the Eastern Alps. All these new information, if integrated with the most recent studies for the Alpine region, may be a relevant support to innovative hypotheses on crust-to-mantle Alpine transition and structure.
Generation of an improved land surface temperature time series to support permafrost modelling in the northern high latitudes
Authors: Dupuis Sonia , Göttsche Frank-Michael , Wunderle Stefan
Published: February 2023

Northern high latitudes have experienced pronounced warming throughout the last decades with particularly high temperatures during winter and spring. Due to Arctic Amplification, the Arctic region is warming thrice as fast as anywhere else. The warming affects the sensible ecosystem, vegetation dynamics and the cryosphere (sea ice, snow and permafrost). Permafrost, which is a crucial component of arctic ecosystems, is particularly sensitive to increasing air temperatures and changes in the snow regime. Climate change has a high impact in these regions because thawing affects the stability of the bedrock, damages infrastructures and releases massive quantities of organic carbon. Permafrost cannot directly be observed from space, but permafrost models link physical surface variables such as land surface temperature (LST) to the thermal ground regime. Models are an important addition to boreholes to monitor the status of the permafrost at hemispheric scale. On a global scale, observation of LST is only available from very few in-situ stations or climate models with coarse spatial resolution. Both data sources are not sufficient to model fine-scaled features. In contrast, LST information retrieved from satellite data has high spatiotemporal coverage.To compute LST on a hemispheric scale, we use the Advanced Very High Resolution Radiometer (AVHRR) Global Area Coverage (GAC) data set starting in 1981. The AVHRR on board the NOAA and MetOp satellite series now covers more than four decades. AVHRR’s two thermal infrared channels allow applying the split-window (SW) method to reduce the atmospheric effect and retrieve LST. Split-window algorithms (SWA) performances depend on the quality of SW coefficients. These are empirical coefficients, which are retrieved by fitting the SWA to a calibration database. Here, the calibration data is generated by running a radiative transfer (RT) model. The input profiles of the RT are selected to cover typical atmospheric conditions occurring in permafrost regions. The coefficients are adjusted for different water vapour and satellite viewing conditions. Cloud and water masks as well as fractional snow cover information from the ESA CCI snow project and emissivity data are included in the final LST retrieval algorithm. Besides, a machine learning algorithm was applied to improve the spatial resolution of the GAC data to generate a 40-year time series with a spatial resolution of 1km. The first validation results of the LST time series are shown.
Nightlights as a tool to study flood exposure and vulnerability for the 2022 Indus River flood.
Authors: Aggarwal Ekta , Gupta Sanjeev , Whittaker Alexander C.
Published: February 2023

Flooding is one of the most devastating of natural disasters, occurring at varying spatial scales and leading to human and resource loss. Where the extent of flooding is large, satellite-derived data such as the NASA-derived DMSP, VIIRS, or the Black Marble nightlights data provide a useful approach for flood extent, flood exposure, and vulnerability. The recent floods in August 2022 on the Indus River, Pakistan is an example of a high-magnitude flood event. According to Pakistan’s National Disaster Management Authority (NDMA), around 33 million people were affected by the floods, and 8 million people were displaced.To quantify exposure to flooding, we explore the use of nightlight data in determining flood vulnerability and human impact. We first associated lit pixels of the NASA DMSP nightlights data with channel pattern type and the proximity to the river in the Indus basin to provide an understanding of the influence of landscape parameters on human presence. Based on the hypothesis of preferential human presence near the river of the basin, we show that nightlight distribution is enhanced by 26% within the 0 to 5 km proximity of the river relative to the basin as a whole. This finding shows how human presence is concentrated in close proximity to the Indus River and its key tributaries.To quantify the impact of the August 2022 floods we use NASA’s monthly and daily Black Marble night light data. We compare published flood extents with spatial and temporal variations in nightlights over similar areas to examine the impact of flooding on human presence. We use this to quantify the impact of the floods as measured in terms of the percentage of affected or reduced nightlight pixels and to estimate differential recovery time periods of the floodplain versus the non-floodplain area of the Indus river. The results will be compared with the population and demographics statistics of the area to provide information about flood exposure and vulnerability of different socio-economic groups within the flood plains. Our findings have the potential to aid improvement in our understanding of flood risk assessment and vulnerability and provide a framework for policymakers to assess flood vulnerability and impact at a basin scale.
Fine scale frontal structure and biological response in an ring-eddy dipole in the Mozambique Channel
Authors: Penven Pierrick , Ternon Jean-Francois , Noyon Margaux , Herbette Steven
Published: February 2023

Located in the southwest Indian Ocean, between Madagascar and the African continent, the Mozambique Channel is a western boundary current system characterized by an intense eddy activity, increasing over the long term (Backeberg et al. 2012). Large anticyclonic rings reaching up to 300 to 350 km in diameter and 2000 m of vertical extension are structuring the marine ecosystems from phytoplankton to top predators (de Ruijter et al., 2002; Ternon et al., 2014, Weimerskirch et al., 2004). They impact the environmental conditions on the Mozambican shelves by promoting the upwelling of rich deeper waters (Lamont et al., 2010; Malauene et al, 2014). Coastal waters, generally rich in plankton and nutrients, can be also be transported offshore along the edges of the rings. The presence of an eddy dipole with the anticyclonic ring in the northern side of the cyclonic eddy can enhance the processes (Roberts et al., 2014). Theses eddy fluxes are supposed to be the dominant source of nutrients for the central Mozambique Channel (Jose et al., 2016). In the context of the RESILIENCE campaign in April-May 2022, we recently observed at fine scale the frontal system of a filament between a Mozambique Channel Ring and a cyclonic eddy in the central Mozambique Channel. Here we present the mean structure, the fine scale processes and the biological evolution. This underlines the importance of mesoscale and sub-mesoscale ocean dynamics for the ecology of the Mozambique Channel and it's evolution.
Geophysical monitoring of the fresh-saline groundwater interface in Belgian polders
Authors: Blanchy Guillaume , Mehmandoostkotlar Ali , Everaert Bert , Huits Dominique , Garré Sarah , Hermans Thomas , Nguyen Frédéric
Published: February 2023

Polders are areas reclaimed on the sea thanks to hydraulic structures like dikes. To prevent flooding, these low-lying areas are constantly drained by a network of ditches that release excess water in the sea (e.g. at low tide). The use of subsurface drainage pipes connected to existing drainage ditches further enabled the drainage of the lands and made them suitable for agriculture. While the groundwater remains saline water from its seaborn nature, with years and precipitation, a fresh water lens, lighter than the deeper saline water, developed near the soil surface, on top of the saline water. This fresh water lens is essential for most conventional crops that would suffer from saline conditions. The thickness of freshwater lenses varies throughout the year as a function of the recharge from rainfall and evapotranspiration.However, intensive rainfall events and prolonged summer droughts are becoming more frequent with Climate Change and lead to decreasing freshwater lens thickness, endangering crop yield. Controlled drainage systems that enable to regulate the water level in the subsurface drains has the potential to mitigate this issue by imposing a temporary higher water level, hence increasing recharge of the freshwater lens. To better understand the dynamics of the fresh/saline water interface throughout the year, we equipped two fields with multilevel piezometers with both head and salinity sensors replicated three times in each field. Along each multilevel piezometer we also installed 1D resistivity sticks with 16 electrodes to obtain a vertical electrical resistivity profile. In addition, electromagnetic induction surveys enabled us to expand the local observations to the entire area (4 ha in total).The datasets collected in the two fields in the conventional scenario (i.e. without controlled drainage) during the first year, showcase the usual dynamics of the interface, its lateral as well as vertical variability. The use of geoelectrical techniques enable us to distinguish fresh and saline water boundaries and its variability per soil layers. The electromagnetic induction surveys reveal old paleochannels that influence the dynamics of the freshwater lens at the field-scale. Moreover, the dataset also demonstrates how different crops (grass and flax) lead to different ground water and salinization dynamics. In this work, we present our first year of collected field data and related interpretation before the installation of the controlled drainage system.
Variability of atmospheric CO2 in Earth System model large-ensemble simulations with an interactive carbon cycle
Authors: Johnson Kelli , Li Hongmei , Ilyina Tatiana
Published: February 2023

Atmospheric CO2 concentrations have increased from around 280 parts per million (ppm) in 1800 to over 416 ppm in 2020. This is a direct result of increasing anthropogenic emissions of CO2 since the industrial era. Nearly half of the emitted anthropogenic CO2 is taken up by the ocean and terrestrial ecosystems, while the remaining half remains in the atmosphere, where it is a heat-trapping greenhouse gas. The growth of atmospheric CO2 varies from year to year with inhomogeneous spatial distribution depending on the CO2 uptake by the ocean and land. The CO2 uptake by the natural sinks and atmospheric growth are affected by the climate variations and the long-term changes; in turn, the variations of the carbon cycle also modulate global climate change. The state-of-the-art large ensemble simulations based on Earth System Models (ESMs) prescribe the concentration of atmospheric CO2, but the missing interactive response of atmospheric CO2 changes to the CO2 fluxes into the ocean and the land hinders the investigation of the variability in atmospheric CO2. Furthermore, such simulations will be insufficient to represent the changes in the efficiency of the land and ocean carbon sinks once emissions start to decline. Based on the low-resolution version of the Max Planck Earth System Model v1.2 (MPI-ESM-1.2-LR), we have done a novel set of 30-member ensemble simulations driven by anthropogenic CO2 emissions. In such simulations, atmospheric CO2 concentrations are computed prognostically, modulated by the strength of CO2 fluxes to the land and the ocean. While general trends in atmospheric CO2 concentrations for different Shared Socioeconomic Pathways (SSP) are well known, trends in its global dispersion and variations within the seasons of each year have not been investigated in ESMs with an interactive carbon cycle. In this project, we use MPI-ESM-1.2-LR large ensemble simulations under four SSP scenarios, i.e., SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5, together with historical runs to analyze changes of atmospheric CO2 concentrations. We focus on seasonal variability and spatial distribution of atmospheric CO2 changes in the presence of internal climate variability. We address two questions: first, what is the temporal evolution of atmospheric CO2 in regard to its seasonal variability by the end of the century following different emission pathways; and second, how does atmospheric CO2 evolve spatially (horizontally across the globe and vertically into the stratosphere) in the historical period and future projections until 2100? This study aims to refine our understanding of the spatial and temporal variations of CO2 in support of activities to monitor and verify decarbonization measures.
Sustainable Management of Coastal Aquifers subject to Seawater Intrusion using Reduced-Order Groundwater Flow Models
Authors: Geranmehr Mohammadali , Baù Domenico , Mayer Alex S. , Mancewicz Lauren , Yu Weijiang
Published: February 2023

The simulation of seawater intrusion (SWI) in coastal aquifers under complex hydrogeological conditions typically requires using "variable-density" models, which simulate the groundwater flow and the transport of salt dissolved in water. When combined with optimization algorithms, variable-density models constitute powerful tools to support the management of groundwater resources in coastal systems vulnerable to SWI, sea-level rise and unstainable groundwater abstraction. However, the application of simulation-optimization (SO) to SWI problems has so far been limited by the prohibitive computational effort required by full-scale variable-density models that simulate the aquifer response to proposed groundwater abstraction strategies. A viable solution is thus to develop “surrogate” models that emulate full-scale model responses at a fraction of their computational cost. In this study, a surrogate model of SEAWAT, a popular variable-density groundwater flow model, will be presented. This surrogate is based on the proper orthogonal decomposition (POD) method, which is a projection-based approach where the coefficient matrices and the right-hand side vectors derived through finite-difference discretization of the coupled flow and transport equations, are mapped onto a space of size significantly smaller than the model grid. Preliminary results show that the POD-based surrogate model is remarkably faster than the full-scale model, and provides results of comparable, and thus acceptable, accuracy. These features make the surrogate ideally suited for substituting the full-scale variable-density model within the SO framework adopted to support the management of coastal aquifers.
Detecting Forest Fires by Using Remotely Sensed Data in Riau, Indonesia
Authors: Agustiyara Agustiyara , Székely Balázs
Published: February 2023

This research aims to shed light on remote sensing data, focusing on remote sensing for forest fires which still largely separates these expertise techniques. In this situation, the use of sentinel data makes it possible to make assessments related to land and forest fires by assessing the land cover function of land fires. The first specific location shows that land fires are clearly visible, especially on the Rupat island which is part of Bengkalis Regency, Riau Province, Indonesia. In a general sense, Rupat Island is a small island with a peatland ecosystem. This becomes complex when various land functions and activities, such as the development of the oil palm plantation industry, protected forest areas, industrial plantation forest (HTI) company areas, peat land, and other land uses activities are found on this island. Forest fires cause extreme long-term damage to the environment, wildlife, flora, and property including forestry and agricultural holdings every year. Along with improving the detection of and response times to such fires, there is also a need to improve post-event delineation, assessment, and monitoring of the affected areas. Such post-event analysis can then feed back into strategies and policies for wildfire prevention, prediction, mitigation, and response. However, the detection of such fires by these tools considers the accuracy in terms of the exact location and extent of land classification and burnt areas. The use of statistically significant remote sensing, the research process two products between 2019 and 2020. The research use data equation through the Sentinel-3 data, where the detection of land fires that are clearly visible in the "fire detection" image by performing a data algorithm to ensure that the fire point is no cloud cover. Sentinel-2 data was also used to explain the loss of vegetation on peatlands in the area of land fires, which clearly shows changes in burnt areas. With the same combination of analyses, sentinel-1 data was also used to clarify the land cover in the fire area, where the classification algorithms (forest) and other functions in sentinel-1 data were identified. Therefore, the use of remote sensing primarily aims to highlight the importance of data fusion and integrate it into the multiple factors and motives for forest and land fires.
Response of atmospheric variability in the Northern Hemisphere winter to past climate conditions and elevated CO2 levels
Authors: Oldeman Arthur , Baatsen Michiel , von der Heydt Anna , van Delden Aarnout , Dijkstra Henk
Published: February 2023

A specific feature where future climate projections fail to see a consistent response to increasing CO2 levels is Northern Hemisphere winter atmospheric dynamics and variability. This holds specifically for the Northern Annular Mode (NAM) and its regional expression, the North Atlantic Oscillation (NAO). The lack of consensus in future projections is caused in part due to the large internal variations of these modes of atmospheric variability compared to the response to elevated CO2.The response of interannual and decadal climate variability to warm conditions can be isolated in climate simulations equilibrated at elevated CO2 concentrations. However, we cannot perform a future model-data comparison. Fortunately, we can turn to the past. The last time the Earth saw similar CO2 concentration as the present day was approximately 3 million years ago, in the mid-Pliocene epoch. The mid-Pliocene is often considered the ‘best analog’ to an equilibrated climate at present or near-future CO2 levels. However, can the mid-Pliocene be used to assess the response of Northern Hemisphere winter atmospheric variability, such as the NAO and NAM, to a warm climate?To answer this question, we have performed a set of sensitivity experiments using a global coupled climate model (CESM1.0.5). We have performed sensitivity studies using a pre-industrial and a mid-Pliocene geography, as well as two levels of radiative forcing (280 ppm and 560 ppm), as a part of intercomparison project PlioMIP2. Our mid-Pliocene simulations generally compare well to proxy reconstructions of sea-surface temperature.We consider the sea-level pressure (SLP) and zonal wind at 200 hPa using 200 years of January-mean data, and perform principal component analysis. In response to the mid-Pliocene boundary conditions (other than CO2), we find a large increase in the mean SLP along with a decreased variance over the North Pacific Ocean. This is accompanied with a weakened jet stream over the western North Pacific, as well as increased occurrence of a split jet condition over the eastern North Pacific. These findings are connected to a regime shift in the modes of atmospheric variability in the Northern Hemisphere, where the so-called North Pacific Oscillation (NPO) becomes the most dominant mode of variability. We do not see tendencies towards similar behavior in the CO2 doubling experiment indicating that the Pliocene boundary conditions are the main driver of the observed shifts in variability. This suggests that the mid-Pliocene is not a good analog for a warm future climate when considering Northern hemisphere winter atmospheric variability.