bluuebunny/crossref_metadata_2025 huggingface dataset:
How to reduce and manage the end-of-life of plastics and find an alternative to plastics?
Authors: Fatica Raffaella
Published: February 2023

ABSTRACT EGU 2023HOW TO REDUCE AND MANAGE THE END-OF-LIFE OF PLASTICS AND FIND AN ALTERNATIVE TO PLASTICS?Raffaella Fatica (raffaella.fatica@liceomamiani.cloud)Liceo statale "Terenzio Mamiani" (Rome, Italy)HOW TO REDUCE AND MANAGE PLASTIC END-OF-LIFE AND FIND AN ALTERNATIVE TO PLASTIC?This will be the incipit that will lead a 5th grade class, composed of 27 students, to acquire a series of knowledge related to plastic, the problem of pollution of the seas and oceans (objective 14 of the 2030 agenda) and the possibility of producing alternative and more sustainable materials such as bioplastics (objective 9 of the 2030 agenda). To develop this project, I intend to start with a series of questions that may arouse interest and curiosity in the students.1st question: "Where does the need to find an alternative to plastics come from?"We will start with plastic islands and analyse the degradation times of various types of materials, both plastic and others. This topic will conclude with a laboratory experiment that answers the question: "Can different plastics be recycled together?".2nd question: "What is the chemical nature of plastics?"This topic will include an introduction to the knowledge of polymers, starting with natural polymers such as carbohydrates, proteins and nucleic acids. We will focus on the proteins contained in milk. This topic will also conclude with a laboratory experience answering the question: "Is it possible to produce bioplastics?"3rd question: "Are we sure that bioplastics, such as those derived from maize, are easier to dispose of than traditional plastics?"Today, traditional plastics are joined by biodegradable and compostable plastics, but these are not necessarily easier to dispose of. To answer this question, we will start with the concepts of biodegradable and compostable and conclude with a laboratory experience that will show that even biodegradable plastics must be properly disposed of.The process that will lead to the end-of-life of plastics will still be a long one, but if everyone becomes aware of the problem, perhaps it will be easier to achieve the goal. 
Coastal groundwater pattern recognition supported by cluster analysis
Authors: Narvaez-Montoya Christian , Mahlknecht Jürgen , Torres-Martínez Juan Antonio , Mora Abraham , Bertrand Guillaume
Published: February 2023

In coastal zones, groundwater overexploitation reduces freshwater outflow to the sea and causes seawater to migrate toward fresh groundwater resources, increasing salinity in groundwater reservoirs. This seawater intrusion is among the world's leading causes of groundwater pollution, as salty water can affect safe drinking consumption, food production, and ecosystem services. To explore this and others contaminations sources, cluster analysis has been used for decades to aid in water resource pattern recognition in coastal aquifers around the world. This work shows how cluster analysis has been applied for seawater intrusion pattern recognition in coastal zonas around the world between 2000 and 2022 through a systematic review based on the PRISMA statement. After the searching and selection stages, it was carried out the bibliometric analysis of the 81 identified studies. Furthermore, it was discussed information about the number of samples, number of variables, redundant variables, sample density per area, sample density per variable, clustering principal features, limitations for sources differentiation, assembly between methods, software, and pre-processing strategies. The identified methods were hierarchical clustering analysis (HCA), K-means clustering, Fuzzy C-means, and self-organizing maps (SOM). While 56 studies applied Q-mode for grouping water samples with similar characteristics, 17 applied R-mode for grouping variables, and 8 applied both modes. The preferred method was HCA with Ward´s linkage and Euclidean distance, but many studies didn’t specify the linkage or the distance criteria.  Of those studies that applied Q-mode, 77% associated at least one cluster with the influence of seawater intrusion. On the other hand, this work shows that 58% of the reviewed studies did not report raw data, which presents issues for validation, replication, and socialization of the results. 
Urban heat load assessment in Zagreb, Croatia: a multi-scale analysis using mobile measurements and satellite imagery
Authors: Žgela Matej , Herceg Bulić Ivana
Published: February 2023

There is often a lack of meteorological stations in cities, which makes it difficult to examine their microclimate. Alternatively, it is possible to get around this by fixing measuring instruments on bicycles and traversing through the city to observe spatial patterns in the urban canopy layer. The "traverse" approach enables insight into the spatial variation of air temperature in relation to urban form.In this research, air temperature measurements were carried out using bicycles and an IoT MF-300 instrument with a synchronized GPS receiver and a temperature probe under different weather conditions throughout 2021 and 2022 in Zagreb, Croatia. The GPS receiver's high sensitivity and position accuracy allowed measurements in places like urban canyons and dense foliage environments. The routes were carefully designed to pass through morphologically diverse parts of Zagreb to emphasize the heat characteristics of the city's microclimate. We specifically analysed the spatial distribution of air temperature and land surface temperature (LST) during a heat wave event on the 24th of June 2021. On that day mobile measurements were conducted between 10:30 and 11:15 AM local time to match the LST measurements of the Landsat-8 satellite that overpassed Zagreb at approximately 10:45 AM. Additional measurements were carried out in other seasons and at different times of the day.Results show thermal differences between surface types and urban forms. During a heat wave event, air temperatures reached up to 35 °C, and LST was above 40 °C, which are high temperatures considering the time of measurement. However, mobile measurements showed that city parks can be even 3 °C cooler compared to densely built-up city areas. Due to the high response time of the instrument, the effect of microscale city properties, such as tree lines, was also observed. These results indicate the cooling effect of green areas in Zagreb and the importance of their preservation for heat load reduction and mitigation of the negative effects of the urban heat island.
Uncertainty of spatial averages and totals of natural resource maps
Authors: Heuvelink Gerard , Wadoux Alexandre
Published: February 2023

Global, continental and regional maps of concentrations, stocks and fluxes of natural resources provide baseline data to assess how ecosystems respond to human disturbance and global warming. They are also used as input to numerous modelling efforts. But these maps suffer from multiple error sources and hence it is good practice to report estimates of the associated map uncertainty, so that users can evaluate their fitness for use. In this presentation we address the question of how to obtain the uncertainty of spatial aggregates of the map predictions. This is needed when the mapped variable is reported as an average or total for subareas within the study area, such as for rectangular grid cells, administrative units or bioclimatic domains, or for the study area as a whole. We first explain why quantification of uncertainty of spatial aggregates is more complex than uncertainty quantification at point support, because it must account for spatial autocorrelation of the map errors. We describe how this can be done with block kriging and illustrate this method in a case study of mapping the topsoil organic carbon content at various administrative aggregation levels in mainland France. Next, we propose an approach that avoids the numerical complexity of block kriging and is feasible for large-scale studies where maps are typically made using machine learning. Our approach relies on Monte Carlo integration to derive the uncertainty of the spatial average or total from point support prediction errors. We account for spatial autocorrelation of the map error by geostatistical modelling of the standardized map error. The methodology is illustrated with mapping aboveground biomass and deriving the associated uncertainty for various block supports in a region in Western Africa. Both case studies clearly show the need to account for spatial autocorrelation in order to get realistic estimates of the uncertainty of spatial averages and totals.
Basal controls of the grounding line dynamics of buttresses marine ice sheets
Authors: Sergienko Olga , Haseloff Marianne
Published: February 2023

The results of numerical studies suggest that the choice of sliding laws affect simulated dynamics of the grounding lines. Sliding laws that depend on the effective pressure imply that basal shear vanishes at the grounding line. Using analytical and numerical approaches we investigate what effects vanishing basal shear play in the dynamics and stability of the buttressed marine ice sheets. Our results show that the steady-state configurations of marine ice sheets with vanishing and non-vanishing basal shear do not differ greatly. In contrast, the time-variant behaviours of such marine ice sheets are drastically different. In response to a stochastic temporal variability in submarine melting, marine ice sheets with vanishing basal shear can exhibit unstoppable retreat while marine ice sheets with non-zero basal shear in the vicinity of the grounding line can exhibit intermittent advance and retreat. These results suggest that basal conditions in the vicinity of the grounding lines exhibit strong control of their dynamic behaviour. They also suggest the importance of the temporal variability of the basal shear in the dynamics of buttressed marine ice sheets.
How multiple stage rifting influences the planning of geothermal systems: a case study from the West Netherlands Basin
Authors: Weert Annelotte , Vinci Francesco , Ogata Kei , Amory Jerome , Tavani Stefano
Published: February 2023

In rift basins, the spatial arrangement of extensional faults can influence the facies and the thickness distribution of the syn- and post-sedimentary infill, which can harbour good potential for geothermal systems. In this framework, unravelling the tectono-stratigraphic evolution of a rift basin is decisive, as it can influence one of the key parameters for planning geothermal doublets: aquifer thickness.In our study, the West Netherlands Basin, located in one of the Netherlands most densely populated areas, is used as a case study. Up to 2022, 14 geothermal doublets were realized in the area, with the main target being the syn-rift deposits of the Late Jurassic Nieuwerkerk Formation. As a NW-SE  oriented transtensional basin, the West Netherlands Basin developed as consequence of Mesozoic extensional tectonics, after which it became inverted during the Late Cretaceous and Cenozoic. Using publicly available seismic 3D and well data, our renewed interpretation of the study area shows two important rift events. The first one during the Early-Mid Jurassic and the second one, partly controlled by structures of the former, during the Late Jurassic, coinciding with the deposition of the Nieuwerkerk Formation.Our study adds to the understanding of a multiple stage rifting history in the West Netherlands Basin. This is important, as the process influences reservoir thicknesses and with that, the amount of MW that can be extracted from geothermal aquifers. Therefore, this study forms a bridge between providing an integrated picture of the West Netherlands Basin and how the basins geological history affects its geothermal resources.
Decomposition kinetics as an optimal control problem
Authors: Manzoni Stefano , Chakrawal Arjun , Ledder Glenn
Published: February 2023

Microbial explicit models are constructed by linking decomposition (the process of organic matter break-down) and substrate uptake to microbial growth, respiration, and mortality. Therefore, the specific choice of the decomposition and/or uptake kinetics affects how in the model microbes grow and die, with consequences for carbon stabilization. There are well-established theories for extracellular enzymatic reactions and for substrate transport and uptake by cells, which allow deriving formulas for the decomposition and uptake kinetics, respectively. These laws account for microbial growth (e.g., in the Monod equation), but implicitly assume that microbial traits encoded in model parameters are static. Yet, microbes adapt to the environmental conditions they experience, resulting in temporally dynamic traits at both population and community levels. Adaptation is a result of natural selection for the fittest organisms. Therefore, we can describe adapted microbes by assuming they maximize their growth for given environmental conditions (e.g., limiting the amount of available resources) and given metabolic tradeoffs (e.g., decreasing efficiency of substrate to biomass conversion at high growth rates). In this contribution, we translate this assumption into a formulation of decomposition as an optimal control problem, where the objective is the maximization of cumulative growth, the constraint is imposed via a substrate mass balance, and the control parameter is the realized substrate uptake rate, assumed to be the outcome of optimally adapted production of extracellular enzymes and cellular uptake capacity. This optimal control problem is solved analytically for a simple case study (one substrate, homogeneous microbial community), leading to optimal decomposition kinetics that scale with the square root of substrate carbon content (different from Monod or Michaelis-Menten equations) and with a strong effect of maintenance respiration. If maintenance respiration is high, the kinetics flattens, and the optimal decomposition rate remains larger than zero even as the substrate is depleted. This means that the optimal decomposition rate approaches zero-order kinetics and exhibits increasingly high values as maintenance costs are increased. Interestingly, a tradeoff emerges between the rate of substrate consumption at the beginning of decomposition and microbial carbon use efficiency (ratio of growth over uptake). At high resource availability, efficient but slow-growing microbes are selected, whereas at low resource availability inefficient but fast-growing microbes are favored because they can more effectively compete for the limited resources. These results suggest that optimization methods offer an alternative way to define decomposition kinetics laws that account for microbial adaptation.
Spatio-temporal flood inundation modeling in the Andes Huallaga basin in Peru
Authors: Lavado-Casimiro Waldo , Qquenta Jonathan , Montesinos Cristian , Asencios Henry , Felipe Oscar
Published: February 2023

The present research focuses on evaluating the prediction capacity of the hydrological flood model called Rainfall-Runoff-Inundation (RRI), using observed data and satellite remote sensing in order to produce flood maps of the Alto Huallaga basin in Peru. The RRI model required as input data the topographic map of the region (we use FABDEM product), information on vegetation cover and land use obtained from FAO-UNESCO, and precipitation and evapotranspiration data from the Peruvian Interpolation data of the SENAMHI's Climatological and Hydrological observations (PISCO).The RRI model was evaluated for the 2014-2019 period, previously carrying out a sensitivity analysis process of the parameters and estimating the geometric parameters of the RRI model using information from satellite altimetry and remote sensing. The hydrological part of the model is calibrated at 2 hydrological stations on the Huallaga River (Tingo María and Tocache), obtaining acceptable results with Kling-Gupta (KGE) coefficients above 0.7 for both stations during the calibration and validation period. In addition, satellite images of the MODIS product were used for the part of flood maps, compared with the results of the RRI (flood areas), obtaining acceptable statistics when comparing the resulting images.This work is part of the results of the Enandes project (Enhancing Adaptive Capacity of Andean Communities through Climate Services) implemented in Peru that seeks to improve climate services in Peru with an emphasis on disaster risk management in Andean basins regarding floods.
Modern Scientific Data Governance Framework
Authors: Ramachandran Rahul , Peng Ge , Bagwell Shelby , Marouane Abdelhak , Jha Sumant , Christman Jerika
Published: February 2023

Science has entered the era of Big Data with new challenges related to data governance, stewardship, and management. The existing data governance practices must catch up to ensure proper data management. Existing data governance policies and stewardship best practices tend to be disconnected from operational data management practices and enforcement and mainly exist in well-meaning documents or reports. These governance policies are, at best, partially implemented and rarely monitored or audited. In addition, existing governance policies keep adding additional data management steps that require a human, ‘a data steward’, in the loop, and the cost of data management can no longer scale proportionately with the current and future increased data volume and complexity. The goal for developing an updated data governance framework is to modernize scientific data governance to the reality of Big data and align it with the current technology trends such as cloud computing and AI. The goals of this framework are two folds. One is to ensure thoroughness that the governance adequately covers the entire data life cycle. Two, provide a practical approach that offers a consistent and repeatable process for different projects. Three core principles ground this framework. First, focus on just enough governance and prevent data governance from becoming a roadblock toward the scientific process. Remove any unnecessary processes and steps. Second, automate data management steps where possible. Actively remove steps that require  ‘human in the loop’ within the management process to be efficient and scale with increasing data. Third, all the processes should continually be optimized using quantified metrics to streamline the monitoring and auditing workflows. 
Reconstructing the Pre-Alpine cycle of Moroccan Atlas system before the inversion phase
Authors: Ankach Mouad , Amrouch Khalid , Gouiza Mohamed
Published: February 2023

The Wilson Cycle (ca. 250-300 Ma) is driven by plate tectonics, and is expressed by the opening of oceanic basins, which are subsequently closed to form orogens. Morocco has experienced several orogenic cycles: e.g., Eburnean, Pan-African, Hercynian (Variscan) and Alpine (Atlasian). The last Wilson Cycle that shaped the geology of Morocco is the Alpine Cycle (300-0 Ma). It started by the dismantlement of the Pangea Supercontinent leading to the opening of the Atlantic Ocean and the Atlas rift system. The latter was subsequently aborted and inverted into a fold-and-thrust belt during the Cenozoic, due to the opening of the South Atlantic and the convergence between Africa and Iberia-Europe. The Atlas system of NW Africa includes two intracontinental ranges, the High and Middle Atlas extending ENE-WSW and NE-SW, respectively. It is a key piece in the Pangea breakup puzzle, as its evolution captures the kinematic of the African plate during Mesozoic to Cenozoic times. Several studies have examined the structural and stratigraphic architectures of the Atlas system during the rifting phase, by removing the Alpine inversion along palinspaticly reconstructed 2D sections. However, little was done to investigate the crustal structure and the amount of crustal stretching during the Triassic to Jurassic extension. This work aims to reconstruct the pre-alpine architecture of the Atlas system and link it directly with the evolution of the crust. Our goal is to provide insights into the amount of crustal thinning that took place during the Mesozoic rifting in the Atlas domain and constrain the strain distribution within the African plate during the dismantlement of the Pangea.Key words: Wilson cycle; Atlas system; Pangea; Break up; Inversion; Pre-Alpine cycle.
Recent variations in ecosystem water use efficiency to seasonal climate variability in China's key tropical-subtropical transitional zones
Authors: Liu Linxin , Zhang Ke , Forzieri Giovanni
Published: February 2023

Understanding how terrestrial ecosystem water use efficiency (WUE) responds to climate change is critical to accurately representing the carbon-water cycle processes. However, the dynamics of WUE under seasonal climate variations and biome-specific characteristics remain still unclear. In this study, we integrated two satellite-based retrieval algorithms to estimate gross primary productivity (GPP) and evapotranspiration (ET). Such indexes served as input to quantify ecosystem WUE (GPP/ET) and explore its dynamics during the dry and wet seasons from 2001 to 2018 in China’s key tropical to subtropical transitional zones, i.e., Yunnan Province. Results show large spatial heterogeneity and seasonal difference in WUE over the observational period. During the dry season, the increasing trends in GPP and ET have led to contrasting WUE patterns in forest and non-forest biomes, leading to positive and negative WUE trends, respectively. During the wet season, the declining trends in GPP occurring in combination with opposite trends in ET, have caused decreasing WUE consistently across all biomes except croplands, likely further modulated by human factors. The observed changes in WUE appear primarily driven by variations in air temperature (Ta) and vapor pressure deficit (VPD) during both dry and wet seasons. Overall, these results provide a valuable case for a better understanding of the carbon-water interplay in tropical-subtropical transitional zones and provide new insights to improve our capacity to predict the terrestrial ecosystem’s response to climate change.
Evaluation of Seasonal Streamflow Forecasts over South American Large Rivers
Authors: Petry Ingrid , Fan Fernando , Siqueira Vinicius , Collischonn Walter , Paiva Rodrigo , Quedi Erik , Gama Cléber , Silveira Reinaldo , Freitas Camila , Aver Cássia
Published: February 2023

Society’s increasing demand for water and the need for its long-term management have motivated efforts toward improving seasonal streamflow forecasts. Currently, seasonal climate forecasts are routinely issued in meteorological centers around the world, generating information for decision-making and seasonal streamflow forecasting (SSF) studies that are becoming more frequent. Seasonal streamflow forecast skill derives from land surface initial conditions and atmospheric boundary conditions that mostly depend on large-scale climate phenomena (such as ENSO). Thus, seasonal rainfall predictions produced by dynamic climate models that represent ocean-atmosphere interactions may have a positive impact on streamflow forecasts. In South America, seasonal streamflow forecasts are essential for the hydropower sector, which is responsible for ~65% of the electric energy produced in countries such as Brazil. In this work, we assessed seasonal streamflow forecasts over South America based on a continental-scale application of a hydrologic-hydrodynamic model and precipitation forecasts from the ECMWF's fifth generation seasonal forecast system (SEAS5). Seasonal streamflow forecasts (SEAS5-SF) were evaluated against a reference model run and forecast skill was estimated relative to the Ensemble Streamflow Prediction (ESP) method. The bias correction of SEAS5 predicted precipitation improved the performance of the seasonal streamflow forecasts, frequently turning negative skill results into near null to positive skill. Results indicate that the ESP remains a hard-to-beat method for seasonal streamflow forecasting in South America. SEAS5-SF skill was found to be dependent on initialization month, season, basin and forecast lead time, with greater skill on the initialization month lead time. Rivers where the forecast skill is higher were Amazon, Araguaia, Tocantins and Paraná. Acknowledgments: This work presents part of the results obtained during the project granted by the Brazilian Agency of Electrical Energy (ANEEL) under its Research and Development program Project PD 6491-0503/2018 – “Previsão Hidroclimática com Abrangência no Sistema Interligado Nacional de Energia Elétrica” developed by the Paraná State electric company (COPEL GeT), the Meteorological System of Paraná (SIMEPAR) and the RHAMA Consulting company. The Hydraulic Research Institute (IPH) from the Federal University of Rio Grande do Sul (UFRGS) contribute to part of the project through an agreement with the RHAMA company (IAP-001313).
Statistical Mapping of Magnetic Topology at Venus
Authors: Xu Shaosui , Frahm Rudy , Ma Yingjuan , Mitchell David , Luhmann Janet , Persson Moa
Published: February 2023

Venus lacks a significant intrinsic magnetic field, and thus, its atmosphere and ionosphere interact directly with the solar wind flow and magnetic field from the Sun. Interplanetary magnetic fields (IMF) can penetrate into the ionosphere when the upstream solar wind dynamic pressure is stronger than the ionospheric plasma pressure. Magnetic topology can be inferred at Venus if it is defined as the magnetic connectivity to the collisional atmosphere/ionosphere, rather than connectivity to the planet’s surface. Magnetic topology can be inferred from the pitch angle and energy distribution of superthermal (> ~1 eV) electrons. More specifically, the presence of loss cones in electron pitch angle distributions infers connectivity to the nightside collisional atmosphere and the presence of ionospheric photoelectrons (identified from electron energy distributions) indicates connectivity to the dayside collisional ionosphere. We design automated procedures to determine magnetic topology with electron and magnetic field measurements by the Venus Express spacecraft over its entire mission (2006-2014). This allows us to provide the first statistical mapping of magnetic topology at Venus. We also examine how the upstream drivers affect the low-altitude magnetic topology, revealing different magnetized states of the Venus ionosphere. We find that open and closed (a surprising topology not expected at Venus) fields cluster around the terminator and draped fields dominate other regions. Our results also reveal that there is more dayside magnetic connectivity in the -E (solar wind motional electric field) hemisphere than the +E hemisphere, and during solar maximum. During solar minimum, however, there is more nightside magnetic connectivity. Last but not the least, to understand the true nature of these magnetic topologies and broadly speaking the planet-solar wind interaction, we need to think about possible ways to measure the deeply penetrated magnetic fields at Venus and Mars.
Summer winds over the Iberian Peninsula related to thermal low conditions from COSMO-REA6 (1995-2018) high-resolution reanalysis
Authors: Ortega María , Sánchez Enrique , Gutiérrez Claudia , López-Franca Noelia , Gaertner Miguel Ángel , Molina María Ofelia
Published: February 2023

Thermal low pressure systems are typically generated over continental mid-latitudes and subtropical regions during summer, related to a strong heating over land caused by the long lasting solar radiation during this part of the year. They present a clear diurnal cycle, being more intense during the afternoon, and weakens at nighttime. In Europe, a thermal low forms frequently over the Iberian Peninsula. As strong pressure gradients are generated from the coastal regions to the interior of the Peninsula, wind characterization is a relevant feature to describe the Iberian thermal low. In particular, wind typically enters from the north (the Basque Country) and the east (the Mediterranean coast of Murcia and Valencia) through gaps between mountain ranges, and move respectively in a southwestward or westward direction. In the northern area, the wind flows into the regions of Burgos and Valladolid after channeling across the Duero valley, while in the southeast it reaches a large part of Castilla-La Mancha and even Extremadura. These winds are known in the Iberian Peninsula, for example, the regional wind from the Mediterranean to the Castilla-La Mancha plateau is typically named as Solano. Nevertheless, no systematic effort has been made to fully characterize and quantify its frequency or intensity, so no objective thresholds of wind speed, direction or spatial extension have been defined so far. A first effort to define such objective values is then proposed here. Hourly 10-m wind and 2-m specific humidity fields from COSMO-REA6 very high resolution (0.055º) reanalysis covering the 1995-2018 period are used. This high resolution, both temporal and spatial, will allow us to inspect the orographic aspects that seem to be relevant for these regional winds, together with its clear diurnal cycle and the moisture transport from coastal to inner regions. Humidity is a relevant variable for characterizing these flows, as there are marked differences between the moist air entering from the sea and the dry summer air characteristic of the inner regions of the Iberian Peninsula. The climatic perspective allows to study if interannual variability or trends are also relevant. First results indicate that these regional winds, with mean hourly speeds above 5 m/s for several hours per day, appear during most of the summer days, with important variations in spatial extension and strength. Strong moisture gradients are frequently observed during such episodes. Maximum speed and humidity jumps occur during the afternoon. This analysis is just a starting point, which will be followed by a deeper examination of these flows.
Extending the Air-Sea Essential Climate Variables CDR with AMSR3 and MWI Microwave Radiances
Authors: Wentz Katherine , Ricciardulli Lucrezia , Meissner Thomas , Wentz Frank
Published: February 2023

Remote Sensing Systems (RSS) provides a global community of researchers and decision makers with inter-calibrated microwave radiances and Air-Sea Essential Climate Variable (AS-ECV) geophysical retrievals originating from passive spaceborne sensors. The geophysical retrievals include: sea-surface temperature, near-surface ocean wind speed and direction, columnar atmospheric water vapor, columnar cloud liquid water, and sea-surface rain rate. In total, RSS generates microwave radiance and AS-ECV data from 14 microwave radiometers that span a time period of 35+ years. Consistent calibration procedures and retrieval methods have been applied during the data processing to ensure these datasets are suitable for climate research. Geophysical retrievals from two new sensors will be added to the RSS data repository in the 2023 to 2024 timeframe: GOSAT-GW AMSR3 and WSF-M MWI. The addition of these two microwave sensors, with their excellent spatial and temporal coverage, will extend the microwave AS-ECV climate data record (CDR) by up to ten years. In this presentation, we will present the intercalibration framework for integrating AS-ECVs from AMSR3 and MWI into the current CDR.Historically, the RSS Radiative Transfer Model (RTM) developed for the SSMI sensor was the primary standard for inter-calibrating passive microwave radiances ranging from 6 to 89 GHz. Now, the calibration is tied to GMI onboard GPM. GMI’s unique design enabled absolute calibration of its antenna temperatures and brightness temperatures using various known calibration parameters, including hot load and cold sky antenna temperature tie points, coefficients that describe the non-linearity between sensor counts and antenna temperatures, and cold space spillover. In this presentation, we will describe how the GMI radiances will be used to calibrate AMSR3 and MWI. GMI’s 65-degree inclined orbit is not sun-synchronous, and it allows tight collocation windows with other satellite sensors. This is particularly useful for calibrating AMSR3 and MWI day and night observations. For a set of collocations, a double difference method will be used to find the AMSR3 and MWI calibration parameters that best match the GMI absolutely-calibrated radiances. We will present the inter-calibration process in detail, including the optimization of calibration parameters, the AS-ECVs used in the RTM in order to correct for small differences between sensors, and cases where the sensor radiance channel is not present in GMI.
New insights into the mesosphere of Venus from MERTIS measurements during the two BepiColombo flybys
Authors: Arnold Gabriele , Haus Rainer , Helbert Joern , D'Amore Mario , Maturilli Alessandro , Saeuberlich Thomas , Hiesinger Harald
Published: February 2023

Analyses of measurements made by MERTIS1 (MErcury Radiometer and Thermal Infrared Spectrometer) during the BepiColombo mission's close flyby 2 of Venus (FB2) have already demonstrated the instrument's capacity to explore the planet's mesosphere at near equatorial latitudes. The MERTIS instrument was designed to study the hot surface of Mercury. It performed well beyond its design limits when analyzing the Venusian mesosphere because of the much lower radiances. MERTIS’ measurements are the first spectrally resolved observations of Venus in the thermal spectral range longward of 5 µm since the Venera-15 Fourier spectrometer experiment in 19832. It could be shown that MERTIS FB2 data enable reliable retrievals of mesospheric temperature profiles and cloud parameters between 60 and 75 km altitude. They are in good agreement with the results of the Venera-15 mission. This indicates the stability of the Venusian atmosphere on time scales of decades3,4.In this paper we discuss preliminary results from MERTIS measurements of the first flyby (FB1) in October 2020. During the first flyby the spacecraft approached the planet from the solar direction over the dayside. The closest approach (CA) occurred at about 11,000 km distance above the evening terminator of the planet, and then the spacecraft moved away from the planet to the anti-solar direction. In this time the apparent size of Venus increased from slightly larger than one MERTIS pixel (0.7 mrad) to more than 1 degree. MERTIS performed close-up dayside observations from early morning to late afternoon via noon time on Venus at latitudes between 50°S and 85°N and obtained about 785,000 hyperspectral observations with the spectrometer channel. Thus, FB1 observations permit much larger latitude coverage from 50°S to 85°N compared to FB2. To process the FB1 data in terms of both a reasonable signal-to-noise ratio and comparable observing conditions, individual spectra were averaged over 5° latitude belts and 0.5 h local time intervals. We further excluded extreme observation geometries for latitudes northward of 80°N and southward of 40°S as well as very weak spectra. As a result, we are able to generate a reliable data base for use in radiative transfer analyses for the Venusian mesosphere. We present preliminary results on the temperature fields of the mesosphere as a function of local time, altitude, and latitude. Hiesinger, H. et al. Space Sci. Rev. 216, 6 (2020).Oertel, D. et al. Adv. Space Res. 5, 25-36 (1985).Arnold, G. et al., SPIE Optic+Photonics, San Diego, Proceedings Volume 12233, doi.org/10.1117/12.2632548 (2022).Helbert, J. et al. submitted to Nature Astronomy (2023).
Allocation mediates plant drought stress and productivity in a changing climate
Authors: Trugman Anna , Quetin Gregory
Published: February 2023

The extent to which future climate change will increase forest stress and the amount to which species and forest ecosystems can acclimate or adapt to increased stress is a major unknown. We used high resolution maps of hydraulic traits representing the diversity in tree drought tolerance across the United States combined with a hydraulically-enabled tree model to quantify the ability for within-species changes in allocation and between-species range shifts to mediate climate stress. We found that forests are likely to experience increases in chronic hydraulic stress with climate change, even with expected increases in atmospheric CO2. Based on current species distributions, regional hydraulic trait diversity was sufficient to buffer against increased stress in 86% of forested areas. Importantly, changes in leaf allocation have the potential to substantially decrease stress, reducing the need for biogeographic shifts in species distributions. However, observed trait velocities are not keeping up with the rate required to ameliorate projected future stress.
Co-composted biochar enhances soil fertility more than individual additives
Authors: Mikajlo Irina , Louvel Brice , Záhora Jaroslav , Lerch Thomas Z. , Pourrut Bertrand
Published: February 2023

Biochar is considered a promising amendment to store carbon and improve degraded soil properties. However, this additive could have disadvantageous effects on plants and soil organisms due to its charring process toxic by-products and its ability to retain nutrients. To mitigate these negative effects, co-amendments with an organic additive such as compost have been proposed, but comparative studies are scarce. In this study, we investigated the influence of biochars applied (i) solely, (ii) mixed with matured compost or (iii) co-composted biochar on soil properties and plant growth. To this aim, three different types of biochar derived from various feedstocks were tested in two soil with different agronomic properties (Luvisol and Fluvisol). After three months of greenhouse experiment with grown lettuce (Lactuca sativa var. capitata L.), the shoot and root biomasses were quantified and the soil physicochemical properties were measured (pH, CEC, total N, organic C and soil available P). Solely applied biochar did not influence plant yield and maintained alkaline soil pH. Contrariwise, biochar mixed with matured compost maintained an average increase of lettuce growth by three times with risen soil nutrient content and kept alkaline pH. Whereas treatments with co-composted biochar and solely added compost promoted plant growth by almost six times, kept pH on neutral levels and nutrients on an average level with CEC equally enhanced, regardless of the biochar origin or the soil type. These results suggest that co-composted biochar addition to the soil is a convincing way to maintain soil fertility in a long term.
Measuring atmospheric turbulence using Background Oriented Schlieren and machine learning
Authors: Hu Zin , Li Cheng
Published: February 2023

Atmospheric turbulence has a huge impact on governing the temperature structure of our atmosphere, on the mixing of water vapor, on forming clouds, and on the future climate. However, unlike water, we cannot see the motion of the atmosphere other than feeling the motion of the wind. The traditional way of visualizing turbulence in transparent media is to use an optical Schlieren system where a razor blade is placed in front of the camera blocking half of the light entering the aperture. Temperature variation of the atmosphere will lead to a variation in the refractive index, which will bend the light. Some light will enter the aperture as normal, but others will be blocked by the razor blade. This setup requires a point source of light and an exact alignment of the optical system, which is hard to do in an atmospheric environment. However, the recent development of Background Oriented Schlieren (BOS) is a simple and cost-effective imaging method for the visualization of atmospheric turbulence leveraging modern computational capabilities. It only requires one camera and a background “noisy” image. The system “calculates” the bending of the light pathing through the media of interest by comparing the original undistorted image with a distorted image by the density variance in the media. No mirror is needed, and the system is no longer limited by the size of the focal-length or the size of the mirror and it is particularly useful for atmospheric studies. Here we build the BOS system using a DSLR camera and we reconstruct the velocity field using machine learning techniques. We show that it is a new measurement technique to retrieve 3D atmospheric turbulence structure and has the potential in a large field campaign.
Deep Direct Current Resistivity Inversion
Authors: Escada Cláudia , Azevedo Leonardo
Published: February 2023

Climate change threats groundwater resources, requiring sustainable management of this critical asset. Widely applied in hydrogeology, direct current resistivity (DCR) methods have been a preferable tool for imaging groundwater resources due to its potential to efficiently image a relatively large area in a relatively short period. DCR methods use electrodes to inject electrical currents into the subsurface ad measure the resulting potential difference (i.e., voltage).The quantitative interpretation of these data (i.e., the spatial prediction of the geological subsurface properties) requires solving a challenging geophysical inversion problem. Deterministic DCR inversion methods are common approaches to reach this objective but might be computationally expensive, requiring a large degree of expertise and predicting a single model unable to capture the small-scale details of subsurface geology. The main goal of this work is to overcome these limitations through the development and implementation of a deep DCR inversion workflow.The proposed methodology follows three main steps: data acquisition, deep neural network (DNN) training and DCR data inversion. For the second step, it is generated a training dataset of electrical resistivity models by geostatistical simulation to represent a variety of possible subsurface scenarios. These models will be the input to train a variational autoencoder (VAE; Kingma & Welling, 2013; Lopez-Alvis et al., 2020). After training, the VAE outputs electrical resistivity simulated models given measured DCR data. The predicted models are then forward modelled (Cockett et al., 2015) to calculate predicted data, which are compared with the recorded data. The misfit between the observed and simulated data is used to iteratively update the DNN weights and parameters.The proposed method is illustrated with its application to a set of DCR data acquired in the southern region of Portugal comprising an area highly affected by droughts and industrial pressure.Cockett, R., Kang, S., Heagy, L. J., Pidlisecky, A., & Oldenburg, D. W. (2015). SimPEG: An open-source framework for simulation and gradient-based parameter estimation in geophysical applications. Computers and Geosciences, 85, 142–154. https://doi.org/10.1016/j.cageo.2015.09.015Kingma, D. P., & Welling, M. (2013). Auto-Encoding Variational Bayes. https://doi.org/10.48550/arXiv.1312.6114Lopez-Alvis, J., Laloy, E., Nguyen, F., & Hermans, T. (2020). Deep generative models in inversion: a review and development of a new approach based on a variational autoencoder. https://doi.org/10.1016/j.cageo.2021.104762
Mapping dengue fever risk for a non-endemic high-density city in subtropical region
Authors: Yin Shi , Hua Junyi , Ren Chao , Guénard Benoit , Wang Runxi , Weemaels André Ibáñez , Shi Yuan , Lee Tsz-Cheung , Yuan Hsiang-Yu , Chong Marc Ka-chun , Tian Linwei
Published: February 2023

Dengue fever is a mosquito-borne disease caused by the dengue virus bringing huge health burdens in tropical regions. With global warming, rapid urbanization, and mosquito species introductions, the range of dengue fever is expected to expand to subtropical regions and increase potential health risks for local populations. To reduce dengue fever transmission, relevant risk map is one of the most effective tools for public health management. Though there is abundant literature about mapping the dengue fever risks in endemic regions, few studies in contrast have investigated dengue fever risks for non-endemic regions; hindering the development of preparedness planning.In this study, the spatial hazard-exposure-vulnerability assessment framework proposed by the Intergovernmental Panel on Climate Change was applied in to detect the dengue fever risk in Hong Kong, which is a typical high-density city located within a subtropical region. Firstly, the spatial distribution of the habitat suitability for Aedes albopictus, a mosquito species common in Hong Kong and proxy for the potential dengue fever hazard, was predicted using MaxEnt models relying on the surveillance data and a list of variables related to urban morphology, landscape, land utilization, and local climate. Secondly, the bivariate local Moran’s I was measured to identify urban areas with both high dengue hazard and high human population exposure. Then, vulnerable groups among the human population were identified from the 2016 Hong Kong census data. Finally, dengue risks were assessed at the community scale by overlapping the results of hazard, exposure, and vulnerability analysis.In the optimal MaxEnt model predicting the presence possibility of Aedes albopictus, the normalized difference vegetation index, frontal area index, and the aggregation index of public residential land ranked the top three among all predictors, with permutation importance of 31.8%, 22.8%, and 17% respectively. Three components were generated after principal component analysis on the vulnerable groups. Lastly, this approach allowed the identification of 17 high-risk spots within Hong Kong. In addition, the underlying factors behind each hot spot were investigated from the aspects of hazard, exposure, and vulnerability respectively, and specific suggestions for dengue prevention were proposed accordingly.The findings provide a useful reference for developing local dengue fever risk prevention measures, with the proposed method easily exportable to other high-density cities within subtropical Asia and elsewhere.This study was funded by the Health and Medical Research Fund of the Food and Health Bureau (No. 20190672).