bluuebunny/crossref_metadata_2025 huggingface dataset:
African monsoon changes in the Late Cenozoic from the climate modelling perspective
Authors: Boateng Daniel , G. Mutz Sebastian
Published: March 2024

Africa's climate underwent significant hydroclimate changes in the Late Cenozoic. For instance, the repeated phases of aridification across the continent played a crucial role in shaping the region’s biodiversity and hominid evolution. Consequently, understanding the historical climate variations in the region becomes essential for reconstructing its paleoenvironment and paleobiological history. Moreover, past climates can be used as analogues for potential future climates and thus help us understand the implications of future climate scenarios. The precipitation seasonality and variability in the region are predominantly driven by the African monsoons, which exhibit intricate climate dynamics controlled by both regional and large-scale atmospheric teleconnections. However, due to the complexity of these dynamics and teleconnections, even state-of-the-art General Circulation Models (GCMs) still struggle to accurately reconstruct its past climate variability and provide reliable future projections.Here, we simulate the response of the African monsoons to different late Cenozoic paleoenvironmental changes, such as atmospheric CO2 concentration (pCO2), orbital forcing, palaeogeography, vegetation, and orography (including the topographic evolution of the East African Rift System (EARS)). We performed time-specific simulations with a high-resolution setup of the GCM ECHAM5-wiso and the paleoenvironmental boundary conditions for the Middle Miocene climate optimum (MMCO; 16.9-14.7 Ma), Middle Miocene climate transition (MMCT; 14.7-13.8 Ma), Mid-Pliocene (MP; ~3 Ma), the Last Glacial Maximum (LGM; ~21 ka), the Mid-Holocene (MH; ~6 ka), and the pre-industrial (PI; the reference year 1850).Furthermore, we conducted topographic sensitivity experiments of the EARS under the MMC and MMCT conditions to understand the role of tectonics in the evolution of Africa’s climate and atmospheric dynamics. We focused our analysis on disentangling the thermodynamic effects (e.g., water vapour content changes) and dynamic effects (e.g., Hadley circulation) on the monsoon changes and associated atmospheric dynamics (e.g., African Easterly Jet, Somalia Jet, Tropical Easterly Jets, low-level westerlies). Overall, the study provides an overview of hydroclimate and climate dynamics changes over Africa for the past 20 Ma, contributing to the understanding of the feedback between changes in pCO2, orbital forcing, and tectonic events that are relevant for improving future climate prediction.
Validation of Multiple Satellite Aerosol Optical Depth (AOD) Retrievals Using Ground-Based AERONET AOD Data over West Africa
Authors: Sani Muawiya , Salihu Said Rabia , Bello Idrith Tijjani , Usman Yerima Sunusi
Published: March 2024

Aerosol Optical Depth (AOD) is an essential parameter for understanding atmospheric aerosol distribution and its impact on climate and air quality. Satellite-based AOD retrievals play a crucial role in large-scale studies, but their accuracy necessitates validation against ground-based measurements. This study focuses on validating AOD data products from multiple satellite sensors (MODIS TERRA, MODIS AQUA, MISR, OMI and MERRA-2) using high-quality ground-based Aerosol Robotic Network (AERONET) AOD data within the West African region. The study aims to assess the performance of different satellite sensors in capturing the spatiotemporal variability of aerosol loading over West Africa for the period 2000–2022. Six AERONET stations (Banizoumbou, Cinzana, Ilorin, Dakar, Capoverde, and Koforidua) are considered within three sub-regions of West Africa (Sahel, Savannah, and Guinea Coast). Rigorous validation techniques, including intercomparison analysis and statistical metrics, are employed to evaluate the agreement between satellite-derived AOD and AERONET measurements. Preliminary results indicate that satellite retrievals generally capture the broad-scale patterns of aerosol distribution in West Africa. However, this study reveals significant discrepancies in some regions, emphasizing the need for improved satellite algorithms, especially in areas with complex aerosol properties. Furthermore, the analysis identifies the best-performing satellite sensors at each AERONET station when employing either daily or monthly data. Daily analysis revealed MODIS AQUA had the best agreement at Banizoumbou, Cinzana Capoverde and Koforidua, while MISR and MODIS TERRA performed best at Dakar and Ilorin, respectively. On the other hand, the monthly analysis revealed MODIS TERRA performs best at Banizoumbou, Dakar, and Capoverde stations, while MERRA performs best at Cinzana and Ilorin stations. MISR shows relatively lower performance compared to MODIS TERRA and MERRA at Banizoumbou and Koforidua stations. But surprisingly, MODIS AQUA wasn’t the best performer at any of the stations based on monthly analysis. These findings highlight the importance of enhancing satellite algorithms to improve the accuracy of aerosol retrievals and the importance of taking caution when selecting a type of satellite data product and the temporal resolution to use for climate studies, air quality monitoring, and environmental management in regions with intricate aerosol characteristics.Keywords: Aerosol Optical Depth (AOD), MODIS TERRA, MODIS AQUA, MISR, OMI, MERRA-2, Aerosol Robotic Network (AERONET), West Africa.
Explaining GNSS station movements based on Earth observation data
Authors: Crocetti Laura , Schneider Rochelle , Soja Benedikt
Published: March 2024

Global Navigation Satellite Systems (GNSS) are best known for their accurate positioning, navigation and timing capabilities. In total, over 20.000 permanent high-grade GNSS stations are available worldwide, the positions of which are monitored with millimeter accuracy. Thanks to the high accuracy and the fact that these stations are mounted on the ground, subtle movements due to hydrological changes and crustal deformation can be observed. Thus, the GNSS observations contain valuable geophysical information. Although many geodetic applications require these movements to be properly understood and potentially corrected, this is not trivial due to the complexity of the interactions within the Earth’s system. Therefore, there is a severe lack of available models explaining residual GNSS station movements beyond conventionally modeled effects. On the opposite, if these movements are properly understood, GNSS observations might contribute to the correct interpretation of emerging environmental changes.This study exploits the wealth of satellite-derived Earth observation (EO) data to derive suitable models to explain GNSS station movements. We combine GNSS station coordinate time series and EO variables with the help of machine learning techniques to benefit from various types of information. While the target vector consists of concatenated GNSS station coordinate time series over Europe, EO variables such as precipitation, soil water, snow water equivalent, and land cover data are used as input features. Different machine learning models, including Random Forest, XGBoost, and Multilayer Perceptron, are investigated and compared. Additionally, a sensitivity analysis is performed to determine the individual impact of EO variables to quantify what drives GNSS movements, which in turn, might allow monitoring the corresponding Earth system processes based on GNSS observations.
Retro-observations of terrestrial and aquatic ecosystem degradation associated with agricultural intensification in South America using sedimentary archives
Authors: Foucher Anthony , Bardelle Amaury , Minella Jean Paolo Gomes , Tassano Marcos , Chalar Guillermo , Cabrera Mirel , Evrard Olivier
Published: March 2024

Since the mid-1980s, agriculture in South America has intensified and expanded significantly. For example, Brazilian census data show that cultivated land increased by 80% between 1996 and 2006, mainly in ecologically fragile areas (e.g., the Amazon, Cerrado, and Pampa). While agriculture plays a critical role in the socio-economic life of South America's agricultural regions, it also has negative environmental impacts, including land-use change, biodiversity loss, soil erosion and agrochemical contamination. To mitigate the negative effects of accelerated sediment transport, conservation practices such as no-tillage were adopted in the 2000s. Despite the advantage of not tilling the soil, the no-till system has a significant potential for soil and water degradation, both because of the high amount of inputs (pesticides and nutrients) added to the soil surface and because of the susceptibility to surface runoff formation and related processes.Agricultural expansion and intensification are expected to continue in South America in the coming decades to meet growing food demand. However, the long-term (>40 years) responses of terrestrial and aquatic ecosystems to these anthropogenic pressures and conservation practices remain poorly documented due to a lack of multi-decadal monitoring stations or field measurements. Sedimentary archives collected in rivers and lakes draining South American regions affected by this agricultural expansion/intensification provide a unique opportunity to reconstruct the magnitude of these environmental impacts. In this study, we propose a synthesis of sedimentary archives published in Brazil, Uruguay, and Argentina, with a focus on the post-1950 period. These studies, which report on sediment dynamics and sediment characteristics (such as organic matter, phosphorus, accumulation rate), will be used to reconstruct the regional trajectory of terrestrial and aquatic ecological degradation related to these increasing human pressures. These trajectories will be compared with existing data on land use change, agricultural inputs, etc. to understand the response of the system to these perturbations and to better anticipate potential future degradation in line with expected trends in the coming years.
Physics-driven feature combination for an explainable AI approach to flare forecasting
Authors: Lampani Margherita , Guastavino Sabrina , Piana Michele , Benvenuto Federico , Massone Anna Maria
Published: March 2024

Typical supervised feature-based machine learning approaches to flare forecasting rely on descriptors extracted from magnetograms, as from Helioseismic and Magnetic Imager (HMI) images, and standardized before being used in the training phase of the machine learning pipeline. However, this artificial intelligence (AI) model does not take into account the physical nature of the features and their role in the plasma physics equations. This talk proposes to generate novel features according to simple physics-driven combinations of the original descriptors, and to show whether this original physically explainable AI model leads to a more predictive solar flare forecasting.
Challenges of old mining cities in the application of the proposed EU Soil Monitoring Law – Outokumpu, Finland, as an example
Authors: Kupila Juho , Solismaa Soili , Loukola-Ruskeeniemi Kirsti , Sorvari Jaana , Reinikainen Jussi , Valve Helena , Kaija Juha
Published: March 2024

The city of Outokumpu in Eastern Finland occupies a Cu-Co-Zn mining region.  Mining and metallurgical activities began already in 1913. This area falls within a zone with naturally high concentrations of Ni, Cu, Co, and Zn in soil and bedrock. In addition, mining waste has been used in earthworks, especially in the construction of the city's streets.In the summer of 2023, the European Parliament and Council proposed a Soil Monitoring Law, comparable to the earlier regulations established to protect air and water. The proposal mandates member states to address soil contamination. The European Union funded Horizon Europe project ISLANDR ‘Information-based Strategies for Land Remediation’ will provide data, tools, and methods to support the initiative. ISLANDR is a cross-disciplinary and multi-actor project and aims to promote the delivery of Green Deal objectives.To provide real-world research context for different land use, climate and vegetation, seven test areas across Europe were chosen for a more detailed survey. Test areas were selected to characterize both point and diffuse sources of pollution, as well as by different soil pollution types.The test area representing the brownfield mining areas is Outokumpu. Extractive wastes rich in sulphur, nickel, copper, zinc, cobalt, chromium, and other 'potentially toxic elements' (PTEs) were stored according to regulation which earlier was not as advanced as today. These wastes were also used for construction purposes, causing additional acidity and PTE load for the environment. Locally, elevated concentrations of PTEs have been observed in soil, groundwater, and surface waters.Recommendations for regulation and remediation methods are compiled. Financial challenges, proposed solutions to improve the environmental status of the region, and opportunities for reusing or decontaminating degraded soils are discussed. Lessons learned in the historical Freiberg mining area in Germany will be utilized (Loukola-Ruskeeniemi et al., 2022: J. Haz. Mat. 424, 127677). The results from Outokumpu and Freiberg will be compared, for example, with the results of the EU MIREU project (Mining and Metallurgy Regions of EU MIREU GTK).
Petrographic and geochemical investigation of magma reservoir processes at Rabaul Caldera, Papua New Guinea
Authors: Hoehn Melina , McCormick Kilbride Brendan , Hartley Margaret
Published: March 2024

Rabaul is a large caldera system located at the northeastern tip of the island of New Britain, Papua New Guinea. Historically, it has been the most active volcano in Papua New Guinea. Rabaul is capable of large volume, high intensity caldera-forming eruptions (high-risk, low-probability events occurring every ca. 2 ka, most recently the Rabaul Pyroclastics event ca. 1400 years ago) and lower intensity but more frequent intra caldera eruptions. All eruptions at Rabaul pose a significant risk to nearby populations and settlements [1,2].Rabaul’s volcanic rocks vary in composition from basaltic andesite to rhyolite and mostly lie on a common liquid line of descent, controlled by fractional crystallization under reducing conditions [1,2,3,4]. Magma mixing and mingling are common, evidenced by basaltic enclaves and mafic minerals in andesitic and dacitic eruption products [1,2,4]. These enclaves signify regular mafic recharge of the main dacitic reservoir, which primes the system for eruptions [4]. Seismic tomography imaging suggests the presence of an extensive, tabular magma body at a depth of 3-6 km with a volume of about 15-150 km3 [5,6].The main goal of this study is to determine how the petrology and geochemistry vary between magmatic products erupted from different intervals in the caldera cycle of Rabaul volcano. In addition, we aim to get a better understanding of the primitive magmas that feed and sustain volcanism at the Rabaul Caldera Complex. Furthermore, we identify the key magma chamber processes influencing mineral chemistry and texture.Here, we present EPMA mineral analysis and thermobarometry model outputs for products of the 1937, 1994 and 2014 eruptions as well as for the most mafic eruption products known, the Kombiu basalts. Our thermobarometry data complement existing geophysical observations of the structure of Rabaul’s magma plumbing system. Furthermore, we present SEM imagery to reveal how mineral textures (zoning, resorption, grain size, grain boundaries) in samples from different eruptions at Rabaul reflect magma chamber processes such as mafic recharge, magma mixing and crystallisation. References: [1] Patia H et al. (2017) J Volcanol Geotherm Res 345:200-217; [2] Fabbro G et al. (2020) J Volcanol Geotherm Res 393:106810; [3] Wood CP et al. (1995) J Volcanol Geotherm Res 69:285-302; [4] Bouvet de Maisonneuve C et al. (2016) GSL; [5] Finlayson et al. (2003) J Volcanol Geotherm Res 124: 153-171; [6] Bai and Greenhalgh (2005) Phys. Earth Planet. Inter. 151: 259-275
Assessment of different vegetation friction approaches in numerical hydrodynamic modeling
Authors: Dallmeier Antonia , Kopmann Rebekka , Folke Frederik , Ruether Nils
Published: March 2024

The correct representation of the interaction between flow and vegetation in numerical hydrodynamic modeling has been of growing importance in recent years. As conventional roughness approaches like Manning-Strickler or Nikuradse fail to represent the hydraulic resistance of vegetation for various hydraulic conditions in depth-averaged models, vegetation approaches must be applied. These approaches calculate the time-variable hydraulic resistance of plants according to the plants' characteristics and the hydraulic conditions within the numerical hydrodynamic simulation. In the open-source numerical modeling software openTELEMAC-MASCARET, eight vegetation approaches are implemented. These approaches account for flexible and rigid plants in emergent and submerged conditions. In addition, a biomorphodynamic model was integrated into openTELEMAC-MASCARET. This biomorphodynamic model uses a drag force approach combined with Stone and Shen's (2002) approach to calculate the flow velocity in submerged flow conditions to account for the hydraulic resistance of plants. In this study, we compare the representation of vegetation in numerical modeling as a drag force according to the biomorphodynamic model with the implementation as a friction approach. This way of implementation also allows a comparison with the above-mentioned vegetation friction approaches. Additionally, Stone and Shen (2002) have developed an approach for calculating the hydraulic resistance, which we also implement to compare the performance of this approach. Therefore, we first convert the drag force approach of the biomorphodynamic model into a friction approach according to existing approaches. The resulting approach and the original hydraulic resistance approach of Stone and Shen (2002) are then implemented in openTELEMAC-MASCARET. In order to evaluate the performance of these two approaches, we compare the resulting Darcy-Weisbach friction factors to those of the existing approaches. Using a simplified test case within openTELEMAC-MASCARET, we calculate the bed shear stress in vegetated areas and compare it with the results of the biomorphodynamic model. The results indicate a good agreement between the newly implemented vegetation approaches and the existing ones and the biomorphodynamic model. This study thus lays the foundation for further numerical investigations using vegetation approaches, especially concerning the interaction between vegetation, sediment, and flow.
Linking ecological and socio-economic changes to assess impacts of global change on landscape and ecosystem services in the European Alps
Authors: Tappeiner Ulrike , Schirpke Uta , Tasser Erich
Published: March 2024

Mountain landscapes, shaped by human activities over centuries, are facing significant transformations in the European Alps, mainly due to the abandonment of formerly managed areas. Their compressed topography and vertical gradients make them particularly vulnerable to global change. However, mountain landscapes and ecosystems contribute crucially to ecosystem services for people living inside and outside these areas.
We will present the dynamic of land-use change for the past 150 years in eight different agrarian structure regions in the Alps and investigate the role of different land-use types, including their land-use intensities, on the supply capacity and flow of provisioning, regulating, and cultural ecosystem services. We will illustrate that the regional framework conditions play a much more important role in landscape development in the European Alps than national frameworks. Higher “green subsidies” reduced the intensiﬁcation trend in agriculture, but also led to increased abandonment. In addition, the landscape also remained more diverse, biodiversity declined less, and many ecosystem services increased. This demonstrates that interpreting historical landscape dynamics and analyzing impacts on ecosystem services using a cross-sectoral approach can be a valuable guide to sustainable decision-making processes in order to enhance landscape resilience.
Finally, we will discuss the results of several studies that assessed future grasslands and forest development under different climate, management, and disturbance scenarios and the resulting changes in service supply. It will be shown that up to the 2050s, socio-economically driven land-use changes and legacy effects will have a more significant influence, whereas afterward, accelerating climate change will become the more important driver of changes. However, the ability of management to control ecosystem service supply decreases sharply with the severity of future climate change if no decisive actions to mitigate climate change are taken. Hence, climate change may severely hamper the management of mountain ecosystems, but value-based visions of local communities may help define appropriate adaption pathways.
Design of a generalized vertical coordinate to properly represent the structure of normal modes in an oceanic model 
Authors: Derrida Gabriel , Debreu Laurent , Lemarie Florian , Chanut Jérôme
Published: March 2024

In ocean modeling, the choice of a suitable vertical coordinate system is crucial due to the complex vertical dynamics of the ocean, playing a significant role in climate considerations. The objective of this research is to develop a generalized vertical coordinate system applicable across various scales, from global to coastal applications. Three primary algorithms for solving generalized vertical coordinate ocean equations are considered: quasi-Eulerian (QE) coordinate, Vertical Lagrangian Remapping (VLR), and the Arbitrary Lagrangian-Eulerian (V-ALE) method. The V-ALE method offers an alternative between QE and VLR, incorporating both Lagrangian and Eulerian components in the movement of the target grid. In this study, the focus is on the V-ALE method, with a particular emphasis on specifying the target grid. The proposed approach consists in defining the target grid to solve a propagation problem in an inhomogeneous environment. The stratification state, a key element of this environment, has a significant influence on the mode structure.From a discrete point of view, the challenge is to identify the optimum grid point positions for correctly representing vertical modes. The aim is to understand the errors introduced by discretization and minimize them to find the optimal point positions. A variational method is also proposed, leading to a non-uniform grid that better represents vertical modes. We illustrate the results obtained with these methods using stratification profiles derived from climatological data.
Conceptual 3D groundwater models of offshore freshened groundwater extraction and its economic viability assessment
Authors: Zamrsky Daniel , van Lith Joep J.H. , van Beek Rens
Published: March 2024

Offshore freshened groundwater reserves have been identified in numerous regions worldwide. These reserves were often deposited during past sea level lowstands and are therefore non-renewable and slowly salinized by infiltrating seawater. However, in some cases these offshore freshened groundwater reserves can be connected to inland groundwater systems and can be recharged by fresh groundwater inflow from the landward direction. It has recently been suggested that these offshore freshened groundwater reserves could provide an additional source of fresh (and brackish) water for coastal communities that often face increasing fresh water stress. The feasibility, both economic and physical, of offshore freshened groundwater extraction is investigated in this study. To assess this feasibility from a physical point of view we built a set of 3D semi-conceptual groundwater flow models using the imod-wq code which allows us to estimate the offshore groundwater salinity development over large time scales (i.e. one glacial-interglacial cycle). The result of these large time scale models can be interpreted as estimations of the current offshore groundwater salinity conditions and thus provide a better picture of the current presence and magnitude of the offshore freshened groundwater resources in the model domain. In the next modelling stress period we introduce a set of pumping wells into the offshore domain and simulate several offshore freshened groundwater extraction scenarios. In such way we can evaluate the time it takes for these offshore freshened groundwater reserves to be fully salinized and exhausted. Additionally, we can also assess any potential negative impacts on the groundwater system in the coastal hinterland such as decreasing groundwater levels and/or increased salinization.In the second part of our study we evaluate the economic feasibility of the offshore freshened groundwater pumping and use as additional fresh water resource for coastal communities. Several coastal areas located in south and south-east Asia (e.g. Pearl River delta) were selected since this region is identified as a region with high possibility and magnitude of offshore freshened groundwater resources. The economic parameters that are taken into account as favourable for offshore freshened groundwater exploration are (i) the overall economic development (e.g. GDP, HDI), (ii) the presence of groundwater pumping and desalination plants inland meaning the technology is already present in the region and (iii) costs of fresh water and groundwater pumping and desalination infrastructure in the region. Our study is only the first step in assessing the feasibility of offshore freshened groundwater exploration and hopefully our approach will be improved and tested in other coastal regions around the world to evaluate the full potential of these still untapped fresh groundwater resources.
Benchmarking physics-based, machine learning, and hybrid hydrology models at multiple catchments in Southern Norway.
Authors: Matheussen Bernt Viggo , Shrestha Rajeev , Beil-Myhre Bjarte
Published: March 2024

Accurate inflow forecasts play a crucial role in the daily operations of hydropower reservoirs. Practitioners in the hydropower industry typically combine physically based models coupled with weather forecasts to produce inflow forecasts to the reservoirs. Despite the emergence of physically-based hydrological models since the early 1960s, their growing complexity has posed challenges in usage and calibration. Recent work by Kratzert et al. (2018) suggests that non-linear regression models such as LSTM neural networks (Hochreiter & Schmidhuber, 1997) may outperform traditional physically based models. Given the plethora of hydrology models, it is crucial to identify the most effective configurations within a diverse range of catchments using objective quantitative performance criteria.This research aims to evaluate various model configurations across multiple catchments, determining the optimal hydrological model for streamflow prediction. Two physics-based models, the Distributed Regression hydrological Model (DRM) by Matheussen at Å Energi and the Statkraft Hydrology Forecasting Toolbox (SHyFT) from Statkraft, were applied alongside two versions of LSTM models tested as standalone and hybrid models with different input and model configurations. Thirteen model configurations underwent testing in sixty-five catchments in southern Norway. The models, including LSTM networks, were trained on either one catchment (Local) or all catchments (Regional) and tested using two train/test periods and two objective criteria: Nash-Sutcliffe Efficiency (NSE) and Kling Gupta Efficiency (KGE). The validation scores for NSE and KGE during the two train-test periods were used for benchmarking. Daily observed climate and streamflow data stems from The Norwegian Water Resources and Energy Directorate (NVE), The Norwegian Meteorological Institute, Å Energi's internal databases and ECMWF (ERA5). We extracted digital elevation data, land cover types, and vegetation information from www.hoydedata.no and the CORINE Land Cover inventory. The key findings of the study shows that the data-driven model outperformed physically based models (SHyFT, DRM). Hybrid models, incorporating output from physics models and meteorological data, surpassed purely data-driven models. The most successful configuration involved two hybrid models, utilizing an LSTM network forced with outputs from physically based models and climate  forcings. The results clearly demonstrates that information about the physical hydrological processes enhance the LSTM model performance.
Solar radiation pressure modeling for BDS-3 MEO satellites precise orbit determination
Authors: Yang Chao , Guo Jing , Xu Xiaolong
Published: March 2024

The empirical CODE orbit model, including the 5-parameter reduced ECOM (ECOM1) and the 7-parameter extended ECOM model (ECOM2), is extensively utilized for solar radiation pressure (SRP) modeling of BDS-3 MEO satellites. This study shows that Satellite Laser Ranging (SLR) residuals of BDS-3 MEO satellites determined with the ECOM model display a systematic dependency with respect to β-angles or ε-angles. BDS-3 MEO satellites, characterized by a stretched satellite body and an extra SAR antenna carrying, contribute to the observed systematic variations. In this study, we established an a priori SRP model for BDS-3 MEO satellites using various approaches to enhance the ECOM. With these model, precise BDS-3 MEO orbits in 2023 were determined. SLR validation indicated that the systematic ε-angles or β-angles-dependent error was reduced. In general, a standard deviation (STD) of SLR residuals better than 4 cm was achieved, and also an improvement of 1–2 times over the five-parameter ECOM model was obtained.
Improving seasonal carbon dynamics in contrasting Mediterranean and Alpine grasslands
Authors: Seitz Josua , Yang Jinyan , Zhu Yu , Lacroix Fabrice , Zaehle Sönke , Luo Yunpeng , Schaumberger Andreas , Bahn Michael , Joseph Lumnesh Swaroop Kumar , Caldararu Silvia
Published: March 2024

Grasslands cover a substantial part of the global land area (~40%) and store about one third of the terrestrial carbon stock. These ecosystems and their significant carbon stocks are very susceptible to climate change and are often extensively managed for human use. Nevertheless, land surface models consistently fail to predict carbon fluxes in grasslands accurately, which is probably due to the lack of a good phenology module. Grassland vulnerability to climate change in combination with their large carbon stocks calls for an improved representation of grasslands in land surface models (LSMs) to accurately predict their fate under a changing climate. Here, we use data from two ecosystem manipulation experiments (MaNiP, Nitrogen and Phosphorus fertilisation in a Mediterranean tree-grass ecosystem and ClimGrass, drought, warming and elevated CO2 in a montane grassland) to improve the representation of carbon dynamics in  the LSM QUINCY. We built a novel turnover and growth model representation for both vegetative and reproductive plant pools in QUINCY based on ecologically realistic temperature and moisture controls as well as plant life history strategies. We show that the modified model can capture seasonality of productivity both in the seasonally cold and seasonally dry systems, under ambient and experimental conditions. This generalised model built upon manipulative experiments will improve global grassland productivity predictions.
Constraining the timing and spatial extent of an early Holocene ungrounding in the Weddell Sea using ice cores: how fast and how far-reaching?
Authors: Bauska Thomas , King Amy , Chapman Korina , Miller Shaun , Nehrbass-Ahles Christoph , Grieman Mackenzie , Fain Xavier , Capron Emilie , Mulvaney Robert , Wolff Eric
Published: March 2024

During the Last Glacial Maximum, the Antarctic ice sheet was significantly larger than today, holding an additional 6 to 14 meters sea level equivalent. Although less than 10% of the total glacial-interglacial range in eustatic sea level change, understanding the “when and where” of how Antarctica reconfigures during a deglaciation is crucial to understanding how the ice sheet will behave in the future. Some models show that many areas of the Antarctic ice sheet are inherently unstable during the Last Glacial Maximum and, when forced by increasing temperatures and rising sea level during the last deglaciation, undergo a rapid retreat to their present-day grounding line configurations (if not beyond).  In particular, the Ross and Weddell Sea regions, which are now largely covered by floating ice shelves, were susceptible to this “tipping point” behaviour.  Recently, evidence from the Skytrain Ice Rise ice core (~79°S, 078°W, 784m altitude) using water isotopes and total air content (a proxy for elevation) provided strong evidence that the Weddell Sea underwent such a transition about 8,000 years before present (BP) (Grieman et al., in press).Here we present new total air content data from the Fletcher Promontory ice core (~78°S, 082°W, 873m altitude) which also lies in the Weddell Sea region about 220 km from Skytrain Ice Rise site, with the fast-flowing Rutford Ice Stream situated in between. The data were measured with a novel, high-accuracy total air content system and span approximately 11,000 to 6,000 years BP with an average resolution of 150 years. The most notable feature is an 8.8 mmol/kg (+/-2.0) increase between 8,000 and 7,000 years BP. This confirms the shift observed in the Skytrain Ice Rise ice core (~6.6 mmol/kg) that has been attributed to a 430 ± 110 m drop in elevation. Using both Skytrain Ice Rise and Fletcher Promontory as the two independently derived elevation histories we will discuss the reliability of total air content as an elevation proxy as well as provide crucial constraints on state-the-art ice sheet model predictions of past “tipping point” behaviour.Grieman, M., Nehrbass-Ahles, C., Hoffmann, H., Bauska, T. K., King, A. C. F., Mulvaney, R., Rhodes, R. H., Rowell, I. F., Thomas, E. R., and Wolff, E. W.: Abrupt Holocene ice loss due to thinning and ungrounding in the Weddell Sea Embayment, Nature Geoscience, In Press.
Comparing space-based to reported carbon monoxide emission estimates for Europe’s iron and steel plants.
Authors: Leguijt Gijs , Maasakkers Joannes D. , Denier van der Gon Hugo A.C. , Segers Arjo J. , Borsdorff Tobias , Aben Ilse
Published: March 2024

Carbon monoxide (CO) is an air pollutant that plays an important role in atmospheric chemistry and its emissions can serve as a proxy for CO2emissions. Within the European Union, large industrial emitters are required to report their annual facility-level emissions to the European Pollutant Release and Transfer Register (E-PRTR) based on stack measurements or calculations. We use TROPOMI satellite observations of carbon monoxide concentrations to estimate the emissions and compare these to the E-PRTR reports. Since 2018, the TROPOMI satellite instrument observes carbon monoxide concentrations at a resolution down to 5.5x7 km2with daily global coverage. CO plumes from large iron and steel plants are clearly visible in the TROPOMI data, enabling us to estimate the plants’ annual emissions. To achieve this, we perform high-resolution atmospheric transport simulations with the WRF model for 2019 over the 21 highest emitting iron and steel plants in Europe. We combine the simulations with TROPOMI observed concentrations in an analytical inversion to estimate the annual emission rates of the individual plants using the E-PRTR emissions as prior estimates. The TROPOMI-based emission estimates generally agree well with the reported emission rates (R2 = 0.87) while showing limited sensitivity to the prior emission estimate. For 10 out of 21 plants the reported and TROPOMI-estimated emission rates agree within 20% whereas 6 plants show discrepancies over 40%. For the plants with the largest emissions, we perform an additional emission quantification using the Cross-Sectional Flux (CSF) method, which does not use any prior knowledge. These CSF estimates are consistent with the inversions, providing additional confidence in the space-based emission estimates. For two plants for which the 2019 inversion-based emission estimates are significantly different from the reported emission rates, we extend our analysis to 2020. The inversion estimates for 2020 agree with those from 2019 and match with reported emissions for 2020, raising questions on reported emissions for 2019. Our work shows that we can use the TROPOMI observations to reliably estimate CO emissions from large iron and steel plants and how these analyses can be used to identify uncertainties in reported emissions.
Bridging the gap between scientists and policymakers: the experience of the H2020 CORE project 
Authors: Russo Raffaella , Gargiulo Maria Vittoria , Capuano Paolo , Staniforth Andrew , Amaratunga Dilanthi , Ruggiero Aino , Duca Gabriella , Dallo Irina , Komendatova Nadejda , Scott Melissa , Bonnamour Marie-Christine , Amoroso Ortensia , Piotrowicz Wojciech
Published: March 2024

Shaping and favoring informed-based decisions is a pivotal responsibility for both scientists and policymakers. Lessons and insights drawn from analyzing past disasters should be documented and shared transparently, using clear and inclusive language. This facilitates identification of challenges that policymakers might face in implementing such findings, especially obstacles arising from end-users, such as citizens.The H2020 CORE EU project entails developing public guidance for enhancing community readiness for emergencies, covering pre-event and post event-response knowledge, and consolidating findings into an accessible online repository, extending availability of findings beyond the project's duration.The CORE project is aimed at building a chain of trust, credibility and citizen engagement, providing guidance and recommendations for policymakers and society, and distilling the project's essence into actionable advice, starting from case studies from Europe and beyond (i.e. L’Aquila earthquake,  Italy (2009), Manchester arena bombing, UK (2017), Venkatapuran industrial accident, India  (2020), Aude region flash flooding, France  (2018), Great east Japan earthquake and tsunami, Japan  (2011), Jerusalem wildfire, Israel (2021), and finally Covid-19 pandemic (2020-2023)).Among its main achievements, CORE has produced a standardized system  template able to analyse disaster case studies, with the aim of fostering transparency and uniformity in data collection and simplifying comparisons across diverse EU regions. Moreover, the project has issued recommendations to governments aimed at enhancing companies' resilience in the face of supply chain disruptions to reduce goods shortages. Additionally, a safety culture toolkit within the Disaster Risk Reduction (DRR) context was developed, catering to diverse stakeholders, such as citizens, public authorities, and practitioners.Furthermore, the project provided guidance to policymakers on understanding the public’s consumer behaviours of available information, identifying information needs, and determining preferred communication channels. Specifically, the initiative from CORE included recommendations to counter misinformation both before, during, and after disastrous events.This work has been supported by the CORE ("sCience and human factor for Resilient sociEty") project, funded by the European Union’s Horizon 2020 research and innovation program under grant agreement No 101021746.
Statistical Post-Processing for Wind Gust and Precipitation Extremes: Insights from a Pre-Operational System
Authors: Kıvrıl Harun , François Bastien , Schmeits Maurice , Whan Kirien , van der Kooij Eva , Squintu Antonello
Published: March 2024

Effective forecasting of weather events, especially extremes, is critical for minimizing potential damage and ensuring public safety. Yet, ensemble forecasts that allow to represent uncertainty in weather predictions like ECMWF-ENS suffer from biases and dispersion issues. These shortcomings decrease the forecasting skill and introduce the need for statistical post-processing methods like Ensemble Model Output Statistics (EMOS) and Quantile Regression Forest (QRF) to enhance the forecast quality. While these methods increase overall forecasting performance in general, their capability to handle extreme events varies. To strengthen the forecasting of these critical events, a closer examination and potential refinement of the statistical post-processing methods are necessary, along with the development of methods tailored to extreme weather events. This study analyzes the performance of pre-operational post-processing models of ECMWF-ENS wind gust and precipitation forecasts in the Netherlands using EMOS and/or QRF techniques. The skill of the models (using Continuous Probability Ranked Skill Score (CRPSS) and Brier Skill Score (BSS)) for both wind gusts and precipitation is demonstrated. Besides, by focusing on windstorm Poly (July 5th, 2023) and a heavy rain case (June 22nd, 2023), the capabilities of the methods in forecasting specific extreme events are investigated. While the QRF forecasts for the heavy rain case show better skill than for the raw forecasts, for the Poly storm case the post-processed models performed worse than the raw forecasts initially. Thus, this work concentrates on the underlying reasons for the limited performance on that event and proposes an error modeling approach to enhance the post-processing performance of the storm event without compromising the overall forecasting performance. 
Pre-dawn water potential determines stomatal sensitivity to vapor pressure deficit in trees
Authors: Peters Richard L. , Arend Matthias , Zahnd Cedric , Hoch Günter , Kahmen Ansgar
Published: March 2024

The balance between terrestrial carbon assimilation and water loss is optimized by stomatal control in leaves. The response of stomatal conductance to increasing vapor pressure deficit (VPD) is critical in the context of climatic change and highly variable between tree species and environments. Why this variability in VPD sensitivity exists is still largely unknown. Yet, as the regulatory cues initiating closure remain unclear, current simulations of forest water use face significant uncertainty.To address this knowledge gap for most of the common European tree species, we present data measured regularly in the crowns of mature trees growing in a natural forest at the Swiss Canopy Crane II (SCCII) site (Basel, Switzerland). We used three years of repeated stomatal conductance measurements across the growing season performed at the leaf level (over 1000 measurements), in combination with concurrent diel leaf water potential measurements and VPD monitoring of over 80 individuals.We show that pre-dawn, rather than the expected midday, tree water status is more critical in adjusting the stomatal closure responses to increasing VPD. A striking reduction can be found in this VPD sensitivity when pre-dawn leaf water potential approaches -1.2 MPa, independent of the species. Only above this threshold, i.e., when trees were well-hydrated, did the species show variance in midday stomatal sensitivity to VPD. This aligns with the commonly adopted hydraulic safety-efficiency theorem for explaining species-specific variance.We argue that daytime canopy conductance does not solely optimize assimilation against the risk of cavitation, which commonly happens during high midday VPD. Rather, our novel finding suggests that mature trees might adjust their water-use strategy to sustain high nighttime turgor pressure (as required for sugar transport and growth), although the regulating mechanisms are yet unknown. The discovery of this uniform pre-dawn threshold across species is particularly critical for reducing uncertainty when modeling forest water use responses to VPD.
Contribution of DORIS System to Global Ionospheric Scintillation Mapping
Authors: Cherrier Marie , Yaya Philippe
Published: March 2024

Ionospheric scintillations due to ionosphere irregularities may severely degrade GNSS data in equatorial and high latitudes regions, and consequently the applications that rely on such data. It is thus of high importance for many users in a large variety of applications to have access to global maps of scintillation intensity, for both signal phase and amplitude. Typically, networks of ground based GNSS receivers are used to derive those maps, but it inevitably leads to sparse coverage. In order to mitigate this weakness, the current study proposes to add original data points based on the DORIS system. DORIS (Doppler Orbitography by Radiopositioning Integrated by Satellite) is a French orbitography system, developed primarily for altimetric purposes by the Centre National d’Etudes Spatiales (CNES), the Institut National de l’information géographique et forestière (IGN) and the Groupe de Recherche de Géodésie Spatiale (GRGS). It consists of a network of around sixty ground-based beacons emitting a radio-frequency signal at 400 MHz and 2 GHz. The on-board receivers (on 9 civilian satellites as of January 2024) then performs Doppler shift measurements that allow precise orbit determination.  Despite a lower data rate (0,1 Hz instead of 1 Hz for the GNSS) and a lower number of satellites, DORIS can add valuable information where there is no GNSS receivers, or by taking advantage of its geometry, in particular with polar satellites. In this study, we will explore to what extent it is possible to define scintillation proxies based on DORIS data losses, phase signal degradation, or power signal attenuation, by a comparison to a scintillation data base from GNSS measurements. Eventually, we will discuss whether the challenging near-real time basis delay is achievable. 