bluuebunny/crossref_metadata_2025 huggingface dataset:
Green Urban Equity: Analyzing the 3-30-300 Rule in UK Cities and Its Socioeconomic Implications
Authors: Zuñiga-Gonzalez Andres , Madhavapeddy Anil , Bardhan Ronita
Published: March 2024

Green spaces in cities have been demonstrated to offer multiple benefits to their inhabitants, including cleaner air, shade in sunny periods, and a place that contributes to mental well-being. In addition, trees in cities are home to several species of animals and work as a nature-based solution that can sequester CO2 and regulate water storage in urban ecosystems. The 3-30-300 rule space rule has been suggested as a strategy for city planners regarding urban forestry. This rule states that every resident’s home or workplace should be close to at least three trees, every neighbourhood should have a 30% canopy cover, and every citizen should have access to a public green space within a 300 m radius. Following this rule guarantees that all citizens obtain all the benefits of urban vegetation; however, this is not the case for all areas, particularly those impoverished ones where access to green spaces is limited, further contributing to social inequality. This study delves into the implementation of this rule across major UK urban areas, employing a blend of remotely sensed imagery, census data, ordnance surveys and machine learning methods. Our findings offer vital insights for city planners, emphasizing the need for a strategic approach to urban green space distribution that fosters social equity and environmental sustainability.
Biodiversity Assessment in Drylands Using Augmented Satellite Imagery Through Deep Learning Models
Authors: Rodríguez Jorge , Johansen Kasper , Cheng Hua , Alwahas Areej , Angulo-Morales Victor , Almashharawi Samer , McCabe Matthew F.
Published: March 2024

As global biodiversity faces increasing threats from climate change, habitat loss, and human activities, effective methods for assessing and monitoring biodiversity are crucial. Drylands are particularly vulnerable to the impacts of climate change, and integrating remote sensing technology with ecological research can help protect these environments. Identification of individual trees and shrubs is fundamental to assess biodiversity and can also improve carbon stocks estimates. However, identifying individual trees using medium resolution satellite images is often not feasible. The use of advanced technologies, such as machine learning and satellite imagery in environmental management plays a key role in biodiversity conservation and can potentially fill this gap. The use of readily available Maxar satellite imagery makes conservation approaches accessible and cost-effective, which is crucial for widespread adoption, especially in resource-limited settings or for large-scale studies. This study aims to improve the identification of vegetation in dryland ecosystems by integrating deep learning methods to remote sensing. The primary objective was to distinguish vegetation from rocks or shadows in these areas, which is often challenging due to the dark appearance of vegetation and the similar visual features of the landscape, such as landforms textures, water bodies or man-made objects.. To address this challenge, a Vision Transformer (ViT) deep learning model was developed to estimate near infrared (NIR) spectral bands from high resolution Maxar Satellite images. By enhancing the spectral richness, the model aids in the differentiation of vegetation. Maxar satellite imagery was primarily used because of its accessibility through Google services, making it ideal for planning initial surveys to identify areas of interest for more detailed study. The accuracy of the model was validated against high-resolution SkySat NIR imagery, and achieved an R2 of 0.92. The obtained NIR band helped to clearly distinguish vegetation from non-vegetative surfaces such as soil, rocks, and water, which were not as discernible in RGB imagery alone. The use of a deep learning method to estimate a synthetic NIR band proved to be cost-effective and efficient for large-scale identification of individual trees and shrubs in drylands, overcoming the limitations of medium-resolution satellite imagery. The findings of the study are crucial to the conservation of biodiversity and offer a practical approach for environmentalists and researchers. Future work includes expanding the dataset to include various dryland environments, and integrating additional data sources such as soil data and topographic features for a more comprehensive analysis.
Towards an Ethics of Modeling and Data Use for Actionable Climate Science
Authors: Morrison Monica
Published: March 2024

Considerable risk is involved in the use of climate models or their products (i.e., simulations and data) when there is a lack of adequacy or fitness for one’s purpose. Of specific concern is the risk of generating information in response to an actionable or applied question or aim that is irrelevant, misleading, inappropriate, inconsistent, or highly inaccurate, as this can lead to downstream harms such as maladaptation. This form of “misuse” is innocent or unintentional, and is largely a function of a user’s misunderstanding or misinterpretation of the intended purposes of a model and/or modeling exercise and the applicability of the model’s products. Ineffective communication and lack of transparency into the intended purposes, assumptions, representational features, adequacies, as well as inadequacies and limitations of a model, can lead to this form of inappropriate and unjustified repurposing. Currently, there is an increase in the demand for open and accessible data, and an increase in the use of climate data, especially data from high-resolution modeling efforts, for applied and actionable purposes (contexts in which derived products are used to inform decision-making). Given both conditions, the reduction and management of possible inappropriate repurposing, i.e., misuse, has become a highly salient consideration for any modeling effort. Producers of models and their products have a moral duty to implement mechanisms to aid users in the identification, understanding, and control of this risk. This can happen by way of the distribution of expert guidance, increase in intentional transparency, and instantiation of systematic norms for clearly and plainly communicating the fitness of purpose and inadequacies of models and their products. This would provide a large step forward toward the reduction of misuse of information in climate science that could lead to harmful consequences, and pave the way for the development of an ethics of scientific practice for the climate science community.
The spatial distribution of Zn and Cd across the soil microscale architecture as mediated by different mineral phases in a supplemented arable soil
Authors: Schweizer Steffen A. , Bachelder Jill , Hoeschen Carmen , Frossard Emmanuel , Wiggenhauser Matthias
Published: March 2024

Zinc (Zn) is an essential trace element for human nutrition as well as for plant growth and soil organisms. Cadmium has similar biogeochemical properties like Zn, but is non-essential for most biota and highly toxic. Due to the on the heterogeneous arrangement of soil mineral phases and organic compounds within a functional soil architecture, there is a lack of knowledge on how the microscale arrangement is interrelated with ecosystem-relevant soil functions such as the storage and cycling of nutrients and contaminants. Here, we present an analytical approach aiming to resolve the spatial distribution of Zn and Cd in a soil at the microscale. Zn and Cd were supplemented in three increasing concentrations to an arable soil from the Jura region, Switzerland. Our image-based investigation was obtained using a dual primary ion source workflow by Nanoscale secondary ion mass spectrometry (NanoSIMS) combining the Cs+ and the RF plasma O− source. The dual workflow enabled correlating the distribution of Zn and Cd with Fe, Al, Si, P, Mg, Ca, S, C and N at a lateral resolution of 120nm. Our observations indicate a high co-localization of Zn and Cd hotspots, whereas these were not related with organic matter patches. Of the three mineral phases identified using a machine-learning image segmentation, most areas were occupied by Al-dominated regions followed by Si-dominated and Fe-dominated parts. Across the increasing supplementation, the Zn and Cd hotspots were preferably co-localized to mineral phases in the following order: Fe-dominated > Al-dominated > Si-dominated. With increasing Zn and Cd supplementation, the Cd/Zn ratio as well as the N/C ratio decreased indicating changes in the biochemical composition of . Our model soil approach illustrates how the spatial arrangement of essential and toxic trace elements at the microscale regulates their fate in the soil. The developed NanoSIMS-based dual primary ion source workflow enables emerging opportunities to characterize how environmental changes affect the spatial distribution of nutrients and contaminants in dynamic soil architectures.
Nitrogen sources, retention and exports in the Hunze, Rhine and Elbe river basins
Authors: Liu Xiaochen , van der Heijden Luuk , Rozemeijer Joachim , Troost Tineke , Blauw Anouk
Published: March 2024

The study focused on simulating the long-term flux of Nitrogen (N) from source to mouth in the Hunze, Rhine, and Elbe river basins. This was achieved by integrating models that encompass hydrology, nutrient input to surface water, and in-stream retention. The aim was to comprehensively understand the spatial and temporal distribution of N sources, soil budget, delivery to streams, and in-stream retention across these basins. Notably, significant improvements in water quality were observed in these rivers following decades of efforts aimed at reducing nutrient pollution from agricultural and sewage sources. These improvements have brought the water quality close to the EU standard of 2.5 mg/L. However, it was observed that post-2000, the decline in N concentration stagnated. This study elucidates the long-term dynamics of N sources and their contribution to surface water in the three basins. The findings, which offer a spatially explicit nutrient source allocation, are crucial for strategically targeting nutrient reduction policies to foster sustainable water quality management.
Hydropeaking on fish physiological stress
Authors: Bejarano Maria Dolores , Hernández-Marchena Raul , De la Llave-Propín Álvaro , Bianucci Paola , Fazelpoor Khosro
Published: March 2024

Research on impacts of hydropeaking on river ecosystems has increased in the last years. For fish, much literature reports stranding and behavior changes, but physiological stress is less understood. In this study, we simulated a natural-flow scenario and five hydropeaking operating scenarios varying in frequency, duration and fall rate of the inundations, and water velocity and level in our Greenchannel facility, which is a mesocosm of fluvial ecosystem. 15 different rainbow trouts (Oncorhynchus mykiss) each time were subject to a scenario during 24 hours, measuring several physiological parameters at the end of the trials: Cortisol, CPK (Creatine Phosphokinase), LDH (Lactate Dehydrogenase), Triglycerides, Lactate, NEFA (Free Fatty Acids) and skin color. Results show how levels of these parameters change significantly in response to higher intensities of hydropeaking, which may lead to bad performance or death in the long term.
Modern-day mass gains over East Antarctica exceed the two decades prior
Authors: Medley Brooke , Sutterley Tyler
Published: March 2024

The recent Ice sheet Mass Balance Inter-comparison Exercise (IMBIE) suggests that between 2012 and 2017 the East Antarctic Ice Sheet was approximately in balance, experiencing a rate of mass change of 23 ± 38 Gt yr-1.  While this study provided an important statistical reconciliation of various studies across several techniques, the root cause of the differences amongst the estimates remains unresolved.  Satellite gravimetry provides a direct measurement of mass change; however, it is sensitive to all mass changes, and the necessary corrections for solid earth changes are substantial and poorly constrained.  Satellite altimetry provides measurements of volume change, which includes changes in ice mass and non-ice mass.  The latter is largely driven by changes in the density of the snow and firn requiring poorly constrained models for conversion to mass.  Here, rather than deriving ice-sheet mass balance using a single technique, we use both satellite gravimetry and altimetry to better: (1) reconcile mass balance estimates between the two techniques, (2) improve constraint on firn dynamics, and (3) attempt to partition the driver of change.  Because these two measurements are sensitive to different processes, using them in conjunction provides additional constraint of the most unknown processes.Our new technique solves for the change in total firn air content through time for the entire Antarctic Ice Sheet that provides a best-fit mass solution between altimetry and gravimetry.  In such a way, we produce ice-sheet mass change at the fine-scale resolution of ice elevation measurements (10 km) that best matches the coarsely resolved (>100km) mass change from gravimetry.  Our results indicate that during the ICESat-2 era (April 2019 through June 2023), the East Antarctic Ice Sheet gained mass at a rate of 160 Gt yr-1, three times the average mass gain over the two decades prior (52 Gt yr-1).  The sector that spans 60E to 130E received the largest anomalous gains in mass (precipitation).  These gains, in conjunction with minor gains from the Antarctic Peninsula (23 Gt yr-1), fully balance the continued mass losses from West Antarctica (-139 Gt yr-1).  Large precipitation events over both East Antarctica and the Antarctic Peninsula are driving the mass gains; however, more time is needed to determine whether these changes are long-term or only short-lived given the ICESat-2 time series is just over 4 years in length.  These results suggest that atmospheric dynamics play a key role in driving the mass balance of the East Antarctic Ice Sheet and have potential to rapidly change the overall mass balance of the ice sheet.
Methodological Developments in the International Land Model Benchmarking Effort
Authors: Collier Nathan , Hoffman Forrest , Lawrence Dave
Published: March 2024

As earth system models (ESMs) become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model performance. The International Land Model Benchmarking (ILAMB) project is a model-data intercomparison and integration project designed to improve the performance of land models and improve the design of new measurement campaigns to reduce uncertainties associated with key land surface processes. While the effort has been established for over a decade, we continue to make developments and improvements in order to incorporate new datasets as well as adapt our scoring methodology to be more useful for model developers in identifying and diagnosing model errors.The version 2.7 release of the ILAMB python software includes new datasets for gross primary productivity and latent/sensible heat flux (WECANN: Water, Energy, and Carbon with Artificial Neural Networks), growing season net carbon flux (Loechli2023), biomass (ESACCI: European Space Agency, Biomass Climate Change Initiative and XuSaatchi2021), methane (Fluxnet), and surface soil moisture (Wang2021). In addition to these land-focused datasets, ILAMB v2.7 marks the first release of the International Ocean Model Benchmarking (IOMB) package. While the codebase remains the same as is used with the land, this release encodes datasets and configuration file to be used in benchmarking ocean models.Finally, we present a shift in the ILAMB scoring methodology. In order to make errors comparable across different areas of the globe, ILAMB originally employed a normalization of errors by the variability of the reference quantity in a particular location. For many variables, this choice tends to strongly weight performance in the tropics and consequently does not give a balanced perspective on model performance across the globe. To balance performance across the globe, we propose a shift to normalize errors by regional error quantiles. We select regions which conform to traditional understanding of biomes in order to focus on areas where we expect errors to be commensurate in the order of magnitude. We then choose a normalizing quantity by taking a quantile of the errors in these biomes across a selection of CMIP5 and CMIP6 era models. In this way, we contextualize the scores by using the performance of the recent generations of models.
Mapping the environmental risk associated to water quality of marinas in Portugal
Authors: Mundt Neele , C. Neves Maria , Cravo Alexandra
Published: March 2024

The growth of tourism and demographic pressure along the Portuguese coast is accompanied by an increasing demand for nautical recreational activities, which has a negative impact on water quality. This study aims to provide decision-makers, such as government agencies and harbor managers, with scientifically-based information to manage marinas and neighboring waterfronts. The goal is to balance environmental protection with economic and social objectives. The assessment follows the Pressure-State-Response (PSR) model, integrating environmental pressures, conditions, and societal responses in the following sequence: (a) build a database with information necessary to determine the environmental impacts of identified pressure activities, such as navigation, port operations, dredging, oil pollution, coastal litter, and nearby industrial activities; (b) identify specific environmental conditions at each marina by mapping and evaluating susceptibility, ecological value, and naturalness using Geographic Information Systems tools; (c) consider locally implemented management strategies to mitigate or prevent negative environmental effects from human pressures; and (d) establish risk thresholds, categorize pressures, states, and responses, and map spatial variations of risk factors. This approach, originally proposed to evaluate the environmental risk of marinas along the Spanish coast, is now being extended to 27 marinas along the west and south Portuguese coast. The resulting maps visually compare risks across different marinas, facilitating the analysis of the effectiveness of operational management measures and instruments. This aids stakeholders and decision-makers in establishing priorities for intervention plans aimed at enhancing water quality.  This work was funded by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) –UIDB/50019/2020 (https://doi.org/10.54499/UIDB/50019/2020),UIDP/50019/2020 (https://doi.org/10.54499/UIDP/50019/2020) andLA/P/0068/2020(https://doi.org/10.54499/LA/P/0068/2020). 
UXarray: Extensions to Xarray to support unstructured grids
Authors: Eroglu Orhan , Chen Hongyu , Chmielowiec Philip , Clyne John , DeCiampa Corrine , Hannay Cecile , Jacob Robert , Jain Rajeev , Loft Richard , Medeiros Brian , Sun Lantao , Ullrich Paul , Zarzycki Colin
Published: March 2024

The arrival of kilometer-scale climate and global weather models presents substantial challenges for the analysis and visualization of the resulting data, not only because of their tremendous size but also because of the employment of unstructured grids upon which the governing equations of state are solved. Few Open Source analysis and visualization software tools exist that are capable of operating directly on unstructured grid data. Those that do exist are not comprehensive in the capabilities they offer, do not scale adequately, or both. Recognizing this gap in much-needed capability, Project Raijin - funded by an NSF EarthCube award - and the DOE SEATS project, launched a collaborative effort to develop an open source Python package called UXarray. UXarray extends the widely used Xarray package, providing support for operating directly (without regridding) on unstructured grid model outputs found in the Earth System Sciences, such as CAM-SE, MPAS, SCRIP, UGRID, and in the future, ICON. Much like Xarray, UXarray provides fundamental analysis and visualization operators, upon which more specialized, domain-specific capabilities can be layered. This talk will present an overview of the current capabilities of UXarray, provide a roadmap for near term future development, and will describe how the Pangeo community can contribute to this on-going effort.
Kinematics of the jamming front resulting from the clogging of the flow of monodisperse inelastic particles in a partially obstructed chute
Authors: L Ferreira Rui M , Mendes Solange , Aleixo Rui , Amaral Amaral , Larcher Michele
Published: March 2024

We characterize experimentally the upstream-progressing jamming wave triggered by the clogging of a granular flow down a partially obstructed chute. We generated dry granular flows in a sloping chute whose outlet was obstructed by a wall with two vertical gaps, twice the diameter of the granular material. We conducted 31 repetitions of the same test to obtain stable statistics. We employed Particle Tracking Velocimetry (PTV) to determine particle velocities at the sidewall and estimated fields of mean velocity and granular temperature by ensemble-averaging. Each ensemble is a set of valid grain velocities collected in space-time bins, that map the entire domain, over all test repetitions. The system is highly dissipative due to collisions and enduring contacts among inelastic particles, resulting in generalised cooling. Clogging occurs as a consequence of the formation of stable arch-like structures at the outlet, while the flow cools down. We observe that the jamming wave propagates against the flow at different values of granular temperature and mean velocity. There is no triple point in the system in the sense that jamming is always preceded by gas-liquid transition. For the tested conditions, jamming can be described as an accretion problem, leading to a granular solid state from liquid state and never from the gaseous state. The jamming wavefront progresses faster as the values of the granular temperature decrease. Flow cooling, including gas-fluid transitions, seem independent of jamming, which is compatible with the range of observed granular Froude and Mach numbers. The jamming wavefront becomes faster than the adiabatic speed of sound of the granular material moving towards the jammed region. Acknowledgements: This work was partially funded by the Portuguese Foundation for Science and Technology (FCT) through Project DikesFPro PTDC/ECI-EGC/7739/2020 and through CERIS funding UIDB/04625/202
Sustainability Analysis of Climate Change Mitigation Measures to Support Community Adaptation against Compound Flooding
Authors: Davani Hassan
Published: March 2024

Results from our recent social survey show that the residents of the City of Imperial Beach (IB) are interested in utilizing rain barrels, a rainwater harvesting (RWH) technique, which can provide flood mitigation and a decentralized water supply. IB experiences compound flooding from intense rainfall combined with sea level rise induced groundwater table rise and overtopping from high waves. A city-wide implementation of RWH has been modeled in the software PCSWMM, where simulated results show a reduction in usually flooded areas with the implementation of rain barrels. This study aims to use GaBi, an LCA software, to analyze the sustainability of the production, installation, and disposal of rain barrels. Currently, existing flood mitigation and stormwater management for the City of IB requires the use of heavy machinery to physically remove water from city streets, and routine pumping of stormwater. This study uses GaBi, to determine the global warming potential of (GWP) and human toxicity potential (HTP) of existing and proposed stormwater discharges and management strategies. The GWP and HTP of the existing situation is compared with a mitigation scenario where a portion of the stormwater is collected in rain barrels, thus (i) reducing need for routine pumping and water removal from streets and (ii) reducing the strain on the centralized water distribution system. Preliminary results show that implementing rain barrels in the Imperial Beach community significantly decreases GWP, but increases HTP. For instance, city-wide implementation of rain barrels, with the total collection of over 10 billion gallons of rainwater in 20 years, could lead to a saving of 29 million kilograms of Carbon Dioxide (CO2) equivalent.
The fate of Greenland Ice Sheet supraglacial lakes in a warm and cool year
Authors: Subramanian Aneesh , Dunmire Devon , Hossain Emam , Gani Md Osman , Banwell Alison , Myers Brendan
Published: March 2024

Supraglacial lakes form on the surface of the Greenland Ice Sheet during the summer months and can directly impact ice sheet mass balance by removing mass via drainage and runoff or indirectly impact mass balance by influencing ice sheet dynamics. Here, we utilize the growing inventory of optical and microwave satellite imagery to automatically determine the fate of Greenland-wide supraglacial lakes during 2018 and 2019, a cool and warm melt season respectively. We use a machine learning time series classification approach to categorize lakes into four different categories: lakes that 1) refreeze, 2) rapidly drain, 3) slowly drain, and 4) become buried lakes at the end of the melt season. We find that during the warmer 2019, not only was the number of lake drainage events higher than in 2018, but also the proportion of lakes that drained was greater. By investigating mean lake depths for these four categories, we show that drained lakes were, on average, 22% deeper than lakes that refroze or became buried lakes. Interestingly, drained lakes had approximately the same maximum depth in 2018 and 2019; however, lakes that did not drain were 29% deeper in 2018, a cooler year. Our unique two-year dataset describing the fate of every Greenland supraglacial lake provides novel insight into lake drainage and refreeze in a relatively warm and cool year, which may be increasingly relevant in a warming climate.
Similarities and differences between natural and simulated slow earthquakes
Authors: Gualandi Adriano , Dal Zilio Luca , Faranda Davide , Mengaldo Gianmarco
Published: March 2024

Earthquakes are understood as frictional instabilities taking place in weak zones of the Earth crust called faults. On the one hand, the lengthy recurrence time of earthquakes makes numerical simulations an invaluable tool to study consecutive ruptures of a given fault. On the other hand, it makes a direct comparison with nature difficult, if not currently impossible. Slow earthquakes, exhibiting lower recurrence times, serve as a viable alternative for validating models against real-world observations. We investigate similarities and differences between natural and simulated slow earthquakes using nonlinear dynamical system tools. We focus on slow earthquakes derived from Global Navigation Satellite System (GNSS) position time series in Cascadia and numerical simulations intended to reproduce their pulse-like nature and scaling laws. We provide metrics to evaluate the accuracy of simulations in mimicking slow earthquake dynamics, and we investigate the influence of spatio-temporal coarsening as well as observational noise. Findings indicate that numerical simulations exhibit average properties akin to natural occurrences. In addition, despite the usage of many degrees of freedom in numerical simulations, we retrieve a low average dimension, like the one obtained for Cascadia slow earthquakes, suggesting that a reduced order model may be a viable representation of slow slip events. Time-dependent, instantaneous properties show strong dependence on the variable considered for the analysis for numerical simulations, but not for natural observations. Our exploration show a possible way to extract dynamic attributes from kinematic information, and enriches the picture that we have of natural-scale friction We propose to use the suggested metrics as an additional tool to narrow the divergence between slow earthquake observations and dynamical simulations.
Modeling Post-Wildfire Rainfall Events in the Santa Cruz Creek Watershed using HEC-HMS and GSSHA
Authors: Walters Avery , Pradhan Nawa Raj , Floyd Ian , Lakshmi Venkataraman
Published: March 2024

The 2007 Zaca Fire burned about 240,000 acres of land north of Lake Cachuma, which supplies water to Santa Barbara, CA. USGS Streamgage 11124500 was able to record pre and post-fire stream discharge for the affected Santa Cruz Creek Watershed, of which 67% was burned. 80% of this burn was severe, which raises concern for extreme flood events following the wildfire. It has been observed that the extreme temperatures in wildfires not only damage vegetation but soils as well -- wildfires much more so than comparatively mild prescribed burns. Our research proposes analyzing precipitation and stream discharge data from the affected Santa Cruz Creek Watershed to quantify the effects of such widespread and severe wildfire. This study uses the Hydrologic Modeling System (HEC-HMS) from the Army Corps of Engineers (ACE) to perform event-based, lumped modeling. It also uses Gridded Surface Subsurface Hydrologic Analysis (GSSHA) to perform physics-based modeling of the same watershed. Doing so should deepen our understanding of the effects of increasingly common and severe wildfires on watershed characteristics like infiltration and streamflow.
GHOTI: Using the GOES-R EXIS/SPS detectors to create a low-latency, high-cadence, TSI proxy and spectral models
Authors: Penton Steven , Snow Martin , Béland Stéphane , Woodraska Don , Coddington Odele
Published: March 2024

The GOES-R series of geostationary satellites include a redesigned instrument for solar spectral irradiance: the Extreme ultra-violet and X-ray Irradiance Sensor (EXIS). Our team will be using the Sun Position Sensor (a set of high-cadence broadband visible light diodes) on GOES-16 and GOES-18 EXIS instruments to construct a high-cadence proxy for Total Solar Irradiance (TSI). This has two advantages over the existing TSI measurements: 1) the measurements are taken at 4 Hz, so the cadence of our TSI proxy is much faster than existing measurements, such as the 6 to 24-hour measurements produced by SORCE or TSIS-1, and 2) from a geostationary position, the time series of measurements is virtually uninterrupted.Our calibration of the GOES-R EXIS diode measurements includes thermal and sun-satellite distance corrections, while the irradiance calibration relies on TSIS-1 TIM TSI composites. Another measurement from GOES-EXIS that will be used is the Magnesium II core-to-wing ratio. The MgII index is a proxy for chromospheric activity and is measured by EXIS every 3 seconds. The combination of the two proxies is used to generate a model of the full solar spectrum similar to the NRLSSI2 empirical model.We are in the final year of a four-year grant to develop the TSI proxy and the SSI model.
Towards optimizing the operation of controlled flood detention basins
Authors: Ruf Mara , Straub Daniel
Published: March 2024

Floods are one of the most hazardous natural phenomena worldwide and they are predicted to increase both in intensity and frequency due to climate change. This necessitates comprehensive flood risk mitigation measures that are planned and controlled from a regional as well as a strategic trans-regional perspective.Controlled flood detention basins can be effective measures for dealing with extreme flood events [1]. By temporally storing water in the detention basin, the discharge in a river is reduced. If the water is removed from the river at the optimal time, this should reduce the peak water level at downstream locations and hence the flood risk.However, the identification of the optimal operation of flood detention basins is a non-trivial as well as non-deterministic problem. Flood forecast uncertainty, dilatation of the wave along the river channel and the uncertainty in the breaching process turns the polder operation into a stochastic optimization problem with multiple possible optimization targets. Hence, this optimization belongs to the class of sequential decision problems under uncertainty. In this contribution, we utilize a developed dynamic-probabilistic flood risk model [2] to analyze and optimize different control strategies as well as the effect of uncertainties on the optimality of the detention basin operation. We consider the case of a single detention basin as well as that of multiple detention basins that are arranged in series. [1] De Kork, J.-L.; Grossmann, M. (2009): Large-scale assessment of flood risk and the effects of mitigation measures along the Elbe River. Natural Hazards (2010) 52:143-166.[2] Ruf, M., Hoffmann, A., Straub, D. (2023): Application of a decision sensitivity measure for the cost-benefit analysis of a flood polder at the Bavarian Danube. 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP 14). Dublin, Ireland.
Radiative Forcing Assessment of Black Carbon in Snow from the Antarctic Peninsula 
Authors: Cereceda-Balic Francisco , Ruggeri María Florencia , Barcaza Gonzalo , Fadic Ximena , Moosmüller Hans
Published: March 2024

The pristine Antarctic environment, despite its remoteness, is not immune to the influence of anthropogenicpollutants. This study focuses on quantifying the Radiative Forcing (RF) resulting from Black Carbon (BC)concentrations in snow samples collected from various points on the Antarctic Peninsula during the austral summerof 2023, aiming to assess the impact of BC on the snowpack albedo and, consequently, on the regional climate. To thebest of our knowledge, in most of the locations studied, BC concentrations in snow have never been measured before.Snow samples were meticulously collected from different locations on the Antarctic Peninsula, covering a diverserange of environments, including base surroundings, remote locations, and icebergs. This effort was undertaken aspart of the ECA59 campaign, funded by the Chilean Antarctic Institute (INACH). The sampling constituted the initialphase of a project involving three distinct sampling periods. Specifically, the collection sites were situated in theeastern sector of the peninsula, known for its minimal human presence and limited prior research, making it arelatively unexplored region. BC concentrations in our snow samples were measured following the method describedin Cereceda-Balic et al. (2022, https://doi.org/10.1016/j.envres.2022.113756). To understand the BC RF, the SNICAR(SNow, ICe, and Aerosol Radiation) model was employed to simulate snow albedo for measured BC concentrations.This methodology allowed for an assessment of the potential BC-induced changes in albedo and the resulting RF. Theanalysis revealed a significant range of BC concentrations in Antarctic snow samples, spanning from 2.4 to 1157 ng g-1. Simulating snow albedo using the SNICAR model indicated BC-induced albedo reductions of up to 20% relative to clean snow. The calculated BC-induced RF reached up to 38 W m-2, indicating a substantial climatic impact of BC in the Antarctic Peninsula region.Our findings underscore the influence of BC on the radiative properties of snow in the Antarctic Peninsula. The diverseBC concentrations observed here suggest varying sources and highlight the need for continued monitoring. The resultsreveal the vulnerability of the Antarctic Peninsula to the impacts of anthropogenic pollutants, even in its seeminglypristine surroundings. Acknowledging and addressing these influences is essential for assessing the broaderimplications of climate change in polar regions. Continued research at these little-explored sites is crucial for refiningclimate models and informing mitigation strategies to preserve the integrity of the Antarctic environment.Acknowledgments: INACH Project RT_34-21, and ANID Project: Fondecyt Projects N°1221526 andN°11220525, ANILLO ACONCAGUA N°ACT210021, and FOVI230167
Tropical Cyclone-related Extreme Rainfall and Its Impact under Solar Radiation Management (SRM) in Eastern Indonesia Region 
Authors: Koesuma Sorja , Faqih Akhmad , Hendri Hendri , Listyarini Jassica , Madi Astiani Adinda , Azzahra Kusuma Delfina , Gernowo Rahmat
Published: March 2024

The provinces of East Nusa Tenggara (NTT) and Papua are located in the eastern part of Indonesia. The occurrence of tropical cyclones and extreme weather events has recently increased in both regions. It is necessary to be aware of the impact, both direct and indirect, of tropical cyclones, which affect the weather, especially extreme rainfall. The study aims to investigate the impact of extreme rainfall and find potential solutions.

We use some of the following tropical cyclone data that happened in Indonesia. The tropical cyclone of Seroja on April 4, 2021, reached mainland NTT and had a significant impact, especially on Timor Island and Sumba Island. The tropical cyclone of Surigae was formed in the northern region of Papua on April 12-19, 2021. The peak of this cyclone was on 16 April 2021. The tropical cyclone of Ray formed around the Northwest/Western Pacific Ocean on December 13-20, 2021.

We analysed the atmospheric dynamics (rainfall) of the tropical cyclone events using the ERA5 model. We also use Bias correction from GeoMIP to analyse the rainfall and compare both results. The result shows that both data are well correlated and tend to decrease.
 U.S. Geological Survey datasets of hydrological extremes and their drivers to enhance security and improve understanding
Authors: Archfield Stacey
Published: March 2024

The intensification of the water cycle over recent decades has produced changes in hydrologic extremes (floods and droughts) unevenly across the globe and the U.S. is not an exception. This has led to increased interest in coordination amongst federal agencies within the U.S. to improve readiness to respond to and mitigate the effects of these extreme events as well as for the U.S. to increase coordination with our international partners, as evidenced by a recent Quadrilateral Security Dialogue between the U.S., Japan, Australia, and India on extreme precipitation and its effects on water quality, inundation, and flooding. As the nation’s unbiased resource for land-surface information, the U.S. Geological Survey has responded by developing a set of interpretative studies and related datasets to understand changes in floods and droughts, the potential drivers of these changes, and strategies for updating frequency-based statistics for hydrological extremes. This presentation and discussion will highlight recent advancements in data and interpretation on hydrologic extremes as well as the detection of changes in, attribution of, and adjustment for observed changes.
Implementation and evaluation of updated photolysis rates in the EMEP model using Cloud-J v7.3e
Authors: van Caspel Willem , Simpson David , Ge Yao , Vieno Massimo
Published: March 2024

Photolysis reactions are an essential component of atmospheric chemistry, with the accurate representation of solar radiation and its interactions with clouds and aerosols being a fundamental part of atmospheric chemistry-transport models (CTMs). The photolysis rate calculation scheme in the EMEP MSC-W CTM has recently been updated to the interactive Cloud-J v7.3e scheme, replacing the old system based on tabulated values (van Caspel, et. al., 2023). The current work highlights the comparison of the photolysis rate systems against aerial observations from the ATom-1 campaign over the Pacific Ocean (Hall, et. al., 2018). This comparison includes sensitivity analysis investigating the impact of model resolution, meteorological input model, and cloud averaging scheme. For air quality simulations, the Cloud-J photolysis rates lead to a clear shift in the partitioning of reactive oxygen into the ozone component, with simulations of surface ozone and carbon monoxide showing a general increase in performance. Annual mass-weighted tropospheric hydroxyl concentrations are increased by 26%, while the photolytic impact of aerosols is mostly limited to tropical biomass burning regions. The model run-time penalty of the interactive photolysis rate calculations is 15% at most, with the run-time of regional (forecasting) simulations being increased by no more than 3%.van Caspel, W. E., Simpson, D., Jonson, J. E., Benedictow, A. M., Ge, Y., di Sarra, A., Pace, G, Vieno, M, Walker, H.L., & Heal, M. R. (2023). Implementation and evaluation of updated photolysis rates in the EMEP MSC-W chemistry-transport model using Cloud-J v7. 3e. Geoscientific Model Development, 16(24), 7433-7459. https://doi.org/10.5194/gmd-16-7433-2023Hall, S. R., Ullmann, K., Prather, M. J., Flynn, C. M., Murray, L. T., Fiore, A. M., Correa, G., Strode, S. A., Steenrod, S. D., Lamarque, J.-F., Guth, J., Josse, B., Flemming, J., Huijnen, V., Abraham, N. L., and Archibald, A. T. (2018): Cloud impacts on photochemistry: building a climatology of photolysis rates from the Atmospheric Tomography mission, Atmos. Chem. Phys., 18, 16809–16828, https://doi.org/10.5194/acp-18-16809-2018
New Developments in Near Real-Time GNSS Zenith Total Delay Estimates at the University of Luxembourg
Authors: Hunegnaw Addisu , Teferle Norma , Jones Jonathan
Published: March 2024

Recently, the University of Luxembourg (UL), in collaboration with the United Kingdom Met Office, has started providing accurate near real-time (NRT) Zenith Total Delays (ZTDs) from networks of GNSS ground stations. This initiative is in alignment with the operational meteorological products from various analysis centers available at the EUMETNET EIG GNSS Water Vapour Programme (E-GVAP) and the team in Luxembourg envisages to re-start its contributions in the near future. Active in Europe, E-GVAP coordinates NRT GNSS-based atmospheric content monitoring to support Numerical Weather Prediction (NWP) modelling with products that are crucial for mesoscale models throughout Europe, for example, for the Met Office. GNSS technology is essential for accurately measuring atmospheric parameters such as ZTD and Integrated Water Vapor (IWV) at high frequencies, regardless of weather conditions. In addition, GNSS data are low-cost when compared to conventional meteorological systems. Ensuring the NRT availability of these data for NWP assimilation systems requires numerous methods in GNSS data handling and processing, quality assurance, and distribution.  The study details the collaborative work between the UK Met Office and the University of Luxembourg in providing accurate and rapidly available meteorological data through GNSS technology. This collaboration has led to the development and update of various systems for the processing of GNSS observations to produce advanced NRT ZTD products at UL and the Met Office. These products are generated at 1-hour intervals on both global and regional scales, and at sub-hourly intervals regionally. This study primarily aims to provide a thorough review and accuracy assessment of NRT ZTD products from the UL, comparing their precision with benchmark data from both post-processed and NRT ZTD estimates from various EGVAP analysis centres. The NRT GNSS processing systems at UL use the Bernese GNSS Software (BSW) versions 5.2 and 5.4 with a double-differencing (DD) approach, and similarly, the post-processed benchmark ZTD estimates employs the DD positioning strategy using the same software packages.
A Model for Fast Estimation of Seawater Intrusion in Coastal Aquifers: Simulating Flow and Land Subsidence
Authors: Yu Weijiang , Baù Domenico , Christelis Vasileios , Geranmehr Mohammadali
Published: March 2024

We introduce a novel groundwater flow model designed for the rapid estimation of seawater intrusion (SWI) in coastal aquifers. Drawing on Girinskii's potential theory (1947) for 2D aquifer flow, the model extends Strack's (1976) adaptation to coastal aquifers under transient state conditions. Key features include applicability to heterogeneous unconfined aquifer systems under time-dependent pumping and spatially distributed groundwater recharge. Assumptions include a sharp seawater-freshwater interface, prevailing horizontal flow, and neglect of flow rates within the saltwater wedge.Built upon a finite-element 2D saturated groundwater simulator, the model derives a solution for the potential using a non-linear formulation of the classic flow equation and can accommodate prescribed-head or prescribed-flux boundary conditions at inland boundaries, as well as time-varying head conditions at the shore boundaries, which is crucial for addressing long-term sea-level rise (SLR). Noteworthy modifications enable the model to estimate land subsidence through a 1D vertical consolidation model directly in terms of potential, providing a holistic view of aquifer dynamics. The model is successfully tested against analytically based solutions and can facilitate swift calculations of aquifer vulnerability indicators, such as SWI toe location, increase in dissolved salt mass, and apparent land subsidence due to compounded effects of SLR, groundwater pumping, and long-term variable recharge conditions. Our presentation will showcase the model's features, preliminary results focusing on the effects of aquifer heterogeneities on the intensity of SWI and land subsidence patterns, model strengths and limitations. Emphasis will be placed on the model computational efficiency, enabling rapid estimation of crucial SWI indicators. Furthermore, the discussion will outline future steps, highlighting the need to balance the simplicity of working hypotheses with the computational demands of more intricate variable density models in assessing complex coastal aquifer dynamics.
An abrupt shift in gross primary productivity over Eastern China-Mongolia and its inter-model diversity in land surface models
Authors: Lee Danbi , Kim Jin-Soo , Park So-Won , Kug Jong-Seong
Published: March 2024

The terrestrial ecosystem in East Asia mainly consists of semi-arid regions that are sensitive to climate change. Therefore, gross primary productivity (GPP) in East Asia could be highly variable and vulnerable to climate change, which can significantly affect the local carbon budget. Here, we examine the spatial and temporal characteristics of GPP variability in East Asia and its relationship with climate factors over the last three decades. We detect an abrupt decrease in GPP over Eastern China-Mongolia region around the year 2000. This is attributed to an abrupt decrease in precipitation associated with the phase shift of the Pacific decadal oscillation (PDO). We also evaluate the reproducibility of offline land surface models to simulate these abrupt changes. Of the twelve models, eight were able to simulate this abrupt response, while the others failed due to the combination of an exaggerated CO2 fertilization effect and an underrated climate impact. For accurate prediction, it is necessary to improve the sensitivity of the GPP to changes in CO2 concentrations and the climate system.