bluuebunny/crossref_metadata_2025 huggingface dataset:
Carbon storage pools of trees: fixed or flexible?
Authors: Hoch Guenter , Weber Raphael , Zahnd Cedric , Kahmen Ansgar
Published: February 2023

Most of the carbon (C) reserves in trees are stored in the living parenchyma of stems and roots and exhibit characteristic variations with phenology, growth and environmental stress. Up to date, it is only partially understood how the formation and re-mobilization of stored C in sapwood is regulated and synchronized over tissues and long distances. Mechanistic concepts of C storage therefore often assume simple bucket-models, where the amount of stored C equals the net-balance between C assimilation and the sum of all C sink activities (e.g., respiration and growth).Here, we summarize results from previous experimental and observational studies in our group, that tested the reaction of non-structural carbohydrate reserve pools in trees to situations of limited photosynthetic C supply. Overall, these studies suggested that C reserve concentrations in sapwood follow abrupt changes of the net C-source-sink balance in the short-term and at severe C starvation, but they consistently reach homeostatic levels that are very similar across different C-source-sink conditions over longer time periods. According to our findings, we propose that C reserve pool sizes in tree are determined and closely controlled rather than the simple net-result of C source vs. -sink activities. With respect to mechanistic C models of trees, this suggests that C reserves should be rather treated as a fixed C-sink than a variable parameter.
A deep neural network model to estimate water retention of compacted clayey soils
Authors: Tyurin Vladimir , Taherdangkoo Reza , Butscher Christoph
Published: February 2023

Soil-water retention is fundamental to understand hydro-mechanical characteristics of unsaturated clayey soils. The soil-water retention curve (SWRC) depends on internal (e.g. mineralogical composition, and chemo-physical properties of soils) and external (e.g. stress states and temperature) factors. The SWRC is usually determined through laboratory testing, which is costly and time consuming. In this study, we compiled an experimental dataset containing water retention data of artificial and natural clayey soils to develop a deep neural network (DNN) model trained with genetic algorithm (GA) to estimate SWRC over a wide suction range. The relevant soil properties including dry density, liquid limit, plastic limit, plasticity index, initial water content, void ratio, and suction are the input variables of the DNN-GA model, while the gravimetric water content is the output variable. The analysis of modeling errors and the comparison of gravimetric water content predicted values with experimental values showed the high efficiency of the model being developed. The DNN-GA model can be used as an accurate alternative to classical soil mechanic correlations.
The challenges of risk dynamics and how to assess them
Authors: de Ruiter Marleen
Published: February 2023

Recent disasters have demonstrated the challenges faced by our global society because of the increasing complexity of disasters caused by natural hazards. For example, a community hit by a natural hazard while still recovering from the impacts of an earlier hazard faces many different challenges than when it is hit by a single hazard that occurs in isolation. With growing awareness of this complexity and its impact on disaster risk, there has been a push, from scientists as well as international organizations such as the UNDRR, for disaster risk research to account for these complexities. This research has aimed to take an increasingly integrated approach, often bridging across individual hazard types to accomplish a more comprehensive understanding of overall risk. Incorporating spatiotemporal dynamics of all risk components (i.e., hazards, exposure, and vulnerability) is key to accurately modelling compound and multi-hazard risk events. There is great potential to better capturedynamics between and within risk components by learning from common approaches and methods used in different research communities. For example, recent years have seen a growing attention for research into compound hazards and hazard drivers using methods such as storylines, agent-based models, and system dynamics, all novelties for this field of research. An important, less studied aspect is that of the dynamics of vulnerability. Many of these once-novel methods now applied in compound hazard research have the potential to improve modelling capabilities of other compound risk aspects, such as vulnerability dynamics. This talk will highlight recent developments in assessing the complexities of disaster risk and discuss potential opportunities to further advance our modelling capabilities through multidisciplinary exchanges.
Winter Precipitation Responses to Projected Arctic Sea-Ice Loss and Global Ocean Warming and Their Opposing Influences over Northwest Europe
Authors: Yu Hao , Screen James , Hay Stephanie , Catto Jennifer , Xu Mian
Published: February 2023

Using a large ensemble of simulations from the Polar Amplification Model Intercomparison Project (PAMIP) and Coupled Model Intercomparison Project Phase 6 (CMIP6), we compare the response of winter-mean precipitation and daily extremes across the North Hemisphere in response to future Arctic sea-ice loss and global ocean warming. North Atlantic-Northwest Europe is simulated to become drier in response to future Arctic sea-ice loss, with reduced precipitation intensity and more dry days. A wetting response to sea-ice loss is simulated over the midlatitude Atlantic Ocean. These responses are robust across the eight models analysed, albeit with differences in their magnitude and spatial pattern. The precipitation response to global ocean warming is broadly opposite in sign, but larger in magnitude, compared to the response to sea-ice loss, over these regions. The precipitation responses to both sea-ice loss and ocean warming are strongly related to coincident changes in storm density and intensity. More specifically, an equatorward shift of the storm tracks in response to sea-ice loss and poleward shift of the storm tracks in response to ocean warming. The linear combination of the responses of future Arctic sea-ice loss and global ocean warming explain well the spatial pattern of the precipitation change at 2 ºC global warming projected in CMIP6. Our results suggest that projected future precipitation change over North Atlantic-Northwest Europe reflects a ‘tug-of-war’ between Arctic sea-ice loss and global ocean warming, but the latter dominates over the former.
Spiciness of the subpolar North Atlantic affects the response of the Atlantic Meridional Overturning Circulation to the North Atlantic Oscillation in CMIP6 models
Authors: Reintges Annika , Robson Jon , Sutton Rowan , Yeager Stephen
Published: February 2023

Climate models are a valuable tool to study the interaction between ocean and atmosphere. Nevertheless, they are known to suffer from various biases and uncertainties. In the subpolar North Atlantic typical biases among models from the Coupled Model Intercomparison Project phase 6 (CMIP6) are found in the mean surface temperature and salinity, and in the mean sea ice concentration. These biases will affect the air-sea interaction.In this study, we are investigating the diversity of CMIP6 models with respect to their response of the Atlantic Meridional Overturning Circulation (AMOC) to the North Atlantic Oscillation (NAO) in pre-industrial control experiments. This response is sensitive to the mean spiciness of the North Atlantic. Thus, we focus on two categories of models: Models that are spicy (warm-salty) and models that are minty (cold-fresh) within the subpolar gyre of the North Atlantic. Spicy models tend to have a lower sea ice cover in the Labrador Sea (LS) and larger LS heat loss during a positive NAO, compared to minty models. Also, spicy models have a weaker stratification in the LS. Sub-surface density changes 1 to 3 years after the NAO are larger in the spicy models and establish a zonal density gradient that can cause a stronger delayed AMOC response that is also more coherent across latitudes.Although some metrics seem to be more realistic in the spicy models, other characteristics seem less realistic compared to the minty models, like the mixed layer depth relative importance between the eastern and the western subpolar North Atlantic. This could be a sign for how some mean states or processes might be right for the wrong reasons and stresses the need for model improvement.
Deployment of the global tide and surge model for estimating sea-level trends along the Dutch coast
Authors: Muis Sanne , Aleksandrova Natalia , Baart Fedor , Stolte Willem , Veentra Jelmer
Published: February 2023

The monitoring of the sea level trend is important for decision-making in the near-future. For the Dutch coast, the Sea Level Monitor periodically publishes new estimates of the sea level rise trend. This observed trend, based on a selection of Dutch tide gauge stations, is used for the planning and management of our coastal defenses in the next 10-15 years. To estimate the trend in mean sea level, the influence of land subsidence, long-term tidal cycles and storm surges levels need to be removed from the observations.In this contribution, we focus on the contribution of storm surges, that are driven by variations of atmospheric pressure and wind. We will present an updated methodology to remove the effects of these variations on the sea-level trend, which is based on monthly mean sea levels derived with a depth-averaged hydrodynamic model instead of a linear regression. A fully automated and portable workflow was developed to deploy Global Tide and Surge Model (GTSM) on a high-performance computing cluster. Leveraging recent updates of the ERA5 climate reanalysis, we extent existing GTSM simulations back to 1950 and to present-day. Based on these new simulations, we will discuss the variability in mean sea levels due to atmospheric conditions, and present how the sea-level trend changes due to the improved correction.
On the Roles of Tropical Waves in the Formation of Global Tropical Cyclone Clusters
Authors: Kieu Chanh , Vu The-Anh
Published: February 2023

This study examines the role of tropical dynamics in the formation of global tropical cyclone (TC) clusters. Using theoretical analyses and idealized simulations, it is found that global TC clusters can be produced by the internal dynamics of the tropical atmosphere, even in the absence of all landmass surface and zonal sea surface temperature (SST) anomalies. Theoretical analyses of a two-dimensional InterTropical Convergence Zone (ITCZ) model reveal indeed some large-scale stationary waves whose zonal and meridional structures could support the formation of TC clusters at the global scale. Additional idealized simulations using the Weather Research and Forecasting (WRF) model confirm these results for a range of experiments. Specifically, the examination of two common tropical wave types including the equatorial Rossby (ER) wave and the equatorial Kelvin (EK) wave shows that ER waves could develop a stationary structure for a range of zonal wavenumbers $m\in[5-11]$, while EK waves do not. This modeling result is consistent with the ITCZ analytical model and suggests that large-scale ER waves could support stationary "hot spots" for global TC formation without any zonal SST anomalies. The findings in this study offer different insights into the importance of tropical waves in producing global TC clusters beyond the traditional explanation based on zonal SST variability.   
Rising carbon dioxide concentrations in Swedish groundwater during 1980−202
Authors: Klaus Marcus
Published: February 2023

Groundwater is one of the largest continental carbon reservoirs and tightly linked to globally significant carbon fluxes such as uptake on land, evasion from inland waters and delivery to oceans. Despite emerging evidence that these fluxes are sensitive to environmental changes, long-term trends in groundwater carbon dynamics remain widely unknown. Here I show that dissolved inorganic carbon and carbon dioxide concentrations in groundwater have increased on average by 29% and 48%, respectively, across Sweden (55−68°N) during 1980−2020. I attribute these changes mainly to a partial recovery from historic atmospheric sulfate deposition and associated shifts in weathering pathways in acid-sensitive bedrock, but also to enhanced soil respiration as a likely consequence of climate and land use changes. The results highlight previously neglected significant long-term and large-scale dynamics in groundwater carbon cycling and have implications for the pathways and time scales through which carbon is cycled through the land - inland water - ocean continuum. The observed dynamics should be included in carbon cycle models for accurate evaluations and predictions of the effects of environmental changes on regional and global carbon fluxes.
The Exploration of 2015-2019 Surface Background Ozone over China: A Model Study by GEOS-Chem High Performance (GCHP)
Authors: Ye Xingpei , Zhang Lin
Published: February 2023

Many studies have been conducted to address the surface ozone pollution issue over China, but few model works focus on the background ozone, a metric to represent the best surface ozone levels that can be achieved through emission controls. Here we apply a state-of-art global chemical transport model GEOS-Chem High Performance (GCHP) to understand the sources contributing to Chinese background (CNB) daily maximum 8 h average (MDA8) ozone, and to identify the driving factor of its interannual variability from 2015 to 2019.The five-year-mean CNB ozone is estimated as 37.8 ppbv, showing a general west-to-east downward gradient. The national-mean CNB ozone levels are the largest in summer (42.5 ppbv), but distinct seasonality can be seen at different regions. Using the tagged ozone technique, we show that the high background levels in western China are due to abundant transport from the free troposphere and adjacent foreign regions, while in eastern China, domestic ozone formation near surface from natural precursors is also important and exhibits intensive seasonal variation. CNB ozone enhancements from lightning NOx, soil NOx, and biogenic volatile organic compound (BVOC) emissions are estimated as 8.1, 6.4 and 3.9 ppbv, respectively, in summertime. We found the greater importance of BVOC over soil NOx to ozone as reported in previous studies is reversed when domestic anthropogenic emissions are turned off, reflecting a more NOx-sensitive ozone chemical regime in a “clean” atmosphere.The interannual variability (IAV) of CNB ozone shows the peak in summer, with standard deviation values during five years of ~5 ppbv over Qinghai-Tibet Plateau (QTP) and >3.5 ppbv over vast eastern China. CNB levels in QTP are found to be well correlated with horizontal circulation anomalies at 500 hPa, while in the east, year-to-year changes in soil NOx emissions dominate the IAV of CNB ozone. We further explore the role of El Nino-Southern Oscillation (ENSO) in modulating the IAV of CNB ozone over southern China in spring. Compared to the La Nina event, the enhanced precipitation and decreased temperature during El Nino inhibit CNB ozone formation in southeast China. However, heat and drought events, as well as enhanced biomass burning emissions during El Nino in Mainland Southeast Asia can largely worsen ozone there, and further rise CNB levels in southwest China under the southerly wind.
A multidisciplinary study to evaluate the sustainability of a volcanic hydrosystem: Chaîne des Puys’s watersheds use by Clermont Auvergne Métropole for drinking water supply
Authors: Aumar Cyril , Nevers Pierre , Celle Hélène , Mailhot Gilles , Huneau Frédéric , Vergnaud Virginie , Yvard Barbara , Clauzet Marie-Laure
Published: February 2023

Clermont Auvergne Métropole is an agglomeration of 300,000 inhabitants. Two types of aquifers are exploited for the drinking water supply of this population: the alluvial aquifer of Allier River (70%) and three volcanic water basins located in the Chaîne des Puys (30%). Recent studies have shown that the quantity of water in the Allier alluvial aquifer decreases drastically during drought periods and that this decrease will amplified in the future due to climate changes (2022 for example). Water managers of Clermont Auvergne Metropole are thus interested in identifying the potential of their volcanic resources to secure the water supply of the population. In this purpose, a multidisciplinary study, using existing data and providing new ones has been projected. This study includes: 1) the use of the geological model previously established by Aumar (2022) at the Chaîne des Puys scale, that allows to constrain the geometry of aquifers; 2) the acquisition of hydrochemical data that help to better define the functioning of the volcanic watersheds; 3) the measurement of hydrodynamic and meteorological data to better define the terms of the hydrological balance. Natural tracers such as stable water isotopes (18O and 2H) or major and trace elements give information on the origin of those groundwaters (local or remote) and in particular their infiltration zone (average altitudes), their flow paths or the impact of various external processes (environmental or anthropic). Groundwater dating methods (CFC, Tritium) brings a constraint on the residence time of water within the aquifer. Yet, groundwater ages are still unknown in all watersheds of the Chaîne des Puys, but it remains essential to understand groundwater flow and storage. The coupling between hydrodynamic monitoring, a large panel of hydrochemical tracers and groundwater residence time data associated with a well constrained geological model allows to provide relevant management tools to stakeholders both in terms of quantification and protection of their resources.  
GGOS’s Geodetic Information Portal: Linking Geodesy and Society
Authors: Sehnal Martin , Sánchez Laura , Angermann Detlef , Craddock Allison , Miyahara Basara
Published: February 2023

The Global Geodetic Observing System (GGOS) of the International Association of Geodesy (IAG) is a collaborative contribution of the global geodesy community to the observation and monitoring of the Earth System. Geodetic observation techniques and analysis infrastructures, as well as the high-quality geodetic products, provide the foundation upon which advances in Earth and planetary system sciences and applications are built.One main objective of GGOS is to support actions and initiatives to communicate the value of Geodesy to society, as well as help to understand and solve complex issues facing the global geodetic community. Towards this objective, GGOS has completely redesigned its website, www.ggos.org, which serves as a “point of entry to geodesy” to facilitate discoverability and usability of geodetic data and products. This includes explanations about: IAG services, geodetic observations and geodetic products. With this, GGOS engages with diverse user communities to increase awareness of geodesy and the ever-expanding benefits of geodesy in every-day applications.In addition, GGOS recently produced short videos to explain the applications and importance of geodesy to non-geodesists. The new “Discover GGOS and Geodesy” video is available on YouTube in multiple languages.
Understanding Atlantic Meridional Overturning Circulation and linked variations in precipitation and temperature distribution during the warmer climate
Authors: Pratap Shailendra , Markonis Yannis , R. Blöcher Johanna
Published: February 2023

Long-term and abrupt changes in precipitation (P) patterns remain ambiguous in a warmer climate. Modern studies project that a warmer climate will cause intensification of the hydrological cycle. However, paleoclimate evidence from the warm period, i.e., the Medieval Climate Anomaly (MCA; 800-1400 AD), contradicts this because, during MCA, some regions were humid (wet), while others had arid (dry) climates. Here, we investigated the P response to variations in the temperature (T) and Atlantic Meridional Overturning Circulation (AMOC) variation throughout the Northern Hemisphere (NH) using 75 for P, 17 for the AMOC, and 48 records for T from NOAA and PAGES paleoclimate databases.Our results show a continuous weakening trend in AMOC from the 9th to 13th centuries. The weakened AMOC has probably altered the atmospheric heat and water vapor distribution, and consequently the hydroclimate around the NH. The hydroclimate over the eastern North America and the Western Europe looks more vulnerable to weak AMOC as it shifted from warm-humid to cold-arid climates. Weak AMOC induces motion in Inter-Tropical Convergence Zone (ITCZ) southwards. Our results show signals of an ITCZ shift over equatorial Africa and southern Asia with the warm and humid response. Although warm (cold) climates are not always associated with increased (decreased) P, they may also lead to arid (humid) climates. Overall, we found that when T is higher than their average, the hydrological conditions are arid, but when T is similar or close to the average level, the conditions are humid. However, these hydroclimate responses may vary according to the regionally available water resources. Therefore, an improved understanding of long-term T variability and AMOC trend changes, specifically during warmer periods, could provide relevant insights into the present and future climates.
Continuous seismic monitoring of a geothermal project using Distributed Acoustic Sensing (DAS): a case study in the German Molasse Basin.
Authors: Azzola Jérôme , Gaucher Emmanuel
Published: February 2023

Distributed Acoustic Sensing (DAS) in geothermal wells is a particularly attractive technology to implement as part of routine seismic monitoring of geothermal plant operations. It brings a large network of sensors close to the monitoring target – the operated reservoir – increasing the sensitivity towards low magnitude events and allows the application of processing procedures inspired by large network or array processing. However, the technical management of the large flow of produced data and the suitability of the strain-rate acquisitions to monitor locally induced seismicity was yet to be fully assessed.We present the results of a continuous 6-month monitoring period that aimed at testing an integrated system designed to manage the acquisition, the processing and the saving of DAS data collected from behind casing at the Schäftlarnstraße (SLS) geothermal project (Munich, Germany). The data management system links the existing on-site infrastructure to a cloud Internet-of-Things (IoT) platform integrated into the company’s IT infrastructure. The cloud platform has been designed to deliver both a secure storage environment for the DAS records and optimized computing resources for their continuous processing.With a special focus on seismic risk mitigation, we investigate the potential of the monitoring concept to provide sensitive detection capabilities, despite operational conditions, while ensuring efficient data processing in order to strive for real-time monitoring. Further analysis of the records confirm additional logging capabilities of borehole DAS. We also evaluate the ability of DAS to provide reliable seismic source description, in particular in terms of location, moment magnitude, and stress drop.Using two detected local seismic events, we demonstrate the relevance of the system for monitoring the SLS-site in an urban environment, while complementing advantageously the surface seismometer-based monitoring network.
Classifying polymers with mid-IR spectra and machine learning: From monitoring to detection
Authors: Tian Xin , Bäuerlein Patrick , Beén Frederic
Published: February 2023

Monitoring and identifying environmental microplastics is of great importance for the scientific world, environmental agencies, and water authorities, to estimate the environmental impact and increase efforts to decrease emissions. As one of the infrared spectroscopy techniques, Laser Directed Infrared (LDIR) imaging can observe various microplastics, in terms of spectroscopical signals. Such signals are useful for follow-up analyses, particularly, identification by machine learning (ML) algorithms. Based on medium or large-sized datasets, past studies applied a variety of ML models to detect microplastics from their LDIR spectra. To tackle it, we first propose a practical data augmentation technique to generate synthetic samples when only a few samples are available. Then a comprehensive comparison of multiple models, including both machine learning and deep learning models, is presented. Our results show that the ensemble ML model, compared to neural network models, can take the least training time to achieve the best performance, i.e., a classification accuracy of 99.5%, even with a small dataset (210 samples collected from aquatic systems). This study provides a generic framework for monitoring and detecting microplastics by combining LDIR and ML.
Mirror mode-like structures around unmagnetised planets: 1. Mars as observed by the MAVEN spacecraft
Authors: Simon Wedlund Cyril , Volwerk Martin , Mazelle Christian , Rojas Mata Sebastián , Stenberg Wieser Gabriella , Futaana Yoshifumi , Halekas Jasper , Rojas-Castillo Diana , Bertucci César , Espley Jared
Published: February 2023

Temperature anisotropy-driven instabilities such as the mirror mode and ion cyclotron instabilities are responsible for the generation of waves in the turbulent magnetosheath of planets. We present two statistical studies of mirror mode-like structures in the magnetosheaths of (mostly) unmagnetised planets such as Mars and Venus, characterised in the same way and with the same tools with the help of on-board magnetometers. In this presentation, we discuss observations by the MAVEN spacecraft. As in our companion Venus study (see poster by Volwerk et al. in the same session), we use magnetic field-only measurements to constrain and identify these quasi-linear compressive structures and discuss ways to mitigate false positive detections based on one instrument only. After calculating the residence time of the spacecraft in the Martian magnetoenvironment, we show two-dimensional statistical maps of mirror mode-like occurrence rates with respect to EUV solar flux levels, Mars Year, and atmospheric seasons. We find detection probabilities of about 1% at most, with two main regions of occurrence, one behind the collisionless shock, the other close to the induced magnetospheric boundary, with the clearest modulation of the probability due to EUV solar flux conditions. Finally, we qualitatively compare our results with past studies at Mars.
Energy deposition of a Pc5 ULF wave in the polar ionosphere measured by EISCAT
Authors: van Hazendonk Charlotte M. , Baddeley Lisa , Laundal Karl M.
Published: February 2023

Ultra low frequency (ULF) waves can contribute significantly to energy and momentum transfer between the Solar Wind – magnetosphere – ionosphere system, however, the energy deposition by ULF waves is often not taken into account in the global energy budget. A case study of spatial and temporal energy deposition of a Pc5 (2 – 7 mHz) ULF wave during non-sunlit conditions is presented. Datasets from the EISCAT Tromsø VHF radar, magnetometers and DMSP satellites were utilized to estimate the wave characteristics and the height-dependent energy deposition rates. The equipartition of energy into the ionosphere through thermal, ion frictional and/or Joule heating are discussed. The goal of this study is to quantify how much energy is deposited by ULF waves in otherwise quiet conditions.
Global and continental burned area detection from remote sensing: the FireCCI products
Authors: Pettinari M. Lucrecia , Lizundia-Loiola Joshua , Khairoun Amin , Roteta Ekhi , Storm Thomas , Boettcher Martin , Danne Olaf , Brockmann Carsten , Chuvieco Emilio
Published: February 2023

The FireCCI project, as part of the ESA Climate Change Initiative (CCI), has developed and validated burned area (BA) algorithms and products with the objective to meet, as far as possible, GCOS (Global Climate Observing System) Essential Climate Variable requirements for global satellite data products from multi-sensor data archives.The current suite of global products include FireCCI51, whose algorithm uses as input MODIS NIR surface reflectance at 250 m and 1-km-resolution active fires, and currently covers a 20-year time series. An evolution of this algorithm uses the SWIR bands of the Sentinel-3 SLSTR sensor, provided at 300 m resolution by the Synergy products developed by ESA. This input is complemented by VIIRS active fire information at 375 m resolution. The resulting BA product, called FireCCIS310, takes advantage of the improved BA detection capacity of the SWIR bands and the higher resolution of the VIIRS thermal information, apart from upgrades in the algorithm itself. This product is currently available for 2019, and it is being further processed for the subsequent years. FireCCIS310 is capable of detecting 28% more BA than FireCCI51 for the same year.Complementary, a specific dataset has been created for sub-Saharan Africa, where more than 70% of the total global burned area occurs. This product, called FireCCISFD (SFD standing for Small Fire Dataset), uses surface reflectance from the Sentinel-2 MSI sensor at 20 m spatial resolution, supplemented by active fire information. Version 1.1 of this dataset (FireCCISFD11) covers the year 2016 and is based on Sentinel-2A data plus MODIS active fires, while the newer version (FireCCISFD20) has been processed for the year 2019, and takes advantage of the additional data provided by Sentinel-2B, duplicating the input data amount and temporal resolution, and the improved spatial resolution of VIIRS active fires. Due to the much higher spatial resolution of the input data, this product detected 58% more BA than FireCCI51 in 2016, and 82% more in 2019, mostly due to the enhanced detection of small burned patches, not detectable with coarser resolution sensors.All these datasets provide very valuable information regarding land cover change dynamics due to fires, and their associated aerosol and greenhouse gasses emitted to the atmosphere. Particularly, the SFD datasets show that current estimations of fire emissions have been underestimated, and that they should be re-assessed taking into account the capabilities of the information provided by medium to high-resolution sensors.
Characterizing the influence of idealized atmospheric forcings on firn using the SNOWPACK firn model
Authors: Thompson-Munson Megan , Kay Jennifer , Markle Bradley
Published: February 2023

The porous layer of snow and firn that blankets ice sheets can store meltwater and buffer an ice sheet’s contribution to sea level rise. A warming climate threatens this buffering capacity and will likely lead to depletion of the air-filled pore space, known as the firn air content. The timing and nature of the firn’s response to climate change is uncertain. Thus, understanding how the firn may evolve in different climate scenarios remains important. Here we use a one-dimensional, physics-based firn model (SNOWPACK) to simulate firn properties over time. To force the model, we generate idealized, synthetic atmospheric datasets that represent distinct climatologies on the Antarctic and Greenland Ice Sheets. The forcing datasets include temperature, precipitation, humidity, wind speed and direction, shortwave radiation, and longwave radiation, which SNOWPACK uses as input to simulate a firn column through time. We perturb the input variables to determine how firn properties respond to the perturbation, and how long it takes for those properties to reach a new equilibrium. We explore how different combinations of perturbations impact the firn to assess the effects of, for example, a warmer and wetter climate versus a warmer and drier climate. The firn properties of greatest interest are the firn air content, liquid water content, firn temperature, density, and ice slab content since these quantities help define the meltwater storage capacity of the firn layer. In our preliminary analysis, we find that with a relatively warm and wet base climatology representative of a location in southern Greenland, increasing the air temperature by 1 K yields a 48% decrease in firn air content and a 3% increase in the deep firn temperature 100 years after the perturbation. SNOWPACK also simulates near-surface, low-permeability ice slabs that inhibit potential meltwater storage in deeper firn. Conversely, decreasing the air temperature by 1 K yields a 7% increase in firn air content and a <1% decrease in the deep firn temperature in the same amount of time. In this scenario, the effects of warming are more extreme and have more adverse impacts on the firn’s meltwater storage capacity when compared to cooling. This work highlights the sensitivity of the firn to changing atmospheric variables and provides a framework for estimating the timescales and magnitude of firn responses to a changing climate.
A new model of deformation and dynamic fracturing above laccolith intrusions
Authors: Poppe Sam , Morand Alexandra , Harnett Claire E. , Cornillon Anne , Heap Michael
Published: February 2023

High-viscosity magma can form laccolith intrusions that deform and fracture the overburden, causing surface uplift and ground fracturing. Laccolith-induced deformation features have been described at well-exposed outcrops of long-solidified intrusions. The lack of recent geophysical data on rare laccolith emplacement events and the use of linearly elastic continuum-based numerical models precludes a clear understanding of the dynamic fracturing mechanisms. We present a new two-dimensional (2D) Discrete Element Method (DEM) approach to dynamic magma intrusion in a particle-based host medium. The model indicates highly discontinuous deformation and dynamic fracturing and visualizes the localization of subsurface strain. We calibrate the numerical rock strength parameters by performing numerical laboratory experiments to natural rock strength values. We systematically explored the effect of numerical parameters that govern host rock strength (bond cohesion, bond tensile strength, bond elastic modulus), and intrusion depth, on the spatial distribution of strain, stress, and fracturing. We find that high host rock stiffness results in widely distributed and dense fracturing associated with symmetrical dome-shaped surface uplift. Low host rock stiffness results in the concentration of central fracturing and narrow lateral shear bands and asymmetric evolution of the laccolith geometry and the surface deformation pattern. These patterns are affected by the intrusion depth. Our models help understand fracture distribution patterns above laccolith intrusions and open unprecedented opportunities for dynamically modelling intrusion-induced deformation in the upper few kilometers of the Earth’s crust.
Monitoring lake ice phenology from CYGNSS: Algorithm development and assessment using Qinghai Lake, Tibet Plateau, as a case study
Authors: Ghiasi Yusof , Duguay Claude , Murfitt Justin , Asgarimehr Milad , Wu Yuhao
Published: February 2023

This study introduces the first use of Global Navigation Satellite System Reflectometry (GNSS-R) for monitoring lake ice phenology. This is demonstrated using Qinghai Lake, Tibetan Plateau, as a case study. Signal-to-Noise Ratio (SNR) values obtained from the Cyclone GNSS (CYGNSS) constellation over four ice seasons (2018 to 2022) were used to examine the impact of lake surface conditions on reflected GNSS signals during open water and ice cover seasons. A moving t-test (MTT) algorithm was applied to time-varying SNR values allowing for the detection of lake ice at daily temporal resolution. Strong agreement is observed between ice phenology records derived from CYGNSS and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. Differences during freeze-up (i.e., the period starting with the first appearance of ice on the lake until the lake becomes fully ice covered) ranged from 3 to 21 days with a mean bias error (MBE) and mean absolute error (MAE) of 10 days, while those during breakup (i.e., the period beginning with the first pixel of open water and ending when the whole lake becomes ice-free) ranged from 3 to 18 days (MBE and MAE:  6 and 7 days, respectively). Observations during the breakup period revealed the sensitivity of GNSS reflected signals to the onset of surface (snow and ice) melt before the appearance of open water conditions as determined from MODIS. While the CYGNSS constellation is limited to the coverage of lakes between 38° S and 38° N, the approach presented herein will be applicable to data from other GNSS-R missions that provide opportunities for the monitoring of ice phenology from large lakes globally (e.g., Spire constellation of satellites).
Physics Informed Deep Learning for Modeling Coseismic Crustal Deformation
Authors: Okazaki Tomohisa , Ito Takeo , Hirahara Kazuro , Ueda Naonori
Published: February 2023

Crustal deformation, which can be modeled by dislocation models, provides critical insights into the evolution of earthquake processes and future earthquake potentials. In this presentation, we introduce our recent work on a novel physics-informed deep learning approach for modeling coseismic crustal deformation (Okazaki et al. 2022). Physics-informed neural networks were proposed to solve both the forward and inverse problems by incorporating partial differential equations into loss functions (Raissi et al. 2019). The use of neural networks enables to represent continuous displacement fields in arbitrary geometrical structures and mechanical properties of rocks without discretization. To accurately model the displacement discontinuity on a fault, which cannot be directly approximated by neural networks composed of continuous functions, the polar coordinate system is introduced. We illustrate the validity and usefulness of the proposed approach through forward modeling of antiplane dislocations, which are used to model strike-slip faults. This approach would have considerable potential for extension to high-dimensional, anelastic, nonlinear, and inverse problems in a straightforward way.ReferenceOkazaki T, Ito T, Hirahara K, Ueda N, Physics-informed deep learning approach for modeling crustal deformation. Nature Communications, 13, 7092 (2022). https://doi.org/10.1038/s41467-022-34922-
Interhemispheric transport into the southern hemisphere polar stratosphere from the Asian monsoon region
Authors: Yan Xiaolu , Konopka Paul , Ploeger Felix , Podglajen Aurélien
Published: February 2023

The South-East Asian boundary layer has become one of the most polluted regions in recent years due to rapideconomic growth, which even affect the trace gas composition in the southern hemisphere by inter-hemispheric transport. Westudy the transport from the boundary layer of the Asian summer monsoon (ASM) region [15◦ N, 45◦ N, 30◦ E, 120◦ E] intothe global upper troposphere and lower stratosphere (UTLS) using the Lagrangian chemistry transport model CLaMS drivenby the ERA5 reanalysis during 2010-2014. In particular, we quantify the inter-hemispheric transport contribution from theASM region to the southern hemisphere polar region (SP) [60◦ S, 90◦ S] and investigate the influence on pollution. Despite thesmaller size of ASM area compared to the southern hemisphere (SH) subtropics [15◦ S, 45◦ S] and tropics [15◦ S, 15◦ N], wefind that the air mass fractions (AMF) from the ASM to the SP are about 1.5 times larger than the corresponding contributionsfrom the SH subtropics and about two times smaller than those from the tropics. Transport from the ASM boundary layer tothe Southern polar vortex occurs largely above about 450 K and on timescales longer than 2 years, while transport timescalesto the Antarctic region below the vortex are shorter than about 2 years. The transport contribution from the ASM region tothe SP presents distinct inter-annual variability, which is strongly related to the strength of polar vortex. The relatively young(less than two years) tracers originating from the ASM region show good correlations with CCl4, F12, and CH3Cl observationsfrom ACE-FTS in the antarctic UTLS. The reconstructed SF6 indicates that about 20% of SF6 in the SP stratosphere originatesfrom the ASM boundary layer, which is larger than the SF6 fraction of SH subtropical origin, while 50% of SF6 in the SPstratosphere originates from the tropical boundary layer.
Scale Dependence of Stochastic-Deterministic Flood Statistics
Authors: Fischer Svenja , Schumann Andreas
Published: February 2023

Scale dependencies are a core element of hydrological sciences. The inclusion of deterministic aspects in flood statistics requires a cross-scale approach that takes into account the differences in flood generation and, in particular, the importance of local and regional processes as well as the interdependencies of flood waves at different spatial scales. The interaction of meteorological drivers with the spatially and temporally variable catchment conditions, e.g. antecedent soil moisture, snow cover or confluences, determines a variety of flood events that are scale-dependent. For example, heavy rainfall floods usually lead to extremely large flood peaks if the catchment is small and has a critical size relative to the spatial extent of the rain cell. The situation is different for synoptic rainfall, where large basins are affected and the total rainfall and the superposition of floods from tributaries can lead to extreme events. Thus, the consideration of flood generation becomes more complex when large river basins are considered instead of small catchments. In addition to the meteorological and catchment-specific factors, the interaction between the individual sub-catchments must also be taken into account. In particular, the superposition of flood waves from tributaries can critically alter the flood hydrograph. How such differences can be determined statistically-deterministically and how the individual factors can be taken into account in a statistical model for estimating design floods is presented here. Univariate mixture models for local floods as well as multivariate statistical models for regional floods help to better understand floods and their development. Their relevance on different spatial scales is discussed here. The result forms the basis for improved flood modelling that extends the classical peak-based flood frequency analysis by essential spatial aspects. 
A data-driven approach to derive spatially explicit dynamic "thresholds" for shallow landslide occurrence in South Tyrol (Italy)
Authors: Steger Stefan , Moreno Mateo , Crespi Alice , Gariano Stefano Luigi , Brunetti Maria Teresa , Melillo Massimo , Peruccacci Silvia , Marra Francesco , Borga Marco , de Vugt Lotte , Zieher Thomas , Rutzinger Martin , Mair Volkmar , Campalani Piero , Pittore Massimiliano
Published: February 2023

When and where shallow landslides occur depends on an interplay of predisposing, preparatory, and triggering factors. At a regional scale, data-driven analyses are extensively used to assess landslide susceptibility based on “static” maps of predisposing conditions. In contrast, data-driven analyses focusing on landslide triggering factors often rely on non-spatially explicit approaches to derive empirical rainfall thresholds. So far, few attempts have been made to integrate the spatial and temporal analysis domains beyond a posterior combination of separately derived susceptibility models and rainfall thresholds.This work focuses on the mountainous Italian province of South Tyrol (7400 km²) and proposes a novel data-driven landslide prediction model that jointly considers landslide predisposition and dynamic preparatory and triggering factors. The approach builds on a hierarchical generalized additive model, multi-temporal shallow landslide data from 2000 to 2020 and a range of environmental variables (e.g., daily rainfall, topography, lithology, forest cover). The model produces maps that portray the relative probability of landslide occurrence. These spatially explicit predictions change dynamically as a function of local predisposition, seasonality, and observed (or hypothesized) dynamic preparatory and triggering rainfall (i.e. cumulative rainfall amounts based on varying day-windows). Linking the model output to known measures of model performance, such as hit rate and false alarm rate, enables the creation of dynamic classified maps that can be interpreted in analogy to commonly used empirical rainfall thresholds. The approach also accounts for potential spatial and temporal biases in the landslide inventory by restricting the underlying data sampling to effectively surveyed areas and time periods and by including (and averaging out) bias-describing random effect variables. Our validation confirms the model's high generalizability and predictive power while providing insights into the interplay of predisposing, preparatory and triggering factors for shallow landslide occurrence in South Tyrol. Application possibilities of this novel approach are discussed.The research leading to these results is related to the PROSLIDE project that received funding from the research program Research Südtirol/Alto Adige 2019 of the Autonomous Province of Bozen/Bolzano – Südtirol/Alto Adige.
Enhanced intensification of hourly rainfall extremes due to urban warming in Phoenix, Arizona
Authors: Huang Jamie , Fatichi Simone , Mascaro Giuseppe , Manoli Gabriele , Peleg Nadav
Published: February 2023

The main cause of flash and pluvial floods in cities is short-duration extreme rainfall events. The built environment can either intensify or weaken extreme rainfall intensity depending on the urban fabric that controls the local environmental and climatic conditions. From 2000 through 2018, we examined how the built area affected hourly extreme rainfall intensities in the large metropolitan area of Phoenix, Arizona, characterized by open low-rise buildings, using a large and dense rain-gauge network of 168 ground stations. We found that hourly extreme rainfall intensities increased both in the city and its surroundings but the increase in the built area was significantly greater (3 times greater) - the mean trend in annual hourly rainfall maximum in the urban area was 0.6 mm h-1 y-1 while in the rural surrounding the mean was 0.2 mm h-1 y-1. We calculated a negative trend in aerosol concentration (−0.005 AOD y−1) but a positive trend in near-surface air temperature that was considerably larger in the urban areas (0.15 °C y−1) as compared to the rural counterpart (0.09 °C y−1). Even though built surfaces and low-rise buildings contributed to an increase in air temperature, they did not affect air humidity. Generally, rainfall extremes follow the Clausius–Clapeyron relationship with an increase at a rate of 7% °C−1. Our results demonstrate that the warming effect associated with a low-rise urban area can result in increased rainfall extremes that are significantly greater than in the surrounding areas of the city.