bluuebunny/crossref_metadata_2025 huggingface dataset:
Measuring Marine Hydrodynamics from Space Using Planet Satellite Imagery 
Authors: Tlhomole James , Piggott Matthew , Hughes Graham
Published: March 2024

The inference of coastal ocean dynamics from consecutive remote sensing images plays a central role in a diverse range of domains such as marine conservation, spatial planning, as well as flood risk. We present a methodology for systematically identifying spatially overlapping image pairs in coastal regions from the PlanetScope archive, with minute-scale time lags and the potential for velocity field inference using classical algorithms. This ability is demonstrated through the novel estimation of submesoscale eddies from PlanetScope image pairs across a range of contexts. These include sea ice floes in the Siberian Sea of Okhotsk, a cyanobacterial bloom in the Baltic Sea, and suspended sediment in the Port of Al-Fao located in the Arabian Gulf. Additionally, comparison of the latter with coinciding velocity fields from a Delft3D model shows good quantitative agreement in regions with high suspended sediment concentration. We successfully develop a workflow pipeline for identifying and processing image pairs from these opportunistic overlaps, unlocking a new large-scale data source of coastal ocean surface velocities to be used alongside modelling frameworks. 
Regional model estimation of seasonal and interannual variability of circulation and volume transport in the Sicily Channel.
Authors: Pasculli Lorenzo , Falcieri Francesco Marcello , Schroeder Katrin , Chiggiato Jacopo , Rubino Angelo
Published: March 2024

The Sicily Channel is a key area for the dynamics of the Mediterranean Sea, as it crucially contributes regulating the exchange of water masses, as well as of biogechemical characteristics between the Western and Eastern Mediterranean basins. This research focuses on investigating the dynamics of the Sicily Channel, particularly its seasonal variability, studied using a high-resolution regional model (Regional Ocean Modeling System – ROMS) and in situ data (moorings equipped with ADCPs) referring to the period from 2010 to 2019. During winter, the surface circulation is mainly influenced by the wind, which fosters the formation of mesoscale variability, whereas it is mainly regulated by the topography of the Strait in summer. The deep circulation is mainly regulated by the Strait's bathymetric constraints and by the remote variability of intermediate waters, which reflect the large-scale variability of the basin. These processes lead to an increase in transport during the winter months, peaking in January-February, while a general decrease occurs in the summer.
Comparing the seasonal predictability of Tropical Pacific variability in EC-Earth3 at two different horizontal resolutions
Authors: Carreric Aude , Ortega Pablo , Lapin Vladimir , Doblas-Reyes Francisco
Published: March 2024

Seasonal prediction is a field of research attracting growing interest beyond the scientific community due to its strong potential to guide decision-making in many sectors (e.g. agriculture and food security, health, energy production, water management, disaster risk reduction) in the face of the pressing dangers of climate change.Among the various techniques being considered to improve the predictive skill of seasonal prediction systems, increasing the horizontal resolution of GCMs is a promising avenue. There are several indications that higher resolution versions of the current generation of climate models might improve key air-sea teleconnections, decreasing common biases of global models and improving the skill to predict certain regions at seasonal scales, e.g. in tropical sea surface temperature.In this study, we analyze the differences in the predictive skill of two different seasonal prediction systems, based on the same climate model EC-Earth3 and initialized in the same way but using two different horizontal resolutions. The standard (SR) and high resolution (HR) configurations are based on an atmospheric component, IFS, of ~100 km and ~40 km of resolution respectively and on an ocean component, NEMO3.6, of ~100 km and ~25 km respectively. We focus in particular on the Tropical Pacific region where statistically significant improvements are found in HR with respect to SR for predicting ENSO and its associated climate teleconnections. We explore some processes that can explain these differences, such as the simulation of the tropical ocean mean state and atmospheric teleconnections between the Atlantic and Pacific tropical oceans. A weaker mean-state bias in the HR configuration, with less westward extension of ENSO-related SST anomalies, leads to better skill in ENSO regions, which can also be linked to better localization of the atmospheric teleconnection with the equatorial Atlantic Ocean. It remains to be assessed if similar improvements are consistently identified for HR versions in other forecast systems, which would prompt their routine use in seasonal climate prediction.
Climate Initiative for Iberian Mountain Areas (CIMAs): improving our understanding of climate variability over mountain areas using high resolution modelling.
Authors: Greciano-Zamorano Emilio , González-Rouco Jesús Fidel , Vegas-Cañas Cristina , García-Pereira Félix , Navarro-Montesinos Jorge , García-Bustamante Elena , Rodríguez-Guisado Esteban , Rodríguez-Camino Ernesto
Published: March 2024

Mountain areas are particularly sensitive to global warming as they usually present a complex distribution of climates and ecosystems and feedbacks tend to amplify the effects of climate change. Additionally, the large spatial variability of temperature gradients and heterogeneity in the occurrence, amount and distribution of precipitation and snow cover in mountainous areas are especially relevant for water resources and stresses the need for high altitude observations and high-resolution modelling over complex terrain. However, harsh meteorological conditions and the complex orography associated with this environment that, as part of the Mediterranean domain, has been underscored as a climate change hot-spot, hinder the obtention of a good coverage of high-altitude observations and pose challenges for regional climate models.CIMAs is a joint effort aiming at improving our understanding of climate variability over mountain regions in Iberia. A pilot area has been selected over the Sierra de Guadarrama (Spanish Central range, about 50 km from Madrid) aiming at studying climate variability through very high (1 km) resolution simulations, exploring models’ ability to capture relevant processes at that scale. A set of observational sites ranging from high altitudes to low levels at both sides of the mountain range has been used.ERA Interim, ERA5 and different WRF nested simulations, spanning the last three decades and reaching 1 km resolution, have been compared to a dense network of in situ observations. Results show a clear improvement with increasing resolution for temperature, but some altitude-related biases for precipitation. In this sense, some sensitivity tests to changing convection parameterizations and to convection permitting configurations have been assessed.
The International Quaternary Map of Europe and Adjacent Areas: Results from mapping of extreme environments inclusive
Authors: Asch Kristine , Reitner Jürgen M.
Published: March 2024

The project of the International Quaternary Map of Europe project (IQUAME 2500) is a major international initiative coordinated by BGR under the auspices of the CGMW (Commission of the Geological Map of the Word, Sub-Commission Europe) and with support of INQUA.The project is collecting  and compiling information from more than 40 partner institutions on numerous aspects of the European Quaternary. This includes the lithology and geochronological age of Quaternary units, genetic descriptions of the units, maximum extent of the ice sheets, extent of Arctic sea ice, off-shore Quaternary information,, directions of ice movement, postglacial rebound, active faults, extent of permafrost and key localities (e.g. geologically and anthropologically interesting sites),The IQUAME is based on hundreds of past mapping campaigns all over Europe. A considerable amount took place in extreme environments such as in polar, mountainous and/or glaciated regions. For example, the mapping of Lateglacial moraines in the Eastern Alps in Austria indicating extensive multiple glacier advances after the breakdown of the Last Glacial Maximum ice cap that occur in a high alpine environment with peaks of 3000 m altitude and steep slopes. The IQUAME also presents offshore map information, as the geology does not end on the shoreline. These data are based on  data of  European Marine Observation and Data Network (EMODnet) Geology project, established in 2009 by the European Commission. Within EMODnet Geology the Workpackage “Seafloor geology” compiles and harmonizes offshore geological map layers  also from the Quaternary, from the EMODnet partners all over Europe.Participation of the numerous international partners and the many different topics requires considerable data harmonization (semantics, structure and geometry). To achieve this, common standards and guidelines were set up and are used by all participants:  structured vocabularies to describe the IQUAME's contents, a common topographic base, technical procedures to include the map data and guidelines to aid the partners to submit their data to the project. The harmonization is still in progress.This contribution shows the pathway from regional mapping campaigns such as the one from the Lateglacial moraines in high alpine valleys and cirques to an overall harmonized Quaternary map layer of the entire Europe.
Unveiling magma dynamics behind geochemical data
Authors: La Spina Alessandro , Burton Mike , Bonfanti Pietro , Murè Filippo
Published: March 2024

Identifying changes on volcano unrest condition and tracking the evolution of eruptive activity are fundamental for volcanic surveillance and monitoring. Under this perspective, magmatic gases play a key role; therefore, monitoring changes in volcanic plume composition is essential.Between and during each eruption large systematic variations in the volcanic plume composition can be observed on Mt. Etna. Specifically, gas emissions implicitly contain critical information on the state of the volcano in terms of magma dynamics in the plumbing system.New technologies have improved the ability to identify gas emissions through remote sensing. Since March 2000, the remote sensing group of INGV-OE Catania has regularly measured the volcanic gas in the plume emitted from Mt. Etna by solar occultation FTIR on average 2-3 acquisitions per week. These measurements allow to quantify the column amounts of SO2, HCl and HF in the path between the instrument and the Sun, and obtain SO2/HCl, HCl/HF and SO2/HF ratiosExtracting meaningful information and gaining new insights from 23 years data collection is a challenging task. Here, we perform a data driven investigation exploiting the relationships between volcanic activity and volcanic gas emissions from 2000 to 2023 period. A general decrease in SO2/HCl ratio, due to an increase in the halogens emission rate (HCl and HF), is observed during eruptions that results closely connected with the central conduit of Etna (e.g. 2004 and 2008).This evidence suggests that magma residence time is required to sustain an efficient halogen degassing via summit craters and the lava flow draining gradually led to a break in the magma convective overturn within a shallow reservoir. Whereas, eruptions not connected with the central conduit of Etna (e.g. 2002-03) are preceded by several weeks of elevated SO2/HCl ratio, produced by a relative reduction in HCl emission consistent with inefficient magma circulation that partially inhibits ascent of magma thought the central conduit of Etna enhances the probability of lateral eruptions.
Modeling tsunami generation and propagation: Insights from sensitivity analysis of landslide parameters at Stromboli
Authors: Trolese Matteo , Cerminara Matteo , Esposti Ongaro Tomaso , de' Michieli Vitturi Mattia , Tadini Alessandro
Published: March 2024

Understanding the generation of tsunamis from landslides at volcanic islands is crucial due to their infrequent, yet potentially catastrophic, impact on coastal communities. We present a sensitivity analysis of the effects of different rheological and geometrical landslide parameters on the generation and propagation of tsunamis in the near field. In particular, we employed the MultiLayer-HySEA model to simulate tsunamis generated by landslides occurring along the northwestern flank of the Stromboli volcano, specifically in the area known as Sciara del Fuoco, which is considered most prone to instability. This shallow-water model implements a two-way coupling between a granular material layer representing the landslide and 3 fluid layers representing the water. The parameters investigated include the initial position, density, volume, and shape of the landslide, as well as its friction angles and water-landslide friction coefficients. We varied each landslide parameter to examine its effect on the tsunami wave height and energy at specific locations. We found that the principal parameters of the synthetic waveforms and the landslide volumes are logarithmically correlated when considering subaerial landslides, while they correlated linearly when considering submarine landslides. We than explored the effect of the other source parameters on such analytical relationships. Based on the variability observed in waveform characteristics, we suggest a ranking of importance for the source characteristics that contribute significantly to the uncertainty/variability of the model output. Our study aligns with previous predictions at Stromboli and offers a valuable tool for reconstructing the source parameters of tsunamis based on proximal sea-level measurements, enabling rapid forecasting of subsequent impacts around the volcanic island.
Attribution and Response of Water Use Efficiency to Future Changes  in the Yellow River Basin
Authors: Chen Siwei , Xu Yueping , Guo Yuxue
Published: March 2024

Ecosystem water use efficiency (WUE, defined as the ratio of primary productivity to evapotranspiration) has garnered significant attention in recent years for its role as a vital indicator of the interplay between carbon and water cycles. Numerous studies have underscored the substantial impact of elevated CO2 concentrations on WUE through changes in climate and land surface properties. However, the relative contributions of these factors and their interrelations remain less clear. This study delves into the linkage between WUE and the water-energy exchange dynamics within the Yellow River Basin, employing the Budyko framework model as a foundation. We propose and validate a linear Budyko model tailored to WUE, demonstrating satisfactory physical performance (R2 = 0.60-0.73). Building on this, we construct an attribution framework for WUE, grounded in the Budyko model and global climate models (GCMs), to quantitatively disentangle the impacts of climate and land use change, as well as to elucidate the mechanisms underlying CO2-induced radiative and biogeochemical effects on WUE. Our attribution analysis suggests that the WUE of the Yellow River Basin is anticipated to increase by 0.36-0.84 (g C/kg H2O) in future scenarios, with climate change being the predominant driving force (77.9%-101.4%). The study also uncovers variations in the response of WUE to different drought conditions within the basin. Specifically, we observe an increase in WUE under moderate drought conditions, whereas a decline is noted in most areas as drought severity escalates. Under high emissions scenarios, WUE exhibits a more pronounced sensitivity to drought, particularly under extreme conditions. The outcomes of this research contribute to our understanding of how future CO2 concentration increments, under varying scenarios, may induce changes in WUE in the Yellow River Basin. Moreover, they reveal the prospective response mechanisms of vegetation to drought events within the basin, offering a scientific basis for the formulation of regional ecological strategies and water management practices. 
Understanding uncertainties in the global Earth climate response with reduced complexity climate models
Authors: Sloughter Trevor , Rogelj Joeri
Published: March 2024

Simple climate models provide a flexible, computationally cost-effective way to emulate the more complex and higher resolution earth system models. As ESMs are improved, adding in new processes that weren't explicitly included before, so too can the simple climate models be refined to reflect changes to our understanding of the climate response to changing emissions. New developments in modelling of peatlands, wetlands, permafrost, and negative emissions scenarios have provided new data to test the simple models MAGICC and FAIR. By comparing their projections under the same scenarios used by more complex models, the reduced complexity models' limitations and uncertainties can be shown, and thus they can be improved to better capture the new knowledge. Here, we focus on peatlands, comparing the results of a new module in the model OSCAR with the current output from MAGICC and FAIR, quantifying the impact that explicit peatland processes have on global temperature. Negative emissions scenarios are also considered, all as part of a broader project to understand overshoot pathways, scenarios in which the global temperature anomaly exceeds 1.5°C but returns to a temperature below that mark. These results will show the value and capability of the simple climate models as they continue to be refined to emulate the larger models.
TriGgeR mechanisms of Antarctic ice sheet INStability across the Plio-pLeistocene trAnsitIoN - GRAINSPLAIN project
Authors: Ferrante Giulia Matilde , De Santis Laura , Andò Sergio , McKay Robert , Kulhanek Denise , Gales Jenny , Perrotti Matteo , Zurli Luca , Singh Satish , Rebesco Michele , Lucchi Renata Giulia , Van Der Flierdt Tina , Van Peer Tim , Morigi Caterina
Published: March 2024

Growing evidence suggests that portions of the Antarctic Ice Sheet (AIS) could cross a tipping point over the next decades due to global warming. The Mid-Pliocene Warm Period (mPWP, 3.3-3 Ma, +2°C) is regarded as one possible geologic analog to the climate of the near future, and paleo-sea level during mPWP interglacials indicates that portions of the AIS were lost at that time. However, due to a lack of ice-proximal data, the timing, magnitude and trigger mechanisms of AIS retreats remain unconstrained. Here, we focus on the Ross Sea, where the IODP Exp. 374 Site U1523 recovered the first Antarctic Plio-Pleistocene record from a current-controlled sediment drift in an environment evolving from ice-proximal to open marine over time. U1523 is located where intrusions of warm deep water and outflows of cold water occur today, controlled mainly by the strength and route of the Antarctic Slope Current. To constrain the relative influence of oceanic currents and AIS dynamics on sediment erosion, transport and deposition across the Plio-Pleistocene transition (3.3-2.6 Ma), we integrate grain size, morpho-mineralogical, magnetic fabric analysis and geophysical logs from site U1523 with the multi-channel seismic line IT94-127A. We complement our dataset with a closeby box core (PNRA ODYSSEA exp., box core 08), that can be regarded as a present day analogue. Here, we present our morpho-mineralogical results on the box core and some specific intervals of the mPWP from site U1523. In particular, we perform single mineral Raman spectroscopy which, together with the entire suite of minerals and their relative abundance, highlight the different depositional environments and the source of the detritus, identifying local vs distant and magmatic vs metamorphic sources. Furthermore, we use the geophysical logs to perform rock physics correlation and we tie them to the seismic line, allowing the analysis to be extrapolated along the shelf.
Four decades of cryosphere albedo from spaceborne observations - assessment with field data
Authors: Box Jason , Bahbah Rasmus , Ahlstrøm Andreas , Wehrlé Adrien , Kokhanovsky Alexander , Picard Ghislain , Arnaud Laurent
Published: March 2024

Snow and ice albedo plays a fundamental role in climate change amplification. Its importance is by modulating absorbed sunlight; the largest average melt energy source. Further, the presence or lack of light absorbing impurities including living matter and meltwater effects can strongly influence snow and ice heating rates. Through multiple consecutive satellite missions, cryosphere albedo has been mapped globally and continuously for more than four decades now.This work examines a 42 year record of cryosphere albedo by joining the satellite climate records of snow and ice albedo from AVHRR 1982 to present, NASA MODIS 1999 to present, and EU Copernicus Sentinel-3 2017 to present. The long-term stability of the climate records is examined using independent field data from Greenland and Antarctica. Additionally, the work presents long term trends in snow and ice albedo in relation to the competing effects of surface melting, snowfall and rainfall.
Advances in monitoring vineyard with multiscale and multiplatform data for precision agriculture systems
Authors: Vitale Andrea , Cutaneo Carmine , Buonanno Maurizio , Bonfante Antonello
Published: March 2024

Within a vineyard, the variation in plant water status is intricately tied to the spatial variability of the soil, where the physical attributes of the soil govern the processes shaping the soil water balance. As the soil and its characteristics exhibit inhomogeneity, horizontally and vertically, the productivity and qualitative response within the vineyard become less uniform. In this context, employing proximal sensing to gauge the apparent soil Electrical Conductivity (ECa) and monitoring it throughout the growing season becomes instrumental in understanding the nature of spatial variability within the vineyard. This not only aids in viticultural microzoning, identifying Homogeneous and functional Homogeneous Zones (HZs and fHZs), but also supports field experiments.We propose a machine learning approach that works as a predictive model for soil ECa, involving spatially predicting ECa based on discrete measurements obtained from a network of Time Domain Reflectometry (TDR) probes capable of measuring ECa. This methodology enables the spatial prediction of ECa values across the surveyed area. The main purpose is to create a process that using multiscale and multiplatform measurements helps the farmer monitoring and interacting with the crop in a better way, reducing resources and improving the crop productivity.Records on soil and atmosphere systems, in-vivo plant monitoring of eco-physiological parameters in 2020 and 2021, and spatial variability of plant status monitored through UAV multispectral images were used to test this approach, on a Greco di Tufo grapevines (white) in southern Italy. The apparent EC measurements were obtained using a PROFILER EMP 400 in both dipole modes and with 3 different frequencies (5, 10 and 15 kHz), exploring different depths of the soil.The predictive model shown a good performance, with results that are in good agreement with previous knowledge of the area.
Burned Area Mapping with Sentinel-2 based on reflectance modelling and deep learning – preliminary global calibration and validation
Authors: Padilla Marc , Ramo Ruben , Sierra Sergio , Mota Bernardo , Lacaze Roselyne , Tansey Kevin
Published: March 2024

Current global burned area products are available at coarse spatial resolutions (300-500 m), what leads to large amounts of errors, hindering an accurate understanding of fire-related processes. This study proposes a global calibration method for a sensor-independent burned area algorithm, previously used with 300 m Sentinel-3 Synergy data, and here implemented with 20 m Sentinel-2 MSI imagery. A binomial model that combines reflectance-based burned area predictions constrained by spatio-temporal densities derived from VIIRS active fires is calibrated using a reference dataset generated from Landsat imagery at a sample of 34 units across the globe. Preliminary leave-one-out cross-validation analyses show promisingly high accuracies (Dice of coefficient of 84.8%, commission error ratio of 13.2%, omission error ratio of 17.1% and relative bias of -4.5%), especially taking into account the mismatch of acquisition dates between reference and algorithm input data, what introduces apparent errors on the validation results.
Assumptions on elastic structure in finite-fault models: the case of the secondary zone of uplift measured after megathrust earthquakes
Authors: Ragon Théa , Simons Mark
Published: March 2024

A secondary zone of surface uplift (SZU), located from 200 to 400 kilometers landward of the trench, has been measured after several megathrust earthquakes. The SZU reached a few centimeters hours to days after the 2011 Mw 9.1 Tohoku (Japan) and 2010 Mw 8.8 Maule (Chile) earthquakes. One interpretation is that this SZU is universal, driven by volume deformation around the slab interface (van Dinther et al. 2019). Indeed, published coseismic finite-fault models for these events do not reproduce the measured SZU.Here, we build on the case of the SZU to understand if, and how, our prior assumptions on the forward model can prevent us (or allow us) to make the most out of our dataset. In particular, we investigate under which assumptions the SZU can, or cannot, be predicted with fault slip. We show the SZU cannot be reproduced with coseismic finite-fault models that neglect 3D elastic heterogeneities in lithospheric structure. In contrast, we can recover the SZU with fault slip if elastic heterogeneities associated with the subducting slab are accounted for, as opposed to assuming homogeneous or layered elastic lithospheric structures. The SZU may therefore result from slip on the slab interface, downdip of the main coseismic patch. We suggest SZU might be caused by rapid afterslip, but a deformation of the volume around the fault cannot be ruled out.Reference: van Dinther, Y., Preiswerk, L. E., & Gerya, T. V. (2019). A Secondary Zone of Uplift Due to Megathrust Earthquakes. Pure and Applied Geophysics, 176(9), 4043–4068. https://doi.org/10.1007/s00024-019-02250-z
Summary of S(A)-RIP Phase 1 and Plans for Phase 2: Chemical Reanalyses & Air Quality, Tropospheric Circulation, Extreme Events, and More
Authors: Wright Jonathon , Manney Gloria L. , Fujiwara Mastomo , Wargan Krzysztof , Davis Sean , Diallo Mohamadou , Ploeger Felix , Knowland K. Emma , Weir Brad
Published: March 2024

Reanalysis datasets are widely used to understand atmospheric processes; however, different reanalyses may give very different results for the same diagnostics. The Atmospheric Processes And their Role in Climate (APARC; formerly SPARC) Reanalysis Intercomparison Project, or S(soon to be A)-RIP (https://s-rip.github.io/), is a coordinated activity to compare key diagnostics among atmospheric reanalyses, identify differences among reanalyses and their underlying causes, provide guidance on appropriate usage of reanalyses in scientific studies, and contribute to future improvements in the reanalysis products via collaborations with reanalysis centers and data users. S-RIP Phase 1 (completed in early 2022) focused primarily on the upper troposphere and above and processes linking these regions to the troposphere and surface. We are broadening our efforts in Phase 2 (S-RIP2), with new directions including studies of the tropospheric circulation, extreme weather events, and their links to the stratosphere, along with evaluation of chemical reanalyses, both those with a stratosphere / upper troposphere focus and those that focus on air quality applications. This presentation will provide a summary of Phase 1 results and discussion of future directions for S-RIP2, emphasizing applications to composition and chemistry studies and capacity building for Early Career Scientists. 
New Data Set of Hydrological Angular Momentum With its Associated 6 Days-Long Forecasts
Authors: Dill Robert , Jensen Laura , Dobslaw Henryk
Published: March 2024

Since more than 15 years, GFZ routinely provides daily updated hydrological effective angular momentum functions (HAM) and its 6 days-long forecasts for the study of Earth orientation parameter variability and for improving polar motion and UT1-UTC predictions. GFZ’s HAM time series are part of a consistent set of effective angular momentum functions (EAM) covering the Earth’s major subsystems atmosphere, oceans, and the terrestrial hydrosphere. In addition, all EAM products are consistent with the GRACE/GRACE-FO atmosphere-ocean dealiasing product AOD1B release 06 which is used for gravity field processing and precise orbit determination.For the new HAM data set we switch our hydrological model setup from the Land Surface Discharge Model (LSDM) to the open source, high-resolution hydrological rainfall-runoff-routing model LISFLOOD (https://ec-jrc.github.io/lisflood/). We slightly adapted the latest LISFLOOD 0.05° version for geodetic applications by modifying the snow melting parameterization, the soil depth parameterization, and implementing a seasonal snow storage model for Antarctica to optimize the agreement of simulated terrestrial water storage with mass anomalies from the satellite gravimetry missions GRACE and GRACE-FO on different spatial and temporal scales. Due to (I) up-to-date surface parameter maps; (ii) increased temporal resolution of 3 hours; (iii) enhanced parameterization of hydrological processes such as evapotranspiration, soil infiltration, snow accumulation and dynamic river routing; and (iv) a much more extensive set of atmospheric forcing parameters from ECMWF’s latest global atmospheric reanalysis ERA5, the derived HAM time series could be substantially improved in terms of long-term stability, seasonal amplitudes, sub-seasonal and episodic variations, and short-term forecasts. Furthermore, the new HAM data set is consistent with the new AOD1B release 07.
A ranking-based sub-selection of the climate ensemble for climate impact studies
Authors: Sikorska-Senoner Anna E. , Rajczak Jan , Zappa Massimiliano , Kotlarski Sven
Published: March 2024

Impact modelling requires fine-scale climate information to simulate possible impacts of climate change on different sectors such as agriculture, water management or food production. Such impact models are run at a much finer spatial and temporal resolution than global or regional climate models, and therefore a pre-selection of climate model chains is required due to the computational limitations of these models. To date, there is no structured guidance for practitioners and impact modelers on how to select climate model chains. This is also the case for the Swiss Climate Scenarios (CH2018), which main products are usually communicated to the users as median, upper and lower estimates calculated for each product and time slice individually.In this work, we present a new sub-selection climate ensemble method tailored to the users’ needs and the desired emission scenario (Representative Concentration Pathways, RCP). The method builds on the core statements of the CH2018, i.e., droughts, heat waves, heavy rainfalls, and snow-scarce winters, and complements them with three further application cases, i.e., temperature, precipitation, combined temperature and precipitation. For each application case and each RCP, three representative climate model chains are selected from the full ensemble to cover the range of the climate change signal. These include one chain corresponding to the upper, middle and lower limits of the ensemble range. The selection of climate model chains is based on the climate change signals calculated for a set of pre-selected climate indicators (e.g., mean temperature or number of hot days). Next, each climate model chain is ranked for each climate indicator according to its climate change signal calculated between the end of the century and the CH2018 reference period (i.e., 2070-2099 vs. 1981-2010). This ranking is used to divide the models into three terciles, representing the upper, lower and middle bounds of the ensemble. For each tercile, one climate model chain is next selected that best meets the selection criteria. As a result, a sub-selected ensemble with three climate model chains is proposed to the users.The method has been developed for Switzerland and five major Swiss regions using the CH2018 GRIDDED dataset, which contains of 68 daily, transient and bias-corrected simulations of climate model chains covering the simulation period of 1981-2099. The method allows the CH2018 users to choose from three RCPs (RCP2.6, RCP4.5 and RCP8.5) and seven application cases to obtain a set of three representative climate model chains. The selected climate model chains were next successfully implemented in a hydrological impact model to assess their applicability for assessing climate impacts on hydrological variables. The method is very flexible and can easily be applied to a new or an extended climate model ensemble or to newly defined application cases.
Advancing Spatiotemporal Rainfall Nowcasting through Deep Learning Techniques
Authors: Abdelhalim Ahmed , Rico-Ramirez Miguel , Liu Weiru , Han Dawei
Published: March 2024

For weather forecasters and hydrologists, predicting rainfall in the short term – minutes to a few hours – is crucial for a range of applications. While traditional nowcasting methods excel in operational settings, they face limitations in predicting convective storm formation and high-intensity events. Enter deep learning, a powerful tool transforming numerous fields. Convolutional neural networks, in particular, have shown promise in improving nowcasting accuracy. These networks can learn complex patterns and relationships within data, like the intricate tapestry of rainfall variations observed in historical radar sequences. However, capturing long-term dependencies in this data remains a challenge, resulting in fuzzy nowcasts and underestimating high-intensity events. This study proposes a novel deep learning model that goes beyond simple extrapolation, effectively capturing both the spatial correlations and temporal dependencies within rainfall data. Our hybrid convolutional neural network architecture tackles this challenge through three key components: Decoder & Encoder: These modules focus on unraveling the intricate spatial patterns of rainfall and a temporal Module to learn the subtle long-term evolutions and interactions between rain cells over time. By capturing these temporal dependencies, the model can produce more accurate forecasts. To evaluate the model performance, it is compared against both deep learning and optical flow baselines. This presentation will introduce the model and provide a summary of its performance in spatiotemporal rainfall nowcasting.Keywords: deep learning; spatiotemporal encoding, rainfall nowcasting; radar; optical flow
The Global Greenhouse Gas Watch
Authors: Balsamo Gianpaolo , Riishojgaard Lars Peter
Published: March 2024

Greenhouse gas emissions, greenhouse gas concentrations and global mean temperature all continue to rise, and in order to stay within the temperature limits stipulated in the text of the Paris Agreement, mitigation action is becoming increasingly urgent However, the fact that we cannot quantitatively and reliably predict future GHG concentrations – and therefore climate scenarios – from assumed future emission pathways is a complicating factor when designing mitigation action. Even more problematic is the assessment the impact or effectiveness of many current or proposed mitigation activities, since it often has to be based on indirect measures such as avoided emissions with respect to a hypothetical baseline, or carbon stored, e.g. in the land or ocean biosphere, neither of which can be directly linked to atmospheric concentrations.In order to provide robust, actionable data that will help Parties to the UNFCCC and other stakeholder design and develop mitigation action and monitor its effectiveness, the World Meteorological Congress in May 2023 endorsed the Global Greenhouse Gas Watch (G3W) as an internationally coordinated framework to provide near-real time GHG (CO2, CH4 and N2O) flux estimates based on atmospheric modelling and atmospheric observations.  At COP28 in Dubai, the G3W was formally recognized by the Subsidiary Body for Scientific and Technological Advice (SBSTA-59) to the UNFCCC.Currently a G3W implementation plan is in development, with the aim of submitting it for approval by the WMO Executive Council by mid-2024. Some of the key elements of the plan are a significant strengthening of the global GHG observing capabilities, improved near-real time exchange of both observational data and flux estimates, and routine intercomparision of model output among all participating flux estimation centers.The presentation will introduce the overall G3W development timeline which aims for a full operational capability to be ready for the Second Global Stocktake in 2027-28, with the main focus on the near-time activities planned for 2024-25.
Impact of long-lasting flood water on agricultural productivity: a case study of the May 2023 Emilia Romagna floods
Authors: Sarcinella Margherita , Pal Jeremy S. , Mysiak Jaroslav
Published: March 2024

Heavy rainfall events occurred in the Emilia-Romagna region in Northern Italy as a result of two major storms on May 2nd and 17th that led to the overflow of 22 rivers and triggered over 250 landslides. This event claimed 15 lives, forced 10 thousand people to evacuate and caused over 400 road closures. Due to a prior long-lasting winter drought and poor land use management that hampered effective water drainage, floodwaters stagnated for over a month in some areas, exacerbating the crisis. Over 40% of regional agricultural land was flooded leading to irreversible crop damage, in some instances, entire harvest loss. The objective of this study is to build a consistent and replicable methodology to quantify the agricultural damages and economic loss resulting from stagnated floodwater over cropland using the Emilia Romagna floods as a case study. The study emphasises the use of remote sensing data as a tool to achieve accurate impact estimates. Sentinel-1 SAR imagery is used to derive 10-meter resolution flood extent and duration maps at a revisit time of 3 to 6 days. The maps are matched with crop data available for the region from the iColt database and damages are computed as a function of ponded water duration and crop type as well as resistance to oxygen deprivation. The data, comprised of crop type, growing season and sowing date, allow for the characterization of the growth state of each crop at the time of flooding, implicitly providing insights on the probability of plant survival. The use of satellite-derived vegetation indices as markers for post-disaster crop recovery, with a focus on identifying crop-specific recovery rates and patterns is highlighted. This study highlights the need for collaborative efforts with key regional entities and can provide factual-hazard-based agricultural loss estimates to local institutions. These findings can guide targeted adaptation strategies, improve the spatial accuracy of loss assessment, and improve our comprehension of the aftermath of prolonged floods on agricultural output.
Numerical experiments on estimating the fault frictional properties and the viscosity from the postseismic deformation
Authors: Ohtani Makiko
Published: March 2024

Following large earthquakes, postseismic crustal deformations are often observed. They include the afterslip and the viscoelastic deformation of the crust and the upper mantle, activated by the coseismic stress change. In order to predict the future deformations, and the stress change distributions, it is important to divide each deformation. The physical parameters; frictional properties of the fault and the rheological properties are the key to determining the slip behavior, but they are generally unknown.Data assimilation (DA) studies have attempted to estimate the frictional properties directly from the observational data. DA incorporates the observed data into the physics-based model to construct a more plausible model. When DA works well, we can obtain the physics-based model, including the physical properties, that can quantitatively explain the observed data. The constructed physics-based model can be used to simulate the slip evolution beyond the data period, i.e., prediction of the deformation.There are two types of DA technique applying to nonlinear system, the sequential method called as Ensemble Kalman filter method (EnKF) and the variational method called as 4DVAR. For the fault system, EnKF is applied to the deformation data to estimate the physical variables (van Dinther et al., 2019, Hirahara and Nishikiori, 2019). 4DVAR is also applied to the afterslip assuming elastic medium to estimate the fault frictional properties (Kano et al., 2015; 2020). If the physics-based model under consideration is linear, the sequential and the variational methods are consistent, but this is not the case for fault systems.In this presentation, I construct a simple model that include the fault slip that follows the rate- an state- friction law and the viscoelastic deformation. Then I apply both EnKF and 4DVAR, and compare the results to discuss the characteristics of the methods.
Earthquake focal mechanisms before and after the onset of re-inflation at Askja caldera, Iceland
Authors: Siggers Isabel , Winder Tom , Rawlinson Nicholas , White Robert S. , Brandsdóttir Bryndís
Published: March 2024

Askja, an active volcano in Iceland’s Northern Volcanic Zone, has experienced over 70 centimetres of uplift since August 2021, following several decades of ground surface deflation. In the same month that surface uplift began, there was also an overall increase in shallow microseismicity. This overlap suggests that there is a link between the shallow seismicity and re-inflation, but much more information is needed to constrain an exact mechanism. To gain more insight into the stresses driving seismicity beneath Askja, and how they may have changed with the onset of uplift, moment tensor solutions were constructed from a subset of events within the Askja caldera, both before and after the start of re-inflation. The goal is to uncover any dominant earthquake slip orientation patterns, and how they have changed post August 2021. Cambridge’s Volcano Seismology Group has maintained a dense seismic network surrounding and within Askja from July 2007 to the present day, which provides sufficient data to produce well constrained moment tensor solutions, even for events as small as magnitude 0.5. Moment tensor solutions constructed from the first year of inflation suggest that the direction of slip along faults encircling the crater lake Öskjuvatn did not change when Askja switched from deflation to re-inflation; however, data from a longer recording period is needed to provide a definitive conclusion. With another 12 months of data from the main network now downloaded, as well as additional data from a supplementary dense network of seismic nodes within the Askja caldera from July 2023 to September 2023, a more in-depth analysis of the moment tensor solutions for shallow microearthquakes underneath the region of uplift through time is now possible. The preliminary results of this analysis will be presented, along with plans for future interrogation of this enhanced dataset.
Projections and drivers of future changes in biological pump as inferred from apparent oxygen utilizations 
Authors: Couespel Damien , Tjiputra Jerry , Lauvset Siv Kari , Goris Nadine
Published: March 2024

The biological carbon pump (BCP) stores a large quantity of carbon in the deep ocean and is a major contributor to the surface to depth gradient in dissolved inorganic carbon. Without the BCP, the atmospheric CO2 concentration would be higher by about 200 ppm. Thus, the BCP is a key component of the global carbon cycle, and yet its future evolution is highly uncertain. In model simulations, changes in the BCP are often estimated using the Apparent Oxygen Utilisation (AOU) that measures the difference between the in-situ oxygen content and the saturated oxygen content. With a changing climate, AOU can vary because of changes in ocean circulation or changes in remineralization. Here, we combine AOU with water mass ideal age to take apart changes in the BCP due to circulation change and to remineralization change. We will apply our analysis to a set of Earth System Models under different global warming scenarios. We will determine the sensitivity of these drivers to different level of climate change and investigate the spatio-temporal variability and magnitude of the projected BCP changes. This analysis may help to trace models uncertainty in future BCP change back to ocean physic and marine biogeochemistry. 
How does subaerial erosion of carbonate platform distort the sedimentary record?
Authors: Liu Xianyi , Hidding Johan , Hohmann Niklas , Burgess Peter , De Vleeschouwer David , Jarochowska Emilia
Published: March 2024

Carbonate platform strata have been extensively utilized to decipher geological history. However, due to the fluctuating ambient environment and the complex growth pattern of carbonate factories, preserved records are generally incomplete. For example, given the platforms are located in shallow water environment, they are prone to subaerial denudation when the sea level falls. Numerical modelling is a popular approach to examine spatial and temporal heterogeneities of carbonate platform architectures. While growth and submarine transportations that have been extensively considered, surprisingly, substantially less efforts have been invested to subaerial denudation and its effects on 3-dimentional carbonate platform architecture (e.g., the denudation rates are simplified to constant dissolution rates regardless of the varying ambient environment and local geomorphology).Herein, we implemented a model with chemical dissolution and physical erosion, calibrated with 35Cl (a geochemical proxy used to estimate kyr-scale denudation) karst regions into CarboKitten.jl (https://mindthegap-erc.github.io/CarboKitten.jl/), a new open-source carbonate platform model. We compared the outputs of models with and without the denudation by using mathematical tool (LBP method) and assessed how the presence of denudation distorts the age-depth relationships. We find that the inclusion of denudation could increase both temporal and spatial heterogeneities, which may decrease the estimation biases on age-depth model. Our results emphasize the importance of considering subaerial denudation in reconstructing geological histories. This study provides a comprehensive framework for refining interpretations and enhancing the accuracy of paleoenvironmental reconstructions based on carbonate platform sediments.