bluuebunny/crossref_metadata_2025 huggingface dataset:
Predicting Vegetation Phenology using Machine Learning based on Wavelet Transform of Meteorological Drivers
Authors: Hafezi Rachti David , Reimers Christian , Liu Guohua , Winkler Alexander J.
Published: February 2023

Climate change and extreme weather events have far reaching consequences for terrestrial ecosystems, particularly for vegetation phenology. However, the effects of meteorological variations on phenology are still not well understood, rendering phenology modeling a major challenge. Here we adapt explainable machine learning (ML) techniques from computer vision to investigate the role of meteorological variability and its multi-scale memory on phenology.Specifically, we develop a modelling framework using convolutional neural networks trained on wavelet transformed key meteorological variables to predict vegetation greenness. The wavelet transformation of the meteorological time series (temperature, soil moisture, and shortwave radiation) yields two-dimensional images that reflect their different frequencies across a broad spectrum from multi-year variability to synoptic time scales. We use the green and red chromatic coordinate (GCC and RCC) from the ground-based PhenoCam network as proxies for the daily state of vegetation phenology. Additionally, to compensate for calibration artifacts across the sites, we use the satellite-based normalized difference vegetation index (NDVI) for normalisation.Explainable ML techniques, such as Integrated Gradients, in combination with the wavelet images give us insight into the importance of the various meteorological factors as well as the length and timing of the weather events for the prediction of phenology. We present first results of our modelling framework and illustrate the effects of meteorological variability, with an emphasis on spring phenology, at different time scales. In particular, we use the interpretability of our model architecture to develop hypotheses and test them with manipulation experiments. In addition, we explore the model's ability to spatially extrapolate to unseen locations during training.Such studies are important to understand the impact of climate change on the seasonal cycle of terrestrial ecosystems and to find out whether ML with explainable techniques can lead to a better understanding and thus improvements in modelling phenology.
Seasonal increase of methane emissions linked to warming in Siberian tundra
Authors: Sachs Torsten , Rößger Norman , Wille Christian , Boike Julia , Kutzbach Lars
Published: February 2023

Methane (CH4) is a strong greenhouse gas that accelerates climate change, yet its emissions from wetlands in general and Arctic permafrost-affected wetlands in particular remain very uncertain in the global CH4 budget. Arctic CH4 sources and the expected effect of permafrost thaw on these sources have gained much attention by the public, media, policy makers, and researchers during the past decade, but neither inversion nor process-based models provide clear trends in emissions and there has not been any observational evidence for increasing CH4 emissions from Arctic permafrost ecosystems.Here, we provide this observational evidence. Based on the longest record of direct Arctic CH4 flux observations acquired since 2002 at a Siberian tundra site using the eddy covariance method, we found an increase in the early summer (June and July) CH4 emissions by 1.9 ± 0.7 % yr-1 since 2004 along with a strong increase in June air temperatures of 0.3 ± 0.1 °C yr-1. Although the tundra’s maximum source strength in August has not yet changed and the overall mean annual emissions of 171.5 ± 12.3 mmol m−2 yr−1 remain in the lower half of the published range, the increase in early summer methane emissions shows that atmospheric warming has begun to affect the methane flux dynamics of permafrost-affected ecosystems in the Arctic. This is especially noteworthy, given the very thick and cold continuous permafrost in the study area compared to most other observational sites.While the observed changes clearly happen in the early warm season, we also estimate 39 % of the annual emission to originate from the re-freezing and frozen period, highlighting the importance of the cold season for annual permafrost CH4 emission estimates and the substantial challenges in achieving continuous data coverage in the Arctic winter.
High Altitude and Long-range Aircraft (HALO) measurements of carbon monoxide and methane to characterize dynamical transport processes in the tropical upper troposphere
Authors: Ort Linda , Röder Lenard , Hoor Peter Michael , Lelieveld Jos , Fischer Horst
Published: February 2023

The dynamics and transport processes in the upper troposphere are of great importance for the global long-term distribution of greenhouse gases and pollution tracers, and hence for the anthropogenic impact on the Earth climate. Especially in the tropics, large amounts of carbon monoxide (CO), carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) are produced by e.g. biomass burning, anthropogenic and agricultural activities. These tracers are vertically transported by deep convective cells in the InterTropical Convergence Zone (ITCZ) into the Tropical Tropopause Layer (TTL). Long-range transport processes distribute the tracers globally, which have lifetimes of up to years and decades. It is crucial to understand the details of the transport processes and how the tracers are distributed throughout the upper troposphere and the lower stratosphere (UTLS).During several aircraft campaigns (CAFE Brazil 2022/2023, SouthTrac 2019, CAFE Africa 2018, OMO 2015, ESMVal 2012) CO, CH4 and N2O have been measured nearly globally and especially in the tropics with quantum cascade laser absorption spectrometers deployed on the High Altitude and Long-range Aircraft (HALO). Combining these measurements, we can present a good overview of the large-scale distribution of the tracers in particular in the tropical troposphere up to altitudes of approx. 14 km.The in-situ aircraft measurements will be used to study interhemispheric transport processes and regional trace gas budgets at the base of the TTL. Therefore, they will be further combined and investigated with modelling data and back trajectories. 
SpannEnD – Prediction of the recent crustal stress state of Germany using a 3D geomechnical-numerical model
Authors: Ahlers Steffen , Reiter Karsten , Hergert Tobias , Henk Andreas , Röckel Luisa , Morawietz Sophia , Heidbach Oliver , Ziegler Moritz , Müller Birgit
Published: February 2023

For the safe usage of the subsurface the stress state is of great importance, e.g., for borehole stability, mitigation of induced seismicity or the search and long-term safety of a high-level nuclear waste deposit. However, the state of knowledge concerning the stress state in Germany is limited as only unevenly distributed stress measurements are available which frequently provide only one component of the stress tensor. The SpannEnD (Spannungsmodell Endlagerung Deutschland) project aims to improve this knowledge with the help of a 3D geomechanical-numerical model. The model is calibrated on available stress magnitudes and enables a continuum-mechanics based prediction of the stress state and its local variability for Germany.The 3D geomechanical-numerical model comprises the upper lithosphere and contains 22 lithological units parametrized with individual mechanical properties (Young’s modulus and Poisson’s ratio) and densities. Linear elasticity is assumed and the finite element method (FEM) is used to solve the equilibrium of forces. Overall, the model contains about 11 million hexahedral elements resulting in a lateral resolution of 2.5 x 2.5 km2 and a vertical resolution of up to 250 m. The model is calibrated by adaptation of displacement boundary conditions with magnitudes of the minimum (Shmin) and maximum horizontal stresses (SHmax). The model results show an overall good fit with these stress magnitudes used for calibration indicated by a mean of the absolute stress differences of 4.6 MPa for Shmin and 6.4 MPa for SHmax. Furthermore, the results agree well with additional data sets excluded from calibration but used for validation, e.g., with a mean of the absolute stress differences of 1.1 MPa for vertical stress magnitudes and an absolute mean deviation of the orientation of SHmax with regard to World Stress Map data of 11.9°.
Synchronization of Blocking Patterns in Diifferent Models, Connected So As to Form a “Supermodel” of Future Climate
Authors: Duane Gregory , Schevenhoven Francine , Weiss Jeffrey
Published: February 2023

The established benefits of post-processing the results of multi-model ensembles, even by simple averaging, suggest a more radical approach: The models should be combined more frequently in run-time so as to form a single “supermodel”.  Simple nudging of models to one another, as frequently as the models might assimilate data from observations, combines model fusion with a reasonable degree of model autonomy.Key to the success of the supermodeling approach is the phenomenon of chaos synchronization, known in the field of nonlinear dynamics, wherein two chaotic systems synchronize when connected through only a few of their variables, despite sensitive dependence on initial conditions. Synchronization gives rise to consensus among models. The nudging coefficients can be trained so that that consensus agrees with observations, because the effective dynamics of the trained supermodel, regarded as a single dynamical system, matches the dynamics of nature. Yet the number of independent nudging coefficients that must be trained is far less than the number of trainable parameters in a typical climate model.It is expected that supermodeling will be especially useful for improving the representation of localized structures, such as blocking patterns, which will wash out if de-synchronized output fields of different models are combined by averaging.  We confirm a hypothesis that such coherent structures will synchronize even when the underlying fields do not, because the internal synchronization within each structure re-enforces synchronization between models: A configuration of CAM4 and CAM5 models, of different resolution, connected by nudging, exhibits correlated blocking activity even when the flows do not otherwise synchronize.  We further explore the basis for correlated blocking activity in a pair of coupled quasi-geostrophic channel models. The local synchronization error is lower in a region of the channels where blocks form than elsewhere in the channels. Blocking correlations emerge as a vestige of “chimera synchronization”, the phenomenon in which complete synchronization of two spatially extended systems is intermittent in space as well as time. Such partial synchronization of different models in the regions of blocks - and of other structures such as jets, fronts, and large-scale convection - would be particularly useful for projecting climate-change patterns in extreme events associated with those structures.
Unravelling the complex dynamic of slow-moving landslides in the Flysch zone region, Lower Austria. A case study of the Hofermühle catchment.
Authors: Jiménez Donato Yenny Alejandra , Carraro Edoardo , Marr Philipp , Kanta Robert , Glade Thomas
Published: February 2023

Slow-moving landslides are complex processes that represent a significant challenge for landslide dynamic analysis and disaster risk reduction. In some cases, they have been considered as early signals of potential destructive events as they can accelerate under specific climatic conditions, causing significant damage.  However, slow-moving landslides have been constantly neglected as the require significant time, human resources, and specific numerical models to assess their non-uniformity. Considering the existing gaps and the lack of data of slow-moving landslides in Austria, a long-term monitoring project has been carried out by the ENGAGE group of the University of Vienna. Several investigation techniques for hydro-geo monitoring have been installed in Lower Austria for multi-temporal landslide investigation in several landslides, using them as living laboratories. Therefore, the present study aims to integrate the valuable hydro-mechanical data to bring light on potential acceleration conditions of slow-moving landslides, frequency and intensity relationships and cascading hazards initiated from within the slow-moving landslide mass.  The geographical and geological conditions of the province of Lower Austria place it as a very susceptible region to the occurrence of landslides. The predominant geology correspond to the units of the Flysch Zone and the Klippen Zone, which are mechanically weak units composed by intercalation of limestones and deeply weathered materials. These conditions, along with the hydrological conditions, land use changes and other anthropogenic impacts contribute to the instability of the region. Consequently, in order to understand landslide processes and mechanisms, we attempt to integrate the hydro-mechanical data compiled from the monitoring sites to model a complex event triggered in 2013, in the Hofermühle catchment, district of Waidhofen an der Ybbs, in order to improve our understanding of landslide conditioning factors and triggering mechanisms of potential cascading hazards in the region.
Impacts of anthropogenic activity and climate change on water resources for the whole of Mongolia by using process-based eco-hydrology model
Authors: Nakayama Tadanobu
Published: February 2023

In Mongolia, overuse and degradation of groundwater is a serious issue. The authors have recently applied a process-based eco-hydrology model, NICE (National Integrated Catchment-based Eco-hydrology) to urban and mining hubs to explicitly quantify spatio-temporal variations in water availability (Nakayama et al., 2021a, 2021b). In this study, NICE was scaled up to the total of 29 river basins in the entire country (Ministry of Nature, Environment and Tourism, 2013). The model simulated the effect of past climatic change and human activity on water resources during 1980-2018 there. The model reasonably reproduced observed river discharge with a maximal value during summer rainfall seasons. The simulation also revealed heterogeneous distributions of hydrologic budget and its response to climatic and anthropogenic disturbances. In addition, the authors detected hot spots of groundwater degradation by anthropogenic activity in the national scale. Analysis of relative contribution of environmental factors further clarified the characteristics in these areas and quantified spatio-temporal trends in groundwater level due to the effects of changes in precipitation and various water uses. Generally, the result showed changes in precipitation had a large effect on changes in groundwater levels until 2000. In contrast, the model clarified human activities have recently had a large impact on groundwater level changes (Banerjee et al., 2014). This trend was particularly conspicuous in river basins with urbanization and mining development such as Orkhon, Kharaa, Tuul, Galba, Ongi, Altain Uvur Govi, and Taats River Basins. This methodology is powerful to resolve future competition for water resources in areas with fewer inventory data that could potentially trigger conflicts between urban, mining, industry, herders and local communities. References;Banerjee, R., et al. 2014. 2030 Mongolia: Targeted Analysis on Water Resources Management Issues, https://www.2030wrg.org/mongolia-targeted-analysis-wrm-issues/.Ministry of Nature, Environment and Tourism. 2013. Basin Boundary Data in Mongolia, Ulaanbaatar.Nakayama, T., et al. 2021a. Ecological Modelling, doi:10.1016/j.ecolmodel.2020.109404.Nakayama, T., et al. 2021b. Ecohydrology & Hydrobiology, doi:10.1016/j.ecohyd.2021.07.006.
Dust impacts on storm development in the Eastern Mediterranean
Authors: Chaniotis Ioannis , Nenes Athanasios , Flocas Helena
Published: February 2023

Suspended particles of mineral dust are known to have a strong impact on the evolution of clouds and precipitation from meteorological to climate timescales. The ability to understand and predict the impacts of dust outbreaks on storm development and evolution would strongly benefit water management, food security, agriculture, and flood early warning systems. This is especially true for the Eastern Mediterranean, being a region heavily impacted by climate extremes and events (drought, floods) and frequent dust transportation from the Saharan desert throughout the year. To investigate the impact of mineral dust on the characteristics of storm development in the E. Mediterranean, several cases studies were examined with the aid of the Integrated Community Limited Area Modeling System (ICLAMS), a version of the Regional Atmospheric Modeling System (RAMS) augmented to include various parameterizations and numerical schemes of the complex microphysical processes of the forementioned aerosol particles. All cases involved storms developed in frontal systems with considerable vertical development and potential for deep convective clouds characterized by strong wind gusts, high rainfall and hailfall rates. In the simulations, dust emissions were allowed to provide particles that act as cloud condensation nuclei (CCN) and ice nuclei (IN). From the simulations we investigate how different descriptions of primary ice formation may affect results regarding cloud and precipitation characteristics, as well as the potential role of ice multiplication processes and the impact of enhanced cloud glaciation on convective invigoration of the storm clouds. In all cases considered (without any effects of ice multiplication and enhanced glaciation from it), precipitation patterns were spatially shifted under the influence of dust, maximum cloud updrafts were significantly increased, and the extreme conditions of rain and hail rates were enhanced considerably (up to 45% and 100% respectively).
What’s brewing? Impacts of cultivation management on the Coffea arabica soil microbiome
Authors: Kutos Steve , Bennett Ruth , Muletz Wolz Carly
Published: February 2023

Coffea arabica (coffee) is cultivated on ~28-million acres and is essential to local economies in the tropics. Coffee cultivation, however, is threatened by ongoing climate change as its optimal growth occurs in narrow temperature and precipitation ranges. Areas currently growing coffee might become unsuitable leading to increased deforestation and negative effects on coffee quality. These impacts may be especially strong in coffee cultivated in sun-grown monocultures (~75% of all production) versus shade-grown agroforestry systems given relatively higher temperatures in deforested landscapes. As such, shade-grown coffee systems might be one management strategy used to buffer from future climatic shifts. While shade-grown systems provide many ecosystem benefits, the impact of the cultivation system on soil microbiomes is poorly understood. Soil microorganisms perform vital ecosystem functions including aiding plants in nutrient acquisition, buffering against stress, as well as improving nutrient cycling. This is particularly true in shade-grown coffee systems where soil carbon could be increased through increased microbial biomass and soil nitrogen could be increased through increased plant-association with N-fixing bacteria. Therefore, further understanding of the effects of coffee cultivation methods on soil microbial communities may be key to future coffee productivity and local soil biogeochemical function. To explore these themes, we sampled the soil microbial communities at 30 coffee farms in Colombia, Peru, and El Salvador. These farms varied in cultivation system (sun vs. shade) and flavor profiles that separate specialty grade from conventional quality. Our aim was to explore if soil microbiome diversity and composition differ among the three countries, cultivation systems, and coffee quality. We sequenced the DNA of bacterial (16S) and fungal (ITS) communities in coffee soil on an Illumina MiSeq with analysis completed in QIIME2 to identify microbial taxa and composition. Coffee soil microbiomes had similar relative abundance of phyla and similar number of bacterial and fungal taxa, regardless of country of origin or cultivation system. However, coffee soil microbiomes showed pronounced differences in the microbial community composition among the different countries and cultivation systems. We show that biogeography is an important determinant of coffee soil microbiomes and location-specific impacts need to be considered in future coffee management. Further, our data suggests that sun-grown systems can alter microbial community composition compared to more-sustainable shade-grown systems potentially changing soil functionality. As an example, there were increases in taxa punitively classified as mycorrhizal fungi and N-fixing bacteria in shade-grown coffee systems. Our next steps are to link this microbial data to coffee quality and soil characteristics to uncover potential factors influencing the community structure as well as nutrient cycling rates.
A novel methodology for remote sensing retrieval of rainfall rates
Authors: Ignaccolo Massimiliano , De Michele Carlo
Published: February 2023

We propose a new methodology for rainfall rate retrieval from remote sensing observations using 166 datasets from 76 different locations on Earth's surface. The method rests upon the data science parametrization of the drop size distribution [Ignaccolo and De Michele (2022) : https://doi.org/10.1175/JHM-D-21-0211.1]. It retrieves the possible triplets (drop count, mean diameter of the drop size distribution, skewness of the drop size distribution) associated with given values of the horizontal and vertical reflectivities. We demonstate how this novel approach is superior to a standard one based upon the mass weighted diameter, normalized intercept and gamma functional form for the drop size distribution. 

 
In situ ion composition observations of Ganymede’s outflowing ionosphere
Authors: Valek Philip , Waite J. Hunter , Allegrini Frederic , Ebert Robert , Bagenal Fran , Bolton Scott , Connerney John , Kurth William , Szalay Jamey , Wilson Robert J.
Published: February 2023

On 7 June 2021 the Juno spacecraft passed through the Ganymede magnetosphere, with a closest approach altitude of 1046 km. While in the magnetosphere, the Jovian Auroral Distributions Experiment-Ion (JADE-I) sensor observed outflowing ionospheric ions. These are the first in situ observations of the ionospheric ion mass composition. The outflowing ions consist of O2+, O+, H2+, H+, and H3+. Ion densities estimated from the measurements agree with the electron density determined by the Waves instrument to within a factor of 2.5. The light ions appear to be in hydrostatic equilibrium, and the altitude profile is generally symmetric between the inbound and outbound legs of the flyby. H3+ ions are an exception to this, with the ratio of H3+/H2+ being ~a factor 4 lower on the outbound than the inbound leg. The heavy ions have higher densities outbound than inbound. The outflowing flux of light ions peak near closest approach, but the heavy ions peak outbound of the flyby.
Atmospheric moisture intrusion into the Arctic: sources, impact, and trends
Authors: Wang Hailong , Zhang Rudong , Zou Yufei , Ma Weiming , Rasch Philip , O'Brien Travis
Published: February 2023

Atmospheric water vapor plays an enormously important role in the water cycle and energy budget of the Arctic. Water vapor in the Arctic also participates in many important feedback mechanisms influencing the climate response to forcing agents and the Arctic amplification. In this study, we conduct analysis of atmospheric moisture transport into the Arctic based on reanalysis products and CMIP6 model simulations. We are particularly interested in the episodic atmospheric-river-like features (AR or moisture intrusion) that play an important role in delivering water to the Arctic. Based on the method of using column-integrated meridional vapor transport for characterizing AR events, we find that the mean AR frequency peaks in the Atlantic sector in all seasons except that it’s more zonally widespread in summer. An increasing trend in the Arctic AR frequency in the recent decades identified from ERA5 can be captured by few CMIP6 models. The historical Arctic AR frequency, sea ice concentration and Arctic warming are highly correlated. Atmospheric circulation patterns that drive the interannual and decadal Arctic AR variation contribute substantially to the historical Arctic warming. We also use the Community Earth System Model (CESM), equipped with a water tagging capability, to quantify contributions of surface evaporation within the Arctic versus from lower-latitude regions as a source of water to the Arctic and characterize moisture transport pathways that control the Arctic water vapor distribution.
A first look at the OPERA Surface Water eXtent and Land Surface Disturbance products and their applications
Authors: Bato M. Grace , Devlin Kelly , Dhillon Rubie , Bonnema Matthew , Sangha Simran , Niemoeller Samantha , Pickens Amy , Shiroma Gustavo H. X. , Handwerger Alexander L. , Jones John W. , Hansen Matthew , Osmanoglu Batuhan , Venkataramani Karthik , Fattahi Heresh , Bekaert David , Song Zhen , Chan Steven
Published: February 2023

Satellite remote sensing data provide key information needed to understand the dynamic behavior of our planet as well as to prepare for, respond to, and recover from disasters. The Observational Products for End-Users from Remote Sensing Analysis (OPERA) project at the Jet Propulsion Laboratory, in partnership with the US Geological Survey and the University of Maryland, starts releasing near-global products that are based on Harmonized Landsat-8 Sentinel-2 A/B (HLS) optical datasets in February 2023: (1) Dynamic Surface Water eXtent (DSWx-HLS) and (2) Land Surface Disturbance (DIST-HLS) product suites. These derived products have applications including  monitoring and guiding future hazard management and recovery efforts. While OPERA does not have an urgent response requirement for disasters, the project will process and deliver the data to end-users as soon as possible. HLS has 2-3 day revisit frequency at the equator allowing the potential for OPERA products to help provide analysis ready data from before, during, and after some events to aid disaster response and recovery efforts. All the DSWx and DIST products will be freely available to the public through various Distributed Active Archive Centers (PO.DAAC for DSWx, https://podaac.jpl.nasa.gov/; LPDAAC for DIST, https://lpdaac.usgs.gov/) and NASA’s Earthdata Search platform based on their scheduled operational release.Here, we present applications of the first provisional products from the DSWx-HLS and DIST-HLS suites to monitor changes in water bodies and vegetation cover due to droughts, floods, and wildfires. In particular, we focus our analysis on: (a) drastic extent changes in reservoirs,  such as for Lake Mead from 2014-present, (b) mapping flood extents such as the 2020 dam failures in Midland, Michigan, and (c) mapping burned areas due to wildfires such as the 2022 wildfires in New Mexico and in California. We develop open-source tutorials using GIS software and Jupyter Notebooks to visualize and showcase these applications. Both the provisional data and the tutorials are available on the OPERA website (https://www.jpl.nasa.gov/go/opera) to ensure broad access and reproducibility. 
How does Eocene warming affected elevation-dependent warming?
Authors: Blau Manuel Tobias , Kad Pratik , Ha Kyung-Ja , Zhu Jiang
Published: February 2023

Elevation-dependent temperature change is a phenomenon found in mountain regions with complex terrain, mostly in the Himalayas and the high terrain of the Tibetan Plateau, where regions in high elevation feature high rates of warming than the region in lower elevation. This pattern referred to as elevation-dependent warming. However, does elevation-dependent warming exist in Eocene hothouse without Tibetan Plateau as well and lower altitude mountain ranges?The Eocene era is considered a replication of the future climate with high atmospheric carbon dioxide. We utilized CESM1.2 as part of the DeepMIP simulations to analyze elevation-dependent temperature change in different mountain ranges in the Eocene and explained the findings using a linear surface energy balance decomposition. The results feature a land-sea contrast with amplification over land and elevation-dependent temperature changes in all mountain ranges with distinct seasonality and pattern. The results suggest that radiative feedback processes have a strong contribution to elevation-dependent warming in the warming climate. Our modeling results provide relevant information for mountain climate change in a past hot climate. Further, the analysis opens new mystery and perspectives related to elevation-dependent warming. Keywords: Eocene, paleoclimate modeling, elevation-dependent warming, CO2 Related Publication:Kad P, Blau M T, Ha K-J, and Zhu J (2022) Elevation-dependent temperature response in early Eocene using paleoclimate model experiment. Environmental Research Letters, 17(11), 114038. (https://doi.org/10.1088/1748-9326/ac9c74)
Parameter ensemble simulations of the North American and Greenland ice sheets and climate of the Last Glacial Maximum with Famous-BISICLES
Authors: Sherriff-Tadano Sam , Gandy Niall , Ivanovic Ruza , Gregoire Lauren , Owen Jonathan , Lang Charlotte , Gregory Jonathan , Smith Robin , Edwards Tamsin
Published: February 2023

Testing the ability of climate-ice sheet coupled models to simulate past ice sheets and climates can provide a way to evaluate the models. One example is the Last Glacial Maximum (LGM), when huge ice sheets covered the Northern Hemisphere, especially over the North America. Here, we perform 200 ensemble member simulations of the North American and Greenland ice sheets and climate of the LGM with an ice sheet-atmosphere-slab ocean coupled model Famous-BISICLES. 16 parameters associated with climate and ice dynamics are varied. The simulated results are evaluated against the LGM global temperature, the total ice volume and the ice extent at the southern margin of the North American ice sheet. In the ensemble simulations, the global temperature is controlled by the combination of precipitation efficiency in the large-scale condensation and entrainment rate in the cumulus convection. Under reasonable LGM global temperature, we find that the surface albedo and Weertman coefficient in the basal sliding law control the North American ice volume. In contrast, the ice volume of Greenland is found to be controlled by the Weertman coefficient. Based on the constraints, the model produces 6 good simulations with reasonable global temperature and North American ice sheet. We also find that warm summer surface temperature biases at the ice sheet interior as well as downscaling of surface mass balance based on altitude can cause strong local ice melting. This implies the need of better representing the atmospheric conditions and surface mass balance in the ice sheet interior.
Severe hail in France: reconstruction of Storm Ela’s and late June 2022 hailstorms
Authors: Panosetti Davide , Allen Christopher , Yaqubi Obaidullah , Thollon Orane
Published: February 2023

Hail is by far the greatest contributor to insured losses from severe convective storms on an annual basis. Individual severe convective storm outbreaks can cause hail losses well above EUR 1 bn. In May and June 2022 a series of such events impacted France, Germany and Belgium. Of these, those occurring on 19-22 June 2022 were particularly damaging as they hit the large metropolitan region of Ile-de-France. There were many reports of large hailstones, causing significant damage to property and motor vehicle. Total insured hail loss estimates in France alone exceeded EUR 2.4 bn, of which EUR 1.34 bn of property loss and EUR 1.08 bn of motor vehicle loss. These were the largest hail events in France in terms of losses since Storm Ela’s, which on 9-10 June 2014 resulted in insured hail losses in excess of 900 mn in 2021 EUR.Common denominator to these two impactful events were persistent meteorological situations conducive to large-scale severe convective storms for several consecutive days. These compounded with local conditions favorable for the development of severe hail. Maximum hailstone sizes of 12 cm in diameter were observed in the administrative regions of Centre-Val-De-Loire (Ela) and Occitanie (June 2022). In this study we present a reconstruction of these events based on eye-witness reports cross-referenced with weather radar data. We analyze the synoptic configurations and pre-convective environments that characterized them, with particular focus on those properties and features that are peculiar to severe hail-forming thunderstorms. These event reconstructions are part of our effort to construct a Realistic Disaster Scenario (RDS) model for France and Belgium to stress test both individual client portfolios and the market as a whole.
Forest Restoration Potential in China: Implications for Carbon Capture
Authors: Jiang Xin
Published: February 2023

When it comes to mitigating the damaging effects of deforestation and the adverse effects of rising carbon dioxide concentrations in the atmosphere, reforestation is an environmentally responsible and effective strategy. China, which has one of the most significant rates of afforestation in the world, has increased its forest cover from 16.6% when it was last measured twenty years ago to 23.0% when it is next measured in 2020. However, there is uncertainty regarding the maximum potential forest coverage that can be achieved through tree planting and restoration. We developed a random forest regression model to map the potential tree coverage across China. The model links environmental factors with the types of forests that are most appropriate. After removing already-forested areas, urban areas, and agricultural land covers and uses, we estimate that there is a total of 67.2 million hectares of land that is currently available for tree restoration. This is a 50% increase over the current understanding of the available land. The establishment of a forest on these lands would result in the creation of 3.99 gigatons of new carbon stocks both above and below ground, which would be an important contribution toward the goal of reaching carbon neutrality. This potential is geographically unbalanced, with the largest restorable carbon potential being located in the south-west (29.5%), followed by the north-east (17.2%), and then the north-west (16.8%). The results of our study highlight the importance of coordinating the planting of trees in reforestation efforts with the uneven distribution of potential carbon storage. Reforestation should provide other environmental services in addition to acting as a biological mitigation strategy to partially offset carbon dioxide emissions caused by the burning of fossil fuels. These services include the restoration of degraded soils, conservation of biological diversity, revitalization of hydrological integrity, localized cooling, and improvement in air quality. Instead of concentrating solely on the act of planting trees, we believe it is more beneficial for forest restoration efforts to concentrate on the ecosystem as a whole rather than just the trees themselves.
Broadband seismological analyses in the Eastern Mediterranean: implications for late-stage subduction, plateau uplift and the development of the North Anatolian Fault
Authors: Bastow Ian , Ogden Christopher , Merry Thomas , Kounoudis Rita , Bell Rebecca , Goes Saskia , Zhou Pengzhe
Published: February 2023

The eastern Mediterranean hosts extensional, strike-slip, and collision tectonics above a set of fragmenting subducting slabs. Widespread Miocene-Recent volcanism and ~2km uplift has been attributed to mantle processes such as delamination, dripping and/or slab tearing/break-off. We investigate this region using broadband seismology: mantle tomographic imaging (Kounoudis et al., 2020), SKS splitting analysis of seismic anisotropy (Merry et al., 2021), and receiver function study of crustal structure (Ogden & Bastow, 2021). Anisotropy and crustal structure are more spatially variable than recognised previously, but variations correspond well with tomographically-imaged mantle structure. Moho depth correlates poorly with elevation, suggesting crustal thickness variations alone do not explain Anatolian topography: a mantle contribution, particularly in central and eastern Anatolia, is needed too. Lithospheric anisotropy beneath the North Anatolian Fault reveals a mantle shear zone deforming coherently with the surface, while backazimuthal variations in splitting parameters indicate fault-related lithospheric deformation. Anisotropic fast directions are either fault-parallel or intermediate between the principle extensional strain rate axis and fault strike, diagnostic of a relatively low-strained transcurrent mantle shear zone.
Identifying and Describing Billions of Objects: an Architecture to Tackle the Challenges of Volume, Variety, and Variability
Authors: Klump Jens , Fils Doug , Devaraju Anusuriya , Ramdeen Sarah , Robertson Jesse , Wyborn Lesley , Lehnert Kerstin
Published: February 2023

Persistent identifiers are applied to an ever-increasing diversity of research objects, including data, software, samples, models, people, instruments, grants, and projects. There is a growing need to apply identifiers at a finer and finer granularity. The systems developed over two decades ago to manage identifiers and the metadata describing the identified objects struggle with this increase in scale. Communities working with physical samples have grappled with these challenges of the increasing volume, variety, and variability of identified objects for many years. To address this dual challenge, the IGSN 2040 project explored how metadata and catalogues for physical samples could be shared at the scale of billions of samples across an ever-growing variety of users and disciplines. This presentation outlines how identifiers and their describing metadata can be scaled to billions of objects. In addition, it analyses who the actors involved with this system are and what their requirements are. This analysis resulted in the definition of a minimum viable product and the design of an architecture that addresses the challenges of increasing volume and variety. The system is also easy to implement because it reuses commonly used Web components. Our solution is based on a Web architectural model that utilises Schema.org, JSON-LD and sitemaps. Applying these commonly used architectural patterns on the internet allows us not only to handle increasing volume, variety and variability but also enable better compliance with the FAIR Guiding Principles.
Outcome and lessons from the Southern Mariana Ocean Bottom Seismic Experiments
Authors: Yang Hongfeng , Zhu Gaohua , Chen Han , Abbas Aqeel
Published: February 2023

The Challenger Deep in the Southern Mariana subduction zone has attracted enormous attention of scientific investigators and explorers during recent decades. Since late 2016, near-field active and passive source seismic experiments has been carried out in the region by deploying Ocean Bottom Seismographs (OBS) in various terms. Both active and passive source tomographic images clearly indicate a well hydrous incoming plate, which is consistent with the observed pervasive normal faults in the out-rise region. Numerous earthquakes have been detected from the OBS recordings, and their locations delineate the subducting plate as well as deep out-rise faults, showing significant along-trench variations. Earthquake clusters are also found beneath the southwestern Mariana Rift and diminish sharply in the north. In addition to the scientific findings, we have discovered unexpected problems with the OBS data, particularly on the timing accuracies that are crucial on seismic records. To fix the various timing problems, we develop a framework of integrating travel times of teleseismic earthquakes and ambient noise cross correlations in different time segments. Such a framework could be applied on other OBS dataset suffering from irregular timing problems.
Re-failure and geomorphological evolution of paleo planar slide
Authors: Yang Che-Ming , Chuang I-Lin , Zhang En-Lun
Published: February 2023

Deep-seated landslides may become long-term creeping or transform to catastrophic landslides. Both serious threat to mountainous roads, villages, tourist area, and reservoir areas, which belongs to long-term and extensive effects. Many historical catastrophic landslides have caused the devastating disasters, such as Tsaoling landslide induced by the 1999 Chichi Earthquake, the Hsiaolin village landslide induced by extreme rain of the 2009 Typhoon Morakot, and the long-term large-scale landslides (creeping) of Lushan and Lishan have affected on the environment of the adjacent areas for decades or even longer. In Taiwan, there are many regions of widespread dip slope landform with potential planar failures, study area ranges the right bank of Chishan River from south to north (~35km in length). Most potential planar failure areas had delineated, and several platforms or gentle surfaces on the slope represent the deposits of paleo planar slides or old landslides in study area. But few cases of the geomorphologic evolution are investigated. However, it is difficult to estimate the slope stability of potential planar failures without geomorphologic evolution model. Therefore, the main purpose of this study is to use field investigation and topographic analysis to establish engineering geological models, then propose the geomorphologic evolution model for evaluation of slope stability. The methods of this study include: (1) identifies the microstructure of landslides by high-resolution LiDAR data, (2) performs the geological investigation to verify topographic interpretation and records occurrences of outcrops, (3) collects historical orthoimages to evaluate the activity of slope, (4) use high-precision aerial photography to establish digital surface model and analysis point cloud data to obtains the discontinuous plane state, and (5) the failure mechanism would be analyzed by the stereographic projection. In study area, 160 platforms are identified and area ranges from 220 m2 to 82386 m2. The largest two platforms, Tianziding (TZD) and Mujiliao (MZL) platforms, are investigated by field survey and drone. The attitudes of interbeds under TZD platform are surveyed along gullies, which is obvious gentler than the strata of dip slope. The front of MZL platform occurred slope failure during 2016 Typhoon Megi, therefore, the exposed rock mass of platform can be identified as deposits of planar slide. The preliminary results can infer that numerous paleo planar slides are exist in study area and the geological profiles of TZD and MZL are plotted. The structures of rock masses and attitudes of discontinuities by field survey and point cloud analysis need to interpreted carefully. Then, the geological model and geomorphological evolution can be proposed. 
Interpreting Machine Learning Models for Geochemistry Data Classification using Decision Boundary Maps
Authors: Wang Yu , Qiu Kunfeng , Telea Alexandru , Hou Zhaoliang , Yu Haocheng
Published: February 2023

Machine learning has been shown to be a highly effective method for classifying geochemistry data, such as mineral forming environments and rock tectonics. However, it can be difficult to understand the decision-making processes of these models. To address this issue, we propose the use of Decision Boundary Maps (DBMs) as a visualization tool for interpreting machine learning models. These maps project high-dimensional geochemistry data onto a 2D plane and depict the decision boundaries in the projected space, providing a visual representation of the algorithm's decision-making processes. In addition, DBMs can reveal trends, correlations, and outliers in the data, helping to interpret the results obtained from machine learning-based geochemistry data classification. Seeing the positions of data points, rather than just class labels, is especially valuable because samples in geological categories often follow a sequence, such as a magmatic to hydrothermal transition. Observing the positions of data points allows for the identification of trends from one class to an adjacent class.
Outer Core Heat Flux in Small Terrestrial Bodies from Electrical Resistivity Measurements of Liquid Fe-8S-4.5Si at High Pressure
Authors: Lenhart Eric , Yong Wenjun , Secco Richard
Published: February 2023

The thermal conductivity values through Earth’s core and planetary cores have important implications for the thermal evolution and magnetism of these bodies. For the outer cores of small terrestrial planetary bodies, this study constrains the thermal conductivity of liquid Fe-8wt%S-4.5wt%Si at pressures 2-5 GPa. Thermal conductivity was estimated using the Wiedemann-Franz Law from electrical resistivity measurements of a small Fe alloy sample at high pressures and high temperatures in a 1000-ton cubic anvil press. The powder samples were prepared by mixing powders of three compositions: Fe, FeS, and Fe-9wt%Si. Electron microprobe analysis and micro X-ray diffraction verified the elemental composition and crystallographic structure of the sample material both before and after pressurization.Resistivity-temperature plots of the Fe-8wt%S-4.5wt%Si data display trends common to Fe mixed with significant amounts of Si: a general rise in resistivity to a peak, a drop in resistivity through the melt, and a leveling of resistivity through the liquid state. Two reversals in slope occur between 800 K and 1000 K. At each integral pressure value between 2-5 GPa, an electrical resistivity in the range 300±100 μΩ·cm was found. Using the Sommerfeld value of the Lorenz number, thermal conductivities in the range 15±5 W/m/K were estimated. Comparative plots including resistivity data of Fe, Fe-4.5wt%Si, Fe-17wt%Si, and Fe-20wt%S are instructive to illuminate the relative effects of S and Si on the resistivity and thus the thermal conductivity and adiabatic heat flow of core mimetic Fe alloys. If the pressure at the top of the core is constrained using the assumptions of hydrostatic equilibrium and a bulk silicate mantle, then these thermal conductivity results may be applied to a number of known small terrestrial bodies, such as Io, in the case of a dominantly Fe-S-Si liquid outer core.
Improved subseasonal prediction of South Asian monsoon rainfall using data-driven forecasts of oscillatory modes
Authors: Bach Eviatar , Krishnamurthy Venkat , Shukla Jagadish , Mote Safa , Sharma A. Surjalal , Kalnay Eugenia , Ghil Michael
Published: February 2023

Predicting the temporal and spatial patterns of South Asian monsoon rainfall within a season is of critical importance due to its impact on agriculture, water availability, and flooding. The monsoon intraseasonal oscillation (MISO) is a robust northward-propagating mode which determines the active and break phases of the monsoon, and much of the regional distribution of rainfall. However, dynamical atmospheric forecast models predict this mode poorly. Data-driven methods for MISO prediction have shown more skill, but only predict the rainfall portion corresponding to MISO.Here, we combine state-of-the-art ensemble precipitation forecasts from a high-resolution atmospheric model with data-driven forecasts of MISO using a novel method. The ensemble members of the detailed atmospheric model are projected onto a lower-dimensional subspace corresponding to the MISO dynamics, and are then weighted according to their distance from the data-driven MISO forecast in this subspace. We thereby achieve significant improvements in rainfall forecasts over India, as well as the broader monsoon region, at 10–30 day lead times, an interval that is generally considered as a predictability gap. Our results demonstrate the potential of leveraging the predictability of intraseasonal oscillations to improve extended-range forecasts; more generally, they point towards a future of combining dynamical and data-driven forecasts for Earth system prediction.