bluuebunny/crossref_metadata_2025 huggingface dataset:
Fostering collaboration through improved software development practices for the ONEFlux eddy covariance data processing pipeline
Authors: Pastorello Gilberto , Trotta Carlo , Ribeca Alessio , Beattie Keith , Ngo Sy-Toan , Chu Housen , Cheah You-Wei , Christianson Danielle , Nicolini Giacomo , Dengel Sigrid , Polidori Diego , Isaac Peter , Archer Matthew , Orchard Dominic , Agarwal Deb , Biraud Sebastien , Torn Margaret , Papale Dario
Published: February 2023

Standardized processing of eddy covariance data is important for studies combining data from multiple sites, for validating remote sensing measurements as well as runs of ecosystem and climate models, and for applications relying on these flux data to create derived products like upscaled fluxes, among other examples. However, maintaining consistency within the software used for this processing while allowing for evolution of this code across research networks presents novel challenges in software development. The introduction of the ONEFlux (Open Network-Enabled Flux) eddy covariance data processing pipeline, originally developed within a collaboration of the AmeriFlux Management Project, the European Fluxes Database, and the ICOS Ecosystem Thematic Centre, supported the creation of consistently processed global eddy covariance data products. In particular, ONEFlux codes were used to generate the FLUXNET2015 dataset, which is widely adopted by thousands of eddy covariance data users in their work in research, ranging from soil microbiology to large scale drought effects, and also education, from basic plant biology all the way to global climate change. We are now more thoroughly instrumenting the code, and the code development process, to better address these challenges, efforts which we will describe in this presentation. In particular, we are seeking to improve software development practices to allow for more streamlined collaboration on expanding and contributing to the codebase. For instance, we are adopting planned release cycles for code updates, designing more detailed ways to incorporate and evaluate new modules, introducing data-centric testing and continuous integration, improving code performance, and adopting several other software engineering best practices more widely in the development workflows. The main goal of these changes is to lower the barriers for running ONEFlux by regional networks processing their data, while at the same time better supporting contributions from the community into the codebase. This will be critical to continue the current use of ONEFlux to generate updated versions of flux datasets by regional networks, the components of new global products.
Burst detection in water distribution systems with LSTM
Authors: Glynis Konstantinos , Kapelan Zoran , Bakker Martijn , Taormina Riccardo
Published: February 2023

This study presents a data-driven method for detecting pipe bursts in water distribution systems using Long Short-Term Memory (LSTM) neural networks. These types of neural networks are able to process sequential data more effectively than traditional neural networks because they have feedback connections between neurons. The proposed method involves performing one-step ahead predictions about the flow and pressure at different sensor locations in the system, using past time series data along with additional time-related features as inputs. The difference between predictions and actual observations is used to classify bursts and trigger alarms by comparing the errors against a time-varied error threshold. The model is trained using data from burst-free periods in the system. The method was tested using simulated fire hydrant bursts as well as real-world bursts in 8 district metered areas (DMAs) located in the United Kingdom. By harnessing transfer learning, the model can incorporate additional data streams from new sensors, performing well even in data frugal conditions, achieving precision scores of up to 98.1% for the analyzed case studies
Ion reflection observed at high Mach number interplanetary shocks: Solar Orbiter observations
Authors: Dimmock Andrew , Gedalin Michael , Trotta Domenico , Lalti Ahmad , Graham Daniel , Khotyaintsev Yuri , Vainio Rami , Blanco-Cano Xochitl , Kajdič Primoz , Owen Christopher
Published: February 2023

Collisionless shocks exist across diverse plasma environments. Examples are supernova remnants, comets, near planets, and interplanetary (IP) shocks in the solar wind. As the shock Mach number increases, so does the complexity of the ion distribution functions at the shock front due to features such as whistler precursors, ion reflection, shock ripples, and nonstationarity. Experimental studies of ion dynamics at supercritical high Mach (>5) number shocks are typically conducted using planetary bow shock crossings since the Mach number of these shocks are higher while the shock speeds with respect to the observing spacecraft are lower. As a result, it is easier to resolve complex features in the ion velocity distribution function. For these reasons, studies concentrating on ion reflection at IP shocks are rare. However, comparisons with IP shocks are interesting since they have a much larger curvature radius and can be accompanied by more energetic particles.In this work, we analyze a quasi-perpendicular shock observed by Solar Orbiter (SolO) on 30 October 2021 with a Mach number of around 7; this is much higher than the typical values of SolO IP shocks, which are between 1-3. For this event, we observed clear signatures in the upstream ion distribution function of reflected ions with energies extending to around 15 keV, which is lower than reported by other studies. The shock also demonstrates a non-planar feature, which may indicate shock rippling. In addition, whistler precursors are also found immediately upstream locally within the shock foot. We present these experimental results and a comparison with test-particle analysis and numerical modeling results.
Ensuring international and interdicipilinary interoperability of research data working groups
Authors: Asmi Ari
Published: February 2023

Interoperable tools for science is a great goal. Vision of seamless, shared and transparent scientific workflows, which can easily implement and automate processes across scientific fields and geographical domains gives hope for solving key scientific and societal challenges. However, we are not there yet. A lot of advances have been made, but there is no global agreement or a set of standards which enable such interoperability. Regional and national initiatives push towards diciplinary or regional open science environments, sharing some of the features of such true global interoperability, but often work in isolation - leading to danger of even more divergence of solutions. Science is global, and such discussions should be global. Scientific processes cover wide range of diciplines, practices and (science) cultural borders, and thus such solutions should be also shared across these boundaries. Modern science needs many kinds of experts, from traditional scientists to data stewards, software engineers and even policy developers and legal experts - and thus the interopebaility need to be considered also across the expert groups as well.In this presentation I will present some of the tools currently available for such international development, specifically concentrating on the development and expertise from (now a decade-old!) Research Data Alliance. I will also present several other initiatives from regional (particularly European) and global importance, and discuss the ways a researcher or a research infrastructure developer could interact with them.
Drivers of Widespread Flooding in Indian River Basins
Authors: Sobhana Nanditha J , Mishra Vimal
Published: February 2023

Widespread riverine flood events wherein most subbasins simultaneously experience flooding have relatively higher socio-economic implications relative to localized flooding within a river basin. Extreme precipitation covering a large area, favourable antecedent soil moisture conditions and unique atmospheric characteristics are often associated with these rare extreme events. Notwithstanding the huge death toll and economic consequences of flooding, there exists only a couple of studies that explore the causative factors of riverine flooding in India. Here, we identify widespread flooding in seven major river basins in India using streamflow simulations from a well-calibrated Variable Infiltration Capacity (VIC) hydrological model. We use an area-weighted threshold to determine the occurrence of widespread flooding. We estimated the probability of widespread flooding In Indian river basins during the observational period from 1959 to 2020. We find a high probability of widespread flooding  (>10% of high flow events in all subbasins) in the peninsular river basins, while the transboundary rivers of Ganga and Brahmaputra exhibit a low probability. Further, using the VIC simulated top layer soil moisture, gridded precipitation observations from India Meteorological Department (IMD) and ERA5 atmospheric variables; we investigate the antecedent soil moisture conditions and atmospheric characteristics associated with widespread flooding. The study results further our understanding of the causes of widespread flooding in Indian river basins and hence have major implications in managing these extreme events. 
Power law Scaling in Drainage Basin Areas of Independent landscapes
Authors: Borse Dnyanesh , Biswal Basudev
Published: February 2023

Power-law distributions occur in a diverse range of phenomena. Natural drainage networks also exhibit distinctive fractal properties and certain power-law scaling relationships irrespective of the underlined controls, such as geology, topography, and climate. Here we study the distribution of basin areas of continents as well as some islands. We used area-fraction vs. rank distribution, where the area fraction represents the area of a basin with respect to the total landscape area. To obtain the basin area distribution, we used HydroRivers data for the nine continent regions and performed DEM analysis for 12 islands. The results show that basin area distribution follows a power law in the case of all continents with scaling exponent ranging from -1.15 to -1.4. In the case of islands, the majority of them followed power law scaling with exponent ranging from -1.2 to around -2.5; however, distributions of some islands deviated from the power laws.We also looked at the basin area distribution with the optimal channel network model with all boundary pixels modelled as outlets. We got the scaling exponent around -1.8. Our recently proposed probabilistic model for drainage network evolution (Borse & Biswal, 2023) shows the capability to produce networks with different distributions. This model can capture the varying range of exponents with its flexible parameters. Further studies would be needed to understand the significance of this basin area distribution scaling exponent and whether it could be used as a metric to characterize landscapes.
A Probabilistic Physics-informed Deep Learning Model for Rainfall-runoff Prediction across Continental United States
Authors: Sadeghi Tabas Sadegh , Samadi Vidya
Published: February 2023

This research investigated the applicability of a probabilistic physics-informed Deep Learning (DL) algorithm, i.e.,deep autoregressive network (DeepAR), for rainfall-runoff modeling across the continental United States (CONUS). Various catchment physical parameters were incorporated into the probabilistic DeepAR algorithm with various spatiotemporal variabilities to simulate rainfall-runoff processes across Hydrologic Unit Code 8 (HUC8). We benchmarked our proposed model against several physics-based hydrologic approaches such as Sacramento Soil Moisture Accounting Model (SAC-SMA), Variable Infiltration Capacity (VIC), Framework for Understanding Structural Errors (FUSE), Hydrologiska Byråns Vattenbalansavdelning (HBV), and the mesoscale hydrologic model (mHM). These approaches were implemented using Catchment Attributes and Meteorology for Large-sample Studies (CAMELS), Maurer datasets. Analysis suggested that catchment physical attributes such as drainage area have significant impacts on rainfall-runoff generation mechanisms while catchment fraction of carbonate sedimentary rocks parameter’s contribution were insignificant. The results of the proposed physics-informed DeepAR simulation were comparable and somewhat superior to the well-known conceptual hydrologic models across CONUS.  
Semantic segmentation of dust storms from Mars images using convolutional neural network architectures
Authors: Nazifi Peyman , Windisch Andreas , Nodjoumi Giacomo
Published: February 2023

This work investigates the feasibility and performance of various state-of-the-art convolutional neural network architectures on the semantic segmentation of MDSSD (Mars Dust Storm Sequence Dataset) dataset.

The MDSSD contains manually identified dust storm sequences of the Mars Reconnaissance Orbiter (MRO), Mars Colour Imager (MARCI), and Mars Daily Global Maps.

The study aims at comparing the performance of a wide selection of convolutional neural network architectures such as U-Net, Attention U-Net, Linknet, and Feature Pyramid Networks (FPN). In addition, an ensemble learning approach is also planned to combine the different architectures and to identify the most optimal model to predict cloud and dust storms from the dataset.
Mathematical Properties of Continuous Ranked Probability Score Forecasting
Authors: Dombry Clément , Pic Romain , Naveau Philippe , Taillardat Maxime
Published: February 2023

The theoretical advances on the properties of scoring rules over the past decades have broaden the use of scoring rules in probabilistic forecasting. In meteorological forecasting, statistical postprocessing techniques are essential to improve the forecasts made by deterministic physical models. Numerous state-of-the-art statistical postprocessing techniques are based on distributional regression evaluated with the Continuous Ranked Probability Score (CRPS). However, theoretical properties of such minimization of the CRPS have mostly considered the unconditional framework (i.e. without covariables) and infinite sample sizes. We circumvent these limitations and study the rate of convergence in terms of CRPS of distributional regression methods. We find the optimal minimax rate of convergence for a given class of distributions. Moreover, we show that the nearest neighbor method and the kernel method for distributional regression reach the optimal rate of convergence in dimension larger than 2 and in any dimension, respectively.Associated article: https://doi.org/10.1016/j.ijforecast.2022.11.
Comparison and analysis of the long-term dynamics of GNSS orbits
Authors: Ait-Lakbir Hanane , Santamaría-Gómez Alvaro , Perosanz Felix , Ray Jim
Published: February 2023

The precision of the GNSS positioning depends on the accuracy and stability of the GNSS satellite orbits. Indeed, the analysis of the GNSS precise orbits determined by the IGS analysis centers shows different long-term behavior in the eccentricities and inclinations of GPS satellites, compared to GLONASS and Galileo satellites. This contribution focuses on analyzing sources of long-term dynamics in the GNSS orbits, particularly in the GPS orbits, and the influence of the constellation design. We investigate orbital resonances resulting from external accelerations such as lunisolar gravitation by semi-analytical simulations and compare the dynamical response of the four available constellations: GPS, Galileo, GLONASS, and BeiDou. Finally, we assess the impact of this different dynamical behavior on Precise Point Positioning (PPP).
Phenology and competitiveness of three temperate tree species in the juvenile stage under warmer springs and drier summers
Authors: Walde Manuel Gabriel , Moser Barbara , Vitasse Yann
Published: February 2023

Vegetation period of temperate tree species was projected to lengthen with climate warming by both advancing leaf-out during spring and delaying leaf senescence during autumn. However, this longer vegetation period does not necessarily translate into higher growth and carbon sequestration due to the increase in adverse weather conditions (e.g., severe drought) that occur during the growing season. Further, it remains unclear how species mixing might help benefit from a longer season and cope with extreme droughts compared to monocultures, i.e., whether diverse ecosystems are more resilient than monocultures. To tackle these questions, we set up experimental mesocosms using saplings from three species (i.e., Fagus sylvatica, Quercus petraea and Tilia cordata) grown either as monocultures or mixtures of two species. Each experimental unit was exposed to either (i) increased spring temperatures using a passive warming method, (ii) reduced precipitation (~ 50%) using rain shelters all year along, (iii) a combination of the two first treatments, or (iv) ambient conditions.In spring 2022 we observed significantly earlier leaf-out of Quercus compared to Fagus and Tilia at ambient conditions and advanced leaf-out by about 4 days for all species when exposed to the passive warming treatment. In autumn 2022 we observed 50% senescence of Tilia several weeks before Fagus and Quercus at ambient conditions. Advanced leaf-out due to increased spring temperature and drought exposure did not affect senescence of any species growing in monocultures. However, the presence of Tilia in the same experimental unit delayed senescence of Fagus by 4 days and senescence of Quercus by 5 days, whereas neither species changed senescence when growing in Fagus-Quercus mixtures compared to growing in monocultures. A potential explanation could be the competition release for water and nutrients due to Tilia’s much earlier senescence. Although we expected saplings with earlier leaf-out to grow stronger and saplings exposed to drought to grow less, height increment of neither species was affected by any treatment.
Seasonal forecasts of wildfire frequency and burned area in the western United States using a stochastic machine learning fire model
Authors: Buch Jatan , Williams A. Park , Gentine Pierre
Published: February 2023

One of the main challenges for forecasting fire activity is the tradeoff between accuracy at finer spatial scales relevant to local decision making and predictability over seasonal (next 2-4 months) and subseasonal-to-seasonal (next 2 weeks to 2 months) timescales. To achieve predictability at long lead times and high spatial resolution, several analyses in the literature have constructed statistical models of fire activity using only antecedent climate predictors. However, in this talk, I will present preliminary seasonal forecasts of wildfire frequency and burned area for the western United States using SMLFire1.0, a stochastic machine learning (SML) fire model, that relies on both observed antecedent climate and vegetation predictors and seasonal forecasts of fire month climate. In particular, I will discuss results obtained by forcing the SMLFire1.0 model with seasonal forecasts from: a) downscaled and bias-corrected North American Multi-Model Ensemble (NMME) outputs, and b) skill-weighted climate analogs constructed using an autoregressive ML model. I will also comment upon the relative contribution of uncertainties, from climate forecasts and fire model simulations respectively, in projections of wildfire frequency and burned area across several spatial scales and lead times. 
The more wastewater reclamation, the less water stress?
Authors: Wang Dan , Sahu Reetik Kumar , Kahil Taher , Tang Ting , Shan Yuli , Hubacek Klaus
Published: February 2023

Wastewater treatment removes water pollutants and wastewater reclamation provides an alternative water supply. It is believed that increasing the rate of wastewater reuse and reclamation can reduce water stress. This study aims at understanding whether reusing more wastewater can help mitigate water stress in China. Through scenario analysis, it is found that the potential for reuse of reclaimed water under a water conservation scenario is only 12-56% of the actual situation, but regional water stress under a water saving scenario is 10-82% lower than the current reality. The results show that a higher amount of reclamation does not necessarily lead to a lower water stress in one region. The potential for wastewater treatment and reuse is determined by return flows, which can reduce water use efficiency and exacerbate water stress. To effectively alleviate water stress, it is important to not only increase wastewater reuse, but also prioritize water conservation.
Cenozoic uplift history and topographic rejuvenation of the northern Atlas-Meseta system (Morocco)
Authors: Clementucci Romano , Ballato Paolo , Siame Lionel , Claudio Faccenna , Simone Racano , Giacomo Torreti , Riccardo Lanari , Laetitia Leanni , Guillou Valery
Published: February 2023

Transient topography represents an opportunity for extracting information on the combined effect of tectonics, mantle-driven processes, lithology and climate across different temporal and spatial scales. The geomorphic signature of transient conditions can be used to unravel the landscape evolution and to assess perturbations in uplift rates, especially in areas devoid of stratigraphic constraints. The Atlas-Meseta system experienced a large scale topographic rejuvenation during the Cenozoic through a combination of different processes. Despite the uplift, the Western Moroccan Meseta (WMM) represents a quiescent tectonic domain with deeply incised valleys and high-standing erosional surfaces (relict landscape). This topography is characterized by elevated non-lithological knickpoints, that delimit an uplifted relict landscape, implying a transient response to a change in uplift rates. Here, we determine denudation rates of selected watersheds and bedrock outcrops from cosmogenic nuclides and perform stream profile, regional and basin-scale geomorphic analysis. Denudation rates of the relict and the rejuvenated landscape range from 15 to 20 m/Myr and from 30 to 40 m/Myr, respectively. These results allow estimating the erodibility parameter for performing river-profile inversions and hence extracting rock uplift rates through time. Inverted rock uplift rates are 10-25 m/Myr from 45 to 22 Ma and 30-55 m/Myr from 22 to 10 Ma. Despite the different time scales, the inverted rates are consistent with 10Be averaged denudation rates (15-20 and 30-40 m/Myr) and river incision values from Pleistocene lava flows (<10 and ~50 m/Myr) for the rejuvenated and relict regions of the WMM. These results agree with geological data and indicate that the observed 400 m of surface uplift in the WMM started to develop at ~22-20 Ma. Given the wavelength of the topographic swell forming the topography of the WMM, uplift is here interpreted to reflect localized crustal thickening through magma addition or lithospheric thinning through mantle delamination. This event, however, represents only a first episode of uplift. The occurrence of ~7-Myr-old marine sediments at ~1200 m of elevation indicates that the adjacent Folded Middle Atlas experienced a more recent surface uplift at ~170 m/Myr. Considering the cumulative amount of surface uplift that varies eastward from 400 to 800 and 1200 m from the Meseta to the Tabular and the Folded Middle Atlas, as well as the spatio-temporal pattern of alkaline volcanism (middle Miocene and Pliocene to Present), we suggest that the most recent episode (second phase) of surface uplift was induced by a larger-scale process that most likely included upwelling of asthenospheric mantle and to a lesser extent crustal shortening and thickening in the Folded Middle Atlas.
Detecting Deep-seated Landslide Movement Using Seismic Signal Analysis of MEMS
Authors: Lin Meei-Ling , Chiu Sheng-Yu , Wang Kuo-Lung , Hsieh Yo-Ming
Published: February 2023

The deep-seated landslides often caused severe hazard due to the large area and landslide mass associated with the landslide movement. Thus, monitoring the landslide movement is an important task for landslide hazard management. The Microelectromechanical Systems (MEMS) technique developed rapidly in recent years provides the ability of low-cost sensors and easy installation for monitoring of the landslide movement in field. Typically, the landslide movement monitoring using MEMS is based on the tilt angle determined from the measured ground acceleration variations in three directions, and being subjected to the signal noise. We adopt Moving Window Fast Fourier Transform and other seismic wave analysis in this study to improve resolution of the seismic signals and achieve a sound detection of deep-seated landslide movement. The MEMS was installed at the Lantai deep-seated landslide study area, which measured the ground accelerations mid-slope of the landslide. The seismic signals recorded for eleven earthquake events and three heavy rainfall events are selected for analysis. It was found that the signal frequency can be separated from the system responses and related to the landslide movement. Validations were conducted by comparing the analysis results to the field monitoring data of in-place inclinometer and borehole extensometer while available. It is suggested that the landslide movement can be identified with seismic signal at approximately 17 Hz, and the results are consistent for both earthquake-induced and rainfall-induced events. 
Kimberlite genesis and mantle metasomatism: Insights from in situ U-Pb dating of single garnet xenocrysts
Authors: Millonig Leo J. , Agasheva Elena V. , Agashev Alexey M. , Albert Richard , Beranoaguirre Aratz , Marschall Horst , Gerdes Axel
Published: February 2023

Garnet xenocrysts from kimberlites provide unique insights into the composition, structure and evolution of the subcontinental lithospheric mantle (SCLM). For example, different metasomatic events in the SCLM are reflected in compositional differences between garnet xenocrysts. As mantle metasomatism largely controls the physical and chemical properties of the SCLM, it exerts first order control over the genesis of kimberlitic magmas and diamond formation. However, dating mantle lithologies and processes is complicated by high ambient temperatures that allow the equilibration of most isotopic systems up to the time of kimberlite eruption. As a consequence, the temporal connection between metasomatic events in the mantle and kimberlite genesis is commonly ambiguous.In this study, we applied LA-ICPMS U-Pb dating to 43 harzburgitic, lherzolithic and megacrystic garnet xenocrysts from the ~376 Ma diamondiferous V. Grib kimberlite, Russia, in order to investigate the link between different types of mantle metasomatism and kimberlite genesis.Our results indicate that, with two possible exceptions, only harzburgitic garnet overlaps in age with the kimberlite eruption, whereas lherzolitic and megacrystic garnet crystals are ~20 to 130 million years older. Furthermore, garnet U-Pb ages and Ni-in-garnet temperatures of ~820 to 1200 °C do not correlate. This, and the high closure temperature of U-Pb in garnet (≥900 °C) suggests that the garnet U-Pb ages indeed reflect metasomatic events in the SCLM. However, the U-Pb ages could also reflect cooling ages. In this case, the metasomatic events recorded in the garnet crystals must still have occurred up to ~130 million years prior to the eruption of the V. Grib kimberlite.These findings have far-reaching implications for the genesis of (diamondiferous) kimberlites, as they clearly show that the time lag between metasomatic events in the SCLM, as recorded in kimberlitic garnet xenocrysts, and kimberlite eruption may extend to tens of millions of years.
Investigation of the influence of faults on geoelectric strikes and dimensionality analysis of MT data in the Sabalan geothermal area
Authors: Ghasemipour Younes , Abtahi Forooshani Sayyed Mohammad , Sadeghisorkhani Hamzeh
Published: February 2023

The Sabalan geothermal in northwestern Iran is the most well-known geothermal in the country. Due to the Sabalan caldera's structures and dozens of younger faults, the area consists of highly fractured rocks. Besides, processing the aeromagnetic data in the area revealed some other hidden faults. To investigate the effect of the faults on the geothermal system, we conducted a dimensionality analysis based on magnetotelluric impedance and phase tensors from two magnetotelluric datasets. The datasets were surveyed at different times, one in the dry season of June 1998 and the other in the wet season of November 2007. The dimensionality behavior obtained from the datasets differs significantly. We realized that the discrepancy was due to the time of conducting the magnetotelluric survey. For instance, the polar diagrams computed from the dry season data showed a better correlation with fault strikes in some of the frequencies where the wet season data polar diagrams were less sensitive to the fault orientations. Besides, the strike of a hidden fault extracted from aeromagnetic data was apt to the extension of Zxy's polar diagram. Furthermore, the dimensionality analysis and skew angle in dry season data demonstrate a 2D to 3D media, whereas the wet season data showed a 1D to 2D earth. We deduced that faults have a more significant role in providing resistivity contrast in dry seasons and hence, a better illustration for the geoelectric strike.
Update on the TROPESS ozone data products: Evaluation, validation and a preliminary examination of their utility in tropospheric ozone trend analysis
Authors: Osterman Gregory , Bowman Kevin
Published: February 2023

We present an update on the status of the tropospheric ozone data products retrieved from satellite observations. Specifically, we will highlight data from the TRopospheric Ozone and its Precursors from Earth System Sounding (TROPESS) project which is a NASA effort that provides retrievals of atmospheric ozone utilizing radiances from a variety of different satellite instruments. The TROPESS project provides ozone data that provides additional data that can used with record established by the Tropospheric Emission Spectrometer (TES) which flew on NASA’s Aura satellite. The new multispectral retrievals of ozone utilize the (Multi-Spectra, Multi-Species, Multi-Sensors Retrievals of Trace Gases (MUSES) retrieval framework to produce consistent estimations of ozone from different satellite radiances. TROPESS ozone data products include those using data from the Atmospheric Infrared Sounder (AIRS), the Ozone Monitoring Instrument (OMI) and the Cross-track Infrared Sounder (CrIS) instruments. The TROPESS joint-satellite data products provide ozone retrievals with vertical sensitivity similar to that seen in TES observations and allow a continuation of the TES ozone data record. Utilizing satellite instruments that observe with wide swaths will provide much broader spatial sampling than TES was able to provide.
The TROPESS team is currently processing ozone data records using radiances from CrIS, AIRS, OMI, TROPOMI and retrievals using combinations of the different satellites. All of the TROPESS products are being validated through comparisons to ozonesondes as well as comparisons to chemical reanalysis products. We will provide an update on the results from these comparisons as well highlighting the differences in vertical sensitivity and spatial sampling of the different products. We will highlight the differences in the sensitivity of the retrievals to ozone in the troposphere and validation of the satellite retrievals at those pressure levels. We will show statistical analysis for the errors in the satellite retrievals and their comparisons to the ozonesondes.
Lastly, we will present results showing the time record of the different ozone products, including showing how the comparisons to models and ozonesondes change with time. Utilizing the AIRS and OMI instrument data will allow us to examine the tropospheric ozone data record going back to 2005 and we will share results of how the TROPESS products can contribute to determining trends in tropospheric ozone.
Geodesy meets tectonophysics: Advancing our estimates of glacial isostatic adjustment
Authors: Steffen Rebekka
Published: February 2023

Glacial isostatic adjustment (GIA) describes the response of the solid earth to ice mass changes and corresponding changes in the sea level. This process is visible in various geoscientific observations, with geodetic measurements being crucial to understand and describe the process. For example, the vertical and horizontal motion of the lithosphere is visible in GNSS (Global Navigation Satellite Systems) time series in the currently (Greenland, Antarctica, Svalbard) and formerly glaciated regions (North America, northern Europe). In addition to geodetic observations of GIA, the solid earth deformation is visible in various geological data. The vertical motion of the lithosphere can be seen in relative sea level and lake level data, but for a different epoch then GNSS data. All these observations help to explain GIA as well as infer the structure of the Earth via so-called GIA models. GIA models can be constrained by geodetic and geological observations and in turn can help to predict these observations. An essential component of GIA models is knowledge about the distribution of material parameters of the Earth’s lithosphere and mantle. This can be obtained from various geophysical measurements (e.g., gravity, seismology).Here, I will show how we can infer the depth of various material layers in the lithosphere from geodetic data exemplary for Greenland and how we can use these in three-dimensional GIA models. I will also discuss the effect of various lithosphere models on the modelled GNSS velocities.
Landslide-covered glaciers: towards a new global geodatabase
Authors: Domej Gisela , Ewertowski Marek , Tomczyk Aleksandra , Małecki Jakub
Published: February 2023

Landslides can modify the behavior of glaciers by delivering additional debris load from adjacent slopes onto the ice surface. Such debris covers may significantly reduce ablation and, hence, result in a positive glacier mass balance (e.g., at the Sherman Glacier in Alaska after a series of landslides that had slid onto it during the Good Friday Earthquake in 1964). In the longer term, this can entail glacier thickening and reduced ice mass velocity (e.g., at the Sioux Glacier in Alaska for a similar setting caused by the same earthquake). Conversely, surges with high ice mass velocities following rock avalanches onto glaciers were also documented (e.g., at the Bualtar Glacier in the Pakistani Karakoram and the Russian Geographical Society Glacier in the Tajik Pamirs).As thermal and hydrological regime changes are widely accepted as factors influencing the kinematic behavior of glaciers, we focus on the relation of landslides and glacial processes to countervail the lack of data on that very topic. Glacial retreat and associated slope debuttressing combined with permafrost thawing are likely to increase the number of landslides onto glacier surfaces as global warming progresses. Therefore, systematic documentation of this phenomenon is necessary to fully assess the consequences for glacier dynamics.The study aims to establish a new spatio-temporal geodatabase to determine – in the first place – worldwide distributions of glaciers covered by landslides, including potential clusters. In the second stage, spatio-temporal trends and event frequencies will be analyzed over a time frame reaching back about 50 years in time (i.e., to the launch of Landsat-1) using historical aerial photographs, and Landsat, ASTER, and Sentinel medium-resolution satellite imagery (i.e., 10-50 ground sampling distance). One of two essential aspects of the database is its planet scale, which ensures a broad spectrum of environmental conditions and possibly affected land systems such as Alaska, the European and New Zealand Alps, Iceland, the Himalayas and Pamirs, or Patagonia. Another major feature is an emphasized distinction of the type of debris on the glacier; moraine debris is not considered in the inventory. The database comprises information on topographic properties of the landslides (i.e., area, width, length, etc.), the approximate event times, prevailing geology (if available from sources), as well as the characteristics of the glaciers (i.e., area, velocity, thermal regime, etc.).At the current stage, the geodatabase and its maps are not yet exhaustive, as we carry on our systematic quantification of landslide-covered glaciers by employing routines within the Google Earth Engine, comparison of existing inventories (e.g., GLIMS, RGI, WGI, etc.), and manual counter-checking and verification. We present the current state of our work with some speaking examples.Research is funded by the National Science Center, Poland, via project number 2021/42/E/ST10/00186.
Near-real Time Daily Drought Monitoring Using an Ensemble of Gridded Precipitation Datasets
Authors: Prat Olivier , Coates David , Wilkins Scott , Willett Denis , Leeper Ronald , Nelson Brian , Shaw Michael , Ansari Steve , Huffman George
Published: February 2023

We present a near-real time drought monitoring framework that uses precipitation estimates from a selection of satellite (CMORPH-CDR, IMERG) and in-situ (NClimGrid) gridded precipitation products datasets. The near-real time availability of precipitation datasets allows for the computation of the standardized precipitation index (SPI) over various time scales (30-, 90-, 180-, 270-, 365-, 730-day) and daily update of drought conditions. The three drought products generated: CMORPH-SPI (Global; 1998-present; 0.25°x0.25°degree spatial resolution), NClimGrid-SPI (CONUS; 1951-present; 0.05°x0.05°), and IMERG-SPI (Global; 2000-present; 0.1°x0.1°) are being evaluated focusing on the influence of the sensors characteristics and resolutions, differing period of record, and various SPI formulations. The remotely sensed and in-situ SPIs are also compared against existing droughts monitoring resources and in particular the US Drought Monitor (USDM).The use of cloud-scale computing resources (Microsoft Azure, Amazon Web Services) reduces considerably the computation time. Gain in computational time and process optimization allow for the implementation of a drought amelioration module that is run conjointly with the daily SPI. The drought conditions derived from the precipitation datasets enable us to estimate the amount of deficit precipitation needed to alleviate drought conditions as a function of drought severity and accumulation periods. The process flexibility also allows for the addition of other variables (i.e. temperature, ET) to develop more complex drought indices.  For instance, daily temperature information available from NClimGrid, is used to compute the Standardized Precipitation-Evapotranspiration Index (SPEI) that is evaluated against NClimGrid-SPI over CONUS.Finally, we present the effort to transfer the SPI from research to operation (R2O). The global daily SPI derived from CMORPH-CDR is publicly available via the Global Drought Information System (GDIS) dashboard (https://gdis-noaa.hub.arcgis.com/pages/drought-monitoring). The other products developed (NClimGrid-SPI, IMERG-SPI) are expected to be added to the existing portfolio of near-real time drought monitoring capabilities.
Fine-scale dynamic modelling of water table depths (WTD) in Danish peatlands
Authors: Denager Tanja , Schneider Raphael , Stisen Simon
Published: February 2023

In Denmark, re-wetting of drained peatland is considered an effective measure for reduction of agricultural greenhouse gas (GHG) emissions, due to the well-established relationship between water table depth and GHG emissions. Returning peatlands to their natural hydrological state, has additional benefits for nutrient loads and biodiversity and has becomes central in environmental policies.Prevailing WTD-dependent GHG upscaling methods for peatlands are based on long term average WTD estimates, while there is limited understanding of the impact of WTD variability, extremes and how those effect rewetting strategies. This project aims to increase our knowledge on peatland WTD variability in space and time in high resolution to enable better estimation of the emission reduction potential and to support the rewetting strategies. Process-based hydrological models are important tools to support that effort.We base our detailed simulation of peatland hydrology on an optimization of the national-scale Danish groundwater flow model with focus on the spatio-temporal patterns in peatlands. We identify the processes that govern peatland dynamics, including estimation of model parameters corresponding to those processes.Besides local-scale insights on WTD dynamics from a highly instrumented peatland, we combine the physically based 3D groundwater flow model with remote sensing-based estimates of WTD in a spatial oriented optimization of the hydrological model.Through scenario simulations we analyze the effects of climate variability and change, and especially how extreme events (e.g. droughts) impact GHG emissions controlled by WTD.Those achievements enhance simulation of peatland processes, and the understanding of the climate response to the changes in WTD and will thereby support the Danish rewetting strategies and enables better upscaling of GHG emissions for national inventories.
Water use efficiency differs for mixed and monospecific boreal forests in Sweden
Authors: Krasnova Alisa , Zhao Peng , Klosterhalfen Anne , Chi Jinshu , Schacherl Tim , B. Nilsson Mats , Peichl Matthias
Published: February 2023

Ecosystem water use efficiency (WUE) is a key characteristic that describes the coupling of carbon and water exchange and can be used as an indicator of a forest's adaptability to varying climatic conditions. Mixed forests, characterized by the coexistence of two or more dominant tree species, may potentially exhibit higher productivity and greater resistance to extreme weather events due to possible niche differentiation among dominant species, leading to more efficient nutrient utilization. However, the increased productivity may also result in higher evapotranspiration demand, resulting in lower WUE compared to monospecific forests. In this study, we aim to assess the variation in WUE of mixed and monospecific boreal forests in response to different environmental factors using eddy-covariance measurements. The two study sites are represented by forest stands of similar age, growing under the same climatic conditions and located in close proximity (~10km distance) in Northern Sweden. The Rosinedalsheden site is a ~100-year-old monospecific pine (Pinus sylvestris) forest stand with sandy soils. The Svartberget site is a mixed ~110-year-old forest featuring pine (Pinus sylvestris, 61%), spruce (Picea abies, 34%), and birch (Betula sp., 5%) species, with soils dominated by till and sorted sediments. Our study spans a period of seven years (2014-2020) and covers a wide range of weather conditions, including the 2018 heatwave.
Post-fire effects on DOC concentrations in streams: A meta-analysis
Authors: Polack Huaman Jessenia
Published: February 2023

Forest fires affects extensive areas each year around the world. An important percentage of those areas represent forested watersheds which provide water supply for different communities, from the microbial till the industrial scale. Forest fires can have an effect in erosion, runoff rates, loss of vegetation cover, rainfall interception, water repellence, among others, which affect the water quality in the streams. The change in the dynamic of a burned watershed produce variation in the DOC concentration, among other water quality parameters, which has a direct impact in the drinking water treatment. This meta-analysis explores post-fire effects in DOC concentrations, during the years after the fire. More than 50 watersheds were identified in the collection of the information. Changes in concentrations were documented primarily within the first 5 years after the fire. The studies were published between 2001 and 2020. We found that percentage of area burned, and fire severity have stronger effect on DOC concentrations. The study documents strong heterogeneity in responses to post-fire effects and DOC concentrations.
Seasonal forecasts and heat stress in an eastern Mediterranean environment
Authors: Varotsos Konstantinos V. , Karali Anna , Giannakopoulos Christos
Published: February 2023

In this study we examine the use of seasonal forecasts on predicting the heat stress conditions in the summer months over the region of Attica in Greece using a number of meteorologically based heat stress indices, namely effective temperature, humidex, discomfort index and heat index (Buzan et al. 2015). To this aim, the fifth generation ECMWF seasonal forecasting system (SEAS5) hindcasts for the period 1993 to 2016 available in C3S Climate Data Store are used. The variables to calculate daily heat stress indices values include instantaneous outputs at 12 UTC for 2-meter temperature, northward and eastward near-surface wind components, as well as 2-m dewpoint temperature. In order to statistically downscale and verify seasonal forecasts, the state-of-the-art global reanalysis dataset ERA5-Land of Copernicus CDS is used. The verification of the heat stress indices re-forecasts is performed using adequate probabilistic verification measures of discrimination and reliability.
Preliminary results indicate that for the majority of the indices, forecasts initialized in June and to a lesser extent in May exhibit statistically significant skill scores in predicting above normal heat stress conditions, while for forecasts initialized in March and April no statistically significant skill is found identifying these forecasts in the not useful category.
Greenhouse Gases Validation and Monitoring over the East Asia by Satellite-based Observation
Authors: Lee Byung-il , Sohn Eunha , Heo Junhyung , Oh Youngsuk , Joo Sangwon , Choi Junyeob , Park Hyein , Lee Myunghee , Kim Yoonjae
Published: February 2023

According to the 6th IPCC report, the concentration of greenhouse gases has increased about 20% since pre-industrial revolution, and 17% of them have increased over the last 10 years. The Korea Metoeorological Administration has analyzed satellite-based greenhouse gases to monitor climate change and support government’s achievement of net zero. The KMA has validated satellite-based greenhouse gases using CO2  observed in situ and retrieved TCCON in Anmyeon, the South Korea which is a GAW site. Both ground- and satellite-based CO2 showed a good agreement in their increasing trends with seasonal variations. However, satellite-based CO2 observed total column appear smaller than in situ observations affected by local sources due to observe near the surface, but agree well with TCCON observed the total column. The RMSD of GOSAT, and OCO2 with in situ and TCCON is estimated about 14.85, 16.93 and 2.81, 2.01 ppmv for a 1.0 degree × 1.0 degree spatial resolution on a daily time scale from January 2014 to December 2018. The results show that satellite-based products could be used greenhouse gases monitoring, but it needs to be verified more validation data.  We will present the detailed methods and results in the conference.This work was funded by the Korea Meteorological Administration’s Research and Development Program “Technical Development on Weather Forecast Support and Convergence Service using Meteorological Satellites” under Grant (KMA2020-00120).