Erratum to: 23 November 1980 Irpinia–Basilicata earthquake (Southern Italy): towards a full knowledge of the seismic effects

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Estimating leaf moisture content at global scale from passive microwave satellite observations of vegetation optical depth

The moisture content of vegetation canopies controls various ecosystem processes such as plant productivity, transpiration, mortality, and flammability. Leaf moisture content (here defined as the ratio of leaf water mass to leaf dry biomass, or live-fuel moisture content, LFMC) is a vegetation property that is frequently used to estimate flammability and the danger of fire occurrence and spread, and is widely measured at field sites around the globe. LFMC can be retrieved from satellite observations in the visible and infrared domain of the electromagnetic spectrum, which is however hampered by frequent cloud cover or low sun elevation angles. As an alternative, vegetation water content can be estimated from satellite observations in the microwave domain. For example, studies at local and regional scales have demonstrated the link between LFMC and vegetation optical depth (VOD) from passive microwave satellite observations. VOD describes the attenuation of microwaves in the vegetation layer. However, neither were the relations between VOD and LFMC investigated at large or global scales nor has VOD been used to estimate LFMC. Here we aim to estimate LFMC from VOD at large scales, i.e. at coarse spatial resolution, globally, and at daily time steps over past decadal timescales. Therefore, our objectives are: (1) to investigate the relation between VOD from different frequencies and LFMC derived from optical sensors and a global database of LFMC site measurements; (2) to test different model structures to estimate LFMC from VOD; and (3) to apply the best-performing model to estimate LFMC at global scales. Our results show that VOD is medium to highly correlated with LFMC in areas with medium to high coverage of short vegetation (grasslands, croplands, shrublands). Forested areas show on average weak correlations, but the variability in correlations is high. A logistic regression model that uses VOD and additionally leaf area index as predictor to account for canopy biomass reaches the highest performance in estimating LFMC. Applying this model to global VOD and LAI observations allows estimating LFMC globally over decadal time series at daily temporal sampling. The derived estimates of LFMC can be used to assess large-scale patterns and temporal changes in vegetation water status, drought conditions, and fire dynamics.</p

Reliability of resilience estimation based on multi-instrument time series

This is the final version. Available from Copernicus Publications via the DOI in this record. Code and data availability: Data used in this study are publicly available from Moesinger et al. (2020) (https://doi.org/10.5281/zenodo.2575599, Moesinger et al., 2019), https://doi.org/10.3390/rs6086929 (Pinzon and Tucker, 2014), https://doi.org/10.5067/MODIS/MCD12Q1.061 (Friedl and Sulla-Menashe, 2015), and https://doi.org/10.5067/MODIS/MOD13C1.006 (Didan, 2015). Code to reproduce the synthetic data used in this study can be found on Zenodo: https://doi.org/10.5281/zenodo.7009414 (Smith and Boers, 2022)Many widely used observational data sets are comprised of several overlapping instrument records. While data inter-calibration techniques often yield continuous and reliable data for trend analysis, less attention is generally paid to maintaining higher-order statistics such as variance and autocorrelation. A growing body of work uses these metrics to quantify the stability or resilience of a system under study and potentially to anticipate an approaching critical transition in the system. Exploring the degree to which changes in resilience indicators such as the variance or autocorrelation can be attributed to non-stationary characteristics of the measurement process - rather than actual changes in the dynamical properties of the system - is important in this context. In this work we use both synthetic and empirical data to explore how changes in the noise structure of a data set are propagated into the commonly used resilience metrics lag-one autocorrelation and variance. We focus on examples from remotely sensed vegetation indicators such as vegetation optical depth and the normalized difference vegetation index from different satellite sources. We find that time series resulting from mixing signals from sensors with varied uncertainties and covering overlapping time spans can lead to biases in inferred resilience changes. These biases are typically more pronounced when resilience metrics are aggregated (for example, by land-cover type or region), whereas estimates for individual time series remain reliable at reasonable sensor signal-to-noise ratios. Our work provides guidelines for the treatment and aggregation of multi-instrument data in studies of critical transitions and resilience.Horizon 2020Marie Skłodowska-Curie ActionsBundesministerium für Bildung und ForschungBrandenburger Staatsministerium für Wissenschaft, Forschung und Kultur (NEXUS

VODCA2GPP – a new, global, long-term (1988–2020) gross primary production dataset from microwave remote sensing

This is the final version. Available on open access from Copernicus Publications via the DOI in this recordData availability: The VODCA2GPP data can be accessed (CC BY-NC-SA 4.0) at TU Data Repository under https://doi.org/10.48436/1k7aj-bdz35 (Wild et al., 2021).Long-term global monitoring of terrestrial gross primary production (GPP) is crucial for assessing ecosystem responses to global climate change. In recent decades, great advances have been made in estimating GPP and many global GPP datasets have been published. These datasets are based on observations from optical remote sensing, are upscaled from in situ measurements, or rely on process-based models. Although these approaches are well established within the scientific community, datasets nevertheless differ significantly. Here, we introduce the new VODCA2GPP dataset, which utilizes microwave remote sensing estimates of vegetation optical depth (VOD) to estimate GPP at the global scale for the period 1988–2020. VODCA2GPP applies a previously developed carbon-sink-driven approach (Teubner et al., 2019, 2021) to estimate GPP from the Vegetation Optical Depth Climate Archive (Moesinger et al., 2020; Zotta et al., 2022​​​​​​​), which merges VOD observations from multiple sensors into one long-running, coherent data record. VODCA2GPP was trained and evaluated against FLUXNET in situ observations of GPP and compared against largely independent state-of-the-art GPP datasets from the Moderate Resolution Imaging Spectroradiometer (MODIS), FLUXCOM, and the TRENDY-v7 process-based model ensemble. The site-level evaluation with FLUXNET GPP indicates an overall robust performance of VODCA2GPP with only a small bias and good temporal agreement. The comparisons with MODIS, FLUXCOM, and TRENDY-v7 show that VODCA2GPP exhibits very similar spatial patterns across all biomes but with a consistent positive bias. In terms of temporal dynamics, a high agreement was found for regions outside the humid tropics, with median correlations around 0.75. Concerning anomalies from the long-term climatology, VODCA2GPP correlates well with MODIS and TRENDY-v7 (Pearson's r 0.53 and 0.61) but less well with FLUXCOM (Pearson's r 0.29). A trend analysis for the period 1988–2019 did not exhibit a significant trend in VODCA2GPP at the global scale but rather suggests regionally different long-term changes in GPP. For the shorter overlapping observation period (2003–2015) of VODCA2GPP, MODIS, and the TRENDY-v7 ensemble, significant increases in global GPP were found. VODCA2GPP can complement existing GPP products and is a valuable dataset for the assessment of large-scale and long-term changes in GPP for global vegetation and carbon cycle studies. The VODCA2GPP dataset is available at the TU Data Repository of TU Wien (https://doi.org/10.48436/1k7aj-bdz35, Wild et al., 2021).Technische Universität Wie

Neon seeding effects on two high-performance baseline plasmas on the Joint European Torus

We present the JETTO-QuaLiKiz-SANCO fully predictive modelling of two JET-ILW high-performance baseline plasmas, a Ne seeded shot and an equivalent unseeded one. The motivation of the work lies in the experimental observation of a slightly higher confinement and performance of the Ne seeded shot with respect to the unseeded one, despite sharing the same main plasma parameters and heating powers. Moreover, the neon seeded shot shows a lower pedestal electron density and a higher core ion temperature with respect to the unseeded one. Integrated modelling is performed in order to understand if the cause of the improved confinement has to be ascribed to the improved pedestal parameters with neon seeding or if an impurity-induced turbulence stabilization is at play. The QuaLiKiz transport model is used for predicting the electron density, electron and ion temperatures and rotation in the core up to the pedestal top, while the pedestal is empirically modelled to reproduce the experimental kinetic profiles. The thermal diffusivities of the two shots, computed by QuaLiKiz, are compared, as well as the turbulence spectra, suggesting that the reduced transport found in the neon seeded shot is due in part to the stabilization of ion temperature gradient and electron temperature gradient modes. Further modelling is performed in order to disentangle the neon seeding effects, which are a direct effect on the turbulence stabilization and an indirect effect on the pedestal parameters. The results suggest that the improved performance with neon is due to a combination of turbulence stabilization and improved pedestal parameters

Case Report Copious Podocyturia without Proteinuria and with Normal Renal Function in a Young Adult with Fabry Disease

The time for starting a patient with Fabry disease on enzyme replacement therapy is still a matter of debate, particularly when no overt classical clinical signs or symptoms are present. With respect to Fabry nephropathy, a dual problem coexists: the reluctance of many nephrologists to start enzyme replacement infusion until signs of renal disease appear as the appearance of proteinuria or an elevation in serum creatinine and the lack of validated biomarkers of early renal damage. In this regard, proteinuria is nowadays considered as an early and appropriate marker of kidney disease and of cardiovascular morbidity and mortality. However, in this report we demonstrate that podocyturia antedates the classical appearance of proteinuria and could be considered as an even earlier biomarker of kidney damage. Podocyturia may be a novel indication for the initiation of therapy in Fabry disease

Overview of the FTU results

Since the 2018 IAEA FEC Conference, FTU operations have been devoted to several experiments covering a large range of topics, from the investigation of the behaviour of a liquid tin limiter to the runaway electrons mitigation and control and to the stabilization of tearing modes by electron cyclotron heating and by pellet injection. Other experiments have involved the spectroscopy of heavy metal ions, the electron density peaking in helium doped plasmas, the electron cyclotron assisted start-up and the electron temperature measurements in high temperature plasmas. The effectiveness of the laser induced breakdown spectroscopy system has been demonstrated and the new capabilities of the runaway electron imaging spectrometry system for in-flight runaways studies have been explored. Finally, a high resolution saddle coil array for MHD analysis and UV and SXR diamond detectors have been successfully tested on different plasma scenarios

Shattered pellet injection experiments at JET in support of the ITER disruption mitigation system design

A series of experiments have been executed at JET to assess the efficacy of the newly installed shattered pellet injection (SPI) system in mitigating the effects of disruptions. Issues, important for the ITER disruption mitigation system, such as thermal load mitigation, avoidance of runaway electron (RE) formation, radiation asymmetries during thermal quench mitigation, electromagnetic load control and RE energy dissipation have been addressed over a large parameter range. The efficiency of the mitigation has been examined for the various SPI injection strategies. The paper summarises the results from these JET SPI experiments and discusses their implications for the ITER disruption mitigation scheme

Comparing pedestal structure in JET-ILW H-mode plasmas with a model for stiff ETG turbulent heat transport

A predictive model for the electron temperature profile of the H-mode pedestal is described, and its results are compared with the pedestal structure of JET-ILW plasmas. The model is based on a scaling for the gyro-Bohm normalized, turbulent electron heat flux qe/qe,gB resulting from electron temperature gradient (ETG) turbulence, derived from results of nonlinear gyrokinetic (GK) calculations for the steep gradient region. By using the local temperature gradient scale length L-Te in the normalization, the dependence of q(e)/q(e,g)B on the normalized gradients R/L-Te and R/(Lne) can be represented by a unified scaling with the parameter eta(e) = L-ne/L-Te, to which the linear stability of ETG turbulence is sensitive when the density gradient is sufficiently steep. For a prescribed density profile, the value of R/L-Te determined from this scaling, required to maintain a constant electron heat flux qe across the pedestal, is used to calculate the temperature profile. Reasonable agreement with measurements is found for different cases, the model providing an explanation of the relative widths and shifts of the T-e and n(e) profiles, as well as highlighting the importance of the separatrix boundary conditions. Other cases showing disagreement indicate conditions where other branches of turbulence might dominate.This article is part of a discussion meeting issue "H-mode transition and pedestal studies in fusion plasmas'