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The initial conditions for the simulation of a seismically induced tsunami for a rapid, assumed-to-be-instantaneous vertical seafloor displacement is given by the Kajiura low-pass filter integral. This work proposes a new, efficient, and accurate approach for its numerical evaluation, valid when the seafloor displacement is discretized as a set of rectangular contributions over variable bathymetry. We compare several truncated quadrature formulae, selecting the optimal one. The reconstruction of the initial sea level perturbation as a linear combination of pre-computed elementary sea surface displacements is tested on the tsunamigenic Kuril earthquake doublet – a megathrust and an outer rise – that occurred in the central Kuril Islands in late 2006 and early 2007. We also confirm the importance of the horizontal contribution to tsunami generation, and we consider a simple model of the inelastic deformation of the wedge on realistic bathymetry. The proposed approach results are accurate and fast enough to be considered relevant for practical applications. A tool to build a tsunami source database for a specific region of interest is provided.

Atmospheric radiative transfer models are extensively used in Earth observation to simulate radiative processes occurring in the atmosphere and to provide both upwelling and downwelling synthetic brightness temperatures for ground-based, airborne, and satellite radiometric sensors. For a meaningful comparison between simulated and observed radiances, it is crucial to characterize the uncertainty in such models. The purpose of this work is to quantify the uncertainty in radiative transfer models due to uncertainty in the associated spectroscopic parameters and to compute simulated brightness temperature uncertainties for millimeter- and submillimeter-wave channels of downward-looking satellite radiometric sensors (MicroWave Imager, MWI; Ice Cloud Imager, ICI; MicroWave Sounder, MWS; and Advanced Technology Microwave Sounder, ATMS) as well as upward-looking airborne radiometers (International Submillimetre Airborne Radiometer, ISMAR, and Microwave Airborne Radiometer Scanning System, MARSS). The approach adopted here is firstly to study the sensitivity of brightness temperature calculations to each spectroscopic parameter separately, then to identify the dominant parameters and investigate their uncertainty covariance, and finally to compute the total brightness temperature uncertainty due to the full uncertainty covariance matrix for the identified set of relevant spectroscopic parameters. The approach is applied to a recent version of the Millimeter-wave Propagation Model, taking into account water vapor, oxygen, and ozone spectroscopic parameters, though the approach is general and can be applied to any radiative transfer code. A set of 135 spectroscopic parameters were identified as dominant for the uncertainty in simulated brightness temperatures (26 for water vapor, 109 for oxygen, none for ozone). The uncertainty in simulated brightness temperatures is computed for six climatology conditions (ranging from sub-Arctic winter to tropical) and all instrument channels. Uncertainty is found to be up to few kelvins [K] in the millimeter-wave range, whereas it is considerably lower in the submillimeter-wave range (less than 1 K).

This article introduces PyRTlib, a new standalone Python package for non-scattering line-by-line microwave radiative transfer simulations. PyRTlib is a flexible and user-friendly tool for computing down- and upwelling brightness temperatures and related quantities (e.g., atmospheric absorption, optical depth, opacity, mean radiating temperature) written in Python, a language commonly used nowadays for scientific software development, especially by students and early-career scientists. PyRTlib allows for simulating observations from ground-based, airborne, and satellite microwave sensors in clear-sky and in cloudy conditions (under non-scattering Rayleigh approximation). The intention for PyRTlib is not to be a competitor to state-of-the-art atmospheric radiative transfer codes that excel in speed and/or versatility (e.g., ARTS, Atmospheric Radiative Transfer Simulator; RTTOV, Radiative Transfer for TOVS (Television Infrared Observation Satellite (TIROS) Operational Vertical Sounder)). The intention is to provide an educational tool, completely written in Python, to readily simulate atmospheric microwave radiative transfer from a variety of input profiles, including predefined climatologies, global radiosonde archives, and model reanalysis. The paper presents quick examples for the built-in modules to access popular open data archives. The paper also presents examples for computing the simulated brightness temperature for different platforms (ground-based, airborne, and satellite), using various input profiles, showing how to easily modify other relevant parameters, such as the observing angle (zenith, nadir, slant), surface emissivity, and gas absorption model. PyRTlib can be easily embedded in other Python codes needing atmospheric microwave radiative transfer (e.g., surface emissivity models and retrievals). Despite its simplicity, PyRTlib can be readily used to produce present-day scientific results, as demonstrated by two examples showing (i) an absorption model comparison and validation with ground-based radiometric observations and (ii) uncertainty propagation of spectroscopic parameters through the radiative transfer calculations following a rigorous approach. To our knowledge, the uncertainty estimate is not provided by any other currently available microwave radiative transfer code, making PyRTlib unique for this aspect in the atmospheric microwave radiative transfer code scenario.

Objective: Cancer-related diseases pose a substantial public health challenge; however, recent treatments have enhanced patient outcomes. Adherence to therapy is crucial, and research focuses on elucidating the factors that influence it. Limited information exists on medication adherence in cancer patients. This study aims to identify risk factors for non-adherence in a cohort of people with solid and hematological tumors. Participants and Methods: This is a cross-sectional study in which participants were recruited from two Oncologic hospital units in Italy. The inclusion criteria were age ≥ 18 years, confirmed malignant neoplasm, and active treatment. Data included sociodemographic and clinical-oncological factors. Treatment adherence was assessed through a clinician-based dichotomous scale. Health-related quality of life (HRQoL) was evaluated with the Short Form Health Survey – 12 items (SF-12), satisfaction with care was measured using the Treatment Perception Questionnaire. Results: A total of 263 participants (132 females, 50.2%) was involved in this study. The mean age was 61.2±13.8. Non-adherence frequency was 9.9%. Factors associated with non-adherence were shorter time since care initiation (

Objective: The demanding nature of oncological therapies may affect treatment motivation and adherence, leading to an increased risk of premature death. Exploring the interaction between depressive episodes and treatment adherence is essential, considering how depression may influence patients' willingness to continue treatment. This study aims to investigate the association between depressive episodes, low treatment adherence, and premature death in individuals with cancer. The study also assessed whether low adherence to therapy acted as a mediator in the relationship between depression and the risk of early death. Participants and Methods: This is a 9-month cohort study in which participants were enrolled in two Italian Oncology hospital units. The Patient Health Questionnaire (PHQ-9) was used for depression screening. Stratified analyses were conducted to explore the relationship between depression, low adherence, and premature death. Results: Out of 263 subjects, depressive episode frequency was 48.2% and low adherence was 9.9%. After 9 months, 13.7% had died. There was a significative association between experiencing a depressive episode (RR=2.14, 95% CI: 1.08-4.39) and low adherence (RR=2.2, 95% CI: 1.01-4.48) upon cohort entry and being deceased at month 9 of observation. The risk associated with depression was found to persist even after accounting for the level of adherence to therapy through standardization (MH-OR=3.11; 95% CI: 1.52-6.34). Conclusions: Individuals with cancer who experience a depressive episode or demonstrate low adherence to therapy are at risk for premature death. Early intervention targeting depressive symptoms and treatment adherence may improve oncological-related outcomes.

The FLASH effect is a radiobiological phenomenon that has garnered considerable interest in the clinical field. Pre-clinical experimental studies have highlighted its potential to reduce side effects on healthy tissues while maintaining isoeffectiveness on tumor tissues, thus widening the therapeutic window and enhancing the effectiveness of radiotherapy. The FLASH effect is achieved through the administration of the complete therapeutic radiation dose within a brief time frame, shorter than 200 milliseconds, and, therefore, utilizing remarkably high average dose rates above at least 40 Gy/s. Despite its potential in radiotherapy, the radiobiological mechanisms governing this effect and its quantitative relationship with temporal parameters of the radiation beam, such as dose-rate, dose-per-pulse, and average dose-rate within the pulse, remain inadequately elucidated. A more profound comprehension of these underlying mechanisms is imperative to optimize the clinical application and translation of the FLASH effect into routine practice. Due to the aforementioned factors, the undertaking of quantitative radiobiological investigations becomes imperative, necessitating the utilization of sophisticated and adaptable apparatus capable of generating radiation beams with exceedingly high dose-rates and dose-per-pulse characteristics. This study presents a comprehensive account of the design and operational capabilities of a Linear Accelerator (LINAC) explicitly tailored for FLASH radiotherapy research purposes. Termed the “ElectronFlash” (EF) LINAC, this specialized system employs a low-energy configuration (7 and 9 MeV) and incorporates a triode gun. The EF LINAC is currently operational at the Centro Pisano FLASH Radiotherapy (CPFR) facility located in Pisa, Italy. Lastly, this study presents specific instances exemplifying the LINAC’s adaptability, enabling the execution of hitherto unprecedented experiments. By enabling independent variations of the temporal parameters of the radiation beam implicated in the FLASH effect, these experiments facilitate the acquisition of quantitative data concerning the effect’s dependence on these specific parameters. This novel approach hopefully contributes to a more comprehensive understanding of the FLASH effect, shedding light on its intricate radiobiological behavior and offering valuable insights for optimizing its clinical implementation.

Summary: Quantifying the risk of progression to Alzheimer’s disease (AD) could help identify persons who could benefit from early interventions. We used data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI, n = 544, discovery cohort) and the National Alzheimer’s Coordinating Center (NACC, n = 508, validation cohort), subdividing individuals with mild cognitive impairment (MCI) into risk groups based on cerebrospinal fluid amyloid-β levels and identifying differential gray matter patterns. We then created models that fused neural networks with survival analysis, trained using non-parcellated T1-weighted brain MRIs from ADNI data, to predict the trajectories of MCI to AD conversion within the NACC cohort (integrated Brier score: 0.192 [discovery], and 0.108 [validation]). Using modern interpretability techniques, we verified that regions important for model prediction are classically associated with AD. We confirmed AD diagnosis labels using postmortem data. We conclude that our framework provides a strategy for risk-based stratification of individuals with MCI and for identifying regions key for disease prognosis.

BackgroundNurse-directed pain protocols for intranasal fentanyl administration are not widely implemented in European (EU) pediatric emergency departments (PED). Barriers include perceived safety concerns for intranasal (IN) fentanyl. The aim of this study is to describe our experience with a nurse-directed triage IN fentanyl protocol with a focus on safety in a tertiary EU PED.MethodsWe conducted a retrospective analysis of patient records of children aged 0–16 years who received nurse-directed IN fentanyl between January 2019 and December 2021 at the PED of the University Children's Hospital of Bern, Switzerland. Extracted data points included demographics, presenting complaint, pain score, IN fentanyl dosage, concomitant pain medication use, and adverse events.ResultsA total of 314 patients were identified with ages ranging from 9 months to 15 years. The main indication for nurse-directed fentanyl administration was musculoskeletal pain due to trauma (n = 284, 90%). Mild adverse events (vertigo) were reported in two patients (0.6%), without a correlation to concomitant pain medication or protocol violation. The only reported severe adverse event of syncope and hypoxia in a 14-year-old adolescent occurred in a setting where the institutional nurse-directed protocol was violated.ConclusionIn accordance with previous studies outside of Europe, our data support the case that when appropriately used, nurse-directed IN fentanyl is a safe potent opioid analgesic for pediatric acute pain management. We strongly encourage the introduction of nurse-directed triage fentanyl protocols Europe-wide in order to provide effective and adequate acute pain management in children.

We present a source solution for the tsunami generated by the Mw 6.6 earthquake that occurred on 2 May 2020, about 80 km offshore south of Crete, in the Cretan Passage, on the shallow portion of the Hellenic Arc subduction zone (HASZ). The tide gauges recorded this local tsunami on the southern coast of Crete and Kasos island. We used Crete tsunami observations to constrain the geometry and orientation of the causative fault, the rupture mechanism, and the slip amount. We first modelled an ensemble of synthetic tsunami waveforms at the tide gauge locations, produced for a range of earthquake parameter values as constrained by some of the available moment tensor solutions. We allow for both a splay and a back-thrust fault, corresponding to the two nodal planes of the moment tensor solution. We then measured the misfit between the synthetic and the Ierapetra observed marigram for each source parameter set. Our results identify the shallow, steeply dipping back-thrust fault as the one producing the lowest misfit to the tsunami data. However, a rupture on a lower angle fault, possibly a splay fault, with a sinistral component due to the oblique convergence on this segment of the HASZ, cannot be completely ruled out. This earthquake reminds us that the uncertainty regarding potential earthquake mechanisms at a specific location remains quite significant. In this case, for example, it is not possible to anticipate if the next event will be one occurring on the subduction interface, on a splay fault, or on a back-thrust, which seems the most likely for the event under investigation. This circumstance bears important consequences because back-thrust and splay faults might enhance the tsunamigenic potential with respect to the subduction interface due to their steeper dip. Then, these results are relevant for tsunami forecasting in the framework of both the long-term hazard assessment and the early warning systems.

Probabilistic tsunami forecasting (PTF) defines an approach to tsunami early warning based on uncertainty quantification, enhancing forecast accuracy and enabling rational decision making. PTF is here developed for near-source tsunami warning, and tested in hindcasting mode over a wide range of past earthquakes.

New instrumental learning occurs through an unexpected delivery of a rewarding stimulus or the withdrawal of a punishing stimulus. The authors show that D1 receptor-expressing medium spiny neurons (MSNs) in the anterior dorsolateral striatum encode newly learned instrumental actions whereas D2 MSNs promote the expression of habitual actions.

Ground-based microwave radiometer (MWR) observations of downwelling brightness temperature (TB) are commonly used to estimate atmospheric attenuation at relative transparent channels for radio propagation and telecommunication purposes. The atmospheric attenuation is derived from TB by inverting the radiative transfer equation with a priori knowledge of the mean radiating temperature (TMR). TMR is usually estimated by either time-variant site climatology (e.g., monthly average computed from atmospheric thermodynamical profiles) or condition-variant estimation from surface meteorological sensors. However, information on TMR may also be extracted directly from MWR measurements at channels other than those used to estimate atmospheric attenuation. This paper proposes a novel approach to estimate TMR in clear and cloudy sky from independent MWR profiler measurements. A linear regression algorithm is trained with a simulated dataset obtained by processing 1 year of radiosonde observations of atmospheric thermodynamic profiles. The algorithm is trained to estimate TMR at K- and V–W-band frequencies (22–31 and 72–82 GHz, respectively) from independent MWR observations at the V band (54–58 GHz). The retrieval coefficients are then applied to a 1-year dataset of real V-band observations, and the estimated TMR at the K and V–W band is compared with estimates from nearly colocated and simultaneous radiosondes. The proposed method provides TMR estimates in better agreement with radiosondes than a traditional method, with 32 %–38 % improvement depending on frequency. This maps into an expected improvement in atmospheric attenuation of 10 %–20 % for K-band channels and ∼30 % for V–W-band channels.

This paper describes the first official release (v1.0) of RTTOV-gb. RTTOV-gb is a FORTRAN 90 code developed by adapting the atmospheric radiative transfer code RTTOV, focused on satellite-observing geometry, to the ground-based observing geometry. RTTOV-gb is designed to simulate ground-based upward-looking microwave radiometer (MWR) observations of atmospheric downwelling natural radiation in the frequency range from 22 to 150 GHz. Given an atmospheric profile of temperature, water vapor, and, optionally, cloud liquid water content, and together with a viewing geometry, RTTOV-gb computes downwelling radiances and brightness temperatures leaving the bottom of the atmosphere in each of the channels of the sensor being simulated. In addition, it provides the sensitivity of observations to the atmospheric thermodynamical state, i.e., the Jacobians. Therefore, RTTOV-gb represents the forward model needed to assimilate ground-based MWR data into numerical weather prediction models, which is currently pursued internationally by several weather services. RTTOV-gb is fully described in a previous paper (De Angelis et al., 2016), while several updates are described here. In particular, two new MWR types and a new parameterization for the atmospheric absorption model have been introduced since the first paper. In addition, estimates of the uncertainty associated with the absorption model and with the fast parameterization are given here. Brightness temperatures (TB) computed with RTTOV-gb v1.0 from radiosonde profiles have been compared with ground-based MWR observations in six channels (23.8, 31.4, 72.5, 82.5, 90.0, and 150.0 GHz). The comparison shows statistics within the expected accuracy. RTTOV-gb is now available to licensed users free of charge from the Numerical Weather Prediction Satellite Application Facility (NWP SAF) website, after registration. Coefficients for four MWR instrument types and two absorption model parameterizations are also freely available from the RTTOV-gb support website.

Site-specific seismic probabilistic tsunami hazard analysis (SPTHA) is a computationally demanding task, as it requires, in principle, a huge number of high-resolution numerical simulations for producing probabilistic inundation maps. We implemented an efficient and robust methodology using a filtering procedure to reduce the number of numerical simulations needed while still allowing for a full treatment of aleatory and epistemic uncertainty. Moreover, to avoid biases in tsunami hazard assessment, we developed a strategy to identify and separately treat tsunamis generated by near-field earthquakes. Indeed, the coseismic deformation produced by local earthquakes necessarily affects tsunami intensity, depending on the scenario size, mechanism and position, as coastal uplift or subsidence tends to diminish or increase the tsunami hazard, respectively. Therefore, we proposed two parallel filtering schemes in the far- and the near-field, based on the similarity of offshore tsunamis and hazard curves and on the similarity of the coseismic fields, respectively. This becomes mandatory as offshore tsunami amplitudes can not represent a proxy for the coastal inundation in the case of near-field sources. We applied the method to an illustrative use case at the Milazzo oil refinery (Sicily, Italy). We demonstrate that a blind filtering procedure can not properly account for local sources and would lead to a nonrepresentative selection of important scenarios. For the specific source–target configuration, this results in an overestimation of the tsunami hazard, which turns out to be correlated to dominant coastal uplift. Different settings could produce either the opposite or a mixed behavior along the coastline. However, we show that the effects of the coseismic deformation due to local sources can not be neglected and a suitable correction has to be employed when assessing local-scale SPTHA, irrespective of the specific signs of coastal displacement.

This paper presents a general approach to quantify absorption model uncertainty due to uncertainty in the underlying spectroscopic parameters. The approach is applied to a widely used microwave absorption model (Rosenkranz, 2017) and radiative transfer calculations in the 20–60 GHz range, which are commonly exploited for atmospheric sounding by microwave radiometer (MWR). The approach, however, is not limited to any frequency range, observing geometry, or particular instrument. In the considered frequency range, relevant uncertainties come from water vapor and oxygen spectroscopic parameters. The uncertainty of the following parameters is found to dominate: (for water vapor) self- and foreign-continuum absorption coefficients, line broadening by dry air, line intensity, the temperature-dependence exponent for foreign-continuum absorption, and the line shift-to-broadening ratio; (for oxygen) line intensity, line broadening by dry air, line mixing, the temperature-dependence exponent for broadening, zero-frequency line broadening in air, and the temperature-dependence coefficient for line mixing. The full uncertainty covariance matrix is then computed for the set of spectroscopic parameters with significant impact. The impact of the spectroscopic parameter uncertainty covariance matrix on simulated downwelling microwave brightness temperatures (TB) in the 20–60 GHz range is calculated for six atmospheric climatology conditions. The uncertainty contribution to simulated TB ranges from 0.30 K (subarctic winter) to 0.92 K (tropical) at 22.2 GHz and from 2.73 K (tropical) to 3.31 K (subarctic winter) at 52.28 GHz. The uncertainty contribution is nearly zero at 55–60 GHz frequencies. Finally, the impact of spectroscopic parameter uncertainty on ground-based MWR retrievals of temperature and humidity profiles is discussed.

Finite-fault models for the 2010 Mw 8.8 Maule, Chile earthquake indicate bilateral rupture with large-slip patches located north and south of the epicenter. Previous studies also show that this event features significant slip in the shallow part of the megathrust, which is revealed through correction of the forward tsunami modeling scheme used in tsunami inversions. The presence of shallow slip is consistent with the coseismic seafloor deformation measured off the Maule region adjacent to the trench and confirms that tsunami observations are particularly important for constraining far-offshore slip. Here, we benchmark the method of Optimal Time Alignment (OTA) of the tsunami waveforms in the joint inversion of tsunami (DART and tide-gauges) and geodetic (GPS, InSAR, land-leveling) observations for this event. We test the application of OTA to the tsunami Green’s functions used in a previous inversion. Through a suite of synthetic tests we show that if the bias in the forward model is comprised only of delays in the tsunami signals, the OTA can correct them precisely, independently of the sensors (DART or coastal tide-gauges) and, to the first-order, of the bathymetric model used. The same suite of experiments is repeated for the real case of the 2010 Maule earthquake where, despite the results of the synthetic tests, DARTs are shown to outperform tide-gauges. This gives an indication of the relative weights to be assigned when jointly inverting the two types of data. Moreover, we show that using OTA is preferable to subjectively correcting possible time mismatch of the tsunami waveforms. The results for the source model of the Maule earthquake show that using just the first-order modeling correction introduced by OTA confirms the bilateral rupture pattern around the epicenter, and, most importantly, shifts the inferred northern patch of slip to a shallower position consistent with the slip models obtained by applying more complex physics-based corrections to the tsunami waveforms. This is confirmed by a slip model refined by inverting geodetic and tsunami data complemented with a denser distribution of GPS data nearby the source area. The models obtained with the OTA method are finally benchmarked against the observed seafloor deformation off the Maule region. We find that all of the models using the OTA well predict this offshore coseismic deformation, thus overall, this benchmarking of the OTA method can be considered successful.

This article focuses on Ordo Romanus XI, a liturgical script that describes the process for performing baptism. Including its preparatory meetings. First, the essay discusses the context in which the source was created, and second draws on its evidence to understand elements of the society of its origin. It is argued that the source was composed in the city of Rome in the second half of the seventh century, and it was intended to introduce innovations into the celebration and conception of baptism there. While previous research has characterized the source as one milestone in the history of baptism, a close reading of it provides valuable hints as to the behavior, attitudes, and identity of seventh-century Romans, both on individual and collective levels. Baptism inducted people into Christian society, cleansed them from sin, and made salvation possible. It mediated both human and supernatural relationships. Further, it strengthened Christian belief, gender roles, and the conception that Romans were the new Israelites. On cover: Monks singing the Office and decorated initial A[sperges me.]. Gradual Olivetan Master (Use of the Olivetan Benedictines), illuminated manuscript on parchment ca. 1430-1439. Italy, Monastero di Santa Maria di Baggio near Milan, Ca 1400-1775. Beinecke Ms1184: The olivetan Gradual. Gradual. General Collection, Beinecke Rare Book and Manuscript Library, Yale University.

We present a database of pre-calculated tsunami waveforms for the entire Mediterranean Sea, obtained by numerical propagation of uniformly spaced Gaussian-shaped elementary sources for the sea level elevation. Based on any initial sea surface displacement, the database allows the fast calculation of full waveforms at the 50 m isobath offshore of coastal sites of interest by linear superposition. A computationally inexpensive procedure is set to estimate the coefficients for the linear superposition based on the potential energy of the initial elevation field. The elementary sources size and spacing is fine enough to satisfactorily reproduce the effects of M> = 6.0 earthquakes. Tsunami propagation is modelled by using the Tsunami-HySEA code, a GPU finite volume solver for the non-linear shallow water equations. Like other existing methods based on the initial sea level elevation, the database is independent on the faulting geometry and mechanism, which makes it applicable in any tectonic environment. We model a large set of synthetic tsunami test scenarios, selected to explore the uncertainty introduced when approximating tsunami waveforms and their maxima by fast and simplified linear combination. This is the first time to our knowledge that the uncertainty associated to such a procedure is systematically analysed and that relatively small earthquakes are considered, which may be relevant in the near-field of the source in a complex tectonic setting. We find that non-linearity of tsunami evolution affects the reconstruction of the waveforms and of their maxima by introducing an almost unbiased (centred at zero) error distribution of relatively modest extent. The uncertainty introduced by our approximation can be in principle propagated to forecast results. The resulting product then is suitable for different applications such as probabilistic tsunami hazard analysis, tsunami source inversions and tsunami warning systems.

On 6 February 2013 an Mw = 8.0 subduction earthquake occurred close to Santa Cruz Islands at the transition between the Solomon and the New Hebrides Trench. The ensuing tsunami caused significant inundation on the closest Nendo Island. The seismic source was studied with teleseismic broadband P-wave inversion optimized with tsunami forward modelling at DART buoys (Lay et al., 2013) and with inversion of teleseismic body and surface waves (Hayes et al., 2014a). The two studies also use different hypocentres and different planar fault models and found quite different slip models. In particular, Hayes et al. (2014a) argued for an aseismic slip patch SE from the hypocentre. We here develop a 3-D model of the fault surface from seismicity analysis and retrieve the tsunami source by inverting DART and tide-gauge data. Our tsunami source model features a main slip patch (peak value of ~ 11 m) SE of the hypocentre and reaching the trench. The rake direction is consistent with the progressively more oblique plate convergence towards the Solomon trench. The tsunami source partially overlaps the hypothesized aseismic slip area, which then might have slipped coseismically.

This study exploits the Meteosat Second Generation (MSG)–Spinning Enhanced Visible and Infrared Imager (SEVIRI) observations to evaluate the rain class at high spatial and temporal resolutions and, to this aim, proposes the Rain Class Evaluation from Infrared and Visible observation (RainCEIV) technique. RainCEIV is composed of two modules: a cloud classification algorithm which individuates and characterizes the cloudy pixels, and a supervised classifier that delineates the rainy areas according to the three rainfall intensity classes, the non-rainy (rain rate value < 0.5 mm h-1) class, the light-to-moderate rainy class (0.5 mm h−1 ≤ rain rate value < 4 mm h-1), and the heavy–to-very-heavy-rainy class (rain rate value ≥ 4 mm h-1). The second module considers as input the spectral and textural features of the infrared and visible SEVIRI observations for the cloudy pixels detected by the first module. It also takes the temporal differences of the brightness temperatures linked to the SEVIRI water vapour channels as indicative of the atmospheric instability strongly related to the occurrence of rainfall events. The rainfall rates used in the training phase are obtained through the Precipitation Estimation at Microwave frequencies, PEMW (an algorithm for rain rate retrievals based on Atmospheric Microwave Sounder Unit (AMSU)-B observations). RainCEIV's principal aim is that of supplying preliminary qualitative information on the rainy areas within the Mediterranean Basin where there is no radar network coverage. The results of RainCEIV have been validated against radar-derived rainfall measurements from the Italian Operational Weather Radar Network for some case studies limited to the Mediterranean area. The dichotomous assessment related to daytime (nighttime) validation shows that RainCEIV is able to detect rainy/non-rainy areas with an accuracy of about 97% (96%), and when all the rainy classes are considered, it shows a Heidke skill score of 67% (62%), a bias score of 1.36 (1.58), and a probability of detection of rainy areas of 81% (81%).

The Precipitation Estimation at Microwave Frequencies (PEMW) algorithm was developed at the Institute of Methodologies for Environmental Analysis of the National Research Council of Italy (IMAA-CNR) for inferring surface rain intensity (sri) from satellite passive microwave observations in the range from 89 to 190 GHz. The operational version of PEMW (OPEMW) has been running continuously at IMAA-CNR for two years. The OPEMW sri estimates, together with other precipitation products, are used as input to an operational hydrological model for flood alert forecast. This paper presents the validation of OPEMW against simultaneous ground-based observations from a network of 20 weather radar systems and a network of more than 3000 rain gauges distributed over the Italian Peninsula and main islands. The validation effort uses a data set covering one year (July 2011–June 2012). The effort evaluates dichotomous and continuous scores for the assessment of rain detection and quantitative estimate, respectively, investigating both spatial and temporal features. The analysis demonstrates 98% accuracy in correctly identifying rainy and non-rainy areas; it also quantifies the increased ability (with respect to random chance) to detect rainy and non-rainy areas (0.42–0.45 Heidke skill score) or rainy areas only (0.27–0.29 equitable threat score). Performances are better than average during summer, fall, and spring, while worse than average in the winter season. The spatial–temporal analysis does not show seasonal dependence except over the Alps and northern Apennines during winter. A binned analysis in the 0–15 mm h−1 range suggests that OPEMW tends to slightly overestimate sri values below 6–7 mm h−1 and underestimate sri above those values. With respect to rain gauges (weather radars), the correlation coefficient is larger than 0.8 (0.9). The monthly mean difference and standard deviation remain within ±1 and 2 mm h−1 with respect to rain gauges (respectively −2–0 and 4 mm h−1 with respect to weather radars).

We present the realization of a fault-source data set designed to become the starting point in regional-scale tsunami hazard studies. Our approach focuses on the parametric fault characterization in terms of geometry, kinematics, and assessment of activity rates, and includes a systematic classification in six justification levels of epistemic uncertainty related with the existence and behaviour of fault sources. We set up a case study in the central Mediterranean Sea, an area at the intersection of the European, African, and Aegean plates, characterized by a complex and debated tectonic structure and where several tsunamis occurred in the past. Using tsunami scenarios of maximum wave height due to crustal earthquakes (Mw=7) and subduction earthquakes (Mw=7 and Mw=8), we illustrate first-order consequences of critical choices in addressing the seismogenic and tsunamigenic potentials of fault sources. Although tsunamis generated by Mw=8 earthquakes predictably affect the entire basin, the impact of tsunamis generated by Mw=7 earthquakes on either crustal or subduction fault sources can still be strong at many locales. Such scenarios show how the relative location/orientation of faults with respect to target coastlines coupled with bathymetric features suggest avoiding the preselection of fault sources without addressing their possible impact onto hazard analysis results.