Systematic study on nail plate assessment: differences in nail plate shape, thickness, power Doppler signal and scanning approach

Ultrasonography (US) of the nail is raising interest in the last years and its feasibility, quickness and amount of descriptive data may provide valuable information. Different authors presented several scanning approaches to nail complex in different pathological conditions, such as psoriasis, but no scanning protocol was ever proposed using healthy subjects as population of reference. The aim of the study was to establish a protocol for the US of nail plate and to assess whether the measurement of the nail plate is influenced by longitudinal vs transverse scan, sex, digit and hand dominance. Using high frequency probe and a Canon Aplio i800 machine, ultrasonographers took scans of nail plates of the hands from healthy subjects. Nail plate shape, thickness and power Doppler signal (PDUS) were evaluated and scans were taken both on longitudinal and transverse axis, at distal, middle and proximal portion of the nail plate or at a fixed angles of - 45 degrees, 0 degrees or + 45 degrees. All the images were then revised and scored using a DICOM software, in order to allow good standards of accuracy and reproducibility. A total of 27 subjects (14 females and 13 males) were assessed. The measures did not result to differ in different portions or angles. Furthermore, no difference appears in sex or dominant vs not dominant hand. A decreasing and significant trend for nail plate thickness was found from the first to the fifth finger. Doppler signal was found in all but one subjects, with a range from almost absent to very evident. No difference was found between groups regarding PDUS. The data provided suggest that a proper scan protocol should include all the nails and evaluation should be done both on longitudinal and transverse axis. Since Doppler signal is highly variable in healthy subjects, its presence should be carefully considered as pathological finding. Observations provided by this study clarify important points of the scanning technique and solve doubts related to which nails should be scanned and where to evaluate quantitative parameters

SM2RAIN–ASCAT (2007–2018): global daily satellite rainfall data from ASCAT soil moisture observations

Abstract. Long-term gridded precipitation products are crucial for several applications in hydrology, agriculture and climate sciences. Currently available precipitation products suffer from space and time inconsistency due to the non-uniform density of ground networks and the difficulties in merging multiple satellite sensors. The recent "bottom-up" approach that exploits satellite soil moisture observations for estimating rainfall through the SM2RAIN (Soil Moisture to Rain) algorithm is suited to build a consistent rainfall data record as a single polar orbiting satellite sensor is used. Here we exploit the Advanced SCATterometer (ASCAT) on board three Meteorological Operational (MetOp) satellites, launched in 2006, 2012, and 2018, as part of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Polar System programme. The continuity of the scatterometer sensor is ensured until the mid-2040s through the MetOp Second Generation Programme. Therefore, by applying the SM2RAIN algorithm to ASCAT soil moisture observations, a long-term rainfall data record will be obtained, starting in 2007 and lasting until the mid-2040s. The paper describes the recent improvements in data pre-processing, SM2RAIN algorithm formulation, and data post-processing for obtaining the SM2RAIN–ASCAT quasi-global (only over land) daily rainfall data record at a 12.5 km spatial sampling from 2007 to 2018. The quality of the SM2RAIN–ASCAT data record is assessed on a regional scale through comparison with high-quality ground networks in Europe, the United States, India, and Australia. Moreover, an assessment on a global scale is provided by using the triple-collocation (TC) technique allowing us also to compare these data with the latest, fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5), the Early Run version of the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG), and the gauge-based Global Precipitation Climatology Centre (GPCC) products. Results show that the SM2RAIN–ASCAT rainfall data record performs relatively well at both a regional and global scale, mainly in terms of root mean square error (RMSE) when compared to other products. Specifically, the SM2RAIN–ASCAT data record provides performance better than IMERG and GPCC in data-scarce regions of the world, such as Africa and South America. In these areas, we expect larger benefits in using SM2RAIN–ASCAT for hydrological and agricultural applications. The limitations of the SM2RAIN–ASCAT data record consist of the underestimation of peak rainfall events and the presence of spurious rainfall events due to high-frequency soil moisture fluctuations that might be corrected in the future with more advanced bias correction techniques. The SM2RAIN–ASCAT data record is freely available at https://doi.org/10.5281/zenodo.3405563 (Brocca et al., 2019) (recently extended to the end of August 2019)

SM2RAIN-ASCAT (2007–2018): global daily satellite rainfallfrom ASCAT soil moisture

Abstract. Long-term gridded precipitation products are crucial for several applications in hydrology, agriculture and climate sciences. Currently available precipitation products obtained from rain gauges, remote sensing and meteorological modelling suffer from space and time inconsistency due to non-uniform density of ground networks and the difficulties in merging multiple satellite sensors. The recent bottom up approach that uses satellite soil moisture observations for estimating rainfall through the SM2RAIN algorithm is suited to build long-term and consistent rainfall data record as a single polar orbiting satellite sensor is used. We exploit here the Advanced SCATterometer (ASCAT) on board three Metop satellites, launched in 2006, 2012 and 2018. The continuity of the scatterometer sensor on European operational weather satellites is ensured until mid-2040s through the Metop Second Generation Programme. By applying SM2RAIN algorithm to ASCAT soil moisture observations a long-term rainfall data record can be obtained, also operationally available in near real time. The paper describes the recent improvements in data pre-processing, SM2RAIN algorithm formulation, and data post-processing for obtaining the SM2RAIN-ASCAT global daily rainfall dataset at 12.5 km sampling (2007–2018). The quality of SM2RAIN-ASCAT dataset is assessed on a regional scale through the comparison with high-quality ground networks in Europe, United States, India and Australia. Moreover, an assessment on a global scale is provided by using the Triple Collocation technique allowing us also the comparison with other global products such as the latest European Centre for Medium-Range Weather Forecasts reanalysis (ERA5), the Global Precipitation Measurement (GPM) mission, and the gauge-based Global Precipitation Climatology Centre (GPCC) product. Results show that the SM2RAIN-ASCAT rainfall dataset performs relatively well both at regional and global scale, mainly in terms of root mean square error when compared to other datasets. Specifically, SM2RAIN-ASCAT dataset provides better performance better than GPM and GPCC in the data scarce regions of the world, such as Africa and South America. In these areas we expect the larger benefits in using SM2RAIN-ASCAT for hydrological and agricultural applications.The SM2RAIN-ASCAT dataset is freely available at https://doi.org/10.5281/zenodo.2591215

Altimetry for the future: Building on 25 years of progress

In 2018 we celebrated 25 years of development of radar altimetry, and the progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy and cryospheric sciences. Many symbolic major events have celebrated these developments, e.g., in Venice, Italy, the 15th (2006) and 20th (2012) years of progress and more recently, in 2018, in Ponta Delgada, Portugal, 25 Years of Progress in Radar Altimetry. On this latter occasion it was decided to collect contributions of scientists, engineers and managers involved in the worldwide altimetry community to depict the state of altimetry and propose recommendations for the altimetry of the future. This paper summarizes contributions and recommendations that were collected and provides guidance for future mission design, research activities, and sustainable operational radar altimetry data exploitation. Recommendations provided are fundamental for optimizing further scientific and operational advances of oceanographic observations by altimetry, including requirements for spatial and temporal resolution of altimetric measurements, their accuracy and continuity. There are also new challenges and new openings mentioned in the paper that are particularly crucial for observations at higher latitudes, for coastal oceanography, for cryospheric studies and for hydrology. The paper starts with a general introduction followed by a section on Earth System Science including Ocean Dynamics, Sea Level, the Coastal Ocean, Hydrology, the Cryosphere and Polar Oceans and the ‘‘Green” Ocean, extending the frontier from biogeochemistry to marine ecology. Applications are described in a subsequent section, which covers Operational Oceanography, Weather, Hurricane Wave and Wind Forecasting, Climate projection. Instruments’ development and satellite missions’ evolutions are described in a fourth section. A fifth section covers the key observations that altimeters provide and their potential complements, from other Earth observation measurements to in situ data. Section 6 identifies the data and methods and provides some accuracy and resolution requirements for the wet tropospheric correction, the orbit and other geodetic requirements, the Mean Sea Surface, Geoid and Mean Dynamic Topography, Calibration and Validation, data accuracy, data access and handling (including the DUACS system). Section 7 brings a transversal view on scales, integration, artificial intelligence, and capacity building (education and training). Section 8 reviews the programmatic issues followed by a conclusion

Altimetry for the future: building on 25 years of progress

In 2018 we celebrated 25 years of development of radar altimetry, and the progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy and cryospheric sciences. Many symbolic major events have celebrated these developments, e.g., in Venice, Italy, the 15th (2006) and 20th (2012) years of progress and more recently, in 2018, in Ponta Delgada, Portugal, 25 Years of Progress in Radar Altimetry. On this latter occasion it was decided to collect contributions of scientists, engineers and managers involved in the worldwide altimetry community to depict the state of altimetry and propose recommendations for the altimetry of the future. This paper summarizes contributions and recommendations that were collected and provides guidance for future mission design, research activities, and sustainable operational radar altimetry data exploitation. Recommendations provided are fundamental for optimizing further scientific and operational advances of oceanographic observations by altimetry, including requirements for spatial and temporal resolution of altimetric measurements, their accuracy and continuity. There are also new challenges and new openings mentioned in the paper that are particularly crucial for observations at higher latitudes, for coastal oceanography, for cryospheric studies and for hydrology. The paper starts with a general introduction followed by a section on Earth System Science including Ocean Dynamics, Sea Level, the Coastal Ocean, Hydrology, the Cryosphere and Polar Oceans and the “Green” Ocean, extending the frontier from biogeochemistry to marine ecology. Applications are described in a subsequent section, which covers Operational Oceanography, Weather, Hurricane Wave and Wind Forecasting, Climate projection. Instruments’ development and satellite missions’ evolutions are described in a fourth section. A fifth section covers the key observations that altimeters provide and their potential complements, from other Earth observation measurements to in situ data. Section 6 identifies the data and methods and provides some accuracy and resolution requirements for the wet tropospheric correction, the orbit and other geodetic requirements, the Mean Sea Surface, Geoid and Mean Dynamic Topography, Calibration and Validation, data accuracy, data access and handling (including the DUACS system). Section 7 brings a transversal view on scales, integration, artificial intelligence, and capacity building (education and training). Section 8 reviews the programmatic issues followed by a conclusion

SM2RAIN-Climate, a monthly global long-term rainfall dataset for climatological studies

Abstract A reliable and accurate long-term rainfall dataset is an indispensable resource for climatological studies and crucial for application in water resource management, agriculture, and hydrology. SM2RAIN (Soil Moisture to Rain) derived datasets stand out as a unique and wholly independent global product that estimates rainfall from satellite soil moisture observations. Previous studies have demonstrated the SM2RAIN products’ high potential in estimating rainfall around the world. This manuscript describes the SM2RAIN-Climate rainfall product, which uses the European Space Agency (ESA) Climate Change Initiative (CCI) soil moisture v06.1 to provide monthly global rainfall for the 24-year period 1998–2021 at 1-degree spatial resolution. The assessment of the proposed rainfall dataset against different existing state-of-the-art rainfall products exhibits the robust performance of SM2RAIN-Climate in most regions of the world. This performance is indicated by correlation coefficients between SM2RAIN-Climate and state-of-the-art products, consistently exceeding 0.8. Moreover, evaluation results indicate the potential of SM2RAIN-Climate as an independent rainfall product from other satellite rainfall products in capturing the pattern of global rainfall trend

Toward a self-calibrated and independent SM2RAIN rainfall product

This is the accepted manuscript version of this paper before copy-editing, formatting, technical enhancements and pagination. The finally published version (version of record) is available via https://doi.org/10.1016/j.jhydrol.2021.126837 © 2021. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/ licenses/by-nc-nd/4.0/Rainfall monitoring is fundamental in many hydrological applications such as flood and landslide forecasting and water resources management. In-situ measurements are the traditional data source of rainfall, but the worldwide declining number of stations, their low spatial representativeness and the data access problem limit their use. Satellite products are being widely used as an alternative data source. Among them, SM2RAIN-based products, which exploit the inversion of the water balance equation to derive rainfall from soil moisture observations, have shown relatively good skills for hydrological applications. However, the need of calibrating the SM2RAIN parameter values against a reference represents one important limitation, particularly over data scarce regions. In this study, we explore the possibility to self-calibrate SM2RAIN and thus to obtain rainfall estimates from the Advanced SCATterometer (ASCAT) soil moisture independently from any reference rainfall dataset. Four parametric relationships relating SM2RAIN parameter values to static descriptors (average rainfall, topography, soil moisture noise) are developed. To develop such relationships, a sample of 1009 points uniformly distributed over the areas covered by rain gauges in Australia, India, Italy and the United States is selected. A global validation of the methodology is conducted by comparing the performances of the parameterized product with the classical product in which the parameter values are estimated by calibration against a reference rainfall dataset. The Final Run of the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) precipitation dataset is used for performance assessment, together with the triple collocation techniques by using the Gauge-based Global Precipitation Climatology Center (GPCC) product and the Late Run of IMERG. The aim of the analysis is to obtain an uncalibrated SM2RAIN methodology to retrieve rainfall whose performance are similar to those obtained with calibration. The results at 1009 points show that the performances of the parameterized SM2RAIN product are in line with those of the calibrated one, with an increased capability in the detection of intense rainfall events and an acceptable reduction of the performance according to both Pearson Correlation and Root Mean Square Error indexes. The application of triple collocation confirms these findings on a global scale, showing that the SM2RAIN product outperforms both GPCC and IMERG –– Late run estimations in areas characterized by low density of rain gauges and good quality of ASCAT soil moisture retrievals (i.e., Africa and South America).1131

Un esperimento di valutazione cognitiva del questionario nell'indagine sui consumi

CON PRI - La misura dei consumi privatiConsiglio Nazionale delle Ricerche (CNR). Biblioteca Centrale / CNR - Consiglio Nazionale delle RichercheSIGLEITItal

L'impiego dei diari individuali e dei documenti di spesa nell'indagine sui consumi

Consiglio Nazionale delle Ricerche (CNR). Biblioteca Centrale / CNR - Consiglio Nazionale delle RichercheSIGLEITItal