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Background: While constraint‐induced movement therapy is strongly recommended as an intervention for infants with unilateral cerebral palsy, the optimal dosage remains undefined. This systematic review aims to identify the most effective level of intensity of constraint‐induced movement therapy to enhance manual function in infants at high risk of asymmetric brain lesions or unilateral cerebral palsy diagnosis. Methods: This systematic review with meta‐analysis encompassed a comprehensive search across four electronic databases to identify articles that met the following criteria: randomised controlled trials, children aged 0–6 with at high risk or with unilateral cerebral palsy, and treatment involving constraint‐induced movement therapy for upper limb function. Studies with similar outcomes were pooled by calculating the standardised mean difference score for each subgroup, and subgroups were stratified every 30 h of total intervention dosage (30–60, 61–90, >90 h). Risk of bias was assessed with Cochrane Collaboration's tool. Results: Seventeen studies were included. Meta‐analyses revealed significant differences among subgroups. The 30–60 h subgroup showed a weak effect for spontaneous use of the affected upper limb during bimanual performance, grasp function, and parents' perception of how often children use their affected upper limb. Additionally, this subgroup demonstrated a moderate effect for the parents' perception of how effectively children use their affected upper limb. Conclusions: Using a dosage ranging from 30 to 60 h when applying a constraint‐induced movement therapy protocol holds promise as the most age‐appropriate and cost‐effectiveness approach for improving upper limb functional outcomes and parent's perception. [ABSTRACT FROM AUTHOR]

Background: Accumulation of bilirubin above normal levels is considered a neurological risk factor for both premature and full‐term newborns. This systematic review aimed to determine the effect of neonatal hyperbilirubinemia on neurodevelopment in preterm and full‐term newborns. Methods: PubMed, EMBASE, Cochrane Library, CINAHL, PsycINFO, Scopus and Lilacs databases were searched for articles published until 1 June 2022. The quality of cohort and case–control studies was assessed with the Newcastle–Ottawa Scale, and the MINCir scale was used to evaluate the methodological quality of therapy studies or the therapeutic procedures. Premature neonates without neurological conditions and those born at term with hyperbilirubinemia as the sole risk factor were included. Studies reporting one or more neurodevelopmental outcomes were included with an inter‐group comparison of a hyperbilirubinemia group versus a non‐hyperbilirubinemia or non‐pathological hyperbilirubinemia group. The main outcomes were auditory function, visual function, cognitive function, motor function, behavior, global development and neurological risk. Results: The search identified 951 studies, 19 of which (n = 2210 newborns) were finally included. Fifteen of the cohort and case–control studies presented low risk of bias, and six studies showed high methodological quality. Within the preterm population, hyperbilirubinemia as the sole risk factor was not shown to affect neurodevelopment. Auditory, neurological and motor development alterations were found in the population of full‐term newborns with hyperbilirubinemia, which were more evident during the first year of life. Conclusions: Elevated bilirubin levels may be a trigger for the onset of neurodevelopmental disorders in full‐term infants during the first year of life. More studies are warranted in the preterm population with hyperbilirubinemia to draw conclusions about its impact on their neurodevelopment. [ABSTRACT FROM AUTHOR]

Introduction: Moderate-late preterm infants constitute the largest segment of preterm births globally. While previously considered to have a low neurological risk, recent research has uncovered an elevated incidence of neurodevelopmental conditions in this group. This study aimed to assess the relationship between the general movement assessment and birth-related risk factor-based tools in moderate-late preterm infants. Methods: A prospective cohort study of 65 moderate-late preterm infants in a neonatal intensive care unit involved the evaluation of general movements, the Nursery Neurobiologic Risk Score, and the Perinatal Risk Inventory. Associations were analyzed using Fisher's exact test, Spearman's correlation was used for ordinal variables, and backward stepwise logistic regression was used to identify predictor variables for the assessments. Results: The findings indicated a high prevalence of normal (41%) and poor (52%) repertoire patterns during the writhing period. While no significant associations were found between the three assessments, a slight approximation emerged between dysmorphic traits and patterns (p = 0.053). Furthermore, an extended period of ventilation correlated with a higher likelihood of developing a cramped synchronized pattern and there was a correlation between both risk factor-based tools (p < 0.001). Conclusions: This research enhances our understanding of the early impact on general movement assessments in moderate-late preterm infants. While no clear relationship emerged between general movement assessment and risk factor-based tools, there was a subtle connection noted with dysmorphic traits. A longer ventilation duration was linked to a higher risk of developing cramped synchronized patterns. [ABSTRACT FROM AUTHOR]

Background and Purpose: Carpal tunnel syndrome is the most common peripheral neuropathy of the upper extremities and kinesio taping is one of the tools used as a complementary tool within the conventional treatment of carpal tunnel syndrome. To investigate the short‐term effects of kinesio taping on pain, functionality, strength, and nerve conduction in subjects suffering from carpal tunnel syndrome. Methods: Systematic review with meta‐analysis. Seven electronic databases (MEDLINE‐Pubmed, Web of Science, Scopus, Cochrane Library, PEDro, CINAHL, and SPORTDiscus) were searched for full‐text articles published from inception to March 1st, 2023. Studies had to meet the following inclusion criteria: randomised clinical trials, including patients of legal age with mild, moderate, or severe symptoms of carpal tunnel syndrome without associated pathologies, and treating the studied body area with kinesio taping, whether or not in combination with other therapies. The DerSimonian and Laird method was employed using random effects models to calculate the pooled estimate of the effect size with confidence intervals of 95%. The risk of bias was assessed with the Cochrane Collaboration's tool and the Grading of Recommendations Assessment, Development and Evaluation approach was used to judge the certainty of the evidence for all outcomes. Results: Thirteen studies were included, comprising 665 participants with carpal tunnel syndrome. This meta‐analysis revealed a strong effect of kinesio taping on distal sensory latency and a weak effect on functionality and pain, while no significantly superior effects were found on the symptom severity, strength, or neurophysiological outcomes (distal motor latency and sensory conduction velocity) compared to other physical therapy techniques or untreated control group in the short term, with moderate‐certainty evidence. Discussion: Kinesio taping is a complementary tool to the conventional treatment of carpal tunnel syndrome that improves functionality, pain, and distal sensory latency in the short term. [ABSTRACT FROM AUTHOR]

Climate classifications are useful to synthesize the physical state of the climate with a proxy that can be directly related to biota. However, they present a potential drawback, namely a strong sensitivity because of the use of hard thresholds (step functions). Thus, minor discrepancies in the base data produce large differences in the type of climate. However, such an a priori limitation is also a strength because such sensitivity can be used to better gauge model performance. Although previous attempts of classifying climates of the world using global climate model outputs were encouraging, the applicability of their classifications to impact studies has been limited by past model issues. Notwithstanding the persistence of certain imperfections and limitations in current models, the high‐quality physical simulations from phase six of the Coupled Intercomparison Project (CMIP6) has opened new possibilities in the field, thanks to their improved representation of atmospheric and oceanic physics. The purpose of this paper is twofold: to show that climate classifications from CMIP6 are sufficiently robust for use in impact studies, and to use those classifications for identifying error sources and potential issues that deserve further attention in models. Thus, 52 CMIP6 climate models were evaluated by using three climate classifications schemes, classical Köppen, extended‐Köppen, and modified Thornthwaite. We first assessed model ability to reproduce present climate types by comparing their outputs with observational data. Models performed best for the Köppen and extended‐Köppen classification methods (Cohen's kappa κ = 0.7), and had moderate scores for the Thornthwaite climate classification (κ = 0.4). By tracing back the observed biases, we were able to pinpoint the misrepresentation of dry climates as a major source of error. Another finding was that most models still had some difficulties in representing the seasonal variability of precipitation over several monsoonal regions, thereby yielding the wrong climate type there. Models were also evaluated for future climate. Substantial changes in climate types are projected in the SSP5‐8.5 scenario. These changes include a shrinkage of polar/frigid climates (22%) and an increase of dry climates (7%). [ABSTRACT FROM AUTHOR]

Hailstorms cause heavy losses, especially when their hailstones reach a large size. One of the European regions most affected by these severe atmospheric events is southern France, where a valuable and extensive hailpad network has been operational for more than three decades. These direct observations are extremely useful because they allow for the definitive verification of hailfall at the ground. Space-based sensors have seen increasing importance in hail monitoring. Global Precipitation Measurement (GPM) is an international mission designed to advance precipitation measurements from multispectral sensors. The GPM core satellite carries a powerful and unprecedented Dual-Frequency Precipitation Radar (DPR) for studying 3D precipitation characteristics. The objective of the present study is to evaluate the DPR sensor ability to identify hailstorms. We identified eight hailstorms over France where DPR data were coincident with ground-based observations from a hailpad network during 2014–2021. In addition, variables provided by the DPR sensor indicative of hail presence were studied and five detection algorithms were tested. This research serves as background for future work and the development of prediction algorithms based on empirical relationships with GPM data. • 2387 hailfall records between 2014 and 2021 were found. • Eight hailstorms were detected by DPR scans. • Hail forecast variables were extracted from the DPR sensor and analyzed. • Five hail-detection algorithms were tested on the storms. [ABSTRACT FROM AUTHOR]

Objective: This systematic review and meta-analysis investigates the effects of strength training program in children and adolescents with cerebral palsy to improve function, activity, and participation. Data sources: Five electronic databases (MEDLINE-Pubmed, Cochrane Library, PEDro, CINAHL, and SPORTDiscus) were systematically searched for full-text articles published from inception to 30 June 2021. Review methods: Randomized controlled trials were included, who compared: (i) child population with spastic cerebral palsy population between 0 and 22 years; (ii) studies in which a muscle strength training program was performed and included dosing information; (iii) studies comparing strength training with other physical therapy technique(s) or untreated control group. Studies with similar outcomes were pooled by calculating standardized mean differences. Risk of bias was assessed with Cochrane Collaboration's tool for assessing the risk of bias and PROSPERO's registration number ID: CRD42020193535. Results: Twenty-seven studies, comprising 847 participants with spastic cerebral palsy. The meta-analyses demonstrated significant standardized mean differences in favor of strength training program compared to other physical therapy technique(s) or untreated control group(s) for muscle strength at the knee flexors, at the knee extensor, at the plantarflexors, maximum resistance, balance, gait speed, GMFM (global, D and E dimension) and spasticity. Conclusion: A strength training program has positive functional and activity effects on muscle strength, balance, gait speed, or gross motor function without increasing spasticity for children and adolescents with cerebral palsy in Gross Motor Function Classification System levels I, II, and III when adequate dosage and specific principles are utilized. [ABSTRACT FROM AUTHOR]

Gridded precipitation datasets have been developed for data assimilation and evaluation tasks of weather and climate models and for climate analyses. Gridded data uncertainty evaluation is crucial to understand the limitations and feasibility. The development of high‐resolution daily gridded precipitation datasets is desirable, but several factors need to be considered, namely rain gauge station availability, their spatial distribution, and orographic and climate characteristics of a study area. Quality assessment of gridded datasets can present difficulties when the influence of these factors is not thoroughly analysed. The main objective of this study was a detailed validation of precipitation grids based on four factors, that is, station density used for grid construction, grid spatial resolution, station altitude, and climate type. To this end, 18 grids were built using six spatial resolutions (0.01°, 0.025°, 0.05°, 0.1°, 0.2° and 0.4°) and three station densities (25, 50 and 75% of all available stations). Results indicate larger differences among the grids as a function of analysed factors. Station density was found to be the main factor, whereas grid spatial resolution had minor importance. However, the latter factor becomes more relevant in areas with strong altitude gradients and when a high station density is available. In addition, weak and moderate precipitation is overestimated on daily grids, whereas heavy precipitation cells are less frequent, reducing data variability. On the contrary, monthly and annual aggregates present less deviation from the observed distribution than daily comparisons. These findings question the applicability of the daily grid datasets for validation studies and climate analysis on a grid cell level. [ABSTRACT FROM AUTHOR]

Snowfall in elevated areas of the mid-latitudes has a strong impact on infrastructure, freshwater availability, and the climate system. The Cantabrian Mountains of the northwestern Iberian Peninsula are very vulnerable to climate change because of their moderate altitudes, which limits their snowfall. Monitoring snow events is essential for the evaluation of weather and climate prediction models. However, measurement networks are scarce in mountainous areas and have great uncertainties because of blizzards. In this study, a multiphysics ensemble of the Weather Research and Forecasting (WRF) model was designed using three microphysics and two planetary boundary layer (PBL) schemes to simulate nine snowfall events in the Cantabrian Mountains during autumn and winter 2021–2022. The WRF was validated using several snow characteristics, such as liquid water equivalent, snow cover, and snow depth. Liquid water equivalent was evaluated using snow-gauge networks and satellite products in an assessment of snow cover. In addition, a monitoring network of webcams and snow poles was implemented, improving the low density of snow observations in the mountains. The results showed good model performance for detection of snow cover and slight overestimation of liquid water equivalent and snow thickness, which may have been caused by under-catchment that is generally an effect of wind on the measurement systems and by snow compaction, respectively. Morrison microphysics and Mellor-Yamada-Nakanishi-Niino (MYNN PBL) yielded better results for liquid water equivalent at higher altitudes and output greater snow cover. The results help determine the best configurations for snow modelling in the study area to develop future studies of the spatiotemporal patterns of snow distribution. • Monitoring system of snow events in Cantabrian Mountains has been developed. • We selected nine snowfall events during autumn and winter 2021–2022. • Three microphysics and two PBL parameterizations were tested. • Morrison microphysics and MYNN PBL yielded better results at higher altitudes. [ABSTRACT FROM AUTHOR]

The aim of this paper is to analyze spatiotemporal distribution of maximum temperatures in the Iberian Peninsula (IP) by using various extreme maximum temperature indices. Thresholds for determining temperature extreme event (TEE) severity are defined using 99th percentiles of daily temperature time series for the period 1948 to 2009. The synoptic-scale fields of such events were analyzed in order to better understand the related atmospheric processes. The results indicate that the regions with a higher risk of maximum temperatures are located in the river valleys of southwest and northeast of the IP, while the Cantabrian coast and mountain ranges are characterized by lower risk. The TEEs were classified, by means of several synoptic fields (sea level pressure, temperature, and geopotential height at 850 and 500 hPa), in four clusters that largely explain their spatiotemporal distribution on the IP. The results of this study show that TEEs mainly occur associated with a ridge elongated from Subtropical areas. The relationships of TEEs with teleconnection patterns, such as the North Atlantic Oscillation (NAO), Western Mediterranean Oscillation (WeMO), and Mediterranean Oscillation (MO), showed that the interannual variability of extreme maximum temperatures is largely controlled by the dominant phase of WeMO in all seasons except wintertime where NAO is prevailing. Results related to MO pattern show less relevance in the maximum temperatures variability. The correct identification of synoptic patterns linked with the most extreme temperature event associated with each cluster will assist the prediction of events that can pose a natural hazard, thereby providing useful information for decision making and warning systems. [ABSTRACT FROM AUTHOR]

Southwestern France is one of the European regions with higher frequency of hail and substantial losses. The Association Nationale d'Etude et de Lutte contre les Fleáux Atmosphériques (ANELFA) maintains a hailpad network there in continuous operation, creating an extensive database for the study of hail. We aimed to create a new forecast tool to improve hailfall detection and determine its spatiotemporal distribution in the region. Using a database of 92 hail days between 2001 and 2010, we obtained vertical profiles of temperature, dew point temperature, and relative humidity from WRF model simulation. After validating these by comparison with radiosonde profiles from Bordeaux at 1200 UTC, 31 stability indexes were obtained for a point representative of the entire study area. These indexes were introduced in a binary logistic regression model, which selected the most accurate ones for detecting hail days in the region, namely, the Showalter index, dew point temperature at 850 hPa, and TQ index. A logistic equation to distinguish between hail and hail-free days was constructed by combining these indexes. Results show a probability of detection (POD) of 87%, false alarm ratio (FAR) of 16.7%, and a Heidke Skill Score (HSS) of 0.696. The logistic equation was then applied to the entire study zone, and the results were introduced in a cluster analysis. Four clusters of hail days were obtained according to the spatial patterns of atmospheric thermodynamic conditions and probability of hail. The average distribution of hail for each cluster shows a strong similarity with the distribution of impacted hailpads from the ANELFA network. The average synoptic environment, monthly distribution and hail characteristics at the surface were also analyzed for each cluster. Cluster 1 (August) was the least frequent, with small and weak hailfalls. Cluster 2 (June and July) and 3 (May and September) had the most intense hail events, while cluster 3 and 4 (May) had the most extensive areas affected. The new forecast tool shows satisfactory results and complements other studies in the same region, and it can be a useful tool for operational forecasters in predicting hail days and determining the spatial distribution of hailfalls. [ABSTRACT FROM AUTHOR]

Hailstorms are meteorological phenomena of great interest to the scientific community, owing to their socioeconomic impact, which is mainly on agricultural production. With its global coverage and high spatial and temporal resolution, satellite remote sensing can contribute to monitoring of such events through the development of appropriate techniques. This paper presents an extensive validation in the south of France of a hail detection tool (HDT) developed for the Middle Ebro Valley (MEV). The HDT is based on consecutive application of two filters, a convection mask (CM) and hail mask (HM), using spectral channels of the Meteosat Second Generation (MSG) satellite. The south of France is an ideal area for studying hailstorms, because there is a robust database of hail falls recorded by an extensive network of hailpads managed by the Association Nationale d'Etude et de Lutte contre les Fleáux Atmosphériques (ANELFA). The results show noticeably poorer performance of the HDT in France relative to that in the MEV, with probability of detection (POD) 60.4% and false alarm rate (FAR) 26.6%. For this reason, a new tool to suit the characteristics of hailstorms in France has been developed. The France Hail Detection Tool (FHDT) was developed using logistic regression from channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor of the MSG. The FHDT was validated, resulting in POD 69.3% and FAR 15.4%, thus improving hail detection in the study area as compared with the previous tool. The new tool was tested in a case study with satisfactory results, supporting its future practical application. [ABSTRACT FROM AUTHOR]

ABSTRACT The study of weather extremes is critical because of their great impact on the environment, economy and society. The identification of areas at greater risk of extreme conditions, and of meteorological situations that give rise to such conditions, enhances the understanding of climate risks and helps establish measures to reduce adverse impacts. In the current paper, precipitation extreme events ( PEEs) in Spain between 1960 and 2011 were analysed. Thresholds for determining event severity were defined using 99th percentiles. First, regions of extreme weather risk were identified and then trends of extreme precipitation index were analysed using the Mann-Kendall test. To better understand atmospheric processes associated with extreme weather events in each season, synoptic-scale fields of events exceeding the 99th percentile were analysed. By applying non-hierarchical K-means clustering, we defined six large-scale atmospheric patterns that largely explain the spatiotemporal distribution of PEEs in the study area. PEEs on the western Iberian Peninsula mainly occurred with zonal flow, with a long Atlantic fetch generating moisture advection towards that area. On the eastern peninsula, the most important pattern for PEE production is characterized by a cutoff low at mid-levels together with easterly moisture flow. The relationship of PEEs with teleconnection patterns, such as the North Atlantic Oscillation ( NAO), Mediterranean Oscillation ( MO) and Western Mediterranean Oscillation ( WeMO), showed that nearly all the events over the southwestern peninsula were during the NAO- and MO-negative phases. However, on the Mediterranean coast, the negative WeMO phase had greater influence. By contrast, the northwestern peninsula and eastern Cantabrian coast showed weaker relationships between these indices and PEEs. The results show a clear ability to identify regions exposed to extreme precipitation hazards. The correct identification of synoptic patterns associated with each type of weather extreme will assist the prediction of such events, thereby providing useful information for decision making and warning systems. [ABSTRACT FROM AUTHOR]

Purpose: Paddle tennis is considered a sport with high ocular risk. The most frequent eye injuries are caused by the impact of shovels, balls or earth particles, with injuries to the posterior pole of the eye (retina and vitreous) being the most serious and can lead to loss of vision due to retinal detachment, choroidal tears or eye burst many times due to not using adequate protection. In this paper, we analyse posterior pole injuries and their treatment. Methods: The cases of ocular injuries in the practice of paddle tennis in the last three years seen in the ophthalmology emergency service of our hospital have been collected. Results: 34 patients have been included, 30 men and 4 women, with a mean age of 34 years. The initial visual acuity was 0.74 and the final visual acuity was 0.9. The lesions seen have been retinal edema, vitreous haemorrhages, retinal haemorrhages, retinochoroidal tears, retinal tears, macular hole, vitreous base avulsion and angular recession glaucoma, in many cases associating more than one type of injury. In most cases, topical treatment (25 cases), topical and oral (5 cases), laser (5 cases) and surgery (3 cases) have been performed. In no case, did they use eye protection. Conclusions: Most of the cases presented good initial visual acuity, however, all presented potentially serious lesions in the posterior pole (retina and/or choroid), including two cases of retinal detachment and one angular recession glaucoma that required surgery. For this reason, it is necessary to insist on the use of approved polycarbonate protective glasses for all players and in case of ocular contusion, review by the ophthalmology service to assess the eye fundus regardless of the initial vision. [ABSTRACT FROM AUTHOR]

Precipitation is one of the most relevant fields in atmospheric modeling because of its environmental, social and economic implications. However, precipitation validation from weather model outputs presents substantial challenges, such as measurement uncertainties, use of gridded datasets vs. direct observations, and the selection of statistical goodness-of-fit measures. The main difficulty of working with precipitation is that it can be spatially irregular, especially in extreme events. High temporal aggregation smooths the field and reduces verification uncertainty. For this reason, validations are usually focused on a daily scale. However, many extreme events occur on shorter periods, for which a sub-daily precipitation assessment is required. In this paper, hourly precipitation verification of the Weather Research and Forecasting (WRF) model is explored for 45 extreme precipitation events (EPEs) recorded in northeastern Spain. For this, stations with recorded EPEs were classified according to the hourly distribution of precipitation. WRF simulations were established considering three microphysics and two planetary boundary layer (PBL) parameterizations. Finally, several statistical goodness-of-fit measures and spatial and temporal precipitation distributions were used for evaluating WRF performance. The results showed that microphysics were more important than PBL parameterizations. Goddard and Thompson together with Mellor-Yamada-Nakanishi and Nino PBL gave better results for most of the analyzed characteristics. However, an optimal combination of parameterizations was not obtained for all EPEs, because event characteristics had important effects on model performance. • Hourly precipitation verification of the WRF model has been explored. • We selected 965 stations where extreme precipitation was recorded. • Three microphysics and two planetary boundary layer parameterizations were tested. • Goddard and Thompson together with Mellor-Yamada-Nakanishi and Nino gave better results. [ABSTRACT FROM AUTHOR]

The Iberian Peninsula (IP), located in a transition area between temperate and subtropical latitudes, has marked temporal and spatial variability of precipitation between its various climatic zones. Therefore, the peninsula is particularly sensitive to climate change owing to frequent periods of precipitation deficit together with societal dependence on water. In this study, we address meteorological droughts of the peninsula between 1901 and 2010, using the Global Precipitation Climatology Center database. First, we carried out a statistical classification of the peninsula according to annual precipitation cycle. The spatiotemporal variability of droughts was evaluated using the Standardized Precipitation Index (SPI) by determining the evolution of areas affected by severe and extreme drought. Subsequently, we calculated the overall trend of precipitation and anomalies to investigate whether an observed drought increase is attributable to a decrease of precipitation or an increase of precipitation extremes. Finally, we examined periodicities of precipitation anomalies via wavelet analysis, relating these to large-scale modes such as the North Atlantic Oscillation (NAO). The results show an increase in the area affected by severe and extreme drought, particularly on Atlantic-facing slopes. The mainland areas have longer and more intense periods of drought, with an average SPI of − 0.52 and 4-month duration. Over the 110 years analyzed, we observed weak trends of annual precipitation in the extreme northwest and southern IP. However, in the last decades of the series, long periods of strong negative anomalies are seen, interspersed with years of strong positive anomalies, suggesting an increase in precipitation pattern extremes. Finally, the relationship between the NAO index and precipitation anomalies on the Atlantic seaboard is highlighted. Thus, in both series we found a 5–6-year periodicity in their first years, with a diminishing cycle period reaching a periodicity of 2–3 years in the final years. This confirms the existence of regular temporal cycles in which droughts alternate with wet periods modulated by large-scale modes. [ABSTRACT FROM AUTHOR]

Abstract: The characterization of atmospheric conditions at different scales and their relationships to meteorological phenomena is a basic tool for improving the understanding and prediction of severe atmospheric events. Hailstorms are relatively common in southern Europe during summer, causing significant adverse impacts to property and infrastructure. This paper provides a spatiotemporal characterization of hail falls in southwestern France between 2000 and 2010, using the hail pad network operated there by the Association Nationale d'Etude et de Lutte contre les Fléaux Atmosphériques (ANELFA). This area is greatly affected by hailstorms. It was observed that the greatest incidence and severity of hail was in the central Pyrenees during May and July, with decreasing frequency and intensity toward the Atlantic coast. We selected 100 events in which severe hailstorms were reported, to study atmospheric parameters responsible for their occurrence. We performed mesoscale simulations with the WRF model, using parameterizations and fields reported in previous studies. By applying principal component analysis (PCA) and cluster analysis, we obtained three configurations to help establish relationships with the spatiotemporal incidence of hailstorms. The method and results obtained improve knowledge of the conditions favorable for hailstorms in southwestern France. This allows better hail prediction by relating atmospheric conditions with characteristics of hail precipitation on the ground. [Copyright &y& Elsevier]

AbstractAimsMethodsResultsConclusionsTo review the literature on the effects of vestibular training on motor function and balance in children and youth with cerebral palsy.Eight databases (MEDLINE-PubMed, PEDro, Cochrane Library, OTSeeker, Web of Science, Scopus Database, CINAHL and SPORTDiscus.) were searched up to May 15th, 2023. Studies comparing vestibular training with other types of interventions. The DerSimonian and Laird method was employed using random effects models to calculate the pooled estimate of the effect size with confidence intervals of 95%. The risk of bias was assessed with the Cochrane Collaboration’s tool and the Grading of Recommendations Assessment, Development and Evaluation approach was used to judge the certainty of the evidence for all outcomes.Eight studies were included comprising 226 participants with cerebral palsy. The meta-analyses demonstrated significant standardized mean differences in favor of vestibular training program compared to other technique(s) for Gross Motor Function Measure (−0.471; 95% confidence intervals: −0.919 to −0.023) and balance (−0.546; 95% confidence intervals: −0.916 to −0.176).Vestibular training has potential benefits in the short-term as a therapeutic approach for improving gross motor function and the balance in children and youth with cerebral palsy, but further research is needed. [ABSTRACT FROM AUTHOR]

The treatment of colored effluents has been addressed using different methodologies, such as the coupling of adsorption to solid-state fermentation (SSF). This work shows for the first time the use of an agricultural by-product (corncob) as the adsorbent for the removal of the binary mixture of dyes, brilliant blue and allura red, and their subsequent decolorization by white-rot fungi. Pleurotus ostreatus , Trametes versicolor and their consortium were the selected fungal species for carrying out the second step of this bioprocess. A 23 full factorial design was adopted, obtaining a maximum decolorization of 90.8 ± 4.1% with T. versicolor at a 20:1 carbon:nitrogen ratio, 80% moisture and the absence of inducer. Moreover, the effect of different carbon and nitrogen sources was evaluated; yeast extract was discovered to be the most efficient nitrogen source, while the supplement of a carbon source was unnecessary to reach high levels of decolorization. Regarding the influence of the inducer, it was found that although copper addition favored enzyme levels of laccase (Lac), no positive effect was observed in either the decolorization rate of the dye mixture or the manganese peroxidase (MnP) activity, and a maximum of 19.8 ± 2.1 U Lac gds−1 and 5.4 ± 1.3 U MnP gds−1 was obtained. These results suggest that the coupled adsorption-SSF methodology using corncob and white-rot fungi represents a promising strategy for the treatment of effluents polluted with dye mixtures. Image 1 • T. versicolor efficiently decolorized the dye mixture adsorbed onto corncob. • The fungal consortium P. ostreatus - T. versicolor did not show the expected synergy. • Nutritional and abiotic changes had high effect on the decolorization. • Laccase was the most abundant enzyme with a direct relationship with decolorization. • Copper addition did not improve the decolorization efficiency. [ABSTRACT FROM AUTHOR]

Daily time series from the Climate Prediction Center (CPC) Africa Rainfall Climatology version 2.0 (ARC2), Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) and Tropical Applications of Meteorology using SATellite (TAMSAT) African Rainfall Climatology And Time series version 2 (TARCAT) high-resolution long-term satellite rainfall products are exploited to study the spatial and temporal variability of East Africa (EA, 5S–20N, 28–52E) rainfall between 1983 and 2015. Time series of selected rainfall indices from the joint CCl/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices are computed at yearly and seasonal scales. Rainfall climatology and spatial patterns of variability are extracted via the analysis of the total rainfall amount (PRCPTOT), the simple daily intensity (SDII), the number of precipitating days (R1), the number of consecutive dry and wet days (CDD and CWD), and the number of very heavy precipitating days (R20). Our results show that the spatial patterns of such trends depend on the selected rainfall product, as much as on the geographic areas characterized by statistically significant trends for a specific rainfall index. Nevertheless, indications of rainfall trends were extracted especially at the seasonal scale. Increasing trends were identified for the October–November–December PRCPTOT, R1, and SDII indices over eastern EA, with the exception of Kenya. In March–April–May, rainfall is decreasing over a large part of EA, as demonstrated by negative trends of PRCPTOT, R1, CWD, and R20, even if a complete convergence of all satellite products is not achieved. [ABSTRACT FROM AUTHOR]

Precipitation in southwestern France was analyzed. Monthly rainfall data from the Global Precipitation Climatology Centre (GPCC) were used to obtain three clusters of average precipitation from May through September for the period 1901–2010. We attempt to understand the role of hailfalls in total precipitation using three different variables related to hail, the number of hail days, hail frequency, and intensity. We examine trends via the Mann–Kendall test and periodicities by wavelet analysis. The results show cluster classification of precipitation to be somewhat consistent with hailpad networks in the study area. In the Pyrenees, there was a non-significant negative trend of precipitation and a substantial increase of hail days and intensity of hail, which were close to the limit of significance. Finally, a wavelet coherence analysis shows a strong influence of the North Atlantic Oscillation (NAO) in the Atlantic region. [ABSTRACT FROM AUTHOR]

During recent decades East Africa (EA) and Southern Africa (SA) have experienced an intensification of hydrological hazards, such as floods and droughts, which have dramatically affected the population, making these areas two of the regions of the African continent most vulnerable to these hazards. Thus, precipitation monitoring and the evaluation of its variability have become fundamentally important actions through the analysis of long-term data records. In particular, satellite-based precipitation products are often used because they counterbalance the sparsity of the rain gauge networks which often characterize these areas. The aim of this work is to compare and contrast the capabilities of three daily satellite-based products in EA and SA from 1983 to 2017. The selected products are two daily rainfall datasets based on high-resolution thermal infrared observations, TAMSAT version 3 and CHIRPS, and a relatively new global product, MSWEP version 2.2, which merges satellite-based, rain gauge and re-analysis precipitation data. The datasets have been directly intercompared, avoiding the traditional rain gauge validation. This is done by means of pairwise comparison statistics at 0.25° spatial resolution and daily time scale to assess rain–detection and quantitative estimate capabilities. Monthly climatology and spatial distribution of seasonality are analyzed as well. The time evolution of the statistical indexes has been evaluated in order to analyze the stability of the rain detection and estimation performances. Considerable agreement among the precipitation products emerged from the analysis, in spite of the differences occurring in specific situations over complex terrain, such as mountainous and coastal regions and deserts. Moreover, the temporal evolution of the statistical indices has demonstrated that the agreement between the products improved over time, with more stable capabilities in identifying precipitating days and estimating daily precipitation starting in the second half of the 1990s. [ABSTRACT FROM AUTHOR]

A gridded precipitation dataset derived from the high-density rain gauge network of the Ebro River Basin Authority is used to evaluate the performance of Integrated Multi-satellitE Retrievals for GPM (IMERG) level-3 estimates. Although aggregated values compare well, several differences are found between climate regions. The research investigates the role of orography and gauge density on IMERG performance. There are important discrepancies over un-instrumented areas in the Pyrenees (R2 = 0.31) but the correlation dramatically increases (R2 > 0.71) when at least one rain gauge is available for calibration, even in complex, high-altitude terrain (>1500 m). IMERG overestimates precipitation at both lower altitudes (<500 m), especially in summer and autumn because of convective activity, and mid-altitudes (600–1200 m) in the northwestern study area, where weather is dominated by the advection of wet maritime air masses. The main conclusion is that IMERG performance strongly depends on altitude and the precipitation regime. IMERG is nonetheless a suitable alternative to gridded gauge-derived only products for hydrologic operations, especially in areas with a sparse rain gauge network. • The performance of IMERG precipitation product in complex terrain areas is evaluated. • Seasonal variability and altitude play a key role in product performance. • IMERG compares well at aggregated level but underestimates precipitation maxima. • Best scores are at mid-elevations and the worst are at low and high elevations. • IMERG is useful in areas where rain gauges are sparse, even in complex regions. [ABSTRACT FROM AUTHOR]

Turbulence and aircraft icing associated with mountain waves are weather phenomena potentially affecting aviation safety. In this paper, these weather phenomena are analysed in the vicinity of the Adolfo Suárez Madrid-Barajas Airport (Spain). Mountain waves are formed in this area due to the proximity of the Guadarrama mountain range. Twenty different weather research and forecasting (WRF) model configurations are evaluated in an initial analysis. This shows the incompetence of some experiments to capture the phenomenon. The two experiments showing the best results are used to simulate thirteen episodes with observed mountain waves. Simulated pseudosatellite images are validated using satellite observations, and an analysis is performed through several skill scores applied to brightness temperature. Few differences are found among the different skill scores. Nevertheless, the Thompson microphysics scheme combined with the Yonsei university PBL scheme shows the best results. The simulations produced by this scheme are used to evaluate the characteristic variables of the mountain wave episodes at windward and leeward and over the mountain. The results show that north-northwest wind directions, moderate wind velocities, and neutral or slightly stable conditions are the main features for the episodes evaluated. In addition, a case study is analysed to evidence the WRF ability to properly detect turbulence and icing associated with mountain waves, even when there is no visual evidence available. [ABSTRACT FROM AUTHOR]

Estimating extreme precipitation events over complex terrain is challenging but crucial for evaluating the performance of climate models for the present climate and expected changes of the climate in the future. New satellites operating in the microwave wavelengths have started to open new opportunities for performing such estimation at adequate temporal and spatial scales and within sensible error limits. This paper illustrates the feasibility and limits of estimating precipitation extremes from satellite data for climatological applications. Using a high-resolution gauge database as ground truth, it was found that global precipitation measurement (GPM) constellation data can provide valuable estimates of extreme precipitation over the southern slopes of the Pyrenees, a region comprising several climates and a very diverse terrain (a challenge for satellite precipitation algorithms). Validation using an object-based quality measure showed reasonable performance, suggesting that GPM estimates can be advantageous reference data for climate model evaluation. [ABSTRACT FROM AUTHOR]

This paper evaluates Integrated Multi-Satellite Retrievals from GPM (IMERG-F) over Europe for the period 2014–2018 in order to evaluate application of the retrievals to hydrology. IMERG-F is compared with a large pan-European precipitation dataset built on rain gauge stations, i.e., the ENSEMBLES OBServation (E-OBS) gridded dataset. Although there is overall agreement in the spatial distribution of mean precipitation (R2 = 0.8), important discrepancies are revealed in mountainous regions, specifically the Alps, Pyrenees, west coast of the British Isles, Scandinavia, the Iberian and Italian peninsulas, and the Adriatic coastline. The results show that the strongest contributors to poor performance are pixels where IMERG-F has no gauges available for adjustment. If rain gauges are available, IMERG-F yields results similar to those of the surface observations, although the performance varies by region. However, even accounting for gauge adjustment, IMERG-F systematically underestimates precipitation in the Alps and Scandinavian mountains. Conversely, IMERG-F overestimates precipitation in the British Isles, Italian Peninsula, Adriatic coastline, and eastern European plains. Additionally, the research shows that gauge adjustment worsens the spatial gradient of precipitation because of the coarse resolution of Global Precipitation Climatology Centre data. [ABSTRACT FROM AUTHOR]

After 5 years in orbit, the Global Precipitation Measurement (GPM) mission has produced enough quality-controlled data to allow the first validation of their precipitation estimates over Spain. High-quality gauge data from the meteorological network of the Spanish Meteorological Agency (AEMET) are used here to validate Integrated Multisatellite Retrievals for GPM (IMERG) level 3 estimates of surface precipitation. While aggregated values compare notably well, some differences are found in specific locations. The research investigates the sources of these discrepancies, which are found to be primarily related to the underestimation of orographic precipitation in the IMERG satellite products, as well as to the number of available gauges in the GPCC gauges used for calibrating IMERG. It is shown that IMERG provides suboptimal performance in poorly instrumented areas but that the estimate improves greatly when at least one rain gauge is available for the calibration process. A main, generally applicable conclusion from this research is that the IMERG satellite-derived estimates of precipitation are more useful (r2 > 0.80) for hydrology than interpolated fields of rain gauge measurements when at least one gauge is available for calibrating the satellite product. If no rain gauges were used, the results are still useful but with decreased mean performance (r2 ≈ 0.65). Such figures, however, are greatly improved if no coastal areas are included in the comparison. Removing them is a minor issue in terms of hydrologic impacts, as most rivers in Spain have their sources far from the coast. [ABSTRACT FROM AUTHOR]

Abstract Aviation safety is a priority that may be compromised by adverse weather conditions. This is the case for poor visibility in the vicinity of airports, which can pose a risk during takeoff and landing. For airports that are prone to fog because of their location, an accurate forecast of poor-visibility episodes is vital. However, the forecasting of low clouds is still a challenge in numerical weather prediction, especially when an airport is near complex terrain for which the use of non-hydrostatic mesoscale models is mandatory. All these factors are present at Tenerife Norte Airport, which is commonly affected by poor visibility from low clouds related to persistent trade winds and moist flows from the Atlantic Ocean. In this paper, several methods for estimating visibility based on mesoscale model outputs are tested. Use of the HARMONIE-AROME model is encouraged because of its excellent performance in the detection of poor-visibility episodes (False Alarm Ratio = 0.34–0.38; Frequency Of Misses = 0.22–0.38, depending on the model version and method used). In addition, the use of satellite application facilities is proposed for the nowcasting of low clouds affecting the airport area. Specifically, we used products that estimate cloud type, cloud top altitude, and integrated water vapor content in the boundary layer. Finally, an application is presented for the monitoring of weather conditions in real time to estimate poor-visibility risk. Highlights • Poor visibility frequently poses a risk to aviation safety at GCXO airport. • Forecasting of these episodes remains a challenge in numerical weather prediction. • Mesoscale models and satellite application facilities are proposed for the task. [ABSTRACT FROM AUTHOR]

Deep convection is a threat to many human activities, with a great impact on aviation safety. On 7 July 2017, a widespread torrential precipitation event (associated with a cut-off low at mid-levels) was registered in the vicinity of Madrid, causing serious flight disruptions. During this type of episode, accurate short-term forecasts are key to minimizing risks to aviation. The aim of this research is to improve early warning systems by obtaining the best WRF model setup. In this paper, the aforementioned event was simulated. Various model configurations were produced using four different physics parameterizations, 3-km and 1-km domain resolutions, and 0.25° and 1° initial condition resolutions. Simulations were validated using data from 17 rain gauge stations. Two validation indices are proposed, accounting for the temporal behaviour of the model. Results show significant differences between microphysics parameterizations. Validation of domain resolution shows that improvement from 3 to 1 km is negligible. Interestingly, the 0.25° resolution for initial conditions produced poor results compared with 1°. This may be linked to a timing error, because precipitation was simulated further east than observed. The use of ensembles generated by combining different WRF model configurations produced reliable precipitation estimates. [ABSTRACT FROM AUTHOR]

The Mediterranean region is a unique area characterized by a large spectrum of atmospheric phenomena, some of which have a high impact on many aspects of human activities, safety and wellbeing. The area is long considered as a hot spot of such atmospheric phenomena deserving multidisciplinary scientific attention. The scientific research that has been carried out on these high impact atmospheric processes that occur in the Mediterranean area is indeed widespread and the available international literature is very extensive. The paper touches initially the temperature and precipitation regimes, followed by a discussion of floods and droughts. The exciting cyclogenetic patterns of explosive cyclones and medicanes are presented in separate sections. The lightning activity and the presence of dust and other pollutants are also presented herein. The atmospheric chemistry of the region which is increasingly becoming of utmost importance for the area under study is distinctly discussed. Attempts to modify the weather (the precipitation, in particular) are outlined too. The effects of climatic change on various atmospheric processes are considered throughout this paper, in addition to a dedicated section on temperature and precipitation. [ABSTRACT FROM AUTHOR]

Wind energy requires accurate forecasts for adequate integration into the electric grid system. In addition, global atmospheric models are not able to simulate local winds in complex terrain, where wind farms are sometimes placed. For this reason, the use of mesoscale models is vital for estimating wind speed at wind turbine hub height. In this regard, the Weather Research and Forecasting (WRF) Model allows a user to apply different initial and boundary conditions as well as physical parameterizations. In this research, a sensitivity analysis of several physical schemes and initial and boundary conditions was performed for the Alaiz mountain range in the northern Iberian Peninsula, where several wind farms are located. Model performance was evaluated under various atmospheric stabilities and wind speeds. For validation purposes, a mast with anemometers installed at 40, 78, 90, and 118 m above ground level was used. The results indicate that performance of the Global Forecast System analysis and European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim) as initial and boundary conditions was similar, although each performed better under certain meteorological conditions. With regard to physical schemes, there is no single combination of parameterizations that performs best during all weather conditions. Nevertheless, some combinations have been identified as inefficient, and therefore their use is discouraged. As a result, the validation of an ensemble prediction system composed of the best 12 deterministic simulations shows the most accurate results, obtaining relative errors in wind speed forecasts that are <15%. [ABSTRACT FROM AUTHOR]

Aircraft icing is one of the most dangerous weather phenomena in aviation security. Therefore, avoiding areas with high probability of icing episodes along arrival and departure routes to airports is strongly recommended. Although such icing is common, forecasting and observation are far from perfect. This paper presents an analysis of an aircraft icing and turbulence event including a commercial flight near the Guadarrama Mountains, during the aircraft approach to the airport. No reference to icing or turbulence was made in the pre-flight meteorological information provided to the pilot, highlighting the need for additional tools to predict such risks. For this reason, the icing episode is simulated by means of the Weather Research and Forecasting (WRF) model and analyzed using images from the Meteosat Second Generation (MSG) satellite, with the aim of providing tools for the detection of icing and turbulence in the airport vicinity. The WRF simulation shows alternating updrafts and downdrafts (> 2 m s − 1 ) on the lee side of the mountain barrier. This is consonant with moderate to strong turbulence experienced by the aircraft on its approach path to the airport and suggests clear air turbulence above the mountain wave cloud top. At the aircraft icing altitude, supercooled liquid water associated with orographic clouds and mountain waves is simulated. Daytime and nighttime MSG images corroborated the simulated mountain waves and associated supercooled liquid water. The results encourage the use of mesoscale models and MSG nowcasting information to minimize aviation risks associated with such meteorological phenomena. [ABSTRACT FROM AUTHOR]

Evaluating satellite ability in capturing sudden natural disasters such as heavy snowstorms is a topic of societal interest. This paper presents a rapid qualitative analysis of an intense snowfall in Madrid using data from the Global Precipitation Measurement (GPM) mission, specifically the GPM IMERG (Integrated Multi-satellitE Retrievals for GPM) Late Precipitation L3 Half Hourly 0.1° × 0.1° V06 estimates of precipitation (IMERG-Late), and Sentinel-2 imagery. The main research question addressed is the consistency of ground observations, model outputs and satellite data, a topic of major interest for an appropriate and timely societal response to severe weather episodes. Indeed, the choice of the 'Late' product over the IMERG 'Final' or other GPM datasets was motivated by the availability of data for near real-time response to the storm. Additionally, the 30-min temporal resolution of the product would in principle allow for a detailed analysis of the dynamic processes involved in the snowstorm. Using several complementary data sources, it is shown that optical remote sensing sensors (Sentinel) add value to existing ground data and that is invaluable for rapid response to severe meteorological events such as Filomena. Regarding the GPM precipitation radar, the sampling of the GPM-core satellite was insufficient to provide the IMERG algorithm with enough quality data to correctly represent the actual sequence of precipitation. Without corrections, the total precipitation differs from observations by a factor of two. The difficulties of retrieving precipitation with radiometers over snow-covered surfaces was a major factor for the mismatch. Thus, the calibrated precipitation product did not fully capture the historic storm, and neither did the IR-based element of the IMERG-Late product, which is a neural network merging of microwave and infrared data. It follows that increased temporal resolution of spaceborne microwave sensors and improved retrieval of precipitation from radiometers are critical in order to provide a complete account of these sorts of extreme, significant, short-duration cases. Otherwise, the high-quality, radar and radiometer data feeding the high temporal resolution algorithms simply slip through the grasp of the ascending and descending orbits, leaving little quality data to be interpolated into successive overpasses. [ABSTRACT FROM AUTHOR]