982 resultados para weather variables


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During the summer and autumn of 2015, El Niño conditions in the east and central Pacific strengthened, disrupting weather patterns throughout the tropics and into the mid-latitudes. For example, rainfall during the summer’s Indian monsoon was approximately 15% below normal. The continued strong El Niño conditions have the potential to trigger damaging impacts (e.g., droughts, famines, floods), particularly in less-developed tropical countries, which would require a swift and effective humanitarian response to mitigate damage to life and property (e.g., health, migration, infrastructure). This analysis uses key climatic variables (temperature, soil moisture and precipitation) as measures to monitor the ongoing risk of these potentially damaging impacts. The previous 2015-2016 El Niño Impact Analysis was based on observations over the past 35 years and produced Impact Tables showing the likelihood and severity of the impacts on temperature and rainfall by season. The current report is an extension of this work, providing information from observations and seasonal forecast models to give a more detailed outlook of the potential near-term impacts of the current El Niño conditions by region. This information has been added to the Impact Tables in the form of an ‘Observations and Outlook’ row. This consists of observational information for the past seasons of JJA 2015, SON 2015 and DJF 2015/2016, a detailed monthly outlook from 5 modeling centres for Mar 2016 and then longer-term seasonal forecast information from 2 modeling centres for the future seasons of AM 2016 and JJA 2016. The seasonal outlook information is an indication of the average likely conditions for that coming month (or season) and region and is not a definite prediction of weather impacts. This report has been produced by University of Reading for Evidence on Demand with the assistance of the UK Department for International Development (DFID) contracted through the Climate, Environment, Infrastructure and Livelihoods Professional Evidence and Applied Knowledge Services (CEIL PEAKS) programme, jointly managed by DAI (which incorporates HTSPE Limited) and IMC Worldwide Limited.

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Remotely sensed rainfall is increasingly being used to manage climate-related risk in gauge sparse regions. Applications based on such data must make maximal use of the skill of the methodology in order to avoid doing harm by providing misleading information. This is especially challenging in regions, such as Africa, which lack gauge data for validation. In this study, we show how calibrated ensembles of equally likely rainfall can be used to infer uncertainty in remotely sensed rainfall estimates, and subsequently in assessment of drought. We illustrate the methodology through a case study of weather index insurance (WII) in Zambia. Unlike traditional insurance, which compensates proven agricultural losses, WII pays out in the event that a weather index is breached. As remotely sensed rainfall is used to extend WII schemes to large numbers of farmers, it is crucial to ensure that the indices being insured are skillful representations of local environmental conditions. In our study we drive a land surface model with rainfall ensembles, in order to demonstrate how aggregation of rainfall estimates in space and time results in a clearer link with soil moisture, and hence a truer representation of agricultural drought. Although our study focuses on agricultural insurance, the methodological principles for application design are widely applicable in Africa and elsewhere.

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Drought events are projected to increase in frequency and magnitude, which may alter the composition of ecological communities. Using a functional community metric that describes abundance, life history traits and conservation status, based upon Grime’s CSR (Competitive-Stress tolerant-Ruderal)¬ scheme, we investigated how British butterfly communities changed during an extreme drought in 1995. Throughout Britain, the total abundance of these insects had a significant tendency to increase, accompanied by substantial changes in community composition, particularly in more northerly, wetter sites. Communities tended to shift away from specialist, vulnerable species, and towards generalist, widespread species and, in the year following, communities had yet to return to equilibrium. Importantly, heterogeneity in surrounding landscapes mediated community responses to the drought event. Contrary to expectation, however, community shifts were more extreme in areas of greater topographic diversity, whilst land-cover diversity buffered community changes and limited declines in vulnerable specialist butterflies.

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Objective: To estimate the prevalence of inadequate nutrient intake among adolescents and the association between socio-economic variables and nutritional status. Design: Cross-sectional study with a population-based sample. Settings: The usual nutrient intake distribution was estimated using the Iowa State University method. The Estimated Average Requirement cut-off point method was used to determine the proportion of adolescents with inadequate intake for each nutrient, according to sex, income, parental educational level and nutritional status. Subjects: Twenty-four-hour dietary recalls were applied in 525 male and female Brazilian adolescents aged 14-18 years. Results: The highest prevalence of inadequate nutrient intake was observed for vitamin E (99% in both sexes). For male and female adolescents, the prevalence of inadequate intake was: Mg, 89% and 84%; vitamin A, 78% and 71 %; vitamin C, 79% and 53%; and vitamin B(6), 21% and 33%, respectively. The prevalence of inadequate intake for niacin, thiamin, riboflavin, Se, Cu and vitamin B(12) was <15 %. Individuals in the lower income and lower parental educational level strata had the highest risk of having inadequate intake for P, riboflavin and vitamins A, B(6) and B(12). Compared with non-overweight individuals, overweight individuals had a higher risk of inadequate intake for Mg, vitamin A, P, thiamin and riboflavin. Conclusions: The present study found a high prevalence of inadequate intake of nutrients that are recognised as being protective against chronic diseases. Adolescents in the lower income and lower parental educational level strata were less likely to have their nutrient intake requirements met.

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Background: Acute respiratory distress syndrome (ARDS) is a frequent respiratory disturbance in preterm newborns. Preceding investigations evaluated chronic physiotherapy effects on newborns with different lung diseases; however, no study analyzed acute physiotherapy treatment on premature newborns with ARDS. In this study we aimed to evaluate the acute effects of chest and motor physiotherapy treatment on hemodynamic variables in preterm newborns with ARDS. Methods: We evaluated heart rate (HR), respiratory rate (RR), systolic (SAP), mean (MAP) and diastolic arterial pressure (DAP), temperature and oxygen saturation (SO(2)%) in 44 newborns with ARDS. We compared all variables between six periods in one day: before first physiotherapy treatment vs. after first physiotherapy treatment vs. before second physiotherapy treatment vs. after second physiotherapy treatment vs. before third physiotherapy treatment vs. after third physiotherapy treatment. Variables were measured 2 minutes before and 5 minutes after each physiotherapy session. We applied Anova one way followed by post hoc Bonferroni test. Results: HR (147.5 +/- 9.5 bpm vs. 137.7 +/- 9.3 bpm; p<0.001), RR (45.5 +/- 8.7cpm vs. 41.5 +/- 6.7 cpm; p=0.001), SAP (70.3 +/- 10.4 mmHg vs. 60.1 +/- 7.1 mmHg; p=0.001) and MAP (55.7 +/- 10 mmHg vs. 46 +/- 6.6 mmHg; p=0.001) were significantly reduced after the third physiotherapy treatment compared to before the first session. There were no significant changes regarding temperature, DAP and SO(2) %. Conclusion: Chest and motor physiotherapy acutely improves HR, RR, SAP, MAP and SO(2) % in newborns with ARDS.

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Weather conditions in critical periods of the vegetative crop development influence crop productivity, thus being a basic parameter for crop forecast. Reliable extended period weather forecasts may contribute to improve the estimation of agricultural productivity. The production of soybean plays an important role in the Brazilian economy, because this country is ranked among the largest producers of soybeans in the world. This culture can be significantly affected by water conditions, depending on the intensity of water deficit. This work explores the role of extended period weather forecasts for estimating soybean productivity in the southern part of Brazil, Passo Fundo, and Londrina (State of Rio Grande do Sul and Parana, respectively) in the 2005/2006 harvest. The goal was to investigate the possible contribution of precipitation forecasts as a substitute for the use of climatological data on crop forecasts. The results suggest that the use of meteorological forecasts generate more reliable productivity estimates during the growth period than those generated only through climatological information.

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We have developed a spectrum synthesis method for modeling the ultraviolet (UV) emission from the accretion disk from cataclysmic variables (CVs). The disk is separated into concentric rings, with an internal structure from the Wade & Hubeny disk-atmosphere models. For each ring, a wind atmosphere is calculated in the comoving frame with a vertical velocity structure obtained from a solution of the Euler equation. Using simple assumptions, regarding rotation and the wind streamlines, these one-dimensional models are combined into a single 2.5-dimensional model for which we compute synthetic spectra. We find that the resulting line and continuum behavior as a function of the orbital inclination is consistent with the observations, and verify that the accretion rate affects the wind temperature, leading to corresponding trends in the intensity of UV lines. In general, we also find that the primary mass has a strong effect on the P Cygni absorption profiles, the synthetic emission line profiles are strongly sensitive to the wind temperature structure, and an increase in the mass-loss rate enhances the resonance line intensities. Synthetic spectra were compared with UV data for two high orbital inclination nova-like CVs-RW Tri and V347 Pup. We needed to include disk regions with arbitrary enhanced mass loss to reproduce reasonably well widths and line profiles. This fact and a lack of flux in some high ionization lines may be the signature of the presence of density-enhanced regions in the wind, or alternatively, may result from inadequacies in some of our simplifying assumptions.

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Both continuum and emission line flickering are phenomena directly associated with the mass-accretion process. In this work we simulated accretion-disk Doppler maps, including the effects of winds and flickering flares. Synthetic flickering Doppler maps were calculated and the effect of the flickering parameters on the maps was explored. Jets and winds occur in many astrophysical objects where accretion disks are present. Jets are generally absent among the cataclysmic variables (CVs), but there is evidence of mass loss by wind in many objects. CVs are ideal objects to study accretion disks, and consequently to study the wind associated with these disks. We also present simulations of accretion disks, including the presence of a wind with orbital phase resolution. Synthetic Ha line profiles in the optical region were obtained and their corresponding Doppler maps were calculated. The effect of the wind simulation parameters on the wind line profiles was also explored. From this study we verified that optically thick lines and/or emission by diffuse material into the primary Roche lobe are necessary to generate single peaked line profiles, often seen in CVs. The future accounting of these effects is suggested for interpreting Doppler tomography reconstructions.

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We describe the public ESO near-IR variability survey (VVV) scanning the Milky Way bulge and an adjacent section of the mid-plane where star formation activity is high. The survey will take 1929 h of observations with the 4-m VISTA telescope during 5 years (2010-2014), covering similar to 10(9) point sources across an area of 520 deg(2), including 33 known globular clusters and similar to 350 open clusters. The final product will be a deep near-IR atlas in five passbands (0.9-2.5 mu m) and a catalogue of more than 106 variable point sources. Unlike single-epoch surveys that, in most cases, only produce 2-D maps, the VVV variable star survey will enable the construction of a 3-D map of the surveyed region using well-understood distance indicators such as RR Lyrae stars, and Cepheids. It will yield important information on the ages of the populations. The observations will be combined with data from MACHO, OGLE, EROS, VST, Spitzer, HST, Chandra, INTEGRAL, WISE, Fermi LAT, XMM-Newton, GAIA and ALMA for a complete understanding of the variable sources in the inner Milky Way. This public survey will provide data available to the whole community and therefore will enable further studies of the history of the Milky Way, its globular cluster evolution, and the population census of the Galactic Bulge and center, as well as the investigations of the star forming regions in the disk. The combined variable star catalogues will have important implications for theoretical investigations of pulsation properties of stars. (C) 2009 Elsevier B.V. All rights reserved.

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Sampling owls in a reliable and standardized way is not easy given their nocturnal habits. Playback is a widely employed technique to survey owls. We assessed the influence of wind speed, temperature, air humidity, and moon phase on the response rate of the Tropical Screech Owl Megascops choliba and the Burrowing Owl Athene cunicularia in southeast Brazil. Tropical Screech Owl occurs in scrubland and wooded habitats, whereas the Burrowing Owl inhabits open grasslands to grassland savannah. Sixteen survey points were systematically distributed in four different landscape types, ranging from open grassland to woodland savannah. Field work was conducted in 2004 from June to December, the reproductive season of the two owl species. Our study design consisted of eight field expeditions of five nights each; four expeditions occurred under full moon and four under new moon conditions. At each survey station, we performed a broadcast/listening sequence involving several calls and vocalizations from each species, starting with Tropical Screech Owl (the smaller species). From 112 sample periods for each species within their respective preferred habitats, we obtained 54 responses from Tropical Screech Owl (48% response rate) and 30 responses (27% response rate) from Burrowing Owl. We found that the response rate of Tropical Screech Owl increased under conditions of higher temperature and air humidity, while the response rate of Burrowing Owl was higher during full moon nights.

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Dystrophin is a protein found at the plasmatic membrane in muscle and postsynaptic membrane of some neurons, where it plays an important role on synaptic transmission and plasticity. Its absence is associated with Duchenne`s muscular dystrophy (DMD), in which cognitive impairment is found. Oxidative stress appears to be involved in the physiopathology of DMD and its cognitive dysfunction. In this regard, the present study investigated oxidative parameters (lipid and protein peroxidation) and antioxidant enzymes activities (superoxide dismutase and catalase) in prefrontal cortex, cerebellum, hippocampus, striatum and cortex tissues from male dystrophic mdx and normal C57BL10 mice. We observed (I) reduced lipid peroxidation in striatum and protein peroxidation in cerebellum and prefrontal cortex; (2) increased superoxide dismutase activity in cerebellum, prefrontal cortex, hippocampus and striatum: and (3) reduced catalase activity in striatum. It seems by our results, that the superoxide dismutase antioxidant mechanism is playing a protective role against lipid and protein peroxidation in mdx mouse brain. (C) 2009 Elsevier Ltd. All rights reserved.

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Considering the Wald, score, and likelihood ratio asymptotic test statistics, we analyze a multivariate null intercept errors-in-variables regression model, where the explanatory and the response variables are subject to measurement errors, and a possible structure of dependency between the measurements taken within the same individual are incorporated, representing a longitudinal structure. This model was proposed by Aoki et al. (2003b) and analyzed under the bayesian approach. In this article, considering the classical approach, we analyze asymptotic test statistics and present a simulation study to compare the behavior of the three test statistics for different sample sizes, parameter values and nominal levels of the test. Also, closed form expressions for the score function and the Fisher information matrix are presented. We consider two real numerical illustrations, the odontological data set from Hadgu and Koch (1999), and a quality control data set.

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We consider climate networks constructed from observed and model simulated fields of three climate variables and investigate their community structure. We find that for all fields the number of effective communities is rather small (four to five). We are able to trace the origin of these communities to certain dynamical properties of climate. Our results suggest that the complete complexity of the climate system condenses beyond the `weather` time scales into a small number of low-dimensional interacting components and provide clues as to the nature of the climate subsystems underlying these components.

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In this paper we study the accumulated claim in some fixed time period, skipping the classical assumption of mutual independence between the variables involved. Two basic models are considered: Model I assumes that any pair of claims are equally correlated which means that the corresponding square-integrable sequence is exchangeable one. Model 2 states that the correlations between the adjacent claims are the same. Recurrence and explicit expressions for the joint probability generating function are derived and the impact of the dependence parameter (correlation coefficient) in both models is examined. The Markov binomial distribution is obtained as a particular case under assumptions of Model 2. (C) 2007 Elsevier B.V. All rights reserved.

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This paper develops a bias correction scheme for a multivariate heteroskedastic errors-in-variables model. The applicability of this model is justified in areas such as astrophysics, epidemiology and analytical chemistry, where the variables are subject to measurement errors and the variances vary with the observations. We conduct Monte Carlo simulations to investigate the performance of the corrected estimators. The numerical results show that the bias correction scheme yields nearly unbiased estimates. We also give an application to a real data set.