977 resultados para temporal sampling


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The high computational cost of calculating the radiative heating rates in numerical weather prediction (NWP) and climate models requires that calculations are made infrequently, leading to poor sampling of the fast-changing cloud field and a poor representation of the feedback that would occur. This paper presents two related schemes for improving the temporal sampling of the cloud field. Firstly, the ‘split time-stepping’ scheme takes advantage of the independent nature of the monochromatic calculations of the ‘correlated-k’ method to split the calculation into gaseous absorption terms that are highly dependent on changes in cloud (the optically thin terms) and those that are not (optically thick). The small number of optically thin terms can then be calculated more often to capture changes in the grey absorption and scattering associated with cloud droplets and ice crystals. Secondly, the ‘incremental time-stepping’ scheme uses a simple radiative transfer calculation using only one or two monochromatic calculations representing the optically thin part of the atmospheric spectrum. These are found to be sufficient to represent the heating rate increments caused by changes in the cloud field, which can then be added to the last full calculation of the radiation code. We test these schemes in an operational forecast model configuration and find a significant improvement is achieved, for a small computational cost, over the current scheme employed at the Met Office. The ‘incremental time-stepping’ scheme is recommended for operational use, along with a new scheme to correct the surface fluxes for the change in solar zenith angle between radiation calculations.

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Within-site variability in species detectability is a problem common to many biodiversity assessments and can strongly bias the results. Such variability can be caused by many factors, including simple counting inaccuracies, which can be solved by increasing sample size, or by temporal changes in species behavior, meaning that the way the temporal sampling protocol is designed is also very important. Here we use the example of mist-netted tropical birds to determine how design decisions in the temporal sampling protocol can alter the data collected and how these changes might affect the detection of ecological patterns, such as the species-area relationship (SAR). Using data from almost 3400 birds captured from 21,000 net-hours at 31 sites in the Brazilian Atlantic Forest, we found that the magnitude of ecological trends remained fairly stable, but the probability of detecting statistically significant ecological patterns varied depending on sampling effort, time of day and season in which sampling was conducted. For example, more species were detected in the wet season, but the SAR was strongest in the dry season. We found that the temporal distribution of sampling effort was more important than its total amount, discovering that similar ecological results could have been obtained with one-third of the total effort, as long as each site had been equally sampled over 2 yr. We discuss that projects with the same sampling effort and spatial design, but with different temporal sampling protocol are likely to report different ecological patterns, which may ultimately lead to inappropriate conservation strategies.

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Monthly zonal mean climatologies of atmospheric measurements from satellite instruments can have biases due to the nonuniform sampling of the atmosphere by the instruments. We characterize potential sampling biases in stratospheric trace gas climatologies of the Stratospheric Processes and Their Role in Climate (SPARC) Data Initiative using chemical fields from a chemistry climate model simulation and sampling patterns from 16 satellite-borne instruments. The exercise is performed for the long-lived stratospheric trace gases O3 and H2O. Monthly sampling biases for O3 exceed 10% for many instruments in the high-latitude stratosphere and in the upper troposphere/lower stratosphere, while annual mean sampling biases reach values of up to 20% in the same regions for some instruments. Sampling biases for H2O are generally smaller than for O3, although still notable in the upper troposphere/lower stratosphere and Southern Hemisphere high latitudes. The most important mechanism leading to monthly sampling bias is nonuniform temporal sampling, i.e., the fact that for many instruments, monthly means are produced from measurements which span less than the full month in question. Similarly, annual mean sampling biases are well explained by nonuniformity in the month-to-month sampling by different instruments. Nonuniform sampling in latitude and longitude are shown to also lead to nonnegligible sampling biases, which are most relevant for climatologies which are otherwise free of biases due to nonuniform temporal sampling.

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We analyzed the effect of periodic drying in the Florida Everglades on spatiotemporal population genetic structure of eastern mosquitofish (Gambusia holbrooki). Severe periodic drying events force individuals from disparate sources to mix in dry season relatively deep-water refuges. In 1996 (a wet year) and 1999 (a dry year), we sampled mosquitofish at 20 dry-season refuges distributed in 3 water management regions and characterized genetic variation for 10 allozyme and 3 microsatellite loci. In 1996, most of the ecosystem did not dry, whereas in 1999, many of our sampling locations were isolated by expanses of dried marsh surface. In 1996, most spatial genetic variation was attributed to heterogeneity within regions. In 1999, spatial genetic variation within regions was not significant. In both years, a small but significant amount of variation (less than 1% of the total variation) was partitioned among regions. Variance was consistently greater than zero among long-hydroperiod sites within a region, but not among short-hydroperiod sites within a region, where hydroperiod was measured as time since last marsh surface dry-down forcing fishes into local refuges. In 1996, all sites were in Hardy–Weinberg equilibrium. In 1999, we observed fewer heterozygotes than expected for most loci and sites suggesting a Wahlund effect arising from fish leaving areas that dried and mixing in deep-water refuges.

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Oscillatory entrainment to the speech signal is important for language processing, but has not yet been studied in developmental disorders of language. Developmental dyslexia, a difficulty in acquiring efficient reading skills linked to difficulties with phonology (the sound structure of language), has been associated with behavioural entrainment deficits. It has been proposed that the phonological ‘deficit’ that characterises dyslexia across languages is related to impaired auditory entrainment to speech at lower frequencies via neuroelectric oscillations (<10 Hz, ‘temporal sampling theory’). Impaired entrainment to temporal modulations at lower frequencies would affect the recovery of the prosodic and syllabic structure of speech. Here we investigated event-related oscillatory EEG activity and contingent negative variation (CNV) to auditory rhythmic tone streams delivered at frequencies within the delta band (2 Hz, 1.5 Hz), relevant to sampling stressed syllables in speech. Given prior behavioural entrainment findings at these rates, we predicted functionally atypical entrainment of delta oscillations in dyslexia. Participants performed a rhythmic expectancy task, detecting occasional white noise targets interspersed with tones occurring regularly at rates of 2 Hz or 1.5 Hz. Both groups showed significant entrainment of delta oscillations to the rhythmic stimulus stream, however the strength of inter-trial delta phase coherence (ITC, ‘phase locking’) and the CNV were both significantly weaker in dyslexics, suggestive of weaker entrainment and less preparatory brain activity. Both ITC strength and CNV amplitude were significantly related to individual differences in language processing and reading. Additionally, the instantaneous phase of prestimulus delta oscillation predicted behavioural responding (response time) for control participants only.

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Up to now, high-resolution mapping of surface water extent from satellites has only been available for a few regions, over limited time periods. The extension of the temporal and spatial coverage was difficult, due to the limitation of the remote sensing technique e.g., the interaction of the radiation with vegetation or cloud for visible observations or the temporal sampling with the synthetic aperture radar (SAR)]. The advantages and the limitations of the various satellite techniques are reviewed. The need to have a global and consistent estimate of the water surfaces over long time periods triggered the development of a multi-satellite methodology to obtain consistent surface water all over the globe, regardless of the environments. The Global Inundation Extent from Multi-satellites (GIEMS) combines the complementary strengths of satellite observations from the visible to the microwave, to produce a low-resolution monthly dataset () of surface water extent and dynamics. Downscaling algorithms are now developed and applied to GIEMS, using high-spatial-resolution information from visible, near-infrared, and synthetic aperture radar (SAR) satellite images, or from digital elevation models. Preliminary products are available down to 500-m spatial resolution. This work bridges the gaps and prepares for the future NASA/CNES Surface Water Ocean Topography (SWOT) mission to be launched in 2020. SWOT will delineate surface water extent estimates and their water storage with an unprecedented spatial resolution and accuracy, thanks to a SAR in an interferometry mode. When available, the SWOT data will be adopted to downscale GIEMS, to produce a long time series of water surfaces at global scale, consistent with the SWOT observations.

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In recent years there has been a growing interest amongst the speech research community into the use of spectral estimators which circumvent the traditional quasi-stationary assumption and provide greater time-frequency (t-f) resolution than conventional spectral estimators, such as the short time Fourier power spectrum (STFPS). One distribution in particular, the Wigner distribution (WD), has attracted considerable interest. However, experimental studies have indicated that, despite its improved t-f resolution, employing the WD as the front end of speech recognition system actually reduces recognition performance; only by explicitly re-introducing t-f smoothing into the WD are recognition rates improved. In this paper we provide an explanation for these findings. By treating the spectral estimation problem as one of optimization of a bias variance trade off, we show why additional t-f smoothing improves recognition rates, despite reducing the t-f resolution of the spectral estimator. A practical adaptive smoothing algorithm is presented, whicy attempts to match the degree of smoothing introduced into the WD with the time varying quasi-stationary regions within the speech waveform. The recognition performance of the resulting adaptively smoothed estimator is found to be comparable to that of conventional filterbank estimators, yet the average temporal sampling rate of the resulting spectral vectors is reduced by around a factor of 10. © 1992.

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An evaluation of the genetic diversity within Fasciola hepatica (liver fluke) may provide an insight into its potential to respond to environmental changes, such as anthelmintic use or climate change. In this study, we determined the mitochondrial DNA haplotypes of >400 flukes from 29 individual cattle, from 2 farms in the Netherlands, as an exemplar of fasciolosis in a European context. Analysis of this dataset has provided us with a measure of the genetic variation within infrapopulations (individual hosts) and the diversity between infrapopulations within a herd of cattle. Temporal sampling from one farm allowed for the measurement of the stability of genetic variation at a single location, whilst the comparison between the two farms provided information on the variation in relation to distance and previous anthelmintic regimes. We showed that the liver fluke population in this region is predominantly linked to 2 distinct clades. Individual infrapopulations contain a leptokurtic distribution of genetically diverse flukes. The haplotypes present on a farm have been shown to change significantly over a relatively short time-period.

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A detailed understanding of flow and contaminant transfer along each of the key hydrological pathways within a catchment is critical for designing and implementing cost effective Programmes of Measures under the Water
Framework Directive.
The Contaminant Movement along Pathways Project (’The Pathways Project’) is an Irish, EPA STRIVE funded, large multi-disciplinary project which is focussed on understanding and modelling flow and attenuation along each of these pathways for the purposes of developing a catchment management tool. The tool will be used by EPA and RBD catchment managers to assess and manage the impacts of diffuse contamination on stream aquatic ecology. Four main contaminants of interest — nitrogen, phosphorus, sediment and pathogens — are being
investigated in four instrumented test catchments. In addition to the usual hydrological and water chemistry/quality parameters typically captured in catchment studies, field measurements at the test catchments include ecological
sampling, sediment dynamics, soil moisture dynamics, and groundwater levels and chemistry/quality, both during and between significant rainfall events. Spatial and temporal sampling of waters directly from the pathways of
interest is also being carried out.
Sixty-five percent of Ireland is underlain by poorly productive aquifers. In these hydrogeological settings, the main pathways delivering flow to streams are overland flow, interflow and shallow bedrock flow. Little is
known about the interflow pathway and its relative importance in delivery of flow and contaminants to the streams. Interflow can occur in both the topsoil and subsoil, and may include unsaturated matrix flow, bypass or macropore
flow, saturated flow in locally perched water tables and artificial field drainage.
Results to date from the test catchment experiments show that artificial field drains play an important role in the delivery of interflow to these streams, during and between rainfall events when antecedent conditions are
favourable. Hydrochemical mixing models, using silica and SAC254 (the absorbance of UV light at a wavelength of 254 nm which is a proxy for dissolved organic matter) as tracers, show that drain flow is an important end
member contributing to the stream and that proportionally, its contribution is relatively high.
Results from the study also demonstrate that waters originating from one pathway often mix with the waters from another, and are subsequently delivered to the stream at rates, and with chemical/quality characteristics,
that are not typical of either pathway. For example, pre-event shallow groundwater not far from the catchment divide comes up to the surface as rejected recharge during rainfall events and is rapidly delivered to the stream
via overland flow and/or artificial land drainage, bringing with it higher nitrate than would often be expected from a quickflow pathway contribution. This is contrary to the assumption often made in catchment studies that the
deeper hydrological pathways have slower response times in stream hydrographs during a rainfall event, and it emphasizes that it is critical to have a strong three-dimensional conceptual model as the basis for the interpretation
of catchment data.

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The Geostationary Earth Radiation Budget instrument on Meteosat-8, located over Africa, provides unprecedented temporal sampling (~17 minutes) of the broadband emitted thermal and reflected solar radiances. We analyse the diurnal cycle of the outgoing longwave radiation (OLR) fluxes derived from the thermal radiances for July 2006. Principal component (PC) analysis separates the signals of the surface temperature response to solar heating and of the development of convective clouds. The first two PCs explain most of the OLR variations: PC1 (surface heating) explains 82.3% of the total variance and PC2 (cloud development) explains 12.8% of the variance. Convection is initiated preferentially over mountainous regions and the cloud then advects downstream in the ambient flow. Diurnal variations are much weaker over the oceans, but a coherent signal over the Gulf of Guinea suggests that the cloudiness is modulated by the diurnally varying contrast between the Gulf and the adjacent land mass.

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This study begins to redress our lack of knowledge of the interactions between colonial hosts and their parasites by focusing on a novel host-parasite system. Investigations of freshwater bryozoan populations revealed that infection by myxozoan parasites is widespread. Covert infections were detected in all 5 populations studied and were often at high prevalence while overt infections were observed in only 1. Infections were persistent in populations subject to temporal sampling. Negative effects of infection were identified but virulence was low. Infection did not induce mortality in the environmental conditions studied. However, the production of statoblasts (dormant propagules) was greatly reduced in bryozoans with overt infections in comparison to uninfected bryozoans. Overtly-infected bryozoans also grew more slowly and had low fission rates relative to colonies lacking overt infection. Bryozoans with covert infections were smaller than uninfected bryozoans. High levels of vertical transmission were achieved through colony fission and the infection of statoblasts. Increased fission rates may be a strategy for hosts to escape from parasites but the parasite can also exploit the fragmentation of colonial hosts to gain vertical transmission and dispersal. Our study provides evidence that opportunities and constraints for host-parasite co-evolution can be highly dependent on organismal body plans and that low virulence may be associated with exploitation of colonial hosts by endoparasites.

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A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and nonconvective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud-resolving model simulations, and from the Bayesian formulation itself. Synthetic rain-rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in TMI instantaneous rain-rate estimates at 0.5°-resolution range from approximately 50% at 1 mm h−1 to 20% at 14 mm h−1. Errors in collocated spaceborne radar rain-rate estimates are roughly 50%–80% of the TMI errors at this resolution. The estimated algorithm random error in TMI rain rates at monthly, 2.5° resolution is relatively small (less than 6% at 5 mm day−1) in comparison with the random error resulting from infrequent satellite temporal sampling (8%–35% at the same rain rate). Percentage errors resulting from sampling decrease with increasing rain rate, and sampling errors in latent heating rates follow the same trend. Averaging over 3 months reduces sampling errors in rain rates to 6%–15% at 5 mm day−1, with proportionate reductions in latent heating sampling errors.

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High density spatial and temporal sampling of EEG data enhances the quality of results of electrophysiological experiments. Because EEG sources typically produce widespread electric fields (see Chapter 3) and operate at frequencies well below the sampling rate, increasing the number of electrodes and time samples will not necessarily increase the number of observed processes, but mainly increase the accuracy of the representation of these processes. This is namely the case when inverse solutions are computed. As a consequence, increasing the sampling in space and time increases the redundancy of the data (in space, because electrodes are correlated due to volume conduction, and time, because neighboring time points are correlated), while the degrees of freedom of the data change only little. This has to be taken into account when statistical inferences are to be made from the data. However, in many ERP studies, the intrinsic correlation structure of the data has been disregarded. Often, some electrodes or groups of electrodes are a priori selected as the analysis entity and considered as repeated (within subject) measures that are analyzed using standard univariate statistics. The increased spatial resolution obtained with more electrodes is thus poorly represented by the resulting statistics. In addition, the assumptions made (e.g. in terms of what constitutes a repeated measure) are not supported by what we know about the properties of EEG data. From the point of view of physics (see Chapter 3), the natural “atomic” analysis entity of EEG and ERP data is the scalp electric field

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Functional neuroimaging studies in human subjects using positron emission tomography or functional magnetic resonance imaging (fMRI) are typically conducted by collecting data over extended time periods that contain many similar trials of a task. Here methods for acquiring fMRI data from single trials of a cognitive task are reported. In experiment one, whole brain fMRI was used to reliably detect single-trial responses in a prefrontal region within single subjects. In experiment two, higher temporal sampling of a more limited spatial field was used to measure temporal offsets between regions. Activation maps produced solely from the single-trial data were comparable to those produced from blocked runs. These findings suggest that single-trial paradigms will be able to exploit the high temporal resolution of fMRI. Such paradigms will provide experimental flexibility and time-resolved data for individual brain regions on a trial-by-trial basis.

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Senior thesis written for Oceanography 445