1,721,723 research outputs found
Geoboletim: Folha informativa do Centro de Geofísica de Évora
Full text linkFolha informativa do Centro de Geofísica de Évor
Popular Culture and Mass Media in Latin America: Some reflections on the work of Jésus Martín-Barbero and Néstor García Canclini
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Surface forcing of the North Atlantic: accuracy and variability
Full text linkA new methodology to estimate the turbulent air – sea heat and moisture fluxes andtheir uncertainty is developed and assessed using Voluntary Observing Ship (VOS)observations. Whilst important drivers of the global oceanic and atmospheric circulationthese fluxes remain poorly quantified, both in terms of mean value and uncertainty. Thenew methodology addresses both of these issues and is extensible to other data sources.The individual observations are first bias and height adjusted to remove systematicerrors and the impact of changing observing heights. They are then characterised interms of random errors using a semi-variogram analysis and a range of variogrammodels. The data quality and sampling are then taken into account using optimalinterpolation (OI) to grid the observations, producing daily mean fields and uncertaintyestimates. These are then used to estimate the fluxes and flux uncertainty on both dailyand monthly time scales.Comparisons of the mean fields and fluxes to the original input data and toindependent buoy observations show the fields not to be significantly biased. Theadjustments applied before gridding and flux calculation are also shown to improve theagreement with the buoy observations. The uncertainty estimates are assessed using aseries of cross validation experiments and 3-way error analyses to make alternativeestimates of the uncertainty. These alternative estimates are shown to be of the sameorder of magnitude as the OI uncertainty estimates and generally to be within 10 – 20%of the OI estimate. Whilst all three estimates are similar there are some systematicdifferences. The OI uncertainty estimates tend to be lower (higher) than the alternativeestimates in high (low) variability regions.The representation of the variability in the new dataset is examined and shown to beimproved compared to previous VOS based datasets. The adjustments are shown tohave little impact on the temporal trends in temperature and humidity whilst reducingthe wind speed and sensible and latent heat flux trends. These reduced trends arethought to be more realistic. The wind speed trend after adjustment is more similar tothe trends reported in previous studies using reanalysis model output. However, thereare still some differences in the trends, with the VOS based estimates larger, leading touncertainty in trend estimates. The trends in the adjusted latent and sensible heat fluxestimates are similar to those seen in other flux datasets but when compared to changesin the upper ocean heat content may still be too large. This may be due to theoverestimate of the wind speed trend. Overall the uncertainty in the wind speed trendgives the largest uncertainty in the flux trends.Finally, the advances made in developing the new methodology are summarised andthe potential uses of the new dataset identified. Future work and improvements are thensuggested
A new air-sea interaction gridded dataset from ICOADS with uncertainty estimates.
No full textThe exchange, or flux, of heat between the oceans and atmosphere is an important driver of the global oceanic and atmospheric circulations but remains poorly quantified. Direct measurement of heat flux remains a research activity and so global heat flux datasets are generated using observations of winds, air and sea temperatures and humidity as input to heat flux parameterisations known as "bulk formulae". We remain dependent on the observations from merchant ships in the Voluntary Observing Ships (VOS) program which are archived in the International Comprehensive Ocean-Atmosphere Dataset (ICOADS): measurements from buoys are sparse and satellites cannot accurately recover all the variables required for heat flux calculation. Careful analysis of VOS data is necessary to produce gridded datasets of meteorological variables and fluxes with the accuracy required for climate research. Past in situ flux datasets have averaged observations on monthly timescales in order to reduce random uncertainty. It has therefore been hard to understand the contributions to observed variability from measurement errors, poor sampling or natural variability. The new dataset, which covers the period 1973 to 2006, avoids this problem by first constructing daily mean fields using optimal interpolation. This allows each component of variability to be handled correctly and, for the first time, uncertainty estimates to be produced. New bias adjustments have also been developed and applied. The new dataset is described and a preliminary comparison with flux estimates from moored buoys, satellites and atmospheric reanalysis models is presented.<br/
Air–Sea fluxes from ICOADS: the construction of a new gridded dataset with uncertainty estimates
No full textThe methods used to calculate a new in situ global dataset of air–sea exchanges, called the NOCS Flux Dataset v2.0, are described. The fluxes have been derived from in situ weather reports from Voluntary Observing Ships (VOS) covering the period 1973–2006. The reports have been adjusted for known biases and residual uncertainties estimated. The dataset is constructed using Optimal Interpolation (OI) using new estimates of random uncertainty in the observations. Daily fields have been calculated on a 1° latitude by 1° longitude grid, each grid box and time step have an associated uncertainty estimate. Monthly fields have been calculated from simple averages of the daily fields and monthly uncertainty estimates from the daily uncertainties, using estimates of the autocorrelation between the daily uncertainty estimates. The uncertainties due to the choice of flux parameterisation have not been accounted for. Bias adjustments applied to the data are shown to reduce trends in the data and to improve the consistency of estimates of air temperature, sea surface temperature (SST) and specific humidity. The bias adjustments also improve the agreement of NOCS v2.0 with independent data from research moorings. Cross-validation of the dataset suggests that the uncertainty estimates are realistic, but that the uncertainties are probably underestimated in high variability regions and overestimated in regions with lower variability
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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