Susana M. Barbosa

The effect of olive leaves supplementation on the feed digestibility, growth performances of pigs and quality of pork meat.

The influence of olive leaves supplementation on feed digestibility, growth performance of pigs and pork meat quality was investigated. Pigs fed diets with olive leaves at 5% (OL5) and 10% (OL10) levels had lower daily weight gain (DG) and daily feed intake (DFI) than pigs fed a conventional diet (OL0) but differences were not observed between groups fed with the different quantities of leaves. Additionally, pigs fed diets with leaves had the worst feed:gain ratio and showed a decrease in overall backfat. Chops from pigs fed the leaf diets had lower peroxide (PV) and conjugated diene (CD) contents than chops from pigs fed conventional diets. Moreover, chops from pigs fed with the higher quantity of leaves also showed a lower drip loss. After a storage period of 8 days at 4°C, meat obtained from both OL5 and OL10 animals also differed (P<0.05) in PV and %CD values from those fed a conventional diet. Since the fatty acid composition of the longissimus muscles was not different, differences in oxidative stability could only be explained by the significantly higher α-tocopherol concentration in intramuscular fat and backfat in pigs fed with olive leaf diets.

Seasonal and daily variation of radon at 10 m depth in borehole, Garhwal Lesser Himalaya, India

Mostly accepted and widely reported radon (Rn(222)) measurements, a tool for earthquake precursor research, is a part of multi-parametric geophysical observation in the Garhwal Lesser Himalaya for earthquake related studies. Radon is being recorded continuously at an interval of 15 min at 10 m depth in a 68 m deep borehole. Three years high resolution 15 min data at 10 m depth shows a complex trend and has a strong seasonal effect along with some diurnal, semi-diurnal and multi-day recurring trends. A well-defined seasonal pattern is prominent with a high emanation in summer and low values in winter accounting for about a 30% decrease in count values in winter when the atmospheric temperature is very low at this station located 1.90 km above mean sea level. Diurnal, semi-diurnal and multi-day trends in this time-series are mainly observed during April-May and October-November. This is the period of spring and autumn when there is a high contrast in day-night atmospheric temperature. Hence the high fluctuation in Rn concentration is mainly caused by the temperature contrast between the air-column inside the borehole and the atmosphere above the earths surface.

Time Series Analysis of Sea-Level Records: Characterising Long-Term Variability

The characterisation and quantification of long-term sea-level variability is of considerable interest in a climate change context. Long time series from coastal tide gauges are particularly appropriate for this purpose. Long-term variability in tide gauge records is usually expressed through the linear slope resulting from the fit of a linear model to the time series, thus assuming that the generating process is deterministic with a short memory component. However, this assumption needs to be tested, since trend features can also be due to non-deterministic processes such as random walk or long range dependent processes, or even be driven by a combination of deterministic and stochastic processes. Specific methodology is therefore required to distinguish between a deterministic trend and stochastically-driven trend-like features in a time series. In this chapter, long-term sea-level variability is characterised through the application of (i) parametric statistical tests for stationarity, (ii) wavelet analysis for assessing scaling features, and (iii) generalised least squares for estimating deterministic trends. The results presented here for long tide gauge records in the North Atlantic show, despite some local coherency, profound differences in terms of the low frequency structure of these sea-level time series. These differences suggest that the long-term variations are reflecting mainly local/regional phenomena.

Testing for Deterministic Trends in Global Sea Surface Temperature

AbstractLong-term variability in global sea surface temperature (SST) is often quantified by the slope from a linear regression fit. Attention is then focused on assessing the statistical significance of the derived slope parameter, but the adequacy of the linear model itself, and the inherent assumption of a deterministic linear trend, is seldom tested. Here, a parametric statistical test is applied to test the hypothesis of a linear deterministic trend in global sea surface temperature. The results show that a linear slope is not adequate for describing the long-term variability of sea surface temperature over most of the earth’s surface. This does not mean that sea surface temperature is not increasing, rather that the increase should not be characterized by the slope from a linear fit. Therefore, describing the long-term variability of sea surface temperature by implicitly assuming a deterministic linear trend can give misleading results, particularly in terms of uncertainty, since the actual increase...

Changing seasonality in North Atlantic coastal sea level from the analysis of long tide gauge records

Sea level is a key variable in the context of global climate change. Climate-induced variability is expected to affect not only the mean sea level but also the amplitude and phase of its seasonal cycle. This study addresses the changes in the amplitude and phase of the annual cycle of coastal sea level in the extra-tropical North Atlantic. The physical causes of these variations are explored by analysing the association between fluctuations in the annual amplitude of sea level and in ancillary parameters [atmospheric pressure, sea-surface temperature and North Atlantic Oscillation (NAO) winter index]. The annual cycle is extracted through autoregressive decomposition, in order to be able to separate variations in seasonality from long-term interannual variations in the mean. The changes detected in the annual sea level cycle are regionally coherent, and related to changes in the analysed forcing parameters. At the northern sites, fluctuations in the annual amplitude of sea level are associated with concurrent changes in temperature, while atmospheric pressure is the dominant influence for most of the sites on the western boundary. The state of the NAO influences the annual variability in the Southern Bight, possibly through NAO-related changes in wind stress and ocean circulation.

Clustering Time Series of Sea Levels: Extreme Value Approach

In this paper, long (>40 years) hourly tide gauge records from the North Atlantic are analyzed. A new time series clustering approach which combines Bayesian methodology, extreme value theory, and classification techniques is adopted for the analysis of the regional variability of sea-level extremes. The tide gauge records are clustered on the basis of their corresponding predictive distributions for 25-, 50-, and 100-year return values. The results of the cluster analysis show a clear distinction between the higher latitude stations for which the return values are largest and the remaining locations. This distinction reflects in the U.S. east coast the transition between the Scottian shelf and Gulf of Maine area and the mid-Atlantic Bight area. For the stations at lower latitudes the results show a grouping based on return levels that is not a function of geographical proximity but reflects local effects in extreme sea levels associated with the specific location of each tide gauge.

Witnessing North Atlantic westerlies variability from ships’ logbooks (1685–2008)

Abstract A monthly index based on the persistence of the westerly winds over the English Chanel is constructed for 1685–2008 using daily data from ships’ logbooks and comprehensive marine meteorological datasets. The so-called Westerly Index (WI) provides the longest instrumental record of atmospheric circulation currently available. Anomalous WI values are associated with spatially coherent climatic signals in temperature and precipitation over large areas of Europe, which are stronger for precipitation than for temperature and in winter and summer than in transitional seasons. Overall, the WI series accord with the known European climatic history, and reveal that the frequency of the westerlies in the eastern Atlantic during the twentieth century and the Late Maunder Minimum was not exceptional in the context of the last three centuries. It is shown that the WI provides additional and complementary information to the North Atlantic Oscillation (NAO) indices. The analysis of WI series during the industrial era indicates an overall good agreement with the winter and high-summer NAO, with the exception of several multidecadal periods of weakened correlation. These decoupled periods between the frequency and the intensity of the zonal flow are interpreted on the basis of several sources of non-stationarity affecting the centres of the variability of the North Atlantic and their teleconnections. Comparisons with NAO reconstructions and long instrumental indices extending back to the seventeenth century suggest that similar situations have occurred in the past, which call for caution when reconstructing the past atmospheric circulation from climatic proxies. The robustness and extension of its climatic signal, the length of the series and its instrumental nature make the WI an excellent benchmark for proxy calibration in Europe and Greenland.

Extreme value and cluster analysis of European daily temperature series

Time series of daily mean temperature obtained from the European Climate Assessment data set is analyzed with respect to their extremal properties. A time-series clustering approach which combines Bayesian methodology, extreme value theory and classification techniques is adopted for the analysis of the regional variability of temperature extremes. The daily mean temperature records are clustered on the basis of their corresponding predictive distributions for 25-, 50- and 100-year return values. The results of the cluster analysis show a clear distinction between the highest altitude stations, for which the return values are lowest, and the remaining stations. Furthermore, a clear distinction is also found between the northernmost stations in Scandinavia and the stations in central and southern Europe. This spatial structure of the return period distributions for 25-, 50- and 100-years seems to be consistent with projected changes in the variability of temperature extremes over Europe pointing to a different behavior in central Europe than in northern Europe and the Mediterranean area, possibly related to the effect of soil moisture and land-atmosphere coupling.

Discrete wavelet analysis of the influence of the North Atlantic Oscillation on Baltic Sea level

ABSTRACT Mean sea level (MSL) in the Baltic Sea is influenced by several factors and therefore presents a complex behaviour over a wide range of time-scales. This work performs a multi-scale analysis of MSL variability in the Baltic Sea using discrete wavelet analysis. The North Atlantic Oscillation (NAO) is well known for having a strong influence in MSL variability over the Baltic; however, the relationship between MSL and NAO at different time-scales is still little understood. In this work a comparison of MSL and NAO variability is performed for a wide range of temporal scales, uncovering distinct relationships in high-frequency and long-term temporal variability. The annual and sub-annual scales are found to account for more than 50% of the total MSL variability. The MSL annual cycle is analysed and a shift from low to high amplitude values is identified in the 1970s for most stations. MSL is found to be anti-correlated to NAO at short time-scales while on the long-term NAO and MSL appear to be positively correlated for most stations. The physical mechanisms behind these distinct relationships deserve deeper study.

Indoor radon periodicities and their physical constraints: a study in the Coimbra region (Central Portugal)

Indoor radon activities were measured during a period of 6 months, as well as several physical environmental variables (temperature, pressure, humidity and rainfall). The location was a small room at an administrative building of the University of Coimbra, usually undisturbed by human activities and situated over bedrock of low-uranium Triassic red sandstones. A low average activity of radon was observed (36 Bq m(-3)), however showing a very well marked daily periodicity (10+/-5 Bq m(-3)), with maximum values occurring more frequently between 9 and 10 a.m. Daily variations are shown to have no relation with earth tides, and their amplitudes exhibit a significant correlation with outdoor temperature; no dependence on barometric pressure was found. Rainfall disturbs the observed daily radon cycles through a strong reduction of their amplitude, but has no effect on the long-term variability of the gas concentration.