103 resultados para summer residence


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Chlorophyll-a concentration variations are described for two major river basins in England, the Humber and the Thames and related to catchment characteristics and nutrient concentrations across a range of rural, agricultural and urban/industrial settings. For all the rivers there are strong seasonal variations, with concentrations peaking in the spring and summer time when biological activity is at its highest. However, there are large variations in the magnitude of the seasonal effects across the rivers. For the spring-summer low-flow periods, average concentrations of chlorophyll-a correlate with soluble reactive phosphor-us (SRP). Chlorophyll-a is also correlated with particulate nitrogen (PN), organic carbon (POC) and suspended sediments. However, the strongest relationships are with catchment area and flow, where two straight line relationships are observed. The results indicate the importance of residence times for determining planktonic growth within the rivers. This is also indicated by the lack of chlorophyll-a response to lowering of SRP concentrations in several of the rivers in the area due to phosphorus stripping of effluents at major sewage treatment works. A key control on chlorophyll-a concentration may be the input of canal and reservoir waters during the growing period: this too relates to issues of residence times. However, there may well be a complex series of factors influencing residence time across the catchments due to features such as inhomogeneous flow within the catchments, a fractal distribution of stream channels that leads to a distribution of residence times and differences in planktonic inoculation sources. Industrial pollution on the Aire and Calder seems to have affected the relationship of chlorophyll-a with PN and POC. The results are discussed in relation to the Water Framework Directive. (c) 2006 Elsevier B.V. All rights reserved.

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Anomalous heavy snow during winter or spring has long been regarded as a possible precursor of deficient Indian monsoon rainfall during the subsequent summer. However previous work in this field is inconclusive, in terms of the mechanism that communicates snow anomalies to the monsoon summer, and even the region from which snow has the most impact. In this study we explore these issues in coupled and atmosphere-only versions of the Hadley Centre model. A 1050-year control integration of the HadCM3 coupled model, which well represents the seasonal cycle of snow cover over the Eurasian continent, is analysed and shows evidence for weakened monsoons being preceded by strong snow forcing (in the absence of ENSO) over either the Himalaya/Tibetan Plateau or north/west Eurasia regions. However, empirical orthogonal function (EOF) analysis of springtime interannual variability in snow depth shows the leading mode to have opposite signs between these two regions, suggesting that competing mechanisms may be possible. To determine the dominant region, ensemble integrations are carried out using HadAM3, the atmospheric component of HadCM3, and a variety of anomalous snow forcing initial conditions obtained from the control integration of the coupled model. Forcings are applied during spring in separate experiments over the Himalaya/Tibetan Plateau and north/west Eurasia regions, in conjunction with climatological SSTs in order to avoid the direct effects of ENSO. With the aid of idealized forcing conditions in sensitivity tests, we demonstrate that forcing from the Himalaya region is dominant in this model via a Blanford-type mechanism involving reduced surface sensible heat and longwave fluxes, reduced heating of the troposphere over the Tibetan Plateau and consequently a reduced meridional tropospheric temperature gradient which weakens the monsoon during early summer. Snow albedo is shown to be key to the mechanism, explaining around 50% of the perturbation in sensible heating over the Tibetan Plateau, and accounting for the majority of cooling through the troposphere.

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In this study, the oceanic regions that are associated with anomalous Ethiopian summer rains were identified and the teleconnection mechanisms that give rise to these associations have been investigated. Because of the complexities of rainfall climate in the horn of Africa, Ethiopia has been subdivided into six homogeneous rainfall zones and the influence of SST anomalies was analysed separately for each zone. The investigation made use of composite analysis and modelling experiments. Two sets of composites of atmospheric fields were generated, one based on excess/deficit rainfall anomalies and the other based on warm/cold SST anomalies in specific oceanic regions. The aim of the composite analysis was to determine the link between SST and rainfall in terms of large scale features. The modelling experiments were intended to explore the causality of these linkage. The results show that the equatorial Pacific, the midlatitude northwest Pacific and the Gulf of Guinea all exert an influence on the summer rainfall in various part of the country. The results demonstrate that different mechanisms linked to sea surface temperature control variations in rainfall in different parts of Ethiopia. This has important consequences for seasonal forecasting models which are based on statistical correlations between SST and seasonal rainfall totals. It is clear that such statistical models should take account of the local variations in teleconnections.

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A seasonal forecasting system that is capable of skilfully predicting rainfall totals on a regional scale would be of great value to Ethiopia. Here, we describe how a statistical model can exploit the teleconnections described in part 1 of this pair of papers to develop such a system. We show that, in most cases, the predictors selected objectively by the statistical model can be interpreted in the light of physical teleconnections with Ethiopian rainfall, and discuss why, in some cases, unexpected regions are chosen as predictors. We show that the forecast has skill in all parts of Ethiopia, and argue that this method could provide the basis of an operational seasonal forecasting system for Ethiopia.

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Several aspects of terrestrial ecosystems are known to be associated with the North Atlantic Oscillation (NAO) through effects of the NAO on winter climate, but recently the winter NAO has also been shown to be correlated with the following summer climate, including drought. Since drought is a major factor determining grassland primary productivity, the hypothesis was tested that the winter NAO is associated with summer herbage growth through soil moisture availability, using data from the Park Grass Experiment at Rothamsted, UK between 1960 and 1999. The herbage growth rate, mean daily rainfall, mean daily potential evapotranspiration (PE) and the mean and maximum potential soil moisture deficit (PSMD) were calculated between the two annual cuts in early summer and autumn for the unlimed, unfertilized plots. Mean and maximum PSMD were more highly correlated than rainfall or PE with herbage growth rate. Regression analysis showed that the natural logarithm of the herbage growth rate approximately halved for a 250 mm increase in maximum PSMD over the range 50-485 mm. The maximum PSMD was moderately correlated with the preceding winter NAO, with a positive winter NAO index associated with greater maximum PSMD. A positive winter NAO index was also associated with low herbage growth rate, accounting for 22% of the interannual variation in the growth rate. It was concluded that the association between the winter NAO and summer herbage growth rate is mediated by the PSMD in summer.

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Two-dimensional flood inundation modelling is a widely used tool to aid flood risk management. In urban areas, where asset value and population density are greatest, the model spatial resolution required to represent flows through a typical street network (i.e. < 10m) often results in impractical computational cost at the whole city scale. Explicit diffusive storage cell models become very inefficient at such high resolutions, relative to shallow water models, because the stable time step in such schemes scales as a quadratic of resolution. This paper presents the calibration and evaluation of a recently developed new formulation of the LISFLOOD-FP model, where stability is controlled by the Courant–Freidrichs–Levy condition for the shallow water equations, such that, the stable time step instead scales linearly with resolution. The case study used is based on observations during the summer 2007 floods in Tewkesbury, UK. Aerial photography is available for model evaluation on three separate days from the 24th to the 31st of July. The model covered a 3.6 km by 2 km domain and was calibrated using gauge data from high flows during the previous month. The new formulation was benchmarked against the original version of the model at 20 m and 40 m resolutions, demonstrating equally accurate performance given the available validation data but at 67x faster computation time. The July event was then simulated at the 2 m resolution of the available airborne LiDAR DEM. This resulted in a significantly more accurate simulation of the drying dynamics compared to that simulated by the coarse resolution models, although estimates of peak inundation depth were similar.