39 resultados para term trends

em CentAUR: Central Archive University of Reading - UK


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With the current concern over climate change, descriptions of how rainfall patterns are changing over time can be useful. Observations of daily rainfall data over the last few decades provide information on these trends. Generalized linear models are typically used to model patterns in the occurrence and intensity of rainfall. These models describe rainfall patterns for an average year but are more limited when describing long-term trends, particularly when these are potentially non-linear. Generalized additive models (GAMS) provide a framework for modelling non-linear relationships by fitting smooth functions to the data. This paper describes how GAMS can extend the flexibility of models to describe seasonal patterns and long-term trends in the occurrence and intensity of daily rainfall using data from Mauritius from 1962 to 2001. Smoothed estimates from the models provide useful graphical descriptions of changing rainfall patterns over the last 40 years at this location. GAMS are particularly helpful when exploring non-linear relationships in the data. Care is needed to ensure the choice of smooth functions is appropriate for the data and modelling objectives. (c) 2008 Elsevier B.V. All rights reserved.

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This paper examines two hydrochemical time-series derived from stream samples taken in the Upper Hafren catchment, Plynlimon, Wales. One time-series comprises data collected at 7-hour intervals over 22 months (Neal et al., submitted, this issue), while the other is based on weekly sampling over 20 years. A subset of determinands: aluminium, calcium, chloride, conductivity, dissolved organic carbon, iron, nitrate, pH, silicon and sulphate are examined within a framework of non-stationary time-series analysis to identify determinand trends, seasonality and short-term dynamics. The results demonstrate that both long-term and high-frequency monitoring provide valuable and unique insights into the hydrochemistry of a catchment. The long-term data allowed analysis of long-termtrends, demonstrating continued increases in DOC concentrations accompanied by declining SO4 concentrations within the stream, and provided new insights into the changing amplitude and phase of the seasonality of the determinands such as DOC and Al. Additionally, these data proved invaluable for placing the short-term variability demonstrated within the high-frequency data within context. The 7-hour data highlighted complex diurnal cycles for NO3, Ca and Fe with cycles displaying changes in phase and amplitude on a seasonal basis. The high-frequency data also demonstrated the need to consider the impact that the time of sample collection can have on the summary statistics of the data and also that sampling during the hours of darkness provides additional hydrochemical information for determinands which exhibit pronounced diurnal variability. Moving forward, this research demonstrates the need for both long-term and high-frequency monitoring to facilitate a full and accurate understanding of catchment hydrochemical dynamics.

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A dynamical wind-wave climate simulation covering the North Atlantic Ocean and spanning the whole 21st century under the A1B scenario has been compared with a set of statistical projections using atmospheric variables or large scale climate indices as predictors. As a first step, the performance of all statistical models has been evaluated for the present-day climate; namely they have been compared with a dynamical wind-wave hindcast in terms of winter Significant Wave Height (SWH) trends and variance as well as with altimetry data. For the projections, it has been found that statistical models that use wind speed as independent variable predictor are able to capture a larger fraction of the winter SWH inter-annual variability (68% on average) and of the long term changes projected by the dynamical simulation. Conversely, regression models using climate indices, sea level pressure and/or pressure gradient as predictors, account for a smaller SWH variance (from 2.8% to 33%) and do not reproduce the dynamically projected long term trends over the North Atlantic. Investigating the wind-sea and swell components separately, we have found that the combination of two regression models, one for wind-sea waves and another one for the swell component, can improve significantly the wave field projections obtained from single regression models over the North Atlantic.

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Long-term trends, interannual and intra-seasonal variability in the mass-balance record from Djankuat glacier, central Greater Caucasus, Russia, are related to local climate change, synoptic and large-scale anomalies in atmospheric circulation. A clear warming signal emerged in the central Greater Caucasus in the early 1990s, leading to a strong increase in ablation. In the absence of a compensating change in winter accumulation, the net mass balance of Djankuat has declined. The highest value of seasonal ablation on record was registered in the summer of 2000. At the beginning of the 21st century these trends reversed. Ablation was below average even in the summer of 2003, which was unusually warm in western Europe. Precipitation and winter accumulation were high, allowing for a partial recovery of net mass balance. The interannual variability in the components of mass balance is weakly related to the North Atlantic Oscillation (NAO) and the Scandinavian teleconnection patterns, but there is a clear link with the large-scale circulation anomalies represented by the Rossby pattern. Five synoptic categories have been identified for the ablation season of 2005, revealing a strong separation between components of radiation budget, air temperature and daily melt. Air temperature is the main control over melt. The highest values of daily ablation are related to the strongly positive NAO which forces high net radiation, and to the warm and moist advection from the Black Sea.

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Global climate change and its impacts are being increasingly studied and precipitation trends are one of the measures of quantifying climate change especially in the tropics. This study uses daily rainfall data to determine if there are changes in the long-term trends in rainfall variability in the East Coast Mountains of Mauritius during the last few decades, and to investigate the factors influencing the trends in the inter-annual to inter-decadal rainfall variability. Statistical modelling has been used to investigate the trends in total seasonal rainfall, the number of rain days and the mean amount of rain per rainy days and the local, regional and large-scale factors that affect them on inter-annual to inter-decadal time scales. The strongest inter-decadal trend was found in the number of rain days for both rainfall seasons, and the other variables were found to have weak or insignificant trends. Both local factors, such as the surrounding sea surface temperatures and large-scale phenomena such as Indian Monsoon and the El Niño Southern Oscillation were found to influence rainfall patterns.

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A physically motivated statistical model is used to diagnose variability and trends in wintertime ( October - March) Global Precipitation Climatology Project (GPCP) pentad (5-day mean) precipitation. Quasi-geostrophic theory suggests that extratropical precipitation amounts should depend multiplicatively on the pressure gradient, saturation specific humidity, and the meridional temperature gradient. This physical insight has been used to guide the development of a suitable statistical model for precipitation using a mixture of generalized linear models: a logistic model for the binary occurrence of precipitation and a Gamma distribution model for the wet day precipitation amount. The statistical model allows for the investigation of the role of each factor in determining variations and long-term trends. Saturation specific humidity q(s) has a generally negative effect on global precipitation occurrence and with the tropical wet pentad precipitation amount, but has a positive relationship with the pentad precipitation amount at mid- and high latitudes. The North Atlantic Oscillation, a proxy for the meridional temperature gradient, is also found to have a statistically significant positive effect on precipitation over much of the Atlantic region. Residual time trends in wet pentad precipitation are extremely sensitive to the choice of the wet pentad threshold because of increasing trends in low-amplitude precipitation pentads; too low a choice of threshold can lead to a spurious decreasing trend in wet pentad precipitation amounts. However, for not too small thresholds, it is found that the meridional temperature gradient is an important factor for explaining part of the long-term trend in Atlantic precipitation.

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A physically motivated statistical model is used to diagnose variability and trends in wintertime ( October - March) Global Precipitation Climatology Project (GPCP) pentad (5-day mean) precipitation. Quasi-geostrophic theory suggests that extratropical precipitation amounts should depend multiplicatively on the pressure gradient, saturation specific humidity, and the meridional temperature gradient. This physical insight has been used to guide the development of a suitable statistical model for precipitation using a mixture of generalized linear models: a logistic model for the binary occurrence of precipitation and a Gamma distribution model for the wet day precipitation amount. The statistical model allows for the investigation of the role of each factor in determining variations and long-term trends. Saturation specific humidity q(s) has a generally negative effect on global precipitation occurrence and with the tropical wet pentad precipitation amount, but has a positive relationship with the pentad precipitation amount at mid- and high latitudes. The North Atlantic Oscillation, a proxy for the meridional temperature gradient, is also found to have a statistically significant positive effect on precipitation over much of the Atlantic region. Residual time trends in wet pentad precipitation are extremely sensitive to the choice of the wet pentad threshold because of increasing trends in low-amplitude precipitation pentads; too low a choice of threshold can lead to a spurious decreasing trend in wet pentad precipitation amounts. However, for not too small thresholds, it is found that the meridional temperature gradient is an important factor for explaining part of the long-term trend in Atlantic precipitation.

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Stratospheric water vapour is a powerful greenhouse gas. The longest available record from balloon observations over Boulder, Colorado, USA shows increases in stratospheric water vapour concentrations that cannot be fully explained by observed changes in the main drivers, tropical tropopause temperatures and methane. Satellite observations could help resolve the issue, but constructing a reliable long-term data record from individual short satellite records is challenging. Here we present an approach to merge satellite data sets with the help of a chemistry–climate model nudged to observed meteorology. We use the models’ water vapour as a transfer function between data sets that overcomes issues arising from instrument drift and short overlap periods. In the lower stratosphere, our water vapour record extends back to 1988 and water vapour concentrations largely follow tropical tropopause temperatures. Lower and mid-stratospheric long-term trends are negative, and the trends from Boulder are shown not to be globally representative. In the upper stratosphere, our record extends back to 1986 and shows positive long-term trends. The altitudinal differences in the trends are explained by methane oxidation together with a strengthened lower-stratospheric and a weakened upper stratospheric circulation inferred by this analysis. Our results call into question previous estimates of surface radiative forcing based on presumed global long-term increases in water vapour concentrations in the lower stratosphere.

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Current research agendas are increasingly encouraging the construction industry to operate on the basis of 'added value'. Such debates echo the established concept of 'high value manufacturing' and associated trends towards servitization. Within construction, the so-called 'value agenda' draws heavily from the notion of integrated solutions. This is held to be especially appropriate in the context of PFI projects. Also relevant is the concept of service-led projects whereby the project rationale is driven by the client's objectives for delivering an enhanced service to its own customers. Such ideas are contextualized by a consideration of broader trends of privatization and outsourcing within and across the construction industry's client base. The current emphasis on integrated solutions reflects long-term trends within privatized client organizations towards the outsourcing of asset management capabilities. However, such trends are by no means uniform or consistent. An in-depth case study of three operating divisions within a major construction company illustrates that firms are unlikely to reorientate their business in response to the 'value agenda'. In the case of PFI, the tendency has been to establish specialist units for the purposes of winning work. Meanwhile, institutionally embedded operating routines within the rest of the business remain broadly unaffected.

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Changes in the extent of glaciers and rates of glacier termini retreat in the eastern Terskey-Alatoo Range, the Tien Shan Mountains, Central Asia have been evaluated using the remote sensing techniques. Changes in the extent of 335 glaciers between the end of the Little Ice Age (LIA; mid-19th century), 1990 and 2003 have been estimated through the delineation of glacier outlines and the LIA moraine positions on the Landsat TM and ASTER imagery for 1990 and 2003 respectively. By 2003, the glacier surface area had decreased by 19% of the LIA value, which constitutes a 76 km(2) reduction in glacier surface area. Mapping of 109 glaciers using the 1965 1:25,000 maps revealed that glacier surface area decreased by 12.6% of the 1965 value between 1965 and 2003. Detailed mapping of 10 glaciers using historical maps and aerial photographs from the 1943-1977 period, has enabled glacier extent variations over the 20th century to be identified with a higher temporal resolution. Glacial retreat was slow in the early 20th century but increased considerably between 1943 and 1956 and then again after 1977. The post-1990 period has been marked by the most rapid glacier retreat since the end of the LIA. The observed changes in the extent of glaciers are in line with the observed climatic warming. The regional weather stations have revealed a strong climatic warming during the ablation season since the 1950s at a rate of 0.02-0.03 degrees Ca-1. At the higher elevations in the study area represented by the Tien Shan meteorological station, the summer warming was accompanied by negative anomalies in annual precipitation in the 1990s enhancing glacier retreat. However, trends in precipitation in the post-1997 period cannot be evaluated due to the change in observational practices at this station. Neither station in the study area exhibits significant long-term trends in precipitation. Crown Copyright (C) 2009 Published by Elsevier B.V. All rights reserved.

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An integrated approach to climate change impact assessment is explored by linking established models of regional climate (SDSM), water resources (CATCHMOD) and water quality (INCA) within a single framework. A case study of the River Kennet illustrates how the system can be used to investigate aspects of climate change uncertainty, deployable water resources, and water quality dynamics in upper and lower reaches of the drainage network. The results confirm the large uncertainty in climate change scenarios and freshwater impacts due to the choice of general circulation model (GCM). This uncertainty is shown to be greatest during summer months as evidenced by large variations between GCM-derived projections of future tow river flows, deployable yield from groundwater, severity of nutrient flushing episodes, and Long-term trends in surface water quality. Other impacts arising from agricultural land-use reform or delivery of EU Water Framework Directive objectives under climate change could be evaluated using the same framework. (c) 2006 Elsevier B.V. All rights reserved.

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This study uses a Granger causality time series modeling approach to quantitatively diagnose the feedback of daily sea surface temperatures (SSTs) on daily values of the North Atlantic Oscillation (NAO) as simulated by a realistic coupled general circulation model (GCM). Bivariate vector autoregressive time series models are carefully fitted to daily wintertime SST and NAO time series produced by a 50-yr simulation of the Third Hadley Centre Coupled Ocean-Atmosphere GCM (HadCM3). The approach demonstrates that there is a small yet statistically significant feedback of SSTs oil the NAO. The SST tripole index is found to provide additional predictive information for the NAO than that available by using only past values of NAO-the SST tripole is Granger causal for the NAO. Careful examination of local SSTs reveals that much of this effect is due to the effect of SSTs in the region of the Gulf Steam, especially south of Cape Hatteras. The effect of SSTs on NAO is responsible for the slower-than-exponential decay in lag-autocorrelations of NAO notable at lags longer than 10 days. The persistence induced in daily NAO by SSTs causes long-term means of NAO to have more variance than expected from averaging NAO noise if there is no feedback of the ocean on the atmosphere. There are greater long-term trends in NAO than can be expected from aggregating just short-term atmospheric noise, and NAO is potentially predictable provided that future SSTs are known. For example, there is about 10%-30% more variance in seasonal wintertime means of NAO and almost 70% more variance in annual means of NAO due to SST effects than one would expect if NAO were a purely atmospheric process.

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During the descent into the recent ‘exceptionally’ low solar minimum, observations have revealed a larger change in solar UV emissions than seen at the same phase of previous solar cycles. This is particularly true at wavelengths responsible for stratospheric ozone production and heating. This implies that ‘top-down’ solar modulation could be a larger factor in long-term tropospheric change than previously believed, many climate models allowing only for the ‘bottom-up’ effect of the less-variable visible and infrared solar emissions. We present evidence for long-term drift in solar UV irradiance, which is not found in its commonly used proxies. In addition, we find that both stratospheric and tropospheric winds and temperatures show stronger regional variations with those solar indices that do show long-term trends. A top-down climate effect that shows long-term drift (and may also be out of phase with the bottom-up solar forcing) would change the spatial response patterns and would mean that climate-chemistry models that have sufficient resolution in the stratosphere would become very important for making accurate regional/seasonal climate predictions. Our results also provide a potential explanation of persistent palaeoclimate results showing solar influence on regional or local climate indicators.

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Most of the dissolved organic carbon (DOC) exported from catchments is transported during storm events. Accurate assessments of DOC fluxes are essential to understand long-term trends in the transport of DOC from terrestrial to aquatic systems, and also the loss of carbon from peatlands to determine changes in the source/sink status of peatland carbon stores. However, many long-term monitoring programmes collect water samples at a frequency (e.g. weekly/monthly) less than the time period of a typical storm event (typically <1–2 days). As widespread observations in catchments dominated by organo-mineral soils have shown that both concentration and flux of DOC increases during storm events, lower frequency monitoring could result in substantial underestimation of DOC flux as the most dynamic periods of transport are missed. However, our intensive monitoring study in a UK upland peatland catchment showed a contrasting response to these previous studies. Our results showed that (i) DOC concentrations decreased during autumn storm events and showed a poor relationship with flow during other seasons; and that (ii) this decrease in concentrations during autumn storms caused DOC flux estimates based on weekly monitoring data to be over-estimated, rather than under-estimated, because of over rather than under estimation of the flow-weighted mean concentration used in flux calculations. However, as DOC flux is ultimately controlled by discharge volume, and therefore rainfall, and the magnitude of change in discharge was greater than the magnitude of decline in concentrations, DOC flux increased during individual storm events. The implications for long-term DOC trends are therefore contradictory, as increased rainfall could increase flux but cause an overall decrease in DOC concentrations from peatland streams. Care needs to be taken when interpreting long-term trends in DOC flux rather than concentration; as flux is calculated from discharge estimates, and discharge is controlled by rainfall, DOC flux and rainfall/discharge will always be well correlated.