976 resultados para SUMMER MONSOON
Resumo:
Tree rings dominate millennium-long temperature reconstructions and many records originate from Scandinavia, an area for which the relative roles of external forcing and internal variation on climatic changes are, however, not yet fully understood. Here we compile 1,179 series of maximum latewood density measurements from 25 conifer sites in northern Scandinavia, establish a suite of 36 subset chronologies, and analyse their climate signal. A new reconstruction for the 1483–2006 period correlates at 0.80 with June–August temperatures back to 1860. Summer cooling during the early 17th century and peak warming in the 1930s translate into a decadal amplitude of 2.9°C, which agrees with existing Scandinavian tree-ring proxies. Climate model simulations reveal similar amounts of mid to low frequency variability, suggesting that internal ocean-atmosphere feedbacks likely influenced Scandinavian temperatures more than external forcing. Projected 21st century warming under the SRES A2 scenario would, however, exceed the reconstructed temperature envelope of the past 1,500 years.
Resumo:
A lacustrine sediment core from Fiddaun, western Ireland was studied to reconstruct summer temperature changes during the Weichselian Lateglacial. This site is located close to the Atlantic Ocean; and so is potentially sensitive to climatic changes associated with changes in ocean circulation. The record, comprising the end of the Weichselian Pleniglacial to the early Holocene, was analysed for fossil chironomids, lithology, and oxygen and carbon isotopes in the sedimentary carbonates. These proxies clearly show rapid warming at the onset of the Lateglacial Interstadial, relatively high summer temperatures during the Interstadial, pronounced cooling during the Younger Dryas, and subsequent warming at the transition to the Holocene. Chironomid-inferred mean July air temperatures for the Interstadial are ~12.5–14.5 °C, ~7.5 °C for the Younger Dryas, and ~15.0 °C for the early Holocene. Furthermore, this research provides evidence for at least two cold events during the Interstadial. These more moderate temperature oscillations can be correlated to Greenland Interstadial events 1b and 1d, on the basis of the age-depth model for the Fiddaun sequence. Based on multiple proxies, the first cold oscillation (GI-1d) was the more severe of the two in Ireland.
Resumo:
In this paper, we develop Bayesian hierarchical distributed lag models for estimating associations between daily variations in summer ozone levels and daily variations in cardiovascular and respiratory (CVDRESP) mortality counts for 19 U.S. large cities included in the National Morbidity Mortality Air Pollution Study (NMMAPS) for the period 1987 - 1994. At the first stage, we define a semi-parametric distributed lag Poisson regression model to estimate city-specific relative rates of CVDRESP associated with short-term exposure to summer ozone. At the second stage, we specify a class of distributions for the true city-specific relative rates to estimate an overall effect by taking into account the variability within and across cities. We perform the calculations with respect to several random effects distributions (normal, t-student, and mixture of normal), thus relaxing the common assumption of a two-stage normal-normal hierarchical model. We assess the sensitivity of the results to: 1) lag structure for ozone exposure; 2) degree of adjustment for long-term trends; 3) inclusion of other pollutants in the model;4) heat waves; 5) random effects distributions; and 6) prior hyperparameters. On average across cities, we found that a 10ppb increase in summer ozone level for every day in the previous week is associated with 1.25 percent increase in CVDRESP mortality (95% posterior regions: 0.47, 2.03). The relative rate estimates are also positive and statistically significant at lags 0, 1, and 2. We found that associations between summer ozone and CVDRESP mortality are sensitive to the confounding adjustment for PM_10, but are robust to: 1) the adjustment for long-term trends, other gaseous pollutants (NO_2, SO_2, and CO); 2) the distributional assumptions at the second stage of the hierarchical model; and 3) the prior distributions on all unknown parameters. Bayesian hierarchical distributed lag models and their application to the NMMAPS data allow us estimation of an acute health effect associated with exposure to ambient air pollution in the last few days on average across several locations. The application of these methods and the systematic assessment of the sensitivity of findings to model assumptions provide important epidemiological evidence for future air quality regulations.