989 resultados para climate variability


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Standard procedures for forecasting flood risk (Bulletin 17B) assume annual maximum flood (AMF) series are stationary, meaning the distribution of flood flows is not significantly affected by climatic trends/cycles, or anthropogenic activities within the watershed. Historical flood events are therefore considered representative of future flood occurrences, and the risk associated with a given flood magnitude is modeled as constant over time. However, in light of increasing evidence to the contrary, this assumption should be reconsidered, especially as the existence of nonstationarity in AMF series can have significant impacts on planning and management of water resources and relevant infrastructure. Research presented in this thesis quantifies the degree of nonstationarity evident in AMF series for unimpaired watersheds throughout the contiguous U.S., identifies meteorological, climatic, and anthropogenic causes of this nonstationarity, and proposes an extension of the Bulletin 17B methodology which yields forecasts of flood risk that reflect climatic influences on flood magnitude. To appropriately forecast flood risk, it is necessary to consider the driving causes of nonstationarity in AMF series. Herein, large-scale climate patterns—including El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and Atlantic Multidecadal Oscillation (AMO)—are identified as influencing factors on flood magnitude at numerous stations across the U.S. Strong relationships between flood magnitude and associated precipitation series were also observed for the majority of sites analyzed in the Upper Midwest and Northeastern regions of the U.S. Although relationships between flood magnitude and associated temperature series are not apparent, results do indicate that temperature is highly correlated with the timing of flood peaks. Despite consideration of watersheds classified as unimpaired, analyses also suggest that identified change-points in AMF series are due to dam construction, and other types of regulation and diversion. Although not explored herein, trends in AMF series are also likely to be partially explained by changes in land use and land cover over time. Results obtained herein suggest that improved forecasts of flood risk may be obtained using a simple modification of the Bulletin 17B framework, wherein the mean and standard deviation of the log-transformed flows are modeled as functions of climate indices associated with oceanic-atmospheric patterns (e.g. AMO, ENSO, NAO, and PDO) with lead times between 3 and 9 months. Herein, one-year ahead forecasts of the mean and standard deviation, and subsequently flood risk, are obtained by applying site specific multivariate regression models, which reflect the phase and intensity of a given climate pattern, as well as possible impacts of coupling of the climate cycles. These forecasts of flood risk are compared with forecasts derived using the existing Bulletin 17B model; large differences in the one-year ahead forecasts are observed in some locations. The increased knowledge of the inherent structure of AMF series and an improved understanding of physical and/or climatic causes of nonstationarity gained from this research should serve as insight for the formulation of a physical-casual based statistical model, incorporating both climatic variations and human impacts, for flood risk over longer planning horizons (e.g., 10-, 50, 100-years) necessary for water resources design, planning, and management.

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Large progress has been made in the past few years towards quantifying and understanding climate variability during past centuries. At the same time, present-day climate has been studied using state-of-the-art data sets and tools with respect to the physical and chemical mechanisms governing climate variability. Both the understanding of the past and the knowledge of the processes are important for assessing and attributing the anthropogenic effect on present and future climate. The most important time period in this context is the past approximately 100 years, which comprises large natural variations and extremes (such as long droughts) as well as anthropogenic influences, most pronounced in the past few decades. Recent and ongoing research efforts steadily improve the observational record of the 20th century, while atmospheric circulation models are used to underpin the mechanisms behind large climatic variations. Atmospheric chemistry and composition are important for understanding climate variability and change, and considerable progress has been made in the past few years in this field. The evolving integration of these research areas in a more comprehensive analysis of recent climate variability was reflected in the organisation of a workshop “Climate variability and extremes in the past 100 years” in Gwatt near Thun (Switzerland), 24–26 July 2006. The aim of this workshop was to bring together scientists working on data issues together with statistical climatologists, modellers, and atmospheric chemists to discuss gaps in our understanding of climate variability during the past approximately 100 years.

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Thirteen annually resolved accumulation-rate records covering the last similar to 200 years from the Pine Island-Thwaites and Ross drainage systems and the South Pole are used to examine climate variability over West Antarctica. Accumulation is controlled spatially by the topography of the ice sheet, and temporally by changes in moisture transport and cyclonic activity. A comparison of mean accumulation since 1970 at each site to the long-term mean indicates an increase in accumulation for sites located in the western sector of the Pine Island-Thwaites drainage system. Accumulation is negatively associated with the Southern Oscillation Index (Sol) for sites near the ice divide, and periods of sustained negative Sol (1940-42, 1991-95) correspond to above-mean accumulation at most sites. Correlations of the accumulation-rate records with sea-level pressure (SLP) and the SOI suggest that accumulation near the ice divide and in the Ross drainage system may be associated with the midlatitudes. The post-1970 increase in accumulation coupled with strong SLP-accumulation-rate correlations near the coast suggests recent intensification of cyclonic activity in the Pine Island-Thwaites drainage system.

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Annually dated ice cores from West and East Antarctica provide proxies for past changes in atmospheric circulation over Antarctica and portions of the Southern Ocean, temperature in coastal West and East Antarctica, and the frequency of South Polar penetration of El Nino events. During the period (AD) 1700-1850, atmospheric circulation over the Antarctic and at least portions of the Southern Hemisphere underwent a mode switch departing from the out-of-phase alternation of multi-decadal long phases of EOF1 and EOF2 modes of the 850 hPa field over the Southern Hemisphere (as defined in the recent record by Thompson and Wallace, 2000; Thompson and Solomon, 2002) that characterizes the remainder of the 700 year long record. From (AD) 1700 to 1850, lower-tropospheric circulation was replaced by in-phase behavior of the Amundsen Sea Low component of EOF2 and the East Antarctic High component of EOF1. During the first phase of the mode switch, both West and East Antarctic temperatures declined, potentially in response to the increased extent of sea ice surrounding both regions. At the end of the mode switch, West Antarctic coastal temperatures rose and East Antarctic coastal temperatures fell, respectively, to their second highest and lowest of the record. Polar penetration of El Nino events increased during the mode switch. The onset of the AD 1700-1850 mode switch coincides with the extreme state of the Maunder Minimum in solar variability. Late 20th-century West Antarctic coastal temperatures are the highest in the record period, and East Antarctic coastal temperatures close to the lowest. Since AD 1700, extratropical regions of the Southern Hemisphere have experienced significant climate variability coincident with changes in both solar variability and greenhouse gases.