979 resultados para climate variability


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Bivalve mollusk shells are useful tools for multi-species and multi-proxy paleoenvironmental reconstructions with a high temporal and spatial resolution. Past environmental conditions can be reconstructed from shell growth and stable oxygen and carbon isotope ratios, which present an archive for temperature, freshwater fluxes and primary productivity. The purpose of this thesis is the reconstruction of Holocene climate and environmental variations in the North Pacific with a high spatial and temporal resolution using marine bivalve shells. This thesis focuses on several different Holocene time periods and multiple regions in the North Pacific, including: Japan, Alaska (AK), British Columbia (BC) and Washington State, which are affected by the monsoon, Pacific Decadal Oscillation (PDO) and El Niño/Southern Oscillation (ENSO). Such high-resolution proxy data from the marine realm of mid- and high-latitudes are still rare. Therefore, this study contributes to the optimization and verification of climate models. However, before using bivalves for environmental reconstructions and seasonality studies, life history traits must be well studied to temporally align and interpret the geochemical record. These calibration studies are essential to ascertain the usefulness of selected bivalve species as paleoclimate proxy archives. This work focuses on two bivalve species, the short-lived Saxidomus gigantea and the long-lived Panopea abrupta. Sclerochronology and oxygen isotope ratios of different shell layers of P. abrupta were studied in order to test the reliability of this species as a climate archive. The annual increments are clearly discernable in umbonal shell portions and the increments widths should be measured in these shell portions. A reliable reconstruction of paleotemperatures may only be achieved by exclusively sampling the outer shell layer of multiple contemporaneous specimens. Life history traits (e.g., timing of growth line formation, duration of the growing season and growth rates) and stable isotope ratios of recent S. gigantea from AK and BC were analyzed in detail. Furthermore, a growth-temperature model based on S. gigantea shells from Alaska was established, which provides a better understanding of the hydrological changes related to the Alaska Coastal Current (ACC). This approach allows the independent measurement of water temperature and salinity from variations in the width of lunar daily growth increments of S. gigantea. Temperature explains 70% of the variability in shell growth. The model was calibrated and tested with modern shells and then applied to archaeological specimens. The time period between 988 and 1447 cal yrs BP was characterized by colder (~1-2°C) and much drier (2-5 PSU) summers, and a likely much slower flowing ACC than at present. In contrast, the summers during the time interval of 599-1014 cal yrs BP were colder (up to 3°C) and fresher (1-2 PSU) than today. The Aleutian Low may have been stronger and the ACC was probably flowing faster during this time.

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This article describes the indigenous knowledge (IK) that agro-pastoralists in larger Makueni District, Kenya hold and how they use it to monitor, mitigate and adapt to drought. It examines ways of integrating IK into formal monitoring, how to enhance its value and acceptability. Data was collected through target interviews, group discussions and questionnaires covering 127 households in eight villages. Daily rainfall data from 1961–2003 were analysed. Results show that agro-pastoralists hold IK on indicators of rainfall variability; they believe in IK efficacy and they rely on them. Because agro-pastoralists consult additional sources, the authors interpret that IK forms a basic knowledge frame within which agro-pastoralists position and interpret meteorological forecasts. Only a few agro-pastoralists adapt their practices in anticipation of IK-based forecasts partly due to the conditioning of the actors to the high rainfall variability characteristic of the area and partly due to lack of resources. Non-drought factors such as poverty, inadequate resources and lack of preparedness expose agro-pastoralists to drought impacts and limit their adaptive capacity. These factors need to be understood and effectively addressed to increase agro-pastoralists’ decision options and the influence of IK-based forecasts on their decision-making patterns. The limited intergenerational transfer of IK currently threatens its existence in the longer term. One way to ensure its continued existence and use is to integrate IK into the education curriculum and to link IK with formal climate change research through the participation of the local people. However, further studies are necessary to address the reliability and validity of the identified IK indicators of climate variability and change.

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To increase the sparse knowledge of long-term Southern Hemisphere (SH) climate variability, we assess an ensemble of 4 transient simulations over the last 500 yr performed with a state-of-the-art atmosphere ocean general circulation model. The model is forced with reconstructions of solar irradiance, greenhouse gas (GHG) and volcanic aerosol concentrations. A 1990 control simulation shows that the model is able to represent the Southern Annular Mode (SAM), and to some extent the South Pacific Dipole (SPD) and the Zonal Wave 3 (ZW3). During the past 500 yr we find that SPD and ZW3 variability remain stable, whereas SAM shows a significant shift towards its positive state during the 20th century. Regional temperatures over South America are strongly influenced by changing both GHG concentrations and volcanic eruptions, whereas precipitation shows no significant response to the varying external forcing. For temperature this stands in contrast to proxy records, suggesting that SH climate is dominated by internal variability rather than external forcing. The underlying dynamics of the temperature changes generally point to a combination of several modes, thus, hampering the possibilities of regional reconstructing the modes from proxy records. The linear imprint of the external forcing is as expected, i.e. a warming for increase in the combined solar and GHG forcing and a cooling after volcanic eruptions. Dynamically, only the increase in SAM with increased combined forcing is simulated.

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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.