3 resultados para Input Distance Function

em Publishing Network for Geoscientific


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Improving the representation of the hydrological cycle in Atmospheric General Circulation Models (AGCMs) is one of the main challenges in modeling the Earth's climate system. One way to evaluate model performance is to simulate the transport of water isotopes. Among those available, tritium (HTO) is an extremely valuable tracer, because its content in the different reservoirs involved in the water cycle (stratosphere, troposphere, ocean) varies by order of magnitude. Previous work incorporated natural tritium into LMDZ-iso, a version of the LMDZ general circulation model enhanced by water isotope diagnostics. Here for the first time, the anthropogenic tritium injected by each of the atmospheric nuclear-bomb tests between 1945 and 1980 has been first estimated and further implemented in the model; it creates an opportunity to evaluate certain aspects of LDMZ over several decades by following the bomb-tritium transient signal through the hydrological cycle. Simulations of tritium in water vapor and precipitation for the period 1950-2008, with both natural and anthropogenic components, are presented in this study. LMDZ-iso satisfactorily reproduces the general shape of the temporal evolution of tritium. However, LMDZ-iso simulates too high a bomb-tritium peak followed by too strong a decrease of tritium in precipitation. The too diffusive vertical advection in AGCMs crucially affects the residence time of tritium in the stratosphere. This insight into model performance demonstrates that the implementation of tritium in an AGCM provides a new and valuable test of the modeled atmospheric transport, complementing water stable isotope modeling.

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Sediment dynamics in limnic, fluvial and marine environments can be assessed by granulometric and rock-magnetic methodologies. While classical grain-size analysis by sieving or settling mainly bears information on composition and transport, the magnetic mineral assemblages reflect to a larger extent the petrology and weathering conditions in the sediment source areas. Here, we combine both methods to investigate Late Quaternary marine sediments from five cores along a transect across the continental slope off Senegal. This region near the modern summer Intertropical Convergence Zone is particularly sensitive to climate change and receives sediments from several aeolian, fluvial and marine sources. From each of the investigated five GeoB sediment cores (494-2956 m water depth) two time slices were processed which represent contrasting climatic conditions: the arid Heinrich Stadial 1 (~ 15 kyr BP) and the humid Mid Holocene (~ 6 kyr BP). Each sediment sample was split into 16 grain-size fractions ranging from 1.6 to 500 µm. Concentration and grain-size indicative magnetic parameters (susceptibility, SIRM, HIRM, ARM and ARM/IRM) were determined at room temperature for each of these fractions. The joint consideration of whole sediment and magnetic mineral grain-size distributions allows to address several important issues: (i) distinction of two aeolian sediment fractions, one carried by the north-easterly trade winds (40-63 µm) and the other by the overlying easterly Harmattan wind (10-20 µm) as well as a fluvial fraction assigned to the Senegal River (< 10 µm); (ii) identification of three terrigenous sediment source areas: southern Sahara and Sahel dust (low fine-grained magnetite amounts and a comparatively high haematite content), dust from Senegalese coastal dunes (intermediate fine-grained magnetite and haematite contents) and soils from the upper reaches of the Senegal River (high fine-grained magnetite content); (iii) detection of partial diagenetic dissolution of fine magnetite particles as a function of organic input and shore distance; (iv) analysis of magnetic properties of marine carbonates dominating the grain-size fractions 63-500 µm.

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Metamodels have proven be very useful when it comes to reducing the computational requirements of Evolutionary Algorithm-based optimization by acting as quick-solving surrogates for slow-solving fitness functions. The relationship between metamodel scope and objective function varies between applications, that is, in some cases the metamodel acts as a surrogate for the whole fitness function, whereas in other cases it replaces only a component of the fitness function. This paper presents a formalized qualitative process to evaluate a fitness function to determine the most suitable metamodel scope so as to increase the likelihood of calibrating a high-fidelity metamodel and hence obtain good optimization results in a reasonable amount of time. The process is applied to the risk-based optimization of water distribution systems; a very computationally-intensive problem for real-world systems. The process is validated with a simple case study (modified New York Tunnels) and the power of metamodelling is demonstrated on a real-world case study (Pacific City) with a computational speed-up of several orders of magnitude.