38 resultados para data-driven simulation


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The performance of reanalysis-driven Canadian Regional Climate Model, version 5 (CRCM5) in reproducing the present climate over the North American COordinated Regional climate Downscaling EXperiment domain for the 1989–2008 period has been assessed in comparison with several observation-based datasets. The model reproduces satisfactorily the near-surface temperature and precipitation characteristics over most part of North America. Coastal and mountainous zones remain problematic: a cold bias (2–6 °C) prevails over Rocky Mountains in summertime and all year-round over Mexico; winter precipitation in mountainous coastal regions is overestimated. The precipitation patterns related to the North American Monsoon are well reproduced, except on its northern limit. The spatial and temporal structure of the Great Plains Low-Level Jet is well reproduced by the model; however, the night-time precipitation maximum in the jet area is underestimated. The performance of CRCM5 was assessed against earlier CRCM versions and other RCMs. CRCM5 is shown to have been substantially improved compared to CRCM3 and CRCM4 in terms of seasonal mean statistics, and to be comparable to other modern RCMs.

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The aim of this study was to explore potential causes and mechanisms for the sequence and temporal pattern of tree taxa, specifically for the shift from shrub-tundra to birch–juniper woodland during and after the transition from the Oldest Dryas to the Bølling–Allerød in the region surrounding the lake Gerzensee in southern Central Europe. We tested the influence of climate, forest dynamics, community dynamics compared to other causes for delays. For this aim temperature reconstructed from a δ18O-record was used as input driving the multi-species forest-landscape model TreeMig. In a stepwise scenario analysis, population dynamics along with pollen production and transport were simulated and compared with pollen-influx data, according to scenarios of different δ18O/temperature sensitivities, different precipitation levels, with/without inter-specific competition, and with/without prescribed arrival of species. In the best-fitting scenarios, the effects on competitive relationships, pollen production, spatial forest structure, albedo, and surface roughness were examined in more detail. The appearance of most taxa in the data could only be explained by the coldest temperature scenario with a sensitivity of 0.3‰/°C, corresponding to an anomaly of − 15 °C. Once the taxa were present, their temporal pattern was shaped by competition. The later arrival of Pinus could not be explained even by the coldest temperatures, and its timing had to be prescribed by first observations in the pollen record. After the arrival into the simulation area, the expansion of Pinus was further influenced by competitors and minor climate oscillations. The rapid change in the simulated species composition went along with a drastic change in forest structure, leaf area, albedo, and surface roughness. Pollen increased only shortly after biomass. Based on our simulations, two alternative potential scenarios for the pollen pattern can be given: either very cold climate suppressed most species in the Oldest Dryas, or they were delayed by soil formation or migration. One taxon, Pinus, was delayed by migration and then additionally hindered by competition. Community dynamics affected the pattern in two ways: potentially by facilitation, i.e. by nitrogen-fixing pioneer species at the onset, whereas the later pattern was clearly shaped by competition. The simulated structural changes illustrate how vegetation on a larger scale could feed back to the climate system. For a better understanding, a more integrated simulation approach covering also the immigration from refugia would be necessary, for this combines climate-driven population dynamics, migration, individual pollen production and transport, soil dynamics, and physiology of individual pollen production.

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We consider a large quantum system with spins 12 whose dynamics is driven entirely by measurements of the total spin of spin pairs. This gives rise to a dissipative coupling to the environment. When one averages over the measurement results, the corresponding real-time path integral does not suffer from a sign problem. Using an efficient cluster algorithm, we study the real-time evolution from an initial antiferromagnetic state of the two-dimensional Heisenberg model, which is driven to a disordered phase, not by a Hamiltonian, but by sporadic measurements or by continuous Lindblad evolution.

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Using quantum Monte Carlo, we study the nonequilibrium transport of magnetization in large open strongly correlated quantum spin-12 systems driven by purely dissipative processes that conserve the uniform or staggered magnetization, disregarding unitary Hamiltonian dynamics. We prepare both a low-temperature Heisenberg ferromagnet and an antiferromagnet in two parts of the system that are initially isolated from each other. We then bring the two subsystems in contact and study their real-time dissipative dynamics for different geometries. The flow of the uniform or staggered magnetization from one part of the system to the other is described by a diffusion equation that can be derived analytically.

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Syndromic surveillance (SyS) systems currently exploit various sources of health-related data, most of which are collected for purposes other than surveillance (e.g. economic). Several European SyS systems use data collected during meat inspection for syndromic surveillance of animal health, as some diseases may be more easily detected post-mortem than at their point of origin or during the ante-mortem inspection upon arrival at the slaughterhouse. In this paper we use simulation to evaluate the performance of a quasi-Poisson regression (also known as an improved Farrington) algorithm for the detection of disease outbreaks during post-mortem inspection of slaughtered animals. When parameterizing the algorithm based on the retrospective analyses of 6 years of historic data, the probability of detection was satisfactory for large (range 83-445 cases) outbreaks but poor for small (range 20-177 cases) outbreaks. Varying the amount of historical data used to fit the algorithm can help increasing the probability of detection for small outbreaks. However, while the use of a 0·975 quantile generated a low false-positive rate, in most cases, more than 50% of outbreak cases had already occurred at the time of detection. High variance observed in the whole carcass condemnations time-series, and lack of flexibility in terms of the temporal distribution of simulated outbreaks resulting from low reporting frequency (monthly), constitute major challenges for early detection of outbreaks in the livestock population based on meat inspection data. Reporting frequency should be increased in the future to improve timeliness of the SyS system while increased sensitivity may be achieved by integrating meat inspection data into a multivariate system simultaneously evaluating multiple sources of data on livestock health.

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Application of pressure-driven laminar flow has an impact on zone and boundary dispersion in open tubular CE. The GENTRANS dynamic simulator for electrophoresis was extended with Taylor-Aris diffusivity which accounts for dispersion due to the parabolic flow profile associated with pressure-driven flow. Effective diffusivity of analyte and system zones as functions of the capillary diameter and the amount of flow in comparison to molecular diffusion alone were studied for configurations with concomitant action of imposed hydrodynamic flow and electroosmosis. For selected examples under realistic experimental conditions, simulation data are compared with those monitored experimentally using modular CE setups featuring both capacitively coupled contactless conductivity and UV absorbance detection along a 50 μm id fused-silica capillary of 90 cm total length. The data presented indicate that inclusion of flow profile based Taylor-Aris diffusivity provides realistic simulation data for analyte and system peaks, particularly those monitored in CE with conductivity detection.