Lord Liverpool and Liberal Toryism, 1820-1827
In: The Economic Journal, Band 52, Heft 205, S. 69
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In: The Economic Journal, Band 52, Heft 205, S. 69
In: The economic history review, Band 12, Heft 1/2, S. 106
ISSN: 1468-0289
In: Pelican books A 1054
In: U Denver Legal Studies Research Paper No. 17-25
SSRN
Working paper
In: International affairs, Band 25, Heft 3, S. 346
ISSN: 1468-2346
World Affairs Online
In: South African Institute of Race Relations, The 14. Hoernlé Memorial Lecture
In: Political science, Band 51, Heft 1, S. 92
ISSN: 0112-8760, 0032-3187
In: Social history, Band 24, Heft 1, S. 55-73
ISSN: 1470-1200
In: Environmental and ecological statistics 3
In: Natural hazards and earth system sciences: NHESS, Band 18, Heft 1, S. 41-63
ISSN: 1684-9981
Abstract. Following the disruption to European airspace caused by the eruption of Eyjafjallajökull in 2010 there has been a move towards producing quantitative predictions of volcanic ash concentration using volcanic ash transport and dispersion simulators. However, there is no formal framework for determining the uncertainties of these predictions and performing many simulations using these complex models is computationally expensive. In this paper a Bayesian linear emulation approach is applied to the Numerical Atmospheric-dispersion Modelling Environment (NAME) to better understand the influence of source and internal model parameters on the simulator output. Emulation is a statistical method for predicting the output of a computer simulator at new parameter choices without actually running the simulator. A multi-level emulation approach is applied using two configurations of NAME with different numbers of model particles. Information from many evaluations of the computationally faster configuration is combined with results from relatively few evaluations of the slower, more accurate, configuration. This approach is effective when it is not possible to run the accurate simulator many times and when there is also little prior knowledge about the influence of parameters. The approach is applied to the mean ash column loading in 75 geographical regions on 14 May 2010. Through this analysis it has been found that the parameters that contribute the most to the output uncertainty are initial plume rise height, mass eruption rate, free tropospheric turbulence levels and precipitation threshold for wet deposition. This information can be used to inform future model development and observational campaigns and routine monitoring. The analysis presented here suggests the need for further observational and theoretical research into parameterisation of atmospheric turbulence. Furthermore it can also be used to inform the most important parameter perturbations for a small operational ensemble of simulations. The use of an emulator also identifies the input and internal parameters that do not contribute significantly to simulator uncertainty. Finally, the analysis highlights that the faster, less accurate, configuration of NAME can, on its own, provide useful information for the problem of predicting average column load over large areas.
In: RECYCL-D-22-04701
SSRN
In: Political studies: the journal of the Political Studies Association of the United Kingdom, Band 14, Heft 2, S. 228-280
ISSN: 1467-9248