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Relevant bibliographies by topics / Reliability ensemble average

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Academic literature on the topic 'Reliability ensemble average'

Author: Grafiati

Published: 4 June 2021

Last updated: 17 February 2022

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Journal articles on the topic "Reliability ensemble average"

1

Velázquez, J. A., F. Anctil, and C. Perrin. "Performance and reliability of multimodel hydrological ensemble simulations based on seventeen lumped models and a thousand catchments." Hydrology and Earth System Sciences 14, no. 11 (2010): 2303–17. http://dx.doi.org/10.5194/hess-14-2303-2010.

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Abstract. This work investigates the added value of ensembles constructed from seventeen lumped hydrological models against their simple average counterparts. It is thus hypothesized that there is more information provided by all the outputs of these models than by their single aggregated predictors. For all available 1061 catchments, results showed that the mean continuous ranked probability score of the ensemble simulations were better than the mean average error of the aggregated simulations, confirming the added value of retaining all the components of the model outputs. Reliability of the

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Velázquez, J. A., F. Anctil, and C. Perrin. "Performance and reliability of multimodel hydrological ensemble simulations based on seventeen lumped models and a thousand catchments." Hydrology and Earth System Sciences Discussions 7, no. 3 (2010): 4023–58. http://dx.doi.org/10.5194/hessd-7-4023-2010.

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Abstract. This work investigates the added value of ensembles constructed from seventeen lumped hydrological models against their simple average counterparts. It is thus hypothesized that there is more information provided by all the outputs of these models than by their single aggregated predictors. For all available 1061 catchments, results showed that the mean continuous ranked probability score of the ensemble simulations were better than the mean average error of the aggregated simulations, confirming the added value of retaining all the components of the model outputs. Reliability of the

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Fortin, V., M. Abaza, F. Anctil, and R. Turcotte. "Why Should Ensemble Spread Match the RMSE of the Ensemble Mean?" Journal of Hydrometeorology 15, no. 4 (2014): 1708–13. http://dx.doi.org/10.1175/jhm-d-14-0008.1.

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Abstract When evaluating the reliability of an ensemble prediction system, it is common to compare the root-mean-square error of the ensemble mean to the average ensemble spread. While this is indeed good practice, two different and inconsistent methodologies have been used over the last few years in the meteorology and hydrology literature to compute the average ensemble spread. In some cases, the square root of average ensemble variance is used, and in other cases, the average of ensemble standard deviation is computed instead. The second option is incorrect. To avoid the perpetuation of pra

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Atger, F. "Relative impact of model quality and ensemble deficiencies on the performance of ensemble based probabilistic forecasts evaluated through the Brier score." Nonlinear Processes in Geophysics 11, no. 3 (2004): 399–409. http://dx.doi.org/10.5194/npg-11-399-2004.

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Abstract. The relative impact of model quality and ensemble deficiencies, on the performance of ensemble based probabilistic forecasts, is investigated from a set of idealized experiments. Data are generated according to a statistical model, the validation of which is achieved by comparing generated data to ECMWF ensemble forecasts and analyses. The performance of probabilistic forecasts is evaluated through the reliability and resolution terms of the Brier score. Results are as follows. (i) Resolution appears essentially attributable to the average level of forecast skill. (ii) The lack of re

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Multsch, S., J. F. Exbrayat, M. Kirby, N. R. Viney, H. G. Frede, and L. Breuer. "Reduction of predictive uncertainty in estimating irrigation water requirement through multi-model ensembles and ensemble averaging." Geoscientific Model Development Discussions 7, no. 6 (2014): 7525–58. http://dx.doi.org/10.5194/gmdd-7-7525-2014.

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Abstract. Irrigation agriculture plays an increasingly important role in food supply. Many evapotranspiration models are used today to estimate the water demand for irrigation. They consider different stages of crop growth by empirical crop coefficients to adapt evapotranspiration throughout the vegetation period. We investigate the importance of the model structural vs. model parametric uncertainty for irrigation simulations by considering six evapotranspiration models and five crop coefficient sets to estimate irrigation water requirements for growing wheat in the Murray-Darling Basin, Austr

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Multsch, S., J. F. Exbrayat, M. Kirby, N. R. Viney, H. G. Frede, and L. Breuer. "Reduction of predictive uncertainty in estimating irrigation water requirement through multi-model ensembles and ensemble averaging." Geoscientific Model Development 8, no. 4 (2015): 1233–44. http://dx.doi.org/10.5194/gmd-8-1233-2015.

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Abstract. Irrigation agriculture plays an increasingly important role in food supply. Many evapotranspiration models are used today to estimate the water demand for irrigation. They consider different stages of crop growth by empirical crop coefficients to adapt evapotranspiration throughout the vegetation period. We investigate the importance of the model structural versus model parametric uncertainty for irrigation simulations by considering six evapotranspiration models and five crop coefficient sets to estimate irrigation water requirements for growing wheat in the Murray–Darling Basin, Au

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Giorgi, Filippo, and Linda O. Mearns. "Calculation of Average, Uncertainty Range, and Reliability of Regional Climate Changes from AOGCM Simulations via the “Reliability Ensemble Averaging” (REA) Method." Journal of Climate 15, no. 10 (2002): 1141–58. http://dx.doi.org/10.1175/1520-0442(2002)015<1141:coaura>2.0.co;2.

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Sacher, William, and Peter Bartello. "Sampling Errors in Ensemble Kalman Filtering. Part II: Application to a Barotropic Model." Monthly Weather Review 137, no. 5 (2009): 1640–54. http://dx.doi.org/10.1175/2008mwr2685.1.

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Abstract In the current study, the authors are concerned with the comparison of the average performance of stochastic versions of the ensemble Kalman filter with and without covariance inflation, as well as the double ensemble Kalman filter. The theoretical results obtained in Part I of this study are confronted with idealized simulations performed with a perfect barotropic quasigeostrophic model. Results obtained are very consistent with the analytic expressions found in Part I. It is also shown that both the double ensemble Kalman filter and covariance inflation techniques can avoid filter d

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Exbrayat, J. F., N. R. Viney, H. G. Frede, and L. Breuer. "Using multi-model averaging to improve the reliability of catchment scale nitrogen predictions." Geoscientific Model Development 6, no. 1 (2013): 117–25. http://dx.doi.org/10.5194/gmd-6-117-2013.

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Abstract. Hydro-biogeochemical models are used to foresee the impact of mitigation measures on water quality. Usually, scenario-based studies rely on single model applications. This is done in spite of the widely acknowledged advantage of ensemble approaches to cope with structural model uncertainty issues. As an attempt to demonstrate the reliability of such multi-model efforts in the hydro-biogeochemical context, this methodological contribution proposes an adaptation of the reliability ensemble averaging (REA) philosophy to nitrogen losses predictions. A total of 4 models are used to predic

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Exbrayat, J. F., N. R. Viney, H. G. Frede, and L. Breuer. "Using multi-model averaging to improve the reliability of catchment scale nitrogen predictions." Geoscientific Model Development Discussions 5, no. 3 (2012): 2289–310. http://dx.doi.org/10.5194/gmdd-5-2289-2012.

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Abstract. Hydro-biogeochemical models are used to foresee the impact of mitigation measures on water quality. Usually, scenario-based studies rely on single model applications. This is done in spite of the widely acknowledged advantage of ensemble approaches to cope with structural model uncertainty issues. As an attempt to demonstrate the reliability of such multi-model efforts in the hydro-biogeochemical context, this methodological contribution proposes an adaptation of the Reliability Ensemble Averaging (REA) philosophy to nitrogen losses predictions. A total of 4 models are used to predic

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Dissertations / Theses on the topic "Reliability ensemble average"

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"The Shift of Precipitation Maxima on the Annual Maximum Series using Regional Climate Model Precipitation Data." Master's thesis, 2013. http://hdl.handle.net/2286/R.I.20926.

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abstract: Ten regional climate models (RCMs) and atmosphere-ocean generalized model parings from the North America Regional Climate Change Assessment Program were used to estimate the shift of extreme precipitation due to climate change using present-day and future-day climate scenarios. RCMs emulate winter storms and one-day duration events at the sub-regional level. Annual maximum series were derived for each model pairing, each modeling period; and for annual and winter seasons. The reliability ensemble average (REA) method was used to qualify each RCM annual maximum series to reproduce his

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Conference papers on the topic "Reliability ensemble average"

1

Kusano, Kazuya, Hironobu Yamakawa, and Kunihiko Ikeda. "Estimation of Uncertain Parameters for Thermal and Fluid Analysis in Engine Room of Construction Machinery Using Data Assimilation." In ASME 2016 Fluids Engineering Division Summer Meeting collocated with the ASME 2016 Heat Transfer Summer Conference and the ASME 2016 14th International Conference on Nanochannels, Microchannels, and Minichannels. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/fedsm2016-7898.

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Recently, the cooling system of hydraulic excavator is often designed using the thermal and fluid analysis to improve the cooling performance. The reliability of the analysis results is important, since it directly influences on the efficiency of development. In the present study, the uncertain parameters were estimated using the data assimilation method to increase the reliability of the thermal and fluid analysis in an engine room of a hydraulic excavator. The ensemble Kalman filter (EnKF) was adapted as a data assimilation method, and the thermal and fluid analysis was conducted with the th

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Croce, Pietro, Paolo Formichi, and Filippo Landi. "Structural safety and design under climate change." In IABSE Congress, New York, New York 2019: The Evolving Metropolis. International Association for Bridge and Structural Engineering (IABSE), 2019. http://dx.doi.org/10.2749/newyork.2019.1129.

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<p>The impact of climate change on climatic actions could significantly affect, in the mid-term future, the design of new structures as well as the reliability of existing ones designed in accordance to the provisions of present and past codes. Indeed, current climatic loads are defined under the assumption of stationary climate conditions but climate is not stationary and the current accelerated rate of changes imposes to consider its effects.</p><p>Increase of greenhouse gas emissions generally induces a global increase of the average temperature, but at local scale, the co

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Lepicovsky, J. "Application of a Split-Fiber Probe to Velocity Measurement in the NASA Research Compressor." In ASME/JSME 2003 4th Joint Fluids Summer Engineering Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/fedsm2003-45607.

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A split-fiber probe was used to acquire unsteady data in a research compressor. The probe has two thin films deposited on a quartz cylinder 200 μm in diameter. A split-fiber probe allows simultaneous measurement of velocity magnitude and direction in a plane that is perpendicular to the sensing cylinder, because it has its circumference divided into two independent parts. Local heat transfer considerations indicated that the probe direction characteristic is linear in the range of flow incidence angles of ±35 dg. Calibration tests confirmed this assumption. Of course, the velocity characterist

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