62,137 research outputs found
The ECMWF Ensemble Prediction System: Looking Back (more than) 25 Years and Projecting Forward 25 Years
This paper has been written to mark 25 years of operational medium-range
ensemble forecasting. The origins of the ECMWF Ensemble Prediction System are
outlined, including the development of the precursor real-time Met Office
monthly ensemble forecast system. In particular, the reasons for the
development of singular vectors and stochastic physics - particular features of
the ECMWF Ensemble Prediction System - are discussed. The author speculates
about the development and use of ensemble prediction in the next 25 years.Comment: Submitted to Special Issue of the Quarterly Journal of the Royal
Meteorological Society: 25 years of ensemble predictio
Estimating the uncertainty of areal precipitation using data assimilation
We present a method to estimate spatially and temporally variable uncertainty of areal precipitation data. The aim of the method is to merge measurements from different sources, remote sensing and in situ, into a combined precipitation product and to provide an associated dynamic uncertainty estimate. This estimate should provide an accurate representation of uncertainty both in time and space, an adjustment to additional observations merged into the product through data assimilation, and flow dependency. Such a detailed uncertainty description is important for example to generate precipitation ensembles for probabilistic hydrological modelling or to specify accurate error covariances when using precipitation observations for data assimilation into numerical weather prediction models. The presented method uses the Local Ensemble Transform Kalman Filter and an ensemble nowcasting model. The model provides information about the precipitation displacement over time and is continuously updated by assimilation of observations. In this way, the precipitation product and its uncertainty estimate provided by the nowcasting ensemble evolve consistently in time and become flow-dependent. The method is evaluated in a proof of concept study focusing on weather radar data of four precipitation events. The study demonstrates that the dynamic areal uncertainty estimate outperforms a constant benchmark uncertainty value in all cases for one of the evaluated scores, and in half the number of cases for the other score. Thus, the flow dependency introduced by the coupling of data assimilation and nowcasting enables a more accurate spatial and temporal distribution of uncertainty. The mixed results achieved in the second score point out the importance of a good probabilistic nowcasting scheme for the performance of the method
Data-driven nonparametric Li-ion battery ageing model aiming at learning from real operation data – Part A : storage operation
Conventional Li-ion battery ageing models, such as electrochemical, semi-empirical and empirical models, require a significant amount of time and experimental resources to provide accurate predictions under realistic operating conditions. At the same time, there is significant interest from industry in the introduction of new data collection telemetry technology. This implies the forthcoming availability of a significant amount of real-world battery operation data. In this context, the development of ageing models able to learn from in-field battery operation data is an interesting solution to mitigate the need for exhaustive laboratory testing
Intensity mapping with neutral hydrogen and the Hidden Valley simulations
This paper introduces the Hidden Valley simulations, a set of
trillion-particle N-body simulations in gigaparsec volumes aimed at intensity
mapping science. We present details of the simulations and their convergence,
then specialize to the study of 21-cm fluctuations between redshifts 2 and 6.
Neutral hydrogen is assigned to halos using three prescriptions, and we
investigate the clustering in real and redshift-space at the 2-point level. In
common with earlier work we find the bias of HI increases from near 2 at z = 2
to 4 at z = 6, becoming more scale dependent at high z. The level of
scale-dependence and decorrelation with the matter field are as predicted by
perturbation theory. Due to the low mass of the hosting halos, the impact of
fingers of god is small on the range relevant for proposed 21-cm instruments.
We show that baryon acoustic oscillations and redshift-space distortions could
be well measured by such instruments. Taking advantage of the large simulation
volume, we assess the impact of fluctuations in the ultraviolet background,
which change HI clustering primarily at large scales.Comment: 36 pages, 21 figures. Simulations available at
http://cyril.astro.berkeley.edu/HiddenValley/ Minor changes in HI
normalization described in footnote of section
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