L
Leonard A. Smith
Researcher at London School of Economics and Political Science
Publications - 153
Citations - 10059
Leonard A. Smith is an academic researcher from London School of Economics and Political Science. The author has contributed to research in topics: Ensemble forecasting & Consensus forecast. The author has an hindex of 44, co-authored 151 publications receiving 9346 citations. Previous affiliations of Leonard A. Smith include Goddard Institute for Space Studies & University of Florida.
Papers
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Journal ArticleDOI
Uncertainty in predictions of the climate response to rising levels of greenhouse gases.
David A. Stainforth,T. Aina,C. Christensen,Matthew Collins,N. Faull,David J. Frame,J. A. Kettleborough,Simon R. Knight,Andrew J. Martin,James M. Murphy,C. Piani,David M. H. Sexton,Leonard A. Smith,Robert A. Spicer,Alan J. Thorpe,Myles R. Allen +15 more
TL;DR: Results from the ‘climateprediction.net’ experiment are presented, the first multi-thousand-member grand ensemble of simulations using a general circulation model and thereby explicitly resolving regional details, finding model versions as realistic as other state-of-the-art climate models but with climate sensitivities ranging from less than 2 K to more than 11’K.
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A dynamical model for generating synthetic electrocardiogram signals
TL;DR: A dynamical model based on three coupled ordinary differential equations is introduced which is capable of generating realistic synthetic electrocardiogram (ECG) signals and may be employed to assess biomedical signal processing techniques which are used to compute clinical statistics from the ECG.
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Monte Carlo SSA: Detecting irregular oscillations in the Presence of Colored Noise
Myles R. Allen,Leonard A. Smith +1 more
TL;DR: In this paper, the Monte Carlo Singular Systems Analysis (SSA) algorithm is used to identify intermittent or modulated oscillations in geophysical and climatic time series, and the results show that the strength of the evidence provided by SSA for interannual and interdecadal climate oscillations has been considerably overestimated.
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Confidence, uncertainty and decision-support relevance in climate predictions.
TL;DR: A reassessment of the role of complex climate models as predictive tools on decadal and longer time scales is argued for and a reconsideration of strategies for model development and experimental design is considered.
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Intrinsic limits on dimension calculations
TL;DR: In this paper, a lower bound on the number of points required for reliable estimation of the correlation exponent is given in terms of the dimension of the object and the desired accuracy, and a method of estimating the correlation integral computed from a finite sample of a white noise signal is given.