.png){kind=icon}
Return
Ensemble forecasting
.png){kind=icon}
PRE
AI
DOI：10.1016/j.jcp.2007.02.014.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Numerical weather prediction models as well as the atmosphere itself can be viewed as nonlinear dynamical systems in which the evolution depends sensitively on the initial conditions. The fact that estimates of the current state are inaccurate and that numerical models have inadequacies, leads to forecast errors that grow with increasing forecast lead time. The growth of errors depends on the flow itself. Ensemble forecasting aims at quantifying this flow-dependent forecast uncertainty. The sources of uncertainty in weather forecasting are discussed. Then, an overview is given on evaluating probabilistic forecasts and their usefulness compared with single forecasts. Thereafter, the representation of uncertainties in ensemble forecasts is reviewed with an emphasis on the initial condition perturbations. The review is complemented by a detailed description of the methodology to generate initial condition perturbations of the Ensemble Prediction System (EPS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). These perturbations are based on the leading part of the singular value decomposition of the operator describing the linearised dynamics over a finite time interval. The perturbations are flow-dependent as the linearisation is performed with respect to a solution of the nonlinear forecast model. The extent to which the current ECMWF ensemble prediction system is capable of predicting flow-dependent variations in uncertainty is assessed for the large-scale flow in mid-latitudes. (c) 2007 Elsevier Inc. All rights reserved.
Keywords:
uncertainty
numerical weather prediction
predictability
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.8
Papers:
1.6W
Citations:
7.4W
Organization
No organization information available
Cited Papers
ShareSave
ShareSave
ShareSaveShareSaveShareSavePartly quenched, synchronously excited fluorescence emission spectra in the characterisation of complex mixtures.png)
The Analyst
The AnalystIF0
PREAI
ShareSave
View more