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Forecasting of ionospheric characteristics during quiet and disturbed conditions
Forecasting procedure quiet and disturbed conditions
2015/9/25
An autocovariance forecasting procedure for single location ionospheric characteristics is presented. Its accuracy is illustrated as a function of the amount of time extrapolation for selected Europea...
Nowcasting, forecasting and warning for ionospheric propagation: tools and methods
Nowcasting ionospheric propagation
2015/9/14
The paper reviews the work done in the course of the COST 271 Action concerned with the development of tools and methods for forecasting, nowcasting and warning of ionospheric propagation conditions. ...
Ensemble Forecasting of Volcanic Emissions in Hawai’i
air quality forecasting ensemble modeling dispersion modeling
2015/8/18
Deterministic model forecasts do not convey to the end users the forecast uncertainty the models possess as a result of physics parameterizations, simplifications in model representation of physical p...
Time-dependent prediction degredation assessment of neural-networks-based TEC forecasting models
Time-dependent prediction degredation assessment neural-networks-based TEC forecasting models
2009/11/12
An estimation of the difference in TEC prediction accuracy achieved when the prediction varies from 1 h to 7 days in advance is described using classical neural networks. Hourly-daily Faraday-rotation...
Initial state perturbations in ensemble forecasting
Initial state perturbations ensemble forecasting
2009/11/2
Due to the chaotic nature of atmospheric dynamics, numerical weather prediction systems are sensitive to errors in the initial conditions. To estimate the forecast uncertainty, forecast centres produc...
Robust nonlinear canonical correlation analysis:application to seasonal climate forecasting
Robust nonlinear canonical correlation analysis seasonal climate
2009/10/30
Robust variants of nonlinear canonical correlation analysis (NLCCA) are introduced to improve performance on datasets with low signal-to-noise ratios, for example those encountered when making seasona...