The numerical results show that there are signicicant uncertainties in the evolution of horizontal structure,rain,cloud prognostic variables and thermal and dyinamical fields. Therefore,explicit forecasts of precipitation,especially ensemble prediction of precpitation,should be performed together with the estimation of different uncertainties of different explicit schemes.
Ensemble prediction experiments and verifications for precipitation are made during 16 August to 30 September of 2004. The results show that the ensemble prediction can increase prediction accuracy of precipitation over 25mm.
The ensemble forecasting experiments by a GCM, IAP T42L9 show that the anomalous heating over the tropics, especially over the central-western Pacific and Atlantic, favors the formation of positive anomalies of height at the Ural region.
The sensitivity of prediction to the initial conditions and the problem of ensemble prediction are also discussed in the paper.
In particular, three types of multi-model ensemble prediction systems, i.e., the simple composite, superensemble, and the composite after statistically correcting individual predictions (corrected composite), are examined and compared to each other.
IAP DCP-II employs ensemble prediction with dynamically conditioned perturbations to reduce the uncertainty associated with seasonal climate prediction.
In particular, seasonal ensemble prediction of watershed variables stands to gain from conditioning on high-temporal resolution climate forecasts.
Finally, all kinds of economic variables, the outputs of linear and nonlinear EC-VAR models and judgmental adjustment model are used as input variables of a typical kernel-based support vector regression (SVR) for ensemble prediction purpose.
Ensemble forecasting of tropical cyclone motion using a baroclinic model
The purpose of this study is to investigate the effectiveness of two different ensemble forecasting (EF) techniques-the lagged-averaged forecast (LAF) and the breeding of growing modes (BGM).
The BFS is compared with Monte Carlo simulation and "ensemble forecasting" technique, none of which can alone produce a probabilistic forecast that quantifies the total uncertainty, but each can serve as a component of the BFS.
Ensemble forecasting of tropical cyclone motion: comparisonbetween regional bred modes and random perturbations
Ensemble forecasting of tropical cyclone motion using a barotropic model.
(3) The ensemble forecast method can effectively improve prediction results.
Only the relative skill of the ensemble forecast mean over the control run is used to evaluate the effectiveness of the EF methods, although the EF technique is also used to quantify forecast uncertainty in some studies.
Additionally, the ensemble forecast approach was also used for the prediction of a tropical typhoons.
Long-term ensemble forecast of snowmelt runoff with the help of the physics-based models of runoff generation
An ensemble forecast exercise is also carried out to check model stability in reference to the uncertainty of input quantities.