단기 앙상블 예보에서 모형의 불확실성 표현: 태풍 루사
Representation of Model Uncertainty in the Short-Range Ensemble Prediction for Typhoon Rusa (2002)
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The most objective way to overcome the limitation of numerical weather predictionmodel is to represent the uncertainty of prediction by introducing probabilistic forecast. The uncertainty of the numerical weather prediction system developed due to the parameterizationof unresolved scale motions and the energy losses from the sub-scale physical processes. In this study, we focused on the growth of model errors. We performed ensemble forecast torepresent model uncertainty. By employing the multi-physics scheme (PHYS) and the stochastickinetic energy backscatter scheme (SKEBS) in simulating typhoon Rusa (2002), weassessed the performance level of the two schemes. The both schemes produced better resultsthan the control run did in the ensemble mean forecast of the track. The results using PHYSimproved by 28% and those based on SKEBS did by 7%. Both of the ensemble mean errors ofthe both schemes increased rapidly at the forecast time 84 hrs. The both ensemble spreadsincreased gradually during integration. The results based on SKEBS represented model errorsvery well during the forecast time of 96 hrs. After the period, it produced an under-dispersivepattern. The simulation based on PHYS overestimated the ensemble mean error during integrationand represented the real situation well at the forecast time of 120 hrs. The displacementspeed of the typhoon based on PHYS was closest to the best track, especially after landfall. Inthe sensitivity tests of the model uncertainty of SKEBS, ensemble mean forecast was sensitiveto the physics parameterization. By adjusting the forcing parameter of SKEBS, the defaultexperiment improved in the ensemble spread, ensemble mean errors, and moving speed.
Abstract
The most objective way to overcome the limitation of numerical weather predictionmodel is to represent the uncertainty of prediction by introducing probabilistic forecast. The uncertainty of the numerical weather prediction system developed due to the parameterizationof unresolved scale motions and the energy losses from the sub-scale physical processes. In this study, we focused on the growth of model errors. We performed ensemble forecast torepresent model uncertainty. By employing the multi-physics scheme (PHYS) and the stochastickinetic energy backscatter scheme (SKEBS) in simulating typhoon Rusa (2002), weassessed the performance level of the two schemes. The both schemes produced better resultsthan the control run did in the ensemble mean forecast of the track. The results using PHYSimproved by 28% and those based on SKEBS did by 7%. Both of the ensemble mean errors ofthe both schemes increased rapidly at the forecast time 84 hrs. The both ensemble spreadsincreased gradually during integration. The results based on SKEBS represented model errorsvery well during the forecast time of 96 hrs. After the period, it produced an under-dispersivepattern. The simulation based on PHYS overestimated the ensemble mean error during integrationand represented the real situation well at the forecast time of 120 hrs. The displacementspeed of the typhoon based on PHYS was closest to the best track, especially after landfall. Inthe sensitivity tests of the model uncertainty of SKEBS, ensemble mean forecast was sensitiveto the physics parameterization. By adjusting the forcing parameter of SKEBS, the defaultexperiment improved in the ensemble spread, ensemble mean errors, and moving speed.
참고문헌 (17)
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