An Ensemble Forecast of the South China Sea Monsoon

T. N. Krishnamurti; Mukul Tewari; Ed Bensman; Wei Han; Zhan Zhang; William K. M. Lau

doi:10.1007/BF02973080

Impact Factor: 5.8

Volume 16 Issue 2

Apr. 1999

Article Contents

Article > ADVANCES IN ATMOSPHERIC SCIENCES > 1999 > 16(2): 159-182

An Ensemble Forecast of the South China Sea Monsoon

1.
Department of Meteorology, Florida State University, Tallahassee, FL 32306-4250,Department of Meteorology, Florida State University, Tallahassee, FL 32306-4250,Department of Meteorology, Florida State University, Tallahassee, FL 32306-4250,Department of Meteorology, Florida State University, Tallahassee, FL 32306-4250,Department of Meteorology, Florida State University, Tallahassee, FL 32306-4250,Climate and Radiation Branch, Code 913, NASA Goddard Space Flight Center Creenbelt, MD 20771

doi: 10.1007/BF02973080

Abstract
References
Related papers
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Abstract:
This paper presents a generalized ensemble forecast procedure for the tropical latitudes. Here we propose an empirical orthogonal function-based procedure for the definition of a seven-mem-ber ensemble. The wind and the temperature fields are perturbed over the global tropics. Although the forecasts are made over the global belt with a high-resolution model, the emphasis of this study is on a South China Sea monsoon. Over this domain of the South China Sea includes the passage of a Tropical Storm, Gary, that moved eastwards north of the Philippines. The ensemble forecast handled the precipitation of this storm reasonably well. A global model at the resolution Triangular Truncation 126 waves is used to carry out these seven forecasts. The evaluation of the ensemble of forecasts is carried out via standard root mean square errors of the precipitation and the wind fields. The ensemble average is shown to have a higher skill compared to a control exper?iment, which was a first analysis based on operational data sets over both the global tropical and South China Sea domain. All of these experiments were subjected to physical initialization which provides a spin-up of the model rain close to that obtained from satellite and gauge-based esti?mates. The results furthermore show that inherently much higher skill resides in the forecast pre?cipitation fields if they are averaged over area elements of the order of 4o latitude by 4o longitude squares.
- Ensemble forecast,
- Triangular truncation
References

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Manuscript History

Manuscript received: 10 April 1999

Manuscript revised: 10 April 1999

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

An Ensemble Forecast of the South China Sea Monsoon

1. Department of Meteorology, Florida State University, Tallahassee, FL 32306-4250,Department of Meteorology, Florida State University, Tallahassee, FL 32306-4250,Department of Meteorology, Florida State University, Tallahassee, FL 32306-4250,Department of Meteorology, Florida State University, Tallahassee, FL 32306-4250,Department of Meteorology, Florida State University, Tallahassee, FL 32306-4250,Climate and Radiation Branch, Code 913, NASA Goddard Space Flight Center Creenbelt, MD 20771

Manuscript received: 1999-04-10
Manuscript revised: 1999-04-10

Abstract: This paper presents a generalized ensemble forecast procedure for the tropical latitudes. Here we propose an empirical orthogonal function-based procedure for the definition of a seven-mem-ber ensemble. The wind and the temperature fields are perturbed over the global tropics. Although the forecasts are made over the global belt with a high-resolution model, the emphasis of this study is on a South China Sea monsoon. Over this domain of the South China Sea includes the passage of a Tropical Storm, Gary, that moved eastwards north of the Philippines. The ensemble forecast handled the precipitation of this storm reasonably well. A global model at the resolution Triangular Truncation 126 waves is used to carry out these seven forecasts. The evaluation of the ensemble of forecasts is carried out via standard root mean square errors of the precipitation and the wind fields. The ensemble average is shown to have a higher skill compared to a control exper?iment, which was a first analysis based on operational data sets over both the global tropical and South China Sea domain. All of these experiments were subjected to physical initialization which provides a spin-up of the model rain close to that obtained from satellite and gauge-based esti?mates. The results furthermore show that inherently much higher skill resides in the forecast pre?cipitation fields if they are averaged over area elements of the order of 4o latitude by 4o longitude squares.

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