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: 3.9

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

[1]	LI Shan, RONG Xingyao, LIU Yun, LIU Zhengyu, Klaus FRAEDRICH, 2013: Dynamic Analogue Initialization for Ensemble Forecasting, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 1406-1420. doi: 10.1007/s00376-012-2244-z
[2]	ZHU Jiang, LIN Caiyan, WANG Zifa, 2009: Dust Storm Ensemble Forecast Experiments in East Asia, ADVANCES IN ATMOSPHERIC SCIENCES, 26, 1053-1070. doi: 10.1007/s00376-009-8218-0
[3]	Yuejian ZHU, 2005: Ensemble Forecast: A New Approach to Uncertainty and Predictability, ADVANCES IN ATMOSPHERIC SCIENCES, 22, 781-788. doi: 10.1007/BF02918678
[4]	Saleh AMINYAVARI, Bahram SAGHAFIAN, Majid DELAVAR, 2018: Evaluation of TIGGE Ensemble Forecasts of Precipitation in Distinct Climate Regions in Iran, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 457-468. doi: 10.1007/s00376-017-7082-6
[5]	Zhenhua HUO, Wansuo DUAN, Feifan ZHOU, 2019: Ensemble Forecasts of Tropical Cyclone Track with Orthogonal Conditional Nonlinear Optimal Perturbations, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 231-247. doi: 10.1007/s00376-018-8001-1
[6]	Jihang LI, Zhiyan ZHANG, Lu LIU, Xubin ZHANG, Jingxuan QU, Qilin WAN, 2021: The Simulation of Five Tropical Cyclones by Sample Optimization of Ensemble Forecasting Based on the Observed Track and Intensity, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 1763-1777. doi: 10.1007/s00376-021-0353-2
[7]	Jiangshan ZHU, Fanyou KONG, Xiao-Ming HU, Yan GUO, Lingkun RAN, Hengchi LEI, 2018: Impact of Soil Moisture Uncertainty on Summertime Short-range Ensemble Forecasts, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 839-852. doi: 10.1007/s00376-017-7107-1
[8]	Lili LEI, Yangjinxi GE, Zhe-Min TAN, Yi ZHANG, Kekuan CHU, Xin QIU, Qifeng QIAN, 2022: Evaluation of a Regional Ensemble Data Assimilation System for Typhoon Prediction, ADVANCES IN ATMOSPHERIC SCIENCES, 39, 1816-1832. doi: 10.1007/s00376-022-1444-4
[9]	Jian RAO, Rongcai REN, Haishan CHEN, Xiangwen LIU, Yueyue YU, Yang YANG, 2019: Sub-seasonal to Seasonal Hindcasts of Stratospheric Sudden Warming by BCC_CSM1.1(m): A Comparison with ECMWF, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 479-494. doi: 10.1007/s00376-018-8165-8
[10]	Wu Aiming, Ni Yunqi, 1999: A Hybrid Coupled Ocean-Atmosphere Model and ENSO Prediction Study, ADVANCES IN ATMOSPHERIC SCIENCES, 16, 405-418. doi: 10.1007/s00376-999-0019-y
[11]	Guo DENG, Yuejian ZHU, Jiandong GONG, Dehui CHEN, Richard WOBUS, Zhe ZHANG, 2016: The Effects of Land Surface Process Perturbations in a Global Ensemble Forecast System, ADVANCES IN ATMOSPHERIC SCIENCES, 33, 1199-1208. doi: 10.1007/s00376-016-6036-8
[12]	Sijia LI, Yuan WANG, Huiling YUAN, Jinjie SONG, Xin XU, 2016: Ensemble Mean Forecast Skill and Applications with the T213 Ensemble Prediction System, ADVANCES IN ATMOSPHERIC SCIENCES, 33, 1297-1305. doi: 10.1007/s00376-016-6155-2
[13]	ZHENG Xiaogu, WU Guocan, ZHANG Shupeng, LIANG Xiao, DAI Yongjiu, LI Yong, , 2013: Using Analysis State to Construct a Forecast Error Covariance Matrix in Ensemble Kalman Filter Assimilation, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 1303-1312. doi: 10.1007/s00376-012-2133-5
[14]	ZHU Jiangshan, Fanyou KONG, LEI Hengchi, 2012: A Regional Ensemble Forecast System for Stratiform Precipitation Events in Northern China. Part I: A Case Study, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 201-216. doi: 10.1007/s00376-011-0137-1
[15]	Jie FENG, Jianping LI, Jing ZHANG, Deqiang LIU, Ruiqiang DING, 2019: The Relationship between Deterministic and Ensemble Mean Forecast Errors Revealed by Global and Local Attractor Radii, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 271-278. doi: 10.1007/s00376-018-8123-5
[16]	ZHU Jiangshan, KONG Fanyou, LEI Hengchi, 2013: A Regional Ensemble Forecast System for Stratiform Precipitation Events in the Northern China Region. Part II: Seasonal Evaluation for Summer 2010, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 15-28. doi: 10.1007/s00376-012-1043-x
[17]	Jian YUE, Zhiyong MENG, Cheng-Ku YU, Lin-Wen CHENG, 2017: Impact of Coastal Radar Observability on the Forecast of the Track and Rainfall of Typhoon Morakot (2009) Using WRF-based Ensemble Kalman Filter Data Assimilation, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 66-78. doi: 10.1007/s00376-016-6028-8
[18]	Kefeng ZHU, Ming XUE, Yujie PAN, Ming HU, Stanley G. BENJAMIN, Stephen S. WEYGANDT, Haidao LIN, 2019: The Impact of Satellite Radiance Data Assimilation within a Frequently Updated Regional Forecast System Using a GSI-based Ensemble Kalman Filter, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 1308-1326. doi: 10.1007/s00376-019-9011-3
[19]	Liu Chunlei, Yao Keya, 1997: Particle Size Truncation Effect on the Inference of Effective Particle Diameter, ADVANCES IN ATMOSPHERIC SCIENCES, 14, 350-354. doi: 10.1007/s00376-997-0055-4
[20]	Chen Jiabin, Ji Liren, Wu Wanli, 1987: DESIGN AND TEST OF AN IMPROVED SCHEME FOR GLOBAL SPECTRAL MODEL WITH REDUCED TRUNCATION ERROR, ADVANCES IN ATMOSPHERIC SCIENCES, 4, 156-168. doi: 10.1007/BF02677062

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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.

Keywords: