Research and Application of Operational MJO Monitoring and Prediction Products in Beijing Climate Center

Wu Jie; Ren Hongli; Zhao Chongbo; Zhang Peiqun; Wu Yujie

doi:10.11898/1001-7313.20160601

Vol.27, NO.6, 2016

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Article Navigation > Journal of Applied Meteorological Science > 2016 > 27(6): 641-653

Wu Jie, Ren Hongli, Zhao Chongbo, et al. Research and application of operational MJO monitoring and prediction products in Beijing Climate Center. J Appl Meteor Sci, 2016, 27(6): 641-653. DOI: 10.11898/1001-7313.20160601.

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Wu Jie, Ren Hongli, Zhao Chongbo, et al. Research and application of operational MJO monitoring and prediction products in Beijing Climate Center. J Appl Meteor Sci, 2016, 27(6): 641-653. DOI: 10.11898/1001-7313.20160601.

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Research and Application of Operational MJO Monitoring and Prediction Products in Beijing Climate Center

DOI: 10.11898/1001-7313.20160601

1.
Laboratory for Climate Studies, National Climate Center, CMA, Beijing 100081
2.
College of Atmospheric Sciences, Nanjing University of Information Science & Technology, Nanjing 210044

Received Date: 2016-05-19
Rev Recd Date: 2016-09-15
Publish Date: 2016-11-30

Abstract

Abstract

Both Madden-Julian oscillation (MJO) and the boreal summer intra-seasonal oscillation (BSISO) have great impacts on the global weather and climate events, which are the most important predictability source of sub-seasonal to seasonal (S2S) prediction. However, the monitoring of MJO/BSISO in China National Climate Center/Beijing Climate Center (NCC/BCC) entirely depends on external data, and the prediction skill of the introduced statistical forecast model is also much lower than dynamic mode, and the practical real-time operation ability has not been established. Therefore, based on CMA (China Meteorological Administration) global analysis data of T639 model, OLR (outgoing long-wave radiation) data of FY-3B satellite and the real-time forecast data of BCC atmospheric general circulation model system (BCC_AGCM2.2), applying the real-time multivariate MJO (RMM) index and BSISO index, BCC develops the MJO real-time monitoring and forecast technology, and establishes the trial ISV (intra-seasonal variability)/MJO prediction system (IMPRESS1.0).In comparison, monitoring results based on T639 wind analysis and FY-3B OLR data is generally consistent with the operational products from other centers, suggesting the capability of characterizing the oscillation and evolution of MJO/BSISO index accurately. Case study for the typical strong MJO event in March 2015 indicates that the amplitude peak of RMM index based on T639 and FY-3B OLR data is weaker than monitoring results based on NCEP and NOAA OLR data. Further analysis for three variables U850 (zonal wind at 850 hPa), U200 (zonal wind at 200 hPa) and OLR show that the convection monitored by FY-3B satellite is more consistent with NOAA's result, while the projection amplitude of the U850 based on T639 analysis against MJO mode is slightly weaker than NCEP/NCAR reanalysis data, which leads to weaker RMM index amplitude. The forecast skill verification shows the IMPRESS1.0 is able to provide correct evolution and intensity information of MJO at least 16 days in advance, and the skill of operational forecast in 2015 reach 18 days. The rolling prediction skill could be improved continually as the evolution of MJO event, and the predicted RMM index phase space track is closer to reality. Meanwhile, the verification of hindcasts by using correlation skill (COR), root mean square error (RMSE) and mean square skill score (MSSS) shows that the IMPRESS1.0 has useful prediction skill for about 12 days for MJO index and 8 days for BSISO1 and BSISO2 index, respectively. The case study for BSISO event in July 2015 also shows prediction skill, the reconstructed anomaly circulation and convection against BSISO index clearly demonstrate the dominant mode and northward propagation of BSISO. Therefore, the unified monitoring and forecast productions based on IMPRESS1.0 can provide important references for extended-range prediction, and offer certain help for operation and research.
- MJO;
- BSISO;
- monitoring and forecast;
- operation system

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References(38)

Figures and Tables

图 1 2015年1—7月RMM指数强度时间序列图

(阴影为澳大利亚气象局监测值)

Fig. 1 Time series of the amplitude of RMM index from Jan to Jul in 2015

(the shaded is based on Australian Bureau of Meteorology monitoring)

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图 2 基于不同资料监测的2015年3月RMM指数空间位相图

(a) 使用所有变量，(b) 仅使用OLR资料，(c) 仅使用850 hPa纬向风场，(d) 仅使用200 hPa纬向风场

Fig. 2 The RMM index phase space diagram plots for Mar 2015，where the RMM indices calculated by all three variables (a), OLR only (b), U850 only (c) and U200 only (d)

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图 3 BCC_AGCM2.2在2015年对RMM指数实时业务预报的相关技巧检验

Fig. 3 The prediction correlation skill verification of RMM indices based on the real-time operational forecast of BCC_AGCM2.2 in 2015

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图 4 2015年3次主要MJO事件的实时监测和预报的RMM指数演变的空间位相图 (红色实线为基于T639和FY-3B OLR的监测结果，彩色虚线为BCC_AGCM2.2不同起报时间的20 d RMM指数预报结果，起报时间以不同颜色区分)

(a) 2015年3月1日—4月15日，(b) 2015年6月1日—7月15日，(c) 2015年12月1日—2016年1月13日

Fig. 4 The phase space diagram of RMM indices evolution for the monitoring and the forecast of three major MJO events in 2015 (the red solid line is based on T639 analysis and FY-3B OLR monitoring, the dash lines of different colors are forecasts based on BCC_AGCM2.2 for 5 start days and show the first 20 days of each forecast)

(a) from 1 Mar to 15 Apr in 2015，(b) from 1 Jun to 15 Jul in 2015，(c) form 1 Dec 2015 to 13 Jan 2016

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图 5 2015年5—10月两个BSISO指数强度时间序列图

(阴影为APCC监测值)

Fig. 5 Time series of the amplitude of BSISO indices from May to Oct in 2015

(the shaded is based on APCC monitoring)

DownLoad: Full-Size Img PowerPoint

图 6 BCC_AGCM2.2对BSISO指数1991—2010年历史回报技巧检验

Fig. 6 The prediction skill of BSISO indices based on BCC_AGCM2.2 for 1991-2010

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图 7 RMM指数空间位相图 (a) RMM指数最近30 d演变和未来30 d预报 (以2015年3月16日为例，紫色圆点为起报点，监测部分为实线，预测部分为虚线)，(b) RMM指数最近45 d演变和10 d前预报结果检验

(以2015年3月26日为例，监测均基于T639和FY-3B OLR资料，预测基于BCC_AGCM2.2资料)

Fig. 7 The RMM index phase space diagram (a) for the latest 30-day monitoring and 30 d forecast (taking 16 Mar 2015 as example, the purple point represent forecast time, the solid line is monitoring and the dash line is forecast), (b) for the latest 45-day monitoring (the solid line) and 10-day forecast verification (the dash line)

(taking 26 Mar 2015 as example, the monitoring is based on T639 analysis and FY-3B OLR data and the forecast is based on BCC_AGCM2.2 data)

DownLoad: Full-Size Img PowerPoint

图 8 赤道地区经向平均 (15°S~15°N) 的最近120 d监测和未来50 d预报的异常850 hPa纬向风场 (a) 和OLR (b) 的纬向-时间剖面图

(以2015年3月16日为例, 阴影和等值线分别代表原始的异常场和RMM指数重构场)

Fig. 8 The time-longitude plot of anomaly U850 (a) and OLR (b) for the latest 120-day monitoring and 50-day forecast (taking 16 Mar 2015 as example), averaged from 15°S to 15°N

(the shaded and contour represent original anomaly and the reconstruction from RMM indices)

DownLoad: Full-Size Img PowerPoint

图 9 2015年BSISO指数监测和未来50 d预测时间序列图

(以2015年7月16日为例, 实线为监测，虚线为预测，其中监测基于T639和FY-3B OLR资料，预测基于BCC_AGCM2.2资料，紫色竖线为起报时间)

Fig. 9 Time series of the BSISO indices for monitoring and 50-day forecast

(taking 16 Jul 2015 as example) (the solid line represent monitoring and the dash line represent forecast, the monitoring is based on T639 analysis and FY-3B OLR data and the forecast is based on BCC_AGCM2.2 data, the purple vertical line shows forecast start time, the horizontal coordinate is calendar month and the vertical coordinate is the value of BSISO indices)

DownLoad: Full-Size Img PowerPoint

图 10 RMM指数最近30 d演变和未来30 d预报的空间位相图

(紫色圆点为起报点，监测部分为实线，预测部分为虚线，监测基于T639和FY-3B OLR资料，预测基于BCC_AGCM2.2资料，指数经过3 d滑动平均) (a) BSISO1指数，(b) BSISO2指数

Fig. 10 The phase space diagram of latest 30-day monitoring and 30-day forecasts

(taking 16 Jul 2015 as example) for 3-day running mean BSISO1 (a) and BSISO2 (b) index (the purple point represents forecast time, the solid line represents monitoring which is based on T639 analysis and FY-3B OLR data and the dash line represents forecast which is based on BCC_AGCM2.2 data)

DownLoad: Full-Size Img PowerPoint

图 11 基于BSISO指数重建的最近1候和预报的未来4候的异常850 hPa风场

(矢量，单位：m·s^-1)、OLR (等值线, 单位：W·m^-2) 和降水场 (填色)

Fig. 11 The reconstruction patterns of anomalous wind at 850 hPa

(the vector, unit:m·s^-1), OLR (the contour, unit:W·m^-2) and precipitation (the shaded) for the first pentad of monitoring and the following four pentads of forecasts

DownLoad: Full-Size Img PowerPoint

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