EGU 2011 General Assembly, Vienna, Austria, April 3-8, 2011 Predictable Climate Dynamics of Abnormal East Asian Winter Monsoon: Once-in-a-century Snowstorms.

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Presentation transcript:

EGU 2011 General Assembly, Vienna, Austria, April 3-8, 2011 Predictable Climate Dynamics of Abnormal East Asian Winter Monsoon: Once-in-a-century Snowstorms in 2007/08 Winter Zhiwei Wu 1,2, Jianping Li 1, Zhihong Jiang 3 and Jinhai He 3 1 Meteorological Research Division, Environment Canada, Dorval, Quebec, Canada 2 LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences 3 Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science &Technology, Nanjing, China

Page 2 – September 16, 2010 Is the 2007/08 EAWM predictable? Extremely abnormal 2007/08 winter A normal winter in southern China Such a record-breaking and long-persisting snowstorm leads to hundreds of people’s death and huge property loss (more than 23 billion US dollars).

Page 3 – September 16, 2010 Research Review Tao and Wei (2008) emphasized roles of the sustaining blocking high in the mid-high latitudes over EA based on synoptic scale analysis of the snowstorm events in January Ding et al. (2008) suggested the strong La Niña event in 2007/2008 winter provides a climate background for invasion of cold air into South China and the persistence of circulation anomalies over the Eurasian continent is the direct cause of the snowstorms. Wen et al. (2008) believed these snowstorms were closely linked to the change in the Middle East jet stream and the anomalous western Pacific subtropical high (WPSH). The tropical intraseasonal oscillation and anomalous Tibetan Plateau warming are also suggested to be responsible for the anomalous 2007/2008 snowstorms (Hong and Li 2009; Bao et al. 2010). Previous studies emphasize the unique features of the 2007/08 winter condition:

Page 4 – September 16, 2010 Although the catastrophic consequences of the 2007/2008 winter snowstorms are unprecedented or once-in-a-century (Zheng 2008; Wang et al. 2008), several similar cases do occur in the past fifty years. This provides the feasibility of investigating the general features of the 2007/2008-like EAWM anomalies and their predictability sources. Is the 2007/08 EAWM predictable?

Page 5 – September 16, 2010 Questions to be answered: What kind of principal mode dominates the abnormal 2007/08 winter monsoon over EA? What are the common features of the 2007/08-like EAWM anomalies? How to predict such winter monsoon anomalies?

Page 6 – September 16, 2010 Data, model and methodology Monthly observed SAT and precipitation data from 160 gauge stations across China for the period European Centre for Medium-Range Weather Forecasts (ECMWF) 40-year reanalysis data (ERA- 40; Uppala et al. 2005) and ERA-interim reanalysis datasets The Met Office Hadley Centre's sea ice and SST datasets gridded at 1.0° × 1.0° resolution (Rayner et al. 2003) Data, model and methodology

Page 7 – September 16, 2010 Data, model and methodology All the numerical experiments presented in this paper are based on the SGCM first developed by Hoskins and Simmons (1975). The resolution used here is T31, with 10 equally spaced sigma levels (Lin and Derome 1996). Data, model and methodology

Page 8 – September 16, 2010 Distinct third principal mode of the EAWM variability The third mode accounts for around 8.7% of the total SAT variances.The eigenvalues of the leading modes suggest that EOF3 is significantly distinguished from EOF1 and EOF2 and other modes in terms of sampling error above the 95% confidence level (North et al. 1982). The spatial pattern of EOF3 shows that during a positive phase of the third mode, anomalous cold SAT tends to occur in southern China-west Mongolia and anomalous warm in central Siberia and Philippine Sea, and vice versa. Distinct third principal mode of the EAWM variability

Page 9 – September 16, 2010 There are four winters in which the third mode becomes dominant and accounts for more than 40% of the total variance for the period. Using observational data at 160 gauge stations across China, as expected, 2007/08 does exhibit a typical high PC3 winter feature in terms of the SAT spatial pattern, namely, anomalous cold SAT in southern China and anomalous warm in northeastern China (color shadings). Distinct third principal mode of the EAWM variability

Page 10 – September 16, 2010 Cold air intrusion via a “northwest pathway” Moisture transport from the Bay of Bengal toward southern China along the southern flank of the Plateau A warm and moist air transport from Philippine Sea and western Pacific Development of a blocking high A northwestward WPSH

Page 11 – September 16, 2010 Origins and predictability sources anomalously negative SIC correlation area located in Arctic Ocean anomalously positive SST correlation area covering the Arctic Ocean areas adjacent to the northern Eurasian continent No significant correlation is found with tropical SST in the prior autumn, while large areas of significant correlations are detected with extra-tropical SST in North Pacific and sustain through the winter (not shown). This indicates that the third mode is more likely to result from the extra-tropical SSTA than ENSO. Origins and predictability sources

Page 12 – September 16, 2010 Physical mechanisms an anomalously positive anomaly center located over northern Eurasian continent, which may favor developing and sustaining of the blocking high over this area There is a significant 550 hPa H anomaly centers as responses to the Pacific SSTA forcing. This pattern favors the enhancement and northwestward shift of the WPSH.

Page 13 – September 16, 2010 Physical mechanisms The 550 hPa H simulation basically captures the major features of the third principal mode of the EAWM, namely, enhanced blocking high over central Siberia and intensified WPSH with a northwestward shift. It further verified the speculation that the Arctic SSTAs and the SSTAs in the extra- tropical Pacific are two major origins and predictability sources of the third principal mode of the EAWM.

Page 14 – September 16, 2010 Seasonal prediction An empirical seasonal prediction model is developed using a linear regression method: where x1, x2 and x3 denote the prior autumn SSTAs averaged in the Arctic Ocean (70°-85°N, 105°E-115°W), central North Pacific (22.5°-35°N, 170°E-110°W) and northeastern Pacific (35°-50°N, 150°-130°W), respectively. The relevant procedures are as following: The cross-validation method systematically deletes thirteen years from the period (namely, years left out in 4 blocks of , , , and , respectively), derives a forecast model from the remaining years, and tests it on the deleted cases.

Page 15 – September 16, 2010 Hindcast result The empirical model shows a promising skill.

Page 16 – September 16, 2010 Real forecast We apply a 30-year moving training window prior to forecast year and perform a 10-year real forecast from 1999/00 winter through 2008/09 winter. The correlation coefficient between the observation and the real forecast is 0.59, exceeding 95% confidence level. The 2007/08 abnormal EAWM is realistically forecast, even better than the hindcast.

Page 17 – September 16, 2010 The extremely abnormal 2007/08 winter over EA is dominated by the distinct third principal mode of the EAWM. SIC or SST anomalies in the Arctic Ocean and SSTAs in central North Pacific and northeastern Pacific provide predictability sources for the third mode. Based on these results, an empirical model is established to predict the third mode of the EAWM. This empirical model provides a real time forecast tool and may facilitate the seasonal prediction of high-impact weather associated with the abnormal EAWM. Conclusion

Page 18 – September 16, 2010

Page 19 – September 16, 2010 Thank you!