1. XiaoJing Jia 2015-3-24@HangZhou
Influence of Forced Large-Scale Atmospheric Patterns on winter climate in China
XiaoJing Jia

2. Contents
Background
The tropical Pacific SST-related large-scale atmospheric patterns and its relationship to the wintertime SAT over China
The Mechanisms
Conclusion

3. El Niño

4. North Atlantic Oscillation（NAO)
这种加强或者减弱的北大西洋西风带直接影响到当地的生态系统和北大西洋地区的渔业市场。是北美和欧洲国家非常关心的问题。 4

5. Eighteen winter average temperature anomalies expressed as departures from the 1951 to 1980 mean. The temperature data consist of land surface temperatures blended with SST data (Jones and Briffa 1992). Negative anomalies are dashed, and regions of insufficient data coverage are not contoured.
(Hurrell, 1996)

6. The relationship between PNA&NAO and the SAT over China (winter)
(Jia and Lin, 2011)

7. Contents
Background
The tropical Pacific SST-related large-scale atmospheric patterns and its relationship to the wintertime SAT over China
The Mechanisms
Improving seasonal forecast skill using the large-scale pattens
Coclusion

8. SVD - （Tropiacl Pacific SST- Z500_NH）
TCC (PNA-ASVD1=0.67)
TCC (NAO-ASVD2=0.81) -
NAO-Like +
Negative SSTA
TCC (Nino3.4-SSVD1=0.97)

9. The relationship between SVD1 &SVD2 and the SAT over China (winter)
NAO
PNA

10. Contents
Background
The tropical Pacific SST-related large-scale atmospheric patterns and its relationship to the wintertime SAT over China
The Mechanisms
Improving seasonal forecast skill using the large-scale pattens
Coclusion

11. SVD2 related atmospheric circulation
SLP
AO-SVD2=0.81
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12. AL SH AL SH

13. SLP
Vector:Wind_Z Shading: SAT Contour: SLP
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14. SLP
Z500
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15. SVD2 related atmospheric circulation
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16. surface
Z500
Z200

17. SVD2 +  East Asian Winter Monsoon weak
Warm China

18. SVD2 related EP flux
Z200
Vector:EP flux ?
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19. SVD2 related precipitation+ - - +
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20. Numerical Experiment (LBM)+ -
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21. + -
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22. Contents
Background
The tropical Pacific SST-related large-scale atmospheric patterns and its relationship to the wintertime SAT over China
The Mechanisms
Improving seasonal forecast skill using the large-scale pattens
Coclusion

23. Model Data seasonal ensemble forecast from six coupled models
APCC/CliPAS Project (Wang et al. 2009; Lee et al. 2010)
---- ENSEM-BLES Project (Weisheimer et al. 2009)

24. SVD1
SVD2
(Jia and Lin, 2014)

25. TCC of PC1&PC2 between models and observations

26. SVD1和SVD2对中国冬季地面气温的关系
（模式集合预报结果）

27. Summary
• The winter SAT over China is significantly influenced by the leading two atmospheric patterns related to the tropical Pacific SST anomalies, especially the SVD2.
• In the positive phase of the SVD2 the EAWM is weaker-than-normal and the winter SAT over China is warmer-than-normal.
• The spatial structure and the time variability of the SVD2 and its relationship to the winter SAT over China are reasonably captured by MME seasonal forecasts.

28. Summary
• A post-processing method based on the relationship between these large scale atmospheric patterns can efficiently improve the models seasonal forecasts skill.
• The improved seasonal forecast skill come smainly from the second SVD mode.

29. THANK YOU !