Interannual and interdecadal variations of wintertime blocking frequency over the Asian continent and its relation to east Asian winter monsoon
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1 Interannual and interdecadal variations of wintertime blocking frequency over the Asian continent and its relation to east Asian winter monsoon Hyunsoo Lee, Won-Tae Yun, and Cheong-Kyu Park Climate Prediction Division Korea Meteorological Administration th Annual Climate Diagnostics and Prediction Workshop (October 26-30, 2009)
2 Contents 1. Introduction 2. Data and methodology 3. Blocking types over the Asian Continent 4. Relationship between blocking and EAWM 5. Predictability of blocking 6. Summary and Conclusion
3 Introduction 1. In recent years, the unusual weather extremes are being frequently observed in all parts of the world (Easterling et al., 2000). These are often associated with the occurrence of blocking which are long-lived, recurrent flow patterns (Carrera et al., 2004; Dole, 1986a,b; Hansen et al., 1993; Higgins and Schubert, 1994,1996; Robertson and Ghil, 1999). 2. Research focus How many primary blocking types are there over the Asian continent? And how do they evolve and have influence on the regional weather system of over the East Asia? How does the blocking activity contribute to the intensity of the east Asian winter monsoon(eawm)? What are the significant precursor to the blocking activity?
4 Data Reanalysis data ( ) - Period: winter (12.1~2.28) - ERA-40 (1958~2002), NCEP-NCAR ( ) Sea surface temperature data (2 2 ) - NOAA Extended Reconstructed SST ( ) provided by the NOAA-CIRES Climate Diagnostics Center Snow cover data (2 2 ) - based on the digital NOAA-NESDIS Weekly Northern Hemisphere Snow Charts ( ) 13 station data in Korea - daily-mean temperature ( )
5 Blocking detection method Difference of 500-hPa GPH gradient (Lejenäs and Økland, 1983; Tibaldi and Molteni, 1990) GHGN Ø n H GHGS L Ø 0 Ø s Blocking frequency - the ratio of blocked days to the total number of wintertime days (90 days) Blocking event : duration day 5 days
6 Interannual variation of blocking frequency (BF) * High BF years: 1963, 1966, 1967, 1968, 1980, 1983, 1984 * Low BF years: 1959, 1972, 1978, 1986, 1991, 2006
7 Composite 500-hPa GPH anomaly
8 Composite 300-hPa U wind
9 Zonal mean (60-140E) GPH and U wind
10 Composite 850-hPa wind and temp. anomaly
11 Composite SLP anomaly
12 Relationship between BF and EAWM EAWMI = U300 (27.5N-37.5N, 110E-170E) U300 (50N-60N, 80E-140E) Jhun and Lee (2004)
13 Cluster analysis Cluster analysis deals with separating data into groups whose identities are not known in advance (Wilks, 1995). Cluster analysis procedures : hierarchical or nonhierarchical Distance between observations : Euclidean, RMS, pattern correlations Distance between clusters : single-linkage, complete-linkage, average-linkage centroid, Ward s minimum variance Examples of cluster analysis in the climatology - weather regimes from upper-air flow pattern (Mo and Ghil, 1988; Molteni et al., 1990) - grouping weather observations into synoptic types (Kalkstein et al., 1987) - grouping members of forecast ensembles (Tracton and Kalnay, 1993) - defining climatic regions based on climate variables (Galliani and Filippini, 1985; Guttman, 1993)
14 Dendrogram and cluster distance Distance between merged clusters Distance G1 G2 G3 G S ta g e num b e r Distance between merged clusters S ta g e num b e r
15 Clusters 500 hpa GPH anomaly
16 Blocking events and types
17 Temporal evolution of blocking Type 1 < 500-hPa GPH > < 850-hPa Wind and Temp. anomaly >
18 Temporal evolution of blocking Type 2 < 500-hPa GPH > < 850-hPa Wind and Temp. anomaly >
19 Temporal evolution of blocking Type 3 < 500-hPa GPH > < 850-hPa Wind and Temp. anomaly >
20 Temporal evolution of blocking Type 4 < 500-hPa GPH > < 850-hPa Wind and Temp. anomaly >
21 Interdecadal variation of BF Interdecadal variation of EAWM (Watanabe and Nitta, 1999; Wang, 2006)
22 Relationship between AO and blocking * High AO years: 1972, 1974, 1975, 1988, 1989, 1991, 1992, 1999, 2006
23 Correlation between BF and SSTA * BF1: blocking frequency for E, BF2: blocking frequency for E
24 Composite difference for ENSO period Six strong El Niño years: 1965/66, 1972/73, 1982/ /87, 1991/92, 1997/98 Six strong La Niña years: 1970/71, 1973/74, 1975/ /89, 1998/99, 1999/2000
25 Relationship between snow cover and blocking - EOF analysis of 500-hPa DJF-mean GPH Pattern correlation = Pattern correlation = 0.91 Autumn SCA: E, 40-70N Cohen and Entekhabi (1999, 2001)
26 Predictability of blocking pattern - AGCM SST forcing (6 El Niño 6 La Niña)
27 AGCM response for less SCA Snow forcing
28 Summary and Conclusion It has been found that four types of the Asian continental blocking, based upon hierarchical cluster analysis, have a profound effect on the cold surge over East Asia. - Type 1 : dipole type, concentrative impact during the period of P-3 ~ P+3 - Type 2 : near dipole type, the strongest and the most persistent type - Type 3 : dipole type, significant impact only during the block period - Type 4 : typical Ω type, concentrative impact during the block period ~ P+6 Even in the seasonal mean sense, the blocking activity over the Asian continent are significantly contributing to the intensity of EAWM which consists of a typical meridional dipole structure in 500 GPH, enhanced SH or AL, and a stronger than normal winter monsoon over the East Asia. The apparent weakening of the EAWM since late 1980s appears to be associated with the considerable decrease of the Asian continental blocking frequency since late 1980s
29 Summary and conclusion Precursor to blocking activity over the Asian continent - SST : warm phase of ENSO tends to weaken the blocking activity cold phase of ENSO tends to strengthen the blocking activity - Snow cover over the Asian continent significantly contribute to BF over the continental Asian region of the subsequent winter (Negative SCA tends to induce the non-blocking flow) The ENSO-related blocking activity and the impact of the preceding autumn SCA over the Asian continent on non-blocking flow have been fairly well simulated in SNU-AGCM.
30
31 Relationship between SCA and blocking - EOF analysis of 500-hPa GPH
32 Jhun and Lee (2004) EAWMI = U300 (27.5N-37.5N, 110E-170E) U300 (50N-60N, 80E-140E)
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