Atmospheric Circulation Patterns over East Asia and Their Connection with Summer Precipitation and Surface Air Temperature in Eastern China during 1961–2013

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Supported by the National Natural Science Foundation of China (41530531, 41675092, and 41305056) and China Meteorological Administration Special Public Welfare Research Fund (GYHY201506001)

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  • Based on the NCEP/NCAR reanalysis data and Chinese observational data during 1961–2013, atmospheric circulation patterns over East Asia in summer and their connection with precipitation and surface air temperature in eastern China as well as associated external forcing are investigated. Three patterns of the atmospheric circulation are identified, all with quasi-barotropic structures: (1) the East Asia/Pacific (EAP) pattern, (2) the Baikal Lake/Okhotsk Sea (BLOS) pattern, and (3) the eastern China/northern Okhotsk Sea (ECNOS) pattern. The positive EAP pattern significantly increases precipitation over the Yangtze River valley and favors cooling north of the Yangtze River and warming south of the Yangtze River in summer. The warm sea surface temperature anomalies over the tropical Ind-ian Ocean suppress convection over the northwestern subtropical Pacific through the Ekman divergence induced by a Kelvin wave and excite the EAP pattern. The positive BLOS pattern is associated with below-average precipitation south of the Yangtze River and robust cooling over northeastern China. This pattern is triggered by anomalous spring sea ice concentration in the northern Barents Sea. The anomalous sea ice concentration contributes to a Rossby wave activity flux originating from the Greenland Sea, which propagates eastward to North Pacific. The positive ECNOS pattern leads to below-average precipitation and significant warming over northeastern China in summer. The reduced soil moisture associated with the earlier spring snowmelt enhances surface warming over Mongolia and northeastern China and the later spring snowmelt leads to surface cooling over Far East in summer, both of which are responsible for the formation of the ECNOS pattern.
  • Fig.  1.   Leading modes of the summer 500-hPa geopotential height anomalies over East Asia and their corresponding PCs: (a) EOF1, (b) EOF2, (c) EOF3, (d) PC1, (e) PC2, and (f) PC3. The numbers in blue at the top of the right-hand panels indicate the percentage of variance explained.

    Fig.  2.   Summer mean anomalies regressed onto PC1 for 1961–2013: (a) 200-, (b) 500-, and (c) 850-hPa geopotential height (gpm), and (d) SLP (hPa). The dotted areas exceed the 95% confidence level with a two-tailed Student’s t-test.

    Fig.  3.   As in Fig. 2, but for PC2.

    Fig.  4.   As in Fig. 2, but for PC3.

    Fig.  5.   Observed summer precipitation anomalies (mm) regressed onto (a) PC1, (c) PC2, and (e) PC3 for 1961–2013 and the spatial distribution of the explained variance of the (b) EAP, (d) BLOS and (f) ECNOS patterns. The black dots in (a, c, e) indicate areas exceeding the 95% confidence level with a two-tailed Student’s t-test.

    Fig.  6.   As in Fig. 5, but for the summer SAT (℃).

    Fig.  7.   Correlations between PC1 and seasonal mean SST in (a) the preceding winter, (b) spring, (c) summer, and (d) autumn. The dotted areas indicate the 95% confidence level with a two-tailed Student’s t-test.

    Fig.  8.   Summer mean (a) SST (shading; ℃), (b) 300-hPa potential velocity (contours; m2 s–1) and divergent wind (vectors; m s–1), and (c) 300-hPa geopotential height (shading; gpm) and 850-hPa horizontal wind (vectors; m s–1) anomalies associated with the simultaneous TIO index for 1961–2013. (d)–(f) Same as (a)–(c), respectively, but associated with PC1. In (a, d), the green solid lines indicate the 27.5℃ of the total SST associated with the TIO index and PC1, respectively. The total SST is defined as the sum of the TIO index/PC1 regression pattern and climatological mean SST. In (b, e), the contour interval is 0.1 × 105 m2 s–1; the zero contour lines are black, whereas the negative (positive) values are blue (red).

    Fig.  9.   Summer mean (a) net latent heat flux (shading; W m–2) and 10-m wind (vectors; m s–1), (b) outgoing longwave radiation (W m–2), (c) 500-hPa vertical velocity (Pa s–1), and (d) precipitation (mm day–1) anomalies associated with the simultaneous TIO index. The dotted areas exceed the 95% confidence level with a two-tailed Student’s t-test.

    Fig.  10.   Correlation between PC2 and seasonal mean SIC in (a) the preceding winter and (b) spring. The dotted areas exceed the 95% confidence level with a two-tailed Student’s t-test.

    Fig.  11.   (a) Spring mean SIC and (b) summer mean 300-hPa geopotentail height (shading; gpm) and wave activity flux (vectors; m–2 s–2) anomalies associated with the inverted SSIC index. (c, d) Same as (a, b), but are associated with PC2. The dotted areas indicate the 95% confidence level with a two-tailed Student’s t-test.

    Fig.  12.   Spring mean (a) SLP, (b) SST (shading; °C) and 10-m wind (vectors; m s–1) anomalies regressed onto PC2, summer mean (c) SST (shading) and 10-m wind (vectors), and (d) precipitation (shading; mm day–1) and divergent wind anomalies (vectors; m s–1) regressed onto the spring Victoria mode index. The Victoria mode index is defined as the normalized PC of the second EOF mode of the North Pacific SST anomalies in spring. The dotted areas exceed the 95% confidence level with a two-tailed Student’s t-test.

    Fig.  13.   Correlation between PC3 and SCE in (a) spring, (b) April, (c) May, and (d) June during 1973–2013.The dotted areas exceed the 90% confidence level with a two-tailed Student’s t-test.

    Fig.  14.   Summer mean (a) 0–10-cm soil moisture (m3 m–3) and (b) 2-m air temperature anomalies (℃) regressed onto the spring snowmelt index. The dotted areas indicate the 95% confidence level with a two-tailed Student’s t-test.

    Table  1   Correlation coefficients between the BLOS and ECNOS patterns and the conventional atmospheric circulation teleconnection patterns in the Northern Hemisphere. The symbols * and ** indicate the 90% and 95% confidence level, respectively

    Pattern AO NAO POL EA WA EU SCAN EAWR WP
    BLOS –0.096 0.341** –0.273** –0.169 –0.031 –0.127 –0.282** 0.311** –0.025
    ECNOS 0.209 0.076 0.221 0.236* –0.052 –0.197 –0.082 0.070 0.234*
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