Monsoon and Enso: Selectively Interactive Systems

Abstract

S i l M M A R YWe attempt to construct a logical framework for the deciphering of the physical processes that determine the interannual variability of the coupled climate system. Of particular interest are the causes of the 'predictability barrier' in the boreal spring when observation-prediction correlations rapidly decline. The barrier is a property of many models and occurs irrespective of what time of year a forecast is initiated. Noting that most models used in interannual prediction emphasize the coupled physics of the Pacific Ocean basin, with the intent of encapsulating the essential structure of the El Nino-Southern Oscillation (ENSO) system, lagged Southern Oscillation Index (SOI) correlations are compared with the model results. The lagged SO1 correlations also decrease rapidly in springtime. In that sensc. the coupled ocean-atmosphere models are behaving in a manner very similar to the real system, at least as it is defined by the SOI.We propose that (i) the springtime is a period where errors may grow most rapidly in a coupled oceanatmosphere forecast model or (ii) there are other influences on the system that are not included in the simple coupled-model formulations. Both propositions are based on observations. By examining the period of correlation decrease, it is noticed that the equatorial pressure gradients tend to be a minimum at the time of the correlation decrease, suggesting that the occan-atmosphere system may be least robust during the spring and, thus, subject to error growth. At the same time the south Asian summer monsoon is growing very rapidly. As the monsoon circulation is highly variable in hoth phase and amplitude from year to year. the oceanatmosphere system may be subject to variable and impulsive forcing each spring.A monsoon intensity index. based on the magnitude of the mean summer vertical shear in the 'South Asia' region, was defined for the broad-scale monsoon. 'Strong' and 'weak' monsoon seasons wxre determined by the index and were shown to he consistent with the independent broad-scale outgoing long-wave-radiation fields. Associated with the anomalous monsoons were global scale. coherent summer circulation patterns. Of particular importance was that stronger (weaker) than average summer trade winds were associated with strong (weak) monsoon periods. Thus, a signal of the variable monsoon was detected in the low-level wind fields over the Pacific Ocean that would be communicated to the Pacific Ocean through surface stresses.A longer-period context for the anomalous summer monsoon circulation fields was sought. Based on the summer monsoon index, annual cycles for the ycars in which there were strong and weak monsoon seasons were composited. Large-scale coherent differcnccs were apparent in the circulation fields over most of the globe including south Asia and the tropical Indian Ocean as far as the previous winter and spring. Although the limited data period renders the absoluteness of thc conclusions difficult to confirm. the results indicate that the variable monsoon (an...

Decadal variability of the Indian Ocean dipole

“…This may be due to their coupling with the overlying atmosphere, as suggested by White et al [2003] in the context of slower tropical Pacific decadal waves. Indeed, the model simulated decadal Webster-Yang index [Webster and Yang, 1992], a zonal wind index defined as June-August (JJA) zonal wind shear between 850 -200 hPa area-averaged over 40°E-110°E, equator-20°N (henceforth WYI), is well correlated to the decadal D20 fall anomalies (Figure 3a) after removal of ENSO component through partial correlation technique; the peak correlations with (reversed sign) occur with 5 years lead (Figure 3b), suggesting that decadal atmospheric variability modulates and possibly forces decadal wavelike processes in the tropical Indian Ocean. Similar partial correlations between the NCEP-based WYI and SODA-derived D20 anomalies during fall are also qualitatively similar (Figures 3c and 3d), supporting the proposed mechanism; we note that the peak lead-time is 6 years in this case, comparable with the 5 years from the CGCM.…”

Predictability of Sri Lankan rainfall based on ENSO

“…The correlations of July-August rainfall with NINO3 were higher than that with other NINO indices (Table III). These correlations drop when the SST field leads the rainfall (Table V) and this may be related to the so called 'spring barrier' of predictability of ENSO (Webster and Yang, 1992). The ENSO rainfall correlation is greater outside the Southern Plains and Western regions, which garners orographic rainfall in this season.…”

Weakening relationship between East Asian winter monsoon and ENSO after mid-1970s

“…The out-of-phase relationship between ENSO and EAWM variation was documented by Webster and Yang [10], Zhang et al [11], and Lau and Nath [12]. Gong et al [13] indicated the connection between variability of the Arctic Oscillation and EAWM.…”