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Jin-Song Xu


Two aspects of the principal oscillation pattern (POP) analysis are used to study the large-scale modes of the coupled atmosphere–ocean system. First, P0Ps can be considered as the normal modes of the system; one way of studying these normal modes is to estimate them from data. Second, a POP analysis can be viewed as a multivariate spectral analysis and the spectral characteristics of the modes are by-products of the POP analysis. Both aspects are studied using a combined dataset that includes both atmospheric (sea level pressure, 700-mb, and 200-mb zonal winds) and oceanic (sea surface temperature, Pacific sea level, and Pacific subsurface temperature) parameters.

Six joint modes of the coupled atmosphere-system are found in this study. For modes with small eigenvalues the atmosphere plays an important role. The associated oceanic anomalies appear to be generated by the anomalous atmospheric conditions. For the other modes, which have most of their power on much longer time scales, the ocean is more actively involved. Modes 4 and 5 describe decadal time scale variations. Mode 4 is characterized by changes in SST in all three tropical oceans, and in organized convection over the west Pacific. The results allow us to speculate that these tropical features might excite changes in the extratropical tropospheric and oceanic circulations. Mode 5 shows global-scale SST anomalies and large atmospheric anomalies in the Southern Hemispheric circulation. Mode 6 is the only oscillatory normal mode found in the coupled atmosphere-ocean system; it describes the quasi-cyclic behavior of the El Niñio-Southern Oscillation phenomenon.

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Jin-Song Xu


Two quasi-periodic oscillations in the tropical atmosphere with similar oscillation period—the stratospheric quasi-biennial and the Southern oscillations—and the relationship between these two oscillations are examined using the Principal Oscillation Pattern (POP) analysis technique.

The POP analysis of the equatorial stratospheric dataset provides a compact description of the QBO. The oscillation features identified by the POP analysis, namely, the spatial structure, the characteristic times of the oscillation, and the asymmetry in downward propagation, are almost identical to those found by earlier studies using more conventional analyses. The simultaneous POP analysis of the equatorial zonal surface wind and sea surface temperature indicates a well-defined cyclic behavior of the SO. In contrast to the very regular QBO, the SO appears to be much more noisy with intermittent quiet phases. A spectral analysis of the complex POP coefficient time series and the SO index reveals a negligible correlation between the two processes. A POP analysis of the combined equatorial dataset of stratospheric wind, zonal surface wind, and SST also indicates no relation between the QBO and the SO. Two independent modes are identified, one of them completely describing the QBO and the other representing the entire SO. No linear relationship is found between the two modes either in space or in time. It is concluded that the SO and the QBO are two independent processes in the tropical atmosphere with similar time scales.

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Jin-Song Xu and Hans Von Storch


Principal oscillation pattern (POP) analysis is a diagnostic technique for deriving the space-time characteristics of a dataset objectively. A multiyear dataset of monthly mean sea level pressure (SLP) in the area 15°S to 40°S is examined with the POP technique. In the low-frequency band one physically significant pair of patterns is identified, which is clearly associated with the Southern Oscillation (SO).

According to the POP analysis, the 50 may be described as a damped oscillatory sequence of patterns …→P 1P 2-P 1-P 2P 1… having a time scale of two to three years. The first pattern, P1, representative of the “peak” phase of ENSO, exhibits a dipole with anomalies of opposite sign over the central and eastern Pacific and over the Indian Ocean/Australian sector. The second, P2, pattern is dominated by an anomaly in the SPCZ region and describes an intermediate, or “onset” phase.

The time coefficients of the two patterns, P1 and P2, may be interpreted as a bivariate index of the SO. Generalizing the original diagnostic concept, the POP framework is used to predict this index and the traditional univariate SO index.

The POP prediction scheme is tested in a series of hindcast experiments. The scheme turns out to be skillful for a lead time of two to three seasons. In terms of a correlation skill score, the POP model is better than persistence and a conventional ARMA model in hindcasting the traditional SO index.

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Jin-Song Xu, Hans von Storch, and Harryvan Loon


Monthly mean sea level pressure (SLP) data from four low-resolution spectral GCMs–ECMWF T21, CCC, NCAR CCM and GFDL R15–are compared with observations for the Southern Hemisphere.

Characteristics of the observed Southern Hemisphere January and July mean mass distribution are:

(i) high pressure areas in the subtropics;

(ii) a steep meridional gradient at midlatitudes;

(iii) a circumpolar trough in the Antarctic;

(iv) a zonal asymmetry dominated by zonal wave 1, which has an almost complete phase reversal near 40°S;

(v) a double westerly wind maximum during the colder part of the year.

The CCC model reproduces some of these features. The ECMWF model, the NCAR CCM, and the GFDL models fail with respect to (ii) and (iii). All GCMs underestimate the intensity of the stationary eddies. None of the models considered reproduces the double westerly wind maximum.

Another marked feature of the Southern Hemisphere circulation is the semiannual wave that dominates the annual curve of SLP at mid- and polar latitudes. Regardless of the various models’ degree of success in reproducing the mean circulation, all fail in simulating the general features of the semiannual wave.

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