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Michael Ghil and Kingtse Mo

Abstract

In Part II of this two-part article, we complete the systematic examination of oscillatory modes in the global atmosphere by studying 12 years of 500 mb geopotential heights in the Southern Hemisphere. As in Part I, for the tropics and Northern Hemisphere extratropics, the data were band-pass filtered to focus on intraseasonal (IS) phenomena, and spatial EOFs were obtained. The leading principal components were subjected to singular spectrum analysis (SSA), in order to identify nonlinear IS oscillations with high statistical confidence.

In the Southern Hemisphere, the dominant mode has a period of 23 days, with spatial patterns carried by the second and third winter EOF of the IS band. It has a zonal wavenumber-four structure. The 40-day mode is second, and dominated by wavenumbers three and four, while a 16-day mode is too weak to separate its spatial behavior from the previous two. The IS dynamics in the Southern Hemisphere is more complex and dominated by shorter wavenumbers than the Northern Hemisphere. No statistically significant correlations between the Southern Hemisphere and the tropics or the Northern Hemisphere are apparent in the IS band.

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Kingtse C. Mo

Abstract

Two sets of experiments were performed. The first set, denoted SSTA, consisted of 90-day forecasts with sea surface temperature anomalies updated with observed values daily during the entire integration. For the summers 1987 and 1988, three SSTA experiments were made using three different initial conditions centered on 1 June of that year, separated by 1 day. The second set of experiments, denoted CSST, used the same initial conditions as the first set, but the integrations were performed using climatological SSTs. All numerical experiments were done using the NMC T80 spectral model of 1990, which is the same model used in making operational medium-range forecasts.

Simulated seasonal ensemble-mean rainfall was compared with satellite estimates of precipitation and observed station rainfall data. Overall agreement between them is good. Two centers of maximum rainfall, over the Arabian Sea and the Bay of Bengal, are captured by the model, but it fails to capture the movement of the rainfall associated with the Indian monsoon. The model is able to simulate the interannual variability of rain in India and over the Sahel, although the simulated convection in the central Pacific associated with the 1987 warm episode is not realistic.

When the model is able to simulate the convection associated with the SSTAs, then the updated SSTs have a large positive impact on tropical impact seasonal forecasts. The impact on the extratropical forecasts is, in general, positive but small.

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Kingtse C. Mo

Abstract

Long-term trends and interannual variations of circulation anomalies in the Southern Hemisphere are examined using the National Centers for Environmental Prediction–National Center for Atmospheric Research reanalysis from 1949 to 1998. The changes in planetary circulation regimes are linked to global sea surface temperature anomalies (SSTAs).

Empirical orthogonal function (EOF) analysis was performed on 500-hPa height anomalies. The leading mode EOF1 shows a strong zonal symmetry with a phase reversal between height anomalies in high and midlatitudes. Apart from zonal symmetry, a zonal wavenumber 3 is evident with three centers located in three southern oceans. In the low-frequency band with fluctuations longer than 60 months, EOF1 is associated with the second rotated EOF mode of SSTAs with positive loadings over three southern oceans and negative loadings in the North Pacific and the North Atlantic.

The next two modes are the Pacific–South American (PSA) patterns. They depict wave-3 patterns in quadrature with each other and a well-defined wave train from the tropical Pacific to Argentina with large amplitudes in the Pacific–South American sector. On decadal timescales, the abrupt warming over the central and eastern Pacific is related to the strengthening of PSA1. In the interannual band, PSA1 is associated with the low-frequency part of El Niño–Southern Oscillation (ENSO) variability with the dominant period of 40–48 months. PSA2 is associated with the quasi-biennial component of ENSO variability with a period of 26 months.

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Kingtse C. Mo

Abstract

No abstract available.

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Kingtse C. Mo

Abstract

The NCEP–NCAR reanalysis together with the outgoing longwave radiation anomalies (OLRAs) and a gridded daily precipitation over the United States were used to analyze precipitation over California on intraseasonal timescales. The intraseasonal (10–90 days) filtered OLRAs were subjected to singular spectrum analysis, which identifies nonlinear oscillations in noisy time series. There are two dominant oscillatory modes associated with California rainfall with periods near 36–40 and 20–25 days.

The 36–40-day mode is related to the Madden–Julian Oscillation (MJO) in the Tropics. Enhanced tropical convection propagates from the western Pacific to the central Pacific. A three-cell pattern with negative OLRAs in California and positive anomalies in the eastern Pacific and the Pacific Northwest starts to develop 4 days later and rainfall starts in California.

Anomalies associated with the 20–25-day mode are responsible for alternating wet and dry episodes over California with periods shorter than the timescales of the MJO. The 20–25-day mode is the leading mode in the 7–30-day band and is related to tropical convection in the Pacific. In the extratropics, cloud bands propagate northward along the west coast of North America from the eastern Pacific just north of the ITCZ through California to the Pacific Northwest. The 200-hPa streamfunction anomaly composites associated with the 20–25-day mode reveal a westward propagating wave train dominated by a zonal wavenumber 2. This mode has a spatial structure similar to the traveling pattern described by Branstator.

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Kingtse C. Mo

Abstract

Data from observations and the Intergovernmental Panel on Climate Change (IPCC) twentieth-century climate change model [phase 3 of the Coupled Model Intercomparison Project (CMIP3)] simulations were analyzed to examine the decadal changes of the impact of ENSO on air temperature T air and precipitation P over the United States. The comparison of composites for the early period (1915–60) and the recent period (1962–2006) indicates that cooling (warming) over the south and warming (cooling) over the north during ENSO warm (cold) winters have been weakening. The ENSO influence on winter P over the Southwest is strengthening, while the impact on P over the Ohio Valley is weakening for the recent decades. These differences are not due to the long-term trends in T air or P; they are attributed to the occurrence of the central Pacific (CPAC) ENSO events in the recent years. The CPAC ENSO differs from the canonical eastern Pacific (EPAC) ENSO. The EPAC ENSO has a sea surface temperature anomaly (SSTA) maximum in the eastern Pacific. Enhanced convection extends from the date line to the eastern Pacific, with negative anomalies in the western Pacific. The atmospheric responses resemble a tropical Northern Hemisphere pattern. The wave train is consistent with the north–south T air contrast over North America during the EPAC ENSO winters. The CPAC ENSO has enhanced convection in the central Pacific. The atmospheric responses show a Pacific–North American pattern. It is consistent with west–east contrast in T air and more rainfall over the Southwest during the CPAC ENSO winters.

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Michael Ghil and Kingtse Mo

Abstract

We have examined systematically oscillatory modes in the Northern Hemisphere and in the tropics. The 700 mb heights were used to analyze extratropical oscillations, and the outgoing longwave radiation to study tropical oscillations in convection. All datasets were band-pass filtered to focus on the intraseasonal (IS) band of 10–120 days. Leading spatial patterns of variability were obtained by applying EOF analysis to these IS data. The leading principal components (PCs) were subjected to singular spectrum analysis (SSA). SSA is a statistical technique related to EOF analysis, but in the time domain, rather than the spatial domain. It helps identify nonlinear oscillations in short and noisy time series.

In the Northern Hemisphere, there are two important modes of oscillation with periods near 48 and 23 days, respectively. The 48-day mode is the most important of the two. It has both traveling and standing components, and is dominated by a zonal wavenumber two. The 23-day mode has the spatial structure and propagation properties described by Branstator and by Kushnir.

In the tropics, the 40–50 day oscillation documented by Madden and Julian, Weickmann, Lau, their colleagues, and many other authors dominates the Indian and Pacific oceans from 60°E to the date line. From 170°W to 90°W, however, a 24–28 day oscillation is equally strong. The extratropical modes are often independent of, and sometimes lead, the tropical modes.

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Kingtse C. Mo

Abstract

Pattern correlations between daily anomalies have been used to study the persistence of the Southern Hemisphere circulations. The dataset consists of daily Australian analyses of 500 mb heights and sea level pressure for the period from 1972 to 1983. Compared to the Northern Hemisphere, the pattern correlations are much lower and more variable in the Southern Hemisphere. The mean one-day lag autocorrelation is only 0.57, compared to 0.81 in the Northern Hemisphere. The correlations increase significantly for the filtered anomalies, which consist of the planetary wavenumbers from 0 to 4.

Subjective criteria based on the pattern correlations are used to select quasi-stationary events. A series of 5 or more daily maps is defined to be quasi-stationary if the pattern correlations between all pairs of five consecutive maps in this time series are larger than or equal to 0.5. In winter, quasi-stationary events can be classified in terms of wavenumbers. Waves 3 and 4 are by far the dominant waves. More than half of the events have wave 3 amplitude with geographically fixed orientations.

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Kingtse C. Mo

Abstract

The intraseasonal rainfall variability over North America is examined using singular spectrum analysis (SSA) and composites of outgoing longwave radiation anomalies (OLRAs), 200-hPa divergence and a gridded rainfall dataset over the United States. The evolution of the Arizona and New Mexico (AZNM) monsoon based on composites indicates that rainfall anomalies propagate eastward from the North Pacific through AZNM, the Great Plains, to the eastern United States. During summer, the wet and dry periods of the AZNM monsoon are modulated by an oscillatory mode with a period of 22–25 days (22-day mode). This is also the dominant mode associated with rainfall events over the Great Plains. The influence of the Madden–Julian Oscillation (MJO) on the AZNM monsoon is secondary. The strongest impact of the MJO is on precipitation over Mexico. SSA performed on the 200-hPa divergence and OLRAs averaged over Mexico show only one oscillatory mode with a period of about 36–40 days.

The 22–25-day mode also exists in the vertically integrated moisture fluxes over the Great Plains. During the wet periods of the AZNM monsoon, more moisture is transported from both the Gulf of Mexico and the Gulf of California to AZNM. The situation reverses when the oscillation reaches the other phase. The 22-day mode is linked to tropical convection. When rainfall associated with the 22-day mode travels eastward from AZNM to the Great Plains, the OLRA composites show westward propagating waves just north of the equator. When enhanced convection reaches the western Pacific, rainfall diminishes over AZNM. When convection in the western Pacific is suppressed and enhanced convection is located in the central Pacific, rainfall intensifies over AZNM.

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Kingtse C. Mo

Abstract

A statistical model based on the combination of singular spectrum analysis (SSA) and the maximum entropy method (MEM) is applied to monitor and forecast outgoing longwave radiation anomalies (OLRAs) in the intraseasonal band over the Indian–Pacific sector and in the pan-American region. SSA is related to empirical orthogonal function analysis (EOF) but is applied to time series. The leading SSA modes (T-EOFs) are orthogonal and they are determined from the training period before filtering. The OLRA time series can be projected onto T-EOFs to obtain the principal components (T-PCs). To obtain fluctuations in any frequency band, one can partially sum up a chosen subset of T-EOFs and the related T-PCs in that band. The filter based on the SSA modes is data adaptive and there is no loss of end points. It is well suited for real-time monitoring of intraseasonal oscillations.

In the Pacific and the pan-American region, there are three leading modes (T-EOFs) of oscillations with periods near 40, 22, and 18 days. The T-PCs associated with these modes are quasiperiodic and they can be modeled by an autoregressive process. To perform forecasts, the MEM is used to determine the autoregressive coefficients from the training period. These coefficients are used to advance T-PCs. The summation of T-EOFs and T-PCs related to three preferred modes gives the predicted OLRAs. For 5-day mean OLRAs, the averaged correlation between the predicted and the observed anomalies is 0.65 at the lead times of four pentads (20 days). The SSA–MEM method is effective for any time series containing large oscillatory components. The deficiency of this method is that the forecasted magnitudes of anomalies are usually weaker than observations.

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