Abstract

The spatial distribution and evolution of variability of near-global SST and SLP data in the quasi-biennial (QB) and 3–7 year low-frequency (LF) period bands are investigated and described. The largest signals in both bands are in the tropics. The near-equatorial characteristics of the QB in the SLP field are those of a quasi-progressive wave while the LF variation in the same field is closer to the standing wave. Both bands show the traditional Southern Oscillation pattern. The SST variability in both bands is essentially that of El Niño.

It is shown that ENSO is partially due to a nonlinear interaction between the two frequency bands. Both bands appear important to the ENSO cycle. The current work could not establish conclusively that if either was the fundamental mode, although there is weak evidence favoring the QB mode.

The QB signal described here is essentially the ENSO signal and does not seem to be simply related to the stratospheric QBO. Calculations suggest the tropospheric QB described here is not due to a consistent interaction of the annual cycle with itself. The current results do not exclude the possibility that the QB is due to forcing processes which regularly switch sign with season.

Abstract

The common variance between 100-yr-long control runs from 11 coupled global climate models (CGCMs) has been studied by use of common empirical orthogonal functions (EOFs). The results suggest that there is a considerable disparity between the CGCMs estimates of internal variability. About one-half of this difference can be attributed to model drift or other low-frequency variations in several of the models. However, even after accounting for this effect, it was found that the models can easily differ by a factor of 2 or more for the energy levels in different EOF mode (wave) numbers. Comparison with observations showed that no one model consistently reproduced the observed partial eigenvalue spectrum. Again, differences between observed and model energy levels were commonly a factor of 2 or more. It is speculated that at least some of the disagreement is due to the relative coarse resolution of the models used in this study.

Separate analysis of a 1000-yr control run of the Geophysical Fluid Dynamics Laboratory model suggested that intramodel variability is much smaller than intermodel variability. It was also found that an estimate of the anthropogenic signal due to greenhouse gases and aerosols from the Max Planck Institute had strong spatial similarities to the leading modes of the models’ common EOFs. This fact complicates the detection/attribution problem.

Abstract

Long-range Naval aircraft using AXBT's obtained meridional temperature sections from the central Pacific Ocean along 158 and 170°W between 30 and 50°N at approximately monthly intervals between November 1974 and April 1977 (29 months). Analyses of these sections show that the seasonal cycle in the central ocean is confined largely to the upper 100 m. The phase of the seasonal cycle increases with depth so that at 100 m it lags the surface by three months. Exceptions to the above statements occur in two narrow bands centered on latitudes 42 and 36°N where the seasonal cycle apparently penetrates in phase to the limit of observations (300 m) except in the interval 100–150 m which lags the surface by 1–2 months. Approximately 90–95% of the variance in the seasonal change of heat storage in the study region can be accounted for by air/sea heat exchange and some type of vertical mixing. Horizontal and vertical advection were of limited and little use, respectively, in reproducing the seasonal cycle variance.

The spatially coherent features of the non-seasonal, or anomaly, field were confined largely to the upper 100 m, with small spatial scales dominating the variance field below 100 m. This implies that the often studied sea surface temperature anomalies are associated with a thermal structure largely confined to the mixed layer. It was not possible to explain quantitatively a significant portion of the variance of the heat storage anomalies in terms of currently available estimates of air/sea heat exchange and advective processes. This result is partially due to noise introduced into the heat budget calculations by sampling variability. However, the major reason for the result appears to be poor estimates of the heat budget source terms. Estimates of these source terms must be substantially improved if quantitative understanding of interannual ocean variability is to be achieved.

Abstract

Advanced statistical techniques have been used to conduct a study of the relationships between ocean and atmosphere variables in the tropical Pacific Ocean. The results of the study show that the ocean variables can hindcast features of the trade wind field (TWF) variability several months into the future. The results are compatible with the notion that the Hadley and Walker cells are associated with east-west and north-south sea surface temperature (SST) gradients as suggested by Bjerknes. However, the level of skill in even specifying the strength of these cells is small, suggesting mechanisms other than those associated with SST are responsible for much of the observed variability in those systems.

TWF predictors can hindcast themselves and ocean variables at both short lead times and lead times near one year. The main components of the wind field responsible for this long-lead-time skill are associated with the southeast trades and a near-equatorial band in the western Pacific. The results also suggest that large El Niño events are predictable a year in advance. This conclusion was supported by an independent test which successfully forecast SST anomalies off Peru one year in advance for the period 1976–79.

The results of the study have been used to test specific ideas and scenarios regarding the physical mechanisms responsible for large-scale air-sea interactions in the tropical Pacific. The results add new ideas and’ additional depth to previous work plus help formulate a more cohesive description of large-scale events. During regimes of cold equator SST the northeast and southeast trade wind field merge and extend into the western Pacific. At these times there is no clear minimum in zonal component of the wind system over the western and central ocean between 15°N and 15°S. During warm equatorial SST situations the two TWF's are separated as evidenced by a strong minimum or even reversal of the zonal component in the region noted above. The associated changes in zonal stress and wind stress curl between warm and cold events is very large. During the transition from cold to warm equator the equatorial SST anomalies move westward from South America to near the dateline. The wind anomalies in the equatorial region move simultaneously from the western Pacific to the central ocean. Both types of anomaly meet in the central ocean during the summer/fall season.

Abstract

Numerous hypotheses have been proposed to explain interannual changes in equatorial water temperatures. It is shown that many of these hypotheses can be tested by expressing them in terms of a statistical-dynamical model based on the heat balance equation. The ability of the resulting model to account for variance in a 20-year record of observed water temperature provides a hitherto unavailable, quantitative measure of the hypothesis consistency.

Field data were used in conjunction with the models to show that the following general conclusions are consistent with available observations: 1) The advective terms (both horizontal and vertical) in the heat balance equation account for 30–50% of the variance in records of interannual changes in near-equatorial SST. 2) The advective changes are closely related to significant changes in the trade wind field, particularly those occurring near the equator and just west of the dateline, as well as major changes in sea level across the entire Pacific Basin.

Specific hypotheses about interannual changes in water temperature were tested. The following conclusions were found to be consistent with the available data: 1) Eastward advection of heat by the North Equatorial Countercurrent is far more important (29% of the variance) to the heat balance of the eastern tropical Pacific than local heating or consequences of long-term variations in the Northeast Trades. 2) At Talara, Peru, 48% of the SST variance was predictable one month in advance using basin-wide fluctuations in sea level as predictors. This suggests the importance to the heat balance off Peru of eastward advection of heat by currents or wave phenomena. Of less importance (14%) was trans-equatorial flow across the Galapagos front. Upwelling induced by local changes in the wind stress was not important, on the interannual time scale, in the estimate of SST. 3) Temperature changes in the central equatorial Pacific (Christmas Island) were consistent with the mechanisms of local upwelling at the equator (25%) and advection from the east (33%).

Abstract

Statistical techniques have been used to study the ability of SLP, SST and a form of persistence to forecast cold/warm season air temperatures over the United States and to determine the space–time evolution of these fields that give rise to forecast skill.

It was found that virtually all forecast skill was due to three climatological features: a decadal scale change in Northern Hemisphere temperature, ENSO-related phenomena, and the occurrence of two distinct short-lived, but large-scale, coherent structures in the atmospheric field of the Northern Hemisphere. The physical mechanisms responsible for the first two signals are currently unknown. One of the large-scale, coherent features seems largely independent of the ENSO phenomena, while the second is at least partially related to ENSO and may be part of a recently discovered global mode of SLP variation. Both features resemble various combinations of known teleconnection patterns. These large-scale coherent structures are essentially stationary patterns of SLP variation that grow in place over two to three months. The structures decay more rapidly, typically in 1 month, leading to a highly asymmetric temporal life cycle.

The average forecast skills found in this study are generally low, except in January and February, and are always much lower than expected from studies of potential predictability. Increase in the average skills will require new information uncorrelated with any of the data used in this study and/or prediction schemes that are highly nonlinear. However, the concept of an average skill may be misleading. A forecast quality index is developed and it is shown that one can say in advance that some years will be highly predictable and others not. Use of the classical definition of “winter” in forecast work may not be advisable since each of the months that make up winter are largely uncorrelated and predicted by different atmospheric features.

Abstract

Many parameters that measure climatic variability have nonstationary statistics, that is, they depend strongly on the phase of the annual cycle. In this case normal statistical analysis techniques based on time-invariant models are inappropriate. Generalized methods accounting for seasonal nonstationarity (phase averaged or cyclostationary models) have been developed to treat such data.

The methods are applied to the problem of predicting El Niño off South America. It is shown that El Niños may be predicted up to a year in advance with considerably more confidence and accuracy using phase-averaged models than with time-invariant models.

In a second application surface air temperature anomalies are predicted over North America from Pacific Ocean sea surface temperatures. Again, the phase-averaged models consistently outperform models based on standard statistical procedures.

Abstract

A dynamical model incorporating observed field data is used to estimate the potential importance of linear and nonlinear vorticity advection to climate forecast models. Forecasts of 30-day averages benefit from inclusion of the linear advection term, but the nonlinear advection appears only marginally helpful. For intermediate averaging times (e.g., 10 days), both advection terms appear to be important. Analysis of the nonlinear terms suggests that they could be most adequately parameterized as a noise process that is “white” in wavenumber space and “red” in the time domain.

Abstract

A theoretical framework is developed to consider the abilities of analog techniques for the prediction of short-term climate fluctuations. The basic element of the framework is the definition of a “climate state vector.” This vector points to the position of a “climate particle” whose motion in a multi-dimensional hyper-space represents the time evolution of the climate system. The particle has a number of properties that describe regional covariability of various climatic fields.

A series of metrics are assigned to the space in which the climate particle moves. These metrics are used to select past states of the climate system which are analogs to a “current” state. The subsequent prediction is made based on the past evolution of the climate state Vector. Forecasts made with the analog selection techniques are evaluated in terms of the local and global skills that attend them. Thus both the spatial and temporal dependence of the skill score field is examined.

Predictions were made for the seasonal average surface air temperature anomaly fields over the North American continent at lead times of one to four seasons in advance. Significant predictive skill was found in the experiments, particularly for the summer season. The result suggests that high predictability is associated with the degree of exactness with which the climate particle retraces its trajectory in hyperspace. This in turn suggests that more accurate predictions can he made with a longer data base than the one used in this study since better analog fits would presumably he found. The results also suggest that both the current state and recent history of the climate system are important in determining the future evolution of climatic anomalies.

Abstract

The dynamics and predictability of decadal climate variability over the North Pacific and North America are investigated by analyzing various observational datasets and the output of a state of the art coupled ocean–atmosphere general circulation model that was integrated for 125 years. Both the observations and model results support the picture that the decadal variability in the region of interest is based on a cycle involving unstable ocean–atmosphere interactions over the North Pacific. The period of this cycle is of the order of a few decades.

The cycle involves the two major circulation regimes in the North Pacific climate system, the subtropical ocean gyre, and the Aleutian low. When, for instance, the subtropical ocean gyre is anomalously strong, more warm tropical waters are transported poleward by the Kuroshio and its extension, leading to a positive SST anomaly in the North Pacific. The atmospheric response to this SST anomaly involves a weakened Aleutian low, and the associated fluxes at the air–sea interface reinforce the initial SST anomaly, so that ocean and atmosphere act as a positive feedback system. The anomalous heat flux, reduced ocean mixing in response to a weakened storm track, and anonmalous Ekman heat transport contribute to this positive feedback.

The atmospheric response, however, consists also of a wind stress curl anomaly that spins down the subtropical ocean gyre, thereby reducing the poleward heat transport and the initial SST anomaly. The ocean adjusts with some time lag to the change in the wind stress curl, and it is this transient ocean response that allows continuous oscillations. The transient response can be expressed in terms of baroclinic planetary waves, and the decadal timescale of the oscillation is therefore determined to first order by wave timescales. Advection by the mean currents, however, is not negligible.

The existence of such a cycle provides the basis of long-range climate forecasting over North America at decadal timescales. At a minimum, knowledge of the present phase of the decadal mode should allow a “now-cast” of expected climate “bias” over North America, which is equivalent to a climate forecast several years ahead.